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Novel Molecular Subtyping Scheme Based on In Silico Analysis of Cuproptosis Regulator Gene Patterns Optimizes Survival Prediction and Treatment of Hepatocellular Carcinoma. Journal of clinical medicine BACKGROUND:The liver plays an important role in maintaining copper homeostasis. Copper ion accumulation was elevated in HCC tissue samples. Copper homeostasis is implicated in cancer cell proliferation and angiogenesis. The potential of copper homeostasis as a new theranostic biomarker for molecular imaging and the targeted therapy of HCC has been demonstrated. Recent studies have reported a novel copper-dependent nonapoptotic form of cell death called cuproptosis, strikingly different from other known forms of cell death. The correlation between cuproptosis and hepatocellular carcinoma (HCC) is not fully understood. MATERIALS AND METHODS:The transcriptomic data of patients with HCC were retrieved from the Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC) and were used as a discovery cohort to construct the prognosis model. The gene expression data of patients with HCC retrieved from the International Cancer Genome Consortium (ICGC) and Gene Expression Omnibus (GEO) databases were used as the validation cohort. The Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis was used to construct the prognosis model. A principal component analysis (PCA) was used to evaluate the overall characteristics of cuproptosis regulator genes and obtain the PC1 and PC2 scores. Unsupervised clustering was performed using the ConsensusClusterPlus R package to identify the molecular subtypes of HCC. Cox regression analysis was performed to identify cuproptosis regulator genes that could predict the prognosis of patients with HCC. The receiver operating characteristics curve and Kaplan-Meier survival analysis were used to understand the role of hub genes in predicting the diagnosis and prognosis of patients, as well as the prognosis risk model. A weighted gene co-expression network analysis (WGCNA) was used for screening the cuproptosis subtype-related hub genes. The functional enrichment analysis was performed using Metascape. The 'glmnet' R package was used to perform the LASSO regression analysis, and the randomForest algorithm was performed using the 'randomForest' R package. The 'pRRophetic' R package was used to estimate the anticancer drug sensitivity based on the data retrieved from the Genomics of Drug Sensitivity in Cancer database. The nomogram was constructed using the 'rms' R package. Pearson's correlation analysis was used to analyze the correlations. RESULTS:We constructed a six-gene signature prognosis model and a nomogram to predict the prognosis of patients with HCC. The Kaplan-Meier survival analysis revealed that patients with a high-risk score, which was predicted by the six-gene signature model, had poor prognoses (log-rank test < 0.001; HR = 1.83). The patients with HCC were grouped into three distinct cuproptosis subtypes (Cu-clusters A, B, and C) based on the expression pattern of cuproptosis regulator genes. The patients in Cu-cluster B had poor prognosis (log-rank test < 0.001), high genomic instability, and were not sensitive to conventional chemotherapeutic treatment compared to the patients in the other subtypes. Cancer cells in Cu-cluster B exhibited a higher degree of the senescence-associated secretory phenotype (SASP), a marker of cellular senescence. Three representative genes, , , and , were identified in patients in Cu-cluster B using WGCNA and the "randomForest" algorithm. A nomogram was constructed to screen patients in the Cu-cluster B subtype based on three genes: , , and . CONCLUSION:Publicly available databases and various bioinformatics tools were used to study the heterogeneity of cuproptosis in patients with HCC. Three HCC subtypes were identified, with differences in the survival outcomes, genomic instability, senescence environment, and response to anticancer drugs. Further, three cuproptosis-related genes were identified, which could be used to design personalized therapeutic strategies for HCC. 10.3390/jcm12185767
Identification of cuproptosis-related molecular classification and characteristic genes in ulcerative colitis. Heliyon Ulcerative colitis (UC) is a refractory inflammatory disease with imbalances in intestinal mucosal homeostasis. Cuproptosis serves as newly identified programmed cell death (PCD) form involved in UC. In the study, UC-related datasets were extracted from the Gene Expression Omnibus (GEO) database. A comparison of UC patients and healthy controls identified 11 differentially expressed cuproptosis-related genes (DE-CRGs), where FDX1, LIAS, and DLAT were differentially expressed in UC groups from the mouse models and clinical samples, with their expression correlating with disease severity. By comprehending weighted gene co-expression network analysis (WGCNA) and differential expression analysis, the key genes common to the module genes relevant to different cuproptosis-related clusters and differentially expressed genes (DEGs) both in different clusters and patients with and without UC were identified using several bioinformatic analysis. Furthermore, the mRNA levels of four characteristic genes with diagnostic potential demonstrated significant decrease in both mouse models and clinical UC samples. Our discoveries offer a theoretical foundation for cuproptosis effect in UC. 10.1016/j.heliyon.2024.e24875
Molecular characteristics, clinical significance, and cancer immune interactions of cuproptosis and ferroptosis-associated genes in colorectal cancer. Frontiers in oncology Objective:To systematically analyze the expression of cuproptosis and ferroptosis genes and their impact on the development, prognosis, tumor microenvironment (TME), and treatment response in colorectal cancer (CRC) patients. Methods:We systematically evaluated 33 cuproptosis and ferroptosis-related genes and comprehensively identified the correlations between cuproptosis and ferroptosis-related genes and transcriptional patterns, prognosis, and clinical features. Three distinct subgroups were identified in CRC using the TCGA database and the GEO database. We next assessed the relationship between the molecular features, prognostic significance, and clinical indicators of the prognostic genes in the cuproptosis and ferroptosis-related gene clusters. In addition, a PAC_score, which accurately predicted the prognosis of CRC patients and the efficacy of immunomodulatory mAbs, was obtained. Results:Patients in the low expression group (low expression of cuproptosis and ferroptosis-related genes) had a longer survival compared to the high expression group. We identified two distinct prognosis-associated molecular subtypes and observed an association between clinical information and prognosis. The enrichment analysis of differential genes associated with prognosis showed that the main enrichment was related to biological processes such as metastasis and metabolism. Next, the PCA_score for predicting overall survival (OS) was established and its reliable predictive value in CRC patients was confirmed. Furthermore, highly reliable nomogram was created to facilitate the clinical feasibility of the PCA_score. It was found that the immunomodulatory mAbs, PD-L1 and CTLA4 were highly expressed in the low PCA_score score group with statistically significance. Conclusion:Overall, the PCA scores of prognostic differential genes in the cuproptosis and ferroptosis-related gene clusters were strongly associated with clinical characteristics, prognosis, and immunotherapy in CRC patients. This data may promote further exploration of more effective immunotherapy strategies for CRC. 10.3389/fonc.2022.975859
Systematic analysis based on the cuproptosis-related genes identifies ferredoxin 1 as an immune regulator and therapeutic target for glioblastoma. BMC cancer Glioblastoma multiforme (GBM) is recognized as the prevailing malignant and aggressive primary brain tumor, characterized by an exceedingly unfavorable prognosis. Cuproptosis, a recently identified form of programmed cell death, exhibits a strong association with cancer progression, therapeutic response, and prognostic outcomes. However, the specific impact of cuproptosis on GBM remains uncertain. To address this knowledge gap, we obtained transcriptional and clinical data pertaining to GBM tissues and their corresponding normal samples from various datasets, including TCGA, CGGA, GEO, and GTEx. R software was utilized for the analysis of various statistical techniques, including survival analysis, cluster analysis, Cox regression, Lasso regression, gene enrichment analysis, drug sensitivity analysis, and immune microenvironment analysis. Multiple assays were conducted to investigate the expression of genes related to cuproptosis and their impact on the proliferation, invasion, and migration of glioblastoma multiforme (GBM) cells. The datasets were obtained and prognostic risk score models were constructed and validated using differentially expressed genes (DEGs) associated with cuproptosis. To enhance the practicality of these models, a nomogram was developed.Patients with glioblastoma multiforme (GBM) who were classified as high risk exhibited a more unfavorable prognosis and shorter overall survival compared to those in the low risk group. Additionally, we specifically chose FDX1 from the differentially expressed genes (DEGs) within the high risk group to assess its expression, prognostic value, biological functionality, drug responsiveness, and immune cell infiltration. The findings demonstrated that FDX1 was significantly upregulated and associated with a poorer prognosis in GBM. Furthermore, its elevated expression appeared to be linked to various metabolic processes and the susceptibility to chemotherapy drugs. Moreover, FDX1 was found to be involved in immune cell infiltration and exhibited correlations with multiple immunosuppressive genes, including TGFBR1 and PDCD1LG2. The aforementioned studies offer substantial assistance in informing the chemotherapy and immunotherapy approaches for GBM. In summary, these findings contribute to a deeper comprehension of cuproptosis and offer novel perspectives on the involvement of cuproptosis-related genes in GBM, thereby presenting a promising therapeutic strategy for GBM patients. 10.1186/s12885-023-11727-z
Molecular subtypes, tumor microenvironment infiltration characterization and prognosis model based on cuproptosis in bladder cancer. PeerJ Cuproptosis is a kind of cell death dependent on copper. We aimed to explore the functions of the cuproptosis in the tumor microenvironment (TME) and construct a cuproptosis-related prognosis signature in bladder cancer (BCa). Using BCa patients in the public cohort, the cuproptosis-related molecular subtypes and cuproptosis-related prognosis signature were developed. Three cuproptosis-related molecular subtypes, with different prognoses and TME characteristics, were identified in BCa. The cuproptosis-related prognosis signature can divide patients into high- and low-risk groups with different prognoses, TME characteristics, chemotherapeutic drug susceptibility and immunotherapeutic response. Low risk group patients had a favored prognosis and response to immunotherapy. The dysregulation of cuproptosis-related genes expression levels was validated in multiple BCa cells using experiments. Cuproptosis has an important role in the tumor progression and the characterization of TME in BCa. The cuproptosis-related prognosis signature is a useful biomarker that can reflect the prognosis, TME characteristics, immunotherapeutic response and chemotherapeutic drug susceptibility in BCa patients. 10.7717/peerj.15088
Commentary: Development and validation of cuproptosis-related gene signature in the prognostic prediction of liver cancer. Frontiers in oncology 10.3389/fonc.2023.1159828
Single-cell and genetic multi-omics analysis combined with experiments confirmed the signature and potential targets of cuproptosis in hepatocellular carcinoma. Frontiers in cell and developmental biology Cuproptosis, as a recently discovered type of programmed cell death, occupies a very important role in hepatocellular carcinoma (HCC) and provides new methods for immunotherapy; however, the functions of cuproptosis in HCC are still unclear. We first analyzed the transcriptome data and clinical information of 526 HCC patients using multiple algorithms in R language and extensively described the copy number variation, prognostic and immune infiltration characteristics of cuproptosis related genes (CRGs). Then, the hub CRG related genes associated with prognosis through LASSO and Cox regression analyses and constructed a prognostic prediction model including multiple molecular markers and clinicopathological parameters through training cohorts, then this model was verified by test cohorts. On the basis of the model, the clinicopathological indicators, immune infiltration and tumor microenvironment characteristics of HCC patients were further explored via bioinformation analysis. Then, We further explored the key gene biological function by single-cell analysis, cell viability and transwell experiments. Meantime, we also explored the molecular docking of the hub genes. We have screened 5 hub genes associated with HCC prognosis and constructed a prognosis prediction scoring model. And the model results showed that patients in the high-risk group had poor prognosis and the expression levels of multiple immune markers, including PD-L1, CD276 and CTLA4, were higher than those patients in the low-risk group. We found a significant correlation between risk score and M0 macrophages and memory CD4 T cells. And the single-cell analysis and molecular experiments showed that BEX1 were higher expressed in HCC tissues and deletion inhibited the proliferation, invasion and migration and EMT pathway of HCC cells. Finally, it was observed that BEX1 could bind to sorafenib to form a stable conformation. The study not only revealed the multiomics characteristics of CRGs in HCC but also constructed a new high-accuracy prognostic prediction model. Meanwhile, BEX1 were also identified as hub genes that can mediate the cuproptosis of hepatocytes as potential therapeutic targets for HCC. 10.3389/fcell.2023.1240390
Prediction model of clinical prognosis and immunotherapy efficacy of gastric cancer based on level of expression of cuproptosis-related genes. Heliyon Background:Gastric cancer is one of the most common malignancies in the world and ranks fourth among cancer-related causes of death. Gastric adenocarcinoma is the most common pathological type of gastric cancer; usually, this tumor is associated with distant metastasis upon first diagnosis and has a poor prognosis. Cuproptosis is a novel mechanism of cell death induced by copper, and is closely related to tumor progression, prognosis and immune response. However, the role of cuproptosis-related genes (CRGs) in the tumor microenvironment (TME) of gastric cancer has yet to be elucidated. Methods:Gastric adenocarcinoma data were downloaded from the Cancer Genome Atlas (TCGA) database. Through bioinformatics analysis, a risk scoring model was constructed from cuproptosis gene-related lncRNA. Then, we investigated the relationship between prognosis and the TIME of gastric cancer according to clinical characteristics and risk score. Results:Validation of the model showed that the overall survival (OS) of the high-risk group was significantly lower than that of the low-risk group (P < 0.001) and that the risk score was an independent predictor of prognosis (P < 0.001). The new model was significantly correlated with the prognosis and TIME of patients with gastric cancer, including immune cell infiltration, tumor mutation burden (TMB) score, targeted drug sensitivity, and immune checkpoint gene expression. In addition, a prognostic nomogram was established based on the risk score (AC008915.2, AC011005.4, AC023511.1, AC139792.1, AL355312.2, LINC01094 and LINC02476). Conclusion:Our analysis revealed that the prognostic model of cuproptosis-related genes could effectively predict the prognosis of patients with gastric cancer and comprehensively establish the relationship between cuproptosis genes and tumor immunity. This may provide a new strategy for the precise treatment of gastric cancer. 10.1016/j.heliyon.2023.e19035
The prognostic value and immune landscape of a cuproptosis-related lncRNA signature in head and neck squamous cell carcinoma. Frontiers in genetics Cuproptosis has been recognized as a novel regulatory cell death, which has been confirmed to promote the occurrence and development of tumors. However, whether cuproptosis-related lncRNA has an impact on the prognosis of squamous cell carcinoma of the head and neck (HNSCC) is still unclear. In total, 501 HNSCC tumor samples and 44 normal were downloaded from the TCGA database. Cuproptosis-related lncRNAs were obtained by co-expressed analysis. We got prognostic lncRNA that was associated with cuproptosis by using univariate Cox regression analysis and LASSO Cox regression. Then we constructed and validated the prognostic signature of HNSCC and analyzed the immune landscape of the signature. The Prognostic Signature is based on 10 cuproptosis-related lncRNAs including AC090587.1, AC004943.2, TTN-AS1, AL162458.1, AC106820.5, AC012313.5, AL132800.1, WDFY3-AS2, CDKN2A-DT, and AL136419.3. The results of overall survival, risk score distribution, and survival status in the low-risk group were better than those in the high-risk group. In addition, all immune checkpoint genes involved were significantly different between the two risk groups (p < 0.05). The risk score was positively correlated with Eosinophils. M0 and M2 phenotype macrophages, mast cells activated, NK cells activated, and negatively related with B cells naive, mast cells resting, plasma cells, CD8T cells, T cells follicular helper, T cells regulatory (Tregs). Consensus clustering was identified in molecular subtypes of HNSC. More high-risk samples concentrated in Cluster1, which had a higher Tumor Immune Dysfunction and Exclusion (TIDE) score and Single Nucleotide Polymorphisms (SNP) alternation than Cluster2. Our study elucidated the correlation between cuproptosis-related lncRNA with prognosis and immune landscape of HNSCC, which may provide references for further research on the exploration of the mechanism and functions of the prognosis for HNSCC. 10.3389/fgene.2022.942785
Prediction of prognosis, immune infiltration, and personalized treatment of hepatocellular carcinoma by analysis of cuproptosis-related long noncoding RNAs and verification . Frontiers in oncology Background:The correlations between cuproptosis and long noncoding RNAs (lncRNAs) with the tumor microenvironment (TME), immunotherapy, and some other characteristics of hepatocellular carcinoma (HCC) remain unclear. Methods:Sixteen cuproptosis regulators and 356 cuproptosis-related lncRNAs (CRLnc) were identified from 374 HCC profiles in The Cancer Genome Atlas (TCGA) database. Six differentially expressed CRLnc were selected, and a prognostic risk model based on the CRLnc signature (CRLncSig) was constructed. The prognostic power of the model was verified. Moreover, a cuproptosis-related gene cluster (CRGC) was generated based on six lncRNAs and differentially expressed genes. The relationship between immune cell infiltration in the TME, immunotherapy, CRLncSig, and CRGC was demonstrated through various algorithms, Tumor Immune Dysfunction and Exclusion (TIDE), tumor mutational burden (TMB), etc. Potential drugs and sensitivity to those agents were evaluated for the risk model. LncRNA AL158166.1 was selected and verified in HCC tissues and cell lines, the impact of its knockdown and overexpression in HCC cells was examined, and the copper (Cu) concentration and the cuproptosis-related gene expression were detected. Results:A CRLncSig prognostic risk model with good predictive ability was constructed. The low-risk group had a longer overall survival (OS), lower tumor purity, more extensive immune cell infiltration, higher immune score, enrichment in immune-activated pathways, and more positive response to immunotherapy versus the high-risk group. CRGC-B exhibited the best OS and the lowest tumor stage; the immune cell infiltration analysis was similar to the low-risk group in CRLncSig. CRGC-B belonged to the "immune-high" group of the TME. The low-risk group had a higher TIDE score and susceptibility to antitumor drugs. The lncRNA AL158166.1 had the highest hazard ratio. The levels of AL158166.1 were higher in HCC tissues versus healthy tissues. Knockdown of AL158166.1 could lead to an increase in intracellular Cu concentration, induce DLAT low expression, and inhibit the proliferation and migration of HCC cells, whereas overexpression of AL158166.1 exerted the reverse effect. Conclusion:Overall, a new CRLncSig prognostic risk model and a cuproptosis-related molecular signature were constructed and evaluated. The model and signature were associated with the prognosis, immune infiltration, and immunotherapy of HCC. Inhibiting the lncRNA AL158166.1 may induce cuproptosis and showed potential for the inhibition of tumors. Evaluation of the CRLnc, CRLncSig, and CRGC may enhance our understanding of the TME, determine the effectiveness of immunotherapy, and act as a marker for the prognosis of HCC. 10.3389/fonc.2023.1159126
Commentary: Copper and cuproptosis-related genes in hepatocellular carcinoma: therapeutic biomarkers targeting tumor immune microenvironment and immune checkpoints. Frontiers in immunology 10.3389/fimmu.2023.1265565
Identification of novel molecular subtypes and a signature to predict prognosis and therapeutic response based on cuproptosis-related genes in prostate cancer. Frontiers in oncology Background:Prostate cancer (PCa) is the most common malignant tumor of the male urinary system. Cuproptosis, as a novel regulated cell death, remains unclear in PCa. This study aimed to investigate the role of cuproptosis-related genes (CRGs) in molecular stratification, prognostic prediction, and clinical decision-making in PCa. Methods:Cuproptosis-related molecular subtypes were identified by consensus clustering analysis. A prognostic signature was constructed with LASSO cox regression analyses with 10-fold cross-validation. It was further validated in the internal validation cohort and eight external validation cohorts. The tumor microenvironment between the two risk groups was compared using the ssGSEA and ESTIMATE algorithms. Finally, qRT-PCR was used to explore the expression and regulation of these model genes at the cellular level. Furthermore, 4D Label-Free LC-MS/MS and RNAseq were used to investigate the changes in CRGs at protein and RNA levels after the knockdown of the key model gene B4GALNT4. Results:Two cuproptosis-related molecular subtypes with significant differences in prognoses, clinical features, and the immune microenvironment were identified. Immunosuppressive microenvironments were associated with poor prognosis. A prognostic signature comprised of five genes (B4GALNT4, FAM83D, COL1A, CHRM3, and MYBPC1) was constructed. The performance and generalizability of the signature were validated in eight completely independent datasets from multiple centers. Patients in the high-risk group had a poorer prognosis, more immune cell infiltration, more active immune-related functions, higher expression of human leukocyte antigen and immune checkpoint molecules, and higher immune scores. In addition, anti-PDL-1 immunotherapy prediction, somatic mutation, chemotherapy response prediction, and potential drug prediction were also analyzed based on the risk signature. The validation of five model genes' expression and regulation in qPCR was consistent with the results of bioinformatics analysis. Transcriptomics and proteomics analyses revealed that the key model gene B4GALNT4 might regulate CRGs through protein modification after transcription. Conclusion:The cuproptosis-related molecular subtypes and the prognostic signature identified in this study could be used to predict the prognosis and contribute to the clinical decision-making of PCa. Furthermore, we identified a potential cuproptosis-related oncogene B4GALNT4 in PCa, which could be used as a target to treat PCa in combination with cuproptosis. 10.3389/fonc.2023.1162653
Prognosis and personalized treatment prediction in lung adenocarcinoma: An and strategy adopting cuproptosis related lncRNA towards precision oncology. Frontiers in pharmacology There is a rapid increase in lung adenocarcinomas (LUAD), and studies suggest associations between cuproptosis and the occurrence of various types of tumors. However, it remains unclear whether cuproptosis plays a role in LUAD prognosis. Dataset of the TCGA-LUAD was treated as training cohort, while validation cohort consisted of the merged datasets of the GSE29013, GSE30219, GSE31210, GSE37745, and GSE50081. Ten studied cuproptosis-related genes (CRG) were used to generated CRG clusters and CRG cluster-related differential expressed gene (CRG-DEG) clusters. The differently expressed lncRNA that with prognosis ability between the CRG-DEG clusters were put into a LASSO regression for cuproptosis-related lncRNA signature (CRLncSig). Kaplan-Meier estimator, Cox model, receiver operating characteristic (ROC), time-dependent AUC (tAUC), principal component analysis (PCA), and nomogram predictor were further deployed to confirm the model's accuracy. We examined the model's connections with other forms of regulated cell death, including apoptosis, necroptosis, pyroptosis, and ferroptosis. The immunotherapy ability of the signature was demonstrated by applying eight mainstream immunoinformatic algorithms, TMB, TIDE, and immune checkpoints. We evaluated the potential drugs for high risk CRLncSig LUADs. Real-time PCR in human LUAD tissues were performed to verify the CRLncSig expression pattern, and the signature's pan-cancer's ability was also assessed. A nine-lncRNA signature, CRLncSig, was built and demonstrated owning prognostic power by applied to the validation cohort. Each of the signature genes was confirmed differentially expressed in the real world by real-time PCR. The CRLncSig correlated with 2,469/3,681 (67.07%) apoptosis-related genes, 13/20 (65.00%) necroptosis-related genes, 35/50 (70.00%) pyroptosis-related genes, and 238/380 (62.63%) ferroptosis-related genes. Immunotherapy analysis suggested that CRLncSig correlated with immune status, and checkpoints, KIR2DL3, IL10, IL2, CD40LG, SELP, BTLA, and CD28, were linked closely to our signature and were potentially suitable for LUAD immunotherapy targets. For those high-risk patients, we found three agents, gemcitabine, daunorubicin, and nobiletin. Finally, we found some of the CRLncSig lncRNAs potentially play a vital role in some types of cancer and need more attention in further studies. The results of this study suggest our cuproptosis-related CRLncSig can help to determine the outcome of LUAD and the effectiveness of immunotherapy, as well as help to better select targets and therapeutic agents. 10.3389/fphar.2023.1113808
Integrative analysis of single-cell and bulk RNA seq to reveal the prognostic model and tumor microenvironment remodeling mechanisms of cuproptosis-related genes in colorectal cancer. Aging BACKGROUND:Recently, there has been a great deal interest in cuproptosis, a form of programmed cell death that is mediated by copper. The specific mechanism through which cuproptosis-related genes impact the development of colorectal cancer (CRC) remains unknown. METHODS:Here, we combined bulk RNA-seq with scRNA-seq to investigate the CRGs functions within CRC. A number of 61 cuproptosis-related genes were chosen for further investigation. Nine prognostic CRGs were identified by Lasso-Cox. The RiskScore was created and the patients have been separated into two different groups, low- and high-RiskScore group. The CIBERSORT, ESTIMATE, MCP-counter, TIDE, and IPS have been employed to score the TME, and GSVA and GSEA were utilized to evaluate the pathway within the both groups. Further, we used cell communication analysis to explore the tumor microenvironment remodeling mechanisms of the COX17 and DLAT based on scRNA-seq. Finally, we used IHC and qPCR to validate the expression of COX17 and DLAT. RESULTS:AOC3, CCS, CDKN2A, COX11, COX17, COX19, DLD, DLAT, and PDHB have been recognized as prognostic CRGs in CRC. The high-risk group exhibited the worst prognosis, an immune-deficient phenotype, and were more resistant to ICB treatment. Further, scRNA-seq analysis revealed that elevated expression of COX17 in CD4-CXCL13Tfh could contribute to the immune evasion while DLAT had the opposite effect, reversing T cell exhaustion and inducing pyroptosis to boost CD8-GZMKT infiltration. CONCLUSIONS:The current investigation has developed a prognostic framework utilizing cuproptosis-related genes that is highly effective in predicting prognosis, TME type, and response to immunotherapy in CRC patients. Furthermore, our study reveals a novel finding that elevated levels of COX17 expression within CD4-CXCL13 T cells in CRC mediates T cell exhaustion and Treg infiltration, while DLAT has been found to facilitate the anti-tumor immunity activation through the T cell exhaustion reversal and the induction of pyroptosis. 10.18632/aging.205324
Identification of two molecular subtypes and a novel prognostic model of lung adenocarcinoma based on a cuproptosis-associated gene signature. Frontiers in genetics Lung adenocarcinoma is the most common subtype of lung cancer clinically, with high mortality and poor prognosis. Cuproptosis present a newly discovered mode of cell death characterized by aggregation of fatty acylated proteins, depletion of iron-sulfur clusterin, triggering of HSP70, and induction of intracellular toxic oxidative stress. However, the impact of cuproptosis on lung adenocarcinoma development, prognosis, and treatment has not been elucidated. By systematically analyzing the genetic alterations of 10 cuproptosis-related genes in lung adenocarcinoma, we found that CDKN2A, DLAT, LIAS, PDHA1, FDX1, GLS, and MTF1 were differentially expressed between lung cancer tissues and adjacent tissues. Based on the expression levels of 10 cuproptosis-related genes, we classified lung adenocarcinoma patients into two molecular subtypes using the Consensus clustering method, of which subtype 2 had a worse prognosis. Differential expression genes associated with prognosis between the two subtypes were obtained by differential analysis and survival analysis, and cox lasso regression was applied to construct a cuproptosis-related prognostic model. Its survival predicting ability was validated in three extrinsic validation cohorts. The results of multivariate cox analysis indicated that cuproptosis risk score was an independent prognostic predictor, and the mixed model formed by cupproptosis prognostic model combined with stage had more robust prognostic prediction accuracy. We found the differences in cell cycle, mitosis, and p53 signaling pathways between high- and low-risk groups according to GO and KEGG enrichment analysis. The results of immune microenvironment analysis showed that the enrichment score of activated dendritic cells, mast cells, and type 2 interferon response were down-regulated in the high-risk group, while the fraction of neutrophils and M0 macrophages were upregulated in the high-risk group. Compared with the high-risk group, subjects in the low-risk group had higher Immunophenoscore and may be more sensitive to immunotherapy. We identified seven chemotherapy agents may improve the curative effect in LUAD samples with higher risk score. Overall, we discovered that cuproptosis is closely related to the occurrence, prognosis, and treatment of lung adenocarcinoma. The cuproptosis prognostic model is a potential prognostic predictor and may provide new strategies for precision therapy in lung adenocarcinoma. 10.3389/fgene.2022.1039983
An effective prognostic model in colon adenocarcinoma composed of cuproptosis-related epigenetic regulators. Frontiers in pharmacology Colorectal adenocarcinoma (COAD) is a common malignant tumor with little effective prognostic markers. Cuproptosis is a newly discovered mode of cell death that may be related to epigenetic regulators. This study aimed to explore the association between epigenetic regulators and cuproptosis, and to establish a prognostic prediction model for COAD based on epigenetic regulators associated with cuproptosis (EACs). RNA sequencing data and clinical data of 524 COAD patients were obtained from the TCGA-COAD database, cuproptosis-related genes were from the FerrDb database, and epigenetic-related genes were from databases such as GO and EpiFactors. LASSO regression analysis and other methods were used to screen out epigenetic regulators associated with cuproptosis and prognosis. The risk score of each patient was calculated and the patients were divided into high-risk group and low-risk group. Next, the survival difference, functional enrichment analyses, tumor mutation burden, chemotherapy drug sensitivity and other indicators between the two groups were compared and analyzed. We found 716 epigenetic regulators closely related to cuproptosis, among which 35 genes were related to prognosis of COAD. We further screened out 7 EACs from the 35 EACs to construct a prognostic prediction model. We calculated the risk score of each patient based on these 7 genes, and divided the patients into high-risk group and low-risk group. We found that the overall survival rate and progression-free survival rate of the high-risk group were significantly lower than those of the low-risk group. This model showed good predictive ability in the training set, test set and overall data set. We also constructed a prognostic prediction model based on risk score and other clinical features, and drew the corresponding Nomogram. In addition, we found significant differences between the high-risk group and the low-risk group in tumor mutation burden, chemotherapy drug sensitivity and other clinical aspects. We established an effective predictive prediction model for COAD based on EACs, revealing the association between epigenetic regulators and cuproptosis in COAD. We hope that this model can not only facilitate the treatment decision of COAD patients, but also promote the research progress in the field of cuproptosis. 10.3389/fphar.2023.1254918
Construction and validation of a cuproptosis-related diagnostic gene signature for atrial fibrillation based on ensemble learning. Hereditas BACKGROUND:Atrial fibrillation (AF) is the most common type of cardiac arrhythmia. Nonetheless, the accurate diagnosis of this condition continues to pose a challenge when relying on conventional diagnostic techniques. Cell death is a key factor in the pathogenesis of AF. Existing investigations suggest that cuproptosis may also contribute to AF. This investigation aimed to identify a novel diagnostic gene signature associated with cuproptosis for AF using ensemble learning methods and discover the connection between AF and cuproptosis. RESULTS:Two genes connected to cuproptosis, including solute carrier family 31 member 1 (SLC31A1) and lipoic acid synthetase (LIAS), were selected by integration of random forests and eXtreme Gradient Boosting algorithms. Subsequently, a diagnostic model was constructed that includes the two genes for AF using the Light Gradient Boosting Machine (LightGBM) algorithm with good performance (the area under the curve value > 0.75). The microRNA-transcription factor-messenger RNA network revealed that homeobox A9 (HOXA9) and Tet methylcytosine dioxygenase 1 (TET1) could target SLC31A1 and LIAS in AF. Functional enrichment analysis indicated that cuproptosis might be connected to immunocyte activities. Immunocyte infiltration analysis using the CIBERSORT algorithm suggested a greater level of neutrophils in the AF group. According to the outcomes of Spearman's rank correlation analysis, there was a negative relation between SLC31A1 and resting dendritic cells and eosinophils. The study found a positive relationship between LIAS and eosinophils along with resting memory CD4 T cells. Conversely, a negative correlation was detected between LIAS and CD8 T cells and regulatory T cells. CONCLUSIONS:This study successfully constructed a cuproptosis-related diagnostic model for AF based on the LightGBM algorithm and validated its diagnostic efficacy. Cuproptosis may be regulated by HOXA9 and TET1 in AF. Cuproptosis might interact with infiltrating immunocytes in AF. 10.1186/s41065-023-00297-6
Proteomics revealed the crosstalk between copper stress and cuproptosis, and explored the feasibility of curcumin as anticancer copper ionophore. Free radical biology & medicine As an essential micronutrient element in organisms, copper controls a host of fundamental cellular functions. Recently, copper-dependent cell growth and proliferation have been defined as "cuproplasia". Conversely, "cuproptosis" represents copper-dependent cell death, in a nonapoptotic manner. So far, a series of copper ionophores have been developed to kill cancer cells. However, the biological response mechanism of copper uptake has not been systematically analyzed. Based on quantitative proteomics, we revealed the crosstalk between copper stress and cuproptosis in cancer cells, and also explored the feasibility of curcumin as anticancer copper ionophore. Copper stress not only couples with cuproptosis, but also leads to reactive oxygen species (ROS) stress, oxidative damage and cell cycle arrest. In cancer cells, a feedback cytoprotection mechanism involving cuproptosis mediators was discovered. During copper treatment, the activation of glutamine transporters and the loss of Fe-S cluster proteins are the facilitators and results of cuproptosis, respectively. Through copper depletion, glutathione (GSH) blocks the cuproptosis process, rescues the activation of glutamine transporters, and prevents the loss of Fe-S cluster proteins, except for protecting cancer cells from apoptosis, protein degradation and oxidative damage. In addition, the copper ionophore curcumin can control the metabolisms of lipids, RNA, NADH and NADPH in colorectal cancer cells, and also up-regulates positive cuproptosis mediators. This work not only established the crosstalk between copper stress and cuproptosis, but also discolored the suppression and acceleration of cuproptosis by GSH and curcumin, respectively. Our results are significant for understanding cuproptosis process and developing novel anticancer reagents based on cuproptosis. 10.1016/j.freeradbiomed.2022.11.023
A novel risk model based on cuproptosis-related lncRNAs predicted prognosis and indicated immune microenvironment landscape of patients with cutaneous melanoma. Frontiers in genetics Cutaneous melanoma (CM) is an aggressive form of malignancy with poor prognostic value. Cuproptosis is a novel type of cell death regulatory mechanism in tumors. However, the role of cuproptosis-related long noncoding RNAs (lncRNAs) in CM remains elusive. The cuproptosis-related lncRNAs were identified using the Pearson correlation algorithm. Through the univariate and multivariate Cox regression analysis, the prognosis of seven lncRNAs associated with cuproptosis was established and a new risk model was constructed. ESTIMATE, CIBERSORT, and single sample gene set enrichment analyses (ssGSEA) were applied to evaluate the immune microenvironment landscape. The Kaplan-Meier survival analysis revealed that the overall survival (OS) of CM patients in the high-risk group was remarkably lower than that of the low-risk group. The result of the validated cohort and the training cohort indicated that the risk model could produce an accurate prediction of the prognosis of CM. The nomogram result demonstrated that the risk score based on the seven prognostic cuproptosis-related lncRNAs was an independent prognostic indicator feature that distinguished it from other clinical features. The result of the immune microenvironment landscape indicated that the low-risk group showed better immunity than high-risk group. The immunophenoscore (IPS) and immune checkpoints results conveyed a better benefit potential for immunotherapy clinical application in the low-risk groups. The enrichment analysis and the gene set variation analysis (GSVA) were adopted to reveal the role of cuproptosis-related lncRNAs mediated by the immune-related signaling pathways in the development of CM. Altogether, the construction of the risk model based on cuproptosis-related lncRNAs can accurately predict the prognosis of CM and indicate the immune microenvironment of CM, providing a new perspective for the future clinical treatment of CM. 10.3389/fgene.2022.959456
Corrigendum: Identification of hub cuproptosis related genes and immune cell infiltration characteristics in periodontitis. Frontiers in immunology [This corrects the article DOI: 10.3389/fimmu.2023.1164667.]. 10.3389/fimmu.2023.1281051
Identification of a Novel Model for Predicting the Prognosis and Immune Response Based on Genes Related to Cuproptosis and Ferroptosis in Ovarian Cancer. Cancers (1) Background: Ovarian cancer (OV) presents a high degree of malignancy and a poor prognosis. Cell death is necessary to maintain tissue function and morphology. Cuproptosis and ferroptosis are two novel forms of death, and we look forward to finding their relationship with OV and providing guidance for treatment. (2) Methods: We derived information about OV from public databases. Based on cuproptosis-related and ferroptosis-related genes, a risk model was successfully constructed, and exceptional subtypes were identified. Next, various methods are applied to assess prognostic value and treatment sensitivity. Besides, the comprehensive analysis of the tumor environment, together with immune cell infiltration, immune function status, immune checkpoint, and human HLA genes, is expected to grant assistance for the prognosis and treatment of OV. (3) Results: Specific molecular subtypes and models possessed excellent potential to predict prognosis. Immune infiltration abundance varied between groups. The susceptibility of individuals to different chemotherapy drugs and immunotherapies could be predicted based on specific groups. (4) Conclusions: Our molecular subtypes and risk model, with strong immune prediction and prognostic prediction capabilities, are committed to guiding ovarian cancer treatment. 10.3390/cancers15030579
Unravelling diagnostic clusters and immune landscapes of cuproptosis patterns in intervertebral disc degeneration through dry and wet experiments. Aging Cuproptosis is a manner of mitochondrial cell death induced by copper. However, cuproptosis modulators' molecular processes in intervertebral disc degeneration (IDD) are still unclear. To better understand the processes of cuproptosis regulators in IDD, a thorough analysis of cuproptosis regulators in the diagnostic biomarkers and subtype determination of IDD was conducted. Then we collected clinical IDD samples and successfully established IDD model and , and carried out real-time quantitative polymerase chain reaction (RT-qPCR) validation of significant cuproptosis modulators. Totally we identified 8 crucial cuproptosis regulators in the present research. Using a random forest model, we isolated 8 diagnostic cuproptosis modulators for the prediction of IDD risk. Then, based on our following decision curve analysis, we selected the five diagnostic cuproptosis regulators with importance scores greater than two and built a nomogram model. Using a consensus clustering method, we divided IDD patients into two cuproptosis clusters (clusterA and clusterB) based on the important cuproptosis regulators. Additionally, each sample's cuproptosis value was evaluated using principal component analysis in order to quantify the cuproptosis clusters. Patients in clusterB had higher cuproptosis scores than patients in clusterA. Moreover, we found that clusterB was involved in the immunity of natural killer cell, while clusterA was related to activated CD4 T cell, activated B cell, etc. Notably, cuproptosis modulators detected by RT-qPCR showed generally consistent expression levels with the bioinformatics results. To sum up, cuproptosis modulators play a crucial role in the pathogenic process of IDD, providing biomarkers and immunotherapeutic approaches for IDD. 10.18632/aging.205449
Cuproptosis-related genes score and its hub gene GCSH: A novel predictor for cholangiocarcinomas prognosis based on RNA seq and experimental analyses. Journal of Cancer Recent researches have demonstrated that cuproptosis, a copper-dependent cell death mechanism, is related to tumorigenesis, progression, clinical prognosis, tumor microenvironment, and drug sensitivity. Nevertheless, the function and impact of cuproptosis in cholangiocarcinoma (CCA), remain elusive. Utilizing data obtained from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA-CHOL) datasets, we conducted subgroup typing of CCA according to cuproptosis-related genes (CRGs) and explored functional differences and prognostic value between groups. A CRG score was established considering clinical prognosis and gene expression. Furthermore, differences in the immune microenvironment, response to immunotherapy, metabolic patterns, and cancer progression characteristics between high- and low-risk groups were examined on the basis of these scores. In vitro experiments validated the function of the key gene glycine cleavage system protein H (GCSH) in cellular and tissues, respectively. Prognostic models established on the basis of subgroup genetic differences achieved satisfactory results in validation. Metabolic-related gene expression levels and tumor microenvironment distribution were significantly different between the high and low CRG groups. GCSH was revealed as the singular prognostic CRG in CCA (HR =6.04; 95% CI: 1.15-31.80). Moreover, inhibition of the cupcoptosis key gene GCSH attenuated the malignant ability of CCA cell lines in vitro, including cell proliferation, migration and invasion, and this function of GCSH may be achieved via JAK-STAT signaling in CCA. The CRG scoring system accurately predicts prognosis and opens up new possibilities for cuproptosis-related therapy for CCA. The cuproptosis key gene GCSH has been preliminarily confirmed as a reliable therapeutic target or prognostic marker for CCA patients. 10.7150/jca.92327
Why not try to predict autism spectrum disorder with crucial biomarkers in cuproptosis signaling pathway? Frontiers in psychiatry The exact pathogenesis of autism spectrum disorder (ASD) is still unclear, yet some potential mechanisms may not have been evaluated before. Cuproptosis is a novel form of regulated cell death reported this year, and no study has reported the relationship between ASD and cuproptosis. This study aimed to identify ASD in suspected patients early using machine learning models based on biomarkers of the cuproptosis pathway. We collected gene expression profiles from brain samples from ASD model mice and blood samples from humans with ASD, selected crucial genes in the cuproptosis signaling pathway, and then analysed these genes with different machine learning models. The accuracy, sensitivity, specificity, and areas under the receiver operating characteristic curves of the machine learning models were estimated in the training, internal validation, and external validation cohorts. Differences between models were determined with Bonferroni's test. The results of screening with the Boruta algorithm showed that FDX1, DLAT, LIAS, and ATP7B were crucial genes in the cuproptosis signaling pathway for ASD. All selected genes and corresponding proteins were also expressed in the human brain. The k-nearest neighbor, support vector machine and random forest models could identify approximately 72% of patients with ASD. The artificial neural network (ANN) model was the most suitable for the present data because the accuracy, sensitivity, and specificity were 0.90, 1.00, and 0.80, respectively, in the external validation cohort. Thus, we first report the prediction of ASD in suspected patients with machine learning methods based on crucial biomarkers in the cuproptosis signaling pathway, and these findings may contribute to investigations of the potential pathogenesis and early identification of ASD. 10.3389/fpsyt.2022.1037503
Construction and characterization of a cuproptosis- and immune checkpoint-based LncRNAs signature for breast cancer risk stratification. Breast cancer (Tokyo, Japan) BACKGROUND:Cuproptosis is the most recently identified form of cell death, and copper homeostasis is an important cancer therapeutic target. However, the therapeutic benefits of cuproptosis-targeted treatment in BRCA remain undetermined. This study utilized LncRNAs linked to cuproptosis genes and immune checkpoint genes to generate a BRCA predictive signature. METHODS:We screened a population of LncRNAs that correlated with both cuproptosis genes and immune checkpoint genes and used ten of these LncRNAs to construct a prognosis-predictive signature. We then validated and proved the efficacy of the signature in predicting the prognosis of BRCA patients. We also unraveled the relationship between the signature and the immunological milieu, immune function, and susceptibility to chemotherapy. RESULTS:The signature derived from the ten cuproptosis- and immune-related prognostic LncRNAs (CuImP-LncRNAs) can be implied to categorize patients into two groups, including the high- and low-risk groups. The value of the signature was validated, and the risk score was verified as an independent prognostic indicator. The TIME and TMB distribution patterns and chemosensitivity were depicted in the high- and low-risk groups, respectively. Patients of the high-risk group with a suppressive immunological intratumor context were more sensitive to a broad range of antitumor agents. In contrast, low-risk individuals with active immune function responded more favorably to immunotherapy. CONCLUSION:Our findings provided a novel and effective model for predicting BRCA prognosis and the propensity to different treatment modalities, thus contributing to the optimization of personalized BRCA therapy in the future. 10.1007/s12282-023-01434-9
Distinct tumor microenvironment landscapes in gastric cancer classified by cuproptosis-related lncRNAs. Journal of Cancer Cuproptosis is a newly discovered non-apoptotic form of cell death that may be related to the development of tumors. Nonetheless, the potential role of cuproptosis-related lncRNAs in tumor microenvironment (TME) formation and patient-tailored treatment optimization of gastric cancer (GC) is still unclear. In this study, the six-lncRNA signature was constructed to quantify the molecular patterns of GC using LASSO-Cox regression model. Receiver operating characteristic (ROC) curves, C-index curves, independent prognostic analysis and principal component analysis (PCA) were conducted to verify and evaluate the model. The results showed that this risk model was accurate and reliable in predicting GC patient survival. In addition, two distinct subgroups were identified based on the risk model, which showed significant difference in biological functions of the associated genes, TME scores, characteristics of infiltrating immune cells and immunotherapy responses. We found that the high-risk subgroup was associated with immune activation and tumor-related pathways. Furthermore, compared with the low-risk subgroup, the high-risk subgroup had higher TME scores, richer immune cell infiltration and a better immunotherapy response. To accurately identify immune cold tumors and hot tumors, all samples of GC were divided into four distinct clusters by consensus clustering. Among them, Cluster 3 was identified as an immune hot tumor and was more sensitive to immunotherapy. Overall, this study demonstrates that cuproptosis-related lncRNAs could accurately predict the prognosis of patients with GC, help make a distinction between immune cold tumors and hot tumors and provide a basis for the precision medicine of GC. 10.7150/jca.79640
The multi-omics analysis identifies a novel cuproptosis-anoikis-related gene signature in prognosis and immune infiltration characterization of lung adenocarcinoma. Heliyon Background:Lung adenocarcinoma (LUAD) has emerged as one of the most aggressive lethal cancers. Anoikis serves as programmed apoptosis initiated by the detachment of cells from the extracel-lular matrix. Cuproptosis is distinct from traditional cell death modalities. The above two modes are both closely related to tumor progression, prognosis, and treatment. However, whether they have synergistic effects in LUAD deserves further investigation. Methods:The anoikis-related prognostic genes (ANRGs) co-expressed with cuproptosis-associated genes (CAGs) were screened using correlation analysis, analysis of variance, least absolute shrinkage, and selection operator (LASSO), and COX regression followed by functional analysis, and then LUAD risk score model was constructed. Using consensus clustering, the relationship between different subtypes and clinicopathological features, immune infiltration characteristics, and somatic mutations was analyzed. A nomogram was developed by incorporating clinical information, which provided a prediction of the survival of patients. Finally, a comprehensive analysis of ANRGs was performed and verified by the HPA database. Results:A total of 27 ANRGs associated with cuproptosis were obtained. On this basis, three distinct ANRGs subtypes were identified, and the differences between clinical prognosis and immune infiltration were observed. A risk score model has been constructed by incorporating seven ANRGs signatures (EIF2AK3, IKZF3, ITGAV, OGT, PLK1, TRAF2, XRCC5). A highly reliable nomogram was developed to help formulate treatment strategies based on risk score and the clinicopathological features of LUAD. The seven-gene signature was turned out to be strongly linked to immune cells and validated in single-cell data. Immunohistochemistry proved that all of them are highly expressed in LUAD tissues. Conclusion:This study reveals the potential relationship between cuproptosis-related ANRGs and clinicopathological features, tumor microenvironment (TME), and mutation characteristics, which can be applied for predicting the prognosis of LUAD and help develop individualized treatment strategies. 10.1016/j.heliyon.2023.e14091
Identification of a novel cuproptosis-associated lncRNA model that can improve prognosis prediction in uterine corpus endometrial carcinoma. Heliyon Uterine corpus endometrial carcinoma (UCEC) is a common female reproductive system cancer. Cuproptosis, a new type of mitochondrial respiration-regulated cell death, is associated with several cancer types. Here, we developed a cuproptosis-associated long non-coding RNA (lncRNA) model to predict the prognosis of patients with UCEC and their response to immune-based treatments. RNA sequencing (RNA-seq) and somatic mutation data for UCEC were obtained from The Cancer Genome Atlas (TCGA) database. LncRNAs co-expressed with cuproptosis-related genes were screened. Patients were randomly divided into two groups, one of which was used as training group to build the model, while the other group served as the validation group. A prognostic model comprising 13 cuproptosis-associated lncRNAs was constructed, and each lncRNA was individually related to patient prognosis. Our model clearly distinguished between risk variables in afflicted individuals. The risk score can provide a more accurate prognostic prediction compared with other clinical covariates. Patient groups at various risk groups were different according to tumor mutational burden and tumor immune dysfunction and exclusion analysis. We identified drugs for which patient populations at various risk groups showed higher sensitivity. Our model may contribute to immune related research and clinical decision-making for optimized treatment. 10.1016/j.heliyon.2023.e22665
Construction and validation of cuproptosis-related lncRNA prediction signature for bladder cancer and immune infiltration analysis. Aging Bladder cancer (BC) is a common urologic tumor with a high recurrence rate. Cuproptosis and long noncoding RNAs (lncRNAs) have demonstrated essential roles in the tumorigenesis of many malignancies. Nevertheless, the prognostic value of cuproptosis-related lncRNA (CRLs) in BC is still unclear. The public data used for this study were acquired from the Cancer Genome Atlas database. A comprehensive exploration of the expression profile, mutation, co-expression, and enrichment analyses of cuproptosis-related genes was performed. A total of 466 CRLs were identified using Pearson's correlation analysis. 16 prognostic CRLs were then retained by univariate Cox regression. Unsupervised clustering divided the patients into two clusters with diverse survival outcomes. The signature consists of 7 CRLs was constructed using the least absolute shrinkage and selection operator (LASSO) Cox regression analyses. Survival curves and receiver operating characteristics showed the prognostic signature possessed good predictive value, which was validated in the testing and entire sets. The reliability and stability of our signature were further confirmed by stratified analysis. Additionally, the signature-based risk score was confirmed as an independent prognostic factor. Gene set enrichment analysis showed molecular alteration in the high-risk group was closely associated with cancer. We then developed the clinical nomogram using independent prognostic indicators. Notably, the infiltration of immune cells and expression of immune checkpoints were higher in the high-risk group, suggesting that they may benefit more from immunotherapy. In summary, the prognostic signature might effectively predict the prognosis and provide new insight into the clinical treatment of BC patients. 10.18632/aging.204972
Role of hippo pathway and cuproptosis-related genes in immune infiltration and prognosis of skin cutaneous melanoma. Frontiers in pharmacology Melanoma is the most lethal type of skin cancer with an increasing incidence. Cuproptosis is the most recently identified copper-dependent form of cell death that relies on mitochondrial respiration. The hippocampal (Hippo) pathway functions as a tumor suppressor by regulating Yes-associated protein/transcriptional coactivator with PDZ-binding motif (YAP/TAZ) activity. However, its role in cuproptosis remains unknown. In addition, the correlation of cuproptosis-related genes and Hippo pathway-related genes with tumor prognosis warrants further investigation. In the present study, we explored the correlation of cuproptosis-related genes and Hippo pathway-related genes with the prognosis of melanoma through analysis of data from a public database and experimental verification. We found eight Hippo pathway-related genes that were downregulated in melanoma and exhibited predictive value for prognosis. There was a significant positive correlation between cuproptosis-related genes and Hippo pathway-related genes in skin cutaneous melanoma. YAP1 expression was positively correlated with ferredoxin 1 (FDX1) expression in the GSE68599 dataset and A2058 cells. Moreover, YAP1 was positively and negatively correlated with M2 macrophages and regulatory T cell infiltration, respectively. In conclusion, the present study demonstrated the prognostic value of Hippo pathway-related genes (particularly YAP1) in melanoma, revealing the correlation between the expression of Hippo pathway-related genes and immune infiltration. Thus, the present findings may provide new clues on the prognostic assessment of patients with melanoma and a new target for the immunotherapy of this disease. 10.3389/fphar.2024.1344755
In Silico Identification and Validation of Cuproptosis-Related LncRNA Signature as a Novel Prognostic Model and Immune Function Analysis in Colon Adenocarcinoma. Current oncology (Toronto, Ont.) Background: Colon adenocarcinoma (COAD) is the most common subtype of colon cancer, and cuproptosis is a recently newly defined form of cell death that plays an important role in the development of several malignant cancers. However, studies of cuproptosis-related lncRNAs (CRLs) involved in regulating colon adenocarcinoma are limited. The purpose of this study is to develop a new prognostic CRLs signature of colon adenocarcinoma and explore its underlying biological mechanism. Methods: In this study, we downloaded RNA-seq profiles, clinical data and tumor mutational burden (TMB) data from the TCGA database, identified cuproptosis-associated lncRNAs using univariate Cox, lasso regression analysis and multivariate Cox analysis, and constructed a prognostic model with risk score based on these lncRNAs. COAD patients were divided into high- and low-risk subgroups based on the risk score. Cox regression was also used to test whether they were independent prognostic factors. The accuracy of this prognostic model was further validated by receiver operating characteristic curve (ROC), C-index and Nomogram. In addition, the lncRNA/miRNA/mRNA competing endogenous RNA (ceRNA) network and protein−protein interaction (PPI) network were constructed based on the weighted gene co-expression network analysis (WGCNA). Results: We constructed a prognostic model based on 15 cuproptosis-associated lncRNAs. The validation results showed that the risk score of the model (HR = 1.003, 95% CI = 1.001−1.004; p < 0.001) could serve as an independent prognostic factor with accurate and credible predictive power. The risk score had the highest AUC (0.793) among various factors such as risk score, stage, gender and age, also indicating that the model we constructed to predict patient survival was better than other clinical characteristics. Meanwhile, the possible biological mechanisms of colon adenocarcinoma were explored based on the lncRNA/miRNA/mRNA ceRNA network and PPI network constructed by WGCNA. Conclusion: The prognostic model based on 15 cuproptosis-related lncRNAs has accurate and reliable predictive power to effectively predict clinical outcomes in colon adenocarcinoma patients. 10.3390/curroncol29090517
Clinical significance and immune landscape of cuproptosis-related lncRNAs in kidney renal clear cell carcinoma: a bioinformatical analysis. Annals of translational medicine Background:Kidney renal clear cell carcinoma (KIRC) is considered an immunogenic tumor. Cuproptosis is a newly identified copper-induced regulated cell death that relies on mitochondria respiration. Long noncoding RNAs (lncRNAs) have emerged as significant players in tumorigenesis and metastasis. However, there is a huge knowledge gap on the prognostic role of cuproptosis-related lncRNAs in KIRC. And, the clinical value of them is still unknown. Here, we aimed to develop a cuproptosis-related lncRNA prognostic signature in KIRC. Methods:The messenger RNA (mRNA)/lncRNA expression profiles and the clinical information including age, gender, tumor stage, grade, and overall survival (OS) were acquired from The Cancer Genome Atlas (TCGA) database. The included KIRC samples were further randomly assigned into training (n=258) or testing (n=257) data sets. We performed Pearson correlation analysis to identify the cuproptosis-related lncRNAs and then constructed the prognostic signature using Cox regression analysis and LASSO algorithm. Subsequently, Kaplan-Meier survival analysis, a nomogram, and receiver operating characteristic (ROC) curve were performed to assess the predictive performance of the signature. Moreover, the immune characteristics and drug sensitivity related to the signature were also explored. Results:The signature comprised 7 cuproptosis-related lncRNAs. The patients with a low-risk score had superior OS compared with those with a high-risk score. The survival rates of the high- and low-risk groups were 44.96% and 83.72% (P<0.001). The area under the curve (AUC) value for 1-, 3-, 5-year survival rate reached 0.814, 0.762 and 0.825, respectively. In addition, a nomogram was also generated; the AUC was 0.785 for risk score, higher than that for age (0.593), gender (0.489), grade (0.679), and stage (0.721). The high-risk group had more enriched immune- and tumor-related genes. Patients with low-risk scores were more sensitive to immunotherapy and the small molecular drugs GSK1904529A, tipifarnib, BX-912, FR-180204, and GSK1070916. Meanwhile, the high-risk group tended to be more sensitive to pyrimethamine, MS-275, and CGP-60474. Conclusions:Collectively, we constructed a cuproptosis-related lncRNA prognostic signature with a higher predictive accuracy compared to multiple clinicopathological parameters, which may provide vital guidance for therapeutic strategies in KIRC. Combination of more prognostic biomarkers may further improve the accuracy. 10.21037/atm-22-5204
Immune patterns of cuproptosis in ischemic heart failure: A transcriptome analysis. Journal of cellular and molecular medicine Cuproptosis is a recently discovered programmed cell death pattern that affects the tricarboxylic acid (TCA) cycle by disrupting the lipoylation of pyruvate dehydrogenase (PDH) complex components. However, the role of cuproptosis in the progression of ischemic heart failure (IHF) has not been investigated. In this study, we investigated the expression of 10 cuproptosis-related genes in samples from both healthy individuals and those with IHF. Utilizing these differential gene expressions, we developed a risk prediction model that effectively distinguished healthy and IHF samples. Furthermore, we conducted a comprehensive evaluation of the association between cuproptosis and the immune microenvironment in IHF, encompassing infiltrated immunocytes, immune reaction gene-sets and human leukocyte antigen (HLA) genes. Moreover, we identified two different cuproptosis-mediated expression patterns in IHF and explored the immune characteristics associated with each pattern. In conclusion, this study elucidates the significant influence of cuproptosis on the immune microenvironment in ischemic heart failure (IHF), providing valuable insights for future mechanistic research exploring the association between cuproptosis and IHF. 10.1111/jcmm.18187
Integrated single-cell and bulk characterization of cuproptosis key regulator PDHB and association with tumor microenvironment infiltration in clear cell renal cell carcinoma. Frontiers in immunology Background:Renal clear cell carcinoma (ccRCC) is one of the most prevalent cancers worldwide. Accumulating evidence revealed that copper-induced cell death played a vital role in various tumors. However, the underlying mechanism of cuproptosis with molecular heterogeneity and tumor microenvironment (TME) in ccRCC remains to be elucidated. The present study aimed to discover the biological function of cuproptosis regulators with the potential to guide clinical therapy. Methods:Using Single-cell RNA-seq, bulk transcriptome and other multi-omics datasets, we identify essential cuproptosis-related hub gene PDHB for further study. The dysregulation of PDHB in ccRCC was characterized, together with survival outcomes, pathway enrichment and immune infiltration among tumor microenvironments. The functional significance and clinical association of PDHB was validated with loss of function experiments and surgical removal specimens. Results:PDHB mRNA and protein expression level was significantly downregulated in ccRCC tissues compared with normal and paired normal tissues. Clinicopathological parameters and tissue microarray (TMA) indicated that PDHB was identified as a prognostic factor for survival outcomes among ccRCC patients. Additionally, low PDHB was negatively correlated with Treg cells, indicating an immunosuppressive microenvironment. Mechanistically, knockdown PDHB appeared to promote the RCC cells proliferation, migration, and invasion potentials. Subsequent studies showed that copper-induced cell death activation could overcome sunitinib resistance in RCC cells. Conclusion:This research illustrated a cuproptosis-related hub gene PDHB which could serve as a potential prognostic marker and provide therapeutic benefits for clinical treatment of ccRCC patients. 10.3389/fimmu.2023.1132661
Molecular subtypes identified by multiomics analysis based on cuproptosis-related genes precisely predict response to immunotherapy and chemotherapy in colorectal cancer. Molecular carcinogenesis Cuproptosis is a newly reported type of programmed cell death that is involved in the progression of various diseases. Some studies have reported its potential significance in multiple tumors. Colorectal cancer (CRC) is one of the malignant tumors with high incidence and mortality. The purpose of this study was to further explore the importance of cuproptosis in the CRC development and treatment. We analyzed the expression, alterations, and promoter methylation of cuproptosis-related genes (CRGs) in patients with CRC. Three machine learning methods was used to determine cuproptosis-related feature genes and a diagnostic model was built based on them. Using the unsupervised clustering, patients with CRC were classified into distinct clusters. Then, the LASSO method was used to establish a cuproptosis risk model. We analyzed the association of risk scores with outcomes, immune microenvironment, response to immunotherapy, and sensitivity to chemotherapeutic drugs. The results showed that the expression of CRGs was dysregulated in CRC. The diagnostic model based on cuproptosis-related feature genes showed great clinical value. The patients in two clusters displayed different prognosis and microenvironment. Furthermore, the risk score was correlated with clinical characteristics, immune infiltration and response to immunotherapy and chemotherapy. Above all, the present findings revealed the involvement of cuproptosis in CRC development and provided a diagnostic tool to evaluate CRC occurrence risk. The immune infiltration and drug sensitivity analysis results helped to predict the response of patients in different subtypes of CRC to immunotherapy and chemotherapy. 10.1002/mc.23613
Analysis of cuproptosis in hepatocellular carcinoma using multi-omics reveals a comprehensive HCC landscape and the immune patterns of cuproptosis. Frontiers in oncology Cuproptosis represents a novel copper-dependent regulated cell death, distinct from other known cell death processes. In this report, a comprehensive analysis of cuproptosis in hepatocellular carcinoma (HCC) was conducted using multi-omics including genomics, bulk RNA-seq, single cell RNA-seq and proteomics. ATP7A, PDHA1 and DLST comprised the top 3 mutation genes in The Cancer Genome Atlas (TCGA)-LIHC; 9 cuproptosis-related genes showed significant, independent prognostic values. Cuproptosis-related hepatocytes were identified and their function were evaluated in single cell assays. Based on cuproptosis-related gene expressions, two immune patterns were found, with the cuproptosis-C1 subtype identified as a cytotoxic immune pattern, while the cuproptosis-C2 subtype was identified as a regulatory immune pattern. Cuproptosis-C2 was associated with a number of pathways involving tumorigenesis. A prognosis model based on differentially expressed genes (DEGs) of cuproptosis patterns was constructed and validated. We established a cuproptosis index (CPI) and further performed an analysis of its clinical relevance. High CPI values were associated with increased levels of alpha-fetoprotein (AFP) and advanced tumor stages. Taken together, this comprehensive analysis provides important, new insights into cuproptosis mechanisms associated with human HCC. 10.3389/fonc.2022.1009036
Establishment and experimental validation of a novel cuproptosis-related gene signature for prognostic implication in cholangiocarcinoma. Frontiers in oncology Background:Cholangiocarcinoma (CCA) is a highly malignant, heterogeneous bile duct malignancy with poor treatment options. A novel type of cell death termed cuproptosis was recently demonstrated to closely correlate with tumor progression. To gain more insight into the role of cuproptosis in CCA, we investigated the prognostic implications of cuproptosis related genes (CRGs) and their relationship to the development of CCA. Methods:Gene expression data for CCA were obtained from the European Bioinformatics Institute (EMBL-EBI) database. Least absolute shrinkage and selection operator (LASSO) penalized Cox regression was used to construct a prognostic risk model based on CRGs. RNA-seq, qRT-PCR and immunohistochemistry staining were used to verify the expression of CRGs in human CCA tissues or cell lines. Further experiments were performed to demonstrate the role of cuproptosis in CCA. Results:We established a 4-gene signature (ATP7A, FDX1, DBT and LIAS) that exhibited good stability and was an independent prognostic factor for CCA. Seventy-five CCA samples were divided into high- and low-risk groups based on the risk score. Enrichment analysis revealed increased extracellular activity in the high-risk group and increased lipid metabolic activity in the low-risk group. Moreover, the 4 signature genes were verified in clinical samples and cell lines by RNA-seq, qRT-PCR and immunohistochemistry. Further experiments confirmed that cuproptosis can significantly inhibit the viability of CCA cells. Knockdown of the key gene LIAS ameliorated the toxicity of cuproptosis to CCA cells. Conclusion:We established a 4-gene prognostic signature based on cuproptosis and explored the role of cuproptosis in CCA. The results provide an effective indicator for predicting the prognosis of cuproptosis in CCA. 10.3389/fonc.2022.1054063
Comprehensive analysis of cuproptosis-related genes on bladder cancer prognosis, tumor microenvironment invasion, and drug sensitivity. Frontiers in oncology Cuproptosis, a newly discovered form of programmed cell death, plays a vital role in the occurrence and development of tumors. However, the role of cuproptosis in the bladder cancer tumor microenvironment remains unclear. In this study, we developed a method for predicting the prognostic outcomes and guiding the treatment selection for patients with bladder cancer. We obtained 1001 samples and survival data points from The Cancer Genome Atlas database and Gene Expression Omnibus database. Using cuproptosis-related genes (CRGs) identified in previous studies, we analyzed CRG transcriptional changes and identified two molecular subtypes, namely high- and low-risk patients. The prognostic features of eight genes (, , , , , , , and ) were determined. The CRG molecular typing and risk scores were correlated with clinicopathological features, prognosis, tumor microenvironment cell infiltration characteristics, immune checkpoint activation, mutation burden, and chemotherapy drug sensitivity. Additionally, we constructed an accurate nomogram to improve the clinical applicability of the CRG_score. qRT-PCR was used to detect the expression levels of eight genes in bladder cancer tissues, and the results were consistent with the predicted results. These findings may help us to understand the role of cuproptosis in cancer and provide new directions for the design of personalized treatment and prediction of survival outcomes in patients with bladder cancer. 10.3389/fonc.2023.1116305
Construct ceRNA Network and Risk Model of Breast Cancer Using Machine Learning Methods under the Mechanism of Cuproptosis. Diagnostics (Basel, Switzerland) Breast cancer (BRCA) has an undesirable prognosis and is the second most common cancer among women after lung cancer. A novel mechanism of programmed cell death called cuproptosis is linked to the development and spread of tumor cells. However, the function of cuproptosis in BRCA remains unknown. To this date, no studies have used machine learning methods to screen for characteristic genes to explore the role of cuproptosis-related genes (CRGs) in breast cancer. Therefore, 14 cuproptosis-related characteristic genes (CRCGs) were discovered by the feature selection of 39 differentially expressed CRGs using the three machine learning methods LASSO, SVM-RFE, and random forest. Through the PPI network and immune infiltration analysis, we found that PRNP was the key CRCG. The miRTarBase, TargetScan, and miRDB databases were then used to identify hsa-miR-192-5p and hsa-miR-215-5p as the upstream miRNA of PRNP, and the upstream lncRNA, CARMN, was identified by the StarBase database. Thus, the mRNA PRNP/miRNA hsa-miR-192-5p and hsa-miR-215-5p/lncRNA CARMN ceRNA network was constructed. This ceRNA network, which has not been studied before, is extremely innovative. Furthermore, four cuproptosis-related lncRNAs (CRLs) were screened in TCGA-BRCA by univariate Cox, LASSO, and multivariate Cox regression analysis. The risk model was constructed by using these four CRLs, and the risk score = C9orf163 * (1.8365) + PHC2-AS1 * (-2.2985) + AC087741.1 * (-0.9504) + AL109824.1 * (0.6016). The ROC curve and C-index demonstrated the superior predictive capacity of the risk model, and the ROC curve demonstrated that the AUC of 1-, 3-, and 5-year OS in all samples was 0.721, 0.695, and 0.633, respectively. Finally, 50 prospective sensitive medicines were screened with the pRRophetic R package, among which 17-AAG may be a therapeutic agent for high-risk patients, while the other 49 medicines may be suitable for the treatment of low-risk patients. In conclusion, our study constructs a new ceRNA network and a novel risk model, which offer a theoretical foundation for the treatment of BRCA and will aid in improving the prognosis of BRCA. 10.3390/diagnostics13061203
Cuproptosis Related Gene Associated with Poor Prognosis and Malignant Biological Characteristics in Lung Adenocarcinoma. Current cancer drug targets PURPOSE:Cuproptosis plays a crucial role in the biological function of cells. The subject of this work was to analyze the effects of cuproptosis-related genes (CRGs) on the prognosis and biological function in lung adenocarcinoma (LUAD). METHODS:In this study, RNA sequencing and clinical data of LUAD samples were screened from public databases and our institution. A CRG signature was identified by least absolute shrinkage and selection operator and Cox regression. In addition, this study analyzed the correlation between prognostic CRGs and clinicopathological features. Finally, this study studied the effect of inhibiting dihydrolipoamide dehydrogenase () expression on cell biological function. RESULTS:There were 10 CRGs that showed differential expression between LUAD and normal tissues (p<0.05). A prognostic signature ( and lipoyltransferase 1 []) was constructed. Survival analysis suggested that patients with LUAD in the high-risk group had shorter overall survival (OS) (p<0.05). High expression of and low expression of were significantly associated with shorter OS (p<0.05). Immunohistochemical analysis revealed that, in LUAD tissues, was highly expressed, whereas was not detected. Finally, inhibition of expression could significantly restrain cell proliferation, invasion and migration. CONCLUSION:Overall, this prognostic CRG signature may play a pivotal role in LUAD outcome, while oncogene may be a future therapeutic candidate for LUAD. 10.2174/0115680096271679231213060750
LINC02362/hsa-miR-18a-5p/FDX1 axis suppresses proliferation and drives cuproptosis and oxaliplatin sensitivity of hepatocellular carcinoma. American journal of cancer research Cuproptosis is a novel cell death mechanism caused by copper overload, with FDX1 serving as the key regulator. LncRNAs are known to play a significant role in the aberrant regulation of gene expression in hepatocellular carcinoma (HCC). In this study, we investigated the biological role of the LINC02362/hsa-miR-18a-5p/FDX1 axis in HCC. We first explored the expression pattern, prognostic value, biological functions, drug sensitivity, and immune effect of FDX1. Using bioinformatics techniques, we then predicted several potential target lncRNAs and miRNAs. We identified a lncRNA-miRNA-FDX1 axis based on the ceRNA mechanism. In vitro experiments were conducted to validate the relationship between the lncRNA-miRNA-FDX1 axis and its biological effects in HCC. Finally, we investigated the relationship between the LINC02362/hsa-miR-18a-5p/FDX1 axis and oxaliplatin-induced cuproptosis in HCC. Our findings indicated that FDX1 expression was downregulated in HCC tissues; however, elevated FDX1 expression correlates with improved prognosis and heightened sensitivity to oxaliplatin. We confirmed that LINC02362 binds to and directly regulates the expression of miR-18a-5p, with FDX1 a target of miR-18a-5p. Experimental results suggested that upregulating LINC02362/hsa-miR-18a-5p/FDX1 axis suppressed the proliferation of HCC cells. Furthermore, LINC02362 knockdown led to a reduction in copper concentration and resistance to elesclomol-Cu. We also discovered that augmenting the LINC02362/hsa-miR-18a-5p/FDX1 axis could bolster the sensitivity of HCC to oxaliplatin through cuproptosis. This work presents the LINC02362/hsa-miR-18a-5p/FDX1 axis as a novel pathway that triggers cuproptosis and enhances the sensitivity of HCC to oxaliplatin, presenting a promising therapeutic avenue to combat oxaliplatin resistance in HCC.
Bioinformatics reveals diagnostic potential of cuproptosis-related genes in the pathogenesis of sepsis. Heliyon Background:Multiple modes of cell death occur during the development of sepsis. Among these patterns, cuproptosis has recently been identified as a regulated form of cell death. However, its impact on the onset and progression of sepsis remains unclear. Method:We screened a dataset of gene expression profiles from patients with sepsis using the GEO database. Survival analysis was performed to analyze the relationship between cuproptosis-related genes (CRGs) and prognosis. Hub genes were identified through univariate Cox regression analysis. The diagnostic value of hub genes in sepsis was tested in both training sets (GSE65682) and validation sets (GSE134347). To examine the association between hub genes and immune cells, single-sample gene set enrichment analysis (ssGSEA) and Pearson correlation analysis were employed. Additionally, the CRGs were validated in a septic mouse model using real-time quantitative PCR (qRT-PCR) and immunohistochemistry (IHC). Results:In sepsis, most CRGs were upregulated, with only DLD and MTF1 downregulated. High expression of three genes (GLE, LIAS, and PDHB) was associated with better prognosis, but only two hub genes (LIAS, PDHB) reached statistical significance. The receiver operating characteristic (ROC) analysis for diagnosing sepsis showed LIAS had a range of 0.793-0.906, while PDHB achieved values of 0.882 and 0.975 in the training and validation sets, respectively. ssGSEA analysis revealed a lower number of immune cells in the sepsis group, and there was a correlation between immune cell population and CRGs (LIAS, PDHB). Analysis in the septic mouse model demonstrated no significant difference in mRNA expression levels and IHC staining between LIAS and PDHB in heart and liver tissues, but up-regulation was observed in lung tissues. Furthermore, the mRNA expression levels and IHC staining of LIAS and PDHB were down-regulated in renal tissues. Conclusions:Cuproptosis is emerging as a significant factor in the development of sepsis. LIAS and PDHB, identified as potential diagnostic biomarkers for cuproptosis-associated sepsis, are believed to play crucial roles in the initiation and progression of cuproptosis-induced sepsis. 10.1016/j.heliyon.2023.e22664
Construction and validation of a cuproptosis-related lncRNA prognosis signature in bladder carcinoma. Journal of cancer research and clinical oncology BACKGROUND:Bladder cancer (BLCA) is a prevalent urological tumor with high morbidity and mortality. However, BLCA treatment remains challenging due to a lack of effective biomarkers. Long non-coding RNAs (lncRNAs), as active participants in tumor progression are involved in multiple biological regulatory mechanisms, and cuproptosis-related genes participate in the development of cancer. It is important to discover cuproptosis- related lncRNAs for BLCA diagnosis and treatment. METHODS:A predictive signature was constructed based on least absolute shrinkage and selection operator regression (LASSO) and Cox regression analyses of the 9 cuproptosis-related lncRNAs. Samples were divided into high-risk group and low-risk group based on their median risk scores to explore their prognosis. RESULTS:This signature is well predictive, as evidenced by the receiver operating characteristic curves (ROC curves) and K-M curves. Based on the nomogram, we were able to visually forecast the survival rates of patients with BLCA at 1-, 3-, and 5-year, and the calibration plots displayed that the actual results were well matched with the predicted 1-, 3-, and 5-year survival rates. Furthermore, BLCA patients in the high-risk group had a higher Tumor Immune Dysfunction and Exclusion (TIDE) score and lower TMB. Finally, we investigated the response of antitumor drugs for BLCA patients in different risk groups, and a statistically significant difference was observed in the sensitivity of those drugs between low- and the high-risk groups. CONCLUSION:According to the 9 cuproptosis-related lncRNAs, we constructed a signature which can be served as a promising prognostic biomarker for BLCA patients. 10.1007/s00432-023-05013-5
Two lncRNA signatures with cuproptosis as a novel prognostic model and clinicopathological value for endometrioid endometrial adenocarcinoma. Aging OBJECTIVE:Cuproptosis may contribute to tumorigenesis. However, the predictive value and therapeutic significance of cuproptosis-related lncRNAs (CRLs) in endometrioid endometrial adenocarcinoma (EEA) remains unknown. METHODS:We obtained RNA-seq data from TCGA database and searched the Literature to identify cuproptosis-related genes. Using machine learning models, we identified prognostic lncRNAs for cuproptosis. Immune properties and drug sensitivity were investigated based on these signatures. Further, a ceRNA network was constructed by bioinformatics and experiments were performed. RESULTS:We determined two cuproptosis-related signatures to build the prognostic model in EEA. Afterward, the risk scores of two cuproptosis-related signatures were associated with clinicopathological molecular typing and as independent prognostic factors for EEA. In addition, we observed significant differences in immune function, checkpoints, and CD8+ T lymphocyte infiltration between the two risk groups. Furthermore, chemotherapy drugs such as AKT inhibitors exhibited lower IC50 values in the high-risk group. We speculate that ACOXL-AS1 can be served as an endogenous 'sponge' to regulate the expression of MTF1 by miR-421. Through experiments, we preliminarily validated the ceRNA network relationship in the cellular model. CONCLUSION:In EEAs, this study proposed a broad molecular signature of CRLs are promising biomarkers for predicting clinical outcomes and therapeutic responses. 10.18632/aging.205299
Integrative analysis of cuproptosis-associated genes for predicting immunotherapy response in single-cell and multi-cohort studies. The journal of gene medicine BACKGROUND:The role of genes associated with the cuproptosis cell signaling pathway in prognosis and immunotherapy in ovarian cancer (OC) has been extensively investigated. In this study, we aimed to explore these mechanisms and establish a prognostic model for patients with OC using bioinformatics techniques. METHODS:We obtained the single cell sequencing data of ovarian cancer from the Gene Expression Omnibus (GEO) database and preprocessed the data. We analyzed a variety of factors including cuproptosis cell signal score, transcription factors, tumorigenesis and progression signals, gene set variation analysis (GSVA) and intercellular communication. Differential gene analysis was performed between groups with high and low cuproptosis cell signal scores, as well as Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. Using bulk RNA sequencing data from The Cancer Genome Atlas, we used the least absolute shrinkage and selection operator (LASSO)-Cox algorithm to develop cuproptosis cell signaling pathword-related gene signatures and validated them with GEO ovarian cancer datasets. In addition, we analyzed the inherent rules of the genes involved in building the model using a variety of bioinformatics methods, including immune-related analyses and single nucleotide polymorphisms. Molecular docking is used to screen potential therapeutic drugs. To confirm the analysis results, we performed various wet experiments such as western blot, cell counting kit 8 (CCK8) and clonogenesis tests to verify the role of the Von Willebrand Factor (VWF) gene in two ovarian cancer cell lines. RESULTS:Based on single-cell data analysis, we found that endothelial cells and fibroblasts showed active substance synthesis and signaling pathway activation in OC, which further promoted immune cell suppression, cancer cell proliferation and metastasis. Ovarian cancer has a high tendency to metastasize, and cancer cells cooperate with other cells to promote disease progression. We developed a signature consisting of eight cuproptosis-related genes (CRGs) (MAGEF1, DNPH1, RARRES1, NBL1, IFI27, VWF, OLFML3 and IGFBP4) that predicted overall survival in patients with ovarian cancer. The validity of this model is verified in an external GEO validation set. We observed active infiltrating states of immune cells in both the high- and low-risk groups, although the specific cells, genes and pathways of activation differed. Gene mutation analysis revealed that TP53 is the most frequently mutated gene in ovarian cancer. We also predict small molecule drugs associated with CRGs and identify several potential candidates. VWF was identified as an oncogene in ovarian cancer, and the protein was expressed at significantly higher levels in tumor samples than in normal samples. The high-score model of the cuproptosis cell signaling pathway was associated with the sensitivity of OC patients to immunotherapy. CONCLUSIONS:Our study provides greater insight into the mechanisms of action of genes associated with the cuproptosis cell signaling pathway in ovarian cancer, highlighting potential targets for future therapeutic interventions. 10.1002/jgm.3600
A risk prognostic model for patients with esophageal squamous cell carcinoma basing on cuproptosis and ferroptosis. Journal of cancer research and clinical oncology BACKGROUND:Cuproptosis, a form of copper-dependent programmed cell death recently presented by Tsvetkov et al., have been identified as a potential therapeutic target for refractory cancers and ferroptosis, a well-known form describing iron-dependent cell death. However, whether the crossing of cuproptosis-related genes and ferroptosis-related genes can introduce some new idea, thus being used as a novel clinical and therapeutic predictor in esophageal squamous cell carcinoma (ESCC) remains unknown. METHODS:We collected ESCC patient data from the Gene Expression Omnibus and the Cancer Genome Atlas databases and used Gene Set Variation Analysis to score each sample based on cuproptosis and ferroptosis. We then performed weighted gene co-expression network analysis to identify cuproptosis and ferroptosis-related genes (CFRGs) and construct a ferroptosis and cuproptosis-related risk prognostic model, which we validated using a test group. We also investigated the relationship between the risk score and other molecular features, such as signaling pathways, immune infiltration, and mutation status. RESULTS:Four CFRGs (MIDN, C15orf65, COMTD1 and RAP2B) were identified to construct our risk prognostic model. Patients were classified into low- and high-risk groups based on our risk prognostic model and the low-risk group showed significantly higher survival possibilities (P < 0.001). We used the "GO", "cibersort" and "ESTIMATE" methods to the above-mentioned genes to estimate the relationship among the risk score, correlated pathways, immune infiltration, and tumor purity. CONCLUSION:We constructed a prognostic model using four CFRGs and demonstrated its potential clinical and therapeutic guidance value for ESCC patients. 10.1007/s00432-023-05005-5
Construction of a Prognostic Model Based on Cuproptosis-Related lncRNA Signatures in Pancreatic Cancer. Canadian journal of gastroenterology & hepatology Aim:The aim of this study is to identify cuproptosis-related lncRNAs and construct a prognostic model for pancreatic cancer patients for clinical use. Methods:The expression profile of lncRNAs was downloaded from The Cancer Genome Atlas database, and cuproptosis-related lncRNAs were identified. The prognostic cuproptosis-related lncRNAs were obtained and used to establish and validate a prognostic risk score model in pancreatic cancer. Results:In total, 181 cuproptosis-related lncRNAs were obtained. The prognostic risk score model was constructed based on five lncRNAs (AC025257.1, TRAM2-AS1, AC091057.1, LINC01963, and MALAT1). Patients were assigned to two groups according to the median risk score. Kaplan-Meier survival curves showed that the difference in the prognosis between the high- and low-risk groups was statistically significant. Multivariate Cox analysis showed that our risk score was an independent risk factor for pancreatic cancer patients. Receiver operator characteristic curves revealed that the cuproptosis-related lncRNA model can effectively predict the prognosis of pancreatic cancer. The principal component analysis showed a difference between the high- and low-risk groups intuitively. Functional enrichment analysis showed that different genes were involved in cancer-related pathways in patients in the high- and low-risk groups. Conclusion:The risk model based on five prognostic cuproptosis-related lncRNAs can well predict the prognosis of pancreatic cancer patients. Cuproptosis-related lncRNAs could be potential biomarkers for pancreatic cancer diagnosis and treatment. 10.1155/2022/4661929
Identification of a novel prognostic signature composed of 3 cuproptosis-related transcription factors in colon adenocarcinoma. Genes & genomics BACKGROUND:Since the mechanism of cuproptosis was recently revealed, many molecules related to this pathway have been widely concerned and exploited to have prognostic potential. However, it is still unknown whether the transcription factors related to cuproptosis could be competent as tumor biomarkers of colon adenocarcinoma (COAD). OBJECTIVE:To analyze the prognostic potential of cuproptosis-related transcription factors in COAD, and validate the representative molecule. METHODS:Transcriptome data and patients' clinical parameters were obtained from the TCGA and GEO database. 19 cuproptosis genes were identified through literature consulting. Cuproptosis-related transcription factors were screened by COX regression analyses. Multivariate Cox regression was applied to construct the signature. Prognostic effects were evaluated by Kaplan Meier survival analyses and ROC analyses. KEGG, GO, and ssGSEA analyses were performed for function prediction. 48 COAD tissues were collected for immunohistochemistry stain to observe the expression level and prognostic value of E2F3. qRT-PCR was performed to detect mRNA expression levels, while cell viability assay was applied to detect the response of COAD cells to elesclomol treatment. RESULTS:A novel signature based on 3 prognostic transcription factors related to cuproptosis was successfully established and verified. Patients in the low-risk group tended to have better overall survival and lower immune phenotype scores than those in the high-risk group. Meanwhile, we also constructed a nomogram based on this signature and predict 10 candidate compounds targeting this signature. As an essential member of this signature, E2F3 was confirmed to be overexpressed in COAD tissues and was associated with poor prognosis of COAD patients. Importantly, CuCl2 and cuproptosis inducer elesclomol treatment could increase the expression of E2F3 in COAD cell while the overexpression of E2F3 significantly enhanced the resistance of COAD cells to elesclomol treatment. CONCLUSION:Our research has identified a new prognostic biomarker and provides some innovative insights into the diagnosis and therapy of patients with COAD. 10.1007/s13258-023-01406-5
Anisomycin has a potential toxicity of promoting cuproptosis in human ovarian cancer stem cells by attenuating YY1/lipoic acid pathway activation. Journal of Cancer Ovarian cancer is a highly malignant gynecologic tumor that seriously endangers women's health. We previously demonstrated that anisomycin significantly inhibited the activity of ovarian cancer stem cells (OCSCs) in vitro and in vivo. In the present study, anisomycin treatment of OCSCs significantly reduced ATP and T-GSH content; and increased pyruvate, LPO, and MDA. Anisomycin also significantly inhibited the proliferation of OCSCs in vitro, and its effect was similar to that of elesclomol and buthionine sulfoximine (BSO), suggesting that it has the potential to promote cuproptosis of OCSCs. Our subsequent cDNA microarray analysis results showed that anisomycin significantly reduced the transcriptional levels of genes that protect copper metabolism and cuproptosis, including the PDH complex, metallothionein, lipoid acid pathway, and FeS cluster proteins. Bioinformatics analysis revealed that four core factors (lipoic acid pathway FDX1, DLD, DLAT, PDH), and transcription factor YY1 were highly expressed in ovarian cancer tissues and were significantly correlated with an unfavorable prognosis. Further analysis depicted multiple YY1-recognized motif basic sites as existing in the promoters of the above four factors. In addition, the expression levels of YY1 in the tissue samples from ovarian cancer patients were significantly positively correlated with the expression levels of FDX1, DLD, DLAT, PDHB, and other genes. Finally, the analysis of the peripheral blood exosome database disclosed that the contents of the four key factors of YY1 and the lipoic acid pathway in the peripheral blood exosomes of patients with ovarian cancer were significantly elevated relative to those of normal healthy individuals. Therefore, our molecular biology experiments combined with bioinformatics analysis results suggest that the direct target of anisomycin-induced cuproptosis in ovarian cancer stem cells is probably a YY1 transcription factor. By inhibiting the expression and activity of YY1, anisomycin could not activate the transcriptional activity of the core genes of the lipoic acid pathway (i.e.,FDX1, DLD, DLAT, and PDHB), and induced the accumulation of cytotoxic substances, eventually leading to potential cuproptosis in ovarian cancer stem cells. 10.7150/jca.77445
Investigation of cuproptosis regulator-mediated modification patterns and SLC30A7 function in GBM. Aging BACKGROUND:Copper-dependent controlled cell death (cuproptosis) is a novel cell death modality that is distinct from known cell death mechanisms. Nonetheless, the potential role of the cuproptosis regulator in tumour microenvironment (TME) of GBM remains unknown. METHODS:Based on 13 widely recognised cuproptosis regulators, the cuproptosis regulation patterns and the biological characteristics of each pattern were comprehensively assessed in GBMs. Machine learning strategies were used to construct a CupScore to quantify the cuproptosis regulation patterns of individual tumours. A PPI network was constructed to predict core-associated genes of cuproptosis regulators. The function of the novel cuproptosis regulators SLC30A7 was examined by and experiment. RESULTS:We identified three distinct cuproptosis regulation patterns, including immune activation, metabolic activation, and immunometabolic double deletion patterns. The CupScore was shown to predict the abundance of tumour inflammation, molecular subtype, stromal activity, gene variation, signalling pathways, and patient prognosis. The low CupScore subtype was characterised by immune activation, isocitrate dehydrogenase mutations, sensitivity to chemotherapy, and clinical benefits. The high CupScore subtype was characterised by activation of the stroma and metabolism and poor survival. Novel cuproptosis regulator SLC30A7 knockdown inhibited the cuproptosi via JAK2/STAT3/ATP7A pathway in GBM. CONCLUSION:Cuproptosis regulators have been shown to play a vital role in TME complexity. Constructing CupScores were trained to evaluate the regulation patterns of cuproptosis in individual tumours. The novel cuproptosis-related genes SLC30A7 was involved in regulation the tumorigenicity of GBM cell via JAK2/STAT3/ATP7A pathway and . 10.18632/aging.205545
Cuproptosis-Related lncRNAs Modulate the Prognosis of MIBC by Regulating the Expression Pattern of Immunosuppressive Molecules Within the Tumor Microenvironment. International journal of general medicine Background:Cuproptosis-related gene and long non-coding RNA (lncRNA) modulation of cancer regulation is well-established. This investigation aimed to elucidate the prognostic implications of cuproptosis-associated lncRNAs in muscle-invasive bladder cancer (MIBC). Methods:Employing the Cancer Genome Atlas (TCGA) and IMvigor210 cohorts, bioinformatics and statistical analyses probed the prognostic relevance of cuproptosis-related lncRNAs. Results:Co-expression analysis revealed tight associations between lncRNA expression and cuproptosis-linked genes, with 13 cuproptosis-related lncRNAs found to correlate with MIBC prognosis. Lasso regression identified a six-lncRNA prognostic signature, enabling patient stratification into high- and low-risk categories. Tissue validation substantiated differential expression of FAM13A-AS1, GHRLOS, LINC00456, OPA1-AS1, RAP2C-AS1, and UBE2Q1-AS1 between MIBC tumor and normal tissues. Comparative analyses of tumor microenvironments and immune profiles between risk groups disclosed elevated immunosuppressive molecule expression, including programmed cell death-1 (PD-L1) and T-cell immunoglobulin-3 (TIM-3), in high-risk individuals. Conclusion:These findings suggest that cuproptosis-related lncRNAs may modulate the expression of immunosuppressive molecules, thereby influencing MIBC tumorigenesis and progression. Further exploration is warranted to unveil novel therapeutic targets for MIBC based on the expression patterns of cuproptosis-related lncRNAs and their impact on immune responses in the tumor microenvironment. 10.2147/IJGM.S438501
Identification of immunological characteristics and cuproptosis-related molecular clusters in primary Sjögren's syndrome. International immunopharmacology BACKGROUND:Primary Sjögren's syndrome (pSS) is a chronic systemic autoimmune disease characterized by lymphocyte infiltration of the exocrine glands. The typical clinical symptoms of pSS include dryness of the mouth (xerostomia) and eyes (xerophthalmia), fatigue, and joint pain. Cuproptosis is a recently identified mode of programmed cell death that leads to the progression of multiple diseases, and the precise etiology and pathophysiology of pSS remain unknown. Consequently, the aim of our study was to explore cuproptosis-related molecular clusters and identify key genes in pSS. METHOD:Gene expression profiles of the peripheral blood in the GSE84844 dataset were downloaded to identify the expression characteristics of cuproptosis regulators and immune cell infiltration. Subsequently, further exploration was conducted on the clusters involving cuproptosis-related genes (CRGs) and the corresponding immune cell infiltration, and the WGCNA algorithm was applied to explore the cluster-specific differentially expressed genes. Finally, the best machine prediction model was selected for candidate hub cuproptosis-associated genes and the accuracy of predictive efficiency was verified by the salivary gland in an external dataset (GSE143153) and enzyme-linked immunosorbent assay. RESULT:Through a comparison of patients with pSS and controls, 7 CRGs and 4 types of immune cells were identified. Immune cell infiltration revealed significant immune heterogeneity in three cuproptosis-related molecular clusters in pSS. The random forest machine model showed the best discriminatory performance (area under the receiver operating characteristic curve (AUC) = 1.000) and built a predictive model based on 5 genes, which demonstrated satisfactory performance (AUC = 0.70) in the GSE143153 dataset. Based on serum samples, EED (AUC = 0.557), CBL (AUC = 0.635), and NFU1 (AUC = 0.655) showed lower expression levels in patients with pSS (p = 0.037, p = 0.000, p = 0.000, respectively). CONCLUSION:In this study, we systematically analyzed the association between pSS and cuproptosis, established a predictive model that screened for high-risk genes linked to the advancement of pSS, and explored the pathogenic mechanisms and novel therapeutic strategies for pSS, targeting EED, CBL and NFU1. 10.1016/j.intimp.2023.111251
Development and validation of cuproptosis-related gene signature in the prognostic prediction of liver cancer. Frontiers in oncology Liver cancer is a generic term referring to several cancer types arising from the liver. Every year, liver cancer causes lots of deaths and other burdens to the people all over the world. Though the techniques in the diagnosis and therapy of liver cancer have undergone significant advances, the current status of treating liver cancer is not satisfactory enough. The improvement of techniques for the prognosis of liver cancer patients will be a great supplement for the treatment of liver cancer. Cuproptosis is a newly identified regulatory cell death type, which may have a close connection to liver cancer pathology. Here, we developed a prognostic model for liver cancer based on the cuproptosis-related mRNAs and lncRNAs. This model can not only effectively predict the potential survival of liver cancer patients, but also be applied to evaluate the infiltration of immune cell, tumor mutation burden, and sensitivity to anti-tumor drugs in liver cancer. In addition, this model has been successfully validated in lots of liver cancer patients' data. In summary, we wish this model can become a helpful tool for clinical use in the therapy of liver cancer. 10.3389/fonc.2022.985484
Identification of cuproptosis and ferroptosis-related subgroups and development of a signature for predicting prognosis and tumor microenvironment landscape in hepatocellular carcinoma. Translational cancer research Background:Ferroptosis and cuproptosis play a crucial role in the progression and dissemination of hepatocellular carcinoma (HCC). The primary objective of this study was to develop a unique scoring system for predicting the prognosis and immunological landscape of HCC based on ferroptosis-related genes (FRGs) and cuproptosis-related genes (CRGs). Methods:As the training cohort, we assembled a novel HCC cohort by merging gene expression data and clinical data from The Cancer Genome Atlas (TCGA) database, and Gene Expression Omnibus (GEO) database. The validation cohort consisted of 230 HCC cases taken from the International Cancer Genome Consortium (ICGC) database. Multiple genomic characteristics, such as tumor mutation burden (TMB), and copy number variations were analyzed concurrently. On the basis of the expression of CRGs and FRGs, patients were classified into cuproptosis and ferroptosis subtypes. Then, we constructed a risk model using least absolute shrinkage and selection operator (LASSO) analysis and Cox regression analysis based on ferroptosis and cuproptosis-related differentially expressed genes (DEGs). Patients were separated into two groups according to median risk score. We compared the immunophenotype, tumor microenvironment (TME), cancer stem cell index, and treatment sensitivity of two groups. Results:Three subtypes of ferroptosis and two subtypes of cuproptosis were identified among the patients. A greater likelihood of survival (P<0.05) was expected for patients in FRGcluster B and CRGcluster B. After that, a confirmed risk signature for ferroptosis and cuproptosis was developed and tested. Patients in the low-risk group had significantly higher survival rates than those in the high-risk group, according to our study (P<0.001). There was also a strong correlation between the signature and other variables including immunophenoscore, TMB, cancer stem cell index, immunological checkpoint genes, and sensitivity to chemotherapeutics. Conclusions:Through this comprehensive research, we identified a unique risk signature associated with HCC patients' treatment status and prognosis. Our findings highlight FRGs' and CRGs' significance in clinical practice and imply ferroptosis and cuproptosis may be therapeutic targets for HCC patients. 10.21037/tcr-23-685
Prognosis and immune response of a cuproptosis-related lncRNA signature in low grade glioma. Frontiers in genetics Cuproptosis is a newly discovered new mechanism of programmed cell death, and its unique pathway to regulate cell death is thought to have a unique role in understanding cancer progression and guiding cancer therapy. However, this regulation has not been studied in low grade glioma (LGG) at present. In this study, data on low grade glioma patients were downloaded from the TCGA database. We screened the genes related to cuproptosis from the published papers and confirmed the lncRNAs related to them. We applied univariate/multivariate, and LASSO regression algorithms, finally identified 11 lncRNAs for constructing prognosis prediction models, and constructed a risk scoring model. The reliability and validity test of the model indicated that the model could well distinguish the prognosis and survival of LGG patients. Furthermore, the analyses of immunotherapy, immune microenvironment, as well as functional enrichment were also performed. Finally, we verified the expression of these six prognostic key lncRNAs using real-time polymerase chain reaction (RT-PCR). In conclusion, this study is the first analysis based on cuproptosis-related lncRNAs in LGG and aims to open up new directions for LGG therapy. 10.3389/fgene.2022.975419
Construction and validation of a cuproptosis-related lncRNA signature as a novel and robust prognostic model for colon adenocarcinoma. Frontiers in oncology Background:Cuproptosis, a newly identified form of programmed cell death, is thought to play a role in tumorigenesis. Long non-coding RNAs (lncRNAs) are reported to be associated with tumor progression and prognosis in colon adenocarcinoma (COAD). However, the role and prognostic value of cuproptosis-related lncRNAs in COAD remains unknown. This study is devoted to constructing and validating a cuproptosis-related lncRNA signature that can predict COAD patient outcomes using bioinformatics methods. Methods:The COAD mRNA and lncRNA expression profiles and corresponding clinical data were downloaded from The Cancer Genome Atlas (TCGA) database and 2,567 cuproptosis-related lncRNAs were obtained. A 10 cuproptosis-related-lncRNA prognostic signature was then constructed using the least absolute shrinkage and selection operator (LASSO) algorithm and Cox regression model and patients were divided into high- and low-risk groups. Kaplan-Meier analysis, receiver operating characteristic (ROC) curve, and a nomogram were employed to evaluate the predictive power of the signature. The immune characteristics and drug sensitivity were also investigated based on the signature. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) was performed to verify the risk model. experiments were conducted to validate the expression of the ten lncRNAs during cuproptosis. Results:The high-risk group was associated with shorter overall survival (OS) time in COAD patients (p<0.001). Multivariate Cox regression indicated that a high-risk score was an independent risk factor for poor prognosis (p<0.001). ROC curve analysis was performed to confirm the validity of the signature (area under the curve (AUC) at 3 years: 0.879). Gene Ontology (GO) enrichment analysis revealed that the signature was highly correlated with the immune response in biological processes. The immune function, the score of the immune cells, and the expression of immune checkpoints were significantly different between the two risk groups. Three drugs, LAQ824, FH535, YM155, were found to be more sensitive in the high-risk group. Finally, the expression levels of the ten lncRNAs comprising the signature were tested by qRT-PCR. Conclusion:A ten-cuproptosis-related lncRNA signature was constructed that provided promising insights into personalized prognosis and drug selection among COAD patients. 10.3389/fonc.2022.961213
Comprehensive analysis of cuproptosis-related lncRNAs signature to predict prognosis in bladder urothelial carcinoma. BMC urology BACKGROUND:Cuproptosis-related genes (CRGs) have been recently discovered to regulate the occurrence and development of various tumors by controlling cuproptosis, a novel type of copper ion-dependent cell death. Although cuproptosis is mediated by lipoylated tricarboxylic acid cycle proteins, the relationship between cuproptosis-related long noncoding RNAs (crlncRNAs) in bladder urothelial carcinoma (BLCA) and clinical outcomes, tumor microenvironment (TME) modification, and immunotherapy remains unknown. In this paper, we tried to discover the importance of lncRNAs for BLCA. METHODS:The BLCA-related lncRNAs and clinical data were first obtained from The Cancer Genome Atlas (TCGA). CRGs were obtained through Coexpression, Cox regression and Lasso regression. Besides, a prognosis model was established for verification. Meanwhile, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, gene ontology (GO) analysis, principal component analysis (PCA), half-maximal inhibitory concentration prediction (IC50), immune status and drug susceptibility analysis were carried out. RESULTS:We identified 277 crlncRNAs and 16 survival-related lncRNAs. According to the 8-crlncRNA risk model, patients could be divided into high-risk group and low-risk group. Progression-Free-Survival (PFS), independent prognostic analysis, concordance index (C-index), receiver operating characteristic (ROC) curve and nomogram all confirmed the excellent predictive capability of the 8-lncRNA risk model for BLCA. During gene mutation burden survival analysis, noticeable differences were observed in high- and low-risk patients. We also found that the two groups of patients might respond differently to immune targets and anti-tumor drugs. CONCLUSION:The nomogram with 8-lncRNA may help guide treatment of BLCA. More clinical studies are necessary to verify the nomogram. 10.1186/s12894-023-01292-9
Comprehensive analysis of cuproptosis-associated LncRNAs predictive value and related CeRNA network in acute myeloid leukemia. Heliyon Background:Acute myeloid leukemia (AML) is characterized by a high recurrence and mortality rate. Cuproptosis is involved in cell death regulation in in a variety of solid tumors. Long non-coding RNAs that regulate cuproptosis genes in the pathogenesis of acute leukemia have yet to be explored. Methods:First, cuproptosis genes with distinct expression levels were discovered by contrasting AML with normal samples from the TCGA and GTEx cohorts. Pearson correlation and univariate Cox-regression analysis were performed to identify cuproptosis-associated lncRNAs with significant prognostic values. Then the least absolute shrinkage and selection operator (LASSO) Cox regression was utilized to establish a multi-gene signature to predict AML prognosis. Next, Kaplan-Meier estimator, receiver operating characteristic curve, and a nomogram were performed to evaluate the predictive capacity of the risk signature. Functional enrichment analyses were employed to assess their function. Moreover, qRT-PCR testing of lncRNA expression in AML samples was conducted. The competing endogenous RNA (ceRNA) network was constructed to find the target genes. Results:A risk model based on the signature of three cuproptosis-associated lncRNAs was developed. The results showed that the model possessed excellent prognostic potential. The nomogram raised the accuracy in predicting AML survival. In addition, functional enrichment analyses demonstrated an enrichment of inflammatory and immune-related pathways. Moreover, correlations between the risk signature and clinicopathological variables, tumor mutational burden, RNA stemness score, immune profile, and drug sensitivity were observed. Furthermore, we discovered that TRAF3IP2-AS1 may function as a ceRNA to regulate cuproptosis and ferroptosis gene expression. Conclusion:The risk signature established in this study could serve as a reliable biosignature for AML prognosis. And the findings presented here may facilitate research on cuproptosis in AML. 10.1016/j.heliyon.2023.e22532
Cuproptosis-associated hub gene identification and immune cell infiltration patterns in silicosis. Toxicology Recent research has hinted at a potential connection between silicosis, a fibrotic lung disease caused by exposure to crystalline silica particles, and cuproptosis. The aim of the study was to explore how cuproptosis-related genes (CRGs) may influence the development of silicosis and elucidate the underlying mechanisms. An analysis of genes associated with both silicosis and cuproptosis was conducted. Key gene identification was achieved through the application of two machine learning techniques. Additionally, the correlation between these key genes and immune cell populations was explored and the critical pathways were discerned. To corroborate our findings, the expression of key genes was verified in both a publicly available silica-induced mouse model and our own silicosis mouse model. A total of 12 differentially expressed CRGs associated with silicosis were identified. Further analysis resulted in the identification of 6 CRGs, namely LOX, SPARC, MOXD1, ALB, MT-CO2, and AOC2. Elevated immune cell infiltration of CD8 T cells, regulatory T cells, M0 macrophages, and neutrophils in silicosis patients compared to healthy controls was indicated. Validation in a silica-induced pulmonary fibrosis mouse model supported SPARC and MT-CO2 as potential signature genes for the prediction of silicosis. These findings highlight a strong association between silicosis and cuproptosis. Among CRGs, LOX, SPARC, MOXD1, ALB, MT-CO2, and AOC2 emerged as pivotal players in the context of silicosis by modulating CD8 T cells, regulatory T cells, M0 macrophages, and neutrophils. 10.1016/j.tox.2024.153762
Identification of Cuproptosis-Related circRNA-miRNA-mRNA Network in Laser-Induced Choroidal Neovascularization Models and in Peripheral Blood Mononuclear Cells of Patients with Neovascular Age-Related Macular Degeneration. Ophthalmic research INTRODUCTION:The aims of this study were to investigate the molecular alterations of cuproptosis-related genes and to construct the cuproptosis-related circular RNA (circRNA)-microRNA (miRNA)-mRNA networks in neovascular age-related macular degeneration (nAMD). METHODS:The transcriptional profiles of laser-induced choroid neovascularization (CNV) mouse models and nAMD patient samples were obtained from sequencing and from the GEO database (GSE146887), respectively. The expression levels of ten cuproptosis-related genes (FDX1, DLAT, LIAS, DLD, PDHB, MTF1, CDKN2A, GLS, LIPT1, and PDHA1) were extracted and verified in both mouse CNV models and patient peripheral blood mononuclear cells (PBMCs) samples. The cuproptosis-related circRNA-miRNA-mRNA network was further constructed based on miRNet database, the dataset GSE131646 of small RNA expression profile, and the dataset GSE140178 of circRNA expression profile in mouse CNV models. RESULTS:The significant upregulation of Cdkn2a and Mtf1 and the downregulation of other 5 cuproptosis-related genes were verified in the mouse CNV model, but only CDKN2A significantly upregulated in PBMCs of patients with nAMD. Four miRNAs were detected in the intersection between miRNet prediction and sequencing data: miR-129-5p, miR-129-2-3p, miR-182-5p, and miR-615-3p. There were 9 circRNAs at the intersection of hsa-miR-182-5p and hsa-miR-615-3p predictions, one circRNA predicted by hsa-miR-129-5p and GSE140178 (hsa-circASH1L), and one circRNA predicted by hsa-miR-182-5p and hsa-miR-615-3p (hsa-circNPEPPS). CONCLUSION:This study suggested the repression of cuproptosis in nAMD pathologies and constructed a cuproptosis-related network of 8 cuproptosis-related genes, 4 miRNAs, and 11 circRNAs. 10.1159/000535170
Integrated analysis reveals a potential cuproptosis-related ceRNA axis SNHG17/miR-29a-3p/GCSH in prostate adenocarcinoma. Heliyon Cuproptosis is a novel form of programmed cell death. The role and mechanism of cuproptosis-related genes in prostate adenocarcinoma have not been fully understood. In this study, a series of bioinformatic analyses were performed. Consequently, glycine cleavage system protein H with high expression and unfavorable prognosis was regarded as the most potential cuproptosis-related gene in prostate adenocarcinoma. Moreover, glycine cleavage system protein H might be a promising indicator for predicting leuprolide sensitivity in prostate adenocarcinoma and three potential drugs targeting glycine cleavage system protein H were identified. Enrichment analysis revealed that glycine cleavage system protein H-correlated genes were significantly enriched in tricarboxylic acid cycle-related pathways. Subsequently, small nucleolar RNA host gene 17/miR-29a-3p axis was found to partially account for overexpression of glycine cleavage system protein H in prostate adenocarcinoma. Collectively, the current study elucidated a potential cuproptosis-related competing endogenous RNA axis small nucleolar RNA host gene 17/miR-29a-3p/glycine cleavage system protein H in prostate adenocarcinoma. 10.1016/j.heliyon.2023.e21506
Identification and validation of cuproptosis-related molecular clusters in non-alcoholic fatty liver disease. Journal of cellular and molecular medicine Non-alcoholic fatty liver disease (NAFLD) is a major chronic liver disease worldwide. Cuproptosis has recently been reported as a form of cell death that appears to drive the progression of a variety of diseases. This study aimed to explore cuproptosis-related molecular clusters and construct a prediction model. The gene expression profiles were obtained from the Gene Expression Omnibus (GEO) database. The associations between molecular clusters of cuproptosis-related genes and immune cell infiltration were investigated using 50 NAFLD samples. Furthermore, cluster-specific differentially expressed genes were identified by the WGCNA algorithm. External datasets were used to verify and screen feature genes, and nomograms, calibration curves and decision curve analysis (DCA) were performed to verify the performance of the prediction model. Finally, a NAFLD-diet mouse model was constructed to further verify the predictive analysis, thus providing new insights into the prediction of NAFLD clusters and risks. The role of cuproptosis in the development of non-alcoholic fatty liver disease and immune cell infiltration was explored. Non-alcoholic fatty liver disease was divided into two cuproptosis-related molecular clusters by unsupervised clustering. Three characteristic genes (ENO3, SLC16A1 and LEPR) were selected by machine learning and external data set validation. In addition, the accuracy of the nomogram, calibration curve and decision curve analysis in predicting NAFLD clusters was also verified. Further animal and cell experiments confirmed the difference in their expression in the NAFLD mouse model and Mouse hepatocyte cell line. The present study explored the relationship between non-alcoholic fatty liver disease and cuproptosis, providing new ideas and targets for individual treatment of the disease. 10.1111/jcmm.18091
Identification and Validation of Glycosyltransferases Correlated with Cuproptosis as a Prognostic Model for Colon Adenocarcinoma. Cells Cuproptosis is a newly defined programmed cell death pattern and is believed to play an important role in tumorigenesis and progression. In addition, many studies have shown that glycosylation modification is of vital importance in tumor progression. However, it remains unclear whether glycosyltransferases, the most critical enzymes involved in glycosylation modification, are associated with cuproptosis. In this study, we used bioinformatic methods to construct a signature of cuproptosis-related glycosyltransferases to predict the prognosis of colon adenocarcinoma patients. We found that cuproptosis was highly correlated with four glycosyltransferases in COAD, and our model predicted the prognosis of COAD patients. Further analysis of related functions revealed the possibility that cuproptosis-related glycosyltransferase Exostosin-like 2 () participated in tumor immunity. 10.3390/cells11233728
A comprehensive analysis focusing on cuproptosis to investigate its clinical and biological relevance in uterine corpus endometrial carcinoma and its potential in indicating prognosis. Frontiers in molecular biosciences Cuproptosis, a novel copper-dependent cell death involving mitochondrial respiration, is distinct from other known death mechanisms, which inspires us to study further in uterine corpus endometrial carcinoma (UCEC). Herein, leveraging comprehensive data from TCGA-UCEC, we conducted transcriptional and genetic analyses of 13 recently identified cuproptosis genes. We discovered severe genetic instability of cuproptosis genes, extensive positive correlations among those genes with each other at the mRNA level, and their involvement in oncogenic pathways in UCEC samples. Next, WGCNA was performed to identify a potential module regulating cuproptosis, in which the hub genes, in addition to 13 cuproptosis genes, were drawn to construct a scoring system termed Cu. Score. Furthermore, its clinical and biological relevance and tumor immune landscape, genetic alterations, as well as predicted sensitivity of chemotherapy drugs in different Cu. Score subgroups had been discussed extensively and in detail. Additionally, univariate Cox and LASSO regression were performed to identify 13 cuproptosis-related prognostic genes to establish a prognostic signature, the Risk. Score. Integrating the Risk. Score and clinical parameters, we established a nomogram with excellent performance to predict the 1-/3-/5-year survival probabilities of UCEC patients. To conclude, we conducted a comprehensive analysis encompassing cuproptosis and developed a cuproptosis scoring system and a prognostic prediction model for UCEC, which may offer help with individualized assessment and treatment for UCEC patients from the perspective of a novel death mechanism. 10.3389/fmolb.2022.1048356
Development and Verification of a novel cuproptosis- and immune-associated based prognostic genetic signature for pancreatic ductal adenocarcinoma. Clinics and research in hepatology and gastroenterology OBJECTIVE:Pancreatic ductal adenocarcinoma (PDAC) is a malignancy with a dismal prognosis. Cuproptosis, a novel mechanism mediated by protein lipoylation, results in acute proteotoxic stress and ultimately cell death. However, the clinical impacts of cuproptosis-associated genes and their relationship with immune status in PDAC have not been documented. In this study, we aimed at constructing a cuproptosis- and immune-associated prognostic signature to stratify and predict the prognosis for PDAC patients. METHODS:The gene expression profiles of 176 PDAC patients from The Cancer Genome Atlas and 167 normal pancreas tissues from the Genotype-Tissue Expression Project were analyzed for differentially expressed genes (DEGs) between PDAC and normal tissues. Pearson correlation analyses were performed to screen out cuproptosis- and immune-associated DEGs. The risk signature of DEGs was constructed using the least absolute shrinkage and selection operator (LASSO) Cox regression analysis, which was validated in the Gene Expression Omnibus (GEO) cohort (n = 114). The immune characteristics in the two risk groups were evaluated using single-sample gene set enrichment analysis and ESTIMATE algorithms. RESULTS:A total of 91 cuproptosis- and immune-associated DEGs were screened out, and eight prognostic-related genes were identified using LASSO Cox regression. The prognostic-related genes were then used to construct a risk scoring model, which stratified patients into low- and high-risk groups and were further verified in the external GEO database. The patients in the high-risk group had significantly shorter overall survival than those in the low-risk group. A nomogram based on the risk signature was then constructed. Immune infiltration evaluation suggested that immune status was more activated in the low-risk group. The mutation spectrum also differed between high- and low-risk groups. CONCLUSIONS:Our cuproptosis- and immune-associated genetic risk signature could be a prognostic biomarker for PDAC. Cuproptosis might be a promising therapeutic target for PDAC. 10.1016/j.clinre.2023.102089
TIGD1 Function as a Potential Cuproptosis Regulator Following a Novel Cuproptosis-Related Gene Risk Signature in Colorectal Cancer. Cancers Cuproptosis is a new form of copper-dependent programmed cell death commonly occurring within the body. There is emerging evidence indicating that cuproptosis has a significant regulatory function in the onset and progression of cancer. However, it is still unclear how cuproptosis regulates cancer and whether other genes are involved in the regulation. Using the TCGA-COAD dataset of 512 samples, we found that seven of ten cuproptosis markers showed prognostic value in colorectal cancer (CRC) using Kaplan-Meier survival analysis. Furthermore, 31 prognostic cuproptosis-related genes were identified using weighted gene co-expression network analysis and univariate Cox analysis. Subsequently, we constructed a 7-PCRG signature using least absolute shrinkage and selection operator (LASSO)-Cox regression analysis. The risk score predicting survival in patients with CRC was evaluated. Two risk groups were classified based on their risk scores. The two groups revealed a significant difference in immune cells, such as B and T cells. Furthermore, we identified differences in many immune functions and checkpoints, including CD276 and CD28. In vitro experiments showed that a hub cuproptosis-related gene, TIGD1, could significantly regulate cuproptosis in CRC after exposure to elesclomol. This study validated that cuproptosis was closely related to the progression of CRC. Seven new cuproptosis-related genes were identified, and the function of TIGD1 in cuproptosis was preliminarily understood. Since a certain concentration of copper in CRC cells is important, cuproptosis may provide a new target for cancer therapy. This study may provide novel insights into the treatment of CRC. 10.3390/cancers15082286
Multi-omics analysis uncovers clinical, immunological, and pharmacogenomic implications of cuproptosis in clear cell renal cell carcinoma. European journal of medical research OBJECTIVE:The latest research proposed a novel copper-dependent programmed cell death named cuproptosis. We aimed to elucidate the influence of cuproptosis in clear cell renal cell carcinoma (ccRCC) from a multi-omic perspective. METHODS:This study systematically assessed mRNA expression, methylation, and genetic alterations of cuproptosis genes in TCGA ccRCC samples. Through unsupervised clustering analysis, the samples were classified as different cuproptosis subtypes, which were verified through NTP method in the E-MTAB-1980 dataset. Next, the cuproptosis score (Cuscore) was computed based on cuproptosis-related genes via PCA. We also evaluated clinical and immunogenomic features, drug sensitivity, immunotherapeutic response, and post-transcriptional regulation. RESULTS:Cuproptosis genes presented multi-layer alterations in ccRCC, and were linked with patients' survival and immune microenvironment. We defined three cuproptosis subtypes [C1 (moderate cuproptosis), C2 (low cuproptosis), and C3 (high cuproptosis)], and the robustness and reproducibility of this classification was further proven. Overall survival was best in C3, moderate in C1, and worst in C2. C1 had the highest sensitivity to pazopanib, and sorafenib, while C2 was most sensitive to sunitinib. Furthermore, C1 patients benefited more from anti-PD-1 immunotherapy. Patients with high Cuscore presented the notable survival advantage. Cuscore was highly linked with immunogenomic features, and post-transcriptional events that contributed to ccRCC development. Finally, several potential compounds and druggable targets (NMU, RARRES1) were selected for low Cuscore group. CONCLUSION:Overall, our study revealed the non-negligible role of cuproptosis in ccRCC development. Evaluation of the cuproptosis subtypes improves our cognition of immunogenomic features and better guides personalized prognostication and precision therapy. 10.1186/s40001-023-01221-4
Signature of seven cuproptosis-related lncRNAs as a novel biomarker to predict prognosis and therapeutic response in cervical cancer. Frontiers in genetics Given the high incidence and high mortality of cervical cancer (CC) among women in developing countries, identifying reliable biomarkers for the prediction of prognosis and therapeutic response is crucial. We constructed a prognostic signature of cuproptosis-related long non-coding RNAs (lncRNAs) as a reference for individualized clinical treatment. A total of seven cuproptosis-related lncRNAs closely related to the prognosis of patients with CC were identified and used to construct a prognostic signature via least absolute shrinkage and selection operator regression analysis in the training set. The predictive performance of the signature was evaluated by Kaplan-Meier (K-M) analysis, receiver operating characteristic (ROC) analysis, and univariate and multivariate Cox analyses. Functional enrichment analysis and single-sample gene set enrichment analysis were conducted to explore the potential mechanisms of the prognostic signature, and a lncRNA-microRNA-mRNA network was created to investigate the underlying regulatory relationships between lncRNAs and cuproptosis in CC. The associations between the prognostic signature and response to immunotherapy and targeted therapy were also assessed. Finally, the prognostic value of the signature was validated using the CC tissues with clinical information in my own center. A prognostic signature was developed based on seven cuproptosis-related lncRNAs, including five protective factors (AL441992.1, LINC01305, AL354833.2, CNNM3-DT, and SCAT2) and two risk factors (AL354733.3 and AC009902.2). The ROC curves confirmed the superior predictive performance of the signature compared with conventional clinicopathological characteristics in CC. The ion transport-related molecular function and various immune-related biological processes differed significantly between the two risk groups according to functional enrichment analysis. Furthermore, we discovered that individuals in the high-risk group were more likely to respond to immunotherapy and targeted therapies including trametinib and cetuximab than those in the low-risk group. Finally, CC tissues with clinical data from my own center further verify the robustness of the seven-lncRNA risk signature. We generated a cuproptosis-related lncRNA risk signature that could be used to predict prognosis of CC patients. Moreover, the signature could be used to predict response to immunotherapy and chemotherapy and thus could assist clinicians in making personalized treatment plans for CC patients. 10.3389/fgene.2022.989646
Construction of a cuproptosis-related lncRNA signature for predicting prognosis and immune landscape in osteosarcoma patients. Cancer medicine BACKGROUND:Long noncoding RNAs (lncRNAs) influence the onset of osteosarcoma. Cuproptosis is a novel cell death mechanism. We attempted to identify a cuproptosis-related lncRNA signature to predict the prognosis and immune landscape in osteosarcoma patients. METHODS:Transcriptional and clinical data of 85 osteosarcoma patients were derived from the TARGET database and randomly categorized into the training and validation cohorts. We implemented the univariate and multivariate Cox regression, along with LASSO regression analyses for developing a cuproptosis-related lncRNA risk model. Kaplan-Meier curves, C-index, ROC curves, univariate and multivariate Cox regression, and nomogram were used to assess the capacity of this risk model to predict the osteosarcoma prognosis. Gene ontology, KEGG, and Gene Set Enrichment (GSEA) analyses were conducted for determining the potential functional differences existing between the high-risk and low-risk patients. We further conducted the ESTIMATE, single-smaple GSEA, and CIBERSORT analyses for identifying the different immune microenvironments and immune cells infiltrating both the risk groups. RESULTS:We screened out four cuproptosis-related lncRNAs (AL033384.2, AL031775.1, AC110995.1, and LINC00565) to construct the risk model in the training cohort. This risk model displayed a good performance to predict the overall survival of osteosarcoma patients, which was confirmed by using the validation and the entire cohort. Further analyses showed that the low-risk patients have more immune activation and immune cells infiltrating as well as a good response to immunotherapy. CONCLUSIONS:We developed a novel cuproptosis-related lncRNA signature with high reliability and accuracy for predicting outcome and immunotherapy response in osteosarcoma patients, which provides new insights into the personalized treatment of osteosarcoma. 10.1002/cam4.5214
Deep learning reveals cuproptosis features assist in predict prognosis and guide immunotherapy in lung adenocarcinoma. Frontiers in endocrinology Background:Cuproptosis is a recently found non-apoptotic cell death type that holds promise as an emerging therapeutic modality in lung adenocarcinoma (LUAD) patients who develop resistance to radiotherapy and chemotherapy. However, the Cuproptosis' role in the onset and progression of LUAD remains unclear. Methods:Cuproptosis-related genes (CRGs) were identified by a co-expression network approach based on LUAD cell line data from radiotherapy, and a robust risk model was developed using deep learning techniques based on prognostic CRGs and explored the value of deep learning models systematically for clinical applications, functional enrichment analysis, immune infiltration analysis, and genomic variation analysis. Results:A three-layer artificial neural network risk model was constructed based on 15 independent prognostic radiotherapy-related CRGs. The risk model was observed as a robust independent prognostic factor for LUAD in the training as well as three external validation cohorts. The patients present in the low-risk group were found to have immune "hot" tumors exhibiting anticancer activity, whereas the high-risk group patients had immune "cold" tumors with active metabolism and proliferation. The high-risk group patients were more sensitive to chemotherapy whereas the low-risk group patients were more sensitive to immunotherapy. Genomic variants did not vary considerably among both groups of patients. Conclusion:Our findings advance the understanding of cuproptosis and offer fresh perspectives on the clinical management and precision therapy of LUAD. 10.3389/fendo.2022.970269
Changes in cuproptosis-related gene expression in periodontitis: An integrated bioinformatic analysis. Life sciences Periodontitis causes inflammatory destruction of tooth-supporting tissues; however, the complex mechanism underlying its etiology remains unclear. Cuproptosis is a type of cell death caused by an imbalance in intracellular copper homeostasis that leads to excess copper. However, changes in the expression and biological function of cuproptosis-related genes (CRGs) in periodontitis are not yet fully understood. This study investigated the comprehensive effects of differentially expressed CRGs (DE-CRGs) on periodontitis via bioinformatic analysis. Nine DE-CRGs were discovered using normal and periodontitis gingival samples, and single-cell RNA sequencing data were analyzed to identify them changes in diverse cell clusters. We then detected the correlation between DE-CRGs and immune infiltration, immune factors, mitochondrial dysfunction, diagnostic efficacy, and predicted drugs. Moreover, changes of DE-CRG in whole periodontitis tissue and a human gingival fibroblast cell line (HGF-1) were confirmed and copper content changes in HGF-1 cells were investigated. Most DE-CRG expression trends were reversed between the periodontal tissues and cell clusters, which may be related to the proportion of cell clusters changes caused periodontitis. Furthermore, most DE-CRG trends in periodontitis cell clusters were inconsistent with the effects of cuproptosis. In HGF-1 cells treated with Porphyromonas gingivalis lipopolysaccharide (Pg-LPS), the intracellular copper content increased by more than threefold, indicating that although some periodontitis cells had excess copper, the amount may not have been sufficient to trigger cuproptosis. Additionally, DE-CRGs were closely associated with multiple biological functions, antibiotic drugs, and natural herbal medicines. Our findings may provide an overview of DE-CRGs in the pathogenesis and treatment of periodontitis. 10.1016/j.lfs.2023.122388
Corrigendum: Cuproptosis key gene FDX1 is a prognostic biomarker and associated with immune infiltration in glioma. Frontiers in medicine [This corrects the article DOI: 10.3389/fmed.2022.939776.]. 10.3389/fmed.2023.1244638
Identification of novel cuproptosis-related lncRNA signatures to predict the prognosis and immune microenvironment of breast cancer patients. Frontiers in oncology Background:Cuproptosis is a new modality of cell death regulation that is currently considered as a new cancer treatment strategy. Nevertheless, the prognostic predictive value of cuproptosis-related lncRNAs in breast cancer (BC) remains unknown. Using cuproptosis-related lncRNAs, this study aims to predict the immune microenvironment and prognosis of BC patients. and develop new therapeutic strategies that target the disease. Methods:The Cancer Genome Atlas (TCGA) database provided the RNA-seq data along with the corresponding clinical and prognostic information. Univariate and multivariate Cox regression analyses were performed to acquire lncRNAs associated with cuproptosis to establish predictive features. The Kaplan-Meier method was used to calculate the overall survival rate (OS) in the high-risk and low-risk groups. High risk and low risk gene sets were enriched to explore functional discrepancies among risk teams. The mutation data were analyzed using the "MAFTools" r-package. The ties of predictive characteristics and immune status had been explored by single sample gene set enrichment analysis (ssGSEA). Last, the correlation between predictive features and treatment condition in patients with BC was analyzed. Based on prognostic risk models, we assessed associations between risk subgroups and immune scores and immune checkpoints. In addition, drug responses in at-risk populations were predicted. Results:We identified a set of 11 Cuproptosis-Related lncRNAs (GORAB-AS1, AC 079922.2, AL 589765.4, AC 005696.4, Cytor, ZNF 197-AS1, AC 002398.1, AL 451085.3, YTH DF 3-AS1, AC 008771.1, LINC 02446), based on which to construct the risk model. In comparison to the high-risk group, the low-risk patients lived longer (p < 0.001). Moreover, cuproptosis-related lncRNA profiles can independently predict prognosis in BC patients. The AUC values for receiver operating characteristics (ROC) of 1-, 3-, and 5-year risk were 0.849, 0.779, and 0.794, respectively. Patients in the high-risk group had lower OS than those in the low-risk group when they were divided into groups based on various clinicopathological variables. The tumor burden mutations (TMB) correlation analysis showed that high TMB had a worse prognosis than low-TMB, and gene mutations were found to be different in high and low TMB groups, such as PIK3CA (36% versus 32%), SYNE1 (4% versus 6%). Gene enrichment analysis indicated that the differential genes were significantly concentrated in immune-related pathways. The predictive traits were significantly correlated with the immune status of BC patients, according to ssGSEA results. Finally, high-risk patients showed high sensitivity in anti-CD276 immunotherapy and conventional chemotherapeutic drugs such as imatinib, lapatinib, and pazopanib. Conclusion:We successfully constructed of a cuproptosis-related lncRNA signature, which can independently predict the prognosis of BC patients and can be used to estimate OS and clinical treatment outcomes in BRCA patients. It will serve as a foundation for further research into the mechanism of cuproptosis-related lncRNAs in breast cancer, as well as for the development of new markers and therapeutic targets for the disease. 10.3389/fonc.2022.988680
Molecular subtypes based on cuproptosis-related genes and tumor microenvironment infiltration characterization in ovarian cancer. Cancer cell international BACKGROUND:Cuproptosis (copper death) is a recently found cell death type produced by copper iron; nonetheless, the properties of cuproptosis molecular subtypes and possible involvement of cuproptosis-related genes (CRGs) in the tumor microenvironment (TME) in ovarian cancer (OC) remain unknown. METHODS:CRG changes were characterized at the genomic and transcriptional levels in 656 OC samples, and their expression patterns were investigated using three different datasets. RESULTS:We identified three distinct molecular subtypes, and discovered that variations in molecular subtypes were linked to patient prognosis, TME cell infiltration characteristics, malignancy, and immune-related pathways. Then, in order to predict overall survival (OS), we created a risk score and tested its predictive potential in OC patients. As a result, we created a very accurate nomogram to increase risk score clinical applicability. Better OS, younger age, early stage, and immune activity were all associated with a low risk score. The hallmarks of a high-risk score are older age, advanced stage, immunosuppression, and a bad prognosis. Furthermore, risk score was linked to immune checkpoint expression (including PD-L1, CTLA4), targeted therapy gene expression (PARP, PDGFRA), cancer stem cell (CSC), chemotherapy and targeted medication sensitivity. CONCLUSIONS:Our comprehensive analysis of CRGs in OC showed their potential role in TME, clinicopathological characteristics, chemotherapy and targeted drug screening and prognosis. These discoveries could help us better understand CRGs in OC, as well as pave the path for novel ways to assess prognosis and design more effective immunotherapy strategies. 10.1186/s12935-022-02756-y
Molecular Subtyping Based on Cuproptosis-Related Genes and Characterization of Tumor Microenvironment Infiltration in Kidney Renal Clear Cell Carcinoma. Frontiers in oncology The incidence of kidney renal clear cell carcinoma (KIRC) is rising worldwide, and the prognosis is poor. Cuproptosis is a new form of cell death that is dependent on and regulated by copper ions. The relationship between cuproptosis and KIRC remains unclear. In the current study, changes in cuproptosis-related genes (CRGs) in TCGA-KIRC transcriptional datasets were characterized, and the expression patterns of these genes were analyzed. We identified three main molecular subtypes and discovered that multilayer CRG changes were associated with patient clinicopathological traits, prognosis, elesclomol sensitivity, and tumor microenvironment (TME) cell infiltration characteristics. Then, a CRG score was created to predict overall survival (OS). The CRG score was found to be strongly linked to the TME. These findings may help elucidate the roles of CRGs in KIRC, potentially enhancing understanding of cuproptosis and supporting the development of more effective immunotherapy strategies. 10.3389/fonc.2022.919083
A Newly Established Cuproptosis-Associated Long Non-Coding RNA Signature for Predicting Prognosis and Indicating Immune Microenvironment Features in Soft Tissue Sarcoma. Journal of oncology Cuproptosis, a new type of programmed cell death, is involved in the development and progression of malignancies. The study of cuproptosis-associated long non-coding RNAs (lncRNAs) in soft tissue sarcomas (STSs) is however limited. There is also uncertainty regarding the prognostic accuracy of cuproptosis-associated lncRNAs in STSs and their relationship to the tumor immune microenvironment. The aim of this study was to determine the prognostic significance of cuprotosis-associated lncRNAs in STSs and their relationship to the tumor immune microenvironment. Transcriptomic and clinical data from patients with STSs were obtained through The Cancer Genome Atlas (TCGA). Overall, 259 patients were randomly allocated to a training group or a testing group. In the training group, a cuproptosis-associated lncRNA signature was constructed, and the signature was verified in the testing group. On the basis of risk scores and clinical features, we later developed a hybrid nomogram. We also performed functional and tumor immune microenvironment analysis based on the cuproptosis-associated lncRNA signature. A signature of 5 cuproptosis-associated lncRNAs was created. Based on this signature, we categorized STS patients into high-risk and low-risk groups. The study showed that patients at high risk had a worse prognosis than those at low risk. A nomogram was then constructed combining clinical characteristics with the risk scores, and it was shown to have credible predictive power. Functional enrichment and tumor immune microenvironmental analyses showed that high-risk STSs tend to be immunologically sensitive tumors. In our study, we found a cuproptosis-associated lncRNAs signature, which serves as an independent prognostic indicator. Cuproptosis-associated lncRNAs may play a role in the tumor immune microenvironment, which might be a therapeutic target for patients with STSs. 10.1155/2022/8489387
Construction of a Cuproptosis-Related Gene Signature for Predicting Prognosis in Gastric Cancer. Biochemical genetics This study aimed to develop and validate a cuproptosis-related gene signature for the prognosis of gastric cancer. The data in TCGA GC TPM format from UCSC were extracted for analysis, and GC samples were randomly divided into training and validation groups. Pearson correlation analysis was used to obtain cuproptosis-related genes co-expressed with 19 Cuproptosis genes. Univariate Cox and Lasso regression analyses were used to obtain cuproptosis-related prognostic genes. Multivariate Cox regression analysis was used to construct the final prognostic risk model. The risk score curve, Kaplan-Meier survival curves, and ROC curve were used to evaluate the predictive ability of Cox risk model. Finally, the functional annotation of the risk model was obtained through enrichment analysis. Then, a six-gene signature was identified in the training cohort and verified among all cohorts using Cox regression analyses and Kaplan-Meier plots, demonstrating its independent prognostic significance for gastric cancer. In addition, ROC analysis confirmed the significant predictive potential of this signature for the prognosis of gastric cancer. Functional enrichment analysis was mainly related to cell-matrix function. Therefore, a new cuproptosis-related six-gene signature (ACLY, FGD6, SERPINE1, SPATA13, RANGAP1, and ADGRE5) was constructed for the prognosis of gastric cancer, allowing for tailored prediction of outcome and the formulation of novel therapeutics for gastric cancer patients. 10.1007/s10528-023-10406-9
Construction of five cuproptosis-related lncRNA signature for predicting prognosis and immune activity in skin cutaneous melanoma. Frontiers in genetics Cuproptosis is a newly discovered new mechanism of programmed cell death, and its unique pathway to regulate cell death is thought to have a unique role in understanding cancer progression and guiding cancer therapy. However, this regulation has not been studied in SKCM at present. In this study, data on Skin Cutaneous Melanoma (SKCM) patients were downloaded from the TCGA database. We screened the genes related to cuproptosis from the published papers and confirmed the lncRNAs related to them. We applied Univariate/multivariate and LASSO Cox regression algorithms, and finally identified 5 cuproptosis-related lncRNAs for constructing prognosis prediction models (VIM-AS1, AC012443.2, MALINC1, AL354696.2, HSD11B1-AS1). The reliability and validity test of the model indicated that the model could well distinguish the prognosis and survival of SKCM patients. Next, immune microenvironment, immunotherapy analysis, and functional enrichment analysis were also performed. In conclusion, this study is the first analysis based on cuproptosis-related lncRNAs in SKCM and aims to open up new directions for SKCM therapy. 10.3389/fgene.2022.972899
A novel prognostic scoring model based on copper homeostasis and cuproptosis which indicates changes in tumor microenvironment and affects treatment response. Frontiers in pharmacology Intracellular copper homeostasis requires a complex system. It has shown considerable prospects for intervening in the tumor microenvironment (TME) by regulating copper homeostasis and provoking cuproptosis. Their relationship with hepatocellular carcinoma (HCC) remains elusive. In TCGA and ICGC datasets, LASSO and multivariate Cox regression were applied to obtain the signature on the basis of genes associated with copper homeostasis and cuproptosis. Bioinformatic tools were utilized to reveal if the signature was correlated with HCC characteristics. Single-cell RNA sequencing data analysis identified differences in tumor and T cells' pathway activity and intercellular communication of immune-related cells. Real-time qPCR analysis was conducted to measure the genes' expression in HCC and adjacent normal tissue from 21 patients. CCK8 assay, scratch assay, transwell, and colony formation were conducted to reveal the effect of genes on cell proliferation, invasion, migration, and colony formation. We constructed a five-gene scoring system in relation to copper homeostasis and cuproptosis. The high-risk score indicated poor clinical prognosis, enhanced tumor malignancy, and immune-suppressive tumor microenvironment. The T cell activity was markedly reduced in high-risk single-cell samples. The high-risk HCC patients had a better expectation of ICB response and reactivity to anti-PD-1 therapy. A total of 156 drugs were identified as potential signature-related drugs for HCC treatment, and most were sensitive to high-risk patients. Novel ligand-receptor pairs such as FASLG, CCL, CD40, IL2, and IFN-Ⅱ signaling pathways were revealed as cellular communication bridges, which may cause differences in TME and immune function. All crucial genes were differentially expressed between HCC and paired adjacent normal tissue. Model-constructed genes affected the phosphorylation of mTOR and AKT in both Huh7 and Hep3B cells. Knockdown of ZCRB1 impaired the proliferation, invasion, migration, and colony formation in HCC cell lines. We obtained a prognostic scoring system to forecast the TME changes and assist in choosing therapy strategies for HCC patients. In this study, we combined copper homeostasis and cuproptosis to show the overall potential risk of copper-related biological processes in HCC for the first time. 10.3389/fphar.2023.1101749
Comprehensive analysis of cuproptosis-related lncRNAs in immune infiltration and prognosis in hepatocellular carcinoma. BMC bioinformatics BACKGROUND:Being among the most common malignancies worldwide, hepatocellular carcinoma (HCC) accounting for the third cause of cancer mortality. The regulation of cell death is the most crucial step in tumor progression and has become a crucial target for nearly all therapeutic options. Cuproptosis, a copper-induced cell death, was recently reported in Science. However, its primary function in carcinogenesis is still unclear. METHODS:Cuproptosis-related lncRNAs significantly associated with overall survival (OS) were screened by stepwise univariate Cox regression. The signature of cuproptosis-related lncRNAs for HCC prognosis was constructed by the LASSO algorithm and multivariate Cox regression. Further Kaplan-Meier analysis, proportional hazards model, and ROC analysis were performed. Functional annotation was performed using gene set enrichment analysis (GSEA). The relationship between prognostic cuproptosis-related lncRNAs and HCC prognosis was further explored by GEPIA( http://gepia.cancer-pku.cn/ ) online analysis tool. Finally, we used the ESTIMATE and XCELL algorithms to estimate stromal and immune cells in tumor tissue and cast each sample to infer the underlying mechanism of cuproptosis-related lncRNAs in the tumor immune microenvironment (TIME) of HCC patients. RESULTS:Four cuproptosis-related lncRNAs were used to construct a prognostic lncRNA signature, which was an independent factor in predicting OS in HCC patients. Kaplan-Meier curves showed significant differences in survival rates between risk subgroups (p = 0.002). At the same time, we found that the expression levels of most immune checkpoint genes increased with increasing risk scores. Tumorigenesis and immunological-related pathways were primarily enhanced in the high-risk group, as determined by GSEA. The results of drug sensitivity analysis showed that compared with patients in the high-risk group, the IC50 values of erlotinib and lapatinib were lower in patients in the low-risk group, while the opposite was true for sunitinib, paclitaxel, gemcitabine, and imatinib. We also found that elevated AL133243.2 expression was significantly associated with worse OS and disease-free survival (DFS), more advanced T stage and higher tumor grade, and reduced immune cell infiltration, suggesting that HCC patients with low AL133243.2 expression in tumor tissues may have a better response to immunotherapy. CONCLUSION:Collectively, the cuproptosis-associated lncRNA signature can serve as an independent predictor to guide individual treatment strategies. Furthermore, AL133243.2 is a promising marker for predicting immunotherapy response in HCC patients. This data may facilitate further exploration of more effective immunotherapy strategies for HCC. 10.1186/s12859-022-05091-1
Landscape and the immune patterns of cuproptosis in oral squamous cell carcinoma. Journal of oral pathology & medicine : official publication of the International Association of Oral Pathologists and the American Academy of Oral Pathology BACKGROUND:Oral squamous cell carcinoma is an increasingly prevalent cancer type characterized by high incidence and mortality rates. Its early detection is challenging, primarily because of the absence of early molecular markers. Cuproptosis is a novel regulatory mechanism of cell death with implications in various cancers. In this study, we aimed to study cuproptosis-related genes in oral squamous cell carcinoma to identify their prognostic value. METHODS:By analyzing genomic, bulk RNA-seq, and single-cell RNA-seq data, we investigated 13 cuproptosis-related genes in The Cancer Genome Atlas-Oral Squamous Cell Carcinoma dataset and Gene Expression Omnibus repository (GSE172577). RESULTS:ATP7A, ATP7B, and DLST were the most frequently mutated genes, with nine of our studied genes associated with overall survival. Single-cell analysis was conducted to identify cuproptosis-related tumor cells in oral squamous cell carcinoma, which revealed two distinct patterns based on the expression of cuproptosis-related genes. These patterns exhibit differences in genetic alterations and tumor immune microenvironment. Finally, we developed a cuproptosis index using a random forest algorithm based on cuproptosis pattern-related genes in which higher levels were linked to poorer prognosis. CONCLUSION:Our findings provide valuable insights into the mechanisms underlying oral squamous cell carcinoma-associated cuproptosis. 10.1111/jop.13489
Definition of a Novel Cuproptosis-Relevant lncRNA Signature for Uncovering Distinct Survival, Genomic Alterations, and Treatment Implications in Lung Adenocarcinoma. Journal of immunology research Objective:Cuproptosis is a newly discovered copper-independent cell death modality, and limited evidence suggests the critical implications in human cancers. Nonetheless, the clinical impacts of cuproptosis-relevant lncRNAs in lung adenocarcinoma (LUAD) remain largely ill-defined. The present study was aimed at defining a cuproptosis-relevant lncRNA signature for LUAD and discuss the clinical utility. Methods:We collected transcriptome expression profiling, clinical information, somatic mutation, and copy number variations from TCGA-LUAD cohort retrospectively. The genetic alterations of cuproptosis genes were systematically assessed across LUAD, and cuproptosis-relevant lncRNAs were screened for defining a LASSO prognostic model. Genomic alterations, immunological and stemness features, and therapeutic sensitivity were studied with a series of computational approaches. Results:Cuproptosis genes displayed aberrant expression and widespread genomic alterations across LUAD, potentially modulated by m6A/m5C/m1A RNA modification mechanisms. We defined a cuproptosis-relevant lncRNA signature, with a reliable efficacy in predicting clinical outcomes. High-risk subset displayed higher somatic mutations, CNVs, TMB, SNV neoantigens, aneuploidy score, CTA score, homologous recombination defects, and intratumor heterogeneity, cytolytic activity, CD8+ T effector, and antigen processing machinery, proving that this subset might benefit from immunotherapy. Increased stemness indexes and activity of oncogenic pathways might contribute to undesirable prognostic outcomes for high-risk subset. Additionally, high-risk patients generally exhibited higher response to chemotherapeutic agents (cisplatin, etc.). We also predicted several small molecule compounds (GSK461364, KX2-391, etc.) for treating this subset. Conclusion:Accordingly, this cuproptosis-relevant lncRNA signature offers an efficient approach to identify and characterize diverse prognosis, genomic alterations, and treatment outcomes in LUAD, thus potentially assisting personalized therapy. 10.1155/2022/2756611
Determination of Cuproptosis-related Subtypes, Development of a Prognostic Model, and Characterization of Tumor Microenvironment Infiltration in Acute Myeloid Leukemia. Anticancer research BACKGROUND/AIM:Acute myeloid leukemia (AML) is a severe malignancy of the bone marrow marked by an abnormal accumulation of bone marrow precursors. Cuproptosis is a recently identified type of copper-dependent regulatory cell apoptosis that relies on mitochondrial respiration. However, its participation in the development of AML remains unclear. This study analyzed the association between cuproptosis-related genes and the prognosis of AML patients. MATERIALS AND METHODS:Cases of AML were acquired from TCGA, GEO, and TARGET and the molecular subgroups characterized by genes associated with cuproptosis, besides the associated cell infiltration of the tumor microenvironment (TME) were investigated. The cuproptosis score was developed using the minor absolute shrinkage and selection operator (LASSO) tool to evaluate the cuproptosis features of a single tumor sample. RESULTS:Two distinct molecular subgroups related to cuproptosis were discovered in AML with different prognoses. The cellular infiltration assay of TME showed immunological heterogeneity between the two subtypes. The cuproptosis score predicted tumor subgroups, immunity, and prognosis. A small cuproptosis value was marked by a good prognosis, whereas the anti-PD-1/PD-L1 immunotherapy group suggested the same cuproptosis group was related to an elevated immunotherapy potency. CONCLUSION:The cuproptosis score is a biomarker important for determining the molecular subgroups, prognosis, TME cell infiltration features, and immunotherapeutic efficacy of individuals with leukemia. 10.21873/anticanres.16582
Comprehensive analysis of the cuproptosis-related model to predict prognosis and indicate tumor immune infiltration in lung adenocarcinoma. Frontiers in oncology Background:Cuproptosis is a novel form of programmed cell death termed as Cu-dependent cytotoxicity. However, the roles of cuproptosis-associated genes (CAGs) in lung adenocarcinoma (LUAD) have not been explored comprehensively. Methods:We obtained CAGs and utilized consensus molecular clustering by "non-negative matrix factorization (NMF)" to stratify LUAD patients in TCGA (N = 511), GSE13213 (N = 117), and GSE31210 (N = 226) cohorts. The ssGSEA and CIBERSORT algorithms were used to evaluate the relative infiltration levels of immune cell types in tumor microenvironment (TME). The risk score based on CAGs was calculated to predict patients' survival outcomes. Results:We identified three cuproptosis-associated clusters with different clinicopathological characteristics. We found that the cuproptosis-associated cluster with the worst survival rates exhibited a high enrichment of activated CD4/8 T cells. In addition, we found that the cuproptosis-associated risk score could be used for patients' prognosis prediction and provide new insights in immunotherapy of LUAD patients. Eventually, we constructed a nomogram-integrated cuproptosis-associated risk score with clinicopathological factors to predict overall survival in LUAD patients, with 1-, 3-, and 5-year area under curves (AUCs) being 0.771, 0.754, and 0.722, respectively, all of which were higher than those of the TNM stage. Conclusions:In this study, we uncovered the biological function of CAGs in the TME and its correlations with clinicopathological parameters and patients' prognosis in LUAD. These findings could provide new angles for immunotherapy of LUAD patients. 10.3389/fonc.2022.935672
Identification and immunological characterization of cuproptosis-related molecular clusters in ulcerative colitis. BMC gastroenterology BACKGROUND:Ulcerative colitis is one of the two main forms of inflammatory bowel disease. Cuproptosis is reported to be a novel mode of cell death. METHODS:We examined clusters of cuproptosis related genes and immune cell infiltration molecules in 86 ulcerative colitis samples from the GSE179285 dataset. We identified the differentially expressed genes according to the clustering method, and the performance of the SVM model, the random forest model, the generalized linear model, and the limit gradient enhancement model were compared, and then the optimal machine model was selected. To assess the accuracy of the learning predictions, the nomogram and the calibration curve and decision curve analyses showed that the subtypes of ulcerative colitis have been accurately predicted. RESULTS:Significant cuproptosis-related genes and immune response cells were detected between the ulcerative colitis and control groups. Two cuproptosis-associated molecular clusters were identified. Immune infiltration analysis indicated that different clusters exhibited significant heterogeneity. The immune scores for Cluster2 were elevated. Both the residual error and root mean square error of the random forest machine model had clinical significance. There was a clear correlation between the differentially expressed genes in cluster 2 and the response of immune cells. The nomogram and the calibration curve and decision curve analyses showed that the subtypes of ulcerative colitis had sufficient accuracy. CONCLUSION:We examined the complex relationship between cuproptosis and ulcerative colitis in a systematic manner. To estimate the likelihood that each subtype of cuproptosis will occur in ulcerative colitis patients and their disease outcome, we developed a promising prediction model. 10.1186/s12876-023-02831-2
Expression and potential immune involvement of cuproptosis in kidney renal clear cell carcinoma. Cancer genetics Cuproptosis is a newly identified programmed cell death pathway mediated by intracellular free copper. Cuproptosis genes were studied in this study for a better insight into the role of cuproptosis in cancers. The analysis identified kidney renal clear cell carcinoma (KIRC) as a cancer type most likely to be affected by cuproptosis. This study analyzed the multi-omic data to explore the cancer-noncancer expression pattern and potential immune involvement of the cuproptosis pathway in KIRC. This study clustered the TCGA KIRC samples based on the gene set of 12 cuproptosis genes to study the role of cuproptosis in the KIRC immune microenvironment and found the potential value of cuproptosis signature for immunotherapy prognosis. This study concluded that cuproptosis might affect KIRC and had potential application value in immune therapy. Hopefully, this study can contribute to the application of cuproptosis in the clinical therapy of KIRC. 10.1016/j.cancergen.2023.03.002
Diagnostic models and predictive drugs associated with cuproptosis hub genes in Alzheimer's disease. Frontiers in neurology Alzheimer's disease (AD) is a chronic neurodegenerative disease, and its underlying genes and treatments are unclear. Abnormalities in copper metabolism can prevent the clearance of β-amyloid peptides and promote the progression of AD pathogenesis. Therefore, the present study used a bioinformatics approach to perform an integrated analysis of the hub gene based on cuproptosis that can influence the diagnosis and treatment of AD. The gene expression profiles were obtained from the Gene Expression Omnibus database, including non-demented (ND) and AD samples. A total of 2,977 cuproptosis genes were retrieved from published articles. The seven hub genes associated with cuproptosis and AD were obtained from the differentially expressed genes and WGCNA in brain tissue from GSE33000. The GO analysis demonstrated that these genes were involved in phosphoribosyl pyrophosphate, lipid, and glucose metabolism. By stepwise regression and logistic regression analysis, we screened four of the seven cuproptosis genes to construct a diagnostic model for AD, which was validated by GES15222, GS48350, and GSE5281. In addition, immune cell infiltration of samples was investigated for correlation with these hub genes. We identified six drugs targeting these seven cuproptosis genes in DrugBank. Hence, these cuproptosis gene signatures may be an important prognostic indicator for AD and may offer new insights into treatment options. 10.3389/fneur.2022.1064639
A cuproptosis score model and prognostic score model can evaluate clinical characteristics and immune microenvironment in NSCLC. Cancer cell international BACKGROUND:Cuproptosis-related genes (CRGs) are associated with lung adenocarcinoma. However, the links between CRGs and non-small-cell lung cancer (NSCLC) are not clear. In this study, we aimed to develop two cuproptosis models and investigate their correlation with NSCLC in terms of clinical features and tumor microenvironment. METHODS:CRG expression profiles and clinical data from NSCLC and normal tissues was obtained from GEO (GSE42127) and TCGA datasets. Molecular clusters were classified into three patterns based on CRGs and cuproptosis cluster-related specific differentially expressed genes (CRDEGs). Then, two clinical models were established. First, a prognostic score model based on CRDEGs was established using univariate/multivariate Cox analysis. Then, through principal component analysis, a cuproptosis score model was established based on prognosis-related genes acquired via univariate analysis of CRDEGs. NSCLC patients were divided into high/low risk groups. RESULTS:Eighteen CRGs were acquired, all upregulated in tumor tissues, 15 of which significantly (P < 0.05). Among the three CRG clusters, cluster B had the best prognosis. In the CRDEG clusters, cluster C had the best survival. In the prognostic score model, the high-risk group had worse prognosis, higher tumor mutation load, and lower immune infiltration while in the cuproptosis score model, a high score represented better survival, lower tumor mutation load, and high-level immune infiltration. CONCLUSIONS:The cuproptosis score model and prognostic score model may be associated with NSCLC prognosis and immune microenvironment. These novel findings on the progression and immune landscape of NSCLC may facilitate the provision of more personalized immunotherapy interventions for NSCLC patients. 10.1186/s12935-024-03267-8
Cuproptosis regulator-mediated patterns associated with immune infiltration features and construction of cuproptosis-related signatures to guide immunotherapy. Frontiers in immunology Background:Liver hepatocellular carcinoma (HCC) is a prevalent cancer that lacks a sufficiently efficient approach to guide immunotherapy. Additionally, cuproptosis is a recently identified regulated cell death program that is triggered by copper ionophores. However, its possible significance in tumor immune cell infiltration is still unclear. Methods:Cuproptosis subtypes in HCC were identified using unsupervised consensus cluster analysis based on 10 cuproptosis regulators expressions, and a cuproptosis-related risk signature was generated using univariate and LASSO Cox regression and validated using the ICGC data. Moreover, the relationship between signature and tumor immune microenvironment (TME) was studied through tumor immunotherapy responsiveness, immune cell infiltration, and tumor stem cell analysis. Finally, clinical specimens were analyzed using immunohistochemistry to verify the expression of the three genes in the signature. Results:Two subtypes of cuproptosis regulation were observed in HCC, with different immune cell infiltration features. Genes expressed differentially between the two cuproptosis clusters in the TCGA were determined and used to construct a risk signature that was validated using the ICGC cohort. Greater immune and stromal cell infiltration were observed in the high-risk group and were associated with unfavorable prognosis. Elevated risk scores were linked with higher RNA stemness scores (RNAss) and tumor mutational burden (TMB), together with a greater likelihood of benefitting from immunotherapy. Conclusion:It was found that cuproptosis regulatory patterns may play important roles in the heterogeneity of immune cell infiltration. The risk signature associated with cuproptosis can assess each patient's risk score, leading to more individualized and effective immunotherapy. 10.3389/fimmu.2022.945516
Identification and immune features of cuproptosis-related molecular clusters in polycystic ovary syndrome. Scientific reports Polycystic ovary syndrome (PCOS), a common reproductive endocrine disease, has clinically heterogeneous characteristics. Recently, cuproptosis causes several diseases by killing cells. Hence, we aimed to explore cuproptosis-related molecular clusters in PCOS and construct a prediction model. Based on the GSE5090, GSE43264, GSE98421, and GSE124226 datasets, an analysis of cuproptosis regulators and immune features in PCOS was conducted. In 25 cases of PCOS, the molecular clusters of cuproptosis-related genes and the immune cell infiltration associated with PCOS were investigated. Weighted gene co-expression network analysis was used to identify differentially expressed genes within clusters. Next, we compared the performance of the random forest model, support vector machine model, generalized linear model, and eXtreme Gradient Boosting for deciding the optimum machine model. Validation of the predictive effectiveness was accomplished through nomogram, calibration curve, decision curve analysis, and using other two datasets. PCOS and non-PCOS controls differed in the dysregulation of cuproptosis-related genes and the activation of immunoreaction. Two cuproptosis-related molecular clusters associated with PCOS were identified. Significant heterogeneity was noted in immunity between the two clusters based on the analysis of immune infiltration. The immune-related pathways related to cluster-specific differentially expressed genes in Cluster1 were revealed by functional analysis. With a relatively low residual error and root mean square error and a higher area under the curve (1.000), the support vector machine model demonstrated optimal discriminative performance. An ultimate 5-gene-based support vector machine model was noted to perform satisfactorily in the other two validation datasets (area under the curve = 1.000 for both). Moreover, the nomogram, calibration curve, and decision curve analysis showed that PCOS subtypes can be accurately predicted. Our study results helped demonstrate a comprehensive understanding of the complex relationship between cuproptosis and PCOS and establish a promising prediction model for assessing the risk of cuproptosis in patients with PCOS. 10.1038/s41598-022-27326-0
Exploring the cuproptosis-related molecular clusters in the peripheral blood of patients with amyotrophic lateral sclerosis. Computers in biology and medicine BACKGROUND:Amyotrophic lateral sclerosis (ALS) is a progressive and lethal neurodegenerative disease. Several studies have suggested the involvement of cuproptosis in its pathogenesis. In this research, we intend to explore the cuproptosis-related molecular clusters in ALS and develop a novel cuproptosis-related genes prediction model. METHODS:The peripheral blood gene expression data was downloaded from the Gene Expression Omnibus (GEO) online database. Based on the GSE112681 dataset, we investigated the critical cuproptosis-related genes (CuRGs) and pathological clustering of ALS. The immune microenvironment features of the peripheral blood in ALS patients were also examined using the CIBERSORT algorithm. Cluster-specific hub genes were determined by the WGCNA. The most accurate prediction model was selected by comparing the performance of four machine learning techniques. ROC curves and two independent datasets were applied to validate the prediction accuracy. The available compounds targeting these hub genes were filtered to investigate their efficacy in treating ALS. RESULTS:We successfully determined four critical cuproptosis-related genes and two pathological clusters with various immune profiles and biological characteristics in ALS. Functional analysis showed that genes in Cluster1 were primarily enriched in pathways closely associated with immunity. The Support Vector Machine (SVM) model exhibited the best discrimination properties with a large area under the curve (AUC = 0.862). Five hub prediction genes (BAP1, SMG1, BCLAF1, DHX15, EIF4G2) were selected to establish a nomogram model, suggesting significant risk prediction potential for ALS. The accuracy of this model in predicting ALS incidence was also demonstrated through calibration curves, nomograms, and decision curve analysis. Finally, three drugs targeting BAP1 were determined through drug-gene interactions. CONCLUSION:This study elucidated the complex associations between cuproptosis and ALS and constructed a satisfactory predictive model to explore the pathological characteristics of different clusters in ALS patients. 10.1016/j.compbiomed.2023.107776
Comprehensive investigation into cuproptosis in the characterization of clinical features, molecular characteristics, and immune situations of clear cell renal cell carcinoma. Frontiers in immunology Background:Copper-induced cell death has been widely investigated in human diseases as a form of programmed cell death (PCD). The newly recognized mechanism underlying copper-induced cell death provided us creative insights into the copper-related toxicity in cells, and this form of PCD was termed cuproptosis. Methods:Through consensus clustering analysis, ccRCC patients from TCGA database were classified into different subgroups with distinct cuproptosis-based molecular patterns. Analyses of clinical significance, long-term survival, and immune features were performed on subgroups accordingly. The cuproptosis-based risk signature and nomogram were constructed and validated relying on the ccRCC cohort as well. The cuproptosis scoring system was generated to better characterize ccRCC patients. Finally, validation was conducted using ccRCC clinical samples and cell lines. Result:Patients from different subgroups displayed diverse clinicopathological features, survival outcomes, tumor microenvironment (TME) characteristics, immune-related score, and therapeutic responses. The prognostic model and cuproptosis score were well validated and proved to efficiently distinguish the high risk/score and low risk/score patients, which revealed the great predictive value. The cuproptosis score also tended out to be intimately associated with the prognosis and immune features of ccRCC patients. Additionally, the hub cuproptosis-associated gene (CAG) FDX1 presented a dysregulated expression pattern in human ccRCC samples, and it was confirmed to effectively promote the killing effects of copper ionophore elesclomol as a direct target. functional assays revealed the prominent anti-cancer role of FDX1 in ccRCC. Conclusion:Cuproptosis played an indispensable role in the regulation of TME features, tumor progression, and long-term prognosis of ccRCC. 10.3389/fimmu.2022.948042
Comprehensive analysis of cuproptosis-related long non-coding RNA signature and personalized therapeutic strategy of breast cancer patients. Frontiers in oncology Background:Breast cancer (BC) is considered to be one of the primary causes of cancer deaths in women. Cuproptosis was suggested to play an important role in tumor proliferation and tumor immune microenvironment. Therefore, an investigation was conducted to identify the relationship between cuproptosis-related long non-coding RNAs (lncRNAs) and BC prognosis. Method:Based on The Cancer Genome Atlas (TCGA), nine cuproptosis-related lncRNAs were identified by Pearson's analysis and Cox regression analysis to create a cuproptosis-related lncRNA signature. Subsequently, patients with BC were divided into high-risk and low-risk groups. The Kaplan-Meier curves and a time-dependent receiver operating characteristic (ROC) analysis were employed to elucidate the predictive capability of the signature. After that, the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was conducted by Gene Set Enrichment Analysis (GSEA), and the lncRNA-mRNA co-expression network was established by Cytoscape software. Furthermore, the ESTIMATE score was calculated, and the immune cell type component analysis was conducted. Eventually, immunotherapy response analysis was applied to identify the predictive power of cuproptosis-related lncRNAs to tumor immunotherapy response, including immune checkpoint gene expression levels, tumor mutational burden (TMB), and microsatellite instability (MSI). Results:Patients with BC in the low-risk groups showed better clinical outcomes. The KEGG pathways in the high-risk groups were mainly enriched in immune response and immune cell activation. Furthermore, the ESTIMATE scores were higher in the low-risk groups, and their immune cell infiltrations were dramatically different from those of the high-risk groups. The low-risk groups were shown to have higher infiltration levels of CD8+ T cells and TMB-high status, resulting in better response to immunotherapies. Conclusion:The findings of this study revealed that the nine-cuproptosis-related lncRNA risk score was an independent prognostic factor for BC. This signature was a potential predictor for BC immunotherapy response. What we found will provide novel insight into immunotherapeutic treatment strategies in BC. 10.3389/fonc.2022.1081089
Database Mining Detected a Cuproptosis-Related Prognostic Signature and a Related Regulatory Axis in Breast Cancer. Disease markers Background:Breast cancer is the frequent cause of disease burden related to cancer among women. It affects one in 20 women globally and up to one in eight women in high-income countries. Cuproptosis is a copper-induced modality of mitochondrial cell death that is involved in tumor proliferation and metastasis. Methods:To construct a prognostic cuproptosis-related signature, LASSO Cox regression analysis was employed. Additionally, ceRNA was developed with an aim of exploring the possible lncRNA-miRNA-mRNA regulatory axis in breast cancer. Results:The expression of FDX1, DLD, DLAT, LIAS, LIPT1, GLS MTF1, and PDHA1 was downregulated, while CDKN2A expression level was elevated in breast cancer in contrast with normal tissue. We furthermore reviewed the genetic mutation landscape of genes linked to cuproptosis in breast cancer. Prognosis analysis revealed poor OS and RFS rates in breast cancer patients with elevated levels of CDKN2A and PDHA1 and low levels of MTF1, DLD, LIPT1, and FDX1. We then constructed a cuproptosis-related signature with six genes (DKN2A, MTF1, PDHA1, DLD, LIPT1, and FDX1) for breast cancer, which predicted the OS rate with an accuracy that ranged from medium to high. Further analysis demonstrated a significant correlation between the cuproptosis-related prognostic signature and pTNM stage, MSI score, drug sensitivity, TMB score, and immune cell infiltration. Moreover, we identified the lncRNA XIST/miR-92b-3p/MTF1 regulatory axis for breast cancer. Conclusion:Multiomics approaches were used to create a cuproptosis-related signature with six genes (DKN2A, MTF1, PDHA1, DLD, LIPT1, and FDX1) for breast cancer. We discovered the lncRNA XIST/miR-92b-3p/MTF1 regulatory axis for breast cancer, which has not yet been investigated previously. 10.1155/2022/9004830
A novel cuproptosis-related lncRNA prognostic signature for predicting treatment and immune environment of head and neck squamous cell carcinoma. Mathematical biosciences and engineering : MBE Head and neck squamous cell carcinoma (HNSCC) is an urgent public health issue due to its poor prognosis and resistance to anti-cancer agents. However, the role of cuproptosis, a newly identified form cell death, in applications of HNSCC is still not a known. In this study, single-cell RNA sequencing data was used to explore cuproptosis-related gene expression in the tumour microenvironment. A prognostic model was constructed based on the cuproptosis-related lncRNA. Various methods were performed to predict the overall survival (OS) of different risk score patients and explore difference in enrichment function and pathways between the risk score patients. Finally, a series of immunogenomic landscape analyses were performed and evaluated the immune function, immune infiltration and sensitivity to chemotherapeutic agents. Cancer cell cluster expressed the essential cuproptosis-related gene. As the risk score increased of HNSCC patients, a significant decrease in survival status and time occurred for patients in the high-risk score patient. The AUC for predicting 1-, 3-, and 5-years OS were 0.679, 0.713 and 0.656, indicating that the model regarded as an independent prognostic signature in comparison with the clinical-pathological characteristics. As a results of GO, the immune function and immune infiltration of different risk score patients were assessed, revealing significant differences in T cell function and abundance of different types of T cells. Low-risk score patients are relatively insensitive to chemotherapy agents such as docetaxel and cisplatin, and easily resistant to immunotherapy. A cuproptosis-related lncRNA prognostic model was constructed to predict OS of HNSCC patients and provided the newly therapeutic strategies. 10.3934/mbe.2022564
Identification of a Novel Cuproptosis-Related Gene Signature in Eutopic Endometrium of Women with Endometriosis. Reproductive sciences (Thousand Oaks, Calif.) Endometriosis (EMs) is a life-long endocrine disorder and a common cause for female infertility and pelvic pain. The key characteristics of eutopic endometrium of EMs patients are high proliferative and migratory potentials. Cuproptosis is a recently identified copper- and-mitochondrial-dependent regulated cell death. Regretfully, its role in EMs remains unclear. In this study, Kyoto Encyclopedia of Genes and Genomes analyses of differentially expressed genes (DEGs) indicated strong activation of the PI3K-Akt-mTOR pathway and biological process analysis reported positive regulation of kinase activity. Next, we screened 11 cuproptosis-related DEGs and found all of them were downregulated in the EMs group, which indicated the suppression of cuproptosis in EMs. One key cuproptosis-related gene, PDHA1, was selected via support vector machine, random forest algorithm and lasso regularization to build a risk-scoring model, which was tested in both internal and external validations. In conclusion, the downregulation and kinase activity of PDHA1 may function with the PI3K-Akt-mTOR pathway in some way, which could suppress the cuproptosis level and account for the cancer-like pathology in EMs. 10.1007/s43032-022-01130-7
Comprehensive Analysis of Cuproptosis Genes and Identification of Cuproptosis Subtypes in Breast Cancer. Combinatorial chemistry & high throughput screening BACKGROUND:Copper-induced death (cuproptosis) is copper-dependent regulated cell death, which is different from known death mechanisms and is dependent on mitochondrial respiration. However, its effect on breast cancer (BRCA) is unclear. OBJECTIVE:The objective of this study is to explore the important clinical significance of cuproptosis genes and to provide a new idea for guiding the personalized immunotherapy strategy of BRCA patients. MATERIALS AND METHODS:We collected cuproptosis genes from published work. The gene alteration, differential expression, and prognostic value of cuproptosis genes were explored in BRCA based on TCGA database. We identified two subtypes (clusters A and B) by performing unsupervised clustering. The difference between two clusters was deeply explored, including clinical features, differential expressed genes (DEGs), pathways, and immune cell infiltration. Based on the DEGs between two clusters, a cuproptosis score was constructed and its predictive capability for overall survival of BRCA patients was validated. RESULTS AND DISCUSSION:Patients with high cuproptosis score have worse survival status, with an increased infiltration level of most immune cells. Further analysis suggested that BRCA patients with high cuproptosis score may be sensitive to immune checkpoint inhibitor (ICI) treatment. CONCLUSION:Our findings may improve our understanding of cuproptosis in BRCA and may distinguish patients suitable for ICI treatment. 10.2174/1386207326666230120112904
Comprehensive analysis of cuproptosis-related lncRNAs model in tumor immune microenvironment and prognostic value of cervical cancer. Frontiers in pharmacology Cervical cancer (CC) is the fourth leading gynecological malignancy in females worldwide. Cuproptosis, a form of cell death induced by copper, elicits a novel therapeutic strategy in anticancer therapy. Nonetheless, the effects of cuproptosis-related lncRNAs in CC remain unclear. Therefore, we aim to investigate cuproptosis-related lncRNAs, develop a risk model for prognostic prediction, and elucidate the immunological profile of CC. Transcription profiles and clinical follow-up data of CC were retrieved from The Cancer Genome Atlas (TCGA) database. Afterward, the risk model was built by distinguishing prognostic cuproptosis-related lncRNAs using the least absolute shrinkage and selection operator (LASSO) Cox regression. The correctness of the risk model was validated, and a nomogram was established followed by tumor immune microenvironment analysis. Tumor immune dysfunction and exclusion (TIDE) scores were used to assess immunotherapy response, and anticancer pharmaceutical half-maximal inhibitory concentration (IC50) prediction was performed for potential chemotherapy medicines. Finally, through coexpression analysis, 199 cuproptosis-related lncRNAs were collected. A unique risk model was generated using 6 selected prognostic cuproptosis-related lncRNAs. The risk score performed a reliable independent prediction of CC survival with higher diagnostic effectiveness compared to generic clinical characteristics. Immunological cell infiltration investigation indicated that the risk model was substantially linked with CC patients' immunology, and the low-risk patients had lower TIDE scores and increased checkpoint expression, suggesting a stronger immunotherapy response. Besides, the high-risk group exhibited distinct sensitivity to anticancer medications. The immune-related progression was connected to the differentially expressed genes (DEGs) between risk groups. Generally, the risk model comprised 6 cuproptosis-related lncRNAs that may help predict CC patients' overall survival, indicate immunocyte infiltration, and identify individualized treatment. 10.3389/fphar.2022.1065701
A cuproptosis-associated long non-coding RNA signature for the prognosis and immunotherapy of lung squamous cell carcinoma. Biomolecules & biomedicine Cuproptosis, a copper-induced mechanism of mitochondrial-related cell death, has been implicated as a breakthrough in the treatment of cancer and has become a new treatment strategy. Furthermore, long non-coding RNA (lncRNA) can change the biological activities of tumor cells. Worldwide, lung squamous cell carcinoma (LUSC) is among the most common annoying tumors. LncRNAs related to cuproptosis are not researched at LUSC. Our research intends to develop a signature on the basis of cuproptosis-associated lncRNAs, which can predict LUSC prognosis and investigate LUSC immunological features. The TCGA database was used to retrieve LUSC transcriptome, clinical, and gene mutation data. For statistical analysis, we utilized the R program. We created a signature consisting of three cuproptosis-related lncRNAs in this investigation (including AC002467.1, LINC01740, and LINC02345). Survival analyses and Receiver Operating Characteristic curves demonstrated that this signature possessed powerful predictive capability. The signature's ability to predict was confirmed by a Receiver Operating Characteristic curve and principal component analysis. Notably, the patient with a high-risk score and a high tumor mutation burden level had a lower survival time. Furthermore, the tumor immune dysfunction and exclusion analysis showed that these individuals with low-risk scores may benefit from immunotherapy. The signature constructed by three cuproptosis-associated lncRNAs may be prognostic markers of LUSC. It contributes to immunotherapy and offers LUSC's therapy a new treatment direction. 10.17305/bb.2022.8481
Identification and integration analysis of a novel prognostic signature associated with cuproptosis-related ferroptosis genes and relevant lncRNA regulatory axis in lung adenocarcinoma. Aging Lung adenocarcinoma (LUAD) is a highly prevalent malignancy worldwide, and its clinical prognosis assessment and treatment is a major research direction. Both ferroptosis and cuproptosis are novel forms of cell death and are considered to be important factors involved in cancer progression. To further understand the correlation between the cuproptosis-related ferroptosis genes (CRFGs) and the prognosis of LUAD, we explore the molecular mechanisms related to the development of the disease. We constructed a prognostic signature containing 13 CRFGs, which, after grouping based on risk score, revealed that the LUAD high-risk group exhibited poor prognosis. Nomogram confirmed that it could be an independent risk factor for LUAD, and ROC curves and DCA validated the validity of the model. Further analysis showed that the three prognostic biomarkers (LIFR, CAV1, TFAP2A) were significantly correlated with immunization. Meanwhile, we found that a LINC00324/miR-200c-3p/TFAP2A regulatory axis could be involved in the progression of LUAD. In conclusion, our report reveals that CRFGs are well correlated with LUAD and provide new ideas for the construction of clinical prognostic tools, immunotherapy, and targeted therapy for LUAD. 10.18632/aging.204561
Comprehensive analysis of cuproptosis genes and cuproptosis-related genes as prognosis factors in esophageal squamous cell carcinoma. Genomics Esophageal squamous cell carcinoma (ESCC) is a common invasive and pernicious cancer with a low five-year survival rate. To identify potential therapeutic targets, we first investigated the characteristics of cuproptosis genes (CUGs) in ESCC. The expression patterns of 10 CUGs (FDX1, LIPT1, LIAS, DLAT, DLD, PDHA1, PDHB, GLS, MTF1, and CDKN2A) were analyzed to identify ESCC-relevant targets. Weighted correlation network analysis (WGCNA) was performed to obtain CUG-related genes (CRGs). A total of seven differentially expressed genes were identified (FDX1, DLAT, LIAS, PDHB, MTF1, GLS, and CDKN2A). DLAT was upregulated in stage III, and LIPT1 was upregulated in N0 + N1 cancers. The high expression of CDKN2A, and PDHA1, was related to better overall survival, whereas the low expression of LIAS was related to better clinical outcomes. WGCNA was performed to get CUG-related genes (CRGs) and showed three key modules that related to FDX1, DLAT, and LIPT1. Moreover, CRGs (BTLA, CT47A1, and PRRX1) were selected to construct a risk score model in order to predict the survival and prognosis of patients with ESCC. Additionally, the cuproptosis score based on CUGs and a nomogram constructed based on it helped accurately predict the prognosis of patients with ESCC; thus, maybe it can be used for the clinical diagnosis of ESCC. The results also showed that milciclib might inhibit the proliferation and migration of KYSE150 and KYSE510 cells by targeting CDKN2A. In conclusion, the abovementioned CUGs and CRGs play a crucial role in tumorigenesis and cancer progression in ESCC, indicating their potential as therapeutic targets. 10.1016/j.ygeno.2023.110732
The cuproptosis related genes signature predicts the prognosis and correlates with the immune status of clear cell renal cell carcinoma. Frontiers in genetics Clear cell renal cell carcinoma (CCRCC) has a high incidence and poor prognosis. Cuproptosis, an independent pattern of cell death associated with copper, plays an important role in cancer proliferation and metastasis. The role of cuproptosis-related genes (CRGs) in CCRCC is unclear. Transcriptome and clinical information for CCRCC were downloaded from The Cancer Genome Atlas (TCGA) database. After dividing the training and testing cohort, a 4-CRGs risk signature (, , , ) was identified in the training cohort using Least absolute shrinkage and selection operator (LASSO) and Cox regression analysis. The effect of the 4-CRGs risk signature on prognosis was assessed using Kaplan-Meier (KM) curves and time-dependent receiver operating characteristic (ROC) curves and verified using the testing cohort. For different risk groups, the immune statue was assessed using the CIBERSORT algorithm, the ssGSEA method and immune checkpoint expression data. Finally, a competitive endogenous RNA (ceRNA) network was constructed using miRTarbase and starBase databases to identify molecules that may have a regulatory relationship with CRCCC. There were significant changes in the overall survival (OS), immune microenvironment, immune function, and checkpoint gene expression among the different risk groups. A ceRNA network consisting of one mRNA, two miRNAs, and 12 lncRNAs was constructed. The 4-CRGs risk signature provides a new method to predict the prognosis of patients with CCRCC and the effect of immunotherapy. We propose a new cuproptosis-associated ceRNA network that can help to further explore the molecular mechanisms of CCRCC. 10.3389/fgene.2022.1061382
A cuproptosis-related gene expression signature predicting clinical prognosis and immune responses in intrahepatic cholangiocarcinoma detected by single-cell RNA sequence analysis. Cancer cell international BACKGROUND:Cholangiocarcinoma represents a malignant neoplasm originating from the hepatobiliary tree, with a subset of tumors developing inside the liver. Intrahepatic cholangiocarcinomas (ICC) commonly exhibit an asymptomatic presentation, rendering both diagnosis and treatment challenging. Cuproptosis, an emerging regulated cell death pathway induced by copper ions, has garnered attention recently. As cancer cells show altered copper metabolism and comparatively higher copper needs, cuproptosis may play a role in the development of ICC. However, studies investigating this possibility are currently lacking. METHODS:Single-cell and bulk RNA sequence data were analyzed, and correlations were established between the expression of cuproptosis-related molecules and ICC patient survival. Genes with predicting survival were used to create a CUPT score using Cox and LASSO regression and tumor mutation burden (TMB) analysis. The CIBERSORT software was employed to characterize immune cell infiltration within the tumors. Furthermore, immune infiltration prediction, biological function enrichment, and drug sensitivity analyses were conducted to explore the potential implications of the cuproptosis-related signature. The effects of silencing solute carrier family 39 member 4 gene (SLC39A4) expression using siRNA were investigated using assays measuring cell proliferation, colony formation, and cell migration. Key genes of cuproptosis were detected by western blotting. RESULTS:The developed CUPT score divided patients into high and low CUPT score groups. Those with a low score had significantly better prognosis and longer survival. In contrast, high CUPT scores were associated with worse clinical outcomes and significantly higher TMB. Comparisons of the two groups also indicated differences in the immune infiltrate present in the tumors. Finally, we were able to identify 95 drugs potentially affecting the cuproptosis pathway. Some of these might be effective in the treatment of ICC. The in vitro experiments revealed that suppressing the expression of SLC39A4 in ICC cell lines resulted in reduced cell proliferation, colony formation, and cell migration. It also led to an increase in cell death and the upregulation of key genes associated with cuproptosis, namely ferredoxin 1 (FDX1) and dihydrolipoyl transacetylase (DLAT). These findings strongly suggest that this cuproptosis-associated molecule may play a pivotal role in the development and metastasis of ICC. CONCLUSIONS:Changes in the expression of a cuproptosis-related gene signature can predict the clinical prognosis of ICC with considerable accuracy. This supports the notion that cuproptosis influences the diversity and complexity of the immune microenvironment, mutational landscape, and biological behavior of ICC. Understanding this pathway better may hold promise for the development of innovative strategies in the management of this disease. 10.1186/s12935-024-03251-2
Molecular subtypes based on cuproptosis regulators and immune infiltration in kidney renal clear cell carcinoma. Frontiers in genetics Copper toxicity involves the destruction of mitochondrial metabolic enzymes, triggering an unusual mechanism of cell death called cuproptosis, which proposes a novel approach using copper toxicity to treat cancer. However, the biological function of cuproptosis has not been fully elucidated in kidney renal clear cell carcinoma (KIRC). Using the expression profile of 13 cuproptosis regulators, we first identified two molecular subtypes related to cuproptosis defined as "hot tumor" and "cold tumor", having different levels of biological function, clinical prognosis, and immune cell infiltration. We obtained three gene clusters using the differentially expressed genes between the two cuproptosis-related subtypes, which were associated with different molecular activities and clinical characteristics. Next, we developed and validated a cuproptosis prognostic model that included two genes (FDX1 and DBT). The calculated risk score could divide patients into high- and low-risk groups. The high-risk group had a poorer prognosis, lower level of immune infiltration, higher frequency of gene alterations, and greater levels of FDX1 methylation and limited DBT methylation. The risk score was also an independent predictive factor for overall survival in KIRC. The established nomogram calculating the risk score achieved a high predictive ability for the prognosis of individual patients (area under the curve: 0.860). We then identified small molecular inhibitors as potential treatments and analyzed the sensitivity to chemotherapy of the signature genes. Tumor immune dysfunction and exclusion (TIDE) showed that the high-risk group had a higher level of TIDE, exclusion and dysfunction that was lower than the low-risk group, while the microsatellite instability of the high-risk group was significantly lower. The results of two independent immunotherapy datasets indicated that cuproptosis regulators could influence the response and efficacy of immunotherapy in KIRC. Our study provides new insights for individualized and comprehensive therapy of KIRC. 10.3389/fgene.2022.983445
Revealing prognostic and tumor microenvironment characteristics of cuproptosis in bladder cancer by genomic analysis. Frontiers in genetics Bladder cancer (BLCA) is the most common malignant tumor in the urinary system, while the prognosis of muscle-invasive bladder cancer (MIBC) is poor. Cuproptosis might be a promising therapeutic approach to trigger tumor cell death. This study aimed to figure out the role of cuproptosis in BLCA and constructed a new cuproptosis scoring system to guide clinical diagnosis and individualize treatments. Consensus clustering was used to classify 490 patients with BLCA from TCGA and GEO cohorts. Survival outcomes and functional enrichment analyses were performed between the different subtypes. The cuproptosis scoring system was constructed by LASSO-Cox analysis. ESTIMATE, CIBERSORT, and ssGSEA were used to investigate the tumor microenvironment (TME). Drug sensitivity was evaluated with pRRophetic. An immunotherapy cohort was used to investigate the treatment response. The cuproptosis scoring system was verified in our own cohort with quantitative real-time PCR. An overview of 12 cuproptosis genes (CuGs) in the TCGA database was depicted. Based on the mRNA expression profiles of CuGs, patients were classified into two cuproptosis molecular patterns. Based on the differential genes between the two cuproptosis patterns, the patients were classified into two cuproptosis gene clusters. There were distinct survival outcomes, signaling pathways, and TME between the two subtypes. A 7-gene cuproptosis scoring system was constructed. Patients with high cuproptosis scores showed worse OS and more immunosuppressing TME than those with low cuproptosis scores. The two cuproptosis score groups had distinct mutation profiles. Patients with high cuproptosis scores tended to be sensitive to chemotherapy drugs, but insensitive to immune checkpoint inhibitors (ICIs) treatment. This study depicted the landscape of cuproptosis in BLCA. We constructed a cuproptosis scoring system to predict the prognosis of BLCA patients. There were significant differences in survival outcomes, TME, mutation profiles, and drug sensitivities in high and low cuproptosis score patients. The cuproptosis scoring system could help oncologists comprehensively understand the tumor characteristic of BLCA and make individualized treatment strategies. 10.3389/fgene.2022.997573
Pan-cancer analysis of cuproptosis regulation patterns and identification of mTOR-target responder in clear cell renal cell carcinoma. Biology direct BACKGROUND:The mechanism of cuproptosis, a novel copper-induced cell death by regulating tricarboxylic acid cycle (TCA)-related genes, has been reported to regulate oxidative phosphorylation system (OXPHOS) in cancers and can be regarded as potential therapeutic strategies in cancer; however, the characteristics of cuproptosis in pan-cancer have not been elucidated. METHODS:The multi-omics data of The Cancer Genome Atlas were used to evaluate the cuproptosis-associated characteristics across 32 tumor types. A cuproptosis enrichment score (CEScore) was established using a single sample gene enrichment analysis (ssGSEA) in pan-cancer. Spearman correlation analysis was used to identify pathway most associated with CEScore. Lasso-Cox regression was used to screen prognostic genes associated with OXPHOS and further construct a cuproptosis-related prognostic model in clear cell renal cell carcinoma (ccRCC). RESULTS:We revealed that most cuproptosis-related genes (CRGs) were differentially expressed between tumors and normal tissues, and somatic copy number alterations contributed to their aberrant expression. We established a CEScore index to indicate cuproptosis status which was associated with prognosis in most cancers. The CEScore was negatively correlated with OXPHOS and significantly featured prognosis in ccRCC. The ccRCC patients with high-risk scores show worse survival outcomes and bad clinical benefits of Everolimus (mTOR inhibitor). CONCLUSIONS:Our findings indicate the importance of abnormal CRGs expression in cancers. In addition, identified several prognostic CRGs as potential markers for prognostic distinction and drug response in the specific tumor. These results accelerate the understanding of copper-induced death in tumor progression and provide cuproptosis-associated novel therapeutic strategies. 10.1186/s13062-022-00340-y
The role of a cuproptosis-related prognostic signature in colon cancer tumor microenvironment and immune responses. Frontiers in genetics Colon adenocarcinoma (COAD) is a common malignant tumor of the digestive tract with poor clinical outcomes. Cuproptosis is a novel cell death mechanism and linked to mitochondrial respiration. However, the role of cuproptosis in colon cancer tumor microenvironment (TME) and immune responses remains unknown. We conducted difference analysis to identify the differential expressed cuproptosis-related genes (CRGs). According to the CRGs, the TCGA-COAD samples were categorized using consensus clustering. The LASSO regression analysis was utilized to develop the cuproptosis-related signature. We then verified the model reliability by Kaplan-Meier, PCA, and ROC analysis. The GES39582 cohort served as the validation set. GO and KEGG functional analyses were conducted to investigate the underlying mechanism. We compared the infiltration levels of immune cells, the expression levels of immune checkpoints, and microsatellite instability (MSI) status between the high- and low-risk groups. Additionally, the relationships between the risk signature and immune cells and cancer stem cell (CSC) were analyzed. Finally, we identified 9 differentially expressed CRGs in COAD. According to the expression of CRGs, the TCGA-COAD samples were separated into two clusters. The 11-gene signature was established by LASSO, and it had excellent predictive power for COAD prognosis. Besides, we used the GSE39582 cohort to validate the prognostic value of the model. GO and KEGG results demonstrated that the survival differences between two risk groups was mainly linked to the extracellular matrix (ECM). Further immune characterization analysis showed the significant differences in the immune cell infiltration and immune responses between two risk groups. Overall, the novel cuproptosis-related signature was able to accurately predict COAD prognosis and played important roles in COAD tumor microenvironment and immune responses. 10.3389/fgene.2022.928105
Comprehensive exploration of the involvement of cuproptosis in tumorigenesis and progression of neuroblastoma. BMC genomics BACKGROUND:Copper-induced cell death, or "cuproptosis," as an apoptotic process, has recently received much attention in human diseases. Recent studies on cuproptosis have provided novel insights into the pathogenesis of various diseases, especially cancers. However, the association between neuroblastoma (NB) and cuproptosis in terms of their clinical outcomes, tumorigenesis, and treatment response remains unclear. METHODS:To determine the role of cuproptosis in NB tumorigenesis and progression, this study employed a systematic technique to explore the characteristic patterns of 10 key cuproptosis-related genes (CUGs) in NB. Consensus clustering analysis of the TARGET and GEO databases divided the NB patients into two subgroups that showed different clinicopathological attributes, molecular patterns, survival outcomes, disease-associated pathways, tumor immune microenvironment (TIME) features, and treatment responses. Moreover, a cuproptosis scoring scheme was established, which divided the patients with NB into two groups with high scores and low scores as per the median score. Furthermore, this research developed a nomogram and risk signature on the basis of this cuproptosis score to better elucidate its function in predicting NB prognosis. In vitro experiments were carried out using Transwell Assay, HLECs tube formation assay, Colony formation assay, Western Blotting Assay, Immunohistochemical (IHC) Staining, Immunofluorescence (IF) Staining and Flow Cytometry Analysis. RESULTS:The results demonstrated that the established cuproptosis score and prediction model could effectively distinguish between the individuals in low and high-risk groups and had a high predictive value. Lastly, bioinformatics analysis and in vitro experiments enabled the identification of PDHA1, a key CUG, which was involved in both DNA replication-related pathways and the cell cycle. It was also associated with tumorigenesis and progression of NB. CONCLUSION:Cuproptosis, especially PDHA1, play a crucial role in the TIME characteristics, tumor progression, and long-term prognosis of NB. The patterns of cuproptosis assessed in this research may improve the understanding of the overall concept of NB tumorigenesis, thus facilitating the development of more effective therapeutic interventions. 10.1186/s12864-023-09699-2
Cuproptosis facilitates immune activation but promotes immune escape, and a machine learning-based cuproptosis-related signature is identified for predicting prognosis and immunotherapy response of gliomas. CNS neuroscience & therapeutics AIMS:Cell death, except for cuproptosis, in gliomas has been extensively studied, providing novel targets for immunotherapy by reshaping the tumor immune microenvironment through multiple mechanisms. This study aimed to explore the effect of cuproptosis on the immune microenvironment and its predictive power in prognosis and immunotherapy response. METHODS:Eight glioma cohorts were included in this study. We employed the unsupervised clustering algorithm to identify novel cuproptosis clusters and described their immune microenvironmental characteristics, mutation landscape, and altered signaling pathways. We verified the correlation among FDX1, SLC31A1, and macrophage infiltration in 56 glioma tissues. Next, based on multicenter cohorts and 10 machine learning algorithms, we constructed an artificial intelligence-driven cuproptosis-related signature named CuproScore. RESULTS:Our findings suggested that glioma patients with high levels of cuproptosis had a worse prognosis owing to immunosuppression caused by unique immune escape mechanisms. Meanwhile, we experimentally validated the positive association between cuproptosis and macrophages and its tumor-promoting mechanism in vitro. Furthermore, our CuproScore exhibited powerful and robust prognostic predictive ability. It was also capable of predicting response to immunotherapy and chemotherapy drug sensitivity. CONCLUSIONS:Cuproptosis facilitates immune activation but promotes immune escape. The CuproScore could predict prognosis and immunotherapy response in gliomas. 10.1111/cns.14380
Effective prognostic risk model with cuproptosis-related genes in laryngeal cancer. Brazilian journal of otorhinolaryngology OBJECTIVE:Laryngeal cancer, characterized by high recurrence rates and a lack of effective biomarkers, has been associated with cuproptosis, a regulated cell death process linked to cancer progression. In this study, we aimed to explore the roles of cuproptosis-related genes in laryngeal cancer and their potential as prognostic markers and therapeutic targets. METHODS:We collected comprehensive data from The Cancer Genome Atlas and Gene Expression Omnibus databases, including gene expression profiles and clinical data of laryngeal cancer patients. Using clustering and gene analysis, we identified cuproptosis-related genes with prognostic significance. A risk model was constructed based on these genes, categorizing patients into high- and low-risk groups for outcome comparison. Univariate and multivariate analyses were conducted to identify independent prognostic factors, which were then incorporated into a nomogram. Gene Set Enrichment Analysis was employed to explore pathways distinguishing high- and low-risk groups. RESULTS:Our risk model, based on four genes, including transmembrane 2, dishevelled binding antagonist of β-catenin 1, stathmin 2, and G protein-coupled receptor 173, revealed significant differences in patient outcomes between high- and low-risk groups. Independent prognostic factors were identified and integrated into a nomogram, providing a valuable tool for prognostic prediction. Gene Set Enrichment Analysis uncovered up-regulated pathways specifically associated with high-risk patient samples. CONCLUSION:This study highlights the potential of cuproptosis-related genes as valuable prognostic markers and promising therapeutic targets in the context of laryngeal cancer. This research sheds light on new avenues for understanding and managing this challenging disease. LEVEL OF EVIDENCE:Level 4. 10.1016/j.bjorl.2023.101384
A novel cuproptosis-related gene signature for overall survival prediction in patients with hepatocellular carcinoma. Heliyon Prognosis prediction is difficult in hepatocellular carcinoma (HCC) due to high heterogeneity and complex etiology. It has recently been discovered that cuproptosis is a type of programmed cell death. However, its significance for HCC is still unclear. We analyzed mRNA expression profiles and clinical information from public databases to determine whether cuproptosis-related genes are associated with improved prognoses for HCC patients. The training cohort consisted of HCC patients from The Cancer Genome Atlas (TCGA), and the validation cohort relied on the International Cancer Genome Consortium (ICGC) database. We constructed a signature containing four genes using the least absolute shrinkage and selection operator (LASSO) COX regression model for calculating risk scores. Two risk groups were formed based on the median score. A significant improvement in survival was observed in the low-risk group compared to the high-risk. The multivariate Cox regression analysis showed that the risk score was an independent predictor of overall survival (OS). Further confirmation of the predictive accuracy of this signature is provided by receiver operating characteristic (ROC) analysis. Functional analysis revealed differences in immune status between the two risk groups. All the results described above were confirmed in the validation cohort. Therefore, a novel cuproptosis-related signature has the potential as a prognostic biomarker for HCC patients. Drugs developed to target cuproptosis-related genes may open up new pathways for treating HCC. 10.1016/j.heliyon.2022.e11768
The LncRNA signature associated with cuproptosis as a novel biomarker of prognosis in immunotherapy and drug screening for clear cell renal cell carcinoma. Frontiers in genetics Cuproptosis is a new form of cell death, the second form of metal ion-induced cell death defined after ferroptosis. Recently, cuproptosis has been suggested to be associated with tumorigenesis. However, the relationship between cuproptosis and patient prognosis in clear cell renal cell carcinoma (ccRCC) in the context of immunotherapy remains unknown. The aim of this study was to investigate the correlation between cuproptosis-related long non-coding RNA (lncRNA) and ccRCC in terms of immunity as well as prognosis. Clinical information on lncRNAs associated with differences in cuproptosis genes in ccRCC and normal tissues was collected from The Cancer Genome Atlas (TCGA) dataset. Univariate Cox regression was used to screen lncRNAs. A total of 11 lncRNAs closely associated with cuproptosis were further screened and established using the least absolute shrinkage and selection operator (LASSO) algorithm and multivariate Cox regression, and the samples were randomly divided into training and test groups. A risk prognostic model was constructed using the training group, and the model was validated using the test group. We investigated the predictive ability of the prognostic risk model in terms of clinical prognosis, tumor mutation, immune escape, immunotherapy, tumor microenvironment, immune infiltration levels, and tumor drug treatment of ccRCC. Using the median risk score, patients were divided into low and high-risk groups. Kaplan-Meier curves showed that the overall survival (OS) of patients in the high-risk group was significantly worse than low-risk group ( < 0.001). Receiver operating characteristic (ROC) curves further validated the reliability of our model. The model consistently and accurately predicted prognosis at 1, 3, and 5 years, with an AUC above 0.7. Tumor cell genes generally precede morphological abnormalities; therefore, the model we constructed can effectively compensate for the traditional method of evaluating the prognosis of patients with renal cancer, and our model was also clinically meaningful in predicting ccRCC staging. In addition, lower model risk scores determined by mutational load indicated a good chance of survival. The high-risk group had greater recruitment of immune cells, while the anti-immune checkpoint immunotherapy was less efficacious overall than that of the low-risk group. Tumor and immune-related pathways were enriched, and anti-tumor agents were selected to improve the survival of ccRCC. This prognostic risk model is based on the levels of cuproptosis-associated lncRNAs and provides a new perspective in the clinical assessment and precise treatment of ccRCC. 10.3389/fgene.2023.1039813
Identification and validation of a novel cuproptosis-related lncRNA signature for prognosis and immunotherapy of head and neck squamous cell carcinoma. Frontiers in cell and developmental biology Head and neck squamous cell carcinoma (HNSCC) is a highly prevalent and heterogeneous malignancy with a dismal overall survival rate. Nevertheless, the effective biomarkers remain ambiguous and merit further investigation. Cuproptosis is a novel defined pathway of programmed cell death that contributes to the progression of cancers. Meanwhile, long non-coding RNAs (lncRNAs) play a crucial role in the biological process of tumors. Nevertheless, the prognostic value of cuproptosis-related lncRNAs in HNSCC is still obscure. This study aimed to develop a new cuproptosis-related lncRNAs (CRLs) signature to estimate survival and tumor immunity in patients with HNSCC. Herein, 620 cuproptosis-related lncRNAs were identified from The Cancer Genome Atlas database through the co-expression method. To construct a risk model and validate the accuracy of the results, the samples were divided into two cohorts randomly and equally. Subsequently, a prognostic model based on five CRLs was constructed by the Cox regression analysis with the least absolute shrinkage and selection operator (LASSO) algorithm. In addition, the prognostic potential of the five-CRL signature was verified Cox regression, survival analysis, the receiver operating characteristic (ROC) curve, nomogram, and clinicopathologic characteristics correlation analysis. Furthermore, we explored the associations between the signature risk score (RS) and immune landscape, somatic gene mutation, and drug sensitivity. Finally, we gathered six clinical samples and different HNSCC cell lines to validate our bioinformatics results. Overall, the proposed novel five-CRL signature can predict prognosis and assess the efficacy of immunotherapy and targeted therapies to prolong the survival of patients with HNSCC. 10.3389/fcell.2022.968590
Identifying a novel cuproptosis-related necroptosis gene subtype-related signature for predicting the prognosis, tumor microenvironment, and immunotherapy of hepatocellular carcinoma. Frontiers in molecular biosciences : Cuproptosis and necroptosis represent two distinct programmed cell death modalities implicated in neoplastic progression; however, the role of combining cuproptosis and necroptosis in hepatocellular carcinoma (HCC) remains to be elucidated. : A total of 29 cuproptosis-related necroptosis genes (CRNGs) were identified, followed by an extensive analysis of their mutational characteristics, expression patterns, prognostic implications, and associations with the tumor microenvironment (TME). Subsequently, a CRNG subtype-related signature was developed, and its value of prognostic prediction, TME, and therapeutic responses in HCC were thoroughly investigated. Last, quantitative real-time PCR and Western blotting were employed for investigating the signature gene expression in 15 paired clinical tissue samples. : Two distinct CRNG subtypes were discerned, demonstrating associations between CRNG expression patterns, clinicopathological attributes, prognosis, and the TME. A CRNG subtype-related prognostic signature, subjected to external validation, was constructed, serving as an independent prognostic factor for HCC patients, indicating poor prognosis for high-risk individuals. Concurrently, the signature's correlations with an immune-suppressive TME, mutational features, stemness properties, immune checkpoint genes, chemoresistance-associated genes, and drug sensitivity were observed, signifying its utility in predicting treatment responses. Subsequently, highly accurate and clinically convenient nomograms were developed, and the signature genes were validated via quantitative real-time PCR and Western blotting, further substantiating the stability and dependability of the CRNG subtype-related prognostic signature. : Overall, this investigation presented an extensive panorama of CRNGs and developed the CRNG subtype-related prognostic signature, which holds potential for implementation in personalized treatment strategies and prognostic forecasting for HCC patients. 10.3389/fmolb.2023.1165243
Identification of cuproptosis-associated IncRNAs signature and establishment of a novel nomogram for prognosis of stomach adenocarcinoma. Frontiers in genetics Stomach adenocarcinoma (STAD) is one of the common cancers globally. Cuproptosis is a newly identified cell death pattern. The role of cuproptosis-associated lncRNAs in STAD is unknown. STAD patient data from TCGA were used to identify prognostic lncRNAs by Cox regression and LASSO. A nomogram was constructed to predict patient survival. The biological profiles were evaluated through GO and KEGG. We identified 298 cuproptosis-related lncRNAs and 13 survival-related lncRNAs. Patients could be categorized into either high risk group or low risk group with 9-lncRNA risk model with significantly different survival time ( < 0.001). ROC curve and nomogram confirmed the 9-lncRNA risk mode had good prediction capability. Patients in the lower risk score had high gene mutation burden. We also found that patients in the two groups might respond differently to immune checkpoint inhibitors and some anti-tumor compounds. The nomogram with 9-lncRNA may help guide treatment of STAD. Future clinical studies are necessary to verify the nomogram. 10.3389/fgene.2022.982888
Construction and validation of a novel cuproptosis-mitochondrion prognostic model related with tumor immunity in osteosarcoma. PloS one BACKGROUND:The purpose of this study was to develop a new prognostic model for osteosarcoma based on cuproptosis-mitochondrion genes. MATERIALS AND METHODS:The data of osteosarcoma were obtained from TARGET database. By using Cox regression and LASSO regression analysis, a novel risk score was constructed based on cuproptosis-mitochondrion genes. Kaplan-Meier, ROC curve and independent prognostic analyses were performed to validate the risk score in GSE21257 dataset. Then, a predictive nomogram was constructed and further validated by calibration plot, C-index and ROC curve. Based on the risk score, all patients were divided into high-risk and low-risk group. GO and KEGG enrichment, immune correlation and drug sensitivity analyses were performed between groups. Real-time quantitative PCR verified the expression of cuproptosis-mitochondrion prognostic model genes in osteosarcoma. And we explored the function of FDX1 in osteosarcoma by western blotting, CCK8, colony formation assay, wound healing assay and transwell assays. RESULTS:A total of six cuproptosis-mitochondrion genes (FDX1, COX11, MFN2, TOMM20, NDUFB9 and ATP6V1E1) were identified. A novel risk score and associated prognostic nomogram were constructed with high clinical application value. Strong differences in function enrichment and tumor immune microenvironment were shown between groups. Besides, the correlation of cuproptosis-mitochondrion genes and drug sensitivity were revealed to search for potential therapeutic target. The expression of FDX1, COX11, MFN2, TOMM20 and NDUFB9 at mRNA level was elevated in osteosarcoma cells compared with normal osteoblast hFOB1.19. The mRNA expression level of ATP6V1E1 was decreased in osteosarcoma. Compared with hFOB1.19, western blotting revealed that the expression of FDX1 was significantly elevated in osteosarcoma cells. Functional experiments indicated that FDX1 mainly promoted the migration of osteosarcoma rather than proliferation. CONCLUSIONS:We developed a novel prognostic model of osteosarcoma based on cuproptosis-mitochondrion genes, which provided great guidance in survival prediction and individualized treatment decision making for patients with osteosarcoma. 10.1371/journal.pone.0288180
Cuproptosis-Related Gene Signature Contributes to Prognostic Prediction and Immunosuppression in Multiple Myeloma. Molecular biotechnology Cuproptosis is a type of programmed cell death triggered by accumulation of intracellular copper which was considered closely related to tumor progression. The study of cuproptosis in multiple myeloma (MM) is however limited. To determine the prognostic significance of cuproptosis-related gene signature in MM, we interrogated gene expression and overall survival with other available clinical variables from public datasets. Four cuproptosis-related genes were included to establish a prognostic survival model by least absolute shrinkage and selection operator (LASSO) Cox regression analysis, which showed a good performance on prognosis prediction in both training and validation cohorts. Patients with higher cuproptosis-related risk score (CRRS) exhibited worse prognosis compared with lower risk score. Survival prediction capacity and clinical benefit were elevated after integrating CRRS to existing prognostic stratification system (International Staging System, ISS or Revised International Staging System, RISS) both on 3-year and 5-year survival. Based on CRRS groups, functional enrichment analysis and immune infiltration in bone marrow microenvironment revealed correlation between CRRS and immunosuppression. In conclusion, our study found that cuproptosis-related gene signature is an independent poor prognostic factor and functions negatively on immune microenvironment, which provides another perspective on prognosis assessment and immunotherapy strategy in MM. 10.1007/s12033-023-00770-7
Comprehensive analysis of cuproptosis-related lncRNAs to predict prognosis and immune infiltration characteristics in colorectal cancer. Frontiers in genetics Cuproptosis is a novel form of cell death discovered in recent. A great quantity of researches has confirmed the close relationships and crucial roles between long non-coding RNAs (lncRNAs) with the progression of colorectal cancer (CRC). However, the relationship between cuproptosis and lncRNAs remains unclear in CRC. 1,111 co-expressed lncRNAs with 16 cuproptosis regulators were retrieved from CRC samples of The Cancer Genome Atlas (TCGA) database. Through univariate Cox and least absolute shrinkage and selection operator regression analysis, a prognosis model was constructed with 15 lncRNAs. The Kaplan-Meier, receiver operating characteristic curve, C-index and principal component analysis identified the prognostic power. Furthermore, a cuproptosis-related cluster was generated based on the 15 lncRNAs by unsupervised methods. The correlations between the cuproptosis-related signatures with immune cell infiltration and anti-tumor therapy were explored by multiple algorithms. A risk score and nomogram with great prediction ability were constructed for CRC prognosis evaluation. The immune activate pathways, immune infiltration cells, immune functions, immune score and immune activation genes were remarkably enriched in the high risk group. The cuproptosis-related cluster was generated, of which the cluster 2 showed longer overall survival. The immune cell infiltration analysis indicated the similar results of cluster 2 with the high risk group, implying a significant marker for "hot tumor." The cluster 2 also presented high expression of immune checkpoint molecules, MSI-H status and higher susceptibility to multiple immunotherapy drugs. We appraised a novel cuproptosis-related prognosis model and molecular signature associated with prognosis, immune infiltration and immunotherapy. The identification of cuproptosis-related lncRNAs improved our understanding of immune infiltration and provided a significant marker for prognosis and immunotherapy in CRC. 10.3389/fgene.2022.984743
Identification of a cuproptosis and copper metabolism gene-related lncRNAs prognostic signature associated with clinical and immunological characteristics of hepatocellular carcinoma. Frontiers in oncology Background:The relationship between cuproptosis and HCC is still in the exploratory stage. Long noncoding RNAs (lncRNAs) have recently been linked to the progression of hepatocellular carcinoma (HCC). However, the clinical significance of lncRNAs associated with cuproptosis remains unclear. Methods:Based on The Cancer Genome Atlas (TCGA) liver hepatocellular carcinoma (LIHC) dataset, we identified characteristic prognostic lncRNAs by univariate, LASSO, and multifactorial regression analysis, and constructed a prognostic signature of cuproptosis-related lncRNAs in HCC. The role of lncRNAs were identified through CCK-8, clone formation in Huh-7 cells with high expression of FDX1. Prognostic potential of the characteristic lncRNAs was evaluated in each of the two cohorts created by randomly dividing the TCGA cohort into a training cohort and a test cohort in a 1:1 ratio. Immune profiles in defined subgroups of cuproptosis-related lncRNA features as well as drug sensitivity were analyzed. Results:We constructed a multigene signature based on four characteristic prognostic lncRNAs (AL590705.3, LINC02870, KDM4A-AS1, MKLN1-AS). These four lncRNAs participated in the development of cuproptosis. HCC patients were classified into high-risk and low-risk groups based on the median value of the risk score. The receiver operating characteristic curve area under the curve values for 1-, 3-, and 5-year survival were 0.773, 0.728, and 0.647, respectively, for the training cohort, and 0.764, 0.671, and 0.662, respectively, for the test cohort. Univariate and multifactorial regression analyses indicated that this prognostic feature was an independent prognostic factor for HCC. Principal component analysis plots clearly distinguished between low- and high-risk patients in terms of their probability of survival. Furthermore, gene set enrichment analysis showed that a variety of processes associated with tumor proliferation and progression were enriched in the high-risk group compared with the low-risk group. Moreover, there were significant differences in the expression of immune cell subpopulations, immune checkpoint genes, and potential drug screening, which provided distinct therapeutic recommendations for individuals with various risks. Conclusions:We constructed a novel cuproptosis-associated lncRNA signature with a significant predictive value for the prognosis of patients with HCC. Cuproptosis-associated lncRNAs are associated with the tumor immune microenvironment of HCC and even the efficacy of tumor immunotherapy. 10.3389/fonc.2023.1153353
Development and validation of a cuproptosis-associated prognostic model for diffuse large B-cell lymphoma. Frontiers in oncology Diffuse large B-cell lymphoma (DLBCL) is a highly heterogeneous disease. Therefore, more reliable biomarkers are required to better predict the prognosis of DLBCL. Cuproptosis is a novel identified form of programmed cell death (PCD) that is different from oxidative stress-related cell death (e.g., apoptosis, ferroptosis, and necroptosis) by Tsvetkov and colleagues in a recent study released in Science. Cuproptosis is copper-dependent PCD that is closely tied to mitochondrial metabolism. However, the prognostic value of cuproptosis-related genes (CRGs) in DLBCL remains to be further elucidated. In the present study, we systematically evaluated the molecular changes of CRGs in DLBCL and found them to be associated with prognosis. Subsequently, based on the expression profiles of CRGs, we characterized the heterogeneity of DLBCL by identifying two distinct subtypes using consensus clustering. Two isoforms exhibited different survival, biological functions, chemotherapeutic drug sensitivity, and immune microenvironment. After identifying differentially expressed genes (DEGs) between CRG clusters, we built a prognostic model with the Least absolute shrinkage and selection operator (LASSO) Cox regression analysis and validated its prognostic value by Cox regression analysis, Kaplan-Meier curves, and receiver operating characteristic (ROC) curves. In addition, the risk score can predict clinical characteristics, levels of immune cell infiltration, and prognosis. Furthermore, a nomogram incorporating clinical features and risk score was generated to optimize risk stratification and quantify risk assessment. Compared to the International Prognostic Index (IPI), the nomogram has demonstrated more accuracy in survival prediction. Furthermore, we validated the prognostic gene expression levels through external experiments. In conclusion, cuproptosis-related gene signature can serve as a potential prognostic predictor in DLBCL patients and may provide new insights into cancer therapeutic targets. 10.3389/fonc.2022.1020566
Cuproptosis-related lncRNAs ovarian cancer: Multi-omics analysis of molecular mechanisms and potential therapeutic targets. Environmental toxicology Ovarian cancer (OV) is an aggressive malignancy that poses a significant threat to the health and lives of women. Cuproptosis is a newly discovered form of programmed cell death that offers a promising therapeutic target, although its significance in cancer progression remains uncertain. In this study, we established a prognostic model of OV with six cuproptosis-related long non-coding RNAs (lncRNAs), including CTC.246B18.8, LINC00337, RP11.568N6.1, RP11.158I9.8, RP11.678G14.3 and CYP4F26P, based on the data of The Cancer Genome Atlas (TCGA). Lower risk scores were associated with favorable prognosis. In addition, a negative outcome was associated with high expression of CTC.246B18.8. According to the ESTIMATE algorithm, CTC.246B18.8 was negatively correlated with the ImmuneScore, and positively with immune checkpoints, immune cell infiltration, and tumor mutation burden (TMB). Moreover, gene set enrichment analysis (GSEA) revealed that pathways related to immunosuppression are likely activated in response to CTC-246B18.8 overexpression. Furthermore, CTC-246B18.8 expression was also associated with the sensitivity to various chemotherapy drugs. The expression patterns of the above lncRNAs were verified in ovarian tumor cell lines (SK-OV-3, COC1, and A2780) and normal ovarian epithelial cells (IOSE - 80). Six cuproptosis-related genes (CRGs), including ATP7B, MTF1, SLC31A1, DLD, ATP7A and DLAT, were differentially expressed between CTC-246B18.8 and CTC-246B18.8 patient groups, and exhibited organ-specific expression patterns pan-cancer. Small molecule drugs that target these CRGs were predicted, and potential candidates included DIAMIDE, bathocuproine disulfonate, D-penicillamine, etc. To summarize, our findings provide molecular insights into the role of cuproptosis in OV, and the signature lncRNAs and CRGs should be investigated further as immunotherapy biomarkers of OV. 10.1002/tox.24067
Molecular Subtypes Based on Cuproptosis-Related Genes and Tumor Microenvironment Infiltration Characterization in Colorectal Cancer. Journal of oncology Recent studies have demonstrated the biological significance of cuproptosis modification, a newly discovered programmed cell death, in tumor progression. Nonetheless, the potential role of cuproptosis-related genes (CRGs) in the immune landscape and tumor microenvironment (TME) formation of colorectal cancer (CRC) remains unknown. We comprehensively assessed cuproptosis modification patterns of 1339 CRC samples based on 27 CRGs and systematically analyzed the correlation of these patterns with TME. The CRG-score was constructed to quantify cuproptosis characteristics by LASSO and multivariate Cox regression methods, and its predictive capability was validated in an independent cohort. We identified three distinct cuproptosis modification patterns in CRC. The TME immune cell infiltration demonstrated immune heterogeneity among these three subtypes. Enrichment for multiple metabolism signatures was pronounced in cluster A. Cluster C was significantly correlated with the signaling pathways of immune activation-related, resulting in poor prognoses. Cluster B with mixed features possibly represents a transition phenotype or intratumoral heterogeneity. Then, based on constructed eight-gene CRG-score, we found that the signature could predict the disease-free survival of CRC patients, and the low CRG-score was related to increased neoantigen load, immunity activation, and microsatellite instability-high (MSI-H). Additionally, we observed significant correlations of the CRG-score with the cancer stem cell index and chemotherapeutic drug susceptibility. This study demonstrated that cuproptosis was correlated with tumor progression, prognosis, and TME. Our findings may improve the understanding of CRGs in TME infiltration characterization of CRC patients and contribute to guiding more effective clinical therapeutic strategies. 10.1155/2022/5034092
A signature of cuproptosis-related lncRNAs predicts prognosis and provides basis for future anti-tumor drug development in breast cancer. Translational cancer research Background:Breast cancer is the most prevalent malignancy worldwide and the leading culprit for women's death. Cuproptosis is a novel and promising modality of tumor cell death and the relationship with long non-coding RNAs (lncRNAs) remains shrouded in a veil. Studies in cuproptosis-related lncRNAs can aid in the clinical management of breast cancer and provide a basis for anti-tumor drug development. Methods:RNA-Seq data, somatic mutation data, and clinical information were downloaded from The Cancer Genome Atlas (TCGA). Patients were divided into high- and low-risk groups according to the risk score. Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses were used to select prognostic lncRNAs to construct a risk score system. Its' prognostic value was confirmed in the training and validation cohorts subsequently. Functional analysis regarding cuproptosis-related lncRNAs was performed. Results:Eighteen cuproptosis-related lncRNAs were identified and 11 of them including , , , , , , , , , and were selected for risk score system construction. The risk score was confirmed as an independent prognostic factor and patients in the high-risk group had a worse prognosis. A nomogram based on the independent prognostic factors was constructed for clinical decision aids. Further analyses revealed that patients in the high-risk group faced a heavier tumor mutational burden (TMB) and suppressed anti-tumor immunity. Besides, cuproptosis-related lncRNAs were associated with the expression of immune checkpoint inhibitors, N6-adenylate methylation (m6a), and drug sensitivity in breast cancer. Conclusions:A prognostic risk score system with satisfactory predictive accuracy was constructed. Besides, cuproptosis-related lncRNAs can influence the immune microenvironment, TMB, m6a, and drug sensitivity in breast cancer, which may provide a basis for future anti-tumor drug development. 10.21037/tcr-22-2702
The core genes of cuproptosis assists in discerning prognostic and immunological traits of clear cell renal cell carcinoma. Frontiers in oncology Objective:Cuproptosis, a nascent and unique pattern of cell death, is poised to spark a new rush of biological research. Yet, the subsumed mechanism of cuproptosis in carcinoma is not wholly clarified. The exclusive aim of this work is to define a novel classification algorithm and risk-prognosis scoring framework based on the expression modalities of cuproptosis genes to monitor clear cell renal cell carcinoma (ccRCC) patients' prognosis and immunotherapeutic response. Methods:We pooled ccRCC data from three large-scale databases as the training subset and gathered a panel of clinical queues, termed the Taizhou cohort, which served as the validation setup. Wilcox test was conducted for comparison of expression variation, while the cox analysis and KM curves were utilized to visualize prognosis. Unsupervised clustering analysis was used to identify cuproptosis phenotypes in ccRCC. Concurrently, LASSO regression-based computational scoring model. A step further, gene set enrichment analysis (GSEA) was performed to check potential biological processes and the "CIBERSORT" R package was used to estimate the proportion of immune cells. To last, immunohistochemistry and qRT-PCR were carried out for the assay of critical genes for cuproptosis. Results:Here, we glimpse the prognostic power of cuproptosis genes in pan-cancer by investigating 33 cancers with multi-omics data to map their genetic heterogeneity landscape. In parallel, we devoted extra attention to their strategic potential role in ccRCC, identifying two phenotypes of cuproptosis with different immune microenvironmental characteristics by pooling ccRCC data from three large-scale databases. Additionally, we compiled a cuproptosis scoring system for clinicians to determine the prognosis, immunotherapy response, and chemosensitivity of ccRCC patients. Notably, we assembled a clinical cohort sample to validate the pivotal gene for cuproptosis, FDX1, to supply more clues to translate the biological significance of cuproptosis in ccRCC. Conclusion:In all, our investigations highlight that cuproptosis is involved in various components of ccRCC and assists in the formation of the tumor immune microenvironment. These results provide partial insights to further comprehend the molecular mechanisms of cuproptosis in ccRCC and could be helpful for the development of personalized therapeutic strategies targeting copper or cuproptosis. 10.3389/fonc.2022.925411
Potential diagnostic biomarkers: 6 cuproptosis- and ferroptosis-related genes linking immune infiltration in acute myocardial infarction. Genes and immunity The current diagnostic biomarkers of acute myocardial infarction (AMI), troponins, lack specificity and exist as false positives in other non-cardiac diseases. Previous studies revealed that cuproptosis, ferroptosis, and immune infiltration are all involved in the development of AMI. We hypothesize that combining the analysis of cuproptosis, ferroptosis, and immune infiltration in AMI will help identify more precise diagnostic biomarkers. The results showed that a total of 19 cuproptosis- and ferroptosis-related genes (CFRGs) were differentially expressed between the healthy and AMI groups. Functional enrichment analysis showed that the differential CFRGs were mostly enriched in biological processes related to oxidative stress and the inflammatory response. The immune infiltration status analyzed by ssGSEA found elevated levels of macrophages, neutrophils, and CCR in AMI. Then, we screened 6 immune-related CFRGs (CXCL2, DDIT3, DUSP1, CDKN1A, TLR4, STAT3) to construct a nomogram for predicting AMI and validated it in the GSE109048 dataset. Moreover, we also identified 5 pivotal miRNAs and 10 candidate drugs that target the 6 feature genes. Finally, RT-qPCR analysis verified that all 6 feature genes were upregulated in both animals and patients. In conclusion, our study reveals the significance of immune-related CFRGs in AMI and provides new insights for AMI diagnosis and treatment. 10.1038/s41435-023-00209-8
Comprehensive analysis of a cuproptosis-related ceRNA network implicates a potential endocrine therapy resistance mechanism in ER-positive breast cancer. BMC medical genomics BACKGROUND:While adjuvant endocrine therapy (ET) may decrease the mortality rate of estrogen receptor-positive (ER+) breast cancer (BC), the likelihood of relapse and metastasis due to ET resistance remains high. Cuproptosis is a recently discovered regulated cell death (RCD), whose role in tumors has yet to be elucidated. Thus, there is a need to study its specific regulatory mechanism in resistance to ET in BC, to identify novel therapeutic targets. METHODS:The prognostic cuproptosis-related genes (CRGs) in ER+ BC were filtered by undergoing Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses in TCGA-BRCA, and a CRGs risk signature was constructed using the correlation coefficient. Immune infiltration analysis, immune function analysis, tumor microenvironment (TME) analysis, immune checkpoint analysis, immunotherapy response analysis, drug sensitivity analysis, and pathway activation analysis were carried out among the high- and low-risk groups in turn. The central CRG of cuproptosis in ER+ BC resistance to ET was acquired through the intersection of protein interaction network (PPI) analysis, genes differentially expressed (DEGs) between human BC cells LCC9 and MCF-7 (GSE159968), and CRGs with prognostic significance in TCGA-BRCA ER+ BC. The miRNAs upstream of the core CRGs were predicted based on the intersection of 4 databases, miRDB, RNA22, miRWalk, and RNAlnter. Candidate miRNAs consisted of the intersection of predicted miRNAs and miRNAs differentially expressed in the LCC9 and MCF-7 cell lines (GSE159979). Candidate lncRNAs were the intersection of the differential lncRNAs from the LCC9 and MCF-7 cell lines and the survival-related lncRNAs obtained from a univariate Cox regression analysis. Pearson's correlation analysis was performed between mRNA-miRNA, miRNA-lncRNA, and mRNA-lncRNA expression separately. RESULTS:We constructed A risk signature of 4-CRGs to predict the prognosis of ER+ BC in TCGA-BRCA, a risk score = DLD*0.378 + DBT*0.201 + DLAT*0.380 + ATP7A*0.447 was used as the definition of the formula. There were significant differences between the high- and low-risk groups based on the risk score of 4-CRGs in aspects of immune infiltration, immune function, expression levels of immune checkpoint genes, and signaling pathways. DLD was determined to be the central CRG of cuproptosis in ER+ BC resistance to ET through the intersection of the PPI network analysis, DEGs between LCC9 and MCF-7 and 4-CRGs. Two miRNAs hsa-miR-370-3p and hsa-miR-432-5p were found taking DLD mRNA as a target, and the lncRNA C6orf99 has been hypothesized to be a competitive endogenous RNA that regulates DLD mRNA expression by sponging off hsa-miR-370-3p and hsa-miR-432-5p. CONCLUSION:This study built a prognostic model based on genes related to cuproptosis in ER+ BC. We considered DLD to be the core gene associated with resistance to ET in ER+ BC via copper metabolism. The search for promising therapeutic targets led to the establishment of a cuproptosis-related ceRNA network C6orf99/hsa-miR-370-3p and hsa-miR-432-5p/DLD. 10.1186/s12920-023-01511-0
Construction and systematic evaluation of a machine learning-based cuproptosis-related lncRNA score signature to predict the response to immunotherapy in hepatocellular carcinoma. Frontiers in immunology Introduction:Hepatocellular carcinoma (HCC) is a common malignant cancer with a poor prognosis. Cuproptosis and associated lncRNAs are connected with cancer progression. However, the information on the prognostic value of cuproptosis-related lncRNAs is still limited in HCC. Methods:We isolated the transcriptome and clinical information of HCC from TCGA and ICGC databases. Ten cuproptosis-related genes were obtained and related lncRNAs were correlated by Pearson's correlation. By performing lasso regression, we created a cuproptosis-related lncRNA prognostic model based on the cuproptosis-related lncRNA score (CLS). Comprehensive analyses were performed, including the fields of function, immunity, mutation and clinical application, by various R packages. Results:Ten cuproptosis-related genes were selected, and 13 correlated prognostic lncRNAs were collected for model construction. CLS was positively or negatively correlated with cancer-related pathways. In addition, cell cycle and immune related pathways were enriched. By performing tumor microenvironment (TME) analysis, we determined that T-cells were activated. High CLS had more tumor characteristics and may lead to higher invasiveness and treatment resistance. Three genes (, and ) were found in high CLS samples with more mutational frequency. More amplification and deletion were detected in high CLS samples. In clinical application, a CLS-based nomogram was constructed. 5-Fluorouracil, gemcitabine and doxorubicin had better sensitivity in patients with high CLS. However, patients with low CLS had better immunotherapeutic sensitivity. Conclusion:We created a prognostic CLS signature by machine learning, and we comprehensively analyzed the signature in the fields of function, immunity, mutation and clinical application. 10.3389/fimmu.2023.1097075
Cuproptosis-associated CDKN2A is targeted by plicamycin to regulate the microenvironment in patients with head and neck squamous cell carcinoma. Frontiers in genetics Head and neck squamous cell carcinoma (HNSCC), the most common malignancy of the head and neck, has an overall 5-year survival rate of <50%. Genes associated with cuproptosis, a newly identified copper-dependent form of cell death, are aberrantly expressed in various tumours. However, their role in HNSCC remains unknown. In this study, bioinformatic analysis revealed that the cuproptosis-related gene CDKN2A was correlated with the malignant behaviour of HNSCC. Kaplan-Meier (KM) curves showed that patients with high CDKN2A expression had a better prognosis. Multiomic analysis revealed that CDKN2A may be associated with cell cycle and immune cell infiltration in the tumour microenvironment and is important for maintaining systemic homeostasis in the body. Furthermore, molecular docking and molecular dynamics simulations suggested strong binding between plicamycin and CDKN2A. And plicamycin inhibits the progression of HNSCC in cellular assays. In conclusion, this study elucidated a potential mechanism of action of the cuproptosis-associated gene CDKN2A in HNSCC and revealed that plicamycin targets CDKN2A to improve the prognosis of patients. 10.3389/fgene.2022.1036408
DARS2 is a prognostic biomarker and correlated with immune infiltrates and cuproptosis in lung adenocarcinoma. American journal of cancer research Overexpression of DARS2 may enhance the progression of hepatocellular carcinoma (HCC). However, there are few extensive reports on DARS2 function in lung adenocarcinoma (LUAD). The differential expression of DARS2 was detected by genomics and in vitro experiments, and the effect of DARS2 expression on LUAD cell activity was analyzed. Functional enrichment analysis was performed to explore possible signal pathways involved in the biological functions of DARS2 and its co-expressed genes. Utilizing TIMER and GEPIA datasets, the association between DARS2 expression and immunological infiltrating cells was analyzed. At the same time, the association between DARS2 expression pattern and LUAD m6A modification and cuproptosis was examined utilizing TCGA and GEO datasets. The level of DARS2 in LUAD increased, and inhibition of DARS2 expression could significantly inhibit the proliferation of LUAD cells. ROC curves showed that DARS2 overexpression could accurately diagnose LUAD and lead to a significant decline in the survival rates of OS, DSS, and PFI in LUAD. Enrichment analysis showed that DARS2 and its co-expressed genes were closely associated with chromosome segregation and the cell cycle. TIMER and GEPIA database analysis demonstrated that the DARS2 expression pattern was adversely correlated with the infiltration of B cells and Tfh cells. TCGA and GEO dataset examination revealed that DARS2 expression was significantly linked to four m6A-related genes and one cuproptosis-related gene. DARS2 expression is increased in LUAD patients and is closely associated with LUAD immune cell infiltration, modification of m6A, and cuproptosis. DARS2 is a potential reliable prognostic biomarker of LUAD.
Significance of cuproptosis-related lncRNA signature in LUAD prognosis and immunotherapy: A machine learning approach. Thoracic cancer OBJECTIVE:Cuproptosis-related genes are closely related to lung adenocarcinoma (LUAD), which can be analyzed via the analysis of long noncoding RNA (lncRNA). To date, the clinical significance and function of cuproptosis-related lncRNAs are still not well elucidated. Further analysis of cuproptosis-related prognostic lncRNAs is of great significance for the treatment, diagnosis, and prognosis of LUAD. METHODS:In this study, a multiple machine learning (ML)-based computational approach was proposed for the identification of the cuproptosis-related lncRNAs signature (CRlncSig) via comprehensive analysis of cuproptosis, lncRNAs, and clinical characteristics. The proposed approach integrated multiple ML algorithms (least absolute shrinkage and selection operator regression analysis, univariate and multivariate Cox regression) to effectively identify the CRlncSig. RESULTS:Based on the proposed approach, the CRlncSig was identified from the 3450 cuproptosis-related lncRNAs, which consist of 13 lncRNAs (CDKN2A-DT, FAM66C, FAM83A-AS1, AL359232.1, FRMD6-AS1, AC027237.4, AC023090.1, AL157888.1, AL627443.3, AC026355.2, AC008957.1, AP000346.1, and GLIS2-AS1). CONCLUSIONS:The CRlncSig could well predict the prognosis of different LUAD patients, which is different from other clinical features. Moreover, the CRlncSig was proved to be an effective indicator of patient survival via functional characterization analysis, which is relevant to cancer progression and immune infiltration. Furthermore, the results of RT-PCR assay indicated that the expression level of FAM83A-AS1 and AC026355.2 in A549 and H1975 cells (LUAD) was significantly higher than that in BEAS-2B cells (normal lung epithelial). 10.1111/1759-7714.14888
Identification of cuproptosis-related diagnostic biomarkers in idiopathic pulmonary fibrosis. Medicine Idiopathic pulmonary fibrosis (IPF) is a progressive and fatal lung disease with clinical and pathological heterogeneity. Recent studies have identified cuproptosis as a novel cell death mechanism. However, the role of cuproptosis-related genes in the pathogenesis of IPF is still unclear. Two IPF datasets of the Gene Expression Omnibus database were studied. Mann-Whitney U test, correlation analysis, functional enrichment analyses, single-sample gene set enrichment analysis, CIBERSORT, unsupervised clustering, weighted gene co-expression network analysis, and receiver operating characteristic curve analysis were used to conduct our research. The dysregulated cuproptosis-related genes and immune responses were identified between IPF patients and controls. Two cuproptosis-related molecular clusters were established in IPF, the high immune score group (C1) and the low immune score group (C2). Significant heterogeneity in immunity between clusters was revealed by functional analyses results. The module genes with the strongest correlation to the 2 clusters were identified by weighted gene co-expression network analysis results. Seven hub genes were found using the Cytoscape software. Ultimately, 2 validated diagnostic biomarkers of IPF, CDKN2A and NEDD4, were obtained. Subsequently, the results were validated in GSE47460. Our investigation illustrates that CDKN2A and NEDD4 may be valid biomarkers that were useful for IPF diagnosis and copper-related clustering. 10.1097/MD.0000000000036801
Identification of cuproptosis-based molecular subtypes, construction of prognostic signature and characterization of immune landscape in colon cancer. Frontiers in oncology Background:Cuproptosis is a newly discovered form of cell death induced by targeting lipoacylated proteins involved in the tricarboxylic acid cycle. However, the roles of cuproptosis-related genes (CRGs) in the clinical outcomes and immune landscape of colon cancer remain unknown. Methods:We performed bioinformatics analysis of the expression data of 13 CRGs identified from a previous study and clinical information of patients with colon cancer obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases. Colon cancer cases were divided into two CRG clusters and prognosis-related differentially expressed genes. Patient data were separated into three corresponding distinct gene clusters, and the relationships between the risk score, patient prognosis, and immune landscape were analyzed. The identified molecular subtypes correlated with patient survival, immune cells, and immune functions. A prognostic signature based on five genes was identified, and the patients were divided into high- and low-risk groups based on the calculated risk score. A nomogram model for predicting patient survival was developed based on the risk score and other clinical features. Results:The high-risk group showed a worse prognosis, and the risk score was related to immune cell abundance, microsatellite instability, cancer stem cell index, checkpoint expression, immune escape, and response to chemotherapeutic drugs and immunotherapy. Findings related to the risk score were validated in the imvigor210 cohort of patients with metastatic urothelial cancer treated with anti-programmed cell death ligand 1. Conclusion:We demonstrated the potential of cuproptosis-based molecular subtypes and prognostic signatures for predicting patient survival and the tumor microenvironment in colon cancer. Our findings may improve the understanding of the role of cuproptosis in colon cancer and lead to the development of more effective treatment strategies. 10.3389/fonc.2023.927608
Evaluation the role of cuproptosis-related genes in the pathogenesis, diagnosis and molecular subtypes identification of atherosclerosis. Heliyon Background:At present, the pathogenesis of atherosclerosis has not been fully elucidated, and the diagnosis and treatment face great challenges. Cuproptosis is a novel cell death pattern that might be involved in the development of atherosclerosis. However, no research has reported the correlation between cuproptosis and atherosclerosis. Methods:The differential cuproptosis-related genes (CRGs) between atherosclerosis group and control group (A-CRGs) were discovered via differential expression analysis. The correlation analysis, PPI network analysis, GO, KEGG and GSEA analysis were performed to investigate the function of A-CRGs. The differences of biological function between atherosclerosis group and control group were investigated via immune infiltration analysis and GSVA. The LASSO regression, nomogram and machine learning models were constructed to predict atherosclerosis risk. The atherosclerosis molecular subtypes clusters were discovered via unsupervised cluster analysis. Subsequently, we used the above research methods to analyze the differential CRGs between clusters (M-CRGs) and evaluate the molecular subtypes identification performance of M-CRGs. Finally, we verified the diagnostic value for atherosclerosis and role in cuproptosis of these CRGs through the validation set and in vitro experiments. Results:Five A-CRGs were identified and they were mainly related to the biological function of copper ion metabolism and immune inflammatory response. The diagnostic models and nomogram of atherosclerosis based on 5 A-CRGs indicated that these genes had well diagnostic value. A total of two molecular subtypes clusters were obtained in the atherosclerosis group. There were many differences in biological functions between these two molecular subtypes clusters, such as mitochondrial outer membrane permeabilization and primary immunodeficiency. In addition, 3 M-CRGs were identified in the 2 clusters. Machine learning models and nomogram constructed based on M-CRGs showed that these genes had well molecular subtypes identification efficacy. In the end, the results of in vitro experiment and validation set confirmed the diagnostic value for atherosclerosis and role in cuproptosis of these genes. Conclusion:The cuproptosis may be a potential pathogenesis of atherosclerosis and CRGs may be promising markers for the diagnosis and molecular subtypes identification of atherosclerosis. 10.1016/j.heliyon.2023.e21158
Clinical significance and potential application of cuproptosis-related genes in gastric cancer. World journal of gastrointestinal oncology BACKGROUND:Worldwide, gastric cancer (GC) is a common lethal solid malignancy with a poor prognosis. Cuproptosis is a novel type of cell death mediated by protein lipoylation and may be related to GC prognosis. AIM:To offer new insights to predict GC prognosis and provide multiple therapeutic targets related to cuproptosis-related genes (CRGs) for future therapy. METHODS:We collected data from several public data portals, systematically estimated the expression level and prognostic values of CRGs in GC samples, and investigated related mechanisms using public databases and bioinformatics. RESULTS:Our results revealed that , , and were differentially expressed in GC samples and exhibited important prognostic significance in The Cancer Genome Atlas (TCGA) cohort. We constructed a nomogram model for overall survival and disease-specific survival prediction and validated it calibration plots. Mecha-nistically, immune cell infiltration and DNA methylation prominently affected the survival time of GC patients. Moreover, protein-protein interaction network, KEGG pathway and gene ontology enrichment analyses demonstrated that , , and related proteins play key roles in the tricarboxylic acid cycle and cuproptosis. Gene Expression Omnibus database validation showed that the expression levels of , , and were consistent with those in the TCGA cohort. Top 10 perturbagens has been filtered by Connectivity Map. CONCLUSION:In conclusion, , , and could serve as potential prognostic biomarkers for GC patients and provide novel targets for immunotarget therapy. 10.4251/wjgo.v15.i7.1200
Relationships of Cuproptosis-Related Genes With Clinical Outcomes and the Tumour Immune Microenvironment in Hepatocellular Carcinoma. Pathology oncology research : POR Cuproptosis is a recently identified form of regulated cell death that plays a critical role in the onset and progression of various cancers. However, the effects of cuproptosis-related genes (CRGs) on hepatocellular carcinoma (HCC) are poorly understood. This study aimed to identify the cuproptosis subtypes and established a novel prognostic signature of HCC. We collected gene expression data and clinical outcomes from the TCGA, ICGC, and GEO datasets, analysed and identified 16 CRGs and the different subtypes of cuproptosis related to overall survival (OS), and further examined the differences in prognosis and immune infiltration among the subtypes. Subtypes-related differentially expressed genes (DEGs) were employed to build a prognostic signature. The relationship of the signature with the immune landscape as well as the sensitivity to different therapies was explored. Moreover, a nomogram was constructed to predict the outcome based on different clinicopathological characteristics. Three cuproptosis subtypes were identified on the basis of 16 CRGs, and subtype B had an advanced clinical stage and worse OS. The immune response and function in subtype B were significantly suppressed, which may be an important reason for its poor prognosis. Based on the DEGs among the three subtypes, a prognostic model of five CRGs was constructed in the training set, and its predictive ability was validated in two external validation sets. HCC patients were classified into high and low-risk subgroups according to the risk score, and found that patients in the low-risk group showed significantly higher survival possibilities than those in the high-risk group ( < 0.001). The independent predictive performance of the risk score was assessed and verified by multivariate Cox regression analysis ( < 0.001). We further created an accurate nomogram to improve the clinical applicability of the risk score, showing good predictive ability and calibration. Low- and high-risk patients exhibit distinct immune cell infiltration and immune checkpoint changes. By further analyzing the risk score, patients in the high-risk group were found to be resistant to immunotherapy and a variety of chemotherapy drugs. Our study identified three cuproptosis subtypes and established a novel prognostic model that provides new insights into HCC subtype prognostic assessment and guides more effective treatment regimens. 10.3389/pore.2022.1610558
Molecular subtypes of cuproptosis regulators and their correlation with clinical prognosis and immune response in glioma. American journal of translational research Cuproptosis is a newly described form of cell death. However, nothing is known about the roles of cuproptosis regulators in glioma. First, we explored the characteristics of cuproptosis molecular subtypes and relevant tumor microenvironment (TME) immune cell infiltration patterns in glioma. Using unsupervised clustering analysis, we identified two cuproptosis subtypes and three gene clusters that exhibited different clinical characteristics and TME cell infiltration patterns. Then, we developed and validated a cuproptosis-related prognostic model for predicting the overall survival of glioma patients. We established a risk score tool based on a nomogram to assess the clinical applicability of the cuproptosis model. A high cuproptosis risk score with high immune cell infiltration level, tumor mutation burden, gene alterations, and immunity activation had an unfavorable overall survival. Next, we identified possible competing endogenous ribonucleic acid regulatory networks based on significantly differentially expressed genes between high-risk and low-risk groups and screened several candidate small molecular compounds that may improve chemotherapy. Data from IMvigor and GSE78200 showed that the cuproptosis score affected the prognosis of patients who received immunotherapy. Our study indicated that cuproptosis regulators are involved in TME immune infiltration and impact the clinical prognosis in glioma. It is necessary for clinical practice to develop different therapeutic strategies according to the different phenotypes associated with immune response. The present findings provide new insight for improving immunotherapy strategies and individualized treatment in glioma.
The value of cuproptosis-related differential genes in guiding prognosis and immune status in patients with skin cutaneous melanoma. Frontiers in pharmacology Skin cutaneous melanoma (SKCM) is one of the most common cutaneous malignancies, which incidence is increasing. Cuproptosis is a new type of programming cell death recently reported, which may affect the progression of SKCM. The mRNA expression data of melanoma were obtained from the Gene Expression Omnibus and the Cancer Genome Atlas databases. We constructed a prognostic model according to the cuproptosis-related differential genes in SKCM. Finally, real-time quantitative PCR was performed to verify the expression of cuproptosis-related differential genes in patients with different stages of cutaneous melanoma. We detected 767 cuproptosis-related differential genes based on 19 cuproptosis-related genes, and screened out 7 differential genes to construct a prognostic model, which including three high-risk differential genes (SNAI2, RAP1GAP, BCHE), and four low-risk differential genes (JSRP1, HAPLN3, HHEX, ERAP2). Kaplan-Meier analysis indicated that SKCM patients with low-risk differential genes signals had better prognosis. The Encyclopedia of Genomes results manifested that cuproptosis-related differential genes are not only involved in T cell receptor signaling channel, natural killer cell mediated cytotoxicity, but also chemokine signaling pathway and B cell receptor signaling pathway. In our risk scoring model, the receiver operating characteristic (ROC) values of the three-time nodes are 0.669 (1-year), 0.669 (3-year) and 0.685 (5-year), respectively. Moreover, the tumor burden mutational and immunology function, cell stemness characteristics and drug sensitivity have significant differences between low-risk group and high-risk group. The mRNA level of SNAI2, RAP1GAP and BCHE in stage Ⅲ+Ⅳ SKCM patients was significantly higher than that in stage Ⅰ+Ⅱ patients, while the level of JSRP1, HAPLN3, HHEX and ERAP2 in stage Ⅰ+Ⅱ SKCM patients was more remarkable higher than that in stage Ⅲ+Ⅳ SKCM patients. In summary, we suggest that cuproptosis can not only regulate the tumor immune microenvironment but also affect the prognosis of SKCM patients, and may offer a basic theory for SKCM patients survival studies and clinical decision-making with potentially therapeutic drugs. 10.3389/fphar.2023.1129544
Development and validation of cuproptosis-associated prognostic signatures in WHO 2/3 glioma. Frontiers in oncology WHO 2/3 glioma is a common intracranial tumor that seriously affects the quality of life and survival time of patients. Previous studies have shown that the tricarboxylic acid (TCA) cycle is closely related to the occurrence and development of glioma, while recent studies have shown that cuproptosis, a novel programmed death pathway, is closely related to the inhibition of the TCA cycle. In our study, eight of ten cuproptosis-related genes (CRGs) were found to be differentially expressed between normal and WHO 2/3 glioma tissues. Through the LASSO algorithm, the cuproptosis-associated risk signatures (CARSs) were constructed, which can effectively predict the prognosis of WHO 2/3 glioma patients and are closely related to clinicopathological features. We analyzed the relationship between risk score and immune cell infiltration through Xcell, ssGSEA, TIMER database, and immune checkpoint molecules. In addition, the relationship between risk score and chemotherapeutic drug sensitivity was also investigated. The prognosis-related independent risk factors FDX1 and CDKN2A identified from CARSs are considered potential prognostic biomarkers for WHO 2/3 glioma. The clinical prognosis model based on cuproptosis is expected to provide an effective reference for the diagnosis and treatment of clinical WHO 2/3 glioma patients. 10.3389/fonc.2022.967159
A Newly Established Cuproptosis-Related Gene Signature for Predicting Prognosis and Immune Infiltration in Uveal Melanoma. International journal of molecular sciences Uveal melanoma (UVM) is the most common primary ocular malignancy in adults and involves several types of regulated cell death. Cuproptosis is a novel method of regulating cell death by binding lipoylated TCA cycle proteins. There is still no research on the relationship between cuproptosis-related genes (CRGs) and UVM. Here, we aimed to develop a prognostic CRG signature for UVM. After a prognostic CRG signature was constructed, we determined the relationship between the signature and immune infiltration, bioinformatics analysis and experimental validation. Finally, a prognostic cuproptosis-related three-gene (CRTG) signature was constructed, which comprised ORAI2, ACADSB and SLC47A1. The risk score of the CRTG signature was negatively correlated with the overall survival (OS) and progression-free survival (PFS) of patients, which revealed strong predictive ability and its independent prognostic value. In addition, we found that the risk score was negative for chromosomes 3 and 6p, and positive for 8q, and high-risk UVM patients showed an increase in protumor immune infiltrates and a high expression of immune checkpoints. Finally, experimental validation verified that the migratory ability of MUM-2B cells was suppressed by the knockdown of the identified genes in vitro. We constructed a CRTG signature that is helpful in predicting prognosis and guiding treatment for patients with UVM. 10.3390/ijms241411358
Multi-omics analysis defines a cuproptosis-related prognostic model for ovarian cancer: Implication of WASF2 in cuproptosis resistance. Life sciences BACKGROUND:Ovarian cancer (OVC) is one of the deadliest and most aggressive tumors in women, with an increasing incidence in recent years. Cuproptosis, a newly discovered type of programmed cell death, is caused by intracellular copper-mediated lipoylated protein aggregation and proteotoxic stress. However, the role of cuproptosis-related features in OVC remains elusive. METHODS:The single-cell sequencing data from GSE154600 and bulk transcriptome data of 378 OVC patients from TCGA database. The RNA-seq and clinical data of 379 OVC patients in GSE140082 and 173 OV patients in GSE53963. The PROGENy score was calculated to assess tumor-associated pathways. Based on gene set enrichment analysis (GSEA) of the cuproptosis pathway, the single cells were divided into the cuproptosis and cuproptosis groups. The differentially expressed genes (DEGs) between the two groups were screened, and 47 prognosis-related genes were identified based on univariate cox regression analysis. Randomforest was used to construct a prognostic model. Immuno-infiltration analysis was performed using ssGSEA and xCell algorithms. In vitro and in vivo experiments were used for functional verification. RESULTS:Six major cell populations was identified, including fibroblast, T cell, myeloid, epithelial cell, endothelial cell, and B cell populations. The PROGENy score which revealed significant activation of the PI3K pathway in T and B cells, and activation of the TGF-β pathway in endothelial cells and fibroblasts. TIMM8B, COX8A, SSR4, HIGD2A, WASF2, PRDX5 and CLDN4 were selected to construct a prognostic model from the identified 47 prognosis-related genes. Furthermore, the cuproptosis and cuproptosis groups showed significant differences in the expression levels of the model genes, immune cell infiltration, and sensitivity to six potential drug candidates. The functional experiments showed that WASF2 is associated with cuproptotic resistance and promotes cancer cell proliferation and resistance to platinum, and its high expression is associated with poor prognosis of OVC patients. CONCLUSION:A clinically significant cuproptosis-related prognostic model was identified which can accurately predict the prognosis and immune characteristics of OVC patients. WASF2, one of the cuproptosis-related gene in the risk model, promotes the proliferation and platinum resistance of OVC cells, and leads poor prognosis. 10.1016/j.lfs.2023.122081
A novel cuproptosis-related subtypes and gene signature associates with immunophenotype and predicts prognosis accurately in neuroblastoma. Frontiers in immunology Background:Neuroblastoma (NB) is the most frequent solid tumor in pediatrics, which accounts for roughly 15% of cancer-related mortality in children. NB exhibited genetic, morphologic, and clinical heterogeneity, which limited the efficacy of available therapeutic approaches. Recently, a new term 'cuproptosis' has been used to denote a unique biological process triggered by the action of copper. In this instance, selectively inducing copper death is likely to successfully overcome the limitations of conventional anticancer drugs. However, there is still a gap regarding the role of cuproptosis in cancer, especially in pediatric neuroblastoma. Methods:We characterized the specific expression of cuproptosis-related genes (CRGs) in NB samples based on publicly available mRNA expression profile data. Consensus clustering and Lasso-Cox regression analysis were applied for CRGs in three independent cohorts. ESTIMATE and Xcell algorithm was utilized to visualize TME score and immune cell subpopulations' relative abundances. Tumor Immune Dysfunction and Exclusion (TIDE) score was used to predict tumor response to immune checkpoint inhibitors. To decipher the underlying mechanism, GSVA was applied to explore enriched pathways associated with cuproptosis signature and Connectivity map (CMap) analysis for drug exploration. Finally, qPCR verified the expression levels of risk-genes in NB cell lines. In addition, PDHA1 was screened and further validated by immunofluorescence in human clinical samples and loss-of-function assays. Results:We initially classified NB patients according to CRGs and identified two cuproptosis-related subtypes that were associated with prognosis and immunophenotype. After this, a cuproptosis-related prognostic model was constructed and validated by LASSO regression in three independent cohorts. This model can accurately predict prognosis, immune infiltration, and immunotherapy responses. These genes also showed differential expression in various characteristic groups of all three datasets and NB cell lines. Loss-of-function experiments indicated that PDHA1 silencing significantly suppressed the proliferation, migration, and invasion, in turn, promoted cell cycle arrest at the S phase and apoptosis of NB cells. Conclusions:Taken together, this study may shed light on new research areas for NB patients from the cuproptosis perspective. 10.3389/fimmu.2022.999849
Study on the role and pharmacology of cuproptosis in gastric cancer. Frontiers in oncology Objective:Gastric cancer has a poor prognosis and high mortality. Cuproptosis, a novel programmed cell death, is rarely studied in gastric cancer. Studying the mechanism of cuproptosis in gastric cancer is conducive to the development of new drugs, improving the prognosis of patients and reducing the burden of disease. Methods:The TCGA database was used to obtain transcriptome data from gastric cancer tissues and adjacent tissues. GSE66229 was used for external verification. Overlapping genes were obtained by crossing the genes obtained by differential analysis with those related to copper death. Eight characteristic genes were obtained by three dimensionality reduction methods: lasso, SVM, and random forest. ROC and nomogram were used to estimate the diagnostic efficacy of characteristic genes. The CIBERSORT method was used to assess immune infiltration. ConsensusClusterPlus was used for subtype classification. Discovery Studio software conducts molecular docking between drugs and target proteins. Results:We have established the early diagnosis model of eight characteristic genes (ENTPD3, PDZD4, CNN1, GTPBP4, FPGS, UTP25, CENPW, and FAM111A) for gastric cancer. The results are validated by internal and external data, and the predictive power is good. The subtype classification and immune type analysis of gastric cancer samples were performed based on the consensus clustering method. We identified C2 as an immune subtype and C1 as a non-immune subtype. Small molecule drug targeting based on genes associated with cuproptosis predicts potential therapeutics for gastric cancer. Molecular docking revealed multiple forces between Dasatinib and CNN1. Conclusion:The candidate drug Dasatinib may be effective in treating gastric cancer by affecting the expression of the cuproptosis signature gene. 10.3389/fonc.2023.1145446
A novel cuproptosis-related prognostic lncRNA signature and lncRNA MIR31HG/miR-193a-3p/TNFRSF21 regulatory axis in lung adenocarcinoma. Frontiers in oncology Lung adenocarcinoma (LUAD) remains the most common subtype of lung malignancy. Cuproptosis is a newly identified cell death which could regulate tumor cell proliferation and progression. Long non-coding RNAs (lncRNAs) are key molecules and potential biomarkers for diagnosing and treating various diseases. However, the effects of cuproptosis-related lncRNAs on LUAD are still unclear. In our study, 7 cuproptosis-related lncRNAs were selected to establish a prognostic model using univariate Cox regression analysis, LASSO algorithm, and multivariate analysis. Furthermore, we evaluated AC008764.2, AL022323.1, ELN-AS1, and LINC00578, which were identified as protective lncRNAs, while AL031667.3, AL606489.1, and MIR31HG were identified as risk lncRNAs. The risk score calculated by the prognostic model proved to be an effective independent factor compared with other clinical features by Cox regression analyses [univariate analysis: hazard ratio (HR) = 1.065, 95% confidence interval (CI) = 1.043-1.087, < 0.001; multivariate analysis: HR = 1.067, 95% CI = 1.044-1.091, < 0.001]. In addition, both analyses (ROC and nomogram) were used to corroborate the accuracy and reliability of this signature. The correlation between cuproptosis-related lncRNAs and immune microenvironment was elucidated, where 7 immune cells and 8 immune-correlated pathways were found to be differentially expressed between two risk groups. Furthermore, our results also identified and verified the ceRNA of cuproptosis-related lncRNA MIR31HG/miR-193a-3p/TNFRSF21 regulatory axis using bioinformatics tools. MIR31HG was highly expressed in LUAD specimens and some LUAD cell lines. Inhibition of MIR31HG clearly reduced the proliferation, migration, and invasion of the LUAD cells. MIR31HG showed oncogenic features sponging miR-193a-3p and tended to positively regulate TNFRSF21 expression. In a word, lncRNA MIR31HG acts as an oncogene in LUAD by targeting miR-193a-3p to modulate TNFRSF21, which may be beneficial to the gene therapy of LUAD. 10.3389/fonc.2022.927706
Novel cuproptosis-related prognostic gene profiles in preeclampsia. BMC pregnancy and childbirth BACKGROUND:Preeclampsia (PE) is a pregnancy-specific disorder with complex pathogenesis. Cuproptosis is a novel identified form of programmed cell death, however, the link between cuproptosis and clinical outcomes in PE is still not fully understood. In this study, we searched for cuproptosis-related genes (CRGs) in the placental tissues of normal and PE patients to clarify the importance of cuproptosis in the development of PE and provide potential predictive indicators for the occurrence of PE. METHODS:Using RNA sequencing data in the GEO database, we conducted functional enrichment analysis of Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Set Enrichment Analysis (GSEA), supported by linear regression model and operating characteristic curve (ROC) curve analysis, and summarized the role of CRGs in preeclampsia. RESULTS:A total of 2831 differentially expressed genes related to PE were screened through multiple database analyses. After further intersection with 19 reported CRGs, 5 CRGs have been closely associated with the pathogenesis of PE, including NFE2L2, PDHA1, PDHB, DLD and GLS. NFE2L2 was identified as a key central gene. Pearson correlation analysis showed that CRGs could be related to several maternal and fetal outcome factors, including the highest pregnancy blood pressure, placenta weight, umbilical blood flow pulsatility index (PI), and neonatal weight. Linear regression equation revealed that the expression of NFE2L2 is negatively correlated with the highest pregnancy blood pressure and umbilical blood flow PI but positively correlated with placental weight and neonatal weight. QRT-PCR showed that the expression of these CRGs was significantly lower in placental tissues. CONCLUSIONS:This cuproptosis pattern may be a potential prognostic factor in patients with PE and could provide new insights into disease progression. 10.1186/s12884-023-06215-y
Cuproptosis-related lncRNAs as potential biomarkers of AML prognosis and the role of lncRNA HAGLR/miR-326/CDKN2A regulatory axis in AML. American journal of cancer research Acute myeloblastic leukemia (AML) is the most prevalent form of AML in adults. Despite the availability of various treatment options, including radiotherapy and chemotherapy, many patients fail to respond to treatment or relapse. Copper is a necessary cofactor for all organisms; however, it turns toxic when concentrations reach a certain threshold maintained by homeostatic systems that have been conserved through evolution. However, the mechanism through which excess copper triggers cell death remains unknown. In this study, data on long non-coding RNAs (lncRNAs) related to cuproptosis were retrieved from publicly available databases. LASSO and univariate and multivariate Cox regression analyses were performed to establish an lncRNA model associated with cuproptosis specific to AML. To investigate the risk model, the Kaplan-Meier curve, principal component analysis, functional enrichment analysis, and nomographs were employed. The underlying clinicopathological characteristics were determined, and drug sensitivity predictions against the model were identified. Six cuproptosis-related lncRNA-based risk models were identified as the independent prognostic factors. By regrouping patients using a model-based method, we were able to more accurately differentiate patients according to their responses to immunotherapy. In addition, prospective compounds targeting AML subtypes have been identified. Using qRT-PCR, we examined the expression levels of six cuproptosis-associated lncRNAs in 30 clinical specimens. The cuproptosis-associated lncRNA risk-scoring model developed herein has implications in monitoring AML prognosis and in the clinical prediction of the response to immunotherapy. Furthermore, we identified and verified the ceRNA of the cuproptosis-related lncRNA HAGLR/miR-326/CDKN2A regulatory axis using bioinformatic tools. HAGLR is highly expressed in AML and AML cell lines. HAGLR inhibition significantly reduced the proliferation of AML cells and promoted apoptosis. Elesclomol promotes the degradation of CDKN2A and inhibits the proliferation of AML cells. Elesclomol combined with si-HAGLR inhibited the AML progression of AML both and .
Comprehensive analysis of cuproptosis and copper homeostasis genotyping and related immune land scape in lung adenocarcinoma. Scientific reports Cuproptosis is a manner of cell death which is related to the homeostasis of copper ions in the cellular environment and is expected to open a new direction of anti-tumor therapy. However, the studies on cuproptosis and copper homeostasis in lung adenocarcinoma (LUAD) are still limited. In this study, we identified new cuproptosis and copper homeostasis related genes (CHRGs) which were effective in stratifying genotyping clusters with survival differences based on transcriptomic data obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). Weighted Gene Co-expression Network Analysis (WGCNA) further expands the screening boundary of CHRGs, and finally we established a 10-CHRGs-based prognostic signature using lasso-penalized cox regression method, which were validated in GSE30219. Comprehensive bioinformatics analysis revealed these genes are potential regulators of modulating immunotherapy efficacy, drug resistance, tumor microenvironment infiltration, and tumor mutation patterns. Lastly, the scRNA-seq datasets GSE183219 and GSE203360 offers the evidences that CHRGs signature are mainly distributed in cancer epithelial cells, real time quantitative polymerase chain reaction (RT-qPCR) also confirmed the differential expression of these genes between normal lung cell line and lung adenocarcinoma cell lines. Collectively, our findings revealed new cuproptosis and copper homeostasis related genotyping clusters and genes which may play important roles in predicting prognosis, influencing tumor microenvironment and drug efficacy in LUAD patients. 10.1038/s41598-023-43795-3
Potential Role of Cuproptosis-Related Lncrna in Prognosis and Immunotherapy of Thyroid Carcinoma. Iranian journal of public health Background:Cuproptosis-related long non-coding RNA (lncRNA) disease is associated with the development and progression of tumors. We aimed to investigate the prediction of cuproptosis-related lncRNA on the prognosis and immunotherapy of patients with thyroid carcinoma (THCA). Methods:The thyroid cancer-associated expression data and lnc RNAs data were downloaded from The Cancer Genome Atlas (TCGA) and Ensembl database. The prognostic model of cuproptosis-related lncRNAs was successfully constructed through Lasso regression analysis and Cox regression analysis. Then, the prognostic value of prognostic model of cuproptosis-related lncRNAs was tested through the survival analysis, ROC curves and nomographic charts. Finally, the prognostic model of cuproptosis-related lncRNAs associated with immunity and mutational load of tumors was analyzed, and potential targeted drugs for THCA were predicted. Results:A cuproptosis-related lncRNA model of THCA (AC026100.1, AF235103.3, LNCSRLR) was successfully constructed, which has an independent prognostic value. Moreover, the cuproptosis-related lncRNA model was associated with immune signatures and mutational load in most tumors, showing its high correlation with the sensitivity of targeted drugs such as 5-Fluorouracil, Bleomycin, Rapamycin and Sunitinib. Conclusion:The cuproptosis-related lncRNA model of THCA has promising applications in the treatment and prognosis of THCA. 10.18502/ijph.v52i5.12718
A cuproptosis-related lncRNA signature identified prognosis and tumour immune microenvironment in kidney renal clear cell carcinoma. Frontiers in molecular biosciences Kidney renal clear cell carcinoma (KIRC) is a heterogeneous malignant tumor with high incidence, metastasis, and mortality. The imbalance of copper homeostasis can produce cytotoxicity and cause cell damage. At the same time, copper can also induce tumor cell death and inhibit tumor transformation. The latest research found that this copper-induced cell death is different from the known cell death pathway, so it is defined as cuproptosis. We included 539 KIRC samples and 72 normal tissues from the Cancer Genome Atlas (TCGA) in our study. After identifying long non-coding RNAs (lncRNAs) significantly associated with cuproptosis, we clustered 526 KIRC samples based on the prognostic lncRNAs and obtained two different patterns (Cuproptosis.C1 and C2). C1 indicated an obviously worse prognostic outcome and possessed a higher immune score and immune cell infiltration level. Moreover, a prognosis signature (CRGscore) was constructed to effectively and accurately evaluate the overall survival (OS) of KIRC patients. There were significant differences in tumor immune microenvironment (TIME) and tumor mutation burden (TMB) between CRGscore-defined groups. CRGscore also has the potential to predict medicine efficacy. 10.3389/fmolb.2022.974722
Identification of a cuproptosis-related lncRNA prognostic signature in lung adenocarcinoma. Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico PURPOSE:Cuproptosis-related long non-coding RNA (lncRNA) diseases are associated with the occurrence and development of tumors. This study aimed to investigate whether cuproptosis-related lncRNA can predict the prognosis of patients with lung adenocarcinoma (LUAD). METHODS:Cuproptosis-related lncRNA prognosis (CLPS) model was successfully constructed through cox regression and lasso regression analyses. Then, the prognostic value of CLPS model was tested through the survival analysis, the ROC curve and the nomogram. Finally, the correlation of CLPS model with tumor immunity and tumor mutation burden was analyzed, and the potential susceptibility of drugs for LUAD were predicted. RESULTS:CLPS model for LUAD (AC090948.1, CRIM1-DT, AC026356.2, AC004832.5, AL161431.1) was successfully constructed, which has an independent prognostic value. Furthermore, the risk score of CLPS model was correlated with tumor immune characteristics and immune escape, which can predict the sensitivity of drugs including Cisplatin, Etoposide, Gemcitabine, and Erlotinib. CONCLUSIONS:In conclusion, it was found that CLPS model was associated with tumor immunity and tumor mutation load, which also predicted four potentially sensitive drugs for LUAD patients at different risks. 10.1007/s12094-022-03057-6
A novel defined cuproptosis-related gene signature for predicting the prognosis of lung adenocarcinoma. Frontiers in genetics Lung adenocarcinoma (LUAD) has become the most prevalent histologic subset of primary lung cancer, and effective innovative prognostic models are needed to enhance the feasibility of targeted therapies for the disease. Programmed cell death (PCD) performs an integral function in the origin and treatment of cancer. Some PCD-related effective signatures for predicting prognosis in LUAD patients could provide potential therapeutic options in LUAD. A copper-dependent cell death referred to as cuproptosis is distinct from known PCD. However, whether cuproptosis is associated with LUAD patients' prognoses and the potential roles of cuproptosis-related genes involved is still unknown. For the prediction of LUAD prognosis, we developed a unique cuproptosis-associated gene signature. In The Cancer Genome Atlas (TCGA) cohort, the score derived from the risk signature on the basis of six cuproptosis-related genes was found to independently serve as a risk factor for anticipating lung cancer-related death. The differentially expressed genes between the high- and low-risk groups were linked to the cilium-related function. LUAD patients' prognoses may now be predicted by a unique gene signature identified in this work. This discovery also provides a substantial foundation for future research into the links between cuproptosis-associated genes and cilium-related function in LUAD patients. 10.3389/fgene.2022.975185
Cuproptosis/OXPHOS tendency prediction of prognosis and immune microenvironment of esophageal squamous cell carcinoma: Bioinformatics analysis and experimental validation. Gene BACKGROUND:Cuproptosis is a newly discovered cell death mechanism that relies on mitochondrial respiration, for which oxidative phosphorylation (OXPHOS) is an essential part. However, the detailed mechanisms of cuproptosis associated with OXPHOS in esophageal squamous cell carcinoma (ESCC) and how this correlation affects prognosis still remains unclear. METHODS:scRNA-seq data of ESCC were downloaded from SRA (Sequence Read Archive) database. "AUCell" algorithm was used to grouping epithelial cells according to cuproptosis and OXPHOS score. Cell-cell communication, Pseudo-time Trajectory and transcription factor enrichment analysis were repectively conducted by "CellChat", "monocle3" package and "pySCENIC" algorithm. Univariate and LASSO cox regression analysis were used to construct the prognostic cuproptosis-OXPHOS signature. Finally, CCK-8 assay and DCFH-DA staining assay were respectively validated the sensitive and ROS production of elesclomol. RESULTS:scRNA-seq data were analyzed to identify 10 core cell types. According to the median scores for cuproptosis and OXPHOS, malignant epithelial cells were divided into double high, double low, and mixed groups. The double high group distributed at the end of the pseudo-time trajectory and harbored HMGA1(+) as specific transcriptional regulons. Knockdown of HMGA1 partly reversed the inhibition of cell viability visualized by CCK-8 assay, while reactive oxygen species (ROS) production by elesclomol was enhanced after HMGA1 silencing. Furthermore, the immunosuppressive signal was significantly increased in the double high group detected by 'CellChat' in single-cell data and 'ssGSEA' in bulk data followed by 'CIBERSORTx' algorithm. Finally, a new cuproptosis-OXPHOS prognostic signature (CNN2, ATP6V0E1, PSMD6, CCDC25, IGFBP2, MT1E, and RPS4Y1) was constructed for the prediction of the prognosis, and a high-risk group corresponding to a more sensitive tendency to erlotinib, dasatinib, and bosutinib treatment was identified. CONCLUSIONS:Our study revealed the relationship between OXPHOS and tendency of cuproptosis in ESCC, and malignant cells with this characteristic exerted immunosuppressive signals and indicated poor prognosis. Furthermore, we constructed the regulatory network in high cuproptosis-OXPHOS ESCC and identified HMGA1 as a potential regulator molecule of cuproptosis mediated by elesclomol. 10.1016/j.gene.2024.148156
Machine learning-based identification of cuproptosis-related markers and immune infiltration in severe community-acquired pneumonia. The clinical respiratory journal BACKGROUND:Severe community-acquired pneumonia (SCAP) is one of the world's most common diseases and a major etiology of acute respiratory distress syndrome (ARDS). Cuproptosis is a novel form of regulated cell death that can occur in various diseases. METHODS:Our study explored the degree of immune cell infiltration during the onset of severe CAP and identified potential biomarkers related to cuproptosis. Gene expression matrix was obtained from GEO database indexed GSE196399. Three machine learning algorithms were applied: The least absolute shrinkage and selection operator (LASSO), the random forest, and the support vector machine-recursive feature elimination (SVM-RFE). Immune cell infiltration was quantified by single-sample gene set enrichment analysis (ssGSEA) scoring. Nomogram was constructed to verify the applicability of using cuproptosis-related genes to predict the onset of severe CAP and its deterioration toward ARDS. RESULTS:Nine cuproptosis-related genes were differentially expressed between the severe CAP group and the control group: ATP7B, DBT, DLAT, DLD, FDX1, GCSH, LIAS, LIPT1, and SLC31A1. All 13 cuproptosis-related genes were involved in immune cell infiltration. A three-gene diagnostic model was constructed to predict the onset of severe CAP: GCSH, DLD, and LIPT1. CONCLUSION:Our study confirmed the involvement of the newly discovered cuproptosis-related genes in the progression of SCAP. 10.1111/crj.13633
Comprehensive analysis of cuproptosis-related long noncoding RNA for predicting prognostic and diagnostic value and immune landscape in colorectal adenocarcinoma. Human genomics BACKGROUND:Cuproptosis, as a copper-induced mitochondrial cell death, has attracted extensive attention recently, especially in cancer. Although some key regulatory genes have been identified in cuproptosis, the related lncRNAs have not been further studied. Exploring the prognostic and diagnostic value of cuproptosis-related lncRNAs (CRLs) in colon adenocarcinoma and providing guidance for individualized immunotherapy for patients are of great significance. RESULTS:A total of 2003 lncRNAs were correlated with cuproptosis genes and considered as CRLs. We screened 33 survival-associated CRLs and established a prognostic signature base on 7 CRLs in the training group. The patients in the low-risk group had better outcomes in both training group (P < 0.001) and test group (P = 0.016). More exciting, our model showed good prognosis prediction in both stage I-II (P = 0.020) and stage III-IV (P = 0.001). The nomogram model could further improve the accuracy of prognosis prediction. Interestingly, glucose-related metabolic pathways, which were closely related to cuproptosis, were enriched in the low-risk group. Meanwhile, the immune infiltration scores were lower in the high-risk group. The high-risk group was more sensitive to OSI.906 and ABT.888, while low-risk group was more sensitive to Sorafenib. Three lncRNAs, FALEC, AC083967.1 and AC010997.4, were highly expressed in serum of COAD patients, and the AUC was 0.772, 0.726 and 0.714, respectively, indicating their valuable diagnostic value. CONCLUSIONS:Our research constructed a prognostic signature based on 7 CRLs and found three promising diagnostic markers for COAD patients. Our results provided a reference to the personalized immunotherapy strategies. 10.1186/s40246-023-00469-5
A novel cuproptosis-related gene signature predicting overall survival in pediatric neuroblastoma patients. Frontiers in pediatrics Background:Cuproptosis is a novel cell death pathway, and the regulatory mechanism in pediatric neuroblastoma (NB) remains to be explored. We amid to investigate cuproptosis-related genes (CRGs) and construct a novel prognostic model for NB. Methods:To evaluate the role of CRGs on the clinical outcome of pediatric NB, the dataset of pediatric patients with NB of GSE49710 dataset was used to identify CRGs in association with patient overall survival (OS), and TARGET database was used to validate the predictive value of cuproptosis-related signature (CRG-score). The correlation between the CRG-score and the tumor microenvironment (TME), clinicopathological parameters, chemotherapy, and the response to immunotherapy was explored. Results:Overall, 31 CRGs were associated with OS in the univariate Cox regression analysis. Then, a prognostic model incorporating 9 CRGs was established with the LASSO regression analysis, which could classify all NB patients into two CRG-score groups. The performance of the signature was verified in both internal and external validation cohorts. Multivariate analysis indicated that the CRG-score was an independent prognostic indicator, and stratification analysis still showed a high predictive ability for survival prediction. The CRG-score was associated with age, MYCN status, INSS stage, and COG risk. Additionally, the higher CRG-score group exhibited lower immune scores, immune cell infiltration, and decreased expression of immune checkpoints. Meanwhile, the CRG-score could predict the drug sensitivity of administering chemotherapeutic agents for NB patients. Conclusions:Our comprehensive analysis of cuproptosis-associated genes in NB provides a new approach for the prediction of clinical outcomes and more effective treatment strategies. 10.3389/fped.2022.1049858
Risk model of hepatocellular carcinoma based on cuproptosis-related genes. Frontiers in genetics Owing to the heterogeneity displayed by hepatocellular carcinoma (HCC) and the complexity of tumor microenvironment (TME), it is noted that the long-term effectiveness of the cancer therapy poses a severe clinical challenge. Hence, it is essential to categorize and alter the treatment intervention decisions for these tumors. "ConsensusClusterPlus" tool was used for developing a secure molecular classification system that was based on the cuproptosis-linked gene expression. Furthermore, all clinical properties, pathway characteristics, genomic changes, and immune characteristics of different cell types involved in the immune pathways were also assessed. Univariate Cox regression and the least absolute shrinkage and selection operator (Lasso) analyses were used for designing the prognostic risk model associated with cuproptosis. Three cuproptosis-linked subtypes (clust1, clust2, and clust3) were detected. Out of these, Clust3 showed the worst prognosis, followed by clust2, while Clust1 showed the best prognosis. Three subtypes had significantly different enrichment in pathways related to Tricarboxylic Acid (TCA) cycle, cell cycle, and cell senescence ( < 0.01). The clust3 subtype with poor prognosis had a low "ImmuneScore" and low immune cell infiltration, and the three subtypes had significant differences in the antigen processing and presentation pathway of the macrophages. Clust1 had a low TIDE score and was sensitive to immunotherapy. Then, according to the prognosis-related genes of cuproptosis, a prognosis risk model related to cuproptosis was constructed, containing seven genes (KIF2C, PTTG1, CENPM, CDC20, CYP2C9, SFN, and CFHR3). "High" group had a higher TIDE score compared to the TIDE score value shown by the "Low" group, which benefited less from immunotherapy, whereas the "High" group patients were more sensitive to the conventional drugs. Finally, the prognosis risk model related to cuproptosis was combined with clinical pathological characteristics to further improve the prognostic model and survival prediction. Three new molecular subgroups based on cuproptosis-linked genes were revealed, and a cuproptosis-related prognostic risk model comprising seven genes was established in this study, which could assist in predicting the prognosis and identifying the patients benefit from immunotherapy. 10.3389/fgene.2022.1000652
Identification and immuno-infiltration analysis of cuproptosis regulators in human spermatogenic dysfunction. Frontiers in genetics Cuproptosis seems to promote the progression of diverse diseases. Hence, we explored the cuproptosis regulators in human spermatogenic dysfunction (SD), analyzed the condition of immune cell infiltration, and constructed a predictive model. Two microarray datasets (GSE4797 and GSE45885) related to male infertility (MI) patients with SD were downloaded from the Gene Expression Omnibus (GEO) database. We utilized the GSE4797 dataset to obtain differentially expressed cuproptosis-related genes (deCRGs) between SD and normal controls. The correlation between deCRGs and immune cell infiltration status was analyzed. We also explored the molecular clusters of CRGs and the status of immune cell infiltration. Notably, weighted gene co-expression network analysis (WGCNA) was used to identify the cluster-specific differentially expressed genes (DEGs). Moreso, gene set variation analysis (GSVA) was performed to annotate the enriched genes. Subsequently, we selected an optimal machine-learning model from four models. Finally, nomograms, calibration curves, decision curve analysis (DCA), and the GSE45885 dataset were utilized to verify the predictions' accuracy. Among SD and normal controls, we confirmed that there are deCRGs and activated immune responses. Through the GSE4797 dataset, we obtained 11 deCRGs. ATP7A, ATP7B, SLC31A1, FDX1, PDHA1, PDHB, GLS, CDKN2A, DBT, and GCSH were highly expressed in testicular tissues with SD, whereas LIAS was lowly expressed. Additionally, two clusters were identified in SD. Immune-infiltration analysis showed the existing heterogeneity of immunity at these two clusters. Cuproptosis-related molecular Cluster2 was marked by enhanced expressions of ATP7A, SLC31A1, PDHA1, PDHB, CDKN2A, DBT, and higher proportions of resting memory CD4 T cells. Furthermore, an eXtreme Gradient Boosting (XGB) model based on 5-gene was built, which showed superior performance on the external validation dataset GSE45885 (AUC = 0.812). Therefore, the combined nomogram, calibration curve, and DCA results demonstrated the accuracy of predicting SD. Our study preliminarily illustrates the relationship between SD and cuproptosis. Moreover, a bright predictive model was developed. 10.3389/fgene.2023.1115669
A cuproptosis-related lncRNAs signature for prognosis, chemotherapy, and immune checkpoint blockade therapy of low-grade glioma. Frontiers in molecular biosciences Cuproptosis is a new type of cell death that is associated with mitochondrial respiration of the tricarboxylic acid cycle. Previous studies showed that long non-coding RNAs (lncRNAs) regulated low-grade glioma (LGG) progression. However, the potential applications of cuproptosis-related lncRNAs (CRLs) in LGG were not explored. A comprehensive analysis was performed in The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) cohorts. We first screened two distinct cuproptosis subtypes based on prognostic CRLs using consensus clustering. To facilitate individualized survival prediction in LGG, we constructed a prognostic signature (including CRNDE, HAR1A, and FAM181A-AS1) in the TCGA dataset. The prognostic signature exhibited excellent predictive ability and reliability, which was validated in the CGGA_325 and CGGA_693 datasets. Notably, patients in the high-risk group had increased immune cell infiltration and expression of immune checkpoints, which indicated that they may benefit more from immune checkpoint blockade (ICB) therapy. Finally, the prognostic signature screened the population with sensitivity to chemotherapy and ICB therapy. In summary, this study initially explored the mechanism of CRLs in LGG and provides some insights into chemotherapy and ICB therapy of LGG. 10.3389/fmolb.2022.966843
A cuproptosis-related long non-coding RNA signature to predict the prognosis and immune microenvironment characterization for lung adenocarcinoma. Translational lung cancer research Background:Cuproptosis or copper-dependent cell death is a newly identified non-apoptotic cell death pathway which plays a critical role in the development of multiple cancers. Long non-coding RNAs (lncRNAs) are increasingly recognized as crucial regulators of programmed cell death and lung adenocarcinoma (LUAD) development, and a comprehensive understanding of cuproptosis-related lncRNAs may improve prognosis prediction of LUAD. However, few studies have explored the association of cuproptosis-related lncRNAs with the prognosis of LUAD. Methods:The RNA sequencing data and corresponding clinical information of patients were extracted from The Cancer Genome Atlas (TCGA) database. Five hundred LUAD patients were randomly divided into a training (n=250) and a testing cohort (n=250). Pearson correlations were performed to identify cuproptosis-related lncRNAs, and univariate Cox regression was performed to screen prognostic lncRNAs. A cuproptosis-related lncRNAs prognostic signature (CLPS) was constructed by the least absolute shrinkage and selection operator Cox regression. Kaplan-Meier analysis, receiver operating characteristic curves, and multivariate Cox regression were performed to verify the prognostic performance of CLPS. Additionally, immune cell infiltration was estimated using the single-sample gene-set enrichment analysis. pRRophetic algorithm and Tumor Immune Dysfunction and Exclusion algorithm were used to assess the immunotherapy and chemotherapy response, respectively. Results:CLPS was established based on 61 cuproptosis-related prognostic lncRNAs and exhibited a satisfactory performance predicting LUAD patients' survival (area under the curve at 1, 3, 5 years was 0.784, 0.749, 0.775, respectively). multivariate Cox analysis confirmed the independent prognostic effect of CLPS (hazard ratio: 1.128; 95% confidence interval: 1.071-1.189; P<0.001), and a nomogram containing it exhibited robust validity in prognostic prediction. We further demonstrated a higher CLPS-risk score was associated with lower levels of signatures including immune cell infiltration, immune activation, and immune checkpoints. Conclusions:The CLPS serves as an effective predictor for the prognosis and therapeutic responses of LUAD patients. Our findings provide promising novel biomarkers and therapeutic targets for LUAD. 10.21037/tlcr-22-660
Identification of cuproptosis-related subtypes in lung adenocarcinoma and its potential significance. Frontiers in pharmacology Cuproptosis is a novel and unique cell death mode that has attracted significant interest in recent years. Little is currently known about whether cuproptosis-related genes (CRGs) are associated with the pathophysiology and survival of patients with lung adenocarcinoma (LUAD). The present study sought to characterize the transcriptional and genetic alteration of CRGs in LUAD and its potential significance in the tumor microenvironment and predicting the prognosis of LUAD. The secondary eventual aim was to study the role of CRGs in predicting immunotherapy response and its clinical value combined with the TNM stage. We found that several CRGs, including FDX1, DLD, SLC31A1, and MTF1, were enriched in macrophages in our single-cell RNA-seq data. Three distinct molecular subtypes were identified and correlated with clinicopathological characteristics, prognosis, biological pathways, and tumor microenvironment (TME) in LUAD. We developed a cuproptosis-related gene score (CRG_score) and validated it in three independent cohorts and clinical subtypes. The low CRG_score group, characterized by a greater immune score, immunophenoscore (IPS), lower tumor immune dysfunction and exclusion (TIDE) score, and T-cell dysfunction score, had a better prognosis, suggesting that the low CRG_score group responded more favorably to immunotherapy, which was validated in the anti-PD-1/L1 immunotherapy cohort (IMvigor210). In contrast, the high CRG_score group was more sensitive to targeted therapy and chemotherapy, with a higher cancer stem cell (CSC) index and lower half-maximal inhibitory concentration (IC50) for many drugs. Given the established crosstalk between CRG_score and tumor TNM stage, we developed an accurate nomogram for clinical application of the CRG_score. Taken together, our rigorous and comprehensive examination of CRGs in LUAD identified their potential functions in TME, clinicopathological characteristics, drug sensitivity, and prognosis. These findings improve the current understanding of cuproptosis in LUAD, paving the way for more accurate prognosis assessment and tailored treatment for this patient population. 10.3389/fphar.2022.934722
Cuproptosis-related gene signature correlates with the tumor immune features and predicts the prognosis of early-stage lung adenocarcinoma patients. Frontiers in genetics Although a majority of early-stage lung adenocarcinoma (es-LUAD) patients have a favorable prognosis, there are still some cases with a risk of recurrence and metastasis. Cuproptosis is a new form of death that differs from other programmed cell death. However, no study has been reported for setting a prognostic model of es-LUAD using cuproptosis pattern-related genes. Using multiple R packages, the data from the GEO database was processed, and es-LUAD patients was classified into two patterns based on cuproptosis-related genes. Key differentially expressed genes (DEGs) in the two patterns were screened to construct a prognostic signature to assess differences in biological processes and immunotherapy responses in es-LUAD. Tumor microenvironment (TME) in es-LUAD was analyzed using algorithms such as TIMER and ssGSEA. Then, a more accurate nomogram was constructed by combining risk scores with clinical factors. Functional enrichment analysis revealed that DEGs in two patterns were correlated with organelle fission, nuclear division, chromosome segregation, and cycle-related pathways. Univariate Cox regression and Lasso-Cox regression analyses identified six prognostic genes: ASPM, CCNB2, CDC45, CHEK1, NCAPG, and SPAG5. Based on the constructed model, we found that the high-risk group patients had higher expression of immune checkpoints (CTLA4, LAG3, PD-L1, TIGIT and TIM3), and a lower abundance of immune cells. Lastly, the nomogram was highly accurate in predicting the 1-, 3-, and 5-year survival status of patients with es-LUAD based on risk scores and clinical factors. The cuproptosis pattern-related signature can serve as a potential marker for clinical decision-making. It has huge potential in the future to guide the frequency of follow-up and adjuvant therapy for es-LUAD patients. 10.3389/fgene.2022.977156
Identification of cuproptosis-related genes and immune infiltration in dilated cardiomyopathy. International journal of cardiology BACKGROUND:Dilated cardiomyopathy (DCM) is a leading cause of heart failure. Cuproptosis is involved in various diseases, although its role in DCM is still unclear. Here, this study aims to investigate the feasibility of using genes related to cuproptosis as diagnostic biomarkers for DCM and the association of their expression with immune infiltration and drug target in cardiac tissue. METHODS:Gene expression data from nonfailure (NF) and DCM samples were retrieved from the GEO database. Cuproptosis scores were calculated using single-sample gene set enrichment analysis (ssGSEA). Weighted gene co-expression network analysis (WGCNA) was used to screen key modules associated with DCM and cuproptosis. Random forest and least absolute shrinkage and selection operator (LASSO) were applied to identify signature genes. Finally, immune cell infiltration was assessed using ssGSEA. mRNA-miRNA-lncRNA regulatory networks and chemical-drug regulatory networks based on signature genes were analyzed by Cytoscape. RESULTS:8 modules were aggregated by WGCNA, among which MEblue was significantly associated with cuproptosis scores and DCM. A diagnostic model made up of six signature genes including SEPTIN1, CLEC11A, ISG15, P3H3, SDSL, and INKA1 was selected. Furthermore, immune infiltration studies showed significant differences between DCM and NF. Drugs networks and ceRNA regulatory network based on six signature genes were successfully constructed. CONCLUSION:Six signature genes (SEPTIN1, CLEC11A, ISG15, P3H3, SDSL, and INKA1) were identified as novel diagnostic biomarkers in DCM. In addition, the expression of these genes was associated with immune cell infiltration, suggesting that cuproptosis may be involved in the immune regulation of DCM. 10.1016/j.ijcard.2023.131702
Prognostic implication of cuproptosis related genes associates with immunity in Ewing's sarcoma. Translational oncology Growing evidence demonstrated that cuproptosis play critical roles in human cancers. We aimed to identify the roles of cuproptosis related genes (CRGs) in prognosis and immunity of Ewing's sarcoma. The data of GSE17674 and GSE63156 were obtained from GEO. The expression of 17 CRGs and immune cells were explored, then correlation was analyzed. Based on CRGs, two molecular clusters were identified by consensus clustering algorithm. KM survival and IME features including immune cells, immune response, checkpoint genes between clusters were evaluated. NFE2L2, LIAS, and CDKN2A were screened out as prognostic signatures by univariate, LASSO and step regression. A risk model was established, and validated by KM method with p = 0.0026, and perfect AUC values. The accuracy of risk model was also well validated in external dataset. A nomogram was constructed and evaluated by calibration curves and DCA. Low level of immune cells, immune response, and enriched checkpoint genes were found in high-risk group. GSEA of signatures and GSVA of ES-related pathways revealed the potential molecular mechanism involved in ES progression. Several drugs showed sensitivity to ES samples. DEGs between risk groups were screened out, and function enrichment was conducted. Finally, scRNA analysis of GSE146221 was done. NFE2L2, and LIAS played crucial role in the evolution of ES by pesudotime and trajectory methods. Our study provided new aspects for further research in ES. 10.1016/j.tranon.2023.101646
Prognostic and immune microenvironment analysis of cuproptosis-related LncRNAs in breast cancer. Functional & integrative genomics Breast cancer is the most common tumor and the leading cause of cancer death in women. Cuproptosis is a new type of cell death, which can induce proteotoxic stress and eventually lead to cell death. Therefore, regulating copper metabolism in tumor cells is a new therapeutic approach. Long non-coding RNAs play an important regulatory role in immune response. At present, cuproptosis-related lncRNAs in breast cancer have not been reported. Breast cancer RNA sequencing, genomic mutations, and clinical data were downloaded from The Cancer Genome Atlas (TCGA). Patients with breast cancer were randomly assigned to the train group or the test group. Co-expression network analysis, Cox regression method, and least absolute shrinkage and selection operator (LASSO) method were used to identify cuproptosis-related lncRNAs and to construct a risk prognostic model. The prediction performance of the model is verified and recognized. In addition, the nomogram was used to predict the prognosis of breast cancer patients. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and immunoassay were used to detect the differences in biological function. Tumor mutation burden (TMB) was used to measure immunotherapy response. A total of 19 cuproptosis genes were obtained and a prognostic model based on 10 cuproptosis-related lncRNAs was constructed. Kaplan-Meier survival curves showed statistically significant overall survival (OS) between the high-risk and low-risk groups. Receiver operating characteristic curve (ROC) and principal component analysis (PCA) show that the model has accurate prediction ability. Compared with other clinical features, cuproptosis-related lncRNAs model has higher diagnostic efficiency. Univariate and multivariate Cox regression analysis showed that risk score was an independent prognostic factor for breast cancer patients. In addition, the nomogram model analysis showed that the tumor mutation burden was significantly different between the high-risk and low-risk groups. Of note, the additive effect of patients in the high-risk group and patients with high TMB resulted in reduced survival in breast cancer patients. Our study identified 10 cuproptosis-related lncRNAs, which may be promising biomarkers for predicting the survival prognosis of breast cancer. 10.1007/s10142-023-00963-y
Identification of Cuproptosis Clusters and Integrative Analyses in Parkinson's Disease. Brain sciences Parkinson's disease (PD) is the second most common neurodegenerative disease; it mainly occurs in the elderly population. Cuproptosis is a newly discovered form of regulated cell death involved in the progression of various diseases. Combining multiple GEO datasets, we analyzed the expression profile and immunity of cuproptosis-related genes (CRGs) in PD. Dysregulated CRGs and differential immune responses were identified between PD and non-PD substantia nigra. Two CRG clusters were defined in PD. Immune analysis suggested that CRG cluster 1 was characterized by a high immune response. The enrichment analysis showed that CRG cluster 1 was significantly enriched in immune activation pathways, such as the Notch pathway and the JAK-STAT pathway. KIAA0319, AGTR1, and SLC18A2 were selected as core genes based on the LASSO analysis. We built a nomogram that can predict the occurrence of PD based on the core genes. Further analysis found that the core genes were significantly correlated with tyrosine hydroxylase activity. This study systematically evaluated the relationship between cuproptosis and PD and established a predictive model for assessing the risk of cuproptosis subtypes and the outcome of PD patients. This study provides a new understanding of PD-related molecular mechanisms and provides new insights into the treatment of PD. 10.3390/brainsci13071015
A novel cuproptosis-related lncRNA signature predicts the prognosis and immune landscape in bladder cancer. Frontiers in immunology Background:Bladder cancer (BLCA) is one of the deadliest diseases, with over 550,000 new cases and 170,000 deaths globally every year. Cuproptosis is a copper-triggered programmed cell death and is associated with the prognosis and immune response of various cancers. Long non-coding RNA (lncRNA) could serve as a prognostic biomarker and is involved in the progression of BLCA. Methods:The gene expression profile of cuproptosis-related lncRNAs was analyzed by using data from The Cancer Genome Atlas. Cox regression analysis and least absolute shrinkage and selection operator analysis were performed to construct a cuproptosis-related lncRNA prognostic signature. The predictive performance of this signature was verified by ROC curves and a nomogram. We also explored the difference in immune-related activity, tumor mutation burden (TMB), tumor immune dysfunction and exclusion (TIDE), and drug sensitivity between the high- and low-risk groups. Results:We successfully constructed a cuproptosis-related lncRNA prognostic signature for BLCA including eight lncRNAs (RNF139-AS1, LINC00996, NR2F2-AS1, AL590428.1, SEC24B-AS1, AC006566.1, UBE2Q1-AS1, and AL021978.1). Multivariate Cox analysis suggested that age, clinical stage, and risk score were the independent risk factors for predicting prognosis of BLCA. Further analysis revealed that this signature not only had higher diagnostic efficiency compared to other clinical features but also had a good performance in predicting the 1-year, 3-year, and 5-year overall survival rate in BLCA. Notably, BLCA patients with a low risk score seemed to be associated with an inflamed tumor immune microenvironment and had a higher TMB level than those with a high risk score. In addition, patients with a high risk score had a higher TIDE score and a higher half maximal inhibitory concentration value of many therapeutic drugs than those with a low risk score. Conclusion:We identified a novel cuproptosis-related lncRNA signature that could predict the prognosis and immune landscape of BLCA. 10.3389/fimmu.2022.1027449
A comprehensive cuproptosis score and associated gene signatures reveal prognostic and immunological features of idiopathic pulmonary fibrosis. Frontiers in immunology Background:Cuproptosis, the most recently identified and regulated cell death, depends on copper ions . Copper regulates the pathogenesis of Idiopathic pulmonary fibrosis (IPF), but the mechanism of action underlying cuproptosis in IPF remains unclear. Methods:We identified three cuproptosis patterns based on ten cuproptosis-related genes using unsupervised consensus clustering. We quantified these patterns using a PCA algorithm to construct a cuproptosis score. ssGSEA and the Cibersort algorithm assessed the immune profile of IPF patients. GSEA and GSVA were used to analyze the functional differences in different molecular patterns. Drug susceptibility prediction based on cuproptosis scores and meaningful gene markers was eventually screened in combination with external public data sets, experiments and our cases. Results:Of the three types of cuproptosis-related clusters identified in the study, patients in the clusterA, geneclusterB, and score-high groups showed improved prognoses. Moreover, each cluster exhibited differential immune characteristics, with the subtype showing a poorer prognosis associated with an immune overreaction. Cuproptosis score can be an independent risk factor for predicting the prognosis of IPF patients. GSEA showed a significant functional correlation between the score and cuproptosis. The genes , and , were identified as prognostic-related signatures in IPF patients. The functional role of immune regulation in IPF was further explored by correlating essential genes with immune factors. Also, the nomogram constructed by cumulative information from gene markers and cuproptosis score showed reliable clinical application. Conclusions:Cuproptosis patterns differ significantly in the prognosis and immune characteristics of IPF patients. The cuproptosis score and five gene signatures can provide a reliable reference in the prognosis and diagnosis of IPF. 10.3389/fimmu.2023.1268141
Identification of cuproptosis-related genes for predicting the development of prostate cancer. Open medicine (Warsaw, Poland) Copper can be toxic at very high intracellular concentrations and can inhibit prostate cancer (PCa) progression. Recently, a study reported the mechanism of cuproptosis and the potentially associated genes. However, the function of these cuproptosis-related genes in PCa remains unknown. Based on the RNA sequence and clinical data from public databases, we analyzed the clinical value of cuproptosis-related genes in PCa. , , , and were expressed differently between normal and PCa tissues. The , , , , and genes can affect PCa progression, while and influence the patients' disease-free survival (DFS) status. The expression of , , , and did not alter upon the incidence of PCa in Chinese patients. A constructed regression model showed that , , , and can be risk factors leading to PCa in both Western and Chinese patients with PCa. The lasso regression model reflected that these genes can affect the patients' DFS status. Additionally, the cuproptosis-related genes were associated with immune cell infiltration. We also verified the high expression of and , in clinical samples. In conclusion, we identified a novel cuproptosis-related gene signature for predicting the development of PCa. 10.1515/med-2023-0717
Cuproptosis-related lncRNAs predict the clinical outcome and immune characteristics of hepatocellular carcinoma. Frontiers in genetics Cuproptosis, as a novel copper-dependent and non-apoptotic form of cell death, is induced by aggregation of lipoylated mitochondrial proteins and the instability of Fe-S cluster proteins. However, the role of cuproptosis-related long noncoding RNAs (CRLncRNAs) in hepatocellular carcinoma (HCC) has not been clearly elucidated. In this study, we identified and characterized cuproptosis-related lncRNAs in HCC. 343 HCC cases from The Cancer Genome Atlas (TCGA) with gene transcriptome data and clinical data were obtained for analysis after the screening. Univariate and multivariate Cox proportional hazards analyses were performed to establish a prognostic cuproptosis-related lncRNA signature (CRlncSig). We established a prognosis-related model consisting of nine cuproptosis-related lncRNAs: GSEC, AL158166.1, AC005479.2, AL365361.1, AC026412.3, AL031985.3, LINC00426, AC009974.2, AC245060.7, which was validated in the internal cohort. High-risk group stratified by the CRlncSig was significantly related to poor prognosis ( < 0.001). The area under the receiver operating characteristic curve (AUC) of 1 year, 3 years, and 5 years of survival were 0.813, 0.789, and 0.752, respectively. Furthermore, a prognostic nomogram including CRlncSig with clinicopathologic factors was built with favorable predictive power. In addition, GO and KEGG enrichment analysis suggested that CRlncSig was involved in many carcinogenesis and immune-related pathways. Additionally, we found that tumor microenvironment, immune infiltration, immune function, and drug response were significantly different between the high-risk and low-risk groups based on the risk model. These results highlight the value of cuproptosis-related lncRNAs on prognosis for HCC patients and provide insight into molecular and immune features underlying cuproptosis-related lncRNAs, which might play an important role in patient management and immunotherapy. 10.3389/fgene.2022.972212
A prognostic signature of cuproptosis and TCA-related genes for hepatocellular carcinoma. Frontiers in oncology Background:Hepatocellular carcinoma (HCC) is the most common malignant tumor of the liver. Cuproptosis is a newly defined form of cell death. Copper ion induces cell death by binding to the tricarboxylic acid cycle (TCA). The effect of cuproptosis-related and TCA-related genes on the clinical prognosis of HCC is still unclear. In this study, we explores the genetic changes of cuproptosis-related genes that affect the TCA process and their potential therapeutic value in HCC patients. Methods:The cuproptosis and TCA-related genes were obtained from cuproptosis-related articles and the molecular signatures database. The prognosis signatures of eight related genes were constructed using the last absolute shrinkage and selection operator (LASSO), and Receiver Operating Characteristic (ROC) curves were used to evaluate the signature. In addition, we analyzed downstream functional enrichment and immune infiltration to explore cuproptosis-inducing drugs and immunotherapeutic responses. All these analyses were validated using multiple datasets of the International Cancer Genome Consortium (ICGC). Results:TCA and copper malnutrition-related genes ( were finally included. According to the risk score, they were divided into high-risk and low-risk groups. Survival analysis showed that the overall survival (OS) of the high-risk group was significantly lower than that of the low-risk group. We established a risk prognostic feature to predict the OS of patients with HCC. Based on this feature and the clinical stage, we constructed a nomogram. Functional enrichment analysis revealed pathways related to organelle division and the cell cycle. Different risk scores had different immune abundances in immune cells (including macrophages and regulatory T-cells) and immune pathways (including antigen-presenting cells co-stimulation). Moreover, the drug sensitivity of eleschomol and PD-L1 in the high-risk group was better than that in the low-risk group. The status of somatic mutation was also closely related to the risk score. Conclusion:In this study, we established a new prediction signature of eight genes related to cuproptosis and the TCA process, which can effectively predict the prognosis of HCC patients. 10.3389/fonc.2022.1040736
Cuproptosis-related classification and personalized treatment in lower-grade gliomas to prompt precise oncology. The journal of gene medicine BACKGROUND:Cuproptosis is implicated in regulating tricarboxylic acid cycle and associated with tumor therapeutic sensitivity, patient outcomes and tumorigenesis. However, the classification and prognostic effect of cuproptosis-associated genes (CAGs), the relationship between cuproptosis and tumor microenvironment (TME) and the treatment of lower-grade glioma (LrGG) remain enigmatic. METHODS:The genetic and transcriptional alterations, prognostic value and classification related to cuproptosis were systematically analyzed. Subtypes of cuproptosis and cuproptosis score (Cuscore) were constructed and further confirmed by two external cohorts. The relationships between cuproptosis and TME, prognosis, and treatment response were also evaluated. RESULTS:Four clusters were identified based on cuproptosis-associated genes. The associations between cuproptosis-associated clusters and clinical features, prognosis, immune cell infiltration, and chemotherapy sensitivity were observed. The Cuscore is an independent prognostic indicator in LrGG patients. The nomogram is constructed according to Cuscore and clinical characteristics, and has good predictive ability and calibration. Patients with high Cuscore had a worse prognosis and advanced performance. A higher Cuscore also indicated a higher stromal score, abundant immune infiltration, and increased tumor mutation burden. A high Cuscore was remarkably related to immune checkpoint inhibitors, immunotherapy response and immune phenotype. CONCLUSIONS:This study demonstrates the clinical effect of CAGs, and suggests that cuproptosis could be a potential therapeutic target in LrGG. 10.1002/jgm.3486
A novel cuproptosis-related lncRNAs signature predicts prognosis in bladder cancer. Aging This study constructed a novel cuproptosis-related lncRNAs signature to predict the prognosis of BLCA patients. The Cancer Genome Atlas (TCGA) database was used to retrieve the RNA-seq data together with the relevant clinical information. The cuproptosis-related genes were first discovered. The cuproptosis-related lncRNAs were then acquired by univariate, the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis to create a predictive signature. An eight cuproptosis-related lncRNAs (AC005261.1, AC008074.2, AC021321.1, AL024508.2, AL354919.2, ARHGAP5-AS1, LINC01106, LINC02446) predictive signature was created. Compared with the low-risk group, the prognosis was poorer for the high-risk group. The signature served as an independent overall survival (OS) predictor. Receiver operating characteristic (ROC) curve indicated that the signature demonstrated superior predictive ability, as evidenced by the area under the curve (AUC) of 0.782 than the clinicopathological variables. When we performed a subgroup analysis of the different variables, the high-risk group's OS for BLCA patients was lower than that of the low-risk group's patients. Gene Set Enrichment Analysis (GSEA) showed that high-risk groups were clearly enriched in many immune-related biological processes and tumor-related signaling pathways. Single sample gene set enrichment analysis (ssGSEA) revealed that the immune infiltration level was different between the two groups. Finally, quantitative RT-PCR showed that AC005261.1, AC021321.1, AL024508.2, LINC02446 and LINC01106 were lowly expressed in tumor cells, while ARHGAP5-AS1 showed the opposite trend. In summary, the predictive signature can independently predict the prognosis and provide clinical treatment guidance for BLCA patients. 10.18632/aging.204861
Cuproptosis combines immune landscape providing prognostic biomarker in head and neck squamous carcinoma. Heliyon Head and neck squamous carcinomas (HNSC) are the seventh most common cancer around the world. Treatment options available today have considerable limitations in terms of efficacy. Identifying novel therapeutic targets for HNSC is, therefore, urgently needed. As a novel determined regulated cell death (RCD), Cuproptosis is correlated with the development, treatment response, and prognosis of various cancer. However, the potential role of Cuproptosis-related genes (CRGs) in the tumor microenvironment (TME) of HNSC remains unclear. To figure out whether TME cells and Cuproptosis could better predict prognosis, in this study, we analyzed the expression, mutation status, and other clinical information of 502 HNSC patients by dividing them into four clusters based on their CRGs and TME cell expression. Utilizing the LASSO-Cox method and bootstrap, we established Prognostic Cuproptosis and TME classifier, which were significantly associated with prognosis, pathways, clinical features, and immune cell infiltration in TME of HNSC. To go further, the subgroup Cup low/TMEhigh displayed a better prognosis than any others. Two GEO datasets demonstrated the proposed risk model's clinical applicability. Our GO enrichment analyses proved the conjoint effect of Cuproptosis and TME on tumor angiogenesis, proliferation, and so on. Single-cell analysis and Immunotherapy profile then provided a foundation for determining the molecular mechanisms. It revealed the prognostic risk score positively correlated with T cell activation and natural killer (NK) recruiting. As far as we know, this study is the first time to explore the involvement of CRGs regulation in the TME of HNSC. In a word, it is vital to use these findings to develop new therapeutic strategies. 10.1016/j.heliyon.2023.e15494
Identification of cuproptosis-related biomarkers in dilated cardiomyopathy and potential therapeutic prediction of herbal medicines. Frontiers in molecular biosciences Dilated cardiomyopathy (DCM) is one of the significant causes of heart failure, and the mechanisms of metabolic ventricular remodelling due to disturbances in energy metabolism are still poorly understood in cardiac pathology. Understanding the biological mechanisms of cuproptosis in DCM is critical for drug development. The DCM datasets were downloaded from Gene Expression Omnibus, their relationships with cuproptosis-related genes (CRGs) and immune signatures were analyzed. LASSO, RF, and SVM-RFE machine learning algorithms were used to identify signature genes and the eXtreme Gradient Boosting (XGBoost) model was used to assess diagnostic efficacy. Molecular clusters of CRGs were identified, and immune Infiltration analysis was performed. The WGCNA algorithm was used to identify specific genes in different clusters. In addition, AUCell was used to analyse the cuproptosis scores of different cell types in the scRNA-seq dataset. Finally, herbal medicines were predicted from an online database, and molecular docking and molecular dynamics simulations were used to support the confirmation of the potential of the selected compounds. We identified dysregulated cuproptosis genes and activated immune responses between DCM and healthy controls. Two signature genes (FDX1, SLC31A1) were identified and performed well in an external validation dataset (AUC = 0.846). Two molecular clusters associated with cuproptosis were further defined in DCM, and immune infiltration analysis showed B-cell naive, Eosinophils, NK cells activated and T-cell CD4 memory resting is significant immune heterogeneity in the two clusters. AUCell analysis showed that cardiomyocytes had a high cuproposis score. In addition, 19 and 3 herbal species were predicted based on FDX1 and SLC31A1. Based on the molecular docking model, the natural compounds Rutin with FDX1 (-9.3 kcal/mol) and Polydatin with SLC31A1 (-5.5 kcal/mol) has high stability and molecular dynamics simulation studies further validated this structural stability. Our study systematically illustrates the complex relationship between cuproptosis and the pathological features of DCM and identifies two signature genes (FDX1 and SLC31A1) and two natural compounds (Rutin and Polydatin). This may enhance our diagnosis of the disease and facilitate the development of clinical treatment strategies for DCM. 10.3389/fmolb.2023.1154920
Identification of a Novel Cuproptosis-Related Gene Signature and Integrative Analyses in Thyroid Cancer. Journal of clinical medicine Cuproptosis is a novel programmed cell death that depends on copper. The role and potential mechanism of cuproptosis-related genes (CRGs) in thyroid cancer (THCA) are still unclear. In our study, we randomly divided THCA patients from the TCGA database into a training set and a testing set. A cuproptosis-related signature consisting of six genes (SLC31A1, LIAS, DLD, MTF1, CDKN2A, and GCSH) was constructed using the training set to predict the prognosis of THCA and was verified with the testing set. All patients were classified into low- and high-risk groups according to risk score. Patients in the high-risk group had a poorer overall survival (OS) than those in the low-risk group. The area under the curve (AUC) values for 5 years, 8 years, and 10 years were 0.845, 0.885, and 0.898, respectively. The tumor immune cell infiltration and immune status were significantly higher in the low-risk group, which indicated a better response to immune checkpoint inhibitors (ICIs). The expression of six cuproptosis-related genes in our prognostic signature were verified by qRT-PCR in our THCA tissues, and the results were consistent with TCGA database. In summary, our cuproptosis-related risk signature has a good predictive ability regarding the prognosis of THCA patients. Targeting cuproptosis may be a better alternative for THCA patients. 10.3390/jcm12052014
Impact of Cuproptosis-related markers on clinical status, tumor immune microenvironment and immunotherapy in colorectal cancer: A multi-omic analysis. Computational and structural biotechnology journal Background:Cuproptosis, a novel identified cell death form induced by copper, is characterized by aggregation of lipoylated mitochondrial enzymes and the destabilization of Fe-S cluster proteins. However, the function and potential clinical value of cuproptosis and cuproptosis-related biomarkers in colorectal cancer (CRC) remain largely unknown. Methods:A comprehensive multi-omics (transcriptomics, genomics, and single-cell transcriptome) analysis was performed for identifying the influence of 16 cuproptosis-related markers on clinical status, molecular functions and tumor microenvironment (TME) in CRC. A novel cuproptosis-related scoring system (CuproScore) based on cuproptosis-related markers was also constructed to predict the prognosis of CRC individuals, TME and the response to immunotherapy. In addition, our transcriptome cohort of 15 paired CRC tissue, tissue-array, and various assays in 4 kinds of CRC cell lines in vitro were applied for verification. Results:Cuproptosis-related markers were closely associated with both clinical prognosis and molecular functions. And the cuproptosis-related molecular phenotypes and scoring system (CuproScore) could distinguish and predict the prognosis of CRC patients, TME, and the response to immunotherapy in both public and our transcriptome cohorts. Besides, the expression, function and clinical significance of these markers were also checked and analyzed in CRC cell lines and CRC tissues in our own cohorts. Conclusions:In conclusion, we indicated that cuproptosis and CPRMs played a significant role in CRC progression and in modeling the TME. Inducing cuproptosis may be a useful tool for tumor therapy in the future. 10.1016/j.csbj.2023.06.011
A cuproptosis random forest cox score model-based evaluation of prognosis, mutation characterization, immune infiltration, and drug sensitivity in hepatocellular carcinoma. Frontiers in immunology Background:Hepatocellular carcinoma is the third most deadly malignant tumor in the world with a poor prognosis. Although immunotherapy represents a promising therapeutic approach for HCC, the overall response rate of HCC patients to immunotherapy is less than 30%. Therefore, it is of great significance to explore prognostic factors and investigate the associated tumor immune microenvironment features. Methods:By analyzing RNA-seq data of the TCGA-LIHC cohort, the set of cuproptosis related genes was extracted correlation analysis as a generalization feature. Then, a random forest cox prognostic model was constructed and the cuproptosis random forest cox score was built by random forest feature filtering and univariate multivariate cox regression analysis. Subsequently, the prognosis prediction of CRFCS was evaluated analyzing data of independent cohorts from GEO and ICGC by using KM and ROC methods. Moreover, mutation characterization, immune cell infiltration, immune evasion, and drug sensitivity of CRFCS in HCC were assessed. Results:A cuproptosis random forest cox score was built based on a generalization feature of four cuproptosis related genes. Patients in the high CRFCS group exhibited a lower overall survival. Univariate multivariate Cox regression analysis validated CRFCS as an independent prognostic indicator. ROC analysis revealed that CRFCS was a good predictor of HCC (AUC =0.82). Mutation analysis manifested that microsatellite instability (MSI) was significantly increased in the high CRFCS group. Meanwhile, tumor microenvironment analysis showed that the high CRFCS group displayed much more immune cell infiltration compared with the low CRFCS group. The immune escape assessment analysis demonstrated that the high CRFCS group displayed a decreased TIDE score indicating a lower immune escape probability in the high CRFCS group compared with the low CRFCS group. Interestingly, immune checkpoints were highly expressed in the high CRFCS group. Drug sensitivity analysis revealed that HCC patients from the high CRFCS group had a lower IC of sorafenib than that from the low CRFCS group. Conclusions:In this study, we constructed a cuproptosis random forest cox score (CRFCS) model. CRFCS was revealed to be a potential independent prognostic indicator of HCC and high CRFCS samples showed a poor prognosis. Interestingly, CRFCS were correlated with TME characteristics as well as clinical treatment efficacy. Importantly, compared with the low CRFCS group, the high CRFCS group may benefit from immunotherapy and sorafenib treatment. 10.3389/fimmu.2023.1146411
Molecular subtypes based on cuproptosis-related genes and tumor microenvironment infiltration characteristics in pancreatic adenocarcinoma. Cancer cell international BACKGROUND:Multiple molecular subtypes with distinct clinical outcomes in pancreatic adenocarcinoma (PAAD) have been identified in recent years. Cuproptosis is a new form of cell death that likely involved in tumor progression. However, the cuproptosis-related molecular subtypes as well as its mediated tumor microenvironment (TME) cell infiltration characteristics largely remain unclear. METHODS:Expression profiles of 10 cuproptosis-related genes (CRGs) and their association with patient survival, TME, cancer stemness and drug resistance were studied in 33 cancer types using the TCGA pan-cancer data. Using 437 PAAD samples from five cohorts (TCGA-PAAD cohort and four GEO cohorts), we explored the molecular subtypes mediated by CRGs, along with the associated TME cell infiltration. Unsupervised methods were utilized to perform cuproptosis subtype clustering. The cuproptosis score was constructed using the COX regression model with least absolute shrinkage and selection operator regression (LASSO) algorithm to quantify the cuproptosis characteristics of a single tumor. RESULTS:The expression of 10 CRGs varies in different cancer types with striking inter- and intra- cancer heterogeneity. We integrated the genomic profiling of the CRGs and identified three distinct cuproptosis subtypes, and found that multi-layer CRG alterations were correlated with patient prognosis and TME cell infiltration characteristics. In addition, a cuproptosis score signature was constructed to predict prognosis, and its clinical impacts were characterized in the TCGA-PAAD cohort. The cuproptosis signature was significantly associated with prognosis, tumor subtypes, CD8 T-cell infiltration, response to immune checkpoint inhibitors (ICIs) and chemotherapeutic drug sensitivity. Furthermore, the expression patterns of CRGs in pancreatic cancer cells and normal controls were validated, which was almost consistent with the results from the public database. The expression level and prognostic predictive capability of DLAT were verified in 97 PAAD patients from our patient cohort. CONCLUSIONS:These findings may help understand the roles of CRGs in PAAD and the molecular characterization of cuproptosis subtypes. In addition, the cuproptosis score could serve as a promising biomarker for predicting prognosis and response to immunotherapy in PAAD patients. 10.1186/s12935-022-02836-z
Cuproptosis depicts tumor microenvironment phenotypes and predicts precision immunotherapy and prognosis in bladder carcinoma. Frontiers in immunology Background:Though immune checkpoint inhibitors (ICIs) exhibit durable efficacy in bladder carcinomas (BLCAs), there are still a large portion of patients insensitive to ICIs treatment. Methods:We systematically evaluated the cuproptosis patterns in BLCA patients based on 46 cuproptosis related genes and correlated these cuproptosis patterns with tumor microenvironment (TME) phenotypes and immunotherapy efficacies. Then, for individual patient's evaluation, we constructed a cuproptosis risk score (CRS) for prognosis and a cuproptosis signature for precise TME phenotypes and immunotherapy efficacies predicting. Results:Two distinct cuproptosis patterns were generated. These two patterns were consistent with inflamed and noninflamed TME phenotypes and had potential role for predicting immunotherapy efficacies. We constructed a CRS for predicting individual patient's prognosis with high accuracy in TCGA-BLCA. Importantly, this CRS could be well validated in external cohorts including GSE32894 and GSE13507. Then, we developed a cuproptosis signature and found it was significantly negative correlated with tumor-infiltrating lymphocytes (TILs) both in TCGA-BLCA and Xiangya cohorts. Moreover, we revealed that patients in the high cuproptosis signature group represented a noninflamed TME phenotype on the single cell level. As expected, patients in the high cuproptosis signature group showed less sensitive to immunotherapy. Finally, we found that the high and low cuproptosis signature groups were consistent with luminal and basal subtypes of BLCA respectively, which validated the role of signature in TME in terms of molecular subtypes. Conclusions:Cuproptosis patterns depict different TME phenotypes in BLCA. Our CRS and cuproptosis signature have potential role for predicting prognosis and immunotherapy efficacy, which might guide precise medicine. 10.3389/fimmu.2022.964393
DNAzyme-Mediated Cascade Nanoreactor for Cuproptosis-Promoted Pancreatic Cancer Synergistic Therapy. Advanced healthcare materials Cuproptosis, a kind of newly recognized cell death modality, shows enormous prospect in cancer treatment. The inducer of cuproptosis has more advantages in tumor therapy, especially that can trigger cuproptosis and chemodynamic therapy (CDT) simultaneously. However, cuproptosis is restricted to the deficiency of intracellular copper ions and the nonspecific delivery of copper-based ionophores. Therefore, high level delivery, responsive release, and utilizing synergistic-function of inducer become the key on cuproptosis-based oncotherapy. In this work, a cascade nanosystem is constructed for enhanced cuproptosis and CDT. In the weak acidic environment of tumor cells, DNA, zinc ions, and Cu can release from the nanosystem. Since Cu having superior performance in mediating both Fenton-like reaction and cuproptosis, the released Cu induces cuproptosis and CDT efficiently, accompanied by Cu generation. Then Cu can be converted into Cu partially by glutathione (GSH) to from a Cu supply loop and ensure the synergistic action. Meanwhile, the consumption of GSH also contributes to cuproptosis and CDT in return. Finally, DNA and Zn form DNAzyme to shear catalase-related RNA, resulting in the accumulation of hydrogen peroxide and further enhancing combination therapy. These results provide a promising nanotherapeutic platform and may inspire the design for potential cancer treatment based on cuproptosis. 10.1002/adhm.202301429
Significance of cuproptosis- related genes in the diagnosis and classification of psoriasis. Frontiers in molecular biosciences Cuproptosis is a novel form of cell death linked to mitochondrial metabolism and is mediated by protein lipoylation. The mechanism of cuproptosis in many diseases, such as psoriasis, remains unclear. In this study, signature diagnostic markers of cuproptosis were screened by differential analysis between psoriatic and non-psoriatic patients. The differentially expressed cuproptosis-related genes (CRGs) for patients with psoriasis were screened using the GSE178197 dataset from the gene expression omnibus database. The biological roles of CRGs were identified by GO and KEGG enrichment analyses, and the candidates of cuproptosis-related regulators were selected from a nomogram model. The consensus clustering approach was used to classify psoriasis into clusters and the principal component analysis algorithms were constructed to calculate the cuproptosis score. Finally, latent diagnostic markers and drug sensitivity were analyzed using the pRRophetic R package. The differential analysis revealed that CRGs (MTF1, ATP7B, and SLC31A1) are significantly expressed in psoriatic patients. GO and KEGG enrichment analyses showed that the biological functions of CRGs were mainly related to acetyl-CoA metabolic processes, the mitochondrial matrix, and acyltransferase activity. Compared to the machine learning method used, the random forest model has higher accuracy in the occurrence of cuproptosis. However, the decision curve of the candidate cuproptosis regulators analysis showed that patients can benefit from the nomogram model. The consensus clustering analysis showed that psoriasis can be grouped into three patterns of cuproptosis (clusterA, clusterB, and clusterC) based on selected important regulators of cuproptosis. In advance, we analyzed the immune characteristics of patients and found that clusterA was associated with T cells, clusterB with neutrophil cells, and clusterC predominantly with B cells. Drug sensitivity analysis showed that three cuproptosis regulators (ATP7B, SLC31A1, and MTF1) were associated with the drug sensitivity. This study provides insight into the specific biological functions and related mechanisms of CRGs in the development of psoriasis and indicates that cuproptosis plays a non-negligible role. These results may help guide future treatment strategies for psoriasis. 10.3389/fmolb.2023.1115091
Novel cuproptosis-related long non-coding RNA signature to predict prognosis in prostate carcinoma. BMC cancer BACKGROUND:Cuproptosis, an emerging form of programmed cell death, has recently been identified. However, the association between cuproptosis-related long non-coding RNA (lncRNA) signature and the prognosis in prostate carcinoma remains elusive. This study aims to develop the novel cuproptosis-related lncRNA signature in prostate cancer and explore its latent molecular function. METHODS:RNA-seq data and clinical information were downloaded from the TCGA datasets. Then, cuproptosis-related gene was identified from the previous literature and further applied to screen the cuproptosis-related differentially expressed lncRNAs. Patients were randomly assigned to the training cohort or the validation cohort with a 1:1 ratio. Subsequently, the machine learning algorithms (Lasso and stepwise Cox (direction = both)) were used to construct a novel prognostic signature in the training cohorts, which was validated by the validation and the entire TCGA cohorts. The nomogram base on the lncRNA signature and several clinicopathological traits were constructed to predict the prognosis. Functional enrichment and immune analysis were performed to evaluate its potential mechanism. Furthermore, differences in the landscape of gene mutation, tumour mutational burden (TMB), microsatellite instability (MSI), drug sensitivity between both risk groups were also assessed to explicit their relationships. RESULTS:The cuproptosis-related lncRNA signature was constructed based on the differentially expressed cuproptosis-related lncRNAs, including AC005790.1, AC011472.4, AC099791.2, AC144450.1, LIPE-AS1, and STPG3-AS1. Kaplan-Meier survival and ROC curves demonstrate that the prognosis signature as an independent risk indicator had excellent potential to predict the prognosis in prostate cancer. The signature was closely associated with age, T stage, N stage, and the Gleason score. Immune analysis shows that the high-risk group was in an immunosuppressive microenvironment. Additionally, the significant difference in landscape of gene mutation, tumour mutational burden, microsatellite instability, and drug sensitivity between both risk groups was observed. CONCLUSIONS:A novel cuproptosis-related lncRNA signature was constructed using machine learning algorithms to predict the prognosis of prostate cancer. It was closely with associated with several common clinical traits, immune cell infiltration, immune-related functions, immune checkpoints, gene mutation, TMB, MSI, and the drug sensitivity, which may be useful to improve the clinical outcome. 10.1186/s12885-023-10584-0
Characterization of cuproptosis identified immune microenvironment and prognosis in acute myeloid leukemia. Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico BACKGROUND:Recent studies have reported that cuproptosis, a novel cell death pathway, strongly correlates with mitochondrial metabolism. In addition, the studies reported that cuproptosis plays a role in the development of several cancers and is regulated by protein lipoylation. During cuproptosis, copper binds to the lipoylated proteins and mediates cancer progression. However, the role of cuproptosis in acute myeloid leukemia (AML) patients is yet to be explored. METHODS:This study curated seven cuproptosis-related-genes (CRGs): FDX1, DLAT, PDHB, PDHA1, DLD, LIAS, and LIPT1 to determine cuproptosis modification patterns and the CRGs signature in AML. The CIBERSORT and ssGSEA algorithms were utilized to evaluate the infiltration levels of different immune cell subtypes. A cuproptosis score system based on differentially expressed genes (DEGs) was constructed using the least absolute shrinkage and selection operator (LASSO) regression analysis. The developed cuproptosis score system was validated using two immunotherapy datasets, IMvigor210 and GSE78220. RESULTS:Three distinct cuproptosis regulation patterns were identified using the Beat AML cohort. The results demonstrated that the three cuproptosis regulation patterns were correlated with various biological pathways and clinical outcomes. Tumor microenvironment (TME) characterization revealed that the identified cuproptosis regulation patterns were consistent with three immune profiles: immune-desert, immune-inflamed, and immune-excluded. The AML patients were grouped into low- and high-score groups based on the cuproptosis score system abstracted from 486 cuproptosis-related DEGs. Patients with lower cuproptosis scores were characterized by longer survival time and attenuated immune infiltration. It was found that lower cuproptosis scores were strongly correlated with lower somatic mutation frequency. Moreover, patients with lower cuproptosis scores presented more favorable immune responses and dual clinical benefits among external validation cohorts. CONCLUSIONS:Cuproptosis phenotypes are significantly correlated with immune microenvironment complexity and variety. Cuprotopsis regulates the response of cancer cells to the immune system. Quantitatively assessing cuproptosis phenotypes in AML improves the understanding and knowledge regarding immune microenvironment characteristics and promotes the development of therapeutic interventions. 10.1007/s12094-023-03118-4
Identification of hub cuproptosis related genes and immune cell infiltration characteristics in periodontitis. Frontiers in immunology Introduction:Periodontitis is an inflammatory disease and its molecular mechanisms is not clear. A recently discovered cell death pathway called cuproptosis, may related to the disease. Methods:The datasets GSE10334 of human periodontitis and control were retrieved from the Gene Expression Omnibus database (GEO) for analysis.Following the use of two machine learning algorithms, least absolute shrinkage and selection operator (LASSO) and support vector machine-recursive feature removal (SVM-RFE) were used to find CRG-based signature. Then the Receiver operating characteristic (ROC) curves was used to evaluate the gene signature's discriminatory ability. The CIBERSORT deconvolution algorithm was used to study the link between hub genes and distinct types of immune cells. Next, the association of the CRGs with immune cells in periodontitis and relevant clusters of cuproptosis were found. The link between various clusters was ascertained by the GSVA and CIBERSORT deconvolution algorithm. Finally, An external dataset (GSE16134) was used to confirm the diagnosis capacity of the identified biomarkers. In addition, clinical samples were examined using qRT-PCR and immunohistochemistry to verifiy the expression of genes related to cuprotosis in periodontitis and the signature may better predict the periodontitis. Results:15 periodontitis-related DE-CRGs were found,then 11-CRG-based signature was found by using of LASSO and SVM-RFE. ROC curves also supported the value of signature. CIBERSORT results of immune cell signature in periodontitis showed that signature genes is a crucial component of the immune response.The relevant clusters of cuproptosis found that the NFE2L2, SLC31A1, FDX1,LIAS, DLD, DLAT, and DBT showed a highest expression levels in Cluster2 ,while the NLRP3, MTF1, and DLST displayed the lowest level in Cluster 2 but the highest level in Cluster1. The GSVA results also showed that the 11 cuproptosis diagnostic gene may regulate the periodontitis by affecting immune cells. The external dataset (GSE16134) confirm the diagnosis capacity of the identified biomarkers, and clinical samples examined by qRT-PCR and immunohistochemistry also verified that these cuprotosis related signiture genes in periodontitis may better predict the periodontitis. Conclusion:These findings have important implications for the cuproptosis and periodontitis, and highlight further research is needed to better understand the mechanisms underlying this relationship between the cuproptosis and periodontitis. 10.3389/fimmu.2023.1164667
Radiosensitization-Related Cuproptosis LncRNA Signature in Non-Small Cell Lung Cancer. Genes A new treatment modality targeting cuproptosis is gradually entering the public horizon. Cuproptosis is a new form of regulated cell death distinct from ferroptosis, apoptosis, autophagy, and necrosis. Previous studies have discovered that the copper level varies considerably in various cancers and that an increase in copper content is directly associated with the proliferation and metastasis of cancer cells. In non-small cell lung cancer (NSCLC) after radiation, the potential utility of cuproptosis-related long noncoding RNAs (lncRNAs) is still unclear. This research aimed to develop a prediction signature based on lncRNAs associated with cuproptosis to predict the prognosis of NSCLC patients following radiation. Methods: Expression data of primary tumors and adjacent solid tissues were downloaded from The Cancer Genome Atlas (TCGA) database, along with the corresponding clinical and mutational data. Univariate and multivariate COX analyses and LASSO regression analyses were performed to obtain a predictive signature of lncRNAs associated with cuproptosis. The data were randomly grouped into a training group used for model construction and a test group used for model validation. The model was validated by drawing a survival curve, risk curve, independent prognostic analysis, ROC curve PFS analysis, etc. Results: The lncRNA signature consisting of six cuproptosis-related lncRNAs (AC104088.1, PPP4R3B-DT, AC006042.3, LUCAT1, HHLA3-AS1, and LINC02029) was used to predict the prognosis of patients. Among them, there were three high-risk lncRNAs (LUCAT1, HHLA3-AS1, and LINC02029) with HR > 1 and three protective lncRNAs (AC104088.1, PPP4R3B-DT, and AC006042.3), with an HR < 1. Data analysis demonstrated that the cuproptosis-related lncRNA signatures could well predict the prognosis of NSCLC patients after radiation. Patients in the high-risk category receive a worse prognosis than those in the low-risk group. Cuproptosis-related risk prediction demonstrated better predictive qualities than age, gender, and pathological stage factors. Conclusion: The risk proposed model can independently predict the prognosis of NSCLC patients after radiotherapy, provide a foundation for the role of cuproptosis-related lncRNAs in NSCLC after radiotherapy, and provide a clinical strategy for radiotherapy combined with cuproptosis in NSCLC patients. 10.3390/genes13112080
Cuproptosis related genes associated with Jab1 shapes tumor microenvironment and pharmacological profile in nasopharyngeal carcinoma. Frontiers in immunology Background:Nasopharyngeal carcinoma (NPC) is the most common subcategory of head and neck squamous cell carcinoma (HNSCC). This study focused on the roles of cuproptosis related genes and Jab1 in the tumor microenvironment of NPC and HNSCC. Methods:Differential expression analysis of Jab1 and cuproptosis related genes in tumor cell enriched region (PanCK-expressing) and immune cell enriched region (CD45-expressing) of NPC microenvironment were performed by packages of R software. Survival analysis was performed using the survival and survminer packages. Corrplot package was used for correlation analysis. ConsensusClusterPlus package was used for cluster clustering among different regions of NPC, and functional enrichment analysis was performed using GSVA, GSEABase, clusterProfiler, org.Hs.eg.db and enrichplot packages. The pRRophetic package was used to predict drug sensitivity in NPC and HNSCC. Results:Relationships exist between cuproptosis related genes and Jab1 in the NPC microenvironment. The expression of cuproptosis related genes and Jab1 differed between tumor cell enriched region and immune cell enriched region. AKT inhibitor VIII, Doxorubicin, Bleomycin and Etoposide showed higher sensitivity to tumor cell than immune cell. In the high Jab1 group, higher expression of ATP7A, DBT, DLD and LIAS were associated with better prognosis of HNSCC patients. In contrast, in the low Jab1 group, higher expression of these genes is associated with worse prognosis of HNSCC patients. Conclusions:Prognostic cuproptosis related genes and Jab1 provided a basis for targeted therapy and drug development. 10.3389/fimmu.2022.989286
A prognostic cuproptosis-related lncRNA predictive signature for bladder cancer patients. Human cell Cuproptosis is a novel form of cell death in tumours. However, the clinical impact and mechanism of cuproptosis in bladder cancer (BC) remain unclear. This study aimed to explore the functions of long noncoding RNAs (lncRNAs) related to cuproptosis in BC and develop a prognostic predictive model. RNA sequencing and clinicopathological data were derived from The Cancer Genome Atlas and randomly divided into training and validation groups. Cuproptosis-related lncRNAs were identified by Cox regression analysis and least absolute shrinkage and selection operator, and the patients were divided into high- and low-risk groups according to the median value of the signature-based risk score. We established a signature of 17 cuproptosis-associated lncRNAs in the training set. In both sets, patients with higher signature-based risk scores had a notably higher probability of death (P ≤ 0.001) and a shorter survival duration. Cox regression analyses confirmed the risk score as an independent predictor of BC prognosis in the entire set. The area under the curve (AUC) values for 1-, 3-, and 5-year survival were 0.767, 0.734, and 0.764, respectively, confirming that the signature could determine the prognosis of BC. A signature-based nomogram was developed, and its prediction accuracy was validated using calibration curves. Several drugs, including Gemcitabine, Oxaliplatin, Mitoxantrone, Camptothecin, Cytarabine and Irinotecan may benefit low-risk BC patients more. Finally, in vitro experiments confirmed that the cuproptosis-related lncRNAs are highly expressed in bladder cancer cells after cuproptosis induced by exogenous copper ions. In conclusion, a cuproptosis-related lncRNA signature independently predicted prognosis in BC, indicating a possible mechanism and clinical treatment approach. 10.1007/s13577-023-00863-0
Cuproptosis-related LncRNA signatures as a prognostic model for head and neck squamous cell carcinoma. Apoptosis : an international journal on programmed cell death Cuproptosis is a novel, distinct form of regulated cell death. However, little is known about the role of cuproptosis-related lncRNAs (CRlncRNAs) in head and neck squamous cell carcinoma (HNSCC). This study aimed to identify a CRlncRNAs signature, explore its prognostic value in HNSCC. RNA-seq data and relevant clinical data were downloaded from The Cancer Genome Atlas (TCGA) database, and cuproptosis-related genes were identified from a search of the relevant candidate-gene literature. Analysis of differentially expressed lncRNAs (DElncRNAs) was performed using the R package "edgeR". The intersection of the lncRNAs between DElncRNAs and CRlncRNAs was obtained using the R package "Venn Diagram". Univariate Cox regression was used to identify cuproptosis-related prognostic lncRNAs. LASSO-Cox method was used to narrow these cuproptosis-related prognostic lncRNAs and construct a prognostic model. Multiple statistical methods were used to evaluate the predictive ability of the model. Moreover, the relationships between the model and immune cell subpopulations, related functions and pathways and drug sensitivity were explored. Then, two risk groups were established according to the risk score calculated by the CRlncRNAs signature included three lncRNAs. In HNSCC patients, the risk score was a better predictor of survival than traditional clinicopathological features. In addition, significant differences in immune cells such as B cells, T cells and macrophages were observed between the two groups. Finally, the high-risk group had a lower IC50 for certain chemotherapeutic agents, such as cisplatin and cetuximab. This 3 CRlncRNAs signature is a powerful prognostic biomarker for predicting clinical outcomes and therapeutic responses in HNSCC patients. 10.1007/s10495-022-01790-5
A cuproptosis-related signature for predicting the prognosis of gastric cancer. Journal of gastrointestinal oncology Background:Gastric cancer (GC) is one of the most common malignancies. Cuproptosis is a newly discovered type of cell death caused by protein toxicity stress, with copper having considerable importance in GC development. Methods:First, differentially expressed (DE) cuproptosis-related genes (CRGs) were screened in GC. The tumor mutation burden (TMB) of CRGs was analyzed. We then performed enrichment analyses of DE-CRGs. Next, we constructed a GC cuproptosis-related (CR) signature (CRs) using Cox and least absolute shrinkage and selection operator (LASSO) regression analyses. The predictive efficacy was assessed using receiver operating characteristic (ROC) curves. Furthermore, we performed gene set enrichment analysis (GSEA). Different methods were used to assess tumor immunity of the CRs, and the Wilcoxon test was used to examine the expressions of . The "pRRophetic" R package (The R Foundation for Statistical Computing) was used to predict the half maximal inhibitory concentration IC50 of common chemotherapeutic agents. Finally, the expression of CRGs in different clusters was analyzed using single-cell RNA sequencing (scRNA-seq). Results:We identified 8 DE-CRGs in GC. There were 9 CRGs with TMB values >1%. We constructed gene expression networks and CRs for GC. The DE-CRGs were involved in important mitochondrial metabolic pathways, and the CRs was a valuable independent prognosis factor. The GSEA revealed that angiogenesis and metabolic-related pathways were enriched in the high-risk group, whereas the low-risk group showed enrichment in DNA replication mismatch and repair pathways. The expressions of immunological checkpoints, , type II interferon (INF) response, major histocompatibility complex (MHC class-I), and the IC50 of the copper-based carrier drug elesclomol were significantly different between the 2 groups of the CRs. Furthermore, the scRNA-seq analysis showed that most CRGs were mainly upregulated in endothelial cells. Conclusions:The novel CRs could predict the prognosis of GC. 10.21037/jgo-23-62
Cuproptosis-Mediated Patterns Characterized by Distinct Tumor Microenvironment and Predicted the Immunotherapy Response for Gastric Cancer. ACS omega Cuproptosis is a newly discovered programmed cell death process, and several cuproptosis-related genes have been reported to regulate cancer cell proliferation and progression. The association between cuproptosis and tumor microenvironment in gastric cancer (GC) remains unclear. This study aimed to explore multiomics characteristics of cuproptosis-related genes regulating tumor microenvironment and provide strategies for prognosis and prediction of immunotherapy response in GC patients. We collected 1401 GC patients from the TCGA and 5 GEO data sets and identified three different cuproptosis-mediated patterns, each of which shared a distinct tumor microenvironment and different overall survival. The GC patients with high cuproptosis levels were enriched in CD8+ T cells and had a better prognosis. Whereas, the low cuproptosis level patients were associated with inhibitory immune cell infiltration and had the worst prognosis. In addition, we constructed a 3-gene (AHCYL2, ANKRD6 and FDGFRB) cuproptosis-related prognosis signature (CuPS) via Lasso-Cox and multivariate Cox regression analysis. The GC patients in the low-CuPS subgroup had higher TMB levels, MSI-H fractions, and PD-L1 expression, which suggests a better immunotherapy response. Therefore, the CuPS might have the potential value for predicting prognosis and immunotherapy sensitivity in GC patients. 10.1021/acsomega.2c07052
Cuproptosis-related lncRNA signature for prognostic prediction in patients with acute myeloid leukemia. BMC bioinformatics BACKGROUND:Long non-coding RNAs (lncRNAs) have been reported to have a crucial impact on the pathogenesis of acute myeloid leukemia (AML). Cuproptosis, a copper-triggered modality of mitochondrial cell death, might serve as a promising therapeutic target for cancer treatment and clinical outcome prediction. Nevertheless, the role of cuproptosis-related lncRNAs in AML is not fully understood. METHODS:The RNA sequencing data and demographic characteristics of AML patients were downloaded from The Cancer Genome Atlas database. Pearson correlation analysis, the least absolute shrinkage and selection operator algorithm, and univariable and multivariable Cox regression analyses were applied to identify the cuproptosis-related lncRNA signature and determine its feasibility for AML prognosis prediction. The performance of the proposed signature was evaluated via Kaplan-Meier survival analysis, receiver operating characteristic curves, and principal component analysis. Functional analysis was implemented to uncover the potential prognostic mechanisms. Additionally, quantitative real-time PCR (qRT-PCR) was employed to validate the expression of the prognostic lncRNAs in AML samples. RESULTS:A signature consisting of seven cuproptosis-related lncRNAs (namely NFE4, LINC00989, LINC02062, AC006460.2, AL353796.1, PSMB8-AS1, and AC000120.1) was proposed. Multivariable cox regression analysis revealed that the proposed signature was an independent prognostic factor for AML. Notably, the nomogram based on this signature showed excellent accuracy in predicting the 1-, 3-, and 5-year survival (area under curve = 0.846, 0.801, and 0.895, respectively). Functional analysis results suggested the existence of a significant association between the prognostic signature and immune-related pathways. The expression pattern of the lncRNAs was validated in AML samples. CONCLUSION:Collectively, we constructed a prediction model based on seven cuproptosis-related lncRNAs for AML prognosis. The obtained risk score may reveal the immunotherapy response in patients with this disease. 10.1186/s12859-023-05148-9
Comprehensive analysis of cuproptosis-related immune biomarker signature to enhance prognostic accuracy in gastric cancer. Aging BACKGROUND:Gastric cancer (GC) is a malignant tumor with high prevalence and fatality. Cuproptosis is a recently identified copper-dependent programmed cell death mechanism. Multiple studies have demonstrated the profound impact of the immune microenvironment on tumor development. Hence, we decided to excavate the potential functional roles of cuproptosis-related immune genes (CRIGs) in GC and their values as biomarkers. METHODS:Cuproptosis- and immune-related genes were curated from top published studies on cell cuproptosis and cellular immunity. Transcriptome data and clinical information were obtained from TCGA, GTEx, and GEO databases. Cox and LASSO analyses were used to establish a prognostic signature for GC. Long-term prognosis, immune infiltration, immune checkpoint, and drug response were compared between signature groups. CRIG expression in GC scRNA-seq was analyzed. Immunohistochemistry was used to evaluate CRIG and cuproptosis regulator FDX1 in GC tissues. RESULTS:Seven CRIGs (ANOS1, CTLA4, ITGAV, CXCR4, NRP1, FABP3, and LGR6) were selected to establish a potent signature to forecast the long-term prognosis of patients. GC patients had worse prognosis and poor responses to chemotherapeutic drugs (5-Fluorouracil and paclitaxel) in the high-risk group. scRNA-seq revealed that CTLA4, ITGAV, CXCR4, and NRP1 enrichment in specific cell types regulated the progression of GC. Moreover, NRP1, CXCR4, LGR6, CTLA4, and FDX1 were elevated in GC tissues, with a positive correlation between their expression and FDX1. CONCLUSIONS:To conclude, this study first provides insights into the functions of CRIGs in GC. Furthermore, a robust cuproptosis-related immune biomarker signature was established to forecast the long-term survival of GC patients accurately. 10.18632/aging.204646
A Prognostic Cuproptosis-Related LncRNA Signature for Colon Adenocarcinoma. Journal of oncology Background:Cuproptosis, a recently discovered form of cell death, is caused by copper levels exceeding homeostasis thresholds. Although Cu has a potential role in colon adenocarcinoma (COAD), its role in the development of COAD remains unclear. Methods:In this study, 426 patients with COAD were extracted from the Cancer Genome Atlas (TCGA) database. The Pearson correlation algorithm was used to identify cuproptosis-related lncRNAs. Using the univariate Cox regression analysis, the least absolute shrinkage and selection operator (LASSO) was used to select cuproptosis-related lncRNAs associated with COAD overall survival (OS). A risk model was established based on the multivariate Cox regression analysis. A nomogram model was used to evaluate the prognostic signature based on the risk model. Finally, mutational burden and sensitivity analyses of chemotherapy drugs were performed for COAD patients in the low- and high-risk groups. Result:Ten cuproptosis-related lncRNAs were identified and a novel risk model was constructed. A signature based on ten cuproptosis-related lncRNAs was an independent prognostic predictor for COAD. Mutational burden analysis suggested that patients with high-risk scores had higher mutation frequency and shorter survival. Conclusion:Constructing a risk model based on the ten cuproptosis-related lncRNAs could accurately predict the prognosis of COAD patients, providing a fresh perspective for future research on COAD. 10.1155/2023/5925935
Cuproptosis signature and PLCD3 predicts immune infiltration and drug responses in osteosarcoma. Frontiers in oncology Osteosarcoma (OS) is a cancer that is frequently found in children and adolescents and has made little improvement in terms of prognosis in recent years. A recently discovered type of programmed cell death called cuproptosis is mediated by copper ions and the tricarboxylic acid (TCA) cycle. The expression patterns, roles, and prognostic and predictive capabilities of the cuproptosis regulating genes were investigated in this work. TARGET and GEO provided transcriptional profiling of OS. To find different cuproptosis gene expression patterns, consensus clustering was used. To identify hub genes linked to cuproptosis, differential expression (DE) and weighted gene co-expression network analysis (WGCNA) were used. Cox regression and Random Survival Forest were used to build an evaluation model for prognosis. For various clusters/subgroups, GSVA, mRNAsi, and other immune infiltration experiments were carried out. The drug-responsive study was carried out by the Oncopredict algorithm. Cuproptosis genes displayed two unique patterns of expression, and high expression of FDX1 was associated with a poor outcome in OS patients. The TCA cycle and other tumor-promoting pathways were validated by the functional study, and activation of the cuproptosis genes may also be connected with immunosuppressive state. The robust survival prediction ability of a five-gene prognostic model was verified. This rating method also took stemness and immunosuppressive characteristics into account. Additionally, it can be associated with a higher sensitivity to medications that block PI3K/AKT/mTOR signaling as well as numerous chemoresistances. U2OS cell migration and proliferation may be encouraged by PLCD3. The relevance of PLCD3 in immunotherapy prediction was verified. The prognostic significance, expressing patterns, and functions of cuproptosis in OS were revealed in this work on a preliminary basis. The cuproptosis-related scoring model worked well for predicting prognosis and chemoresistance. 10.3389/fonc.2023.1156455
Targeting cuproptosis by zinc pyrithione in triple-negative breast cancer. iScience Triple-negative breast cancer (TNBC) poses a considerable challenge due to its aggressive nature. Notably, metal ion-induced cell death, such as ferroptosis, has garnered significant attention and demonstrated potential implications for cancer. Recently, cuproptosis, a potent cell death pathway reliant on copper, has been identified. However, whether cuproptosis can be targeted for cancer treatment remains uncertain. Here, we screened the US Food and Drug Administration (FDA)-approved drug library and identified zinc pyrithione (ZnPT) as a compound that significantly inhibited TNBC progression. RNA sequencing revealed that ZnPT disrupted copper homeostasis. Furthermore, ZnPT facilitated the oligomerization of dihydrolipoamide S-acetyltransferase, a landmark molecule of cuproptosis. Clinically, high expression levels of cuproptosis-related proteins were significantly correlated with poor prognosis in TNBC patients. Collectively, these findings indicate that ZnPT can induce cell death by targeting and disrupting copper homeostasis, providing a potential experimental foundation for exploring cuproptosis as a target in drug discovery for TNBC patients. 10.1016/j.isci.2023.108218
Pan-cancer patterns of cuproptosis markers reveal biologically and clinically relevant cancer subtypes. Biomarker research Cuproptosis is a newly discovered type of cell death triggered by copper accumulation. Here we exhibited the genetic profiles of 10 cuproptosis-associated genes (CuAGs) across 21 cancer types. Only 8.0% (627/7839) of tumors possessed at least 1 mutation on CuAGs, while the copy number amplifications or deletions on the alleles of CuAGs were ubiquitous. Generally, the expression of CuAGs showed heterogeneity across cancer types and the expression of CuAGs showed different correlations with MSI, TMB, immune and stromal features in different cancer types. Therefore, CuAGs were ubiquitously and heterogeneously dysregulated in pan-cancer. With a Non-negative Matrix Factorization method, we divided patients of each cancer type into cuproptosis-based subtypes, which showed a close but heterogeneous correlation with different biological and clinical features. Accordingly, we summarized all cancer types into four categories. The cancers in which cuproptosis subtypes correlated with MSI and TMB were annotated as Genomic disturbed. Those correlated with stromal scores were categorized as Stromal remolded. The others only associated with immune infiltration were labeled as Immune inhibited. A minor fraction of cancers not correlated with any biological indicators were marked as Cuproptosis inert. Together, we provided a pan-cancer overview of cuproptosis markers which revealed biologically and clinically relevant cancer subtypes in different cancers. 10.1186/s40364-022-00446-5
Analysis of cuproptosis-related lncRNA signature for predicting prognosis and tumor immune microenvironment in pancreatic cancer. Apoptosis : an international journal on programmed cell death Pancreatic cancer (PC) is a highly malignant digestive tract tumor, with a dismal 5-year survival rate. Recently, cuproptosis was found to be copper-dependent cell death. This work aims to establish a cuproptosis-related lncRNA signature which could predict the prognosis of PC patients and help clinical decision-making. Firstly, cuproptosis-related lncRNAs were identified in the TCGA-PAAD database. Next, a cuproptosis-related lncRNA signature based on five lncRNAs was established. Besides, the ICGC cohort and our samples from 30 PC patients served as external validation groups to verify the predictive power of the risk signature. Then, the expression of CASC8 was verified in PC samples, scRNA-seq dataset CRA001160, and PC cell lines. The correlation between CASC8 and cuproptosis-related genes was validated by Real-Time PCR. Additionally, the roles of CASC8 in PC progression and immune microenvironment characterization were explored by loss-of-function assay. As showed in the results, the prognosis of patients with higher risk scores was prominently worse than that with lower risk scores. Real-Time PCR and single cell analysis suggested that CASC8 was highly expressed in pancreatic cancer and related to cuproptosis. Additionally, gene inhibition of CASC8 impacted the proliferation, apoptosis and migration of PC cells. Furthermore, CASC8 was demonstrated to impact the expression of CD274 and several chemokines, and serve as a key indicator in tumor immune microenvironment characterization. In conclusion, the cuproptosis-related lncRNA signature could provide valuable indications for the prognosis of PC patients, and CASC8 was a candidate biomarker for not only predicting the progression of PC patients but also their antitumor immune responses. 10.1007/s10495-023-01843-3
A novel cuproptosis pattern and tumor immune microenvironment characterization in urothelial carcinoma of the bladder. Frontiers in immunology Background:Urothelial carcinoma of the bladder (UCB) is the most prevalent malignant tumor of the urinary system worldwide, which has a significant recurrence rate despite multiple treatment options available. As a unique and novel copper-dependent programmed cell death mechanism, the comprehensive impact of cuproptosis on the tumor immune microenvironment, clinicopathological characteristics and the prognosis of patients remains largely unclear. Methods:A total of 568 UCB samples were thoroughly examined for cuproptosis patterns using data downloaded from TCGA and GEO, based on 10 cuproptosis-related genes reported previously. Then, the univariate COX regression analysis was performed on the genes that differed across the various patterns. To measure individual cuproptosis pattern, a cuproptosis score system was constructed using a principal component analysis algorithm. To validate the scoring system, immunohistochemical staining was performed on tumor tissues with different pathological grades, and experiments were conducted about the differentially expressed genes related to prognosis. Finally, the capacity of scoring system to predict the response to immunotherapy was verified by using data from IMvigor 210 cohort. Results:Four unique cuproptosis clusters and two gene clusters were finally found by the investigation. The clinical features and prognosis of patients, as well as the mRNA transcriptome, pathway enrichment, and immune cell infiltration in TME, varied dramatically between various cuproptosis clusters and gene clusters. To identify individual cuproptosis patterns in UCB patients, we also established a cuproptosis scoring system. After validation with multiple methods, it was indicated that the score system could predict the prognosis of UCB patients and was significantly connected to clinical features such TNM category, tumor grade, molecular type and ultimate survival status. The clinical outcomes of UCB patients were predicted effectively according to the tumor mutation burden in conjunction with the scoring system. Furthermore, we found that the cuproptosis score had a significant correlation with the response to immunotherapy and the sensitivity to chemotherapy. Conclusion:This study revealed the potential impact of cuproptosis on the UCB tumor immune microenvironment and clinical pathological characteristics. The cuproptosis score system could effectively predict the prognosis of patients and the response to chemotherapy and immunotherapy. 10.3389/fimmu.2023.1219209
Cuproptosis-related lncRNAs forecast the prognosis of acute myeloid leukemia. Translational cancer research Background:Acute myeloid leukemia (AML) is a highly heterogeneous cluster of hematologic malignancies. Leukemic stem cells (LSCs) are one of the culprits for the persistence and relapse of AML. The discovery of copper-induced cell death, namely cuproptosis, gives bright insights into the treatment of AML. Analogous to copper ions, long non-coding RNAs (lncRNAs) are not bystanders for AML progression, especially for LSC physiology. Uncovering the involvement of cuproptosis-related lncRNAs in AML will benefit clinical management. Methods:Detection of prognostic relevant cuproptosis-related lncRNAs are carried out by Pearson correlation analysis and univariate Cox analysis with RNA sequencing data of The Cancer Genome Atlas-Acute Myeloid Leukemia (TCGA-LAML) cohort. After the least absolute shrinkage and selection operator (LASSO) regression and the subsequent multivariate Cox analysis, a cuproptosis-related risk score (CuRS) system was derived to weigh the risk of AML patients. Thereafter, AML patients were classified into two groups by their risk property which was validated with principal component analysis (PCA), risk curves, Kaplan-Meier survival analysis, the combined receiver operating characteristic (ROC) curves, and nomogram. Variations in biological pathways and divergences in immune infiltration and immune-related processes between groups were resolved by GSEA and CIBERSORT algorism, respectively. Response to chemotherapies were scrutinized as well. The expression profiles of the candidate lncRNAs were examined by real-time quantitative polymerase chain reaction (RT-qPCR) and the specific mechanisms of lncRNA were determined by transcriptomic analysis. Results:We fabricated an efficient prognostic signature named CuRS incorporating 4 lncRNAs (, , , and ) relevant to immune environment and chemotherapy responsiveness. The relevance of lncRNA with proliferation, migration ability, Daunorubicin resistance and its reciprocal action with were demonstrated in an LSC cell line. Transcriptomic analysis suggested correlations between and T cell differentiation and signaling, intercellular junction genes. Conclusions:The prognostic signature CuRS can guide prognostic stratification and personalized AML therapy. Analysis of offers a foundation for investigating LSC-targeted therapies. 10.21037/tcr-22-2526
Cuproptosis identifies respiratory subtype of renal cancer that confers favorable prognosis. Apoptosis : an international journal on programmed cell death Cuproptosis is a newly discovered cell death induced by excessive copper in mitochondria distinct from any known forms of apoptosis. Role of cuproptosis has not been well-reported in cancer, especially in clear-cell renal cell carcinoma (ccRCC). We comprehensively interrogated cuproptotic gene signature in ccRCC by reproducing multi-omics datasets and found cuproptosis was decreased in ccRCC compared with normal kidney. Cuproptosis identified a subgroup with significantly better prognosis. Functional annotation supported increased tricarboxylic acid cycle activity and decreased hypoxia signaling corroborated by metabolomics. Cuproptotic tumors showed decreased angiogenesis but were sensitive to Sunitinib and Sorafenib. Cuproptotic level in ccRCC cell lines showed robust negative correlation with copper ionophore Elesclomol. All findings support a respiratory subtype of ccRCC identified by cuproptosis. 10.1007/s10495-022-01769-2
A novel cuproptosis-related gene signature to predict prognosis in Glioma. BMC cancer Glioma is primary brain tumour with a poor prognosis. Metabolic reprogramming is a hallmark of glioma, and is critical in the development of antiglioma agents and glioma therapy. Cuproptosis is a novel form of cell death mediated by protein lipidation and highly associated with mitochondrial metabolism. However, the clinical impact of cuproptosis-related genes (CRGs) in glioma remains largely unknown. The purpose of this study is to create a new CRGs signature that can be used to predict survival and immunotherapy in glioma patients. LASSO regression analysis was applied to establish prognostic gene signatures. Furthermore, a CRGs signature-based nomogram was developed and demonstrated good predictive potential. We also analyzed the relationship of CRGs and immune infiltration and the correlation with the pathological grade of glioma. Finally, we explored the miRNA that may regulate cuproptosis-related gene FDX1. We found that miR-606 was markedly downregulated in GBM, overexpression of miR-606 can significantly inhibit aerobic glycolysis and proliferation of GBM cells. FDX1 was upregulated in GBM, knockdown of FDX1 significantly inhibit aerobic glycolysis and proliferation of GBM cells. And luciferase assay was used to verified that miR-606 binds to and regulates FDX1 mRNA. These results provide a basis for further exploring the biological mechanisms of cuproptosis. This study may provide new potential therapeutic perspectives for patients with glioma. 10.1186/s12885-023-10714-8
Cuproptosis-related lncRNAs predict prognosis and immune response of thyroid carcinoma. Frontiers in genetics To estimate the survival and prognosis of patients with thyroid carcinoma (THCA) based on the Long non-coding RNA (lncRNA) traits linked to cuproptosis and to investigate the connection between the immunological spectrum of THCA and medication sensitivity. RNA-Seq data and clinical information for THCA were obtained from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. We built a risk prognosis model by identifying and excluding lncRNAs associated with cuproptosis using Cox regression and LASSO methods. Both possible biological and immune infiltration functions were investigated using Principal Component Analysis (PCA), Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and immunoassays. The sensitivity of the immune response to possible THCA medicines was assessed using ratings for tumor immune dysfunction and exclusion (TIDE) and tumor mutational burden (TMB). Seven cuproptosis-related lncRNAs were used to construct our prognostic prediction model: AC108704.1, DIO3OS, AL157388.1, AL138767.3, STARD13-AS, AC008532.1, and PLBD1-AS1. Using data from TCGA's training, testing, and all groups, Kaplan-Meier and ROC curves demonstrated this feature's adequate predictive validity. Different clinical characteristics have varying effects on cuproptosis-related lncRNA risk models. Further analysis of immune cell infiltration and single sample Gene Set Enrichment Analysis (ssGSEA) supported the possibility that cuproptosis-associated lncRNAs and THCA tumor immunity were closely connected. Significantly, individuals with THCA showed a considerable decline in survival owing to the superposition effect of patients in the high-risk category and high TMB. Additionally, the low-risk group had a higher TIDE score compared with the high-risk group, indicating that these patients had suboptimal immune checkpoint blocking responses. To ensure the accuracy and reliability of our results, we further verified them using several GEO databases. The clinical and risk aspects of cuproptosis-related lncRNAs may aid in determining the prognosis of patients with THCA and improving therapeutic choices. 10.3389/fgene.2023.1100909