
Comprehensive Analysis of the Relationship between Cuproptosis-Related Gene GCSH and Prognosis, Tumor Microenvironment Infiltration, and Therapy Response in Endometrial Cancer.
Oncology
INTRODUCTION:Cuproptosis is a novel form of cell death regulated by protein lipoylation and implicated in mitochondrial metabolism. However, further research is needed to explore the influence of the cuproptosis-related gene γ-glutamylcysteine synthetase (GCSH) on the prognosis of endometrial cancer (EC), the tumor immune microenvironment, and therapeutic response. METHODS:The differential expression of GCSH between EC and normal tissues was analyzed using multiple public databases. Additionally, cancer and adjacent tissues were prospectively collected from 17 EC patients, and immunohistochemical analysis was performed to further investigate GCSH expression differences. The relationship between GCSH and the prognosis and clinicopathological characteristics of EC patients was evaluated, and a nomogram was constructed to predict patient survival based on GCSH expression. Subsequently, Gene set variation analysis was used to explore the potential biological functions of GCSH in EC. The impact of GCSH on the tumor microenvironment (TME) was estimated. Finally, the effect of GCSH on the response to immunotherapy and chemotherapeutic drugs in EC was investigated. RESULTS:The expression of GCSH was significantly upregulated in EC. High GCSH expression was associated with poor prognosis in EC patients. Enrichment analysis revealed an association between high GCSH and immune suppression. Furthermore, high GCSH was found to be associated with a non-inflamed TME, leading to decreased infiltration levels of immune cells. Lastly, it was observed that patients with high GCSH exhibited insensitivity to both immunotherapy and chemotherapeutic drugs. CONCLUSION:This study revealed the role of GCSH in TME, response to therapy, and clinical prognosis in EC, which provided novel insights for the therapeutic application in EC.
10.1159/000534018
Construction of a novel cuproptosis-related gene signature for predicting prognosis and estimating tumor immune microenvironment status in papillary thyroid carcinoma.
BMC cancer
BACKGROUND:Cuproptosis, a new form of programmed cell death, has been recently reported to be closely related to tumor progression. However, the significance of cuproptosis-related genes (CRGs) in papillary thyroid carcinoma (PTC) is still unclear. Therefore, this study aimed to investigate the role of the CRG signature in prognosis prediction and immunotherapeutic effect estimation in patients with PTC. METHODS:RNA-seq data and the corresponding clinical information of patients with PTC were obtained from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Comprehensive analyses, namely, consensus clustering, immune analyses, functional enrichment, least absolute shrinkage and selection operator-multivariate Cox regression, and nomogram analysis, were performed to identify new molecular subgroups, determine the tumor immune microenvironment (TIME) status of the identified subgroups, and construct a clinical model. Independent verification cohort data and quantitative real-time polymerase chain reaction (qPCR) was performed to validate the expression of specific prognosis-related and differentially expressed CRGs (P-DECRGs). RESULTS:In the TCGA database, 476 patients with PTC who had complete clinical and follow-up information were included. Among 135 CRGs, 21 were identified as P-DECRGs. Two molecular subgroups with significantly different disease-free survival and TIME statuses were identified based on these 21 P-DECRGs. The differentially expressed genes between the two subgroups were mainly associated with immune regulation. The risk model and nomogram were constructed based on four specific P-DECRGs and validated as accurate prognostic predictions and TIME status estimation for PTC by TCGA and GEO verification cohorts. Finally, the qPCR results of 20 PTC and paracancerous thyroid tissues validated those in the TCGA database. CONCLUSIONS:Four specific P-DECRGs in PTC were identified, and a clinical model based on them was established, which may be helpful for individualized immunotherapeutic strategies and prognostic prediction in patients with PTC.
10.1186/s12885-022-10175-5
The Cuproptosis-Related Long Noncoding RNA Signature Predicts Prognosis and Tumour Immune Analysis in Osteosarcoma.
Computational and mathematical methods in medicine
Background:Cuprotopsis is a type of programmed cell death discovered in recent years. Long noncoding RNAs (lncRNAs) play an important regulatory role in programmed cell death. The effect of cuproptosis-related lncRNAs on osteosarcoma is unknown. Our work, based on cuproptosis-related lncRNAs, proposes a gene signature to assess the prognosis of patients with osteosarcoma. Methods:Osteosarcoma gene expression data from The Cancer Genome Atlas (TCGA), clinical features of osteosarcoma and RNA sequencing data of normal adipose tissue were obtained from the UCSC Xena database. A cuproptosis-related lncRNA risk model was established to calculate the risk score. At the same time, cluster analysis, clinicopathological analysis, functional enrichment analysis, and prediction of compounds with potential therapeutic value were evaluated. We analyzed whether there was a correlation between the risk score and tumour immunity. RT-qPCR was used to verify the expression level of lncRNA. Results:Nine lncRNAs (AC124798.1, AC006033.2, AL450344.2, AL512625.2, LINC01060, LINC00837, AC004943.2, AC064836.3, and AC100821.2) were identified to create a risk model and indicate the prognosis of patients with osteosarcoma. The high-risk group had a worse prognosis than the low-risk group. Analysis of clinicopathological features, principal component analysis, receiver operating characteristic curve, c-index curve, and comparative analysis of models proved that the model is reliable. Functional enrichment analysis suggests that the risk score may correlate with cell energy metabolism and tumour-related biological function. Three potentially therapeutic compounds have been predicted. These analyses may be beneficial to the treatment of osteosarcoma in the future. RT-qPCR verified the expression level of three lncRNA (LINC01060, NKILA, and SNHG8). Conclusions:Cuproptosis-related lncRNAs have a strong relationship with osteosarcoma patients. Nine lncRNA models can effectively forecast the prognosis of osteosarcoma and may play a significant role in the individualized treatment of osteosarcoma patients in the future.
10.1155/2022/6314182
Development and Evaluation of a Novel Cuproptosis-Related lncRNA Signature for Gastric Cancer Prognosis.
Computational and mathematical methods in medicine
Background:According to a growing body of research, long noncoding RNAs (lncRNAs) participate in the progress of gastric cancer (GC). Cuproptosis is a distinct kind of programmed cell death, separating it from several other forms of programmed cell death that may be caused by genetic programming. Consequently, it is crucial to examine cuproptosis-related lncRNAs (CRLs) prognostic importance for the prognosis and treatment response in GC. Method:The Cancer Genome Atlas (TCGA) database was used to retrieve RNA-seq data, pertinent clinical information, and somatic mutation data. A list of cuproptosis-related genes (CRGs) was obtained from prior work. We can distinguish prognostic CRLs using coexpression and univariate Cox analysis. Then, using CRLs, we developed a risk prediction model using multivariate Cox regression analysis and the least absolute shrinkage selection operator (LASSO) technique. To evaluate the diagnostic accuracy of this model, a Kaplan-Meier (K-M) survival analysis and a receiver operating characteristic (ROC) analysis were used. Moreover, the relationships between the risk model and immunological function, somatic mutation, and drug sensitivity were also investigated. Results:Using the multivariate Cox analysis technique, we developed a signature based on cuproptosis-related four lncRNAs. We then classified patients into high-risk and low-risk groups based on the likelihood of unfavorable outcomes. The model was subjected to further testing, including K-M survival analysis, ROC analysis, and multivariate Cox regression analysis, all of which proved the model's exceptional robustness and predictive capacity. In addition, a nomogram that has a strong capacity for prediction ability was built. This nomogram included age, gender, clinical grade, pathologic stage, T stage, and risk score. Furthermore, we discovered substantial disparities in immune function and the number of mutations carried by tumors between the high-risk and low-risk groups. Moreover, this research also found that the IC50 values for 27 chemotherapeutic drugs varied widely across patients within high- and low-risk groups. Conclusion:The proposed 4-CRLs signature is a promising biomarker to predict clinical outcomes in GC.
10.1155/2023/6354212
Prognostic analysis of cuproptosis-related gene in triple-negative breast cancer.
Frontiers in immunology
Background:Cuproptosis is a copper-dependent cell death mechanism that is associated with tumor progression, prognosis, and immune response. However, the potential role of cuproptosis-related genes (CRGs) in the tumor microenvironment (TME) of triple-negative breast cancer (TNBC) remains unclear. Patients and methods:In total, 346 TNBC samples were collected from The Cancer Genome Atlas database and three Gene Expression Omnibus datasets, and were classified using R software packages. The relationships between the different subgroups and clinical pathological characteristics, immune infiltration characteristics, and mutation status of the TME were examined. Finally, a nomogram and calibration curve were constructed to predict patient survival probability to improve the clinical applicability of the CRG_score. Results:We identified two CRG clusters with immune cell infiltration characteristics highly consistent with those of the immune-inflamed and immune-desert clusters. Furthermore, we demonstrated that the gene signature can be used to evaluate tumor immune cell infiltration, clinical features, and prognostic status. Low CRG_scores were characterized by high tumor mutation burden and immune activation, good survival probability, and more immunoreactivity to CTLA4, while high CRG_scores were characterized by the activation of stromal pathways and immunosuppression. Conclusion:This study revealed the potential effects of CRGs on the TME, clinicopathological features, and prognosis of TNBC. The CRGs were closely associated with the tumor immunity of TNBC and are a potential tool for predicting patient prognosis. Our data provide new directions for the development of novel drugs in the future.
10.3389/fimmu.2022.922780
Comprehensive analysis of cuproptosis-related long noncoding RNA immune infiltration and prediction of prognosis in patients with bladder cancer.
Frontiers in genetics
Bladder cancer (BCa), among the world's most common malignant tumors in the urinary system, has a high morbidity and mortality. Though cuproptosis is a new type of cell death mediated by lipoylated tricarboxylic acid (TCA) cycle proteins, the role of cuproptosis-related long noncoding RNAs (crlncRNAs) in bladder tumors awaits further elucidation. In this paper, we tried to explore how important crlncRNAs are for BCa. The crlncRNAs were first obtained through Pearson correlation analysis of the RNA-seq data and corresponding clinical data downloaded from The Cancer Genome Atlas (TCGA). Then, three lncRNAs were acquired by Cox regression and Lasso regression to build a prognostic model of crlncRNAs for verification. In the meantime, clinicopathological correlation analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, principal component analysis (PCA), immunoassay, and half-maximal inhibitory concentration prediction (IC50) were carried out. Then, an entire tumor was classified into two clusters by crlncRNA expression to further discuss the differences in prognosis, immune status and drug susceptibility among different subgroups. We obtained a total of 152 crlncRNAs and built a risk model for screened crlncRNAs. We validated the model and found that calibration charts feature a high consistency in verifying nomogram prediction. Receiver operating characteristic (ROC) curve and univariate and multivariate Cox regression suggested that this model can be applied as an independent prognostic factor of bladder cancer due to its high accuracy. According to KEGG analysis, high-risk groups were enriched in cancer and immune-related pathways. During tumor immunoassay, noticeable differences were observed in both immune infiltration and checkpoints between high- and low-risk patients. Of the two subgroups divided among patients by consensus clustering, cluster 2 had a better prognosis, whereas cluster 1 had higher immunoreactivity scores, more immune cell infiltrations and immune checkpoint expressions, and different sensitivities to drugs. The research findings demonstrate that crlncRNAs can be used to predict the prognosis and immune microenvironment of patients suffering from BCa, and differentiate between BCa subgroups to improve the individual therapy of BCa.
10.3389/fgene.2022.990326
Identification and validation of cuproptosis-related LncRNA signatures as a novel prognostic model for head and neck squamous cell cancer.
Cancer cell international
BACKGROUND:Head and neck squamous cell cancer (HNSCC) is a common malignant cancer. We aimed to explore prognostic cuproptosis-related lncRNAs (CRLs) and prognostic risk models for HNSCC. METHODS:The transcriptome profiles and clinical data were obtained from the TCGA database, and 19-cuproptosis-related genes (CRGs) were acquired from previous studies. Then, the prognostic model based on seven CRLs was established. We analysed its value to evaluate the prognosis, drug sensitivity, and tumour immune functions of patients with HNSCC. Finally, we used quantitative reverse transcription polymerase chain reaction (qRT‒PCR) to validate the seven CRLs. RESULTS:We established a 7-CRL signature. Kaplan‒Meier (K-M) curve analysis demonstrated a significantly preferable prognosis in the low-risk group. Multivariate Cox regression analysis revealed that the risk score could serve as an independent prognostic factor. Nomogram, ROC curve, and principal component analysis indicated that the signature presented significant predictive capability. Moreover, most of the high-risk group showed lower levels of IC for certain chemotherapy drugs, such as cisplatin, cytarabine, docetaxel, doxorubicin, etoposide, gemcitabine, methotrexate, paclitaxel, and dasatinib. Finally, the expression of AP001372.2, MIR9-3HG, AL160314.2, POLH-AS1, and AL109936.2 was upregulated, while AC090587.1 and WDFY3-AS2 were downregulated in HNSCC cell lines compared with normal cell lines by qRT‒PCR. CONCLUSIONS:The 7-CRL signature was presented to be a novel biomarker for predicting prognosis for HNSCC.
10.1186/s12935-022-02762-0
The Prognostic Role of Cuproptosis in Head and Neck Squamous Cell Carcinoma Patients: A Comprehensive Analysis.
Disease markers
Purpose:Head and neck squamous cell carcinoma (HNSCC) exhibits a high mortality and morbidity rate, and its treatment is facing clinical challenges. Cuproptosis, a copper-dependent cell death process, can help derive new forms of cancer therapies. However, the potential of cuproptosis-related genes (CRGs) as novel biomarkers for risk prediction, screening, and prognosis remains to be further explained in HNSCC. Methods:We built a prognostic multigene signature with CRGs, which is associated with the tumor immune microenvironment (TME) by gene set enrichment analysis (GSEA), in the TCGA cohort. Furthermore, we systematically correlated risk signature with immunological characteristics in TME including tumor-infiltrating immune cells (TIICs), immune checkpoints, T cell inflamed score, and cancer immunity cycles. We also thoroughly investigated the biological functions of cuproptosis-associated lncRNAs and its immunological characteristics. Results:CRGs-related prognostic model showed good prediction performance. A higher risk score was associated with a poorer overall survival (OS) than those with low-risk scores, according to the results of the survival analysis ( < 0.0001). The risk score was significantly related to the variable clinicopathological factors. Samples with high-risk scores had lower levels of CD8+ T cells infiltration. Immune therapy might be effective for the low-risk subtype of HNSCC patients ( < 0.05). Moreover, 11 differentially expressed lncRNAs as the independent prognostic factor could also predict TME in an accurate manner. Conclusion:Our study identified and validated novel cuproptosis-related biomarkers for HNSCC prognosis and screening, which offer better insights into developing accurate, reliable, and novel cancer therapies in the era of precision medicine.
10.1155/2022/9996946
Analysis of the correlation between non-alcoholic fatty liver disease and the risk of colorectal neoplasms.
Frontiers in pharmacology
This study aims at assessing the potential association between non-alcoholic fatty liver disease (NAFLD) and colorectal neoplasms (CRN). PubMed, Cochrane Library, and Embase were searched for cohort studies. 14 cohort studies with a total population of 38,761,773 were included for meta-analysis after selection. The results showed that NAFLD is related to an increased risk of CRN (OR = 1.23; 95% CI: 1.14-1.32; I = 70.7%, < 0.001). In the subgroup analysis, NAFLD were found to be the independent risk factor of colorectal adenoma (CRA) (OR = 1.29; 95% CI = 1.15-1.45; I = 66.4%) and colorectal cancer (CRC) (OR = 1.13; 95% CI = 1.12-1.15; I = 69.4%). There is no close correlation between smoking status of NAFLD patients and CRN. Interestingly, bioinformatics analysis revealed that there were overlap of dysregulated gene sets among NAFLD, CRC, and two recently identified regulated cell death types, ferroptosis and cuproptosis, respectively. Our meta- and bioinformatics analysis shows that NAFLD increases the risk of CRN. Ferroptosis and cuproptosis may be the critical links between NAFLD and CRN, respectively. These findings here support that NAFLD is necessary to be considered as an emerging risk factor for CRN.
10.3389/fphar.2022.1068432
High expression of cuproptosis-related gene FDX1 in relation to good prognosis and immune cells infiltration in colon adenocarcinoma (COAD).
Journal of cancer research and clinical oncology
BACKGROUND:Cuproptosis induced by FDX1 is a newly discovered mechanism regulating cell death. However, the role of FDX1 in the pathogenesis of colon adenocarcinoma (COAD) remains to be studied. METHODS:FDX1 expression was analyzed with The Cancer Genome Atlas (TCGA) database and Human Protein Atlas (HPA) database. Association between FDX1 expression and COAD prognosis was investigated via the Kaplan-Meier (KM) survival curve. The differentially expressed genes (DEGs) of FDX1 were screened with R packages and the PPI were constructed via STRING database. Cytoscape software was used to detect the most profound modules in the PPIs network. CancerSEA database was used to analyze the effect of FDX1 expression levels on different functional status of COAD cells. The relationship between FDX1 expression and immune infiltration of COAD was analyzed by TIMER2.0 database. The COAD patients with high expression of FDX1 by Western blot, and the levels of immune infiltration were measured by flow cytometry. RESULTS:FDX1 was low expressed in most cancers, such as BRCA, KICH, and COAD. The overall survival (OS) and disease-specific survival (DSS) of COAD with high FDX1 expression were better than that of the low expression group. GO-KEGG enrichment analysis revealed that FDX1 and its co-expressed genes played an important role in the pathogenesis of COAD. Moreover, FDX1 expression in COAD were positively associated with "quiescence" and "inflammation" but negatively correlated with "invasion". FDX1 expression was positively correlated with infiltration levels of CD8 T cells, NK cells, and neutrophils. Oppositely, FDX1 expression was negatively correlated with that of CD4 T cells and cancer-associated fibroblasts (CAFs). Finally, 6 COAD patients with high expression of FDX1 were screened, and the proportion of CD8 T cells in cancer tissues of these patients was significantly higher than that in paracancerous, while the CD4 T cells presented the opposite pattern. CONCLUSION:FDX1 plays a role in inducing cuproptosis and modulating tumor immunity, which could be considered as potential therapeutic targets in COAD.
10.1007/s00432-022-04382-7
Identification and validation of a prognostic signature of cuproptosis-related genes for esophageal squamous cell carcinoma.
Aging
Esophageal squamous cell carcinoma (ESCC) is a highly lethal form of cancer. Cuproptosis is a recently discovered form of regulated cell death. However, its significance in ESCC remains largely unknown. In this study, we observed significant expression differences in most of the 12 cuproptosis-related genes (CRGs) in the TCGA-ESCC dataset, which was validated using GSE20347, GSE38129, and individual ESCC datasets. We were able to divide patients in the TCGA-ESCC cohort into two subgroups based on disease, and found significant differences in survivor outcomes and biological functions between these subgroups. Additionally, we identified 11 prognosis-related genes from the 12 CRGs using LASSO COX regression analysis and constructed a CRGs signature for ESCC. Patients were categorized into high- and low-risk subgroups based on their median risk score, with those in the high-risk subgroup having significantly worse overall survival than those in the low-risk subgroup. The CRGs signature was also highly accurate in predicting prognosis and survival outcomes. Univariate and multivariate Cox regression analyses revealed that 8 of the 11 CRGs were independent prognostic factors for predicting survival in ESCC patients. Furthermore, our nomogram performed well and could serve as a useful tool for predicting prognosis. Finally, our risk model was found to be relevant to the sensitivity of targeted agents and immune infiltration. Functional enrichment analysis demonstrated that the risk model was associated with biological pathways of tumor migration and invasion. In summary, our study may provide a promising prognostic signature based on CRGs and offers potential targets for personalized therapy.
10.18632/aging.205012
Validation of a Novel Cuproptosis-Related Prognostic Gene Marker and Differential Expression Associated with Lung Adenocarcinoma.
Current issues in molecular biology
BACKGROUND:Cuproptosis induction is seen as a promising alternative for immunotherapies and targeted therapies in breast cancer. The objective of this research was to examine the prognostic and biological importance of cuproptosis-related genes (CRGs) in lung adenocarcinoma (LUAD). METHODS:The following methods were used: GSE10072 dataset and TCGA database analysis, differential expression analysis of CRGs, and biological function (BP) and signaling pathway enrichment analysis, prognostic analysis and clinical analysis of CRGs, construction of the prognostic signature and RNA modified genes and miRNA analysis of CRGs in LUAD, immunoinfiltration analysis and immunohistochemical staining of DβH, UBE2D3, SOD1, UBE2D1 and LOXL2. RESULTS:AOC1, ATOX1, CCL8, CCS, COX11, CP, LOXL2, MAP2K2, PDK1, SCO2, SOD1, UBE2D1, UBE2D3 and VEGFA showed significantly higher expression, while ATP7B, DβH, PDE3B, SLC31A2, UBE2D2, UBE2D4 and ULK2 showed lower expression in LUAD tissues than normal tissues. We also found that ATP7B (4%), AOC1 (3%) PDE3B (2%), DβH (2%), CP (1%), ULK2 (1%), PDK1 (1%), LOXL2 (1%) and UBE2D3 (1%) showed higher mutation frequencies. The univariate Cox analysis was used to identify CRGs that have prognostic value. It identified 21 genes that showed significant prognostic value, containing DβH, UBE2D3, SOD1, UBE2D1 and LOXL2. Patients with DβH up-expression have a longer survival time and patients with UBE2D3, SOD1, UBE2D1 and LOXL2 down-expression also have a longer survival time. hsa-miR-29c-3p, hsa-miR-29a-3p, hsa-miR-181c-5p, hsa-miR-1245a, etc., play an important role in the miRNA regulatory network, and in LUAD, miR-29a, miR-29c and miR-181c high expression survival was longer, and miR-1245a low expression survival was longer. We also performed an analysis to examine the relationships between DβH, LOXL2, SOD1, UBE2D1 and UBE2D3 and immune infiltration in LUAD, including B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils and DCs. CONCLUSION:DβH, UBE2D3, SOD1, UBE2D1, and LOXL2 are potential candidates implicated in LUAD and can be further explored for their application as diagnostic, prognostic, and therapeutic biomarkers for LUAD.
10.3390/cimb45100536
A Polymeric Hydrogel to Eliminate Programmed Death-Ligand 1 for Enhanced Tumor Radio-Immunotherapy.
ACS nano
Programmed death-ligand 1 (PD-L1) is a specialized shield on tumor cells that evades the immune system. Even inhibited by PD-L1 antibodies, a cycling process constantly transports PD-L1 from inside to outside of cells, facilitating the renewal and replenishment of PD-L1 on the cancer cell membrane. Herein, we develop a sodium alginate hydrogel consisting of elesclomol-Cu and galactose to induce persistent cuproptosis, leading to the reduction of PD-L1 for radio-immunotherapy of colon tumors. First, a prefabricated hydrogel is synthesized by immobilizing elesclomol onto a sodium alginate saccharide chain through the coordination with bivalent copper ions (Cu), followed by incorporation of galactose. After implantation into the tumors, this prefabricated hydrogel can be further cross-linked in the presence of physiological calcium ions (Ca), resulting in the formation of a hydrogel with controlled release of elesclomol-Cu (ES-Cu) and galactose. The hydrogel effectively induces the oligomerization of DLAT and cuproptosis in colorectal cancer cells. Interestingly, radiation-induced PD-L1 upregulation is abrogated in the presence of the hydrogel, releasing ES-Cu and galactose. Consequently, the sensitization of tumor to radiotherapy and immunotherapy is significantly improved, further prolonging the survival of tumor-bearing mice in both local and metastatic tumors. Our study introduces an approach that combines cuproptosis with immunotherapy and radiotherapy.
10.1021/acsnano.3c08875
Identification of cuproptosis-related lncRNA prognostic signature for osteosarcoma.
Frontiers in endocrinology
Background:Copper is an indispensably mineral element involved in various metabolic processes and functions in the active sites of many metalloproteins. Copper dysregulation is associated with cancers such as osteosarcoma (OS), the most common primary bone malignancy with invasiveness and metastasis. However, the causality between cuproptosis and OS remains elusive. We aim to identify cuproptosis-related long non-coding RNAs (lncRNAs) for osteosarcomatous prognosis, immune microenvironment response, and immunotherapy. Methods:The Person correlation and differential expression analysis were used to identify differentially expressed cuproptosis-related lncRNAs (CRLs). The univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analysis were performed to construct the CRL signature. The Kaplan-Meier (K-M) survival analysis, receiver operating characteristic (ROC) curve, internal validation, independent prognostic analysis, and nomograph were used to evaluate the prognostic value. The functional enrichment, tumor microenvironment, immunotherapy and chemotherapy response between the two distinct groups were further explored using a series of algorithms. The expression of signature CRLs was verified by real-time quantitative polymerase chain reaction (RT-qPCR) in OS cell lines. Results:A novel CRL signature consisting of four CRLs were successfully identified. The K-M survival analysis indicated that the OS patients in the low-risk groups had a better prognosis than that in the high-risk group. Then, the ROC curve and subgroup survival analysis confirmed the prognostic evaluation performance of the signature. Equally, the independent prognostic analysis demonstrated that the CRL signature was an independently predicted factor for OS. Friends analysis determined the hub genes that played a critical role in differentially expressed genes between two distinct risk groups. In addition, the risk score was related to immunity status, immunotherapy response, and chemotherapeutic drug sensitivity. Finally, the expression of these signature CRLs detected by RT-qPCR was consistent with the bioinformatic analysis results. Conclusion:In summary, our study confirmed that the novel CRL signature could effectively evaluate prognosis, tumor immune microenvironment, and immunotherapy response in OS. It may benefit for clinical decision-making and provide new insights for personalized therapeutics.
10.3389/fendo.2022.987942
Machine learning-based solution reveals cuproptosis features in inflammatory bowel disease.
Frontiers in immunology
Background:Cuproptosis, a new cell death mode, is majorly modulated by mitochondrial metabolism and protein lipoylation. Nonetheless, cuproptosis-related genes (CRGs) have not yet been thoroughly studied for their clinical significance and relationship with the immune microenvironment in inflammatory bowel disease (IBD). Methods:We screened CRGs that had a significant correlation with immune status, which was determined utilizing single-sample GSEA (ssGSEA) and Gene Expression Omnibus datasets (GSE75214). Furthermore, utilizing the R package "CensusClusterPlus", these CRGs' expression was used to obtain different patient clusters. Subsequently, gene-set enrichment analysis (GSEA), gene set variation analysis (GSVA), and CIBERSORT assessed the variations in the enrichment of gene function and the abundance of immune cell infiltration and immune functions across these clusters. Additionally, weighted gene co-expression network analysis (WGCNA) and analysis of differentially expressed genes (DEGs) were executed, and for the purpose of identifying hub genes between these clusters, the construction of protein-protein interaction (PPI) network was done. Lastly, we used the GSE36807 and GSE10616 datasets as external validation cohorts to validate the immune profiles linked to the expression of CRG. ScRNA-seq profiling was then carried out using the publicly available dataset to examine the CRGs expression in various cell clusters and under various conditions. Results:Three CRGs, PDHA1, DLD, and FDX1, had a significant association with different immune profiles in IBD. Patients were subsequently classified into two clusters: low expression levels of DLD and PDHA1, and high expression levels of FDX1 were observed in Cluster 1 compared to Cluster 2. According to GSEA, Cluster 2 had a close association with the RNA processes and protein synthesis whereas Cluster 1 was substantially linked to environmental stress response and metabolism regulations. Furthermore, Cluster 2 had more immune cell types, which were characterized by abundant memory B cells, CD4+ T memory activated cells, and follicular helper T cells, and higher levels of immune-related molecules (CD44, CD276,CTLA4 and ICOS) than Cluster 1. During the analysis, the PPI network was divided into three significant MCODEs using the Molecular Complex Detection (MCODE) algorithm. The three MCODEs containing four genes respectively were linked to mitochondrial metabolism, cell development, ion and amino acid transport. Finally, external validation cohorts validated these findings, and scRNA-seq profiling demonstrated diverse intestinal cellular compositions with a wide variation in CRGs expression in the gut of IBD patients. Conclusions:Cuproptosis has been implicated in IBD, with PDHA1, DLD, and FDX1 having the potential as immune biomarkers and therapeutic targets. These results offer a better understanding of the development of precise, dependable, and cutting-edge diagnosis and treatment of IBD.
10.3389/fimmu.2023.1136991
Crosstalk between copper homeostasis and cuproptosis reveals a lncRNA signature to prognosis prediction, immunotherapy personalization, and agent selection for patients with lung adenocarcinoma.
Aging
BACKGROUND:Copper homeostasis and cuproptosis play critical roles in various biological processes of cancer; however, whether they can impact the prognosis of lung adenocarcinoma (LUAD) remain to be fully elucidated. We aimed to adopt these concepts to create and validate a lncRNA signature for LUAD prognostic prediction. METHODS:For this study, the TCGA-LUAD dataset was used as the training cohort, and multiple datasets from the GEO database were pooled as the validation cohort. Copper homeostasis and cuproptosis regulated genes were obtained from published studies, and various statistical methods, including Kaplan-Meier (KM), Cox, and LASSO, were used to train our gene signature CoCuLncSig. We utilized KM analysis, COX analysis, receiver operating characteristic analysis, time-dependent AUC analysis, principal component analysis, and nomogram predictor analysis in our validation process. We also compared CoCuLncSig with previous studies. We performed analyses using R software to evaluate CoCuLncSig's immunotherapeutic ability, focusing on eight immune algorithms, TMB, and TIDE. Additionally, we investigated potential drugs that could be effective in treating patients with high-risk scores. Additionally qRT-PCR examined the expression patterns of CoCuLncSig lncRNAs, and the ability of CoCuLncSig in pan-cancer was also assessed. RESULTS:CoCuLncSig containing eight lncRNAs was trained and showed strong predictive ability in the validation cohort. Compared with previous similar studies, CoCuLncSig had more prognostic ability advantages. CoCuLncSig was closely related to the immune status of LUAD, and its tight relationship with checkpoints IL10, IL2, CD40LG, SELP, BTLA, and CD28 may be the key to its potential immunotherapeutic ability. For the high CoCuLncSig score population, we found 16 drug candidates, among which epothilone-b and gemcitabine may have the most potential. The pan-cancer analysis found that CoCuLncSig was a risk factor in multiple cancers. Additionally, we discovered that some of the CoCuLncSig lncRNAs could play crucial roles in specific cancer types. CONCLUSION:The current study established a powerful prognostic CoCuLncSig signature for LUAD that was also valid for most pan-cancers. This signature could serve as a potential target for immunotherapy and might help the more efficient application of drugs to specific populations.
10.18632/aging.205281
Identification and development of a novel risk model based on cuproptosis-associated RNA methylation regulators for predicting prognosis and characterizing immune status in hepatocellular carcinoma.
Hepatology international
BACKGROUND:Cuproptosis, a novel cell death caused by excess copper, is quite obscure in hepatocellular carcinoma (HCC) and needs more investigation. METHODS:RNA-seq and clinical data of HCC patients TCGA database were analyzed to establish a predictive model through LASSO Cox regression analysis. External dataset ICGC was used for the verification. GSEA and CIBERSORT were applied to investigate the molecular mechanisms and immune microenvironment of HCC. Cuproptosis induced by elesclomol was confirmed via various in vitro experiments. The expression of prognostic genes was verified in HCC tissues using qRT-PCR analysis. RESULTS:Initially, 18 cuproptosis-associated RNA methylation regulators (CARMRs) were selected for prognostic analysis. A nine-gene signature was created by applying the LASSO Cox regression method. Survival and ROC assays were carried out to validate the model using TCGA and ICGC database. Moreover, there exhibited obvious differences in drug sensitivity in terms of common drugs. A higher tumor mutation burden was shown in the high-risk group. Additionally, significant discrepancies were found between the two groups in metabolic pathways and RNA processing via GSEA analysis. Meanwhile, CIBERSORT analysis indicated different infiltrating levels of various immune cells between the two groups. Elesclomol treatment caused a unique form of programmed cell death accompanied by loss of lipoylated mitochondrial proteins and Fe-S cluster protein. The results of qRT-PCR indicated that most prognostic genes were differentially expressed in the HCC tissues. CONCLUSION:Overall, our predictive signature displayed potential value in the prediction of overall survival of HCC patients and might provide valuable clues for personalized therapies.
10.1007/s12072-022-10460-2
An original cuproptosis-related genes signature effectively influences the prognosis and immune status of head and neck squamous cell carcinoma.
Frontiers in genetics
Recently, a non-apoptotic cell death pathway that is dependent on the presence of copper ions was proposed, named as cuproptosis. Cuproptosis have been found to have a strong association with the clinical progression and prognosis of several cancers. Head and neck squamous cell carcinoma (HNSC) are among the most common malignant tumors, with a 5-year relative survival rate ranging between 40% and 50%. The underlying mechanisms and clinical significance of cuproptosis-related genes (CRGs) in HNSC progression have not been clarified. In this study, expression pattern, biological functions, Immunohistochemistry (IHC), gene variants and immune status were analyzed to investigate the effects of CRGs on HNSC progression. Moreover, a 12-CRGs signature and nomogram were also constructed for prognosis prediction of HNSC. The results revealed that some CRGs were dysregulated, had somatic mutations, and CNV in HNSC tissues. Among them, ISCA2 was found to be upregulated in HNSC and was strongly correlated with the overall survival (OS) of HNSC patients (HR = 1.13 [1.01-1.26], -value = 0.0331). Functionally, CRGs was mainly associated with the TCA cycle, cell cycle, iron-sulfur cluster assembly, p53 signaling pathway, chemical carcinogenesis, and carbon metabolism in cancer. A 12-CRGs signature for predicting the OS was constructed which included, CAT, MTFR1L, OXA1L, POLE, NTHL1, DNA2, ATP7B, ISCA2, GLRX5, NDUFA1, and NDUFB2. This signature showed good prediction performance on the OS (HR = 5.3 [3.4-8.2], -value = 3.4e-13) and disease-specific survival (HR = 6.4 [3.6-11], -value = 2.4e-10). Furthermore, 12-CRGs signature significantly suppressed the activation of CD4 T cells and antigen processing and presentation. Finally, a nomogram based on a 12-CRGs signature and clinical features was constructed which showed a significantly adverse effect on OS (HR = 1.061 [1.042-1.081], -value = 1.6e-10) of HNSC patients. This study reveals the association of CRGs with the progression of HNSC based on multi-omics analysis. The study of CRGs is expected to improve clinical diagnosis, immunotherapeutic responsiveness and prognosis prediction of HNSC.
10.3389/fgene.2022.1084206
Cuproptosis-related LINC02454 as a biomarker for laryngeal squamous cell carcinoma based on a novel risk model and in vitro and in vivo analyses.
Journal of cancer research and clinical oncology
PURPOSE:Laryngeal squamous cell carcinomas (LSCCs) are aggressive tumors with the second-highest morbidity rate in patients with head and neck squamous cell carcinoma. Cuproptosis is a type of programmed cell death that impacts tumor malignancy and progression. The purpose of this study was to investigate the relationship between cuproptosis-related long non-coding RNAs (crlncRNAs) and the tumor immune microenvironment and chemotherapeutic drug sensitivity in LSCC, and crlncRNA impact on LSCC malignancy. MATERIALS AND METHODS:Clinical and RNA-sequencing data from patients with LSCC were retrieved from the Cancer Genome Atlas. Differentially expressed prognosis-related crlncRNAs were identified based on univariate Cox regression analysis, a crlncRNA signature for LSCC was developed and validated using LASSO Cox regression. Finally, the effect of LINC02454, the core signature crlncRNA, on LSCC malignancy progression was evaluated in vitro and in vivo. RESULTS:We identified a four-crlncRNA signature (LINC02454, AC026310.1, AC090517.2, and AC000123.1), according to which we divided the patients into high- and low-risk groups. The crlncRNA signature risk score was an independent prognostic indicator for overall and progression-free survival, and displayed high predictive accuracy. Patients with a higher abundance of infiltrating dendritic cells, M0 macrophages, and neutrophils had worse prognoses and those in the high-risk group were highly sensitive to multiple chemotherapeutic drugs. Knockdown of LINC02454 caused tumor suppression, via cuproptosis induction. CONCLUSIONS:A novel signature of four crlncRNAs was found to be highly accurate as a risk prediction model for patients with LSCC and to have potential for improving the diagnosis, prognosis, and treatment of LSCC.
10.1007/s00432-023-05281-1
Identification and validation of cuproptosis related genes and signature markers in bronchopulmonary dysplasia disease using bioinformatics analysis and machine learning.
BMC medical informatics and decision making
BACKGROUND:Bronchopulmonary Dysplasia (BPD) has a high incidence and affects the health of preterm infants. Cuproptosis is a novel form of cell death, but its mechanism of action in the disease is not yet clear. Machine learning, the latest tool for the analysis of biological samples, is still relatively rarely used for in-depth analysis and prediction of diseases. METHODS AND RESULTS:First, the differential expression of cuproptosis-related genes (CRGs) in the GSE108754 dataset was extracted and the heat map showed that the expression of NFE2L2 gene was significantly higher in the control group whereas the expression of GLS gene was significantly higher in the treatment group. Chromosome location analysis showed that both the genes were positively correlated and associated with chromosome 2. The results of immune infiltration and immune cell differential analysis showed differences in the four immune cells, significantly in Monocytes cells. Five new pathways were analyzed through two subgroups based on consistent clustering of CRG expression. Weighted correlation network analysis (WGCNA) set the screening condition to the top 25% to obtain the disease signature genes. Four machine learning algorithms: Generalized Linear Models (GLM), Random Forest (RF), Support Vector Machine (SVM), and Extreme Gradient Boosting (XGB) were used to screen the disease signature genes, and the final five marker genes for disease prediction. The models constructed by GLM method were proved to be more accurate in the validation of two datasets, GSE190215 and GSE188944. CONCLUSION:We eventually identified two copper death-associated genes, NFE2L2 and GLS. A machine learning model-GLM was constructed to predict the prevalence of BPD disease, and five disease signature genes NFATC3, ERMN, PLA2G4A, MTMR9LP and LOC440700 were identified. These genes that were bioinformatics analyzed could be potential targets for identifying BPD disease and treatment.
10.1186/s12911-023-02163-x
A cuproptosis-related lncRNA signature predicts the prognosis and immune cell status in head and neck squamous cell carcinoma.
Frontiers in oncology
Introduction:The incidence of head and neck squamous cell carcinoma (HNSCC), one of the most prevalent tumors, is increasing rapidly worldwide. Cuproptosis, as a new copper-dependent cell death form, was proposed recently. However, the prognosis value and immune effects of cuproptosis-related lncRNAs (CRLs) have not yet been elucidated in HNSCC. Methods:In the current study, the expression pattern, differential profile, clinical correlation, DNA methylation, functional enrichment, univariate prognosis factor, and the immune effects of CRLs were analyzed. A four-CRL signature was constructed using the least absolute shrinkage and selection operator (LASSO) algorithm. Results:Results showed that 20 CRLs had significant effects on the stage progression of HNSCC. Sixteen CRLs were tightly correlated with the overall survival (OS) of HNSCC patients. Particularly, lnc-FGF3-4 as a single risk factor was upregulated in HNSCC tissues and negatively impacted the prognosis of HNSCC. DNA methylation probes of cg02278768 (MIR9-3HG), cg07312099 (ASAH1-AS1), and cg16867777 (TIAM1-AS1) were also correlated with the prognosis of HNSCC. The four-CRL signature that included MAP4K3-DT, lnc-TCEA3-1, MIR9-3HG, and CDKN2A-DT had a significantly negative effect on the activation of T cells follicular helper and OS probability of HNSCC. Functional analysis revealed that cell cycle, DNA replication, and p53 signal pathways were enriched. Discussion:A novel CRL-related signature has the potential of prognosis prediction in HNSCC. Targeting CRLs may be a promising therapeutic strategy for HNSCC.
10.3389/fonc.2023.1055717
Development and validation of cuproptosis-related lncRNA signatures for prognosis prediction in colorectal cancer.
BMC medical genomics
BACKGROUND:Cuproptosis, a novel form of programmed cell death, plays an essential role in various cancers. However, studies of the function of cuproptosis lncRNAs (CRLs) in colorectal cancer (CRC) remain limited. Thus, this study aims to identify the cuprotosis-related lncRNAs (CRLs) in CRC and to construct the potential prognostic CRLs signature model in CRC. METHODS:First, we downloaded RNA-Seq data and clinical information of CRC patients from TCGA database and obtained the prognostic CRLs based on typical expression analysis of cuproptosis-related genes (CRGs) and univariate Cox regression. Then, we constructed a prognostic model using the Least Absolute Shrinkage and Selection Operator algorithm combined with multiple Cox regression methods (Lasso-Cox). Next, we generated Kaplan-Meier survival and receiver operating characteristic curves to estimate the performance of the prognostic model. In addition, we also analysed the relationships between risk signatures and immune infiltration, mutation, and drug sensitivity. Finally, we performed quantitative reverse transcription polymerase chain reaction (qRT -PCR) to verify the prognostic model. RESULT:Lasso-Cox analysis revealed that four CRLs, SNHG16, LENG8-AS1, LINC0225, and RPARP-AS1, were related to CRC prognosis. Receiver operating characteristic (ROC) and Kaplan-Meier analysis curves indicated that this model performs well in prognostic predictions of CRC patients. The DCA results also showed that the model included four gene signatures was better than the traditional model. In addition, GO and KEGG analyses revealed that DE-CRLs are enriched in critical signalling pathway, such as chemical carcinogenesis-DNA adducts and basal cell carcinoma. Immune infiltration analysis revealed significant differences in immune infiltration cells between the high-risk and low-risk groups. Furthermore, significant differences in somatic mutations were noted between the high-risk and low-risk groups. Finally, we also validated the expression of four CRLs in FHCs cell lines and CRC cell lines using qRT-PCR. CONCLUSION:The signature composed of SNHG16, LENG8-AS1, LINC0225, and RPARP-AS1, which has better performance in predicting colorectal cancer prognosis and are promising biomarkers for prognosis prediction of CRC.
10.1186/s12920-023-01487-x
Cuproptosis/ferroptosis-related gene signature is correlated with immune infiltration and predict the prognosis for patients with breast cancer.
Frontiers in pharmacology
Breast invasive carcinoma (BRCA) is a malignant tumor with high morbidity and mortality, and the prognosis is still unsatisfactory. Both ferroptosis and cuproptosis are apoptosis-independent cell deaths caused by the imbalance of corresponding metal components in cells and can affect the proliferation rate of cancer cells. The aim in this study was to develop a prognostic model of cuproptosis/ferroptosis-related genes (CFRGs) to predict survival in BRCA patients. Transcriptomic and clinical data for breast cancer patients were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Cuproptosis and ferroptosis scores were determined for the BRCA samples from the TCGA cohort using Gene Set Variation Analysis (GSVA), followed by weighted gene coexpression network analysis (WGCNA) to screen out the CFRGs. The intersection of the differentially expressed genes grouped by high and low was determined using X-tile. Univariate Cox regression and least absolute shrinkage and selection operator (LASSO) were used in the TGCA cohort to identify the CFRG-related signature. In addition, the relationship between risk scores and immune infiltration levels was investigated using various algorithms, and model genes were analyzed in terms of single-cell sequencing. Finally, the expression of the signature genes was validated with quantitative real-time PCR (qRT‒PCR) and immunohistochemistry (IHC). A total of 5 CFRGs (ANKRD52, HOXC10, KNOP1, SGPP1, TRIM45) were identified and were used to construct proportional hazards regression models. The high-risk groups in the training and validation sets had significantly worse survival rates. Tumor mutational burden (TMB) was positively correlated with the risk score. Conversely, Tumor Immune Dysfunction and Exclusion (TIDE) and tumor purity were inversely associated with risk scores. In addition, the infiltration degree of antitumor immune cells and the expression of immune checkpoints were lower in the high-risk group. In addition, risk scores and mTOR, Hif-1, ErbB, MAPK, PI3K/AKT, TGF-β and other pathway signals were correlated with progression. We can accurately predict the survival of patients through the constructed CFRG-related prognostic model. In addition, we can also predict patient immunotherapy and immune cell infiltration.
10.3389/fphar.2023.1192434
Cuproptosis-related prognostic signatures predict the prognosis and immunotherapy in HCC patients.
Medicine
Cuproptosis, an unusual type of programmed cell death mechanism of cell death, involved the disruption of specific mitochondrial metabolic enzymes in the occurrence and development of tumors. However, it was still unclear how the relationship between cuproptosis-related genes (CRGs) may contribute to hepatocellular carcinoma (HCC) potential the prognosis of HCC remained limited. Here, the landscape of 14 CRGs in HCC was evaluated using the Cancer Genome Atlas and International Cancer Genome Consortium datasets. And then, 4 CRGs (ATP7A, MTF1, GLS, and CDKN2A) were screened for the construction of risk signatures for prognosis and drug therapy. The HCC patients with CRGs high-risk showed poor prognosis than those with low risk. Moreover, the CRGs risk signature was shown to be an independent prognostic factor and associated with the immune microenvironment in HCC. Meanwhile, we constructed and verified a prognostic model based on cuproptosis-related lncRNAs (Cr-lncRNAs). We obtained 291 Cr-lncRNAs and constructed Cr-lncRNA prognosis signature based on 3 key Cr-lncRNAs (AC026356.1, NRAV, AL031985.3). The Cr-lncRNA prognosis signature was also an independent prognostic factor and associated with the immune microenvironment in HCC. Finally, the drug sensitivity database showed that 8 candidate drugs related to CRGs signature and Cr-lncRNAs signature. In summary, we evaluated and validated the CRGs and Cr-lncRNAs as potential predictive markers for prognosis, immunotherapy, and drug candidate with the personalized diagnosis and treatment of HCC.
10.1097/MD.0000000000034741
Novel targets for gastric cancer: The tumor microenvironment (TME), N6-methyladenosine (m6A), pyroptosis, autophagy, ferroptosis and cuproptosis.
Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie
Gastric cancer (GC) is a fatal illness, and its mortality rate is very high all over the world. At present, it is a serious health problem for any country. It is a multifactorial disease due to the rising drug resistance and the increasing global cancer burden, the treatment of GC still faces many obstacles and problems. In recent years, research on GC is being carried out continuously, and we hope to address the new targets of GC treatment through this review. At the same time, we also hope to discover new ways to fight GC and create more gospel for clinical patients. First, we discuss the descriptive tumor microenvironment (TME), N6-methyladenosine (m6A), pyroptosis, autophagy, ferroptosis, and cuproptosis. Finally, we expounded on the new or potential targets of GC treatment.
10.1016/j.biopha.2023.114883
Pan-cancer integrated bioinformatics analysis reveals cuproptosis related gene FDX1 is a potential prognostic and immunotherapeutic biomarker for lower-grade gliomas.
Frontiers in molecular biosciences
FDX1 participates in cuproptosis, a copper-dependent cell death mode, which might influence tumor progressions like ferroptosis and pyroptosis. However, the role of FDX1 in tumors remains to be explored. This study investigated FDX1 expression features, and correlations to prognosis, tumor stages, immune microenvironment, and cuproptosis from a pan-cancer perspective based on integrated bioinformatics. FDX1 mRNA and clinical data were obtained from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Broad Institute Cancer Cell Line Encyclopedia (CCLE) databases. Differential expression of FDX1 in tumor stages was performed on GEPIA2.0. Cox proportional hazard regression and survival curve were used to analyze the prognostic value of FDX1. The relationships between FDX1 expression and immune infiltration, immune cells, immune checkpoints, tumor mutation burden (TMB), microsatellite instability (MSI), mismatch repair (MMR), and DNA methyltransferase (DNMT) were explored. GSEA was utilized to find the biological function of FDX1 in LGG. Results showed that FDX1 was abnormally expressed in multiple tumor types and demonstrated variability in various tumor stages. Survival analysis revealed FDX1 predicted poor prognosis in glioma (GBMLGG), brain lower-grade glioma (LGG), and good prognosis in the pan-kidney cohort (KIPAN), and kidney renal clear cell carcinoma (KIRC). Immune correlation analysis suggested FDX1 showed positive correlations to StromalScore, ImmuneScore, ESTIMATEScore in LGG and negative correlation in KIRC. Additionally, positive correlations were observed between FDX1 and immune cells infiltration, immune checkpoints, tumor stemness, homologous recombination deficiency (HRD), and TMB in LGG in the pan-cancer analysis. Validation with CGGA suggested prognostic value and immune correlation of FDX1 in LGG. Specifically, high expression of FDX1 was accompanied by high expression of immune checkpoints such as CD276 (B7-H3), CD274 (PD-L1), PDCD1LG2 (PD-L2), CTLA4, and HAVCR2. These findings illustrated that FDX1 might be considered a potential poor prognosis biomarker and immunotherapy predictor in LGG.
10.3389/fmolb.2023.963639
Identification of a novel cuproptosis-related gene signature for multiple myeloma diagnosis.
Immunity, inflammation and disease
BACKGROUND:Multiple myeloma (MM) ranks second among the most prevalent hematological malignancies. Recent studies have unearthed the promise of cuproptosis as a novel therapeutic intervention for cancer. However, no research has unveiled the particular roles of cuproptosis-related genes (CRGs) in the prediction of MM diagnosis. METHODS:Microarray data and clinical characteristics of MM patients were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed gene analysis, least absolute shrinkage and selection operator (LASSO) and support vector machine-recursive feature elimination (SVM-RFE) algorithms were applied to identify potential signature genes for MM diagnosis. Predictive performance was further assessed by receiver operating characteristic (ROC) curves, nomogram analysis, and external data sets. Functional enrichment analysis was performed to elucidate the involved mechanisms. Finally, the expression of the identified genes was validated by quantitative real-time polymerase chain reaction (qRT-PCR) in MM cell samples. RESULTS:The optimal gene signature was identified using LASSO and SVM-RFE algorithms based on the differentially expressed CRGs: ATP7A, FDX1, PDHA1, PDHB, MTF1, CDKN2A, and DLST. Our gene signature-based nomogram revealed a high degree of accuracy in predicting MM diagnosis. ROC curves showed the signature had dependable predictive ability across all data sets, with area under the curve values exceeding 0.80. Additionally, functional enrichment analysis suggested significant associations between the signature genes and immune-related pathways. The expression of the genes was validated in MM cells, indicating the robustness of these findings. CONCLUSION:We discovered and validated a novel CRG signature with strong predictive capability for diagnosing MM, potentially implicated in MM pathogenesis and progression through immune-related pathways.
10.1002/iid3.1058
Identification and validation of potential diagnostic signature and immune cell infiltration for NAFLD based on cuproptosis-related genes by bioinformatics analysis and machine learning.
Frontiers in immunology
Background and aims:Cuproptosis has been identified as a key player in the development of several diseases. In this study, we investigate the potential role of cuproptosis-related genes in the pathogenesis of nonalcoholic fatty liver disease (NAFLD). Method:The gene expression profiles of NAFLD were obtained from the Gene Expression Omnibus database. Differential expression of cuproptosis-related genes (CRGs) were determined between NAFLD and normal tissues. Protein-protein interaction, correlation, and function enrichment analyses were performed. Machine learning was used to identify hub genes. Immune infiltration was analyzed in both NAFLD patients and controls. Quantitative real-time PCR was employed to validate the expression of hub genes. Results:Four datasets containing 115 NAFLD and 106 control samples were included for bioinformatics analysis. Three hub CRGs (NFE2L2, DLD, and POLD1) were identified through the intersection of three machine learning algorithms. The receiver operating characteristic curve was plotted based on these three marker genes, and the area under the curve (AUC) value was 0.704. In the external GSE135251 dataset, the AUC value of the three key genes was as high as 0.970. Further nomogram, decision curve, calibration curve analyses also confirmed the diagnostic predictive efficacy. Gene set enrichment analysis and gene set variation analysis showed these three marker genes involved in multiple pathways that are related to the progression of NAFLD. CIBERSORT and single-sample gene set enrichment analysis indicated that their expression levels in macrophages, mast cells, NK cells, Treg cells, resting dendritic cells, and tumor-infiltrating lymphocytes were higher in NAFLD compared with control liver samples. The ceRNA network demonstrated a complex regulatory relationship between the three hub genes. The mRNA level of these hub genes were further confirmed in a mouse NAFLD liver samples. Conclusion:Our study comprehensively demonstrated the relationship between NAFLD and cuproptosis, developed a promising diagnostic model, and provided potential targets for NAFLD treatment and new insights for exploring the mechanism for NAFLD.
10.3389/fimmu.2023.1251750
Construction of prognostic risk model of bladder cancer based on cuproptosis-related long non-coding RNAs.
Zhejiang da xue xue bao. Yi xue ban = Journal of Zhejiang University. Medical sciences
OBJECTIVES:To construct a prognosis risk model based on long noncoding RNAs (lncRNAs) related to cuproptosis and to evaluate its application in assessing prognosis risk of bladder cancer patients. METHODS:RNA sequence data and clinical data of bladder cancer patients were downloaded from the Cancer Genome Atlas database. The correlation between lncRNAs related to cuproptosis and bladder cancer prognosis was analyzed with Pearson correlation analysis, univariate Cox regression, Lasso regression, and multivariate Cox regression. Then a cuproptosis-related lncRNA prognostic risk scoring equation was constructed. Patients were divided into high-risk and low-risk groups based on the median risk score, and the immune cell abundance between the two groups were compared. The accuracy of the risk scoring equation was evaluated using Kaplan-Meier survival curves, and the application of the risk scoring equation in predicting 1, 3 and 5-year survival rates was evaluated using receiver operating characteristic (ROC) curves. Univariate and multivariate Cox regression were used to screen for prognostic factors related to bladder cancer patients, and a prognostic risk assessment nomogram was constructed, the accuracy of which was evaluated with calibration curves. RESULTS:A prognostic risk scoring equation for bladder cancer patients was constructed based on nine cuproptosis-related lncRNAs. Immune infiltration analysis showed that the abundances of M0 macrophages, M1 macrophages, M2 macrophages, resting mast cells and neutrophils in the high-risk group were significantly higher than those in the low-risk group, while the abundances of CD8 T cells, helper T cells, regulatory T cells and plasma cells in the low-risk group were significantly higher than those in the high-risk group (all <0.05). Kaplan-Meier survival curve analysis showed that the total survival and progression-free survival of the low-risk group were longer than those of the high-risk group (both <0.01). Univariate and multivariate Cox analysis showed that the risk score, age and tumor stage were independent factors for patient prognosis. The ROC curve analysis showed that the area under the curve (AUC) of the risk score in predicting 1, 3 and 5-year survival was 0.716, 0.697 and 0.717, respectively. When combined with age and tumor stage, the AUC for predicting 1-year prognosis increased to 0.725. The prognostic risk assessment nomogram for bladder cancer patients constructed based on patient age, tumor stage, and risk score had a prediction value that was consistent with the actual value. CONCLUSIONS:A bladder cancer patient prognosis risk assessment model based on cuproptosis-related lncRNA has been successfully constructed in this study. The model can predict the prognosis of bladder cancer patients and their immune infiltration status, which may also provide a reference for tumor immunotherapy.
10.3724/zdxbyxb-2022-0539
Artificial intelligence reveals dysregulation of osteosarcoma and cuproptosis-related biomarkers, PDHA1, CDKN2A and neutrophils.
Scientific reports
At present, the impact of cuproptosis-related genes in the study of osteosarcoma is largely unknown. Genome-wide data of osteosarcoma and controls were downloaded from 3 different databases, and specific diagnostic models associated with cuproptosis in osteosarcoma were constructed by support vector machines with artificial intelligence, random forest trees and LASSO regression. Differential analysis of immune cell infiltration was examined using routine blood data from 25,665 cases. Differential expression was examined using immunohistochemistry and PCR. PDHA1 and CDKN2A were obtained as specific cuproptosis-related biomarkers for osteosarcoma after artificial intelligence analysis. PDHA1, CDKN2A and neutrophils were differentially expressed in OS and control groups. PDHA1 and CDKN2A are significantly dysregulated in OS and are able to serve as biomarkers of OS.
10.1038/s41598-023-32195-2
Development and validation of a cuproptosis-related lncRNA model correlated to the cancer-associated fibroblasts enable the prediction prognosis of patients with osteosarcoma.
Journal of bone oncology
Background:Osteosarcoma is the most common primary pediatric and adolescent bone malignancy. An imbalance in copper homeostasis caused by copper ion accumulation could increase intracellular toxicity and regulate cancer cell growth. This study aimed to identify long non-coding RNAs (lncRNAs) associated with cuproptosis to predict prognosis and target drug use to improve patient survival. Methods:RNA sequencing and relevant clinical information of ninety-three osteosarcoma patients were obtained from the TARGET database. We then identified thirteen prognostic cuproptosis-related lncRNAs(CRLncs) using coexpression and univariate Cox analyses. The prognostic risk model with three CRLncs was constructed using the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis. Patients were divided into low-risk and high-risk subgroups using the median risk score. The tumor microenvironment (TME) and immune status of identified subgroups were analyzed using ESTIMATE, CIBERSORT, MCP-counter, xCELL, EPIC, and ssGSEA analyses. Functional analyses were conducted to elucidate the underlying mechanisms, including GO, KEGG, GSVA, and GSEA analyses. Also, the relationships between the model, tumor immunity, and drug sensitivity were explored. Lastly, the expression level of ZNF37BP, AL353759.1, and AC005034.5 was validated . Results:We constructed a model containing three CRLncs (ZNF37BP, AL353759.1, and AC005034.5) and validated its excellent prognostic and predictive power. The AUC curves for 1-year, 3-year, and 5-year survival probabilities were 0.76, 0.84, and 0.89, respectively. Patients in the high-risk group had a shorter overall survival (OS) time than those in the low-risk. The stroma score and cancer-associated fibroblasts (CAFs) were significantly higher in the low-risk group. Immune cells such as T cells CD4 naive, T cells gamma delta, NK cells resting, dendritic cells resting, and mast cells activated were significantly upregulated in the high-risk group. Based on functional analyses, the PI3K-Akt pathway was identified as a critical metabolic pathway in osteosarcoma. Additionally, we obtained three potentially effective drugs for OS: erlotinib, MP470, and WH-4-023 targeting the PI3K-Akt pathway. The expression level of ZNF37BP was significantly elevated in OS cell lines than in normal osteoblast hFOB1.19 cells, and that of ATP7A, LIPT1, AL353759.1, and AC005034.5 were decreased considerably in OS cell lines. Conclusion:Cuproptosis-related lncRNAs are correlated with the CAFs of osteosarcoma, and this could serve as a foundation for OS survival prediction and treatment.
10.1016/j.jbo.2022.100463
The cuproptosis-related gene glutaminase promotes alveolar macrophage copper ion accumulation in chronic obstructive pulmonary disease.
International immunopharmacology
Cuproptosis, a novel mode of cell death, is strongly associated with a variety of diseases. However, the contribution of cuproptosis to the onset or progression of chronic obstructive pulmonary disease (COPD), the third most common chronic cause of mortality, is not yet clear. To investigate the potential role of cuproptosis in COPD, raw datasets from multiple public clinical COPD databases (including RNA-seq, phenotype, and lung function data) were used. For further validation, mice exposed to cigarette smoke for three months were used as in vivo models, and iBMDMs (immortalized bone marrow-derived macrophages) and RAW264.7 cells stimulated with cigarette smoke extract were used as in vitro models. For the first time, the expression of the cuproptosis-related gene glutaminase (GLS) was found to be decreased in COPD, and the low expression of GLS was significantly associated with the grade of pulmonary function. In vivo experiments confirmed the decreased expression of GLS in COPD, particularly in alveolar macrophages. Furthermore, in vitro studies revealed that copper ions accumulated in alveolar macrophages, leading to a substantially decreased amount of cell activity of macrophages when stimulated with cigarette extract. In summary, we demonstrate the high potential of GLS as an avenue for diagnosis and therapy in COPD.
10.1016/j.intimp.2024.111585
Cuproptosis Depicts Immunophenotype and Predicts Immunotherapy Response in Lung Adenocarcinoma.
Journal of personalized medicine
BACKGROUND:Although significant progress has been made in immunotherapy for lung adenocarcinoma (LUAD), there is an urgent need to identify effective indicators to screen patients who are suitable for immunotherapy. Systematically investigating the cuproptosis-related genes (CRGs) in LUAD may provide new ideas for patients' immunotherapy stratification. METHOD:We comprehensively analyzed the landscape of 12 CRGs in a merged TCGA and GEO LUAD cohort. We investigated the associations between tumor microenvironment and immunophenotypes. We utilized a risk score to predict the prognosis and immunotherapy response for an individual patient. Additionally, we conducted CCK-8 experiments to evaluate the impact of DLGAP5 knockdown on A549 cell proliferation. RESULT:We utilized an integrative approach to analyze 12 CRGs and differentially expressed genes (DEGs) in LUAD samples, resulting in the identification of two distinct CRG clusters and two gene clusters. Based on these clusters, we generated immunophenotypes and observed that the inflamed phenotype had the most abundant immune infiltrations, while the desert phenotype showed the poorest immune infiltrations. We then developed a risk score model for individual patient prognosis and immunotherapy response prediction. Patients in the low-risk group had higher immune scores and ESTIMATE scores, indicating an active immune state with richer immune cell infiltrations and higher expression of immune checkpoint genes. Moreover, the low-risk group exhibited better immunotherapy response according to IPS, TIDE scores, and Imvigor210 cohort validation results. In addition, our in vitro wet experiments demonstrated that DLGAP5 knockdown could suppress the cell proliferation of A549. CONCLUSION:Novel cuproptosis molecular patterns reflected the distinct immunophenotypes in LUAD patients. The risk model might pave the way to stratify patients suitable for immunotherapy and predict immunotherapy response.
10.3390/jpm13030482
Genomic and immune landscape in hepatocellular carcinoma: Implications for personalized therapeutics.
Environmental toxicology
Hepatocellular carcinoma (HCC) is a globally prevalent malignancy, marked by genetic heterogeneity and intricate tumor microenvironment interactions. In this study, we undertook a detailed single-cell analysis of six active HCC patients, highlighting strong correlations between gene expression levels and cellular characteristics. UMAP clustering revealed seven distinct cell categories with associated gene expressions. A divergence was observed in tumor cells into high and low cuproptosis groups, each associated with distinct pathways: oxidative stress for the high cuproptosis group and inflammatory and angiogenesis pathways for the low group. CellChat analysis on the TCGA-LIHC cohort displayed unique intercellular interactions among hepatocytes, T cells, and other cells, with pathways like COLLAGEN and VEGF being pivotal. Functional enrichment analyses exposed pathways enriched between cuproptosis groups, with KEGG emphasizing diseases like Parkinson's. COX survival analysis identified key prognostic genes, revealing distinct survival rates between risk groups in TCGA and GSE14520 cohorts. Mutation data highlighted missense mutations, with TTN, TP53, and CTNNB1 being the most mutated in HCC. Immune infiltration analysis via CIBERSORTx indicated differences between risk groups in NK cells, neutrophils, and other cells. Our drug sensitivity investigation showed significant correlations between model genes and drug responsiveness, emphasizing the importance of patient risk stratification for therapeutic approaches. Further, ATP6V1G1 was recognized in its role in apoptosis and migration in HCC cells. In conclusion, our findings illuminate the complexities of HCC progression, potential predictive genetic markers for drug response, and the pivotal role of ATP6V1G1, suggesting avenues for targeted therapeutic strategies in HCC.
10.1002/tox.24062
Prediction of risk and clinical outcome of cuproptosis in lung squamous carcinoma.
BMC pulmonary medicine
BACKGROUND:Lung squamous cell carcinoma (LUSC) is an important subtype of non-small cell lung cancer. Its special clinicopathological features and molecular background determine the limitations of its treatment. A recent study published on Science defined a newly regulatory cell death (RCD) form - cuproptosis. Which manifested as an excessive intracellular copper accumulation, mitochondrial respiration-dependent, protein acylation-mediated cell death. Different from apoptosis, pyroptosis, necroptosis, ferroptosis and other forms of regulatory cell death (RCD). The imbalance of copper homeostasis in vivo will trigger cytotoxicity and further affect the occurrence and progression of tumors. Our study is the first to predict the prognosis and immune landscape of cuproptosis-related genes (CRGs) in LUSC. METHODS:The RNA-seq profiles and clinical data of LUSC patients were downloaded from TCGA and GEO databases and then combined into a novel cohort. R language packages are used to analyze and process the data, and CRGs related to the prognosis of LUSC were screened according to the differentially expressed genes (DEGs). After analyzed the tumor mutation burden (TMB), copy number variation (CNV) and CRGs interaction network. Based on CRGs and DEGs, cluster analysis was used to classify LUSC patients twice. The selected key genes were used to construct a CRGs prognostic model to further analyze the correlation between LUSC immune cell infiltration and immunity. Through the risk score and clinical factors, a more accurate nomogram was further constructed. Finally, the drug sensitivity of CRGs in LUSC was analyzed. RESULTS:Patients with LUSC were divided into different cuproptosis subtypes and gene clusters, showing different levels of immune infiltration. The risk score showed that the high-risk group had higher tumor microenvironment score, lower tumor mutation load frequency and worse prognosis than the low-risk group. In addition, the high-risk group was more sensitive to vinorelbine, cisplatin, paclitaxel, doxorubicin, etoposide and other drugs. CONCLUSIONS:Through bioinformatics analysis, we successfully constructed a prognostic risk assessment model based on CRGs, which can not only accurately predict the prognosis of LUSC patients, but also evaluate the patient 's immune infiltration status and sensitivity to chemotherapy drugs. This model shows satisfactory predictive results and provides a reference for subsequent tumor immunotherapy.
10.1186/s12890-023-02490-9
Underlying mechanisms of novel cuproptosis-related dihydrolipoamide branched-chain transacylase E2 (DBT) signature in sunitinib-resistant clear-cell renal cell carcinoma.
Aging
Renal cell carcinoma (RCC) is the predominant form of malignant kidney cancer. Sunitinib, a primary treatment for advanced, inoperable, recurrent, or metastatic RCC, has shown effectiveness in some patients but is increasingly limited by drug resistance. Recently identified cuproptosis, a copper-ion-dependent form of programmed cell death, holds promise in combating cancer, particularly drug-resistant types. However, its effectiveness in treating drug resistant RCC remains to be determined. Exploring cuproptosis's regulatory mechanisms could enhance RCC treatment strategies. Our analysis of data from the GEO and TCGA databases showed that the cuproptosis-related gene DBT is markedly under expressed in RCC tissues, correlating with worse prognosis and disease progression. In our study, we investigated copper CRGs in ccRCC, noting substantial expression differences, particularly in advanced-stage tumors. We established a connection between CRG expression levels and patient survival, positioning CRGs as potential therapeutic targets for ccRCC. In drug resistant RCC cases, we found distinct expression patterns for DBT and GLS CRGs, linked to treatment resistance. Our experiments demonstrated that increasing DBT expression significantly reduces RCC cell growth and spread, underscoring its potential as a therapeutic target. This research sheds new light on the role of CRGs in ccRCC and their impact on drug resistance.
10.18632/aging.205504
Signature construction and molecular subtype identification based on cuproptosis-related genes to predict the prognosis and immune activity of patients with hepatocellular carcinoma.
Frontiers in immunology
Background:Hepatocellular carcinoma (HCC) is one of the most common malignancies in the world, with high incidence, high malignancy, and low survival rate. Cuproptosis is a novel form of cell death mediated by lipoylated TCA cycle proteins-mediated novel cell death pathway and is highly associated with mitochondrial metabolism. However, the relationship between the expression level of cuproptosis-related genes (CRGs) and the prognosis of HCC is still unclear. Methods:Combining the HCC transcriptomic data from The Cancer Genome Atlas(TCGA) and Gene Expression Omnibus (GEO) databases, we identified the differentially expressed cuproptosis-related genes (DECRGs) and obtained the prognosis-related DECRGs through univariate regression analysis.LASSO and multivariate COX regression analyses of these DECRGs yielded four genes that were used to construct the signature. Next, we use ROC curves to evaluate the performance of signatures. The tumor microenvironment, immune infiltration, tumor mutation load, half-maximum suppression concentration, and immunotherapy effects were also compared between the low-risk and high-risk groups. Finally, we analyzed the expression level, prognosis, and immune infiltration correlation on the four genes that constructed the model. Results:Four DECRGs s were used to construct the signature. The ROC curves indicated that signature can better assess the prognosis of HCC patients. Patients were grouped according to the signature risk score. Patients in the low-risk group had a significantly longer survival time than those in the high-risk group. Furthermore, the tumor mutation burden (TMB) values were associated with the risk score and the higher-risk group had a higher proportion of TP53 mutations than the low-risk group.ESTIMATE analysis showed significant differences in stromal scores between the two groups.N6-methyladenosine (m6A) and multiple immune checkpoints were expressed at higher levels in the high-risk group. Then, we found that signature score correlated with chemotherapeutic drug sensitivity and immunotherapy efficacy in HCC patients. Finally, we further confirmed that the four DECRGs genes were associated with the prognosis of HCC through external validation. Conclusions:We studied from the cuproptosis perspective and developed a new prognostic feature to predict the prognosis of HCC patients. This signature with good performance will help physicians to evaluate the overall prognosis of patients and may provide new ideas for clinical decision-making and treatment strategies.
10.3389/fimmu.2022.990790
METTL3 as a novel diagnosis and treatment biomarker and its association with glycolysis, cuproptosis and ceRNA in oesophageal carcinoma.
Journal of cellular and molecular medicine
METTL3 has been shown to be involved in regulating a variety of biological processes. However, the relationship between METTL3 expression and glycolysis, cuproptosis-related genes and the ceRNA network in oesophageal carcinoma (ESCA) remains unclear. ESCA expression profiles from databases were obtained, and target genes were identified using differential analysis and visualization. Immunohistochemistry (IHC) staining assessed METTL3 expression differences. Functional enrichment analysis using GO, KEGG and GSEA was conducted on the co-expression profile of METTL3. Cell experiments were performed to assess the effect of METTL3 interference on tumour cells. Correlation and differential analyses were carried out to assess the relationship between METTL3 with glycolysis and cuproptosis. qRT-PCR was used to validate the effects of METTL3 interference on glycolysis-related genes. Online tools were utilized to screen and construct ceRNA networks based on the ceRNA theory. METTL3 expression was significantly higher in ESCA compared to the controls. The IHC results were consistent with the above results. Enrichment analysis revealed that METTL3 is involved in multiple pathways associated with tumour development. Significant correlations were observed between METTL3 and glycolysis-related genes and cuproptosis-related gene. Experiments confirmed that interfered with METTL3 significantly inhibited glucose uptake and lactate production in tumour cells, and affected the expression of glycolytic-related genes. Finally, two potential ceRNA networks were successfully predicted and constructed. Our study establishes the association between METTL3 overexpression and ESCA progression. Additionally, we propose potential links between METTL3 and glycolysis, cuproptosis and ceRNA, presenting a novel targeted therapy strategy for ESCA.
10.1111/jcmm.18195
A novel signature of combing cuproptosis- with ferroptosis-related genes for prediction of prognosis, immunologic therapy responses and drug sensitivity in hepatocellular carcinoma.
Frontiers in oncology
Background:Our study aimed to construct a novel signature (CRFs) of combing cuproptosis-related genes with ferroptosis-related genes for the prediction of the prognosis, responses of immunological therapy, and drug sensitivity of hepatocellular carcinoma (HCC) patients. Methods:The RNA sequencing and corresponding clinical data of patients with HCC were downloaded from The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC), GSE76427, GSE144269, GSE140580, Cancer Cell Line Encyclopedia (CCLE), and IMvigor210 cohorts. CRFs was constructed using the least absolute shrinkage and selection operator (LASSO) algorithm. The analyses involved in the prognosis, response to immunologic therapy, efficacy of transcatheter arterial chemoembolization (TACE) therapy, and drug sensitivity were performed. Furthermore, the molecular function, somatic mutation, and stemness analyses were further performed between the low- and high-risk groups, respectively. In this study, the statistical analyses were performed by using the diverse packages of R 4.1.3 software and Cytoscape 3.8.0. Results:CRFs included seven genes (G6PD, NRAS, RRM2, SQSTM1, SRXN1, TXNRD1, and ZFP69B). Multivariate Cox regression analyses demonstrated that CRFs were an independent risk factor for prognosis. In addition, these patients in the high-risk group presented with worse prognoses and a significant state of immunosuppression. Moreover, patients in the high-risk group might achieve greater outcomes after receiving immunologic therapy, while patients in the low-risk group are sensitive to TACE. Furthermore, we discovered that patients in the high-risk group may benefit from the administration of sunitinib. In addition, enhanced mRANsi and tumor mutation burden (TMB) yielded in the high-risk group. Additionally, the functions enriched in the low-risk group differed from those in the other group. Conclusion:In summary, CRFs may be regarded not only as a novel biomarker of worse prognosis, but also as an excellent predictor of immunotherapy response, efficacy of TACE and drug sensitivity in HCC, which is worthy of clinical promotion.
10.3389/fonc.2022.1000993
Construction of lncRNA prognostic model related to cuproptosis in esophageal carcinoma.
Frontiers in genetics
Esophageal carcinoma (ESCA) is one of the most prevalent malignant tumors in the world. The prognosis of patients has significantly improved with the development of surgery, targeted therapy and immunotherapy. But the 5-year survival rate of ESCA patients is still incredibly low. Cuproptosis is a type of mitochondrial cell death induced by copper. It is unclear how cuproptosis-related lncRNAs (CRLs) affect ESCA prognosis. In this study, we obtained the clinical data of ESCA patients, the transcriptome data from TCGA and identified CRLs by co-expression analysis, lasso regression, and cox regression analysis, to build a prognostic model. Then we validated the prognostic model using the Kaplan-Meier curve, cox regression analysis, and ROC, to create a nomogram based on risk score to forecast the prognosis of ESCA. Next, the immune escape of the CRLs was examined using the TIDE algorithm to assess its sensitivity to possible ESCA medications. To predict the prognosis of ESCA patients, we created a predictive model using 6 CRLs (AC034199.1, AC125437.1, AC107032.2, CTBP1-DT, AL024508.1, and AC008610.1), validated by the Kaplan-Meier and ROC curves. The model has a higher diagnostic value compared to other clinical features. The 6 CRLs expressed high in TCGA and ESCA specimens. Enrichment analysis revealed CRLs largely contributed to the interaction between cytokines and their receptors as well as complement coagulation cascades. The immunity escape analysis demonstrated that immunotherapy had a worse effect in the low-risk group than in the high-risk group. Additionally, we screened out potential antineoplastic drugs according to the results of the immunoassay and obtained 5 drugs, including CP-466722, crizotinib, MS-275, KIN001-135, and CP-466722. The prognosis of patients with ESCA can be correctly predicted by the 6 CRLs chosen from this investigation. It lays the groundwork for more investigation into the ESCA mechanism and the identification of novel therapeutic targets.
10.3389/fgene.2023.1120827
Based on cuproptosis-related lncRNAs, a novel prognostic signature for colon adenocarcinoma prognosis, immunotherapy, and chemotherapy response.
Frontiers in pharmacology
Colon adenocarcinoma (COAD) is a special pathological subtype of colorectal cancer (CRC) with highly heterogeneous solid tumors with poor prognosis, and novel biomarkers are urgently required to guide its prognosis. RNA-Seq data of COAD were downloaded through The Cancer Genome Atlas (TCGA) database to determine cuproptosis-related lncRNAs (CRLs) using weighted gene co-expression network analysis (WGCNA). The scores of the pathways were calculated by single-sample gene set enrichment analysis (ssGSEA). CRLs that affected prognoses were determined via the univariate COX regression analysis to develop a prognostic model using multivariate COX regression analysis and LASSO regression analysis. The model was assessed by applying Kaplan-Meier (K-M) survival analysis and receiver operating characteristic curves and validated in GSE39582 and GSE17538. The tumor microenvironment (TME), single nucleotide variants (SNV), and immunotherapy response/chemotherapy sensitivity were assessed in high- and low-score subgroups. Finally, the construction of a nomogram was adopted to predict survival rates of COAD patients during years 1, 3, and 5. We found that a high cuproptosis score reduced the survival rates of COAD significantly. A total of five CRLs affecting prognosis were identified, containing AC008494.3, EIF3J-DT, AC016027.1, AL731533.2, and ZEB1-AS1. The ROC curve showed that RiskScore could perform well in predicting the prognosis of COAD. Meanwhile, we found that RiskScore showed good ability in assessing immunotherapy and chemotherapy sensitivity. Finally, the nomogram and decision curves showed that RiskScore would be a powerful predictor for COAD. A novel prognostic model was constructed using CRLs in COAD, and the CRLs in the model were probably a potential therapeutic target. Based on this study, RiskScore was an independent predictor factor, immunotherapy response, and chemotherapy sensitivity for COAD, providing a new scientific basis for COAD prognosis management.
10.3389/fphar.2023.1200054
Arecoline Is Associated With Inhibition of Cuproptosis and Proliferation of Cancer-Associated Fibroblasts in Oral Squamous Cell Carcinoma: A Potential Mechanism for Tumor Metastasis.
Frontiers in oncology
Background:Metastatic disease remains the primary cause of death in patients with oral squamous cell carcinoma (OSCC), especially those who use betel nut. The different steps of the metastatic cascade rely on reciprocal interactions between cancer cells and the tumor microenvironment (TME). Cancer-associated fibroblasts (CAFs) are regarded as a significant component in the TME of OSCC. However, the precise mechanisms regulating CAFs in OSCC are poorly understood. Methods:Thirteen genes related to the arecoline were analyzed to explore the significant ones involved in arecoline-related OSCC metastasis. The GSE139869 (n = 10) and The Cancer Genome Atlas (TCGA)-OSCC data (n = 361) were mined for the identification of the differentially expressed genes. The least absolute shrinkage and selection operator (LASSO) regression was performed to identify the independent prognostic signatures. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted to explore the functional enrichment of selected genes, and gene set enrichment analysis of cuproptosis-related genes was completed. Spearman's analysis and Tumor Immune Estimation Resource (TIMER) were used to visualize the correlation between the infiltration of CAFs and the gene expression. The correlation analysis of the cells and different genes, including CAF infiltration and transcripts per million expression, was assessed. The relationship between arecoline and CAFs was confirmed by cell counting kit-8 assay (CCK-8). CancerSEA was searched to identify the single-cell phenotype. Result:Arecoline-associated fibrosis-related OSCC differentially expressed genes (AFOC-DEGs), namely, PLAU, IL1A, SPP1, CCL11, TERT, and COL1A2, were screened out and selected from the Gene Expression Omnibus (GEO) database and TCGA database. AFOC-DEGs were highly expressed in OSCC, which led to poor survival of patients. Functional enrichment analysis, protein-protein interaction network construction, and Spearman's correlation analysis all suggested that AFOC-DEGs were closely associated with cuproptosis. Cellular experiments demonstrated that arecoline stimulation could significantly increase the cell viability of CAFs. Single-sample Gene Set Enrichment Analysis (ssGSEA) results showed that GLS and MTF1 were highly expressed when fibroblasts proliferated at high enrichment levels. In addition, analysis of single-cell sequencing results suggested that OSCC cells with high expression of AFOC-DEGs were associated with OSCC metastasis. Conclusion:We found a close association between arecoline, cuproptosis, and CAFs, which might play an important role in the metastasis of OSCC.
10.3389/fonc.2022.925743
A novel prognostic signature based on cuproptosis-related lncRNA mining in colorectal cancer.
Frontiers in genetics
Colorectal cancer (CRC) is a common malignant tumor that affects the large bowel or the rectum. Cuproptosis, recently discovered programmed cell death process, may play an important role in CRC tumorigenesis. Long non-coding RNAs (lncRNAs) can alter the proliferation of colorectal cancer cells through the control and activation of gene expression. To date, cuproptosis-related lncRNAs, have not been investigated as potential predictive biomarkers in colorectal cancer. The mRNA and lncRNA expression data of colorectal cancer were gathered from The Tumor Genome Atlas (TCGA) database, and Pearson correlation analysis and univariate Cox regression analysis were used to identify the lncRNAs with differential prognosis. Colorectal cancer was classified using consistent clustering, and the clinical significance of different types, tumor heterogeneity, and immune microenvironment differences was investigated. The differential lncRNAs were further screened using LASSO regression to develop a risk scoring model, which was then paired with clinicopathological variables to create a nomogram. Finally, the copy number changes in the high-risk and low-risk groups were compared. Two clusters were formed based on the 28 prognostic cuproptosis-related lncRNAs, and the prognosis of cluster 2 was found to be significantly lower than that of cluster 1. Cluster 1 showed increased immune cell infiltration and immunological score, as well as strong enrichment of immune checkpoint genes. Next, LASSO regression was used to select 11 distinctive lncRNAs, and a risk score model was constructed using the training set to distinguish between high and low-risk groups. Patients in the high-risk group had a lower survival rate than those in the low-risk group, and both the test set and the total set produced consistent results. The AUC value of the ROC curve revealed the scoring model's efficacy in predicting long-term OS in patients. Moreover, the model could be used as an independent predictor when combined with a multivariate analysis of clinicopathological features, and our nomogram could be used intuitively to predict prognosis. Collectively, we developed a risk model using 11 differential lncRNAs and demonstrated that the model has predictive value as well as clinical and therapeutic implications for predicting prognosis in CRC patients.
10.3389/fgene.2022.969845
Cuproptosis regulatory genes greatly contribute to clinical assessments of hepatocellular carcinoma.
BMC cancer
BACKGROUND:Hepatocellular carcinoma (HCC) is a common abdominal cancer with dissatisfactory therapeutic effects. The discovery of cuproptosis lights on new approach for cancer treatment and assessment. So far, there is extremely limited research investigating the roles of cuproptosis-related (CR) genes in cancers. METHODS:A novel CR risk signature was constructed using the Lasso regression analysis. Its prognostic value was assessed via a series of survival analyses and validated in three GEO cohorts. The effects of CR risk signature on tumor immune microenvironment (TIM) were explored through CIBERSORT, ESTIMATE, and ssGSEA algorithms. Using GESA, we investigated its impacts on various metabolism process. The somatic mutation features of CR signature genes were also explored via cBioPortal database. Using tumor mutation burden, expressions of immune checkpoints, TIDE score, IMvigor 210 cohort, and GSE109211 dataset, we explored the potential associations of CR risk score with the efficacy of immune checkpoint inhibitors (ICIs) and sorafenib. Finally, the biofunctions of DLAT in HCC cells were ascertained through qPCR, immunohistochemistry, colony formation, and Transwell assays. RESULTS:FDX1, DLAT, CDKN2A and GLS constituted the CR risk signature. CR risk signature possessed high prognostic value and was also applicable to three validation cohorts. Meanwhile, it could improve the accuracy and clinical making-decision benefit of traditional prognostic model. Moreover, high CR risk was indicative of unfavorable anti-tumor immune response and active metabolisms of glycolysis and nucleotide. As for therapeutic correlation, CR risk score was a potential biomarker for predicting the efficacy of ICIs and sorafenib. Through qPCR and immunohistochemistry detection in clinical samples, we reconfirmed DLAT was significantly upregulated in HCC samples. Overexpression of DLAT could promote the proliferation, migration, and invasion of HepG2 and HuH-7 cells. CONCLUSIONS:The novel CR risk signature greatly contributed to the clinical assessment of HCC. Cuproptosis regulatory gene DLAT possessed cancer-promoting capacities and was expected to be a promising therapeutic target for HCC.
10.1186/s12885-022-10461-2
Comprehensive analysis of cuproptosis-related genes in immune infiltration and prognosis in lung adenocarcinoma.
Computers in biology and medicine
Copper-dependent cell death, called cuproptosis, is connected to tumor development, prognosis, and the immune response. Nevertheless, the function of cuproptosis-related genes (CRGs) in the tumor microenvironment (TME) of lung adenocarcinoma (LUAD) remains unknown. This work used R software packages to classify the raw data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases of LUAD patients. Afterward, the connections of the various subgroups, clinical pathological traits, and immune infiltration (IMIF) features with the TME mutation status were explored. Ultimately, a nomogram and calibration curve were developed, aiming at enhancing the clinical application of CRG scores and estimating the survival probability of patients. Moreover, the relationships between cuproptosis and the molecular traits, immune cell infiltration of tumor tissue, prognosis, and clinical treatment of patients were investigated in this work. Subsequently, the CRG score was established to predict overall survival (OS), and its credible predictive ability in LUAD patients was identified. Afterward, a highly credible nomogram was created to contribute to the clinical viability of the CRG score. Furthermore, as demonstrated, gene signatures could be applied in assessing tumor immune cell infiltration, clinical traits, and prognosis. In addition, high tumor mutation burden, immunological activity, and significant survival probability were characterized by low CRG scores, and high CRG scores were related to immunosuppression and stromal pathway activation. The current work also discovered a predictive CRG-related signature for LUAD patients, probably contributing to TME trait clarification and more potent immunotherapy strategy exploration.
10.1016/j.compbiomed.2023.106831
CDKN2A was a cuproptosis-related gene in regulating chemotherapy resistance by the MAGE-A family in breast cancer: based on artificial intelligence (AI)-constructed pan-cancer risk model.
Aging
BACKGROUND:Before the discovery of cuproptosis, copper-loaded nanoparticle is a wildly applied strategy for enhancing the tumor-cell-killing effect of chemotherapy. Although copper(ii)-related researches are wide, details of cuproptosis-related bioprocess in pan-cancer are not clear yet now, especially for prognosis and drug sensitivity prediction yet now. METHODS:In this study, VOSviewer is used for the literature review, and R4.2.0 is used for data analysis. Public data are collected from TCGA and GEO, local breast cancer cohort is collected to verify the expression level of CDKN2A. RESULTS:7036 published articles exhibited a time-dependent linear relationship (R=0.9781, p<0.0001), and breast cancer (33.4%) is the most researched topic. Cuproptosis-related-genes (CRGs)-based unsupervised clustering divides pan-cancer subgroups into four groups (CRG subgroup) with differences in prognosis and tumor immunity. 44 tumor-driver-genes (TDGs)-based prediction model of drug sensitivity and prognosis is constructed by artificial intelligence (AI). Based on TDGs and clinical features, a nomogram is (C- index: 0.7, p= 6.958e- 12) constructed to predict the prognosis of breast cancer. Importance analysis identifies CDKN2A has a pivotal role in AI modeling, whose higher expression indicates worse prognosis in breast cancer. Furthermore, inhibition of CDKN2A down-regulates decreases Snail1, Twist1, Zeb1, vimentin and MMP9, while E-cadherin is increased. Besides, inhibition of CDKN2A also decreases the expression of MEGEA4, phosphorylated STAT3, PD-L1, and caspase3, while cleaved-caspase3 is increased. Finally, we find down-regulation of CDKN2A or MAGEA inhibits cell migration and wound healing, respectively. CONCLUSIONS:AI identified CRG subgroups in pan-cancer based on CRGs-related TDGs, and 44-gene-based AI modeling is a novel tool to identify chemotherapy sensitivity in breast cancer, in which CDKN2A/MAGEA4 pathway played the most important role.
10.18632/aging.205125
A Noval Established Cuproptosis-Associated LncRNA Signature for Prognosis Prediction in Primary Hepatic Carcinoma.
Evidence-based complementary and alternative medicine : eCAM
The copper ion content in the body maintains homeostasis, and when dysregulated, it can produce cytotoxicity and induce cell death through a variety of pathways. Cuproptosis refers to copper ions combining directly with acylated molecules, leading to the accumulation of oligomerization of lipoylated protein and subsequent downregulation of iron-sulfur cluster proteins; this induces proteotoxic stress and cell death. This study on the relationship between cuproptosis-related lncRNAs (CRLns) and the prognosis of primary hepatic carcinoma (PHC) has important clinical guiding significance for the diagnosis and treatment of PHC. Prognosis-related CRLRs were identified via rank-sum tests, correlational analyses, and univariate Cox regression, and a CRLR risk-scoring model (CRLRSM) was constructed using LASSO Cox regression. Patients were divided into high-risk and low-risk groups based on the median CRLRSM scores. Variance analysis for cuproptosis-related genes, gene set enrichment analysis, and correlational analysis for risk and immunity were performed using boxplots. Quantitative polymerase chain reactions were used to verify the CRLR levels in PHC cell lines. The study results showed that patients in the CRLRSM high-risk group had worse survival rates than those in the low-risk group. The PHC stage and risk score were independent prognostic factors for hepatocellular carcinoma. There were 7 CRLRs (MIR210HG, AC099850.3, AL031985.3, AC012073.1, MKLN1-AS, KDM4A-AS1, and PLBD1-AS1) associated with PHC prognosis, primarily through cellular metabolism, growth, proliferation, apoptosis, and immunity. In conclusion, the overexpression of 7 CRLRs in patients with PHC indicates a poor prognosis.
10.1155/2022/2075638
Identification and immunological characterization of cuproptosis-related molecular clusters in ischemic stroke.
Neuroreport
The present study elucidated cuproptosis-related molecular clusters involved in ischemic stroke and developed predictive models. Transcriptomic and immunological profiles of ischemic stroke-related datasets were extracted from the Gene Expression Omnibus database. Next, we conducted weighted gene co-expression network analysis to determine cluster-specific differentially expressed genes (DEGs). Models such as random forest and eXtreme gradient boosting (XGB) were evaluated to select the best prediction performance model. Subsequently, we validated the model's predictive efficiency by using nomograms, decision curve analysis, calibration curves, and receiver operating characteristic curve analysis with an external dataset. We identified two cuproptosis-related clusters involved in ischemic stroke. The DEGs in Cluster 2 were closely associated with amino acid metabolism, various immune responses, and cell proliferation pathways. The XGB model showed lower residuals, a smaller root mean square error, and a greater area under the curve value (AUC = 0.923), thus exhibiting the best discriminative performance. The AUC value for the external validation dataset was 0.921, thus confirming the high performance of the model. NFE2L2, NLRP3, GLS, LIPT1, and MTF1 were identified as potential cuproptosis predictors, thus shedding new light on ischemic stroke pathogenesis and heterogeneity.
10.1097/WNR.0000000000001972
Cuproptosis Regulates Microenvironment and Affects Prognosis in Prostate Cancer.
Biological trace element research
Current immunotherapy for prostate cancer is still in the stage of clinical trials. This delay is thought to be caused by an unclear regulatory mechanism of the immune microenvironment, which makes it impossible to distinguish patients suitable for immunotherapy. Cuprotosis may be related to the heterogeneity of immune microenvironment, which was regarded as a new copper-dependent cell death mode, was proposed, and gain attention. We explored for the first time the relationship between cuprotosis and the immune microenvironment of prostate cancer and constructed cuprotosis score. RNA sequencing data sets for prostate cancer were downloaded from public databases. Consensus clustering was applied to distinguish cuprotosis phenotype based on the expression of cuproptosis-related genes (CRGs) identified as prognostic factors. Genomic phenotypes of CRG clusters were depicted via consensus clustering. Cuprotosis score was established on the basis of differentially expressed genes (DEGs) identified as prognostic factors via principal component analysis. Cuprotosis score = the first principal component of prognostic factors + the second principal component of prognostic factors. The value of cuproptosis score in predicting prognosis and immunotherapy response was evaluated. PDHA1 (HR = 3.86, P < 0.001) and GLS (HR = 1.75, P = 0.018) were risk factors for prognosis of prostate cancer patients, while DBT (HR = 0.66, P = 0.048) was a favorable factor for prognosis of prostate cancer patients. CRG clusters had different prognosis and immune cell infiltration. So as gene clusters. Prostate cancer patients with low cuprotosis score showed better prognosis for biochemical relapse-free survival. Cuprotosis score is accompanied with high immune score and Gleason score. As cuprotosis genes, PDHA1, GLS, and DBT were identified as independent prognostic factors of prostate cancer. Cuprotosis score was established via principal component analysis of PDHA1, GLS, and DBT, which can be used as a predictor of prognosis and immunotherapy response of prostate cancer patients, and can characterize immune cells infiltration in tumors. Cuproptosis was involved in the regulation of immune microenvironment, which may depend on the effect of tricarboxylic acid cycle. Our study provided clues to reveal the relationship between copper death and immune microenvironment, highlighted the clinical significance of cuproptosis, and provided a reference for the development of personalized immunotherapy.
10.1007/s12011-023-03668-2
Identification of a cuproptosis-related lncRNA signature to predict the prognosis and immune landscape of head and neck squamous cell carcinoma.
Frontiers in oncology
Background:Cuproptosis is considered a novel copper-induced cell death model regulated by targeting lipoylated TCA cycle proteins. In this study, we established a novel signature based on cuproptosis-related lncRNAs (crlncRNAs) to predict the prognosis and immune landscape of head and neck squamous cell carcinoma. Methods:RNA-seq matrix, somatic mutation files, and clinical data were obtained from The Cancer Genome Atlas database. After dividing patients into two sets, a crlncRNA signature was established based on survival related crlncRNAs, which were selected by the univariate Cox analysis and least absolute shrinkage and selection operator Cox regression. To evaluate the model, Kaplan-Meier survival analysis and time-dependent receiver operating characteristic (ROC) were utilized, and a nomogram was established for survival prediction. Immune landscape analysis, drug sensitivity, cluster analysis, tumor mutation burden (TMB) and ceRNA network analysis were conducted subsequently. Results:A crlncRNA related prognosis signature was finally constructed with 12 crlncRNAs. The areas under the ROC curves (AUCs) were 0.719, 0.705 and 0.693 respectively for 1, 3, and 5-year's overall survival (OS). Patients in the low-risk group behaved a better prognosis, lower TMB, higher immune function activity and scores. In addition, patients from cluster 2 were more sensitive to chemotherapy and immunotherapy. Conclusion:In this study, we constructed a novel crlncRNA risk model to predict the survival of HNSCC patients. This reliable and acceptable prognostic signature may guide and promote the progress of novel treatment strategies for HNSCC patients.
10.3389/fonc.2022.983956
Copper Induces Cognitive Impairment in Mice via Modulation of Cuproptosis and CREB Signaling.
Nutrients
It has been reported that disordered Cu metabolism is associated with several neurodegenerative diseases, including Alzheimer's disease (AD) and Parkinson's disease (PD). However, the underlying mechanism is still unclear. In this study, 4-week-old male mice were exposed to Cu by free-drinking water for three months. Then, the effects of Cu on cognitive functions in mice were tested by Morris water maze tests, and the potential mechanisms were investigated by the ELISA, immunochemistry, TUNEL, and Western blot tests. It was found that Cu exacerbates learning and memory impairment, and leads to Cu-overload in the brain and urine of mice. The results showed that Cu induces neuronal degeneration and oxidative damage, promotes the expression of apoptosis-related protein Bax, cuproptosis-related proteins FDX1 and DLAT and the proteotoxic stress marker HSP70, and decreases Fe-S cluster proteins. In addition, Cu affects the pre-synaptic and post-synaptic regulatory mechanisms through inhibiting the expression of PSD-95 and SYP. Cu also suppresses phosphorylation levels in CREB and decreases the expression of BDNF and TrkB in the mouse hippocampus. In conclusion, Cu might mediate cuproptosis, damage synaptic plasticity and inhibit the CREB/BDNF pathway to cause cognitive dysfunction in mice.
10.3390/nu15040972
The pathogenesis of DLD-mediated cuproptosis induced spinal cord injury and its regulation on immune microenvironment.
Frontiers in cellular neuroscience
Introduction:Spinal cord injury (SCI) is a severe central nervous system injury that leads to significant sensory and motor impairment. Copper, an essential trace element in the human body, plays a vital role in various biological functions and is strictly regulated by copper chaperones and transporters. Cuproptosis, a novel type of metal ion-induced cell death, is distinct from iron deprivation. Copper deprivation is closely associated with mitochondrial metabolism and mediated by protein fatty acid acylation. Methods:In this study, we investigated the effects of cuproptosis-related genes (CRGs) on disease progression and the immune microenvironment in acute spinal cord injury (ASCI) patients. We obtained the gene expression profiles of peripheral blood leukocytes from ASCI patients using the Gene Expression Omnibus (GEO) database. We performed differential gene analysis, constructed protein-protein interaction networks, conducted weighted gene co-expression network analysis (WGCNA), and built a risk model. Results:Our analysis revealed that dihydrolipoamide dehydrogenase (DLD), a regulator of copper toxicity, was significantly associated with ASCI, and DLD expression was significantly upregulated after ASCI. Furthermore, gene ontology (GO) enrichment analysis and gene set variation analysis (GSVA) showed abnormal activation of metabolism-related processes. Immune infiltration analysis indicated a significant decrease in T cell numbers in ASCI patients, while M2 macrophage numbers were significantly increased and positively correlated with DLD expression. Discussion:In summary, our study demonstrated that DLD affects the ASCI immune microenvironment by promoting copper toxicity, leading to increased peripheral M2 macrophage polarization and systemic immunosuppression. Thus, DLD has potential as a promising biomarker for ASCI, providing a foundation for future clinical interventions.
10.3389/fncel.2023.1132015
Identification of a novel cuproptosis-related gene signature for rheumatoid arthritis-A prospective study.
The journal of gene medicine
BACKGROUND:Rheumatoid arthritis (RA) is a multifactorial systemic autoimmune disease characterized by ongoing synovial inflammation, leading to the degradation of cartilage. Cuproptosis, as a newly characterized form of cell death, may influence RA progression by regulating immune cells and chondrocytes. This study sets out to identify the hub cuproptosis-related gene (CRG) associated with the pathogenesis of RA. METHODS:A series of bioinformatic analyses were performed to evaluate the expression score of CRGs and the immune infiltration landscape between RA and normal samples. The hub gene was screened through the correlation analysis of CRGs, and the interaction network between the hub gene and transcription factors (TFs) was constructed. Finally, the hub gene was validated through quantitative real-time polymerase chain reaction (qRT-PCR) of patient samples and cell experiments. RESULTS:Drolipoamide S-acetyltransferase (DLAT) was screened as the hub gene. Correlation analysis between the hub gene and immune microenvironment demonstrated that DLAT had the highest correlation with T follicular helper cells. Eight pairs of DLAT-TF interaction networks were constructed. Single-cell sequencing showed that CRGs were highly expressed in RA chondrocytes, and chondrocytes could be classified into three different subsets. qRT-PCR was used to validate the above results. Dlat knockdown in immortalized human chondrocytes led to significantly improved mitochondrial membrane potentials and reduced levels of intracellular reactive oxygen species (ROS), mitochondrial ROS and apoptosis. CONCLUSIONS:This study rudimentarily demonstrates the correlation between CRGs and immune cell infiltration in RA. The biomarker DLAT may provide comprehensive insights into the pathogenesis and drug targets of RA.
10.1002/jgm.3535
Bioinformatics prediction and experimental verification identify cuproptosis-related lncRNA as prognosis biomarkers of hepatocellular carcinoma.
Biochemistry and biophysics reports
Cuproptosis is a form of cell death caused by intracellular copper excess, which plays an important regulatory role in the development and progression of cancers, including hepatocellular carcinoma (HCC), a prevalent malignancy with high morbidity and mortality. This study aimed to create a cuproptosis associated long non-coding RNAs (CAlncRNAs)signature to predict HCC patient survival and immunotherapy response. Firstly, we identified 509 CAlncRNAs using Pearson correlation analysis in The Cancer Genome Atlas (TCGA) datasets, before the three CAlncRNAs (MKLN1-AS, FOXD2-AS1, LINC02870) with the most prognostic value were further screened. Then, we constructed a prognostic risk model for HCCwas using univariate and LASSO Cox regression analyses. Multivariate Cox regression analyses illustrated that this model was an independent prognostic factor for overall survival (OS) prediction, outperforming traditional clinicopathological factors. And the risk score not only could be prognostic factors independent of other factors but also suited for patients with diverse ages, stages, and grades. The 1-, 3-, and 5- years areas under the curves (AUC) values of the model were 0.759, 0.668 and 0.674 respectively. Pathway analyses showed that the high-risk groupenriched in immune-related pathways. Importantly, patients with higher risk scores exhibited higher mutation frequency, higher TMB scores, and lower TIDE scores. Besides, we screened for two chemical drugs (A-443654 and Pyrimethamine) with the greatest value for high-risk HCC patients. Finally, the abnormal high expression of the three CAlncRNAs were confirmed in HCC tissues and cells by Real Time Quantitative PCR (RT-qPCR). And proliferative, migratory and invasion abilities of HCC cell were restrained via silencing CAlncRNAs expression In summary, we built a CAlncRNAs-based risk score model, which can be a candidate for HCC patients prognostic prediction and offer some useful information for immunotherapies.
10.1016/j.bbrep.2023.101502
Verification of cuproptosis-related diagnostic model associated with immune infiltration in rheumatoid arthritis.
Frontiers in endocrinology
Background:Rheumatoid arthritis (RA) is a chronic autoimmune disease closely related to inflammation. Cuproptosis is a newly discovered unique type of cell death, and it has been found that it may play an essential role in the occurrence and development of RA. Therefore, we intend to explore the potential association between cuproptosis-related genes (CRGs) and RA to provide a new biomarker for the treatment and prognosis of RA. Methods:Download GSE93777 datasets from the GEO database. Variance analysis was performed on the CRGs that had been reported. Then, the random forest (RF) model and nomogram of differentially expressed CRGs were constructed, and the ROC curve was used to evaluate the accuracy of the diagnostic model. Next, RA patients were subtyped by consensus clustering, and immune infiltration was analyzed in each subgroup to confirm the correlation between CRGs and abundance of immune cells. The expression levels of CRGs were verified by qRT-PCR. Results:Eight differentially expressed CRGs (DLST, DLD, PDHB, PDHA1, ATP7A, CDKN2A, LIAS, DLAT) were screened out by differential analysis to construct an RF model. The ROC curve proved that this model had good diagnostic accuracy. Based on the above eight significant CRGs, a nomogram was built to predict effective and high-precision results. The consensus clustering method identified two CRG patterns. Most of the immune cells were enriched in cluster A, indicating that cluster A may be related to the development of RA. Finally, qRT-PCR verified the expression of eight key genes, further confirming our findings. Conclusion:The diagnosis model of RA based on the above eight CRGs has excellent diagnostic potential. Based on these, patients can be divided into two different molecular subtypes; it is expected to develop a new treatment strategy for RA.
10.3389/fendo.2023.1204926
Prognostic value and immune landscapes of cuproptosis-related lncRNAs in esophageal squamous cell carcinoma.
Aging
BACKGROUND:Precisely forecasting the prognosis of esophageal squamous cell carcinoma (ESCC) patients is a formidable challenge. Cuproptosis has been implicated in ESCC pathogenesis; however, the prognostic value of cuproptosis-associated long noncoding RNAs (CuRLs) in ESCC is unclear. METHODS:Transcriptomic and clinical data related to ESCC were sourced from The Cancer Genome Atlas (TCGA). Using coexpression and Cox regression analysis to identify prognostically significant CuRLs, a prognostic signature was created. Nomogram models were established by incorporating the risk score and clinical characteristics. Tumor Immune Dysfunction and Rejection (TIDE) scores were derived by conducting an immune landscape analysis and evaluating the tumor mutational burden (TMB). Drug sensitivity analysis was performed to explore the underlying molecular mechanisms and guide clinical dosing. RESULTS:Our risk score based on 5 CuRLs accurately predicted poorer prognosis in high-risk ESCC patients across almost all subgroups. The nomogram that included the risk score provided more precise prognostic predictions. Immune pathways, such as the B-cell receptor signaling pathway, were enriched in the datasets from high-risk patients. High TMB in high-risk patients indicated a relatively poor prognosis. High-risk patients with lower TIDE scores were found to benefit more from immunotherapy. High-risk patients exhibited greater responsiveness to Nilotinib, BI-2536, P22077, Zoledronate, and Fulvestrant, as revealed by drug sensitivity analysis. Real-time PCR validation demonstrated significant differential expression of four CuRLs between ESCC and normal cell lines. CONCLUSIONS:The above risk score and nomogram can accurately predict prognosis in ESCC patients and provide guidance for chemotherapy and immunotherapy.
10.18632/aging.205089
Significance of Cuproptosis-related genes in immunological characterization, diagnosis and clusters classification in Parkinson's disease.
Cellular and molecular biology (Noisy-le-Grand, France)
Parkinson's disease (PD) is a progressive neurological disorder that affects millions of people throughout the world. Cuproptosis is a newly discovered form of programmed cell death linked to several neurological disorders. Nevertheless, the precise mechanisms of Cuproptosis-related genes (CRGs) in PD remain unknown. This study investigated immune infiltration and CRG expression profiling in patients with Parkinson's disease and healthy controls. Subsequently, we construct a predictive model based on 5 significant CRGs. The performance of the predictive model was validated by nomograms and external datasets. Additionally, we classified PD patients into two clusters based on CRGs and three gene clusters based on differentially expressed genes (DEG) of CRGs clusters. We further evaluated immunological characterization between the different clusters and created the CRGs scores to quantify CRGs patterns. Finally, we investigate the prediction of CRGs drugs and the ceRNA network, providing new insights into the pathogenesis and management of PD.
10.14715/cmb/2023.69.12.20
The FDX1 methylation regulatory mechanism in the malignant phenotype of glioma.
Genomics
To explore FDX1 methylation as a regulatory mechanism in the malignant phenotype of glioma, we screened for pathways involved through bioinformatic analysis, then proceeded with RIP and cell models to verify the regulation of RNAs and mitophagy. We chose Clone and Transwell assays to evaluate the malignant phenotype of glioma cells. MMP was detected by flow cytometry and mitochondrial morphology was observed by TEM. We also constructed animal models to study the sensitivity of glioma cells to cuproptosis. We successfully identified the signalling pathway: our cell model showed that C-MYC could upregulate FDX1 through YTHDF1 and inhibit mitophagy in glioma cells. Functional experiments revealed C-MYC could also enhance glioma cell proliferation and invasion via YTHDF1 and FDX1. In vivo experiments showed glioma cells were highly sensitive to cuproptosis. We concluded that C-MYC could upregulate FDX1 by m6A methylation, thus promoting the malignant phenotype in glioma cells.
10.1016/j.ygeno.2023.110601
Identification of cuproptosis-related long noncoding RNA signature for predicting prognosis and immunotherapy response in bladder cancer.
Scientific reports
Bladder cancer (BC) is the most common malignant tumour of the urinary system and one of the leading causes of cancer-related death. Cuproptosis is a novel form of programmed cell death, and its mechanism in tumours remains unclear. This study aimed to establish the prognostic signatures of cuproptosis-related lncRNAs and determine their clinical prognostic value. RNA sequencing data from The Cancer Genome Atlas were used to detect the expression levels of cuproptosis-related genes in BC. Cuproptosis-related lncRNAs linked to survival were identified using co-expression and univariate Cox regression. Furthermore, consensus cluster analysis divided the lncRNAs into two subtypes. Subsequently, we established a signature model consisting of seven cuproptosis-related lncRNAs (AC073534.2, AC021321.1, HYI-AS1, PPP1R26-AS1, AC010328.1, AC012568.1 and MIR4435-2Hg) using least absolute shrinkage and selection operator regression. Survival analysis based on risk score showed that the overall survival and progression-free survival of patients in the high-risk group were worse than those in the low-risk group. Multivariate Cox analysis demonstrated the independent prognostic potential of this signature model for patients with BC. Moreover, age and clinical stage were also significantly correlated with prognosis. The constructed nomogram plots revealed good predictive power for the prognosis of patients with BC and were validated using calibration plots. Additionally, enrichment analysis, Single sample gene set enrichment analysis and immune infiltration abundance analysis revealed significant differences in immune infiltration between the two risk groups, with high levels of immune cell subset infiltrations observed in the high-risk group accompanied by various immune pathway activation. Moreover, almost all the immune checkpoint genes showed high expression levels in the high-risk group. Moreover, TIDE analysis suggested that the high-risk group was more responsive to immunotherapy. Finally, eight drugs with low IC50 values were screened, which may prove to be beneficial for patients in the high-risk group.
10.1038/s41598-022-25998-2
The characterization of tumor microenvironment infiltration and the construction of predictive index based on cuproptosis-related gene in primary lung adenocarcinoma.
Frontiers in oncology
Objective:We aimed to use the cancer genome atlas and gene expression omnibus databases to explore the characterization of tumor microenvironment (TME) infiltration and construct a predictive index of prognosis and treatment effect based on cuproptosis-related genes (CRGs) in primary lung adenocarcinoma (LUAD). Methods:We described the alterations of CRGs in 954 LUAD samples from genetic and transcriptional fields and evaluated their expression patterns from three independent datasets. We identified two distinct molecular subtypes and found that multi-layer CRG alterations were correlated with patient clinicopathological features, prognosis, and TME cell infiltrating characteristics. Then, a cuproptosis scoring system (CSS) for predicting the prognosis was constructed, and its predictive capability in LUAD patients was validated. Results:Two molecular subtypes of cuproptosis (Copper Genes cluster A and cluster B) in LUAD were identified. Copper Genes cluster B had better survival than those with Copper Genes cluster A (0.01). Besides, we found that the infiltration of activated CD4 T cells, natural killer T cells, and neutrophils was stronger in cluster A than in cluster B. Then, we constructed a highly accurate CSS to predict the prognosis, targeted therapy effect, and immune response. Compared with the low-CSS subgroup, the mutations of the , , and genes were more common in the high-CSS subgroup, while the mutation of , , and genes were more common in the low-CSS subgroup than in high-CSS subgroup. The low-score CSS group had an inferior survival than high-score CSS group (0.01). In addition, CSS presented good ability to predict the immune response (area under curve [AUC], 0.726). Moreover, AZD5363 and AZD8186 were the inhibitors of and , respectively, and had lower IC50 and AUC in the low-score CSS group than it in the high-score CSS group. Conclusions:CRGs are associated with the development, TME, and prognosis of LUAD. Besides, a scoring system based on CRGs can predict the efficacy of targeted drugs and immune response. These findings may improve our understanding of CRGs in LUAD and pave a new path for the assessment of prognosis and the development of more effective targeted therapy and immunotherapy strategies.
10.3389/fonc.2022.1011568
Insights into prognosis and immune infiltration of cuproptosis-related genes in breast cancer.
Frontiers in immunology
Introduction:Breast cancer (BC) has been ranking first in incidence and the leading cause of death among female cancers worldwide based on the latest report. Regulated cell death (RCD) plays a significant role in tumor initiation and provides an important target of cancer treatment. Cuproptosis, a novel form of RCD, is ignited by mitochondrial stress, particularly the lipoylated mitochondrial enzymes aggregation. However, the role of cuproptosis-related genes (CRGs) in tumor generation and progression remains unclear. Methods:In this study, the mRNA expression data of CRGs in BC and normal breast tissue were extracted from TCGA database, and protein expression patterns of these CRGs were analyzed using UALCAN. The prognostic values of CRGs in BC were explored by using KaplanMeier plotter and Cox regression analysis. Genetic mutations profiles were evaluated using the cBioPortal database. Meanwhile, we utilized CIBERSORT and TIMER 2.0 database to perform the correlation analysis between CRGs and immune cell infiltration. Results:Our results indicated that CRGs expression is significantly different in BC and normal breast tissues. Then we found that upregulated PDHA1 expression was associated with worse endpoint of BC. Moreover, we also performed immune infiltration analysis of CRGs, and demonstrated that PDHA1 expression was closely related to the infiltration levels of CD4+ memory T cell, macrophage M0 and M1 cell and mast cell in BC. Conclusions:Our results demonstrated the prognostic and immunogenetic values of PDHA1 in BC. Therefore, PDHA1 can be an independent prognostic biomarker and potential target for immunotherapy of BC.
10.3389/fimmu.2022.1054305
Characterization of tumor microenvironment and sensitive chemotherapy drugs based on cuproptosis-related signatures in renal cell carcinoma.
Aging
Cuproptosis is a novel type of copper-induced cell death and is considered as a new therapeutic target for many cancers. Distant metastases occur in about 40% of patients with advanced renal cell carcinoma (RCC), with a poor 5-year prognosis of about 10%. Through a series of comprehensive analyses, four differentially expressed cuproptosis-related lncRNAs (DECRLs) were identified as candidate biomarkers for RCC. The risk model constructed by using these four DECRLs can better predict the prognosis of patients with RCC, which is determined by the receiver operating characteristic (Time dependent area under curve value at 1-year, 3-year, 5-year, and 10-year were 0.82, 0.80, 0.76, and 0.73 respectively). There were significant differences in immune status between high-risk and low-risk RCC patients. The differentially expressed gene enrichment terms between high- and low-risk patients was also dominated by immune-related terms. The risk score was also correlated with immunotherapy as measured by the tumor immune dysfunction and exclusion (TIDE) score. In addition, we also found that the sensitivity of many chemotherapy drugs varies widely between high- and low-risk patients. The sensitivity of the three chemotherapy drugs (AZD4547, Vincristine, and WEHI-539) varied among high- and low-risk patients, and was significantly negatively correlated with risk values, suggesting that they could be used as clinical treatment drugs for RCC. Our study not only obtained four potential biomarkers, but also provided guidance for immunotherapy and chemotherapy treatment of RCC, as well as new research strategies for the screening of other cancer biomarkers and sensitive drugs.
10.18632/aging.205043
Cuproptosis-related risk score based on machine learning algorithm predicts prognosis and characterizes tumor microenvironment in head and neck squamous carcinomas.
Scientific reports
Cuproptosis is a recently discovered type of programmed cell death that shows significant potential in the diagnosis and treatment of cancer. It has important significance in the prognosis of HSNC. This study aims to construct a cuproptosis-related prognostic model and risk score through new data analysis methods such as machine learning algorithms for the prognosis analysis of HSNC. Protein-protein interaction network and machine learning methods were employed to identify hub genes that were used to construct a TreeGradientBoosting model for predicting overall survival. The relationship between the risk scores obtained from the model and features such as tumor microenvironment (TME) and tumor immunity was explored. The C-indexes of the TreeGradientBoosting model in the training and validation cohorts were 0.776 and 0.848, respectively. The nomogram based on risk scores and clinical features showed good performance, and distinguished the TME and immunity between high-risk and low-risk groups. The cuproptosis-associated risk score can be used to predict prognoses, TME, and tumor immunity of HNSC patients.
10.1038/s41598-023-38060-6
Copper homeostasis and cuproptosis in atherosclerosis: metabolism, mechanisms and potential therapeutic strategies.
Cell death discovery
Copper is an essential micronutrient that plays a pivotal role in numerous physiological processes in virtually all cell types. Nevertheless, the dysregulation of copper homeostasis, whether towards excess or deficiency, can lead to pathological alterations, such as atherosclerosis. With the advent of the concept of copper-induced cell death, termed cuproptosis, researchers have increasingly focused on the potential role of copper dyshomeostasis in atherosclerosis. In this review, we provide a broad overview of cellular and systemic copper metabolism. We then summarize the evidence linking copper dyshomeostasis to atherosclerosis and elucidate the potential mechanisms underlying atherosclerosis development in terms of both copper excess and copper deficiency. Furthermore, we discuss the evidence for and mechanisms of cuproptosis, discuss its interactions with other modes of cell death, and highlight the role of cuproptosis-related mitochondrial dysfunction in atherosclerosis. Finally, we explore the therapeutic strategy of targeting this novel form of cell death, aiming to provide some insights for the management of atherosclerosis.
10.1038/s41420-023-01796-1
A mitochondria-targeted anticancer copper dithiocarbamate amplifies immunogenic cuproptosis and macrophage polarization.
Journal of materials chemistry. B
The way that cancer cells die inspires treatment regimens and cytolytic cuproptosis induced by copper complexes, like copper(II) bis(diethyldithiocarbamate) (CuET), has emerged as a novel therapeutic target. Herein, a triphenylphosphonium-modified CuET (TPP-CuET) is designed to target mitochondrial metabolism, triggering intense immunogenic cuproptosis in breast cancer cells and remodeling tumor-associated macrophages. TPP-CuET enables an enhanced mitochondrial copper accumulation in comparison to CuET (29.0% 19.4%), and severely disrupts the morphology and functions of mitochondria, encompassing the tricarboxylic acid cycle, ATP synthesis, and electron transfer chain. Importantly, it triggers amplified immunogenic death of cancer cells, and the released damage-associated molecular patterns effectively induce M1 polarization and migration of macrophages. Transcriptome analysis further reveals that TPP-CuET promotes antigen processing and presentation in cancer cells through the MHC I pathway, activating the immune response of CD8 T cells and natural killer cells. To the best of our knowledge, TPP-CuET is the first mitochondrial targeted immunogenic cuproptosis inducer and is expected to flourish in antitumor immunotherapy.
10.1039/d3tb02886k
Identification of Key Genes and Immunological Features Associated with Copper Metabolism in Parkinson's Disease by Bioinformatics Analysis.
Molecular neurobiology
To explore diagnostic genes associated with cuproptosis in Parkinson's disease (PD) and to characterize immune cell infiltration by comprehensive bioinformatics analysis, three PD datasets were downloaded from the GEO database, two of which were merged and preprocessed as the internal training set and the remaining one as the external validation set. Based on the internal training set, differential analysis was performed to obtain differentially expressed genes (DEGs), and weighted gene co-expression network analysis (WGCNA) was conducted to obtain significant module genes. The genes obtained here were intersected to form the intersecting genes. The intersecting genes obtained from DEGs and WGCNA were intersected with cuproptosis-related genes (CRGs) to generate cuproptosis-related disease signature genes, and functional enrichment analysis was performed on Disease Ontology (DO), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG). Subsequently, LASSO analysis of the cuproptosis-related disease signature genes was performed to identify key genes and construct a diagnostic and predictive model. Then, single sample gene set enrichment analysis (ssGSEA) was performed on the internal training set to further analyze the correlation between key genes and immune cells. Lastly, the results were validated using an external validation set. A total of 405 DEGs were obtained by differential analysis, and 6 gene modules were identified by WGCNA analysis. The genes in the most significant modules were intersected with the DEGs to obtain 21 intersecting genes. The functions of the intersecting genes were mainly enriched in neurotransmitter transport, GABA-ergic synapse, synaptic vesicle cycle, serotonergic synapse, phenylalanine metabolism, tyrosine metabolism, tryptophan metabolism, etc. Subsequently, the intersecting genes were intersected with CRGs, and LASSO regression analysis was performed to screen 3 key cuproptosis-related disease signature genes, namely, SLC18A2, SLC6A3, and SV2C. The calibration curve of the nomogram model constructed based on these 3 key genes to predict PD showed good agreement, with a C-index of 0.944 and an area under the ROC (AUC) of 0.944 (0.833-1.000). It was also validated by the external dataset that the model constructed with these 3 key genes had good diagnostic and predictive power for PD. The ssGSEA analysis revealed that neutrophils might be the potential core immune cells and that SLC18A2, SLC6A3, and SV2C were significantly negatively correlated with neutrophils, which was also verified in the validation set. PD diagnosis and prediction model based on CRGs (SLC18A2, SLC6A3, and SV2C) has good diagnostic and predictive performance and could be a useful tool in the diagnosis of PD.
10.1007/s12035-023-03565-8
Deep learning enables the discovery of a novel cuproptosis-inducing molecule for the inhibition of hepatocellular carcinoma.
Acta pharmacologica Sinica
Hepatocellular carcinoma (HCC) is one of the most common and deadly cancers in the world. The therapeutic outlook for HCC patients has significantly improved with the advent and development of systematic and targeted therapies such as sorafenib and lenvatinib; however, the rise of drug resistance and the high mortality rate necessitate the continuous discovery of effective targeting agents. To discover novel anti-HCC compounds, we first constructed a deep learning-based chemical representation model to screen more than 6 million compounds in the ZINC15 drug-like library. We successfully identified LGOd1 as a novel anticancer agent with a characteristic levoglucosenone (LGO) scaffold. The mechanistic studies revealed that LGOd1 treatment leads to HCC cell death by interfering with cellular copper homeostasis, which is similar to a recently reported copper-dependent cell death named cuproptosis. While the prototypical cuproptosis is brought on by copper ionophore-induced copper overload, mechanistic studies indicated that LGOd1 does not act as a copper ionophore, but most likely by interacting with the copper chaperone protein CCS, thus LGOd1 represents a potentially new class of compounds with unique cuproptosis-inducing property. In summary, our findings highlight the critical role of bioavailable copper in the regulation of cell death and represent a novel route of cuproptosis induction.
10.1038/s41401-023-01167-7
Identification of hub biomarkers and exploring the roles of immunity, M6A, ferroptosis, or cuproptosis in rats with diabetic erectile dysfunction.
Andrology
BACKGROUND:Currently, patients with diabetic erectile dysfunction (DMED) were not satisfied with the effects of first-line phosphodiesterase type 5 inhibitors (PDE5Is). Hence, this paper was designed to mine hub biomarkers in DMED and explore its potential mechanisms. METHODS:Gene expression matrix of DMED was downloaded from the gene expression omnibus (GEO; GSE2457) dataset. The top 20 genes were selected based on the connectivity degrees in protein-protein interaction (PPI) network. Functional enrichment analysis was utilized to reveal DMED-related signaling pathways. We also explored the roles of immunity, m6A, ferroptosis, or cuproptosis in DMED and constructed Sprague Dawley (SD) rats DMED model to verify gene expressions by quantitative real-time polymerase chain reaction (qRT-PCR). RESULTS:Based on the threshold, a total of 122 differently expressed genes (DEGs) were identified in DMED, including 39 up-regulated and 83 down-regulated genes. Functional enrichment analysis implied that these DEGs were significantly enriched in peroxisome proliferator-activated receptors, ferroptosis, hypoxia-inducible factor 1 signaling pathways, and so on. SD rats DMED model was also successfully established by us and validated by intracavernous pressure/mean arterial pressure, Masson's trichrome staining, and immunohistochemical analysis. We further verified the expression of these top 20 genes from the PPI network by qRT-PCR in the SD rats DMED model and finally identified Sparc, Lox, Srebf1, and Mmp3 as hub biomarkers (all p < 0.05). As for immunity and cuproptosis, our analysis indicated that DMED had nothing to do with them (all p > 0.05). Actually, DMED was markedly associated with m6A regulators and ferroptosis. CONCLUSIONS:We identified Sparc, Lox, Srebf1, and Mmp3 as potential hub biomarkers in the SD rats DMED model for future drug development and found its significant associations with m6A regulators and ferroptosis, but not with immunity or cuproptosis.
10.1111/andr.13265
Machine learning identification of cuproptosis and necroptosis-associated molecular subtypes to aid in prognosis assessment and immunotherapy response prediction in low-grade glioma.
Frontiers in genetics
Both cuproptosis and necroptosis are typical cell death processes that serve essential regulatory roles in the onset and progression of malignancies, including low-grade glioma (LGG). Nonetheless, there remains a paucity of research on cuproptosis and necroptosis-related gene (CNRG) prognostic signature in patients with LGG. We acquired patient data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) and captured CNRGs from the well-recognized literature. Firstly, we comprehensively summarized the pan-cancer landscape of CNRGs from the perspective of expression traits, prognostic values, mutation profiles, and pathway regulation. Then, we devised a technique for predicting the clinical efficacy of immunotherapy for LGG patients. Non-negative matrix factorization (NMF) defined by CNRGs with prognostic values was performed to generate molecular subtypes (i.e., C1 and C2). C1 subtype is characterized by poor prognosis in terms of disease-specific survival (DSS), progression-free survival (PFS), and overall survival (OS), more patients with G3 and tumour recurrence, high abundance of immunocyte infiltration, high expression of immune checkpoints, and poor response to immunotherapy. LASSO-SVM-random Forest analysis was performed to aid in developing a novel and robust CNRG-based prognostic signature. LGG patients in the TCGA and GEO databases were categorized into the training and test cohorts, respectively. A five-gene signature, including SQSTM1, ZBP1, PLK1, CFLAR, and FADD, for predicting OS of LGG patients was constructed and its predictive reliability was confirmed in both training and test cohorts. In both the training and the test datasets (cohorts), higher risk scores were linked to a lower OS rate. The time-dependent ROC curve proved that the risk score had outstanding prediction efficiency for LGG patients in the training and test cohorts. Univariate and multivariate Cox regression analyses showed the CNRG-based prognostic signature independently functioned as a risk factor for OS in LGG patients. Furthermore, we developed a highly reliable nomogram to facilitate the clinical practice of the CNRG-based prognostic signature (AUC > 0.9). Collectively, our results gave a promising understanding of cuproptosis and necroptosis in LGG, as well as a tailored prediction tool for prognosis and immunotherapeutic responses in patients.
10.3389/fgene.2022.951239
Comprehensive analysis of a novel cuproptosis-related lncRNA signature associated with prognosis and tumor matrix features to predict immunotherapy in soft tissue carcinoma.
Frontiers in genetics
A crucial part of the malignant processes of soft tissue sarcoma (STS) is played by cuproptosis and lncRNAs. However, the connection between cuproptosis-related lncRNAs (CRLs) and STS is nevertheless unclear. As a result, our objective was to look into the immunological activity, clinical significance, and predictive accuracy of CRLs in STS. The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases, respectively, provided information on the expression patterns of STS patients and the general population. Cuproptosis-related lncRNA signature (CRLncSig) construction involved the univariate, multivariate, and least absolute shrinkage and selection operator Cox regression analysis. The predictive performance of the CRLncSig was evaluated using a serial analysis. Further research was done on the connections between the CRLncSig and the tumor immune milieu, somatic mutation, immunotherapy response, and chemotherapeutic drug susceptibility. Notably, an investigation served to finally validate the expression of the hallmark CRLs. A novel efficient CRLncSig composed of seven CRLs was successfully constructed. Additionally, the low-CRLncSig group's prognosis was better than that of the high-CRLncSig group's based on the new CRLncSig. The innovative CRLncSig then demonstrated outstanding, consistent, and independent prognostic and predictive usefulness for patients with STS, according to the evaluation and validation data. The low-CRLncSig group's patients also displayed improved immunoreactivity phenotype, increased immune infiltration abundance and checkpoint expression, and superior immunotherapy response, whereas those in the high-CRLncSig group with worse immune status, increased tumor stemness, and higher collagen levels in the extracellular matrix. Additionally, there is a noticeable disparity in the sensitivity of widely used anti-cancer drugs amongst various populations. What's more, the nomogram constructed based on CRLncSig and clinical characteristics of patients also showed good predictive ability. Importantly, Real-Time Quantitative Polymerase Chain Reaction (RT-qPCR) demonstrated that the signature CRLs exhibited a significantly differential expression level in STS cell lines. In summary, this study revealed the novel CRLncSig could be used as a promising predictor for prognosis prediction, immune activity, tumor immune microenvironment, immune response, and chemotherapeutic drug susceptibility in patients with STS. This may provide an important direction for the clinical decision-making and personalized therapy of STS.
10.3389/fgene.2022.1063057
Consensus Clustering and Survival-Related Genes of Cuproptosis in Cutaneous Melanoma.
Mediators of inflammation
As a highly malignant tumor, the morbidity and mortality of cutaneous melanoma (CM) are increasing year by year. A novel type of cell death connected to mitochondrial metabolism is called cuproptosis. Cuproptosis regulates tumor biological behavior. Thus, genes controlling cuproptosis could be a promising candidate bioindicator for cancer therapy. Datasets of CM patients were obtained from the public database that includes clinical information and RNA-seq data. We divided CM patients into three different subgroups by unsupervised clustering method and explored the differences in functional pathways among the three subgroups by GSVA to prove the possible potential mechanism of copper death-related genes in the formation and development of CM. Secondly, we used differential analysis and Cox regression analysis to find the differential genes related to prognosis, constructed the CRG score, found the critical score for dividing high and low CRG score groups, and then analyzed the prognosis and immune infiltration of high and low CRG score groups. The results show a great correlation between OS and CRG scores. Compared with patients with high CRG scores, patients with low CRG scores have a significantly higher survival rate. In a word, copper sagging plays a certain role in the progress of CM.
10.1155/2023/3615688
A novel prognostic signature for lung adenocarcinoma based on cuproptosis-related lncRNAs: A Review.
Medicine
Lung adenocarcinoma (LUAD) is a highly heterogeneous disease with complex pathogenesis, high mortality, and poor prognosis. Cuproptosis is a new type of programmed cell death triggered by copper accumulation that may play an important role in cancer. LncRNAs are becoming valuable prognostic factors in cancer patients. The effect of cuproptosis-related lncRNAs (CRlncRNAs) on LUAD has not been clarified. Based on the Cancer Genome Atlas database, CRlncRNAs were screened by co-expression analysis of cuproptosis- related genes and lncRNAs. Using CRlncRNAs, Cox and LASSO regression analyses constructed a risk prognostic model. The predictive efficacy of the model was assessed and validated using survival analysis, receiver operating characteristic curve, univariate and multifactor Cox regression analysis, and principal component analysis. A nomogram was constructed and calibration curves were applied to enhance the predictive efficacy of the model. Tumor Mutational Burden analysis and chemotherapeutic drug sensitivity prediction were performed to assess the clinical feasibility of the risk model. The novel prognostic signature consisted of 5 potentially high-risk CRlncRNAs, MAP3K20-AS1, CRIM1-DT, AC006213.3, AC008035.1, and NR2F2-AS1, and 5 potentially protective CRlncRNAs, AC090948.1, AL356481.1, AC011477.2, AL031600.2, and AC026355.2, which had accurate and robust predictive power for LUAD patients. Collectively, the novel prognostic signature constructed based on CRlncRNAs can effectively assess and predict the prognosis of patients and provide a new perspective for the diagnosis and treatment of LUAD.
10.1097/MD.0000000000031924
DLAT is a promising prognostic marker and therapeutic target for hepatocellular carcinoma: a comprehensive study based on public databases.
Scientific reports
Cuproptosis is a new mechanism of cell death that differs from previously identified regulatory cell death mechanisms. Cuproptosis induction holds promise as a new tumour treatment. Therefore, we investigated the value of cuproptosis-related genes in the management of hepatocellular carcinoma (HCC). The cuproptosis-related gene Dihydrolipoamide S-Acetyltransferase (DLAT) were significantly upregulated in liver cancer tissues. High levels of DLAT were an independent prognostic factor for shorter overallsurvival (OS) time. DLAT and its related genes were mainly involved in cell metabolism, tumor progression and immune regulation. DLAT was significantly associated with the level of immune cell infiltration and immune checkpoints in HCC. HCC with high DLAT expression was predicted to be more sensitive to sorafenib treatment. The risk prognostic signature established based on DLAT and its related genes had a good prognostic value. The cuproptosis-related gene DLAT is a promising independent prognostic marker and therapeutic target in HCC. The new prognostic signature can effectively predict the prognosis of HCC patients.
10.1038/s41598-023-43835-y
Construction of cuproptosis-related lncRNAs/mRNAs model and prognostic prediction of hepatocellular carcinoma.
American journal of cancer research
Cuproptosis is a recently reported novel form of cell death, which is involved in the regulation of tumor progression. However, the specific role of cuproprosis in hepatocellular carcinoma (HCC) development remains unclear. In this study, we comprehensively analyzed the effect of cuproprosis-related lncRNAs/mRNAs on the prognosis of HCC patients based on the RNA-Seq transcriptome data and clinical data. We identified 6 cuproprosis-related signatures by Cox and Lasso regression analysis, including 3 mRNAs (FBXO30, RNF2, MPDZ) and 3 lncRNAs (PICSAR, LINC00426, AL590705.3). In addition, we constructed a prognostic prediction model for HCC. Risk analysis, RT-qPCR, and Kaplan-Meier analysis showed that the expression of FBXO30, RNF2, AL590705.3 and PICSAR was elevated in HCC, while the expression of MPDZ and LINC00426 was suppressed which was associated with better overall survival. Furthermore, immune response analysis suggested that HCC with high-risk score might respond favorably to immunotherapy. Moreover, the potential drugs that HCC might be sensitive to were screened by drug sensitivity profiling analysis. Taken together, our findings provided important information for the prediction of the prognosis of HCC patients and the development of personalized targeted therapy.
Molecular Characterization of Cuproptosis-related lncRNAs: Defining Molecular Subtypes and a Prognostic Signature of Ovarian Cancer.
Biological trace element research
Cuproptosis, a newly discovered form of programmed cell death, relies on mitochondrial respiration, the chain of which has been found to be altered in ovarian cancer (OC). The current work probed into the effects of Cuproptosis on the prognosis, immune microenvironment and therapeutic response of OC based on Cuproptosis-related lncRNAs. Data on OC gene expression and clinical characteristics were collected from TCGA, ICGC and GEO databases, and mRNA and lncRNA were distinguished. Cuproptosis-related lncRNAs were screened for consensus clustering analysis. Differentially expressed lncRNAs (DElncRNAs) were identified between clusters, and least absolute shrinkage and selection operator (LASSO) and Cox regression analysis were performed to establish a prognostic signature. Its potential value in OC was evaluated by Gene Set Enrichment Analysis (GSEA), tumor cell mutation and immune microenvironment analysis, and response to immunotherapy and antineoplastic drugs. According to the classification scheme of Cuproptosis-related lncRNAs, OC was divided into four molecular subtypes, which were different in survival time, immune characteristics and somatic mutation. The prognostic signature between subtypes included 10 lncRNAs, which were significantly correlated with the prognosis, immune microenvironment related indexes, the expression of immune checkpoint molecules and the sensitivity of antineoplastic drug Paclitaxel and Gefitinib of OC. We examined the expression of ten LncRNAs in OC cell lines and found that LINC00189, ZFHX4-AS1, RPS6KA2-IT1 and C9orf106 were expressed elevated in OC cell lines, and LINC00861, LINC00582, DEPDC1-AS1, LINC01556, LEMD1-AS1, TYMSOS expression was decreased in OC cell lines. The results of CCK8 showed that the cell viability of OC cells decreased after inhibition of C9orf106, whereas the cell viability of OC cells increased after inhibition of LEMD1-AS1. This work revealed new Cuproptosis-related lncRNA molecular subtypes exhibiting tumor microenvironment (TME) heterogeneity for OC and proposed a prognostic signature that may have benefits in understanding the prognosis, pathological features and immune microenvironment of OC patients.
10.1007/s12011-023-03780-3
Identification of GLS as a cuproptosis-related diagnosis gene in acute myocardial infarction.
Frontiers in cardiovascular medicine
Acute myocardial infarction (AMI) has the characteristics of sudden onset, rapid progression, poor prognosis, and so on. Therefore, it is urgent to identify diagnostic and prognostic biomarkers for it. Cuproptosis is a new form of mitochondrial respiratory-dependent cell death. However, studies are limited on the clinical significance of cuproptosis-related genes (CRGs) in AMI. In this study, we systematically assessed the genetic alterations of CRGs in AMI by bioinformatics approach. The results showed that six CRGs (LIAS, LIPT1, DLAT, PDHB, MTF1, and GLS) were markedly differentially expressed between stable coronary heart disease (stable_CAD) and AMI. Correlation analysis indicated that CRGs were closely correlated with N6-methyladenosine (m6A)-related genes through R language "corrplot" package, especially GLS was positively correlated with FMR1 and MTF1 was negatively correlated with HNRNPA2B1. Immune landscape analysis results revealed that CRGs were closely related to various immune cells, especially GLS was positively correlated with T cells CD4 memory resting and negatively correlated with monocytes. Kaplan-Meier analysis demonstrated that the group with high DLAT expression had a better prognosis. The area under curve (AUC) certified that GLS had good diagnostic value, in the training set (AUC = 0.87) and verification set (ACU = 0.99). Gene set enrichment analysis (GSEA) suggested that GLS was associated with immune- and hypoxia-related pathways. In addition, Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, competing endogenous RNA (ceRNA) analysis, transcription factor (TF), and compound prediction were performed to reveal the regulatory mechanism of CRGs in AMI. Overall, our study can provide additional information for understanding the role of CRGs in AMI, which may provide new insights into the identification of therapeutic targets for AMI.
10.3389/fcvm.2022.1016081
A novel cuproptosis-related lncRNA signature predicts prognosis and therapeutic response in bladder cancer.
Frontiers in genetics
Bladder cancer (BC) ranks the tenth in the incidence of global tumor epidemiology. LncRNAs and cuproptosis were discovered to regulate the cell death. Herein, we downloaded transcriptome profiling, mutational data, and clinical data on patients from The Cancer Genome Atlas (TCGA). High- and low-risk BC patients were categorized. Three CRLs (AL590428.1, AL138756.1 and GUSBP11) were taken into prognostic signature through least absolute shrinkage and selection operator (LASSO) Cox regression. Worse OS and PFS were shown in high-risk group ( < 0.05). ROC, independent prognostic analyses, nomogram and C-index were predicted CRLs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis indicated IncRNAs play a biological role in BC progression. Immune-related functions showed the high-risk group received more benefit from immunotherapy and had stronger immune responses, and the overall survival was better ( < 0.05). Finally, a more effective outcome ( < 0.05) was found from clinical immunotherapy the TIDE algorithm and many potential anti-tumor drugs were identified. In our study, the cuproptosis-related signature provided a novel tool to predict the prognosis in BC patients accurately and provided a novel strategy for clinical immunotherapy and clinical applications.
10.3389/fgene.2022.1082691
Drug repositioning of disulfiram induces endometrioid epithelial ovarian cancer cell death via the both apoptosis and cuproptosis pathways.
Oncology research
Various therapeutic strategies have been developed to overcome ovarian cancer. However, the prognoses resulting from these strategies are still unclear. In the present work, we screened 54 small molecule compounds approved by the FDA to identify novel agents that could inhibit the viability of human epithelial ovarian cancer cells. Among these, we identified disulfiram (DSF), an old alcohol-abuse drug, as a potential inducer of cell death in ovarian cancer. Mechanistically, DSF treatment significantly reduced the expression of the anti-apoptosis marker B-cell lymphoma/leukemia-2 (Bcl-2) and increase the expression of the apoptotic molecules Bcl2 associated X (Bax) and cleaved caspase-3 to promote human epithelial ovarian cancer cell apoptosis. Furthermore, DSF is a newly identified effective copper ionophore, thus the combination of DSF and copper was used to reduce ovarian cancer viability than DSF single treatment. Combination treatment with DSF and copper also led to the reduced expression of ferredoxin 1 and loss of Fe-S cluster proteins (biomarkers of cuproptosis). , DSF and copper gluconate significantly decreased the tumor volume and increased the survival rate in a murine ovarian cancer xenograft model. Thus, the role of DSF revealed its potential for used as a viable therapeutic agent for the ovarian cancer.
10.32604/or.2023.028694
Exploring the correlation of glycolysis-related chondroitin polymerizing factor () with clinical characteristics, immune infiltration, and cuproptosis in bladder cancer.
American journal of cancer research
Bladder cancer (BLCA) is a common malignant neoplasm of the urinary system. Glycolysis is an essential metabolic pathway regulated by various genes with implications for tumor progression and immune escape. Scoring the glycolysis for each sample in the TCGA-BLCA dataset was done using the ssGSEA algorithm for quantification. The results showed that the score in BLCA tissues was markedly greater than those in adjacent tissues. Additionally, the score was found to be correlated with metastasis and high pathological stage. Functional enrichment analyses of the glycolysis-related genes showed they were related to roles associated with tumor metastasis, glucose metabolism, cuproptosis, and tumor immunotherapy in BLCA. Using 3 different machine learning algorithms, we identified chondroitin polymerizing factor () as a central glycolytic gene with high expression in BLCA. In addition, we showed is a valuable diagnostic marker of BLCA with an area under the ROC (AUC) of 0.81. Sequencing BLCA 5637 cells after siRNA-mediated silencing and bioinformatics revealed that positively correlated with the markers of epithelial-to-mesenchymal transformation (EMT), glycometabolism-related enzymes, and immune cell infiltration. In addition, silencing inhibited the infiltration of multiple immune cells in BLCA. Genes that promote cuproptosis negatively correlated with expression and were up-regulated after silencing. High expression was a risk factor for overall and progression-free survival of patients who received immunotherapy for BLCA. Finally, using immunohistochemistry, we demonstrated that the CHPF protein had high expression in BLCA, increasing in high-grade tumors and those with muscle invasion. The CHPF expression levels were also positively associated with F-fluorodeoxyglucose uptake in PET/CT images. We conclude that the glycolysis-related gene is an effective diagnostic and treatment target for BLCA.
The signature of cuproptosis-related immune genes predicts the tumor microenvironment and prognosis of prostate adenocarcinoma.
Frontiers in immunology
Background:Cuproptosis plays a crucial role in cancer, and different subtypes of cuproptosis have different immune profiles in prostate adenocarcinoma (PRAD). This study aimed to investigate immune genes associated with cuproptosis and develop a risk model to predict prognostic characteristics and chemotherapy/immunotherapy responses of patients with PRAD. Methods:The CIBERSORT algorithm was used to evaluate the immune and stromal scores of patients with PRAD in The Cancer Genome Atlas (TCGA) cohort. Validation of differentially expressed genes DLAT and DLD in benign and malignant tissues by immunohistochemistry, and the immune-related genes of DLAT and DLD were further screened. Univariable Cox regression were performed to select key genes. Least absolute shrinkage and selection operator (LASSO)-Cox regression analyse was used to develop a risk model based on the selected genes. The model was validated in the TCGA, Memorial Sloan-Kettering Cancer Center (MSKCC) and Gene Expression Omnibus (GEO) datasets, as well as in this study unit cohort. The genes were examined functional enrichment analysis, and the tumor immune features, tumor mutation features and copy number variations (CNVs) of patients with different risk scores were analysed. The response of patients to multiple chemotherapeutic/targeted drugs was assessed using the pRRophetic algorithm, and immunotherapy was inferred by the Tumor Immune Dysfunction and Exclusion (TIDE) and immunophenoscore (IPS). Results:Cuproptosis-related immune risk scores (CRIRSs) were developed based on PRLR, DES and LECT2. High CRIRSs indicated poor overall survival (OS), disease-free survival (DFS) in the TCGA-PRAD, MSKCC and GEO datasets and higher T stage and Gleason scores in TCGA-PRAD. Similarly, in the sample collected by the study unit, patients with high CRIRS had higher T-stage and Gleason scores. Additionally, higher CRIRSs were negatively correlated with the abundance of activated B cells, activated CD8 T cells and other stromal or immune cells. The expression of some immune checkpoints was negatively correlated with CRIRSs. Tumor mutational burden (TMB), mutant-allele tumor heterogeneity (MATH) and copy number variation (CNV) scores were all higher in the high-CRIRS group. Multiple chemotherapeutic/targeted drugs and immunotherapy had better responsiveness in the low-CRIRS group. Conclusion:Overall, lower CRIRS indicated better response to treatment strategies and better prognostic outcomes.
10.3389/fimmu.2023.1181370
FNBP4 is a Potential Biomarker Associated with Cuproptosis and Promotes Tumor Progression in Hepatocellular Carcinoma.
International journal of general medicine
Background:Hepatocellular carcinoma (HCC) is one of the most common malignant tumors that lacks an efficient therapeutic approach because of its elusive molecular mechanisms. This study aimed to investigate the biological function and potential mechanism of formin-binding protein 4 (FNBP4) in HCC. Methods:FNBP4 expression in tissues and cells were detected by quantitative real-time PCR (qRT‒PCR), Western blot, and immunohistochemistry (IHC). The Kaplan-Meier method was used to explore the correlation between the FNBP4 expression and clinical survival. MTT, EdU incorporation, colony formation, and Transwell assays were performed to evaluate the function of FNBP4 in cell proliferation and migration in vitro. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was used to explore the potential mechanism of FNBP4. The prognostic risk signature and nomogram were constructed to demonstrate the prognostic value of FNBP4. Results:We found that FNBP4 was upregulated in patients with HCC and associated with poor overall survival (OS). Furthermore, knockdown of FNBP4 inhibited the proliferation and migration in HCC cells. Then, we performed a KEGG pathway analysis of the coexpressed genes associated with FNBP4 and found that FNBP4 may be associated with tumor-related signaling pathways and cuproptosis. We verified that FNBP4 could cause cell cycle progression and inactivation of the hippo signaling pathway. A prognostic risk signature containing three FNBP4-related differentially expressed cuproptosis regulators (DECRs) was established and can be used as an independent risk factor to evaluate the prognosis of patients with HCC. In addition, a nomogram including a risk score and clinicopathological factors was used to predict patient survival probabilities. Conclusion:FNBP4, as a potential biomarker associated with cuproptosis, promotes HCC cell proliferation and metastasis. We provide a new potential strategy for HCC treatment by targeting FNBP4.
10.2147/IJGM.S395881
Identification and validation of a novel cuproptosis-related lncRNA signature for predicting colorectal cancer patients' survival.
Journal of gastrointestinal oncology
Background:Cuproptosis is a novel form of cell death referred to as copper-dependent cytotoxicity. The regulation of proptosis is becoming an increasingly popular cancer treatment modality. To date, few studies have attempted to identify the cuproptosis-related long non-coding RNAs (CRLs). In this study, we sought to investigate the CRLs and construct a novel prognostic model for colorectal cancer (CRC). Methods:The RNA-sequencing data of CRC patients were obtained from The Cancer Genome Atlas database. An analysis was conducted to identify the differentially expressed long non-coding RNAs, and a correlation analysis was performed to identify the CRLs. A univariate Cox analysis was conducted to select the prognostic CRLs. Based on a least absolute shrinkage and selection operator regression analysis, a prognostic signature comprising the 22 identified CRLs was constructed. A survival receiver operating characteristic curve analysis was conducted to evaluate the performance of the signature. Finally, an analysis was performed to investigate the function of lncRNA AC090116.1 in the CRC cells. Results:A signature comprising 22 CRLs was developed. The patients in the training and validation sets were divided into the low- and high-risk groups and had significantly different survival probabilities. This signature had outstanding prognostic accuracy in predicting the 5-year overall survival of patients [training set, area under the curve (AUC) =0.820; validation set, AUC =0.810]. The pathway enrichment analysis showed that the differential genes between low and high groups were enriched in several important oncogenic- and metastatic-associated processes and pathways. Finally, the experiments showed that AC090116.1 silencing promoted the cuproptosis processes and suppressed cell proliferation. Conclusions:Our findings provided promising insights into the CRLs involved in CRC. The signature based on CRLs has been successfully devised to prognosticate the clinical outcomes and treatment responses in patients.
10.21037/jgo-23-228
The Prognosis and Immunotherapy Prediction Model of Ovarian Serous Cystadenocarcinoma Patient was Constructed Based on Cuproptosis-Related LncRNA.
The Tohoku journal of experimental medicine
Cuproptosis can serve as potential prognostic predictors in patients with cancer. However, the role of this relationship in ovarian serous cystadenocarcinoma (OV) remains unclear. 376 OV tumor samples were obtained from the Cancer Genome Atlas (TCGA) database, and long non-coding RNAs (lncRNAs) related to cuproptosis were obtained through correlation analysis. The risk assessment model was further constructed by univariate Cox regression analysis and LASSO Cox regression. Bioinformatics was used to analyze the regulatory effect of relevant risk assessment models on tumor mutational burden (TMB) and immune microenvironment. We obtained 5 lncRNAs (AC025287.2, AC092718.4, AC112721.2, LINC00996, and LINC01639) and incorporated them into the Cox proportional hazards model. Kaplan-Meier (KM) curve analysis of the prognosis found that the high-risk group was associated with a poorer prognosis. The receiver operating characteristic (ROC) curve showed stronger predictive power compared to other clinicopathological features. Immune infiltration analysis showed that high-risk scores were inversely correlated with CD8+ T cells, CD4+ T cells, macrophages, NK cells, and B cells. Functional enrichment analysis found that they may act via the extracellular matrix (ECM)-interacting proteins and other pathways. We successfully constructed a reliable cuproptosis-related lncRNA model for the prognosis of OV.
10.1620/tjem.2023.J056
Elucidating Cuproptosis-Associated Genes in the Progression from Nash to HCC Using Bulk and Single-Cell RNA Sequencing Analyses and Experimental Validation.
Medicina (Kaunas, Lithuania)
: Non-alcoholic steatohepatitis (NASH) is a significant risk factor for hepatocellular carcinoma (HCC) development. Timely treatment during the NASH stage is essential to minimize the possibility of disease progression to HCC. Cuproptosis is a newly identified form of cellular death that could impact the progression of various diseases and cancers. : Transcriptome and single-cell sequencing datasets were utilized to investigate the role of cuproptosis-related genes (CRGs) in NASH progression to HCC. FDX1, LIPT1, and PDHP were identified as CRGs in NASH patients, and FDX1, DBT, GCSH, SLC31A1, and DLAT were identified as CRGs in patients with NASH progressing to HCC. FDX1 was found to play a significant role in both NASH patients and patients with NASH progressing to HCC. This study constructed cuproptosis-related clusters (CRCs) using the Nonnegative Matrix Factorization algorithm, and they were linked to fatty acid metabolism and the PPAR signaling pathway in both NASH CRCs and HCC CRCs. The Weighted Correlation Network Analysis algorithm identified CRP, CRC, TAT, CXCL10, and ACTA1 as highly relevant genes in NASH CRCs and HCC CRCs. The expression of FDX1 was validated in both mouse models and human NASH samples. : The investigation highlights FDX1 as a pivotal CRG in both NASH and NASH progression to HCC. The comprehensive characterization of CRGs sheds light on their potential biofunctional importance in the context of NASH and HCC. Our experimental results show that FDX1 expression was significantly increased in NASH patients. : The present study identified key CRGs, revealing their potential impact on NASH and HCC. Meanwhile, targeting FDX1 may prevent the progression of NASH to HCC.
10.3390/medicina59091639
Cuproptosis-related lncRNA SNHG16 as a biomarker for the diagnosis and prognosis of head and neck squamous cell carcinoma.
PeerJ
Background:We aim to investigate the potential value of cuproptosis-related lncRNA signaling in predicting clinical prognosis and immunotherapy and its relationship with drug sensitivity in head and neck squamous cell carcinoma (HNSCC). Methods:We first identified the lncRNAs associated with cuproptosis genes in HNSCC and then conducted a series of analytical studies to investigate the expression and prognostic significance of these lncRNAs. Finally, we used RT-qPCR to validate our findings in a laryngeal squamous cell carcinoma cell line and 12 pairs of laryngeal squamous cell carcinoma and adjacent normal tissues. Results:We identified 11 differentially expressed lncRNAs that were associated with cuproptosis genes in HNSCC and also served as prognostic markers for this cancer. Enrichment analysis revealed that these lncRNAs were related to immune-related functions that were suppressed in patients with oncogene mutations in the high-risk group. The patients with a high tumor mutation burden exhibited poor overall survival (OS). We used the tumor immune dysfunction and exclusion model to show that the patients in the high-risk group had great potential for immune evasion and less effective immunotherapy. We also identified several drugs that could be effective in treating HNSCC. Experimental validation showed that AC090587.1 and AC012184.3 exhibited differential expression between the TU686 and HBE cell lines, and SNHG16 showed differential expression among the TU686, TU212, and control HBE cells. Among the 12 pairs of cancer and adjacent tissues collected in the clinic, only SNHG16 showed differential expression. Targeted therapy against SNHG16 holds promise as a prospective novel strategy for the clinical management of HNSCC.
10.7717/peerj.16197
The function and immune role of cuproptosis associated hub gene in Barrett's esophagus and esophageal adenocarcinoma.
Bioscience trends
Barrett's esophagus (BE) is a precancerous lesion of esophageal adenocarcinoma (EAC), with approximately 3-5% of patients developing EAC. Cuproptosis is a kind of programmed cell death phenomenon discovered in recent years, which is related to the occurrence and development of many diseases. However, its role in BE and EAC is not fully understood. We used single sample Gene Set Enrichment Analysis (ssGSEA) for differential analysis of BE in the database, followed by enrichment analysis of Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO) and GSEA, Protein-Protein Interaction (PPI), Weighted Gene Co-expression Network Analysis (WGCNA), Receiver Operating Characteristic Curve (ROC) and finally Quantitative Real Time Polymerase Chain Reaction (qRT-PCR) and immunohistochemistry (IHC) of clinical tissues. Two hub genes can be obtained by intersection of the results obtained from the cuproptosis signal analysis based on BE. The ROC curves of these two genes predicted EAC, and the Area Under the Curve (AUC) values could reach 0.950 and 0.946, respectively. The mRNA and protein levels of Centrosome associated protein E (CENPE) and Shc SH2 domain binding protein 1 (SHCBP1) were significantly increased in clinical EAC tissues. When they were grouped by protein expression levels, high expression of CENPE or SHCBP1 had a poor prognosis. The CENPE and SHCBP1 associated with cuproptosis may be a factor promoting the development of BE into EAC which associated with the regulation of NK cells and T cells.
10.5582/bst.2023.01164
Comprehensive analysis of prognosis of cuproptosis-related oxidative stress genes in multiple myeloma.
Frontiers in genetics
Multiple myeloma (MM) is a highly heterogeneous hematologic malignancy. The patients' survival outcomes vary widely. Establishing a more accurate prognostic model is necessary to improve prognostic precision and guide clinical therapy. We developed an eight-gene model to assess the prognostic outcome of MM patients. Univariate Cox analysis, Least absolute shrinkage and selection operator (LASSO) regression, and multivariate Cox regression analyses were used to identify the significant genes and construct the model. Other independent databases were used to validate the model. The results showed that the overall survival of patients in the high-risk group was signifificantly shorter compared with that of those in the low-risk group. The eight-gene model demonstrated high accuracy and reliability in predicting the prognosis of MM patients. Our study provides a novel prognostic model for MM patients based on cuproptosis and oxidative stress. The eight-gene model can provide valid predictions for prognosis and guide personalized clinical treatment. Further studies are needed to validate the clinical utility of the model and explore potential therapeutic targets.
10.3389/fgene.2023.1100170
Cuproptosis-related LncRNAs signature as biomarker of prognosis and immune infiltration in pancreatic cancer.
Frontiers in genetics
Pancreatic cancer (PC) is a malignant gastrointestinal tumor with a terrible prognosis. Cuproptosis is a recently discovered form of cell death. This study is intended to explore the relationship between cuproptosis-related lncRNAs (CRLncs) signature with the prognosis and the tumor microenvironment (TME) of PC. Transcript sequencing data of PC samples with clinical information were obtained from the Cancer Genome Atlas (TCGA). Univariate Cox regression analysis and LASSO regression analysis were employed to construct the prognostic signature based on CRLncs associated with PC survival. A nomogram was created according to this signature, and the signaling pathway enrichment was analyzed. Subsequently, we explored the link between this prognostic signature with the mutational landscape and TME. Eventually, drug sensitivity was predicted based on this signature. Forty-six of 159 CRLncs were most significantly relevant to the prognosis of PC, and a 6-lncRNA prognostic signature was established. The expression level of signature lncRNAs were detected in PC cell lines. The AUC value of the ROC curve for this risk score predicting 5-year survival in PC was .944, which was an independent prognostic factor for PC. The risk score was tightly related to the mutational pattern of PC, especially the driver genes of PC. Single-sample gene set enrichment analysis (ssGSEA) demonstrated a significant correlation between signature with the TME of PC. Ultimately, compounds were measured for therapy in high-risk and low-risk PC patients, respectively. A prognostic signature of CRLncs for PC was established in the current study, which may serve as a promising marker for the outcomes of PC patients and has important forecasting roles for gene mutations, immune cell infiltration, and drug sensitivity in PC.
10.3389/fgene.2023.1049454
Establishment and validation of a cuproptosis-related lncRNA signature that predicts prognosis and potential targeted therapy in hepatocellular carcinoma.
Biotechnology & genetic engineering reviews
BACKGROUND:Cuproptosis is a recently identified form of programmed cell death and could be a new direction for tumour therapy, and it has important clinical implications. Long non-coding RNAs (lncRNAs) can intervene in diverse biological processes and have a decisive role in hepatocellular carcinoma (HCC). However, how cuproptosis-related lncRNAs (CRLs) participate in regulating HCC has yet to be recognised. This study aimed to establish and validate a prognostic signature of CRLs and to analyse their clinical value in HCC patients. METHODS:To analyse the function of CRLs in the prognosis of HCC, RNA sequencing data, mutation data, and clinically relevant data were collected from the Cancer Genome Atlas Database (TCGA). Then, TCGA cohort was randomly divided into training and test sets. The training set was utilized to define prognostic signature of CRLs using bioinformatics methods. Subsequently, we verified the accuracy of this prognostic signature in the test set. Finally, we performed immune-related analysis, the half-maximal inhibitory concentration (IC50) prediction, gene set enrichment analysis, and tumour mutational burden (TMB) analysis. RESULTS:We established a prognostic signature for the CRLs (SNHG4, AC026412.3, AL590705.3, and CDKN2A-DT). This signature-based risk group displayed an accurate predictive ability for the survival time of patients with HCC. We observed discrepancies in immune cells, immune function, the expression level of genes related to immune checkpoints, and TMB in high- and low-risk groups. CONCLUSION:This CRLs prognostic signature could predict clinical outcomes in patients with HCC as well as the efficacy of targeted and therapy immunotherapy.
10.1080/02648725.2023.2190640
Systematic analysis of cuproptosis-related genes in immunological characterization and predictive drugs in Alzheimer's disease.
Frontiers in aging neuroscience
Objectives:This study aimed to make a systematic analysis of cuproptosis-related genes (CRGs) in immunological characterization and predictive drugs in Alzheimer's disease (AD) through bioinformatics and biological experiments. Methods:The molecular clusters related to CRGs and associated immune cell infiltrations in AD were investigated. The diagnostic models were constructed for AD and different AD subtypes. Moreover, drug prediction and molecular docking were also performed. Subsequently, a molecular dynamics (MD) simulation was conducted to further verify the findings. Finally, RT-qPCR validation was performed. Results:The characterization of 12 AD-related CRGs was evaluated in AD, and a diagnostic model for AD showed a satisfying discrimination power based on five CRGs by LASSO regression analysis. The dysregulated CRGs and activated immune responses partially differed between patients with AD and healthy subjects. Furthermore, two molecular subtypes (clusters A and B) with different immune infiltration characteristics in AD were identified. Similarly, a diagnostic model for different AD subtypes was built with nine CRGs, which achieved a good performance. Molecular docking revealed the optimum conformation of CHEMBL261454 and its target gene CSNK1D, which was further validated by MD simulation. The RT-qPCR results were consistent with those of the comprehensive analysis. Conclusion:This study systematically elucidated the complex relationship between cuproptosis and AD, providing novel molecular targets for treatment and diagnosis biomarkers of AD.
10.3389/fnagi.2023.1204530
Cuproptosis-related ceRNA axis triggers cell proliferation and cell cycle through CBX2 in lung adenocarcinoma.
BMC pulmonary medicine
BACKGROUND:Lung adenocarcinoma (LUAD) has high morbidity and mortality. Despite substantial advances in treatment, the prognosis of patients with LUAD remains unfavorable. The ceRNA axis has been reported to play an important role in the pathogenesis of LUAD. In addition, cuproptosis is considered an important factor in tumorigenesis. The expression of CBX2 has been associated with the development of multiple tumors, including LUAD. However, the precise molecular mechanisms through which the cuproptosis-related ceRNA network regulates CBX2 remain unclear. METHODS:The DEGs between tumor and normal samples of LUAD were identified in TCGA database. The "ConsensusClusterPlus" R package was used to perform consensus clustering based on the mRNA expression matrix and cuproptosis-related gene expression profile. Then, LASSO-COX regression analysis was performed to identify potential prognostic biomarkers associated with cuproptosis, and the ceRNA network was constructed. Finally, the mechanisms of ceRNA in LUAD was studied by cell experiments. RESULTS:In this study, the AC144450.1/miR-424-5p axis was found to promote the progression of LUAD by acting on CBX2. The expression of AC144450.1 and miR-424-5p can be altered to regulate CBX2 and is correlated with cell proliferation and cell cycle of LUAD. Mechanistically, AC144450.1 affects the expression of CBX2 by acting as the ceRNA of miR-424-5p. In addition, a cuproptosis-related model were constructed in this study to predict the prognosis of LUAD. CONCLUSIONS:This study is the first to demonstrate that the AC144450.1/miR-424-5p/CBX2 axis is involved in LUAD progression and may serve as a novel target for its diagnosis and treatment.
10.1186/s12890-024-02887-0
Coordination of Single-cell and Bulk RNA Sequencing to Construct a Cuproptosis-related Gene Prognostic Index for Endometrial Cancer Prognosis, Immune Microenvironment Infiltration, and Immunotherapy Treatment Options.
Journal of Cancer
: This study aims to identify molecular subtypes and develop a cuproptosis-related gene prognostic index (CRGPI) for endometrial cancer (EC), in addition to outlining the immune features and the efficacy of immune checkpoint inhibitor (ICI) therapy in CRGPI-defined groups of EC. : Between malignant and normal cells distinguished from single-cell RNA sequencing data GSE154763 dataset, the difference in KEGG pathways and cuproptosis-related gene (CRG) scores was intensively investigated. On the basis of TCGA dataset (n=492), CRGs were used to identify two distinct molecular subtypes. Using the Cox regression method, a CRGPI was constructed and externally validated with the IMvigor210 dataset (n=348) and GSE78220. Then, the molecular and immune characteristics and the efficacy of ICI therapy in subgroups defined by CRGPI were investigated. : Compared to normal cells, the expression of the TCA cycle and CRGs genes was significantly higher in malignant cells. The CRGPI was established on the premise of ATF5, FBXO46, P2RX4, SMARCD3, DAPK3, and C1orf53. Comprehensive results demonstrated a correlation between a low CRGPI score and better overall survival, younger age, early stage, immune cells and functions activation, high tumor mutation burden and high microsatellite instability, as well as better benefit from ICI therapy, and its significance for forecasting immunotherapeutic effects was verified as well (IMvigor210 cohort: HR, 1.358; 95% CI, 1.047, 1.761; p=0.02; GSE78220 cohort: HR, HR = 3.857, 95% CI, 1.009, 14.74; p=0.034). CRGPI anticipated the immunotherapy medication. : CRGPI is a prospective biomarker to estimate the prognosis, immune and molecular characteristics, and treatment benefit of immunotherapy in EC.
10.7150/jca.86325
Prediction of immune infiltration and prognosis for patients with cholangiocarcinoma based on a cuproptosis-related lncRNA signature.
Heliyon
Objective:Cholangiocarcinoma (CHOL) is a malignant disease that affects the digestive tract, and it is characterized by a poor prognosis. This research sought to explore the involvement of cuproptosis-related lncRNAs (CRLs) in the prognostic prediction and immune infiltration of cholangiocarcinoma. Methods:The expression profiles and clinical data of CHOL patients were acquired from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, and CRLs were defined via co-expression analysis. Two molecular clusters distinguished by cuproptosis-related genes (CRGs) were produced. Then a risk signature consisted by four CRLs was formed, and all samples were separated into low- and high-risk groups using a risk score. Kaplan-Meier survival analysis, principal component analysis, differentially expressed analysis, immune cell infiltration analysis, and sensitivities analysis of chemotherapy drugs were conducted between the two groups. Simultaneously, the expression values of four lncRNAs confirmed by real-time PCR in our own 20 CHOL samples were brought into the risk model. Results:The CHOL samples could be differentiated into two molecular clusters, which displayed contrasting survival times. Additionally, patients with higher risk scores had significantly worse prognosis compared to those in the low-risk group. Furthermore, both immune infiltration and enrichment analysis revealed significant discrepancies in the tumor immune microenvironment (TIME) between different risk groups. Moreover, the predictive power and the correlation with CA19-9 and CEA of risk signature were validated in our own samples. Conclusion:We developed a risk signature which could serve as an independent prognostic factor and offer a promising prediction for not only prognosis but also TIME in CHOL patients.
10.1016/j.heliyon.2023.e22774
Crosstalk of cuproptosis-related subtypes, establishment of a prognostic signature, and immune infiltration characteristics in gastric cancer.
Heliyon
Background:Cuproptosis is a novel form of cellular demise that occurs through a unique pathway involving lipoylated proteins in the tricarboxylic acid (TCA) cycle and is closely linked to mitochondrial metabolism. Nevertheless, the comprehensive elucidation of the impact of carcinogenesis-associated genes (CRGs) on prognosis, tumor microenvironment (TME), and therapeutic response in patients with gastric cancer (GC) remains unclear. Methods:In total, 1374 GC samples were gathered from three Gene Expression Omnibus (GEO) datasets and The Cancer Genome Atlas database. The samples were then stratified into different subtypes through unsupervised clustering of the 13 CRG profiles. The CRG_score was developed to quantify CRG patterns of individual tumors. Subsequently, we investigated the associations among the various groups and clinicopathological features, immune infiltration features, TME mutation status, and response to immunotherapy. Results:The GC samples were divided into two clusters based on their distinct clinicopathological features, prognosis, and immune characteristics. Using LASSO and Cox regression analyses, 9 genes were identified for constructing a prognostic signature related to cuproptosis. The novel signature displayed outstanding durability and prognostic capability for the overall lifespan of individuals. Additionally, the expression levels of signature genes in GC tissues and adjacent normal tissues were tested by qRT-PCR. Moreover, we developed a remarkably dependable nomogram to enhance the practicality of the CRG_score in clinical settings. High tumor mutation burden, increased microsatellite instability-high, immune activation, along with good survival probability and increased immunoreactivity to immune checkpoint inhibitors, were distinguishing features of low CRG_scores. Conclusions:The findings of this study revealed the possible impacts of CRGs on the TME, clinical and pathological characteristics, and outlook of patients with GC. This signature was strongly linked to the immune response against GC and has the potential to serve as a valuable tool for predicting patient prognosis.
10.1016/j.heliyon.2024.e24411
Comprehensive analysis of the relationship between cuproptosis-related genes and esophageal cancer prognosis.
World journal of clinical cases
BACKGROUND:Esophageal cancer is one of the most common malignant tumors of the digestive system, with a 5-year survival rate of 15% to 50%. Cuproptosis, a unique kind of cell death driven by protein lipoylation, is strongly connected to mitochondrial metabolism. The clinical implications of cuproptosis-related genes in esophageal cancer, however, are mainly unknown. AIM:To identify cuprotosis-related genes that are differentially expressed in esophageal cancer and investigate their prognostic significance. METHODS:With |log fold change| > 1 and false discovery rate < 0.05 as criteria, the Wilcox test was used to evaluate the differentially expressed genes between 151 tumor tissues and 151 normal esophageal tissues. Cuproptosis-related genes were selected to be linked with prognosis using univariate Cox regression analysis. Genes were separated into high- and low- expression groups based on their cutoff value of gene expression, and the correlation between the two groups and overall survival or progression-free survival was investigated using the log-rank test. The C-index, calibration curve, and receiver operator characteristic (ROC) curve were used to assess a nomogram containing clinicopathological characteristics and cuproptosis-related genes. RESULTS:Pyruvate dehydrogenase A1 (PDHA1) was found to be highly correlated with prognosis in univariate Cox regression analysis (hazard ratio = 22.96, 95% confidence interval = 3.09-170.73; = 0.002). According to Kaplan-Meier survival curves, low expression of PDHA1 was associated with a better prognosis (log-rank = 0.0007). There was no significant correlation between PDHA1 expression and 22 different types of immune cells. Tumor necrosis factor superfamily member 15 (TNFSF15) ( = 3.2 × 10; = 0.37), TNFRSF14 ( = 8.1 × 10; = 0.42), H long terminal repeat-associating 2 ( = 6.0 × 10; = 0.42) and galectin 9 ( = 3.1 × 10; = 0.37) were all found to be considerably greater in the high PDHA1 expression group, according to an analysis of genes related to 47 immunological checkpoints. The low PDHA1 expression group had significantly lower levels of cluster of differentiation 44 (CD44) ( = 0.00028; R = -0.29), TNFRSF18 ( = 1.2 × 10; R = -0.35), programmed cell death 1 ligand 2 ( = 0.0032; R = -0.24), CD86 ( = 0.018; R = -0.19), and CD40 ( = 0.0047; R = -0.23), and the differences were statistically significant. We constructed a prognostic nomogram incorporating pathological type, tumor-node-metastasis stage, and PDHA1 expression, and the C-index, calibration curve, and ROC curve revealed that the nomogram's predictive performance was good. CONCLUSION:Cuproptosis-related genes can be used as a prognostic predictor for esophageal cancer patients, providing novel insights into cancer treatment.
10.12998/wjcc.v10.i33.12089
Identification and validation of a novel cuproptosis-related gene signature in multiple myeloma.
Frontiers in cell and developmental biology
Cuproptosis is a newly identified unique copper-triggered modality of mitochondrial cell death, distinct from known death mechanisms such as necroptosis, pyroptosis, and ferroptosis. Multiple myeloma (MM) is a hematologic neoplasm characterized by the malignant proliferation of plasma cells. In the development of MM, almost all patients undergo a relatively benign course from monoclonal gammopathy of undetermined significance (MGUS) to smoldering myeloma (SMM), which further progresses to active myeloma. However, the prognostic value of cuproptosis in MM remains unknown. In this study, we systematically investigated the genetic variants, expression patterns, and prognostic value of cuproptosis-related genes (CRGs) in MM. CRG scores derived from the prognostic model were used to perform the risk stratification of MM patients. We then explored their differences in clinical characteristics and immune patterns and assessed their value in prognosis prediction and treatment response. Nomograms were also developed to improve predictive accuracy and clinical applicability. Finally, we collected MM cell lines and patient samples to validate marker gene expression by quantitative real-time PCR (qRT-PCR). The evolution from MGUS and SMM to MM was also accompanied by differences in the CRG expression profile. Then, a well-performing cuproptosis-related risk model was developed to predict prognosis in MM and was validated in two external cohorts. The high-risk group exhibited higher clinical risk indicators. Cox regression analyses showed that the model was an independent prognostic predictor in MM. Patients in the high-risk group had significantly lower survival rates than those in the low-risk group ( < 0.001). Meanwhile, CRG scores were significantly correlated with immune infiltration, stemness index and immunotherapy sensitivity. We further revealed the close association between CRG scores and mitochondrial metabolism. Subsequently, the prediction nomogram showed good predictive power and calibration. Finally, the prognostic CRGs were further validated by qRT-PCR . CRGs were closely related to the immune pattern and self-renewal biology of cancer cells in MM. This prognostic model provided a new perspective for the risk stratification and treatment response prediction of MM patients.
10.3389/fcell.2023.1159355
Sepsis induced cardiotoxicity by promoting cardiomyocyte cuproptosis.
Biochemical and biophysical research communications
BACKGROUND:Currently, sepsis induced cardiotoxicity is among the major causes of sepsis-related death. The specific molecular mechanisms of sepsis induced cardiotoxicity are currently unknown. Therefore, the purpose of this paper is to identify the key molecule mechanisms for sepsis induced cardiotoxicity. METHODS:Original data of sepsis induced cardiotoxicity was derived from Gene Expression Omnibus (GEO; GSE63920; GSE44363; GSE159309) dataset. Functional enrichment analysis was used to analysis sepsis induced cardiotoxicity related signaling pathways. Our findings also have explored the relationship of cuproptosis and N6-Methyladenosine (m6A) in sepsis induced cardiotoxicity. Mice are randomly assigned to 3 groups: saline treatment control group, LPS group administered a single 5 mg/kg dose of LPS for 24 h, LPS + CD274 inhibitor group administered 10 mg/kg CD274 inhibitor for 24 h. RESULTS:Overall, expression of cuproptosis-related genes (CRGs) CD274, Ceruloplasmin (CP), Vascular endothelial growth factor A (VEGFA), Copper chaperone for cytochrome c oxidase 11 (COX11), chemokine C-C motif ligand 8 (CCL8), Mitogen-activated protein kinase kinase 1(MAP2K1), Amine oxidase 3 (AOC3) were significantly altered in sepsis induced cardiotoxicity. The results of spearman correlation analysis was significant relationship between differentially regulated genes (DEGs) of CRGs and the expression level of m6A methylation genes. GO and KEGG showed that these genes were enriched in response to interferon-beta, MHC class I peptide loading complex, proteasome core complex, chemokine receptor binding, TAP binding, chemokine activity, cytokine activity and many more. These findings suggest that cuproptosis is strongly associated with sepsis induced cardiotoxicity. CONCLUSION:In the present study, we found that cuproptosis were associated with sepsis induced cardiotoxicity. The CD274, CP, VEGFA, COX11, CCL8, MAP2K1, AOC3 genes are showing a significant difference expression in sepsis induced cardiotoxicity. Our studies have found significant correlations between CRGs and m6A methylation related genes in sepsis induced cardiotoxicity. These results provide insight into mechanism for sepsis induced cardiotoxicity.
10.1016/j.bbrc.2023.149245
Bioinformatics analysis and experimental validation of cuproptosis-related lncRNA LINC02154 in clear cell renal cell carcinoma.
BMC cancer
BACKGROUND:Clear cell renal cell carcinoma (ccRCC) is common in urinary system tumors. Cuproptosis is a non-apoptotic cell death pathway. Copper binds to fatty acylated mitochondrial proteins and activates various forms of cell death. LncRNA LINC02154 is significantly highly expressed in cells and tissues of many types of tumors, and the risk signature of LINC02154 in some tumors has been validated for effectiveness. METHODS:We constructed a risk prognostic signature by obtaining differentially expressed long noncoding RNAs (lncRNAs) associated with ccRCC outcomes and cuproptosis from The Cancer Genome Atlas (TCGA). We used TCGA to construct training and testing sets to analyze the risk signature and the impact of LINC02154, and we performed relevant survival analyses. Tumor mutational burdens were analyzed in different LINC02154 expression groups and risk score groups. We next analyzed the immune microenvironment of LINC20154. We performed LINC20154-related drug sensitivity analyses. We also investigated the cellular function of LINC02154 in the ACHN cell line and performed CCK-8 assay, EdU, wound-healing assay, and Transwell assay. The essential genes FDX1 and DLST of cuproptosis were detected by western blot. RESULTS:We demonstrated that LINC02154's impact on outcomes was statistically significant. We also demonstrated the association of different ages, genders, stages, and grades with LINC02154 and risk models. The results showed a significant difference in tumor mutation burden between the groups, which was closely related to clinical prognosis. We found differences in immune cells among groups with different levels of LINC02154 expression and significant differences in immune function, immunotherapeutic positive markers, and critical steps of the immune cycle. The sensitivity analysis showed that differential expression of LINC02154 discriminated between sensitivity to axitinib, doxorubicin, gemcitabine, pazopanib, sorafenib, sunitinib, and temsirolimus. This difference was also present in the high-risk group and low-risk group. We demonstrated that the proliferation and migration of t ACHN cells in the LINC02154 knockdown group were inhibited. The western blot results showed that the knockdown of LINC02154 significantly affected the expression of FDX1 and DLST, critical genes of cuproptosis. CONCLUSION:Finally, we demonstrated that LINC02154 and our constructed risk signature could predict outcomes and have potential clinical value.
10.1186/s12885-023-10639-2
Is a Pan-Cancer Prognostic and Immunotherapeutic Predictor Associated with EMT and Cuproptosis in HNSCC.
International journal of molecular sciences
Metabolism plays a critical role in cancer. has been implicated in cardiovascular and metabolic disorders, while its association with tumorigenesis and tumor immunity remains poorly defined in the literature. We conducted comprehensive pan-cancer analyses based on the TCGA database to examine expression and its prognostic implications. Correlations between expression level and tumor immunity and immunotherapy were investigated by immune infiltration, enrichment, and TIDE analysis methods. Immunohistochemistry detected expression in HNSCC. We used the GSEA method to explore the potential signaling pathways in which is involved, and a correlation analysis to investigate the relationships between and epithelial-mesenchymal transition (EMT) and cuproptosis. In addition, the effects of knockdown on the EMT process, invasion, stemness, and cuproptosis of HNSCC cells were examined by scratch, Transwell, CCK8, sphere formation, and flow cytometry, while changes in related proteins were detected using the immunoblotting method. is highly expressed in most cancers, and it is associated with patient prognosis. expression positively correlates with immunosuppressive cell infiltration and immune checkpoint molecules, while being negatively associated with effector T cells. Moreover, significant correlations are observed between expression and tumor mutation burden (TMB) and microsatellite instability (MSI) in some cancers. In HNSCC, expression is related to advanced clinicopathological factors and unfavorable outcomes. Patients with high expression levels are prone to experience immune escape and benefit less from immune checkpoint inhibitor (ICI) therapy. Moreover, expression may affect EMT, stemness, and cuproptosis resistance outcomes. is an immune-related prognostic biomarker with potential as a prognostic indicator for immunotherapy, and it may also be involved in regulating the EMT process and cuproptosis in HNSCC.
10.3390/ijms241612904
Cuproptosis-related gene subtypes predict prognosis in patients with head and neck squamous cell carcinoma.
Journal of otolaryngology - head & neck surgery = Le Journal d'oto-rhino-laryngologie et de chirurgie cervico-faciale
BACKGROUND:Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer worldwide. A novel form of copper-dependent and reactive oxygen species (ROS)-dependent cell death, cuproptosis, has been described in many cancers. The roles and potential mechanisms of cuproptosis-related genes (CRGs) are still unclear in HNSCC. METHOD:We downloaded TCGA datasets of HNSCC genomic mutations and clinic data from The Cancer Genome Atlas. Based on the Cuproptosis-related differentially expressed genes in HNSCC, we constructed a prognostic signature. RESULTS:Eight CRGs have been identified as associated with the prognosis of HNSCC. According to Kaplan-Meier analyses, HNSCC with a high Risk Score had a poor prognosis. Furthermore, the AUC of the Risk Score for the 1-, 3-, and 5- year overall survival was respectively, 0.70, 0.71, and 0.68. TCGA data revealed that T cell functions, such as HLA, cytolytic activity, inflammation regulation, co-inhibition, and co-stimulation, differed significantly between members of the low and high groups. The immune checkpoint genes PD-L1, PD-L1, and CTLA-4 were also expressed differently in the two risk groups. CONCLUSIONS:A CRG signature was defined that is associated with the prognosis of patients with HNSCC.
10.1186/s40463-023-00655-4
Cuproptosis-related gene as a prognostic indicator in non-small cell lung cancer: Functional involvement and regulation ofexpression.
Biomolecules & biomedicine
Non-small cell lung cancer (NSCLC) is a leading cause of cancer-related deaths, necessitating a deeper understanding of novel cell death pathways like cuproptosis. This study explored the relevance of cuproptosis-related genes in NSCLC and their potential prognostic significance. We analyzed the expression of 16 cuproptosis-related genes in 1017 NSCLC tumors and 578 Genotype-Tissue Expression (GTEx) normal samples from The Cancer Genome Atlas (TCGA) to identify significant genes. A risk model and prognostic nomogram were employed to identify the pivotal prognostic gene. Further in vitro experiments were conducted to investigate the functions of the identified genes in NSCLC cell lines. LIPT1, a gene for lipoate-protein ligase 1 enzyme, emerged as the central prognostic gene with decreased expression in NSCLC. Importantly, elevated LIPT1 levels were associated with a favorable prognosis for NSCLC patients. Overexpression of LIPT1 inhibited cell growth and enhanced apoptosis in NSCLC. We confirmed that LIPT1 downregulates the copper chaperone gene antioxidant 1 (ATOX1), thereby impeding NSCLC progression. Our study identified LIPT1 as a valuable prognostic biomarker in NSCLC as it elucidates its tumor-inhibitory role through the modulation of ATOX1. These findings offered insights into the potential therapeutic targeting of LIPT1 in NSCLC, contributing to a deeper understanding of this deadly disease.
10.17305/bb.2023.9931
Cuproptosis patterns and tumor immune infiltration characterization in colorectal cancer.
Frontiers in genetics
Faced with the high heterogeneity and poor prognosis of colorectal cancer (CRC), this study sought to find new predictive prognostic strategies to improve the situation. Cuproptosis is a novel cell death mechanism that relies on copper regulation. However, the role of cuproptosis-related gene (CRG) in CRC remains to be elucidated. In this study, we comprehensively assessed the CRG landscape in CRC based on The Cancer Genome Atlas (TCGA). We identified differential expression and genetic alterations of CRG in CRC. CRG is highly correlated with initiation, progression, prognosis, and immune infiltration of CRC. We construct a risk score signature containing 3 CRGs based on LASSO. We explored the correlation of CRG-Score with clinicopathological features of CRC. Age, stage, and CRG-Score were integrated to construct a nomogram. The nomogram has robust predictive performance. We also understand the correlation of CRG-Score with CRC immune landscape. CRG-Score can effectively predict the immune landscape of CRC patients. Low-risk CRC patients have greater immunogenicity and higher immune checkpoint expression. Low-risk CRC patients may be better candidates for immunotherapy. At the same time, we also predicted more sensitive drugs in the high-risk CRC patients. In conclusion, the CRG risk score signature is a strong prognostic marker and may help provide new insights into the treatment of individuals with CRC.
10.3389/fgene.2022.976007
A novel cuproptosis-related gene prognostic signature in colon adenocarcinoma.
Canadian journal of physiology and pharmacology
Cuproptosis is the latest cell death type caused by enhanced mitochondrial-dependent energy metabolism. This study plans to establish a survival prognosis model for colon adenocarcinoma (COAD) patients based on cuproptosis-related genes (CRGs). We investigated the genetic alterations of CRGs in COAD based on The Cancer Genome Atlas database and validated in the GSE41328 dataset. Our results showed that LIPT1, PDHA1, GLS, and CDKN2A had significantly higher expression in COAD tissues than in normal tissues, while FDX1, DLD, and MTF1 had significantly lower expression in COAD tissues than in normal tissues (|(log2(fold change))| > 2, < 0.05). DLD (hazard ratio (HR): 0.658; 95% confidence interval (CI): 0.445, 0.974; = 0.037) and CDKN2A (HR: 1.785; 95% CI: 1.200, 2.654; = 0.004) expressions were linked with overall survival throughout a log-rank test. CRG prognostic scores exhibited an area under the curve of 0.737, 0.646, and 0.633 at 1, 3, and 5 years. Patients with a high-risk factor suffered from poor prognosis (HR = 1.514; 95% CI: 1.022, 2.243; = 0.0386). An independent validation dataset (GSE41328 ( = 20)) confirmed the above results. The CRGs' signature may be used as a prognostic predictor for COAD patients, providing unique insights into anticancer therapy.
10.1139/cjpp-2023-0118
Identification of cuproptosis-related subtypes, establishment of a prognostic model and tumor immune landscape in endometrial carcinoma.
Computers in biology and medicine
Cuproptosis, the mechanism of copper-dependent cell death, is distinct from all other known forms of regulated cell death and dependents on mitochondrial respiration. Cuproptosis promises to be a novel treatment, especially for tumors resistant to conventional therapies. We investigated the changes in cuproptosis-related genes (CRGs) in endometrial cancer (EC) cohorts from the merged Gene Expression Omnibus and the Cancer Genome Atlas databases, which could be divided into three distinct CRGclusters. Patients in CRGcluster C would have higher survival probability (P = 0.007), and higher levels of tumor microenvironment (TME) cell infiltration than other CRGclusters. CRG score was calculated via the results of univariate, multivariate cox analysis and least absolute shrinkage and selection operator regression analysis. Patients were divided into two risk subgroups according to the median risk score. Low-risk patients exhibited a more favorable prognosis, higher immunogenicity, and greater immunotherapy efficacy. Besides, CRG scores were strongly correlated to copy number variation, immunophenoscore, tumor mutation load, cancer stem cell index, microsatellite instability, and chemosensitivity. The c-index of our model is 0.702, which is higher than other four published model. The results proved that our model can distinguish EC patients with high-risk and low-risk and accurately predict the prognosis of EC patients. It will provide new ideas for clinical prognosis and precise treatments.
10.1016/j.compbiomed.2022.105988
Cuproptosis-related long non-coding RNAs model that effectively predicts prognosis in hepatocellular carcinoma.
World journal of gastrointestinal oncology
BACKGROUND:Cuproptosis has recently been considered a novel form of programmed cell death. To date, long-chain non-coding RNAs (lncRNAs) crucial to the regulation of this process remain unelucidated. AIM:To identify lncRNAs linked to cuproptosis in order to estimate patients' prognoses for hepatocellular carcinoma (HCC). METHODS:Using RNA sequence data from The Cancer Genome Atlas Live Hepatocellular Carcinoma (TCGA-LIHC), a co-expression network of cuproptosis-related genes and lncRNAs was constructed. For HCC prognosis, we developed a cuproptosis-related lncRNA signature (CupRLSig) using univariate Cox, lasso, and multivariate Cox regression analyses. Kaplan-Meier analysis was used to compare overall survival among high- and low-risk groups stratified by median CupRLSig risk score. Furthermore, comparisons of functional annotation, immune infiltration, somatic mutation, tumor mutation burden (TMB), and pharmacologic options were made between high- and low-risk groups. RESULTS:Three hundred and forty-three patients with complete follow-up data were recruited in the analysis. Pearson correlation analysis identified 157 cuproptosis-related lncRNAs related to 14 cuproptosis genes. Next, we divided the TCGA-LIHC sample into a training set and a validation set. In univariate Cox regression analysis, 27 LncRNAs with prognostic value were identified in the training set. After lasso regression, the multivariate Cox regression model determined the identified risk equation as follows: Risk score = (0.2659 × PICSAR expression) + (0.4374 × FOXD2-AS1 expression) + (-0.3467 × AP001065.1 expression). The CupRLSig high-risk group was associated with poor overall survival (hazard ratio = 1.162, 95%CI = 1.063-1.270; < 0.001) after the patients were divided into two groups depending upon their median risk score. Model accuracy was further supported by receiver operating characteristic and principal component analysis as well as the validation set. The area under the curve of 0.741 was found to be a better predictor of HCC prognosis as compared to other clinicopathological variables. Mutation analysis revealed that high-risk combinations with high TMB carried worse prognoses (median survival of 30 mo 102 mo of low-risk combinations with low TMB group). The low-risk group had more activated natural killer cells (NK cells, = 0.032 by Wilcoxon rank sum test) and fewer regulatory T cells (Tregs, = 0.021) infiltration than the high-risk group. This finding could explain why the low-risk group has a better prognosis. Interestingly, when checkpoint gene expression (CD276, CTLA-4, and PDCD-1) and tumor immune dysfunction and rejection (TIDE) scores are considered, high-risk patients may respond better to immunotherapy. Finally, most drugs commonly used in preclinical and clinical systemic therapy for HCC, such as 5-fluorouracil, gemcitabine, paclitaxel, imatinib, sunitinib, rapamycin, and XL-184 (cabozantinib), were found to be more efficacious in the low-risk group; erlotinib, an exception, was more efficacious in the high-risk group. CONCLUSION:The lncRNA signature, CupRLSig, constructed in this study is valuable in prognostic estimation of HCC. Importantly, CupRLSig also predicts the level of immune infiltration and potential efficacy of tumor immunotherapy.
10.4251/wjgo.v14.i10.1981
An integrative analysis revealing cuproptosis-related lncRNAs signature as a novel prognostic biomarker in hepatocellular carcinoma.
Frontiers in genetics
Cuproptosis is a newly defined form of cell death, whether cuproptosis involved in hepatocellular carcinoma (HCC) remains elusive. We obtained patients' RNA expression data and follow-up information from University of California Santa Cruz (UCSC) and The Cancer Genome Atlas (TCGA). We analyzed the mRNA level of Cuproptosis-related genes (CRGs) and performed univariate Cox analysis. Liver hepatocellular carcinoma (LIHC) was chosen for further investigation. Real-Time quantitative PCR (RT-qPCR), Western blotting (WB), Immunohistochemical (IHC), and Transwell assays were used to determine expression patterns and functions of CRGs in LIHC. Next, we identified CRGs-related lncRNAs (CRLs) and differentially expressed CRLs between HCC and normal cases. Univariate Cox analysis, least absolute shrinkage selection operator (LASSO) analysis and Cox regression analysis were used to construct the prognostic model. Univariate and multivariate Cox analysis was used to assess whether the risk model can act as an independent risk factor of overall survival duration. Different risk groups performed immune correlation analysis, tumor mutation burden (TMB), and Gene Set Enrichment Analysis (GSEA) analysis were performed in different risk groups. Finally, we assessed the performance of the predictive model in drug sensitivity. CRGs expression levels have significant differences between tumor and normal tissues. High expression of Dihydrolipoamide S-Acetyltransferase () correlated to metastasis of HCC cells and indicated poor prognosis for HCC patients. Our prognostic model consisted of four cuproptosis-related lncRNA (AC011476.3, AC026412.3, NRAV, MKLN1-AS). The prognostic model performed well in predicting survival rates. The results from Cox regression analysis suggested that risk score can serve as an independent prognostic element for survival durations. Survival analysis revealed that low risk patients have extended survival periods compared with those with high risk. The results of the immune analysis indicated that risk score has a positive correlation with B cell and CD4 T cell Th2, while has a negative relationship with endothelial cell and hematopoietic cells. Besides, immune checkpoint genes have higher expression folds in the high-risk set than in the low-risk set. The high-risk group had higher rates of genetic mutation than the low-risk set while having a shorter survival time. GSEA revealed the signaling pathways enriched in the high-risk group were mostly immune-related, while metabolic-related pathways were enriched in the low-risk group. Drugs sensitivity analysis indicated that our model has the ability to predict the efficacy of clinical treatment. The Cuproptosis-related lncRNAs prognostic formula is a novel predictor of HCC patients' prognosis and drug sensitivity.
10.3389/fgene.2023.1056000
Prognostic and Immunological Significance of the Molecular Subtypes and Risk Signatures Based on Cuproptosis in Hepatocellular Carcinoma.
Mediators of inflammation
Background:Hepatocellular carcinoma (HCC) remains a challenging medical problem. Cuproptosis is a novel form of cell death that plays a crucial role in tumorigenesis, angiogenesis, and metastasis. However, it remains unclear whether cuproptosis-related genes (CRGs) influence the outcomes and immune microenvironment of HCC patients. Method:From The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases, we obtained the mRNA expression file and related clinical information of HCC patients. We selected 19 CRGs as candidate genes for this study according to previous literature. We performed a differential expression analysis of the 19 CRGs between malignant and precancerous tissue. Based on the 19 CRGs, we enrolled cluster analysis to identify cuproptosis-related subtypes of HCC patients. A prognostic risk signature was created utilizing univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses. We employed independent and stratification survival analyses to investigate the predictive value of this model. The functional enrichment features, mutation signatures, immune profile, and response to immunotherapy of HCC patients were also investigated according to the two molecular subtypes and the prognostic signature. Results:We found that 17 CRGs significantly differed in HCC versus normal samples. Cluster analysis showed two distinct molecular subtypes of cuproptosis. Cluster 1 is preferentially related to poor prognosis, high activity of immune response signaling, high mutant frequency of , and distinct immune cell infiltration versus cluster 2. Through univariate and LASSO Cox regression analyses, we created a cuproptosis-related prognostic risk signature containing , , , , and . High-risk HCC patients were shown to have a worse prognosis. The risk signature was proved to be an independent predictor of prognosis in both the TCGA and ICGC datasets, according to multivariate analysis. The signature also performed well in different stratification of clinical features. The immune cells, which included regulatory T cells (Treg), B cells, macrophages, mast cells, NK cells, and aDCs, as well as immune functions containing cytolytic activity, MHC class I, and type II IFN response, were remarkably distinct between the high-risk and low-risk groups. The tumor immune dysfunction and exclusion (TIDE) score suggested that high-risk patients had a higher response rate to immune checkpoint inhibitors than low-risk patients. Conclusion:This research discovered the potential prognostic and immunological significance of cuproptosis in HCC, improved the understanding of cuproptosis, and may deliver new directions for developing more efficacious therapeutic techniques for HCC patients.
10.1155/2023/3951940
Comprehensive analysis of cuproptosis-related lncRNAs in the prognosis and therapy response of patients with bladder cancer.
Annals of translational medicine
Background:Cuproptosis is the recently defined regulatory cell death (RCD) that plays essential roles in tumorigenesis and progression. Long noncoding RNAs (lncRNAs) regulate the gene expression through various means. However, the clinical value of cuproptosis-related lncRNAs in bladder cancer (BLCA) remains poorly described. Methods:We downloaded the transcriptome sequencing data and clinical information from The Cancer Genome Atlas (TCGA) database. Univariate, multivariate, and lasso Cox regression analyses were performed to construct the prognostic risk signature, the predictive accuracy of which was validated in the subsequent independence and stratification analyses. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were used to explore the underlying molecular mechanisms involved in the signature to explore therapeutic vulnerabilities and potential targets in BLCA. Tumor mutational burden (TMB) and tumor immune dysfunction and exclusion (TIDE) were used to estimate the response to immune checkpoint inhibitors (ICIs). We further explored the potential new drug-target candidates based on the half maximal inhibitory concentration for this patient population. Results:Fifteen cuproptosis-related lncRNAs significantly associated with survival were identified to construct the risk signature based on the normalized expression level and regression coefficient of each gene. The patients with BLCA and high-risk scores defined by the signature were associated with worse survival outcomes. The differentially expressed genes (DEGs) between the 2 risk groups had different biological activity. Furthermore, the patients in the low-risk group exhibited a higher TMB index and a lower TIDE score. The sensitivity of multiple antitumor drugs was negatively related to risk score, including AR-42, AS605240, FK866, TAK-715, and tubastatin A, while the sensitivity of some antitumor drugs, such as AMG-706, BX-795, and RO-3306, were positively correlated with risk score. Conclusions:Our study established and verified a novel clinical risk signature with cuproptosis-related lncRNAs that may predict therapy response and prognosis with robust and stable accuracy in patients with BLCA and enhance the personalized management of this patient population.
10.21037/atm-22-5294
Developing four cuproptosis-related lncRNAs signature to predict prognosis and immune activity in ovarian cancer.
Journal of ovarian research
BACKGROUND:There has been a recent discovery of a new type of cell death produced by copper-iron ions, called Cuproptosis (copper death). The purpose of this study was to identify LncRNA signatures associated with Cuproptosis in ovarian cancer that could be used as prognostic indicators. METHODS:RNA sequencing (RNA-seq) profiles with clinicopathological data from TCGA database were used to select prognostic CRLs and then constructed prognostic risk model using multivariate regression analysis and LASSO algorithms. An independent dataset from GEO database was used to validate the prognostic performance. Combined with clinical factors, we further constructed a prognostic nomogram. In addition, tumor immune microenvironment, somatic mutation and drug sensitivity were analyzed using ssGSEA, GSVA, ESTIMATE and CIBERSORT algorithms. RESULT:A total of 129 CRLs were selected whose expression levels were significantly related to expression levels of 10 cuproptosis-related genes. The univariate Cox regression analysis showed that 12 CRLs were associated with overall survival (OS). Using LASSO algorithms and multivariate regression analysis, we constructed a four-CRLs prognostic signature in the training dataset. Patients in the training dataset could be classified into high- or low-risk subgroups with significantly different OS (log-rank p < 0.001). The prognostic performance was confirmed in TCGA-OC cohort (log-rank p < 0.001) and an independent GEO cohort (log-rank p = 0.023). Multivariate cox regression analysis proved the four-CRLs signature was an independent prognostic factor for OC. Additionally, different risk subtypes showed significantly different levels of immune cells, signal pathways, and drug response. CONCLUSION:We established a prognostic signature based on cuproptosis-related lncRNAs for OC patients, which will be of great value in predicting the prognosis patients and may provide a new perspective for research and individualized treatment.
10.1186/s13048-023-01165-7
Cuproptosis engages in c-Myc-mediated breast cancer stemness.
Journal of translational medicine
BACKGROUND:Intra-tumoral heterogeneity (ITH) is a distinguished hallmark of cancer, and cancer stem cells (CSCs) contribute to this malignant characteristic. Therefore, it is of great significance to investigate and even target the regulatory factors driving intra-tumoral stemness. c-Myc is a vital oncogene frequently overexpressed or amplified in various cancer types, including breast cancer. Our previous study indicated its potential association with breast cancer stem cell (BCSC) biomarkers. METHODS:In this research, we performed immunohistochemical (IHC) staining on sixty breast cancer surgical specimens for c-Myc, CD44, CD24, CD133 and ALDH1A1. Then, we analyzed transcriptomic atlas of 1533 patients with breast cancer from public database. RESULTS:IHC staining indicated the positive correlation between c-Myc and BCSC phenotype. Then, we used bioinformatic analysis to interrogate transcriptomics data of 1533 breast cancer specimens and identified an intriguing link among c-Myc, cancer stemness and copper-induced cell death (also known as "cuproptosis"). We screened out cuproptosis-related characteristics that predicts poor clinical outcomes and found that the pro-tumoral cuproptosis-based features were putatively enriched in MYC-targets and showed a significantly positive correlation with cancer stemness. CONCLUSION:In addition to previous reports on its oncogenic roles, c-Myc showed significant correlation to stemness phenotype and copper-induced cell toxicity in breast cancer tissues. Moreover, transcriptomics data demonstrated that pro-tumoral cuproptosis biomarkers had putative positive association with cancer stemness. This research combined clinical samples with large-scale bioinformatic analysis, covered description and deduction, bridged classic oncogenic mechanisms to innovative opportunities, and inspired the development of copper-based nanomaterials in targeting highly heterogeneous tumors.
10.1186/s12967-023-04204-5
Identification of cuproptosis and immune-related gene prognostic signature in lung adenocarcinoma.
Frontiers in immunology
Background:Cuproptosis is a novel form of programmed cell death that differs from other types such as pyroptosis, ferroptosis, and autophagy. It is a promising new target for cancer therapy. Additionally, immune-related genes play a crucial role in cancer progression and patient prognosis. Therefore, our study aimed to create a survival prediction model for lung adenocarcinoma patients based on cuproptosis and immune-related genes. This model can be utilized to enhance personalized treatment for patients. Methods:RNA sequencing (RNA-seq) data of lung adenocarcinoma (LUAD) patients were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The levels of immune cell infiltration in the GSE68465 cohort were determined using gene set variation analysis (GSVA), and immune-related genes (IRGs) were identified using weighted gene coexpression network analysis (WGCNA). Additionally, cuproptosis-related genes (CRGs) were identified using unsupervised clustering. Univariate COX regression analysis and least absolute shrinkage selection operator (LASSO) regression analysis were performed to develop a risk prognostic model for cuproptosis and immune-related genes (CIRGs), which was subsequently validated. Various algorithms were utilized to explore the relationship between risk scores and immune infiltration levels, and model genes were analyzed based on single-cell sequencing. Finally, the expression of signature genes was confirmed through quantitative real-time PCR (qRT-PCR), immunohistochemistry (IHC), and Western blotting (WB). Results:We have identified 5 Oncogenic Driver Genes namely CD79B, PEBP1, PTK2B, STXBP1, and ZNF671, and developed proportional hazards regression models. The results of the study indicate significantly reduced survival rates in both the training and validation sets among the high-risk group. Additionally, the high-risk group displayed lower levels of immune cell infiltration and expression of immune checkpoint compared to the low-risk group.
10.3389/fimmu.2023.1179742
The cuproptosis-associated 13 gene signature as a robust predictor for outcome and response to immune- and targeted-therapies in clear cell renal cell carcinoma.
Frontiers in immunology
Cuproptosis, the newly identified form of regulatory cell death (RCD), results from mitochondrial proteotoxic stress mediated by copper and FDX1. Little is known about significances of cuproptosis in oncogenesis. Here we determined clinical implications of cuproptosis in clear cell renal cell carcinoma (ccRCC). Based on the correlation and survival analyses of cuproptosis-correlated genes in TCGA ccRCC cohort, we constructed a cuproptosis-associated 13 gene signature (CuAGS-13) score system. In both TCGA training and two validation cohorts, when patients were categorized into high- and low-risk groups according to a median score as the cutoff, the CuAGS-13 high-risk group was significantly associated with shorter overall survival (OS) and/or progression-free survival (PFS) independently (<0.001 for all). The CuAGS-13 score assessment could also predict recurrence and recurrence-free survival of patients at stage I - III with a high accuracy, which outperformed the ccAccB/ClearCode34 model, a well-established molecular predictor for ccRCC prognosis. Moreover, patients treated with immune checkpoint inhibitors (ICIs) acquired complete/partial remissions up to 3-time higher coupled with significantly longer PFS in the CuAGS-13 low- than high-risk groups in both training and validation cohorts of ccRCCs (7.2 - 14.1 2.1 - 3.0 months, <0.001). The combination of ICI with anti-angiogenic agent Bevacizumab doubled remission rates in CuAGS-13 high-risk patients while did not improve the efficacy in the low-risk group. Further analyses showed a positive correlation between CuAGS-13 and TIDE scores. We also observed that the CuAGS-13 score assessment accurately predicted patient response to Sunitinib, and higher remission rates in the low-risk group led to longer PFS (Low- high-risk, 13.9 5.8 months, = 5.0e-12). Taken together, the CuAGS-13 score assessment serves as a robust predictor for survival, recurrence, and response to ICIs, ICI plus anti-angiogenic drugs and Sunitinib in ccRCC patients, which significantly improves patient stratifications for precision medicine of ccRCC.
10.3389/fimmu.2022.971142
Prognostic prediction of head and neck squamous cell carcinoma: Construction of cuproptosis-related long non-coding RNA signature.
Journal of clinical laboratory analysis
BACKGROUND:Recently, a new type of programmed cell death, cuproptosis, has been identified to play important role in the progression of tumors. We constructed a cuproptosis-related long non-coding RNA (lncRNA) signature to predict the prognostic significance for head and neck squamous cell carcinoma (HNSCC). METHODS:The risk model was developed based on differentially expressed lncRNAs associated with cuproptosis. Principal component analysis was used to assess the validity. The Kaplan-Meier curves were analyzed to compare the overall survival (OS), disease-specific survival (DSS), and progression-free survival (PFS) values. The multivariate and univariate Cox regression analyses were used to evaluate the prognostic efficiency. Furthermore, the functional enrichment, immune cell infiltration, tumor mutation burden (TMB), and sensitivity toward chemotherapy were also explored. RESULTS:Six cuproptosis-related lncRNAs (AL109936.2, CDKN2A-DT, AC090587.1, KLF3-AS1, AL133395.1, and LINC01063) were identified to construct the independent prognostic predictor for HNSCC. The area under the curve and C-index values obtained using the risk model were higher than the values corresponding to the clinical factors. Analysis of Kaplan-Meier curves indicated that the OS, PFS, and DSS time recorded for the patients in the low-risk group were higher than the corresponding values recorded for the patients belonging to the high-risk group. By functional enrichment analysis, we observed that differentially expressed genes were enriched in the immune response and tumor-associated pathways. The patients characterized by a low-risk score exhibited better immune cell infiltration than the patients belonging to the other group. We also observed that the sensitivity of the individuals belonging to the low-risk group to chemotherapeutic agents (cisplatin, docetaxel, and paclitaxel) was higher than the sensitivity of those in the other group. CONCLUSIONS:A cuproptosis-related lncRNA-based signature that functioned as an independent prognosis predictor for HNSCC patients was constructed. The chemosensitivity of individual patients can be potentially predicted using this signature.
10.1002/jcla.24723
Development and experimental verification of a prognosis model for cuproptosis-related subtypes in HCC.
Hepatology international
BACKGROUND:Cuproptosis is a recently discovered mechanism of programmed cell death caused by intracellular aggregation of mitochondrial lipoylated proteins and destabilization of iron-sulfur proteins triggered by copper. Hepatocellular carcinoma (HCC) is a common malignant tumor with a poor prognosis. We aimed to predict the survival of patients with HCC using the cuproptosis-related gene (CRG) expression. METHODS:We analyzed the expression, methylation, and mutation status of CRGs in 538 HCC patients and correlated the date with clinical prognosis. HCC patients were divided into two clusters based on their CRG expression. The relationship between CRGs, risk genes, and the immune microenvironment was analyzed using the CIBERSORT algorithm and the single-cell data analysis method. A cuproptosis risk model was constructed according to the five risk genes using the LASSO COX method. To facilitate the clinical applicability of the proposed risk model, we constructed a nomogram and conducted an antineoplastic drug sensitivity analysis. RESULTS:Our results suggest that the expression levels of CRGs in HCC are regulated by methylation. The prognoses were significantly different between the patients of the two clusters. The prognostic risk score positively correlated with memory T cell activation and negatively correlated with natural killer (NK) and regulatory T cell activation. CONCLUSION:Our findings indicate the involvement of CRG regulation in HCC and provide new insights into prognosis assessment. Drug sensitivity analysis predicted drug candidates for the treatment of patients with different HCC subtypes.
10.1007/s12072-022-10381-0
Comprehensive bioinformatics analysis to identify a novel cuproptosis-related prognostic signature and its ceRNA regulatory axis and candidate traditional Chinese medicine active ingredients in lung adenocarcinoma.
Frontiers in pharmacology
Lung adenocarcinoma (LUAD) is the most ordinary histological subtype of lung cancer, and regulatory cell death is an attractive target for cancer therapy. Recent reports suggested that cuproptosis is a novel copper-dependent modulated form of cell death dependent on mitochondrial respiration. However, the role of cuproptosis-related genes (CRGs) in the LUAD process is unclear. In the current study, we found that DLD, LIAS, PDHB, DLAT and LIPA1 in 10 differentially expressed CRGs were central genes. GO and KEGG enrichment results showed that these 10 CRGs were mainly enriched in acetyl-CoA biosynthetic process, mitochondrial matrix, citrate cycle (TCA cycle) and pyruvate metabolism. Furthermore, we constructed a prognostic gene signature model based on the six prognostic CRGs, which demonstrated good predictive potential. Excitedly, we found that these six prognostic CRGs were significantly associated with most immune cell types, with DLD being the most significant (19 types). Significant correlations were noted between some prognostic CRGs and tumor mutation burden and microsatellite instability. Clinical correlation analysis showed that DLD was related to the pathological stage, T stage, and M stage of patients with LUAD. Lastly, we constructed the lncRNA UCA1/miR-1-3p/DLD axis that may play a key role in the progression of LUAD and screened nine active components of traditional Chinese medicine (TCM) that may regulate DLD. Further, cell experiments and molecular docking were used to verify this. In conclusion, we analyzed the potential value of CRGs in the progression of LUAD, constructed the potential regulatory axis of ceRNA, and obtained the targeted regulatory TCM active ingredients through comprehensive bioinformatics combined with experimental validation strategies. This work not only provides new insights into the treatment of LUAD but also includes a basis for the development of new immunotherapy drugs that target cuproptosis.
10.3389/fphar.2022.971867
Machine learning screening for Parkinson's disease-related cuproptosis-related typing development and validation and exploration of personalized drugs for cuproptosis genes.
Annals of translational medicine
Background:Parkinson's disease (PD) is a common, degenerative disease of the nervous system that is characterized by the death of dopaminergic neurons in the substantia nigra densa (SNpc). There is growing evidence that copper (Cu) is involved in myelin formation and is involved in cell death through modulation of synaptic activity as well as neurotrophic factor-induced excitotoxicity. Methods:This study aimed to explore potential cuproptosis-related genes (CRGs) and immune infiltration patterns in PD and the development of Cu chelators relevant for PD treatment. The PD datasets GSE7621, GSE20141, and GSE49036 were downloaded from the Gene Expression Omnibus (GEO) database. The consensus clustering method was used to classify the specimens of PD. Using weighted gene co-expression network analysis (WGCNA) and random forest (RF) tree model, support vector machine (SVM) learning model, extreme gradient boosting (XGBoost) model, and general linear model (GLM) algorithms to screen disease progression-related models, the column charts were created to verify the accuracy of these CRGs in predicting PD progression. Single sample genomic enrichment analysis (ssGSEA) was used to estimate the correlation between genes associated with copper poisoning and genes associated with immune cells and immune function. Molecular docking was used to verify interactions with copper chelating agents associated with cuproptosis for PD treatment. Results:Through ssGSEA, we identified three copper poisoning related genes , and , which are related to immune cells in PD. We also verified that LAGASCATRIOL can bind to through molecular docking. Consistent cluster analysis identified two subtypes, among which C2 subtype was just enriched in PD. And to more accurately diagnose PD progression, patients can benefit from a feature map based on these genes. Conclusions:CRGs such as , , and were identified to be associated with the pathogenesis of PD and provide a possible new direction for the treatment of PD, which needs further in-depth study.
10.21037/atm-22-5756
Comprehensive analysis of cuproptosis-related prognostic gene signature and tumor immune microenvironment in HCC.
Frontiers in genetics
Copper is an indispensable mineral element involved in many physiological metabolic processes. Cuproptosis is associated with a variety of cancer such as hepatocellular carcinoma (HCC). The objective of this study was to examine the relationships between the expression of cuproptosis-related genes (CRGs) and tumor characteristics, including prognosis and microenvironment of HCC. The differentially expressed genes (DEGs) between high and low CRGs expression groups in HCC samples were identified, and further were analyzed for functional enrichment analysis. Then, CRGs signature of HCC was constructed and analyzed utilizing LASSO and univariate and multivariate Cox regression analysis. Prognostic values of CRGs signature were evaluated by Kaplan-Meier analysis, independent prognostic analysis and nomograph. The expression of prognostic CRGs was verified by Real-time quantitative PCR (RT-qPCR) in HCC cell lines. In addition, the relationships between prognostic CRGs expression and the immune infiltration, tumor microenvironment, antitumor drugs response and m6A modifications were further explored using a series of algorithms in HCC. Finally, ceRNA regulatory network based on prognostic CRGs was constructed. The DEGs between high and low CRG expression groups in HCC were mainly enriched in focal adhesion and extracellular matrix organization. Besides, we constructed a prognostic model that consists of CDKN2A, DLAT, DLST, GLS, and PDHA1 CRGs for predicting the survival likelihood of HCC patients. And the elevated expression of these five prognostic CRGs was substantially in HCC cell lines and associated with poor prognosis. Moreover, immune score and m6A gene expression were higher in the high CRG expression group of HCC patients. Furthermore, prognostic CRGs have higher mutation rates in HCC, and are significantly correlated with immune cell infiltration, tumor mutational burden, microsatellite instability, and anti-tumor drug sensitivity. Then, eight lncRNA-miRNA-mRNA regulatory axes that affected the progression of HCC were predicted. This study demonstrated that the CRGs signature could effectively evaluate prognosis, tumor immune microenvironment, immunotherapy response and predict lncRNA-miRNA-mRNA regulatory axes in HCC. These findings extend our knowledge of cuproptosis in HCC and may inform novel therapeutic strategies for HCC.
10.3389/fgene.2023.1094793
Identification of cuproptosis-related lncRNAs to predict prognosis and immune infiltration characteristics in alimentary tract malignancies.
BMC bioinformatics
BACKGROUND:Alimentary tract malignancies (ATM) caused nearly one-third of all tumor-related death. Cuproptosis is a newly identified cell death pattern. The role of cuproptosis-associated lncRNAs in ATM is unknown. METHOD:Data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were used to identify prognostic lncRNAs by Cox regression and LASSO. Then a predictive nomogram was constructed based on seven prognostic lncRNAs. In addition, the prognostic potential of the seven-lncRNA signature was verified via survival analysis, the receiver operating characteristic (ROC) curve, calibration curve, and clinicopathologic characteristics correlation analysis. Furthermore, we explored the associations between the signature risk score and immune landscape, and somatic gene mutation. RESULTS:We identified 1211 cuproptosis-related lncRNAs and seven survival-related lncRNAs. Patients were categorized into high-risk and low-risk groups with significantly different prognoses. ROC and calibration curve confirmed the good prediction capability of the risk model and nomogram. Somatic mutations between the two groups were compared. We also found that patients in the two groups responded differently to immune checkpoint inhibitors and immunotherapy. CONCLUSION:The proposed novel seven lncRNAs nomogram could predict prognosis and guide treatment of ATM. Further research was required to validate the nomogram.
10.1186/s12859-023-05314-z
MUC20 regulated by extrachromosomal circular DNA attenuates proteasome inhibitor resistance of multiple myeloma by modulating cuproptosis.
Journal of experimental & clinical cancer research : CR
BACKGROUND:Proteasome inhibitors (PIs) are one of the most important classes of drugs for the treatment of multiple myeloma (MM). However, almost all patients with MM develop PI resistance, resulting in therapeutic failure. Therefore, the mechanisms underlying PI resistance in MM require further investigation. METHODS:We used several MM cell lines to establish PI-resistant MM cell lines. We performed RNA microarray and EccDNA-seq in MM cell lines and collected human primary MM samples to explore gene profiles. We evaluated the effect of MUC20 on cuproptosis of PI-resistant MM cells using Co-immunoprecipitation (Co-IP), Seahorse bioenergetic profiling and in vivo assay. RESULTS:This study revealed that the downregulation of Mucin 20 (MUC20) could predict PI sensitivity and outcomes in MM patients. Besides, MUC20 attenuated PI resistance in MM cells by inducing cuproptosis via the inhibition of cyclin-dependent kinase inhibitor 2 A expression (CDKN2A), which was achieved by hindering MET proto-oncogene, receptor tyrosine kinase (MET) activation. Moreover, MUC20 suppressed MET activation by repressing insulin-like growth factor receptor-1 (IGF-1R) lactylation in PI-resistant MM cells. This study is the first to perform extrachromosomal circular DNA (eccDNA) sequencing for MM, and it revealed that eccDNA induced PI resistance by amplifying kinesin family member 3 C (KIF3C) to reduce MUC20 expression in MM. CONCLUSION:Our findings indicated that MUC20 regulated by eccDNA alleviates PI resistance of MM by modulating cuproptosis, which would provide novel strategies for the treatment of PI-resistant MM.
10.1186/s13046-024-02972-6
Identification of cuproptosis-related subtypes and characterization of the tumor microenvironment landscape in head and neck squamous cell carcinoma.
Journal of clinical laboratory analysis
BACKGROUND:Cuproptosis is considered a novel copper-dependent cell death model. In this study, we established a novel scoring system based on 10 cuproptosis-related genes (CRGs) to predict the prognosis and immune landscape of head and neck squamous cell carcinoma (HNSCC). METHODS:The RNA-seq data of HNSCC patients were downloaded from the GEO and TCGA databases and were merged into a novel HNSCC cohort. Multiomics landscape analyses were conducted, including tumor mutation burden (TMB), copy number variations and the interaction network of CRGs. Patients were then divided into different cuproptosis subtypes based on the expression of 10 CRGs and subsequently regrouped into novel gene clusters referring to differentially expressed genes. A cuproptosis score (CS) system was established using principal component analysis. The CIBERSORT, ssGSEA and ESTIMATE algorithms were used to assess the tumor immune microenvironment. Moreover, the immunotherapeutic and chemotherapeutic responses were assessed. RESULTS:Patients were divided into three cuproptosis subtypes and subsequently regrouped into three gene clusters, reflecting different immune infiltration. Assessed by the CS system, those with higher CSs exhibited worse prognosis and higher TMB frequency. Nevertheless, the immune-related analysis revealed patients in the low-CS group appeared immunosuppressive and easily suffered from immune escape. High CSs possibly show high expression of immune checkpoint genes and enhance chemotherapy sensitivity to cisplatin, docetaxel, and gemcitabine. CONCLUSION:We established a novel scoring system to predict the prognosis and immune landscape of HNSCC patients. This signature exhibits satisfactory predictive effects and the potential to guide comprehensive treatment for patients.
10.1002/jcla.24638
Characterization of chromatin regulators identified prognosis and heterogeneity in hepatocellular carcinoma.
Frontiers in oncology
Liver carcinogenesis is a multiprocess that involves complicated interactions between genetics, epigenetics, and transcriptomic alterations. Aberrant chromatin regulator (CR) expressions, which are vital regulatory epigenetics, have been found to be associated with multiple biological processes. Nevertheless, the impression of CRs on tumor microenvironment remodeling and hepatocellular carcinoma (HCC) prognosis remains obscure. Thus, this study aimed to systematically analyze CR-related patterns and their correlation with genomic features, metabolism, cuproptosis activity, and clinicopathological features of patients with HCC in The Cancer Genome Atlas, International Cancer Genome Consortium-LIRI-JP cohort, and GSE14520 that utilized unsupervised consensus clustering. Three CR-related patterns were recognized, and the CRs phenotype-related gene signature (CRsscore) was developed using the least absolute shrinkage and selection operator-Cox regression and multivariate Cox algorithms to represent the individual CR-related pattern. Additionally, the CRsscore was an independent prognostic index that served as a fine predictor for energy metabolism and cuproptosis activity in HCC. Accordingly, describing a wide landscape of CR characteristics may assist us to illustrate the sealed association between epigenetics, energy metabolism, and cuproptosis activity. This study may discern new tumor therapeutic targets and exploit personalized therapy for patients.
10.3389/fonc.2022.1002781
Prognostic and immune correlation evaluation of a novel cuproptosis-related genes signature in hepatocellular carcinoma.
Frontiers in pharmacology
Hepatocellular carcinoma (HCC) is one of the world's malignant tumors with high morbidity and mortality. Cuproptosis is a novel form of cell death. However, the prognostic evaluation and immune relevance of cuproptosis-related genes (CRGs) in HCC are largely unknown. In our study, we constructed a prognostic model of CRGs in HCC and performed immune infiltration, functional analysis, immune checkpoint and drug sensitivity analysis. Systematically elaborated the prognostic and immune correlation of CRGs in HCC. The results showed that 15 CRGs were up-regulated or down-regulated in HCC, and the mutation frequency of CRGs reached 10.33% in HCC, with CDKN2A having the highest mutation frequency. These 19 CRGs were mainly involved in the mitochondrion, immune response and metabolic pathways. Five selected genes (CDKN2A, DLAT, DLST, GLS, PDHA1) were involved in constructing a prognostic CRGs model that enables the overall survival in HCC patients to be predicted with moderate to high accuracy. Prognostic CRGs, especially CDKN2A, the independent factor of HCC prognosis, may be closely associated with immune-cell infiltration, tumor mutation burden (TMB), microsatellite instability(MSI), and immune checkpoints. CD274, CTLA4, LAG3, PDCD1, PDCD1LG2 and SIGLEC15 may be identified as potential therapeutic targets and CD274 correlated highly with prognostic genes. Quantitative Real-Time PCR (qRT-PCR) and immunohistochemical were performed to validate the mRNA and protein expression levels of CDKN2A in adjacent normal tissues and HCC tissues, and the results were consistent with gene difference analysis. In conclusion, CRGs, especially CDKN2A, may serve as potential prognostic predictors in HCC patients and provide novel insights into cancer therapy.
10.3389/fphar.2022.1074123
Cuproptosis-Inducible Chemotherapeutic/Cascade Catalytic Reactor System for Combating with Breast Cancer.
Small (Weinheim an der Bergstrasse, Germany)
Cascade hydroxyl radical generating hydrogel reactor structures including a chemotherapeutic agent are invented for multiple treatment of breast cancer. Glucose oxidase (GOx) and cupric sulfate (Cu) are introduced for transforming accumulated glucose (in cancer cells) to hydroxyl radicals for starvation/chemodynamic therapy. Cu may also suppress cancer cell growth via cuproptosis-mediated cell death. Berberine hydrochloride (BER) is engaged as a chemotherapeutic agent in the hydrogel reactor for combining with starvation/chemodynamic/cuproptosis therapeutic modalities. Moreover, Cu is participated as a gel crosslinker by coordinating with catechol groups in hyaluronic acid-dopamine (HD) polymer. Controlling viscoelasticity of hydrogel reactor can extend the retention time following local injection and provide sustained drug release patterns. Low biodegradation rate of designed HD/BER/GOx/Cu hydrogel can reduce dosing frequency in local cancer therapy and avoid invasiveness-related inconveniences. Especially, it is anticipated that HD/BER/GOx/Cu hydrogel system can be applied for reducing size of breast cancer prior to surgery as well as tumor growth suppression in clinical application.
10.1002/smll.202301402
Ferroptosis, Pyroptosis, and Cuproptosis in Alzheimer's Disease.
ACS chemical neuroscience
Alzheimer's disease (AD), the most common type of dementia, is a neurodegenerative disorder characterized by progressive cognitive dysfunction. Epidemiological investigation has demonstrated that, after cardiovascular and cerebrovascular diseases, tumors, and other causes, AD has become a major health issue affecting elderly individuals, with its mortality rate acutely increasing each year. Regulatory cell death is the active and orderly death of genetically determined cells, which is ubiquitous in the development of living organisms and is crucial to the regulation of life homeostasis. With extensive research on regulatory cell death in AD, increasing evidence has revealed that ferroptosis, pyroptosis, and cuproptosis are closely related to the occurrence, development, and prognosis of AD. This paper will review the molecular mechanisms of ferroptosis, pyroptosis, and cuproptosis and their regulatory roles in AD to explore potential therapeutic targets for the treatment of AD.
10.1021/acschemneuro.3c00343
Multi-omics analysis reveals cuproptosis and mitochondria-based signature for assessing prognosis and immune landscape in osteosarcoma.
Frontiers in immunology
Background:Osteosarcoma (OSA), the most common primary mesenchymal bone tumor, is a health threat to children and adolescents with a dismal prognosis. While cuproptosis and mitochondria dysfunction have been demonstrated to exert a crucial role in tumor progression and development, the mechanisms by which they are regulated in OSA still await clarification. Methods:Two independent OSA cohorts containing transcriptome data and clinical information were collected from public databases. The heterogeneity of OSA were evaluated by single cell RNA (scRNA) analysis. To identify a newly molecular subtype, unsupervised consensus clustering was conducted. Cox relevant regression methods were utilized to establish a prognostic gene signature. Wet lab experiments were performed to confirm the effect of model gene in OSA cells. Results:We determined 30 distinct cell clusters and assessed OSA heterogeneity and stemness scRNA analysis. Then, univariate Cox analysis identified 24 candidate genes which were greatly associated with the prognosis of OSA. Based on these prognostic genes, we obtained two molecular subgroups. After conducting step Cox regression, three model genes were selected to construct a signature showing a favorable performance to forecast clinical outcome. Our proposed signature could also evaluate the response to chemotherapy and immunotherapy of OSA cases. Conclusion:We generated a novel risk model based on cuproptosis and mitochondria-related genes in OSA with powerful predictive ability in prognosis and immune landscape.
10.3389/fimmu.2023.1280945
A Novel Cuproptosis-Related Prognostic Gene Signature and Validation of Differential Expression in Clear Cell Renal Cell Carcinoma.
Genes
Clear cell renal cell carcinoma (ccRCC) is the most prevalent subtype of renal cell carcinoma, which is characterized by metabolic reprogramming. Cuproptosis, a novel form of cell death, is highly linked to mitochondrial metabolism and mediated by protein lipoylation. However, the clinical impacts of cuproptosis-related genes (CRGs) in ccRCC largely remain unclear. In the current study, we systematically evaluated the genetic alterations of cuproptosis-related genes in ccRCC. Our results revealed that CDKN2A, DLAT, DLD, FDX1, GLS, PDHA1 and PDHB exhibited differential expression between ccRCC and normal tissues (|log2(fold change)| > 2/3 and p < 0.05). Utilizing an iterative sure independence screening (SIS) method, we separately constructed the prognostic signature of CRGs for predicting the overall survival (OS) and progression-free survival (PFS) in ccRCC patients. The prognostic score of CRGs yielded an area under the curve (AUC) of 0.658 and 0.682 for the prediction of 5-year OS and PFS, respectively. In the Kaplan−Meier survival analysis of OS, a higher risk score of cuproptosis-related gene signature was significantly correlated with worse overall survival (HR = 2.72 (2.01−3.68), log-rank p = 1.76 × 10−7). Patients with a higher risk had a significantly shorter PFS (HR = 2.83 (2.08−3.85), log-rank p = 3.66 × 10−7). Two independent validation datasets (GSE40435 (N = 101), GSE53757 (N = 72)) were collected for meta-analysis, suggesting that CDKN2A (log2(fold change) = 1.46, 95%CI: 1.75−2.35) showed significantly higher expression in ccRCC tissues while DLAT (log2(fold change) = −0.54, 95%CI: −0.93−−0.15) and FDX1 (log2(fold change) = −1.01, 95%CI: −1.61−−0.42) were lowly expressed. The expression of CDKN2A and FDX1 in ccRCC was also significantly associated with immune infiltration levels and programmed cell death protein 1 (PD-1) expression (CDKN2A: r = 0.24, p = 2.14 × 10−8; FDX1: r = −0.17, p = 1.37 × 10−4). In conclusion, the cuproptosis-related gene signature could serve as a potential prognostic predictor for ccRCC patients and may offer novel insights into the cancer treatment.
10.3390/genes13050851
[Cuproptosis-related lncRNAs to predict biochemical recurrence of prostate cancer].
Zhonghua nan ke xue = National journal of andrology
OBJECTIVE:To construct a cuproptosis-related lncRNA model and obtain some new ideas and methods for predicting the biochemical recurrence (BCR) of PCa. METHODS:We identified cuproptosis-related lncRNAs from the gene expression data, mutation load data and clinical data on PCa patients in the Cancer Genome Atlas (TCGA) database and divided the patients into a training group and a verification group. We constructed a prognostic risk scoring model based on the cuproptosis -related lncRNAs, verified the validity of the model by BCR-free survival analysis, logistic regression analysis and independent prognosis analysis, and visualized the results using ROC curve analysis, Kaplan-Meier survival curves and the correlation heat map. We performed differential analysis and survival analysis of the tumor mutation burden (TMB), and assessed the value of the model and TMB in predicting the BCR of PCa. RESULTS:A prognostic risk scoring model was successfully constructed based on the 6 cuproptosis -related lncRNAs identified from the PCa cases in the training group, which were divided into a high- and a low-risk groups according to the median value. The incidence of BCR rose with the increase of the risk score, and the BCR-free time was significantly shorter in the high-risk group (P < 0.05). The model also exhibited a high differentiation value in different age groups (P < 0.05), which was shown to be a reliable and independent prognostic indicator for predicting the BCR of PCa, even more valuable than other clinicopathological indicators. TMB was differentially expressed in the high- and low-risk groups (P < 0.01) and significantly correlated with BCR. The highest rate of BCR-free survival was found in the patients with low risk scores and low TMB (P < 0.01). CONCLUSION:A cuproptosis -related lncRNA model was successfully constructed, which can accurately predict the risk of BCR in PCa patients. The higher the prognostic risk score, the greater the possibility of BCR. TMB is high in patients with a high risk, and the TMB level has certain suggestive significance for BCR.
Prognostic, Clinicopathological, and Function of Key Cuproptosis Regulator in Clear Cell Renal Cell Carcinoma.
Genes
Clear cell renal cell carcinoma (ccRCC) is the most common histological subtype of renal cancer. Cuproptosis is suggested to be a novel therapy target for cancer treatment. However, the function of cuproptosis and its key regulator FDX1 in ccRCC remains unclear. In this study, we adequately explored the prognostic factors, clinicopathological characteristics, and function of FDX1 in ccRCC. We found that the expression of FDX1 was significantly downregulated in ccRCC samples. Patients with a higher FDX1 expression had a significantly better prognosis, including overall survival (OS) (Hazard ratio (HR): 2.54, 95% confidence interval (CI): 1.82−3.53, p < 0.001), disease-specific survival (DSS) (HR: 3.04, 95% CI: 2.04−4.54, p < 0.001), and progression-free survival (PFS) (HR: 2.54, 95% CI: 1.82−3.53, p < 0.001). FDX1 was a clinical predictor to stratify patients into the high or low risk of poor survival, independent of conventional clinical features, with the area under the ROC curve (AUC) of 0.658, 0.677, and 0.656 for predicting the 5-year OS, DSS, and PFS. The nomogram model based on FDX1 had greater predictive power than other individual prognostic parameters. FDX1 mainly participated in the oxidative-related process and mitochondrial respiration-related processes but was not associated with immune infiltration levels. In conclusion, the cuproptosis key regulator FDX1 could serve as a potential novel prognostic biomarker for ccRCC patients.
10.3390/genes13101725
A novel cuproptosis-related gene model predicts outcomes and treatment responses in pancreatic adenocarcinoma.
BMC cancer
BACKGROUND:Cuproptosis is recently emerging as a hot spot in cancer research. However, its role in pancreatic adenocarcinoma (PAAD) has not yet been clarified. This study aimed to explore the prognostic and therapeutic implications of cuproptosis-related genes in PAAD. METHODS:Two hundred thirteen PAAD samples from the International Cancer Genome Consortium (ICGC) were split into training and validation sets in the ratio of 7:3. The Cox regression analyses generated a prognostic model using the ICGC cohort for training (n = 152) and validation (n = 61). The model was externally tested on the Gene Expression Omnibus (GEO) (n = 80) and The Cancer Genome Atlas (TCGA) datasets (n = 176). The clinical characteristics, molecular mechanisms, immune landscape, and treatment responses in model-defined subgroups were explored. The expression of an independent prognostic gene TSC22D2 was confirmed by public databases, real-time quantitative PCR (RT-qPCR), western blot (WB), and immunohistochemistry (IHC). RESULTS:A prognostic model was established based on three cuproptosis-related genes (TSC22D2, C6orf136, PRKDC). Patients were stratified into high- and low-risk groups using the risk score based on this model. PAAD patients in the high-risk group had a worse prognosis. The risk score was statistically significantly correlated with most clinicopathological characteristics. The risk score based on this model was an independent predictor of overall survival (OS) (HR = 10.7, p < 0.001), and was utilized to create a scoring nomogram with excellent prognostic value. High-risk patients had a higher TP53 mutation rate and a superior response to multiple targeted therapies and chemotherapeutic drugs, but might obtain fewer benefits from immunotherapy. Moreover, elevated TSC22D2 expression was discovered to be an independent prognostic predictor for OS (p < 0.001). Data from public databases and our own experiments showed that TSC22D2 expression was significantly higher in pancreatic cancer tissues/cells compared to normal tissues/cells. CONCLUSION:This novel model based on cuproptosis-related genes provided a robust biomarker for predicting the prognosis and treatment responses of PAAD. The potential roles and underlying mechanisms of TSC22D2 in PAAD need further explored.
10.1186/s12885-023-10678-9
Analysis of cuproptosis-related genes in Ulcerative colitis and immunological characterization based on machine learning.
Frontiers in medicine
Cuproptosis is a novel form of cell death, mediated by protein lipid acylation and highly associated with mitochondrial metabolism, which is regulated in the cell. Ulcerative colitis (UC) is a chronic inflammatory bowel disease that recurs frequently, and its incidence is increasing worldwide every year. Currently, a growing number of studies have shown that cuproptosis-related genes (CRGs) play a crucial role in the development and progression of a variety of tumors. However, the regulatory role of CRGs in UC has not been fully elucidated. Firstly, we identified differentially expressed genes in UC, Likewise, CRGs expression profiles and immunological profiles were evaluated. Using 75 UC samples, we typed UC based on the expression profiles of CRGs, followed by correlative immune cell infiltration analysis. Using the weighted gene co-expression network analysis (WGCNA) methodology, the cluster's differentially expressed genes (DEGs) were produced. Then, the performances of extreme gradient boosting models (XGB), support vector machine models (SVM), random forest models (RF), and generalized linear models (GLM) were constructed and predicted. Finally, the effectiveness of the best machine learning model was evaluated using five external datasets, receiver operating characteristic curve (ROC), the area under the curve of ROC (AUC), a calibration curve, a nomogram, and a decision curve analysis (DCA). A total of 13 CRGs were identified as significantly different in UC and control samples. Two subtypes were identified in UC based on CRGs expression profiles. Immune cell infiltration analysis of subtypes showed significant differences between immune cells of different subtypes. WGCNA results showed a total of 8 modules with significant differences between subtypes, with the turquoise module being the most specific. The machine learning results showed satisfactory performance of the XGB model (AUC = 0.981). Finally, the construction of the final 5-gene-based XGB model, validated by the calibration curve, nomogram, decision curve analysis, and five external datasets (GSE11223: AUC = 0.987; GSE38713: AUC = 0.815; GSE53306: AUC = 0.946; GSE94648: AUC = 0.809; GSE87466: AUC = 0.981), also proved to predict subtypes of UC with accuracy. Our research presents a trustworthy model that can predict the likelihood of developing UC and methodically outlines the complex relationship between CRGs and UC.
10.3389/fmed.2023.1115500
Cuproptosis-related gene signatures for predicting prognosis of lung adenocarcinoma.
Medicine
Lung cancer (LC) is a common malignancy with high mortality rate, and lung adenocarcinoma (LUAD) is one of the common pathological types. Cuproptosis is a recently discovered new type of cell death dependent on mitochondria. However, the role of cuproptosis in LUAD is unknown. We obtained LUAD transcriptome data from the Cancer Genome Atlas (TCGA). Long-stranded non-coding RNA (LncRNAs) based on cuproptosis prognosis associated with LUAD were constructed for prognostic multi-LncRNA characterization. We divided TCGA-LUAD into training set and validation set to prove feasibility, and all samples were divided into high-risk group or low risk group. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used to evaluate potential biological functions and explore the relationship between risk models and immunity. We identified 3 differentially expressed LncRNAs associated with LUAD prognosis and constructed prognostic model. Kaplan-Meier (K-M) analysis revealed prognostic model and LUAD prognosis. Our risk assessment model has a good reliability in predicting the prognosis of LUAD and was able to improve predictive ability of tumor mutational burdern. Single sample gene enrichment analysis (ssGSEA) revealed risk subgroups were associated with immune-related functions. The prognostic model based on cuproptosis lncRNA has important value in predicting the survival of LUAD patients.
10.1097/MD.0000000000030446
Cuproptosis-related gene CDKN2A as a molecular target for IPF diagnosis and therapeutics.
Inflammation research : official journal of the European Histamine Research Society ... [et al.]
BACKGROUND:Idiopathic pulmonary fibrosis (IPF) is a progressive chronic interstitial lung disease with limited therapeutic options. Cuproptosis is a recently proposed novel form of programmed cell death, which has been strongly implicated in the development of various human diseases. However, the prognostic and therapeutic value of cuproptosis-related genes (CRGs) in IPF remains to be elucidated. METHODS:In the present study, weighted gene co-expression network analysis (WGCNA) was employed to identify the key CRGs associated with the development of IPF. The subsequent GSEA, immune cell correlation analysis, and single-cell RNA-Seq analysis were conducted to explore the potential role of the identified CRGs in IPF. In addition, ROC curves and survival analysis were used to assess the prognostic value of the key CRGs in IPF. Moreover, we explored the molecular mechanisms of participation of identified key CRGs in the development of pulmonary fibrogenesis through in vivo and in vitro experiments. RESULTS:The expression level of cyclin-dependent kinase inhibitor 2A (CDKN2A) is upregulated in the lung tissues of IPF patients and associated with disease severity. Notably, CDKN2A was constitutively expressed by fibrosis-promoting M2 macrophages. Decreased CDKN2A expression sensitizes M2 macrophages to elesclomol-induced cuproptosis in vitro. Inhibition of CDKN2A decreases the number of viable macrophages and attenuates bleomycin-induced pulmonary fibrosis in mice. CONCLUSION:These findings indicate that CDKN2A mediates the resistance of fibrosis-promoting M2 macrophages to cuproptosis and promotes pulmonary fibrosis in mice. Our work provides fresh insights into CRGs in IPF with potential value for research in the pathogenesis, diagnosis, and a new therapy strategy for IPF.
10.1007/s00011-023-01739-7
The activity of cuproptosis pathway calculated by AUCell algorithm was employed to construct cuproptosis landscape in lung adenocarcinoma.
Discover. Oncology
Cuproptosis is a recently described copper-dependent cell death pathway. Consequently, there are still few studies on lung adenocarcinoma (LUAD)-related cuproptosis, and we aimed to deepen in this matter. In this study, data from 503 patients with lung cancer from the TCGA-LUAD cohort data collection and 11 LUAD single-cells from GSE131907 as well as from 10 genes associated with cuproptosis were analyzed. The AUCell R package was used to determine the copper-dependent cell death pathway activity for each cell subpopulation, calculate the CellChat score, and display cell communication for each cell subpopulation. The PROGENy score was calculated to show the scores of tumor-related pathways in different cell populations. GO and KEGG analyses were used to calculate pathway activity. Univariate COX and random forest analyses were used to screen prognosis-associated genes and construct models. The ssGSEA and xCell algorithms were used to calculate the immunocyte infiltration score. Based on data from the GDSC database, the drug sensitivity score was calculated using oncoPredict. Finally, in vitro experiments were performed to determine the role of TLE1, the most important gene in the prognostic model. The 11 LUAD single-cell samples were classified into 8 different cell populations, from which epithelial cells showed the highest copper-dependent cell death pathway activity. Epithelial cell subsets were significantly positively correlated with MAKP, hypoxia, and other pathways. In addition, cell subgroup communication showed highly active collagen and APP pathways. Using the Findmark algorithm, differentially expressed genes (DEGs) between epithelial and other cell types were identified. Combined with the bulk data in the TCGA-LUAD database, DEGs were enriched in pathways such as EGFR tyrosine kinase inhibitor resistance, Hippo signaling pathway, and tight junction. Subsequently, we selected 4 genes (out of 112) with prognostic significance, ANKRD29, RHOV, TLE1, and NPAS2, and used them to construct a prognostic model. The high- and low-risk groups, distinguished by the median risk score, showed significantly different prognoses. Finally, we chose TLE1 as a biomarker based on the relative importance score in the prognostic model. In vitro experiments showed that TLE1 promotes tumor proliferation and migration and inhibits apoptosis.
10.1007/s12672-023-00755-7
Prognostic value of cuproptosis-related genes signature and its impact on the reshaped immune microenvironment of glioma.
Frontiers in pharmacology
Glioma is the most prevalent malignancy in the central nervous system. The impact of ion-induced cell death on malignant tumors' development and immune microenvironment has attracted broad attention in recent years. Cuproptosis is a novel copper-dependent mechanism that could potentially regulate tumor cell death by targeting mitochondria respiration. However, the role of cuproptosis in gliomas remains unclear. In the present study, we investigated the relationships between the expression of cuproptosis-related genes (CRGs) and tumor characteristics, including prognosis and microenvironment of glioma, by analyzing multiple public databases and our cohort. Consensus clustering based on the expression of twelve CRGs stratified the glioma patients into three subgroups with significantly different prognosis and immune microenvironment landscapes. Reduced immune infiltration was associated with the less aggressive CRG cluster. A prognostic CRGs risk signature (CRGRS), based on eight critical CRGs, classified the patients into low- and high-risk groups in the training set and was endorsed by validation sets from multiple cohorts. The high-risk group manifested a shorter overall survival, and further survival analysis demonstrated that the CRGRS was an independent prognostic factor. The nomogram combining CRGRS and other clinicopathological factors exhibited good accuracy in predicting the prognosis of glioma patients. Moreover, analyses of tumor immune microenvironment indicated that higher CRGRS was correlated with increased immune cell infiltration but diminished immune function. Gliomas in the high-risk group exhibited higher expression of multiple immune checkpoints, including PD-1 and PD-L1, and a better predicted therapy response to immune checkpoint inhibitors. In conclusion, our study elucidated the connections between CRGs expression and the aggressiveness of gliomas, and the application of CRGRS derived a new robust model for prognosis evaluation of glioma patients. The correlations between the profiles of CRGs expression and immune tumor microenvironment illuminated prospects and potential indications of immunotherapy for glioma.
10.3389/fphar.2022.1016520
Brain-Targeted HFn-Cu-REGO Nanoplatform for Site-Specific Delivery and Manipulation of Autophagy and Cuproptosis in Glioblastoma.
Small (Weinheim an der Bergstrasse, Germany)
Durable glioblastoma multiforme (GBM) management requires long-term chemotherapy after surgery to eliminate remaining cancerous tissues. Among chemotherapeutics, temozolomide is considered as the first-line drug for GBM therapy, but the treatment outcome is not satisfactory. Notably, regorafenib, an oral multi-kinase inhibitor, has been reported to exert a markedly superior effect on GBM suppression compared with temozolomide. However, poor site-specific delivery and bioavailability significantly restrict the efficient permeability of regorafenib to brain lesions and compromise its treatment efficacy. Therefore, human H-ferritin (HFn), regorafenib, and Cu are rationally designed as a brain-targeted nanoplatform (HFn-Cu-REGO NPs), fulfilling the task of site-specific delivery and manipulating autophagy and cuproptosis against GBM. Herein, HFn affords a preferential accumulation capacity to GBM due to transferrin receptor 1 (TfR1)-mediated active targeting and pH-responsive delivery behavior. Moreover, regorafenib can inhibit autophagosome-lysosome fusion, resulting in lethal autophagy arrest in GBM cells. Furthermore, Cu not only facilitates the encapsulation of regorafenib to HFn through coordination interaction but also disturbs copper homeostasis for triggering cuproptosis, resulting in a synergistical effect with regorafenib-mediated lethal autophagy arrest against GBM. Therefore, this work may broaden the clinical application scope of Cu and regorafenib in GBM treatment via modulating autophagy and cuproptosis.
10.1002/smll.202205354
A novel prognostic signature of cuproptosis-related genes and the prognostic value of FDX1 in gliomas.
Frontiers in genetics
Gliomas are the most common malignant tumors of the central nervous system, with extremely bad prognoses. Cuproptosis is a novel form of regulated cell death. The impact of cuproptosis-related genes on glioma development has not been reported. The TCGA, GTEx, and CGGA databases were used to retrieve transcriptomic expression data. We employed Cox's regressions to determine the associations between clinical factors and cuproptosis-related gene expression. Overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) were evaluated using the Kaplan-Meier method. We also used the least absolute shrinkage and selection operator (LASSO) regression technique. The expression levels of all 10 CRGs varied considerably between glioma tumors and healthy tissues. In glioma patients, the levels of CDKN2A, FDX1, DLD, DLAT, LIAS, LIPT1, and PDHA1 were significantly associated with the OS, disease-specific survival, and progression-free interval. We used LASSO Cox's regression to create a prognostic model; the risk score was (0.882340) *FDX1 expression + (0.141089) *DLD expression + (-0.333875) *LIAS expression + (0.356469) *LIPT1 expression + (-0.123851) *PDHA1 expression. A high-risk score/signature was associated with poor OS (hazard ratio = 3.50, 95% confidence interval 2, -4.55, log-rank < 0.001). Cox's regression revealed that the FDX1 level independently predicted prognosis; FDX1 may control immune cell infiltration of the tumor microenvironment. The CRG signature may be prognostic in glioma patients, and the FDX1 level may independently predict glioma prognosis. These data may afford new insights into treatment.
10.3389/fgene.2022.992995
Construction of a risk model and prediction of prognosis and immunotherapy based on cuproptosis-related LncRNAs in the urinary system pan-cancer.
European journal of medical research
BACKGROUND:Urinary pan-cancer system is a general term for tumors of the urinary system including renal cell carcinoma (RCC), prostate cancer (PRAD), and bladder cancer (BLCA). Their location, physiological functions, and metabolism are closely related, making the occurrence and outcome of these tumors highly similar. Cuproptosis is a new type of cell death that is different from apoptosis and plays an essential role in tumors. Therefore, it is necessary to study the molecular mechanism of cuproptosis-related lncRNAs to urinary system pan-cancer for the prognosis, clinical diagnosis, and treatment of urinary tumors. METHOD:In our study, we identified 35 co-expression cuproptosis-related lncRNAs (CRLs) from the urinary pan-cancer system. 28 CRLs were identified as prognostic-related CRLs by univariate Cox regression analysis. Then 12 CRLs were obtained using lasso regression and multivariate cox analysis to construct a prognostic model. We divided patients into high- and low-risk groups based on the median risk scores. Next, Kaplan-Meier analysis, principal component analysis (PCA), functional rich annotations, and nomogram were used to compare the differences between the high- and low-risk groups. Finally, the prediction of tumor immune dysfunction and rejection, gene mutation, and drug sensitivity were discussed. CONCLUSION:Finally, the candidate molecules of the urinary system pan-cancer were identified. This CRLs risk model may be promising for clinical prediction of prognosis and immunotherapy response in urinary system pan-cancer patients.
10.1186/s40001-023-01173-9
Cuproptosis related gene PDHB is identified as a biomarker inversely associated with the progression of clear cell renal cell carcinoma.
BMC cancer
BACKGROUND:Cuproptosis is a newly discovered programmed cell death dependent on mitochondrial respiratory disorder induced by copper overload. Pyruvate dehydrogenase E1 subunit beta (PDHB) is one of the cuproptosis genesand is a nuclear-encoded pyruvate dehydrogenase, which catalyzes the conversion of pyruvate to acetyl coenzyme A. However, the mechanism of PDHB in clear cell renal cell carcinoma (ccRCC) remains unclear. METHODS:We used data from TCGA and GEO to assess the expression of PDHB in normal and tumor tissues. We further analyzed the relationship between PDHB and somatic mutations and immune infiltration. Finally, we preliminarily explored the impact of PDHB on ccRCC. RESULTS:The expression level of PDHB was lower in tumor tissue compared with normal tissue. Meanwhile, the expression level of PDHB was also lower in high-grade tumors than low-grade tumors. PDHB is positively correlated with prognosis in ccRCC. Furthermore, PDHB may be associated with decreased risk of VHL, PBRM1 and KDM5C mutations. In 786-O cells, copper chloride could promote the expression of cuproptosis genes (DLAT, PDHB and FDX1) and inhibit cell growth. Last but not least, we found that PDHB could inhibit the proliferation and migration of ccRCC cells. CONCLUSION:Our results demonstrated that PDHB could inhibit the proliferation, migration and invasion in ccRCC cells, which might be a prognostic predictor of ccRCC. Targeting this molecular might provide a new therapeutic strategy for patients with advanced ccRCC.
10.1186/s12885-023-11324-0
Prognosis, Immune Microenvironment Infiltration and Immunotherapy Response in Clear Cell Renal Cell Carcinoma Based on Cuproptosis-related Immune Checkpoint Gene Signature.
Journal of Cancer
Immune checkpoint genes (ICGs), which are the cornerstone of immunotherapy, influence the incidence and progression of clear cell renal cell carcinoma (ccRCC). It is important to note that there is not much data in the literature to determine how cuproptosis and antitumor immunity are related. On the basis of The Cancer Genome Atlas ccRCC dataset (n=526), cuproptosis-related ICGs (CICGs) were used to identify distinct molecular subtypes. Using the Cox regression method, a risk signature was constructed and externally validated using the ICGC (n=91) and primary ccRCC subgroups of GSE22541 (n=24). The molecular and immune characteristics and efficacy of immunotherapy in the subgroups defined by the risk score were investigated. Four risk CICGs were verified through in vitro experiment. We identified two unique molecular subgroups with substantial prognostic differences based on 17 CICGs. The two subtypes clearly differ in terms of the tumor immune microenvironment (TME). A predictive risk signature (CD276, HLA-E, LGALS9, and TNFRSF18) was created and externally confirmed, and their expressions were validated by realtime PCR. The multivariate Cox regression analysis demonstrated that this signature could independently predict survival. Thus, a credible nomogram incorporating the signature, age, stage, and grade was constructed, and discrimination was confirmed using the C-index, calibration curve, and decision curve analyses. The underlying implications for immune checkpoint inhibitors, the landscape of the TME, and single-cell level localization are depicted. In addition, its accuracy in forecasting actual immunotherapeutic results has been proven (CheckMate025 and TCGA-SKCM cohorts). The sensitivity of the two risk groups to various drug-targeted therapy methods was analyzed. The data provided here provide the groundwork for creating customized therapeutic options for individuals with ccRCC. The findings also suggested that researching the cuproptosis-based pathway might improve ccRCC patient better prognosis, development of anti-tumor immunity, and therapeutic strategies for immunotherapy.
10.7150/jca.88467
Identification of a prognostic model using cuproptosis-related genes in uveal melanoma.
Frontiers in cell and developmental biology
The most common intraocular malignancy in adults remains uveal melanoma (UVM), and those with metastatic disease have a poor outlook. Proliferation, angiogenesis, and metastasis of tumor cells can be triggered by cuproptosis, affecting the survival of cancer patients. Nonetheless, cuproptosis-related genes (CRGs) have not been identified in UVM. In this study, we analyzed 10 CRGs in 80 patients with UVM in the Cancer Genome Atlas (TCGA) database regarding the alterations of the genes including copy number variation and methylation. We further constructed a prognostic gene model using these CRGs and built the risk score formula. Univariate and multivariate Cox regression was applied to validate the risk score as an independent prognostic factor. The prognostic model was validated using 63 UVM samples from the GSE22138 cohort, an independent validation data set. Based on the risk scores for 80 patients with UVM from TCGA, we categorized the patients into high- and low-risk groups. Differentially expressed genes (DEGs) between groups were enriched in allograft rejection, hypoxia, glycolysis, TNFα signaling NF-κB, and interferon-γ responses via Gene set enrichment analysis (GSEA). CD8 T cells and exhausted T cells were notably enriched in the high-risk group. In conclusion, the alteration of CRGs is related to patients with UVM, and the constructed CRG-related model may be helpful to predict the prognosis of such patients.
10.3389/fcell.2022.973073
Cuproptosis-related lncRNA signatures: Predicting prognosis and evaluating the tumor immune microenvironment in lung adenocarcinoma.
Frontiers in oncology
Background:Cuproptosis, a unique kind of cell death, has implications for cancer therapy, particularly lung adenocarcinoma (LUAD). Long non-coding RNAs (lncRNAs) have been demonstrated to influence cancer cell activity by binding to a wide variety of targets, including DNA, RNA, and proteins. Methods:Cuproptosis-related lncRNAs (CRlncRNAs) were utilized to build a risk model that classified patients into high-and low-risk groups. Based on the CRlncRNAs in the model, Consensus clustering analysis was used to classify LUAD patients into different subtypes. Next, we explored the differences in overall survival (OS), the tumor immune microenvironment (TIME), and the mutation landscape between different risk groups and molecular subtypes. Finally, the functions of LINC00592 were verified through experiments. Results:Patients in various risk categories and molecular subtypes showed statistically significant variations in terms of OS, immune cell infiltration, pathway activity, and mutation patterns. Cell experiments revealed that LINC00592 knockdown significantly reduced LUAD cell proliferation, invasion, and migration ability. Conclusion:The development of a trustworthy prediction model based on CRlncRNAs may significantly aid in the assessment of patient prognosis, molecular features, and therapeutic modalities and may eventually be used in clinical applications.
10.3389/fonc.2022.1088931
Cuproptosis-related gene expression is associated with immune infiltration and CD47/CD24 expression in glioblastoma, and a risk score based on these genes can predict the survival and prognosis of patients.
Frontiers in oncology
Introduction:Glioblastoma (GBM) is the most invasive type of glioma, is insensitive to radiotherapy and chemotherapy, and has high proliferation and invasive ability, with a 5-year survival rate of <5%. Cuproptosis-related genes (CRGs) have been successfully used to predict the prognosis of many types of tumors. However, the relationship between cuproptosis and GBM remains unclear. Methods:Here, we sought to identify CRGs in GBM and elucidate their role in the tumor immune microenvironment and prognosis. To that aim, changes in CRGs in The Cancer Genome Atlas (TCGA) transcriptional and Gene Expression Omnibus (GEO) datasets (GEO4290 and GEO15824) were characterized, and the expression patterns of these genes were analyzed. Results:A risk score based on CRG expression characteristics could predict the survival and prognosis of patients with GBM and was significantly associated with immune infiltration levels and the expression of CD47 and CD24, which are immune checkpoints of the "don't eat me "signal. Furthermore, we found that the CDKN2A gene may predict GBM sensitivity and resistance to drugs. Discussion:Our findings suggest that CRGs play a crucial role in GBM outcomes and provide new insights into CRG-related target drugs/molecules for cancer prevention and treatment.
10.3389/fonc.2023.1011476
EREG is the core onco-immunological biomarker of cuproptosis and mediates the cross-talk between VEGF and CD99 signaling in glioblastoma.
Journal of translational medicine
BACKGROUND:Glioma is the most prevalent primary tumor of the central nervous system. Glioblastoma multiforme (GBM) is the most malignant form of glioma with an extremely poor prognosis. A novel, regulated cell death form of copper-induced cell death called "cuproptosis" provides a new prospect for cancer treatment by regulating cuproptosis. METHODS:Data from bulk RNA sequencing (RNA-seq) analysis (The Cancer Genome Atlas cohort and Chinese Glioma Genome Atlas cohort) and single cell RNA-seq (scRNA-seq) analysis were integrated to reveal their relationships. A scoring system was constructed according to the cuproptosis-related gene expression, and core genes were experimentally verified using real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR), Western blot (WB), immunohistochemistry (IHC), and immunofluorescence (IF). Moreover, cell counting kit-8 (CCK8), colony formation, 5-ethynyl-2'-deoxyuridine (EdU) incorporation, transwell, and flow cytometry cell cycle were performed to evaluate cell proliferation, invasion, and migration. RESULTS:The Cuproptosis Activation Scoring (CuAS) Model has stable and independent prognostic efficacy, as verified by two CGGA datasets. Epiregulin (EREG), the gene of the model has the most contributions in the principal component analysis (PCA), is an onco-immunological gene that can affect immunity by influencing the expression of programmed death-ligand 1 (PD-L1) and mediate the process of cuproptosis by influencing the expression of ferredoxin 1 (FDX1). Single cell transcriptome analysis revealed that high CuAS GBM cells are found in vascular endothelial growth factor A (VEGFA) + malignant cells. Oligodendrocyte transcription factor 1 (OLIG1) + malignant is the original clone, and VEGF and CD99 are the differential pathways of specific cell communication between the high and low CuAS groups. This was also demonstrated by immunofluorescence in the tissue sections. Furthermore, CuAS has therapeutic potential for immunotherapy, and we predict that many drugs (methotrexate, NU7441, KU -0063794, GDC-0941, cabozantinib, and NVP-BEZ235) may be used in patients with high CuAS. CONCLUSION:EREG is the core onco-immunological biomarker of CuAS and modulates the cross-talk between VEGF and CD99 signaling in glioblastoma, and CuAS may provide support for immunotherapy and chemotherapy.
10.1186/s12967-023-03883-4
Cuproptosis-related risk score predicts prognosis and characterizes the tumor microenvironment in colon adenocarcinoma.
Frontiers in oncology
Introduction:Cuproptosis is a novel copper-dependent regulatory cell death (RCD), which is closely related to the occurrence and development of multiple cancers. However, the potential role of cuproptosis-related genes (CRGs) in the tumor microenvironment (TME) of colon adenocarcinoma (COAD) remains unclear. Methods:Transcriptome, somatic mutation, somatic copy number alteration and the corresponding clinicopathological data of COAD were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus database (GEO). Difference, survival and correlation analyses were conducted to evaluate the characteristics of CRGs in COAD patients. Consensus unsupervised clustering analysis of CRGs expression profile was used to classify patients into different cuproptosis molecular and gene subtypes. TME characteristics of different molecular subtypes were investigated by using Gene set variation analysis (GSVA) and single sample gene set enrichment analysis (ssGSEA). Next, CRG Risk scoring system was constructed by applying logistic least absolute shrinkage and selection operator (LASSO) cox regression analysis and multivariate cox analysis. Real-time quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry (IHC) were used to exam the expression of key Risk scoring genes. Results:Our study indicated that CRGs had relatively common genetic and transcriptional variations in COAD tissues. We identified three cuproptosis molecular subtypes and three gene subtypes based on CRGs expression profile and prognostic differentially expressed genes (DEGs) expression profile, and found that changes in multilayer CRGs were closely related to the clinical characteristics, overall survival (OS), different signaling pathways, and immune cell infiltration of TME. CRG Risk scoring system was constructed according to the expression of 7 key cuproptosis-related risk genes (GLS, NOX1, HOXC6, TNNT1, GLS, HOXC6 and PLA2G12B). RT-qPCR and IHC indicated that the expression of GLS, NOX1, HOXC6, TNNT1 and PLA2G12B were up-regulated in tumor tissues, compared with those in normal tissues, and all of GLS, HOXC6, NOX1 and PLA2G12B were closely related with patient survival. In addition, high CRG risk scores were significantly associated with high microsatellite instability (MSI-H), tumor mutation burden (TMB), cancer stem cell (CSC) indices, stromal and immune scores in TME, drug susceptibility, as well as patient survival. Finally, a highly accurate nomogram was constructed to promote the clinical application of the CRG Risk scoring system. Discussion:Our comprehensive analysis showed that CRGs were greatly associated with TME, clinicopathological characteristics, and prognosis of patient with COAD. These findings may promote our understanding of CRGs in COAD, providing new insights for physicians to predict prognosis and develop more precise and individualized therapy strategies.
10.3389/fonc.2023.1152681
Identification of a Novel Cuproptosis-Related Gene Signature for Prognostic Implication in Head and Neck Squamous Carcinomas.
Cancers
Head and neck squamous carcinoma (HNSC) is a frequent and deadly malignancy that is challenging to manage. The existing treatment options have considerable efficacy limitations. Hence, the identification of new therapeutic targets and the development of efficacious treatments are urgent needs. Cuproptosis, a non-apoptotic programmed cell death caused by excess copper, has only very recently been discovered. The present study investigated the prognostic importance of genes involved in cuproptosis through the mRNA expression data and related clinical information of HNSC patients downloaded from public databases. Our results revealed that many cuproptosis-related genes were differentially expressed between normal and HNSC tissues in the TCGA cohort. Moreover, 39 differentially expressed genes were associated with the prognosis of HNSC patients. Then, a 24-gene signature was identified in the TCGA cohort utilizing the LASSO Cox regression model. HNSC expression data used for validation were obtained from the GEO database. Consequently, we divided patients into high- and low-risk groups based on the 24-gene signature. Furthermore, we demonstrated that the high-risk group had a worse prognosis when compared to the low-risk group. Additionally, significant differences were found between the two groups in metabolic pathways, immune microenvironment, etc. In conclusion, we found a cuproptosis-related gene signature that can be used effectively to predict OS in HNSC patients. Thus, targeting cuproptosis might be an alternative and promising strategy for HNSC patients.
10.3390/cancers14163986
Identification and validation of cuproptosis-related genes for diagnosis and therapy in nonalcoholic fatty liver disease.
Molecular and cellular biochemistry
In recent years, nonalcoholic fatty liver disease (NAFLD) has become a more serious public health issue worldwide. This study strived to investigate the molecular mechanism of pathogenesis of NAFLD and explore promising diagnostic and therapeutic targets for NAFLD. Raw data from GSE130970 were downloaded from the Gene Expression Omnibus database. We used the dataset to analyze the expression levels of cuproptosis-related genes in NAFLD patients and healthy controls to identify the differentially expressed cuproptosis-related genes (DECRGs). The relationship and potential mechanism between DECRGs and clinicopathological factors were examined by enrichment analysis and two consensus clustering methods. We screened key DECRGs based on Random Forest (RF), and then verified the key DECRGs in NAFLD patients, high-fat diet (HFD)-fed mice, and palmitic acid-induced AML12 cells. ROC analysis showed good diagnostic function of DECRGs in normal and NAFLD liver tissue. Two consensus clusters indicated the important role of cuproptosis in the development of NAFLD. We screened for key DECRGs (DLD, DLAT) based on RF and found a close relationship between the DECRGs and clinicopathological factors. We collected clinical blood samples to verify the differences in gene expression levels by qPCR. In addition, we further verified the expression levels of DLD and DLAT in HFD mice and AML12 cells, which showed the same results. This study provides a novel perspective on the pathogenesis of NAFLD. We identified two cuproptosis-related genes that are closely related to NAFLD. These genes may play a significant role in the molecular pathogenesis of NAFLD, which may be useful to make progress in the diagnosis and treatment of NAFLD.
10.1007/s11010-024-04957-7
Identification and immunological role of cuproptosis in osteoporosis.
Heliyon
Background:osteoporosis is a skeletal disorder disease features low bone mass and poor bone architecture, which predisposes to increased risk of fracture. Copper death is a newly recognized form of cell death caused by excess copper ions, which presumably involve in various disease. Accordingly, we intended to investigate the molecular clusters related to the cuproptosis in osteoporosis and to construct a predictive model. Methods:we investigated the expression patterns of cuproptosis regulators and immune signatures in osteoporosis based on the GSE56815 dataset. Through analysis of 40 osteoporosis samples, we investigated molecular clustering on the basis of cuproptosis--related genes, together with the associated immune cell infiltration. The WGCNA algorithm was applied to detect cluster-specific differentially expressed genes. Afterwards, the optimum machine model was selected by calculating the performance of the support vector machine model, random forest model, eXtreme Gradient Boosting and generalized linear model. Nomogram, decision curve analysis, calibration curves, and the GSE7158 dataset was utilizing to confirm the prediction efficiency. Results:Differences between osteoporotic and non-osteoporotic controls confirm poorly adjusted copper death-related genes and triggered immune responses. In osteoporosis, two clusters of molecules in connection with copper death proliferation were outlined. The assessed levels of immune infiltration showed prominent heterogeneity between the different clusters. Cluster 2 was characterized by a raised immune score accompanied with relatively high levels of immune infiltration. The functional analysis we performed showed a close relationship between the different immune responses and specific differentially expressed genes in cluster 2. The random forest machine model showed the optimum discriminatory performance due to relatively low residuals and root mean square errors. Finally, a random forest model based on 5 genes was built, showing acceptable performance in an external validation dataset (AUC = 0.750). Calibration curve, Nomogram, and decision curve analyses also evinced fidelity in predicting subtypes of osteoporosis. Conclusion:Our study identifies the role of cuproptosis in OP and essentially illustrates the underlying molecular mechanisms that lead to OP heterogeneity.
10.1016/j.heliyon.2024.e26759
Machine learning-driven prognostic analysis of cuproptosis and disulfidptosis-related lncRNAs in clear cell renal cell carcinoma: a step towards precision oncology.
European journal of medical research
Cuproptosis and disulfidptosis, recently discovered mechanisms of cell death, have demonstrated that differential expression of key genes and long non-coding RNAs (lncRNAs) profoundly influences tumor development and affects their drug sensitivity. Clear cell renal cell carcinoma (ccRCC), the most common subtype of kidney cancer, presently lacks research utilizing cuproptosis and disulfidptosis-related lncRNAs (CDRLRs) as prognostic markers. In this study, we analyzed RNA-seq data, clinical information, and mutation data from The Cancer Genome Atlas (TCGA) on ccRCC and cross-referenced it with known cuproptosis and disulfidptosis-related genes (CDRGs). Using the LASSO machine learning algorithm, we identified four CDRLRs-ACVR2B-AS1, AC095055.1, AL161782.1, and MANEA-DT-that are strongly associated with prognosis and used them to construct a prognostic risk model. To verify the model's reliability and validate these four CDRLRs as significant prognostic factors, we performed dataset grouping validation, followed by RT-qPCR and external database validation for differential expression and prognosis of CDRLRs in ccRCC. Gene function and pathway analysis were conducted using Gene Ontology (GO) and Gene Set Enrichment Analysis (GSEA) for high- and low-risk groups. Additionally, we have analyzed the tumor mutation burden (TMB) and the immune microenvironment (TME), employing the oncoPredict and Immunophenoscore (IPS) algorithms to assess the sensitivity of diverse risk categories to targeted therapeutics and immunosuppressants. Our predominant objective is to refine prognostic predictions for patients with ccRCC and inform treatment decisions by conducting an exhaustive study on cuproptosis and disulfidptosis.
10.1186/s40001-024-01763-1
PDE3B regulates KRT6B and increases the sensitivity of bladder cancer cells to copper ionophores.
Naunyn-Schmiedeberg's archives of pharmacology
Cuproptosis is a new Cu-dependent programmed cell death manner that has shown regulatory functions in many tumor types, however, its mechanism in bladder cancer remains unclear. Here, we reveal that Phosphodiesterase 3B (PDE3B), a cuproptosis-associated gene, could reduce the invasion and migration of bladder cancer. PDE3B is downregulated in bladder cancer tissues, which is correlated with better prognosis. Conversely, overexpression of PDE3B in bladder cancer cell could significantly resist invasion and migration, which is consistent with the TCGA database results. Future study demonstrate the anti-cancer effect of PDE3B is mediated by Keratin 6B (KRT6B) which leads to the keratinization. Therefore, PDE3B can reduce KRT6B expression and inhibit the invasion and migration of bladder cancer. Meanwhile, increased expression of PDE3B was able to enhance the sensitivity of Cuproptosis drug thiram. This study show that PDE3B/KRT6B is a potential cancer therapeutic target and PDE3B activation is able to increase the sensitivity of bladder cancer cells to copper ionophores.
10.1007/s00210-023-02928-1
Paeoniflorin attenuates cuproptosis and ameliorates left ventricular remodeling after AMI in hypobaric hypoxia environments.
Journal of natural medicines
This study investigates the cardioprotective effects of Paeoniflorin (PF) on left ventricular remodeling following acute myocardial infarction (AMI) under conditions of hypobaric hypoxia. Left ventricular remodeling post-AMI plays a pivotal role in exacerbating heart failure, especially at high altitudes. Using a rat model of AMI, the study aimed to evaluate the cardioprotective potential of PF under hypobaric hypoxia. Ninety male rats were divided into four groups: sham-operated controls under normoxia/hypobaria, an AMI model group, and a PF treatment group. PF was administered for 4 weeks after AMI induction. Left ventricular function was assessed using cardiac magnetic resonance imaging. Biochemical assays of cuproptosis, oxidative stress, apoptosis, inflammation, and fibrosis were performed. Results demonstrated PF significantly improved left ventricular function and remodeling after AMI under hypobaric hypoxia. Mechanistically, PF decreased FDX1/DLAT expression and serum copper while increasing pyruvate. It also attenuated apoptosis, inflammation, and fibrosis by modulating Bcl-2, Bax, NLRP3, and oxidative stress markers. Thus, PF exhibits therapeutic potential for left ventricular remodeling post-AMI at high altitude by inhibiting cuproptosis, inflammation, apoptosis and fibrosis. Further studies are warranted to optimize dosage and duration and elucidate PF's mechanisms of action.
10.1007/s11418-024-01781-7
Copper and cuproptosis: new therapeutic approaches for Alzheimer's disease.
Frontiers in aging neuroscience
Copper (Cu) plays a crucial role as a trace element in various physiological processes in humans. Nonetheless, free copper ions accumulate in the brain over time, resulting in a range of pathological changes. Compelling evidence indicates that excessive free copper deposition contributes to cognitive decline in individuals with Alzheimer's disease (AD). Free copper levels in the serum and brain of AD patients are notably elevated, leading to reduced antioxidant defenses and mitochondrial dysfunction. Moreover, free copper accumulation triggers a specific form of cell death, namely copper-dependent cell death (cuproptosis). This article aimed to review the correlation between copper dysregulation and the pathogenesis of AD, along with the primary pathways regulating copper homoeostasis and copper-induced death in AD. Additionally, the efficacy and safety of natural and synthetic agents, including copper chelators, lipid peroxidation inhibitors, and antioxidants, were examined. These treatments can restore copper equilibrium and prevent copper-induced cell death in AD cases. Another aim of this review was to highlight the significance of copper dysregulation and promote the development of pharmaceutical interventions to address it.
10.3389/fnagi.2023.1300405
Exploration of the role of Cuproptosis genes and their related long non-coding RNA in clear cell renal cell carcinoma: a comprehensive bioinformatics study.
BMC cancer
Clear cell renal cell carcinoma is a common malignant tumor of the urinary system. The mechanism of its occurrence and development is unknown, and there is currently few effective comprehensive predictive markers for prognosis and treatment response. With the discovery of a new cell death process - cuproptosis drew the attention of researchers. We constructed a model for the prediction of clinical prognosis and immunotherapy response through integrative analysis of gene expression datasets from KIRC samples in The Cancer Genome Atlas (TCGA) database. During the course of the study, we found that cuproptosis genes are significantly differentially expressed between clear cell renal cell carcinoma samples and normal samples. Based on this, we put forward the prognostic model for cuproptosis gene related-long non-coding RNA. And through various statistic and external independent cohorts, we proved that the model is accurate and stable, worthy of clinical application and further exploration and validation.
10.1186/s12885-022-10278-z
A novel defined cuproptosis-related gene signature for predicting the prognosis of colon adenocarcinoma.
Frontiers in oncology
The prognosis of colon adenocarcinoma (COAD) needs to be improved. Cuproptosis is a recently discovered cell death caused by intracellular overload of copper ions. There have been no reports about the cuproptosis-related prognostic model in COAD. First, we screened 30 differentially expressed genes (DEGs) from patients with COAD using The Cancer Genome Atlas (TCGA) database. Gene Expression Omnibus (GEO) database was used as a validation set to establish a risk model of five cuproptosis-related genes (CKDN2A, SDHB, CCS, ULK1, and CMC1) by least absolute shrinkage and selection operator (LASSO) Cox regression analysis. In both TCGA and GEO cohorts, we could see that overall survival of COAD patients of the low-risk group was longer. Combined with the clinical characteristics, the risk score was found to be an independent prognostic factor. Furthermore, single-sample Gene Set Enrichment Analysis (ssGSEA) showed that the levels of Th1 and Treg immune cells changed both in TCGA and GEO databases. Finally, clinical samples were used to verify the mRNA and protein levels of five risk-model genes. In conclusion, this model could predict the prognosis of COAD patients, and the mechanism may be related to the changes in immune cells in the tumor microenvironment (TME).
10.3389/fonc.2022.927028
Deciphering the molecular classification of pediatric sepsis: integrating WGCNA and machine learning-based classification with immune signatures for the development of an advanced diagnostic model.
Frontiers in genetics
Pediatric sepsis (PS) is a life-threatening infection associated with high mortality rates, necessitating a deeper understanding of its underlying pathological mechanisms. Recently discovered programmed cell death induced by copper has been implicated in various medical conditions, but its potential involvement in PS remains largely unexplored. We first analyzed the expression patterns of cuproptosis-related genes (CRGs) and assessed the immune landscape of PS using the GSE66099 dataset. Subsequently, PS samples were isolated from the same dataset, and consensus clustering was performed based on differentially expressed CRGs. We applied weighted gene co-expression network analysis to identify hub genes associated with PS and cuproptosis. We observed aberrant expression of 27 CRGs and a specific immune landscape in PS samples. Our findings revealed that patients in the GSE66099 dataset could be categorized into two cuproptosis clusters, each characterized by unique immune landscapes and varying functional classifications or enriched pathways. Among the machine learning approaches, Extreme Gradient Boosting demonstrated optimal performance as a diagnostic model for PS. Our study provides valuable insights into the molecular mechanisms underlying PS, highlighting the involvement of cuproptosis-related genes and immune cell infiltration.
10.3389/fgene.2024.1294381
Revolutionizing breast cancer treatment: Harnessing the related mechanisms and drugs for regulated cell death (Review).
International journal of oncology
Breast cancer arises from the malignant transformation of mammary epithelial cells under the influence of various carcinogenic factors, leading to a gradual increase in its prevalence. This disease has become the leading cause of mortality among female malignancies, posing a significant threat to the health of women. The timely identification of breast cancer remains challenging, often resulting in diagnosis at the advanced stages of the disease. Conventional therapeutic approaches, such as surgical excision, chemotherapy and radiotherapy, exhibit limited efficacy in controlling the progression and metastasis of the disease. Regulated cell death (RCD), a process essential for physiological tissue cell renewal, occurs within the body independently of external influences. In the context of cancer, research on RCD primarily focuses on cuproptosis, ferroptosis and pyroptosis. Mounting evidence suggests a marked association between these specific forms of RCD, and the onset and progression of breast cancer. For example, a cuproptosis vector can effectively bind copper ions to induce cuproptosis in breast cancer cells, thereby hindering their proliferation. Additionally, the expression of ferroptosis‑related genes can enhance the sensitivity of breast cancer cells to chemotherapy. Likewise, pyroptosis‑related proteins not only participate in pyroptosis, but also regulate the tumor microenvironment, ultimately leading to the death of breast cancer cells. The present review discusses the unique regulatory mechanisms of cuproptosis, ferroptosis and pyroptosis in breast cancer, and the mechanisms through which they are affected by conventional cancer drugs. Furthermore, it provides a comprehensive overview of the significance of these forms of RCD in modulating the efficacy of chemotherapy and highlights their shared characteristics. This knowledge may provide novel avenues for both clinical interventions and fundamental research in the context of breast cancer.
10.3892/ijo.2024.5634
Integrated machine learning and bioinformatic analyses used to construct a copper-induced cell death-related classifier for prognosis and immunotherapeutic response of hepatocellular carcinoma patients.
Frontiers in pharmacology
Copper as phytonutrient has powerful activity against health diseases. A newly discovered mechanism of cell death that affects energy metabolism by copper ("cuproptosis") can induce multiple cuproptosis-related genes. Hepatocellular carcinoma (HCC) is a poorly prognosed widespread cancer having danger of advanced metastasis. Therefore, earlier diagnosis followed by the specific targeted therapy are required for improved prognosis. The work herein constructed scoring system built on ten cuproptosis-related genes (CRGs) to predict progression of tumor and metastasis more accurately and test patient reaction toward immunotherapy. A comprehensive assessment of cuproptosis patterns in HCC samples from two databases and a real-world cohort was performed on ten CRGs, that were linked to immune cell infiltration signatures of TME (tumor microenvironment). Risk signatures were created for quantifying effect of cuproptosis on HCC, and the effects of related genes on cellular function of HCC were investigated, in addition to the effects of immunotherapy and targeted therapy drugs. Two distinct cuproptosis-associated mutational patterns were identified, with distinct immune cell infiltration characteristics and survival likelihood. Studies have shown that assessment of cuproptosis-induced tumor mutational patterns can help predict tumor stage, phenotype, stromal activity, genetic diversity, and patient prognosis. High risk scores are characterized by lower survival and worse treatment with anti-PD-L1/CTAL4 immunotherapy and first-line targeted drugs. Cytological functional assays show that CDKN2A and GLS promote proliferation, migration and inhibit copper-dependent death of HCC cells. HCC patients with high-risk scores exhibit significant treatment disadvantage and survival rates. Cuproptosis plays a non-negligible role in the development of HCC. Quantifying cuproptosis-related designs of tumors will aid in phenotypic categorization, leading to efficient personalized and targeted therapeutics and precise prediction of prognosis and metastasis.
10.3389/fphar.2023.1188725
A novel Cuprotosis-related signature predicts the prognosis and selects personal treatments for melanoma based on bioinformatics analysis.
Frontiers in oncology
Background:Melanoma is a common and aggressive cutaneous malignancy characterized by poor prognosis and a high fatality rate. Recently, due to the application of Immune-checkpoint inhibitors (ICI) in melanoma treatment, melanoma patients' prognosis has been tremendously improved. However, the treatment effect varies quite differently from patient to patient. In this study, we aim to construct and validate a Cuproptosis-related risk model to improve outcome prediction of ICIs in melanoma and divide patients into subtypes with different Cuproptosis-related genes. Methods:Here, according to differentially expressed genes from four melanoma datasets in GEO (Gene Expression Omnibus), and one in TCGA (The Cancer Genome Atlas) database, a novel signature was developed through LASSO and Cox regression analysis. We used 781 melanoma samples to examine the molecular subtypes associated with Cuproptosis-related genes and studied the related gene mutation and TME cell infiltration. Patients with melanoma can be divided into at least three subtypes based on gene expression profile. Survival pan-cancer analysis was also conducted for melanoma patients. Results:The Cuproptosis risk score can predict tumor immunity, subtype, survival, and drug sensitivity for melanoma. And Cuproptosis-associated subtypes can help predict therapeutic outcomes. Conclusion:Cuproptosis risk score is a promising potential biomarker in cancer diagnosis, molecular subtypes determination, TME cell infiltration characteristics, and therapy response prediction in melanoma patients.
10.3389/fonc.2023.1108128
Construction and comprehensive analysis of a curoptosis-related lncRNA signature for predicting prognosis and immune response in cervical cancer.
Frontiers in genetics
Cuproptosis (copper-ion-dependent cell death) is an unprogrammed cell death, and intracellular copper accumulation, causing copper homeostasis imbalance and then leading to increased intracellular toxicity, which can affect the rate of cancer cell growth and proliferation. This study aimed to create a newly cuproptosis-related lncRNA signature that can be used to predict survival and immunotherapy in patients with cervical cancer, but also to predict prognosis in patients treated with radiotherapy and may play a role in predicting radiosensitivity. First of all, we found lncRNAs associated with cuproptosis between cervical cancer tumor tissues and normal tissues. By LASSO-Cox analysis, overlapping lncRNAs were then used to construct lncRNA signatures associated with cuproptosis, which can be used to predict the prognosis of patients, especially the prognosis of radiotherapy patients, ROC curves and PCA analysis based on cuprotosis-related lncRNA signature and clinical signatures were developed and demonstrated to have good predictive potential. In addition, differences in immune cell subset infiltration and differences in immune checkpoint expression between high-risk and low-risk score groups were analyzed, and we investigated the relationship between this signature and tumor mutation burden. In summary, we constructed a lncRNA prediction signature associated with cuproptosis. This has important clinical implications, including improving the predictive value of cervical cancer patients and providing a biomarker for cervical cancer.
10.3389/fgene.2023.1023613
Developing CuS for Predicting Aggressiveness and Prognosis in Lung Adenocarcinoma.
Genes
Cuproptosis is a newfound cell death form that depends on copper (Cu) ionophores to transport Cu into cancer cells. Studies on the relationship have covered most common cancer types and analyzed the links between cuproptosis-related genes (CRGs) and various aspects of tumor characteristics. In this study, we evaluated the role of cuproptosis in lung adenocarcinoma (LUAD) and constructed the cuproptosis-related score (CuS) to predict aggressiveness and prognosis in LUAD, so as to achieve precise treatment for patients. CuS had a better predictive performance than cuproptosis genes, possibly due to the synergy of SLC family genes, and patients with a high CuS had a poor prognosis. Functional enrichment analysis revealed the correlation between CuS and immune and mitochondrial pathways in multiple datasets. Furthermore, we predicted six potential drugs targeting high-CuS patients, including AZD3759, which is a targeted drug for LUAD. In conclusion, cuproptosis is involved in LUAD aggressiveness, and CuS can accurately predict the prognosis of patients. These findings provide a basis for precise treatment of patients with high CuS in LUAD.
10.3390/genes14051055
The potential value of cuprotosis in myocardial immune infiltration that occurs in pediatric congenital heart disease in response to surgery with cardiopulmonary bypass.
Immunity, inflammation and disease
BACKGROUND:Cardiopulmonary bypass may cause malfunction in the myocardium. Cuproptosis is a novel cell death aggregating mitochondrial proteins. However, the research on cardiopulmonary bypass-caused heart tissue injury in immune infiltration and cuproptosis is limited. METHOD:Immune infiltration, enrichment analysis, protein-protein interaction network, and medication prediction are applied to reanalysis differentially expressed genes and cuproptosis-related genes in gene expression omnibus data set GSE132176. RESULTS:Seven cuproptosis related genes (PDHA1, LIPT1, LIAS, DLST, DLD, DLAT, and DBT) and dendritic cells and Th1 cells are involved in heart tissue injury in response to surgery with cardiopulmonary bypass. CONCLUSIONS:Immune infiltration and cuproptosis are potential mechanisms by which cardiopulmonary bypass surgery may cause damage to heart tissue, which may be a new therapeutic target.
10.1002/iid3.795
Prognostic and metabolic characteristics of a novel cuproptosis-related signature in patients with hepatocellular carcinoma.
Heliyon
Cuproptosis is a novel discovered mode of programmed cell death. To identify the molecular regulatory patterns related to cuproptosis, this study was designed for exploring the correlation between cuproptosis-related genes (CRGs) and the prognosis, metabolism, and treatment of hepatocellular carcinoma (HCC). Cancer Genome Atlas (TCGA) database was used to screen 363 HCC samples, which were categorized into 2 clusters based on the expression of CRGs. Survival analysis demonstrated that overall survival (OS) was better in Cluster 1 than Cluster 2 which might to be relevant to differences in metabolic based on functional analysis. With LASSO regression analysis and univariate COX regression, 8 prognosis-related genes were screened, a differently expressed genes (DEGs) were then constructed (HCC patients' DEGs)-based signature. The signature's stability was also validated in the 2 independent cohorts and test cohorts (GSE14520, HCC dataset in PCAWG). The 1-year, 3-year, and 5-year area under the curve (AUC) were 0.756, 0.706, and 0.722, respectively. The signature could also well predict the response to chemotherapy, targeted and transcatheter arterial chemoembolization (TACE) by providing a risk score. Moreover, the correlation was uncovered by the research between the metabolism and risk score. In conclusion, a unique cuproptosis-related signature that be capable of predicting patients' prognosis with HCC, and offered valuable insights into chemotherapy, TACE and targeted therapies for these patients has been developed.
10.1016/j.heliyon.2023.e23686
Comprehensive bioinformatics analysis reveals the role of cuproptosis-related gene Ube2d3 in myocardial infarction.
Frontiers in immunology
Background:Myocardial infarction (MI) caused by severe coronary artery disease has high incidence and mortality rates, making its prevention and treatment a central and challenging aspect of clinical work for cardiovascular practitioners. Recently, researchers have turned their attention to a novel mechanism of cell death caused by Cu, cuproptosis. Methods:This study integrated data from three MI-related bulk datasets downloaded from the Gene Expression Omnibus (GEO) database, and identified 16 differentially expressed genes (DEGs) related to cuproptosis by taking intersection of the 6378 DEGs obtained by differential analysis with 49 cuproptosis-related genes. Four hub genes, Dbt, Dlat, Ube2d1 and Ube2d3, were screened out through random forest analysis and Lasso analysis. In the disease group, Dbt, Dlat, and Ube2d1 showed low expression, while Ube2d3 exhibited high expression. Results:Focusing on Ube2d3 for subsequent functional studies, we confirmed its high expression in the MI group through qRT-PCR and Western Blot detection after successful construction of a MI mouse model by left anterior descending (LAD) coronary artery ligation, and further clarified the correlation of cuproptosis with MI development by detecting the levels of cuproptosis-related proteins. Moreover, through experiments, Ube2d3 was confirmed to be highly expressed in oxygen-glucose deprivation (OGD)-treated cardiomyocytes AC16. In order to further clarify the role of Ube2d3, we knocked down Ube2d3 expression in OGD-treated AC16 cells, and confirmed Ube2d3's promoting role in the hypoxia damage of AC16 cells by inducing cuproptosis, as evidenced by the detection of MTT, TUNEL, LDH release and cuproptosis-related proteins. Conclusion:In summary, our findings indicate that Ube2d3 regulates cuproptosis to affect the progression of MI.
10.3389/fimmu.2024.1353111
Copper's dual role: unravelling the link between copper homeostasis, cuproptosis, and cardiovascular diseases.
Hypertension research : official journal of the Japanese Society of Hypertension
This graphic depicts the interplay between copper homeostasis and cuproptosis and their role in cardiovascular diseases. Copper is vital for cardiac mitochondrial function, while its dysregulation induces cuproptosis via Ferredoxin1 (FDX1) and lipoic acid synthase (LIAS). Cuproptosis is linked to myocardial ischemia/reperfusion injury, heart failure, atherosclerosis, and arrhythmias. Copper deficiency impacts atherosclerosis markers. Therapeutic interventions include copper chelators (e.g., ammonium tetrathiomolybdate), and oxidative phosphorylation inhibitors like elesclomol and copper ionophores (CuII(atsm), CuII(gtsm), and disulfiram). These interventions modulate intracellular copper, elevate NO, and reduce inflammatory cytokines, contributing to decreased cardiovascular diseases.
10.1038/s41440-024-01636-4
A novel prognostic model of breast cancer based on cuproptosis-related lncRNAs.
Discover. Oncology
OBJECTIVE:Breast cancer (BC) is a deadly form of malignancy responsible for the death of a large number of women every year. Cuproptosis is a newly discovered form of cell death that may have implications for the prognosis of BC. Long non-coding RNAs (lncRNAs) have been shown to be involved in the progression and development of BC. Here within, a novel model capable of predicting the prognosis of patients with BC was established based on cuproptosis-related lncRNAs. METHODS:Data of breast cancer patients was downloaded, including clinical information from The Cancer Genome Atlas (TCGA) database and lncRNAs related to cuproptosis were isolated. In total, nine lncRNAs related to copper death were obtained by Cox regression model based on Least Absolute Shrinkage and Selector Operation (LASSO) algorithm for model construction. The model was verified by overall survival (OS), progression-free survival (PFS) and receiver operating characteristic (ROC) curve. The differences in immune function, tumor mutation burden (TMB) and tumor immune dysfunction and exclusion (TIDE) between patients with different risk scores were analyzed. RESULTS:Based on cuproptosis-related lncRNAs, a prognostic model for predicting BC was constructed. Each patient was assigned a risk score based on our model formula. We found that patients with higher risk scores had significantly lower OS and PFS, increased TMB, and higher sensitivity to immunotherapy. CONCLUSIONS:The model established in this study based on cuproptosis-related lncRNAs may be capable of improving the OS of patients with BC.
10.1007/s12672-024-00888-3
Development and validation of a combined cuproptosis and immunogenic cell death prognostic model for diffuse large B-cell lymphoma.
Aging
BACKGROUND:Diffuse large B-cell lymphoma (DLBCL) is the most common type of non-Hodgkin lymphoma worldwide with a high degree of heterogeneity. Cuproptosis and immunogenic cell death (ICD) have been considered to be vital for tumor progression. However, current understanding of cuproptosis and immunogenic cell death in DLBCL is still very limited. We aim to explore a prognostic model combining cuproptosis and immunogenic cell death in DLBCL. METHODS:Pearson's correlation analysis was utilized to acquire lncRNAs associated with cuproptosis and immunogenic cell death. Prognostic biomarker identification and model construction involved the use of univariate Cox regression, least absolute shrinkage and selection operator (LASSO) Cox regression, and multivariate Cox regression. We assessed the predictive capability of the risk model by conducting Kaplan-Meier analysis and time-dependent ROC analysis. The analysis and comparison of immune infiltration and drug sensitivity were conducted in this study. Moreover, RT-qPCR was employed to validate the expression of lncRNAs associated with cuproptosis and immunogenic cell death in DLBCL cell lines. RESULTS:We identified 4 prognosis-related lncRNAs (ANKRD10-IT1, HOXB-AS1, LINC00520 and LINC01165) that were correlated with cuproptosis and immunogenic cell death. The model was verified to have a good and independent predictive ability in the prognostic prediction of DLBCL patients. Moreover, significant difference was observed in immune infiltration and drug sensitivity between high- and low-risk groups. CONCLUSION:Our discoveries could enhance the comprehension of the role of cuproptosis and ICD in DLBCL, potentially offering novel viewpoints and knowledge for personalized and precise treatment of DLBCL individuals.
10.18632/aging.205399
Transcriptomic profiling identifies differentially expressed genes and related pathways associated with wound healing and cuproptosis-related genes in Ganxi goats.
Frontiers in veterinary science
Introduction:Wound healing is very important for the maintenance of immune barrier integrity, which has attracted wide attention in past 10 years. However, no studies on the regulation of cuproptosis in wound healing have been reported. Methods:In this study, the skin injury model was constructed in Gnxi goats, and the function, regulatory network and hub genes of the skin before and after the injury were comprehensively analyzed by transcriptomics. Results:The results showed that there were 1,438 differentially expressed genes (DEGs), genes up-regulated by 545 and genes down-regulated by 893, which were detected by comparing day 0 and day 5 posttraumatic skin. Based on GO-KEGG analysis, DEGs that were up-regulated tended to be enriched in lysosome, phagosome, and leukocyte transendothelial migration pathways, while down-regulated DEGs were significantly enriched in adrenergic signaling in cardiomyocytes and calcium signaling pathway. There were 166 overlapped genes (DE-CUGs) between DEGs and cuproptosis-related genes, with 72 up-regulated DE-CUGs and 94 down-regulated DE-CUGs. GOKEGG analysis showed that up-regulated DE-CUGs were significantly enriched in ferroptosis, leukocyte transendothelial migration and lysosome pathways, while down-regulated DE-CUGs were significantly enriched in Apelin signaling pathway and tyrosine metabolism pathways. By constructing and analyzing of protein-protein interaction (PPI) networks of DEGs and DE-CUGs, 10 hub DEGs (ENSCHIG00000020079, PLK1, AURKA, ASPM, CENPE, KIF20A, CCNB2, KIF2C, PRC1 and KIF4A) and 10 hub DE-CUGs (MMP2, TIMP1, MMP9, MMP14, TIMP3, MMP1, EDN1, GCAT, SARDH, and DCT) were obtained, respectively. Discussion:This study revealed the hub genes and important wound healing pathways in Ganxi goats, and identified the correlation between wound healing and cuproptosis for the first time, and found that MMP2, TIMP1, MMP9, and EDN1 were the core genes associated. This study enriched the transcriptome data of wound healing in Ganxi goats and expanded the research direction of cuproptosis.
10.3389/fvets.2023.1149333
Development and Validation of the novel Cuproptosis- and Immune-related Signature for Predicting Prognosis in Hepatocellular Carcinoma.
Journal of Cancer
: Hepatocellular carcinoma often results in late-stage diagnosis, leading to decreased treatment success. To improve prognosis, this study integrates cuproptosis with immune risk scoring models for HCC patients. We identified differentially expressed genes connected to cuproptosis and immune responses using Pearson correlation. A risk signature was then constructed via LASSO regression, and its robustness was validated in the International Cancer Genome Consortium dataset. Additionally, qPCR confirmed findings in tumor and normal tissues. : Eight genes emerged as key prognostic markers from the 110 differentially expressed genes linked to cuproptosis and immunity. A risk-scoring model was developed using gene expression, effectively categorizing patients into low- or high-risk groups. Validated in the ICGC dataset, high-risk patients had significantly reduced survival times. Multivariate Cox regression affirmed the risk signature's independent predictive capability. A clinical nomogram based on the risk signature was generated. Notably, low-risk patients might benefit more from immune checkpoint inhibitors. qPCR and western blotting results substantiated our bioinformatics findings. : The genetic risk signature linked to cuproptosis and immunity holds potential as a vital prognostic biomarker for Hepatocellular carcinoma, providing avenues for tailored therapeutic strategies.
10.7150/jca.92558
Copper oxide nanoparticles suppress retinal angiogenesis via inducing endothelial cell cuproptosis.
Nanomedicine (London, England)
Copper oxide nanoparticles (CuO NPs) exhibit antitumor activity; however, their potential as an antiangiogenesis agent is unknown. The antiangiogenesis properties of CuO NPs were evaluated and and the underlying mechanism was examined using RNA sequencing and metabolomic analyses. CuO NPs inhibited endothelial cell function . They also mitigated retinal vasculature development and alleviated pathological retinal angiogenesis . RNA sequencing and metabolomic analyses revealed that CuO NPs disrupt the tricarboxylic acid cycle and induce cuproptosis, which was further supported by evaluating cuproptosis-related metabolites and proteins. CuO NPs may be an effective antiangiogenic agent for the treatment of retinal angiogenesis.
10.2217/nnm-2023-0301
Potential of lncRNAs to regulate cuproptosis in hepatocellular carcinoma: Establishment and validation of a novel risk model.
Heliyon
Cuproptosis, a distinct form of programmed cell death, is an emerging field in oncology with promising implications. This novel mode of cell death has the potential to become a regulatory target for tumor therapy, thus expanding the currently limited treatment options available for patients with cancer. Our research team focused on investigating the role of functional long non-coding RNA (lncRNAs) in hepatocellular carcinoma (HCC). We were particularly intrigued by the potential implications of HCC-lncRNAs on cuproptosis. Through a comprehensive analysis, we identified three cuproptosis-related lncRNAs (CRLs): AC018690.1, AL050341.2, and LINC02038. These lncRNAs were found to influence the sensitivity of HCC to cuproptosis. Based on our results, we constructed a risk model represented by the equation: risk score = 0.82 * + 0.65 * + 0.61 * . Notably, significant disparities were observed in clinical features, such as the response rate to immunotherapy and targeted therapy, as well as in cellular characteristics, including the composition of the tumor immune microenvironment (TIME), when comparing the high- and low-risk groups. Most importantly, knockdown of these CRLs was confirmed to significantly weaken the resistance to cuproptosis in HCC. This effect resulted from the accelerated accumulation of lipoacylated-DLAT and lipoacylated-DLST. In summary, we identified three CRLs in HCC and established a novel risk model with potential clinical applications. Additionally, we proposed a potential therapeutic method consisting of sorafenib-copper ionophores-immunotherapy.
10.1016/j.heliyon.2024.e24453
Integrative analysis of the cuproptosis-related gene ATP7B in the prognosis and immune infiltration of IDH1 wild-type glioma.
Gene
Glioma is the most common malignant tumor in the brain and the central nervous system with a poor prognosis, and wild-type isocitrate dehydrogenase (IDH) glioma indicates a worse prognosis. Cuproptosis is a recently discovered form of cell death regulated by copper-dependent mitochondrial respiration. However, the effect of cuproptosis on tumor prognosis and immune infiltration is not clear. In this research, we analyzed of public databases to show the correlation between cuproptosis-related genes and the prognosis of IDH1 wild-type glioma. Nine out of 12 genes were upregulated in IDH1 wild-type glioma patients, and 6 genes were significantly associated with overall survival (OS), while 5 genes were associated with progression-free survival (PFS). Then, we constructed a prognostic cuproptosis-related gene signature for IDH1 wild-type glioma patients. ATP7B was considered an independent prognostic indicator, and a low expression level of ATP7B was related to a shorter period of OS and PFS. Moreover, downregulation of ATP7B was correlated not only with the infiltration of activated NK cells, CD8 + T cells and M2 macrophages; but also with high expression of immune checkpoint genes and tumor mutation burden (TMB). In the IDH1 wild-type glioma tissues we collected, our data also confirmed that high tumor grade was accompanied by low expression of ATP7B and high expression of PD-L1, which was associated with increasing infiltration of CD8 + immune cells. In conclusion, our research constructed a prognostic cuproptosis-related gene signature model to predict the prognosis of IDH1 wild-type glioma. ATP7B is deemed to be a potential prognostic indicator and novel immunotherapy biomarker for IDH1 wild-type glioma patients.
10.1016/j.gene.2024.148220
Copper metabolism-related risk score identifies hepatocellular carcinoma subtypes and SLC27A5 as a potential regulator of cuproptosis.
Aging
AIMS:Dysregulated copper metabolism has been noticed in many types of cancer including hepatocellular carcinoma (HCC); however, a comprehensive understanding about this dysregulation still remains unclear in HCC. METHODS:A set of bioinformatic tools was integrated to analyze the expression and prognostic significance of copper metabolism-related genes. A related risk score, termed as CMscore, was developed via univariate Cox regression, least absolute shrinkage and selection operator (LASSO) Cox regression and multivariate Cox regression. Pathway enrichment analyses and tumor immune cell infiltration were further investigated in CMscore stratified HCC patients. Weighted correlation network analysis (WGCNA) was used to identify potential regulator of cuproptosis. RESULTS:Copper metabolism was dysregulated in HCC. HCC patients in the high-CMscore group showed a significantly lower overall survival (OS) and enriched in most cancer-related pathways. Besides, HCC patients with high CMscore had higher expression of pro-tumor immune infiltrates and immune checkpoints. Moreover, cancer patients with high CMscore from two large cohorts exhibited significantly prolonged survival time after immunotherapy. WGCNA and subsequently correlation analysis revealed that SLC27A5 might be a potential regulator of cuproptosis in HCC. experiments revealed that SLC27A5 inhibited cell proliferation and migration of HCC cells and could upregulate FDX1, the key regulator of cuproptosis. SIGNIFICANCE:The CMscore is helpful in clustering HCC patients with distinct prognosis, gene mutation signatures, and sensitivity to immunotherapy. SLC27A5 might serve as a potential target in the induction of cuproptosis in HCC.
10.18632/aging.205334
Multifunctional nanomaterials cell cuproptosis and oxidative stress for treating osteosarcoma and OS-induced bone destruction.
Materials today. Bio
Reactive Oxygen Species (ROS) refers to a highly reactive class of oxidizing species that have the potential to induce cellular apoptosis and necrosis. Cuproptosis, a type of cell death, is primarily associated with the effects of copper ions. However, the specific relationship between ROS, cuproptosis, and osteosarcoma (OS) remains relatively unexplored. Additionally, there is limited research on the use of cuproptosis in conjunction with oxidative stress for treating OS and inhibiting tumor-induced bone destruction. To address these gaps, a novel treatment approach has been developed for OS and neoplastic bone destruction. This approach involves the utilization of glutathione (GSH) and pH-responsive organic-inorganic mesoporous silica nanoparticles@CuS@oxidized Dextran (short for MCD). The MCD material demonstrates excellent cytocompatibility, osteogenesis, tumor suppression, and the ability to inhibit osteoclast formation. The specific mechanism of action involves the mitochondria of the MCD material inhibiting key proteins in the tricarboxylic acid (TCA) cycle. Simultaneously, the generation of ROS promotes this inhibition and leads to alterations in cellular energy metabolism. Moreover, the MCD biomaterial exhibits promising mild-temperature photothermal therapy in the second near-infrared (NIR-II) range, effectively mitigating tumor growth and OS-induced bone destruction .
10.1016/j.mtbio.2024.100996
Lipid changes and molecular mechanism inducing cuproptosis in Cryptocaryon irritans after copper-zinc alloy exposure.
Pesticide biochemistry and physiology
Cryptocaryons irritans is a ciliate parasite responsible for cryptocaryoniasis, leading to considerable economic losses in aquaculture. It is typically managed using a copper-zinc alloy (CZA), effectively diminishing C. irritans infection rates while ensuring the safety of aquatic organisms. Nevertheless, the precise mechanism underlying cuproptosis induced C. irritans mortality following exposure to CZA remains enigmatic. Therefore, this study delves into assessing the efficacy of CZA, investigate cuproptosis as a potential mechanism of CZA action against C. irritans, and determine the alterations in antioxidant enzymes, peroxidation, and lipid metabolism. The mRNA expression of dihydrolipoamide S-acetyltransferase was upregulated after 40 and 70 min, while aconitase 1 was implicated in cuproptosis following 70 min of CZA exposure. Furthermore, the relative mRNA levels of glutathione reductase experienced a significant increase after 40 and 70 min of CZA exposure. In contrast, the relative mRNA levels of glutathione S-transferase and phospholipid-hydroperoxide glutathione peroxidase were significantly decreased after 70 min, suggesting a disruption in antioxidant defense and an imbalance in copper ions. Lipidomics results also unveiled an elevation in glycerophospholipids metabolism and the involvement of the lipoic acid pathway, predominantly contributing to cuproptosis. In summary, exposure to CZA induces cuproptosis in C. irritans, impacts glutathione-related enzymes, and alters glycerophospholipids, consequently triggering lipid oxidation.
10.1016/j.pestbp.2023.105756
Discovering and Validating Cuproptosis-Associated Marker Genes for Accurate Keloid Diagnosis Through Multiple Machine Learning Models.
Clinical, cosmetic and investigational dermatology
Background:Keloid is a common condition characterized by abnormal scarring of the skin, affecting a significant number of individuals worldwide. Objective:The occurrence of keloids may be related to the reduction of cell death. Recently, a new cell death mode that relies on copper ions has been discovered. This study aimed to identify novel cuproptosis-related genes that are associated with keloid diagnosis. Methods:We utilized several gene expression datasets, including GSE44270 and GSE145725 as the training group, and GSE7890, GSE92566, and GSE121618 as the testing group. We integrated machine learning models (SVM, RF, GLM, and XGB) to identify 10 cuproptosis-related genes (CRGs) for keloid diagnosis in the training group. The diagnostic capability of the identified CRGs was validated using independent datasets, RT-qPCR, Western blotting, and IHC analysis. Results:Our study successfully categorized keloid samples into two clusters based on the expression of cuproptosis-related genes. Utilizing WGCNA analysis, we identified 110 candidate genes associated with cuproptosis. Subsequent functional enrichment analysis results revealed that these genes may play a regulatory role in cell growth within keloid tissue through the MAPK pathway. By integrating machine learning models, we identified CRGs that can be used for diagnosing keloid. The diagnostic efficacy of CRGs was confirmed using independent datasets, RT-qPCR, Western blotting, and IHC analysis. GSVA analysis indicated that high expression of CRGs influenced the gene set related to ECM receptor interaction. Conclusion:This study identified 10 cuproptosis-related genes that provide insights into the molecular mechanisms underlying keloid development and may have implications for the development of targeted therapies.
10.2147/CCID.S440231
Comprehensive analysis of the role of cuproptosis-related genes in the prognosis and immune infiltration of adrenocortical Carcinoma.
Heliyon
Background:Cuproptosis is a recently discovered form of nonapoptotic programmed cell death. However, no research on cuproptosis in the context of adrenocortical carcinoma has been conducted, and the prognostic value of assessing cuproptosis remains unclear. Methods:In this study, we established comprehensive models to assess gene expression changes, mutation status, and prognosis prediction and developed a prognostic nomogram for cuproptosis-related genes. Using data from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and Genotype-Tissue Expression (GTEx) databases, an analysis of 11 cuproptosis-related genes was performed. Additionally, a risk scoring method and nomogram were used to assess the relationships among cuproptosis-associated genes, transcript expression, clinical characteristics, and prognosis. The connections among tumors, immune checkpoints, and immune infiltration were also analyzed. Results:The patterns observed in patients with adrenocortical carcinoma who were assessed using cuproptosis-associated risk scores provide useful information for understanding gene mutations, clinical outcomes, immune cell infiltration, and immune checkpoint analysis results. , , , , , , and were differentially expressed in patients with adrenocortical carcinoma and normal controls. In addition, higher risk scores were significantly associated with poor overall survival and progression-free interval. The nomogram model subsequently developed to facilitate the clinical application of the analysis showed good predictive and calibration capabilities. GSE10927 and GSE33371 were used for independent cohort validation. Moreover, , , and other cuproptosis-related genes were significantly associated with immune infiltration and checkpoints. Conclusion:We confirmed that our model had excellent predictive ability in patients with adrenocortical carcinoma. Therefore, an in-depth evaluation of patients using cuproptosis-related risk scores is clinically essential and can assist in therapy in the future.
10.1016/j.heliyon.2023.e23661
Development and validation of a novel 5 cuproptosis-related long noncoding RNA signature to predict diagnosis, prognosis, and drug therapy in clear cell renal cell carcinoma.
Translational andrology and urology
Background:Cuproptosis has been reported as a new form of cell death. However, its potential mechanism of action in clear cell renal cell carcinoma (ccRCC) remains unclear. Therefore, we systematically clarified the role of cuproptosis in ccRCC and aimed to develop a novel signature of cuproptosis-related long noncoding RNAs (lncRNA) (CRLs) to assess the clinical characteristics of ccRCC patients. Methods:Gene expression, copy number variation, gene mutation, and clinical data for ccRCC were obtained from The Cancer Genome Atlas (TCGA). CRL signature was constructed with least absolute shrinkage and selection operator (LASSO) regression analysis. The clinical diagnostic value of the signature was verified by clinical data. The prognostic value of the signature was detected by Kaplan-Meier analysis and receiver operating characteristic (ROC) curve. The prognostic value of the nomogram was evaluated by calibration curves, ROC curves, and decision curve analysis (DCA). Gene set enrichment analysis (GSEA), single sample GSEA (ssGSEA) and cell type identification by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm were used to analyze the differences of immune function and immune cell infiltration among different risk groups. Prediction of clinical treatment differences in populations with different risks and susceptibilities was completed with R package (The R Foundation of Statistical Computing). Verification of key lncRNA expression was performed by quantitative real-time polymerase chain reaction (qRT-PCR). Results:The cuproptosis-related genes were extensively dysregulated in ccRCC. A total of 153 differentially expressed prognostic CRLs were identified in ccRCC. Furthermore, a 5-lncRNA signature (, and ) were obtained that showed good performance in the diagnosis and prognosis of ccRCC. The nomogram could more accurately predict overall survival (OS). Immune functions such as T-cell and B-cell receptor signaling pathways showed differences between different risk groups. Clinical treatment value analysis showed that the signature may be able to effectively guide immunotherapy and target therapy. In addition, qRT-PCR results showed significant differences in the expression of key lncRNAs in ccRCC. Conclusions:Cuproptosis plays an important role in the progression of ccRCC. The 5-CRL signature can guide the prediction of clinical characteristics and tumor immune microenvironment of ccRCC patients.
10.21037/tau-23-65
A risk model based on ferroptosis- and cuproptosis-related lncRNAs predicts prognosis and immune microenvironment in lung adenocarcinoma by bioinformatics analysis and experimental verification.
American journal of cancer research
Ferroptosis and cuproptosis are both novel types of cell death. Long noncoding RNAs (lncRNAs) are associated with multiple cancers. Notably, bioinformatics study of ferroptosis- and cuproptosis-related lncRNAs (FCLs) in lung adenocarcinoma (LUAD) has not been elucidated. In this study, we used univariate Cox, multivariate Cox, and least absolute shrinkage and selection operator Cox (LASSO-Cox) analyses to screen three FCLs, namely AC079193.2, AC090559.1, and AL512363.1. We then showed that these three FCLs were tumor-specific and correlated with ferroptosis and cuproptosis using qRT-PCR. Next, a prognostic risk model consisting of high- and low-risk cohorts was successfully constructed based on The Cancer Genome Atlas-LUAD data. The high-risk group consistently demonstrated poor prognosis. The accuracy of the model was evaluated using AUC, C-index curves, and nomograms. Furthermore, KEGG and GO analysis with R software showed significant enrichment in immune functions and metabolic pathways. Hereto, the immune function and immune cell expression results were more pronounced in the low-risk versus high-risk group. In conclusion, the prognostic risk model comprised of three FCLs effectively predicted patient outcomes and is associated with the immune microenvironment in LUAD.
Alternative splicing variants involved in pyroptosis and cuproptosis contribute to phenotypic remodeling of the tumor microenvironment in cervical cancer.
Reproductive sciences (Thousand Oaks, Calif.)
Cervical cancer (CC) remains a prevalent gynecological malignancy, posing a significant health burden among women worldwide. With the remarkable discoveries of cellular pyroptosis and cuproptosis, there has been a growing focus on exploring the intricate relationship between these two forms of cell death and their impact on tumor progression. In recent years, alternative splicing has emerged as a significant field in cancer research. Thus, the integration of alternative splicing, pyroptosis, and cuproptosis holds immense value in studying their collective impact on the occurrence and progression of cervical cancer. In this study, alternative splicing data of pyroptosis- and cuproptosis-associated genes were integrated with public databases, including TCGA, to establish a prognostic model for cervical cancer based on COX regression modeling. Subsequently, the tumor microenvironment (TME) phenotypes in the high-risk and low-risk patient groups were characterized through a comprehensive bioinformatics analysis. The findings of this study revealed that the low-risk group exhibited a predominant immune-active TME phenotype, while the high-risk group displayed a tumor-favoring metabolic phenotype. These results indicate that the alternative splicing of pyroptosis- and cuproptosis-associated genes plays a pivotal role in remodeling the phenotypic landscape of the cervical cancer TME by modulating immune responses and metabolic pathways. This study provides valuable insights into the interplay between alternative splicing variants involved in pyroptosis and cuproptosis and the TME, contributing to a deeper understanding of cervical cancer pathogenesis and potential therapeutic avenues.
10.1007/s43032-023-01284-y
Predictors based on cuproptosis closely related to angiogenesis predict colorectal cancer recurrence.
Frontiers in oncology
Up to one-third of colorectal cancer (CRC) patients experience recurrence after radical surgery, and it is still very difficult to assess and predict the risk of recurrence. Angiogenesis is the key factor of recurrence as metastasis of CRC is closely related to copper metabolism. Expression profiling by microarray from two datasets in Gene Expression Omnibus (GEO) was selected for quality control, genome annotation, normalization, etc. The identified angiogenesis-derived and cuproptosis-related Long non-coding RNAs (lncRNAs) and clinical data were screened and used as predictors to construct a Cox regression model. The stability of the model was evaluated, and a nomogram was drawn. The samples were divided into high-risk and low-risk groups according to the linear prediction of the model, and a Kaplan-Meier survival analysis was performed. In this study, a model was established to predict the postoperative recurrence of colon cancer, which exhibits a high prediction accuracy. Furthermore, the negative correlation between cuproptosis and angiogenesis was validated in colorectal cancer cell lines and the expression of lncRNAs was examined.
10.3389/fonc.2023.1322421
Comprehending the cuproptosis and cancer-immunity cycle network: delving into the immune landscape and its predictive role in breast cancer immunotherapy responses and clinical endpoints.
Frontiers in immunology
Background:The role of cuproptosis, a phenomenon associated with tumor metabolism and immunological identification, remains underexplored, particularly in relation to the cancer-immunity cycle (CIC) network. This study aims to rigorously examine the impact of the cuproptosis-CIC nexus on immune reactions and prognostic outcomes in patients with breast cancer (BC), striving to establish a comprehensive prognostic model. Methods:In the study, we segregated data obtained from TCGA, GEO, and ICGC using CICs retrieved from the TIP database. We constructed a genetic prognostic framework using the LASSO-Cox model, followed by its validation through Cox proportional hazards regression. This framework's validity was further confirmed with data from ICGC and GEO. Explorations of the tumor microenvironment were carried out through the application of ESTIMATE and CIBERSORT algorithms, as well as machine learning techniques, to identify potential treatment strategies. Single-cell sequencing methods were utilized to delineate the spatial distribution of key genes within the various cell types in the tumor milieu. To explore the critical role of the identified CICs, experiments were conducted focusing on cell survival and migration abilities. Results:In our research, we identified a set of 4 crucial cuproptosis-CICs that have a profound impact on patient longevity and their response to immunotherapy. By leveraging these identified CICs, we constructed a predictive model that efficiently estimates patient prognoses. Detailed analyses at the single-cell level showed that the significance of CICs. Experimental approaches, including CCK-8, Transwell, and wound healing assays, revealed that the protein HSPA9 restricts the growth and movement of breast cancer cells. Furthermore, our studies using immunofluorescence techniques demonstrated that suppressing HSPA9 leads to a notable increase in ceramide levels. Conclusion:This research outlines a network of cuproptosis-CICs and constructs a predictive nomogram. Our model holds great promise for healthcare professionals to personalize treatment approaches for individuals with breast cancer. The work provides insights into the complex relationship between the cuproptosis-CIC network and the cancer immune microenvironment, setting the stage for novel approaches to cancer immunotherapy. By focusing on the essential gene HSPA9 within the cancer-immunity cycle, this strategy has the potential to significantly improve the efficacy of treatments against breast cancer.
10.3389/fimmu.2024.1344023
Development and verification of a newly established cuproptosis-associated lncRNA model for predicting overall survival in uterine corpus endometrial carcinoma.
Translational cancer research
Background:Uterine corpus endometrial carcinoma (UCEC) is a prevalent gynecologic malignant tumor with high recurrence and mortality rates. This study aimed to develop and validate a prognostic model for patients with UCEC based on cuproptosis-related long non-coding RNA (lncRNA) signature. Methods:Transcriptome and clinical UCEC data were obtained from The Cancer Genome Atlas (TCGA) database. Correlation analysis was conducted to screen out the cuproptosis-related lncRNAs, and univariate regression analysis was performed to determine prognostic factors associated with overall survival (OS). A cuproptosis-related lncRNA risk model was constructed through least absolute shrinkage and selection operator (LASSO) regression and cross-validation. The accuracy and reliability of the model were verified through Kaplan-Meier (KM), proportional hazards model (Cox) regression, nomogram, principal component analysis (PCA), and stage analysis. Gene Ontology (GO) enrichment, immune function, and tumor mutation burden (TMB) analyses were conducted between low-risk and high-risk groups, and antineoplastic drugs were predicted. Results:By correlation analysis, 155 cuproptosis-related lncRNAs were acquired, and 9 lncRNAs were identified as independent prognostic factors. A 6-cuproptosis-related lncRNA model was established. The results revealed that patients in the high-risk group were more inclined to have a poor OS than those in the low-risk group. Risk score was an independent prognostic factor and had a high accuracy and predictive value. The extracellular structure and anchored components of membrane-related GO terms were significantly enriched. Immune function and TMB results were assumed to be different from each other, which might explain a better outcome in the low-risk group than that in the high-risk group. Eighteen compounds were predicted as chemotherapy drugs with high half maximal inhibitory concentration (IC50) in the high-risk group. Conclusions:We successfully developed a cuproptosis-related lncRNA risk model for the prediction of prognosis, while simultaneously providing insights on new approaches for immunotherapy and chemotherapy for patients with UCEC.
10.21037/tcr-23-61
A Deep Learning Approach for Prognostic Evaluation of Lung Adenocarcinoma Based on Cuproptosis-Related Genes.
Biomedicines
Lung adenocarcinoma represents a significant global health challenge. Despite advances in diagnosis and treatment, the prognosis remains poor for many patients. In this study, we aimed to identify cuproptosis-related genes and to develop a deep neural network model to predict the prognosis of lung adenocarcinoma. We screened differentially expressed genes from The Cancer Genome Atlas data through differential analysis of cuproptosis-related genes. We then used this information to establish a prognostic model using a deep neural network, which we validated using data from the Gene Expression Omnibus. Our deep neural network model incorporated nine cuproptosis-related genes and achieved an area under the curve of 0.732 in the training set and 0.646 in the validation set. The model effectively distinguished between distinct risk groups, as evidenced by significant differences in survival curves ( < 0.001), and demonstrated significant independence as a standalone prognostic predictor ( < 0.001). Functional analysis revealed differences in cellular pathways, the immune microenvironment, and tumor mutation burden between the risk groups. Furthermore, our model provided personalized survival probability predictions with a concordance index of 0.795 and identified the drug candidate BMS-754807 as a potentially sensitive treatment option for lung adenocarcinoma. In summary, we presented a deep neural network prognostic model for lung adenocarcinoma, based on nine cuproptosis-related genes, which offers independent prognostic capabilities. This model can be used for personalized predictions of patient survival and the identification of potential therapeutic agents for lung adenocarcinoma, which may ultimately improve patient outcomes.
10.3390/biomedicines11051479
Ferroptosis and cuproptposis in kidney Diseases: dysfunction of cell metabolism.
Apoptosis : an international journal on programmed cell death
Metal ions play an important role in living organisms and are involved in essential physiological activities. However, the overload state of ions can cause excess free radicals, cell damage, and even cell death. Ferroptosis and cuproptosis are specific forms of cell death that are distinct from apoptosis, necroptosis, and other regulated cell death. These unique modalities of cell death, dependent on iron and copper, are regulated by multiple cellular metabolic pathways, including steady-state metal redox treatment mitochondrial activity of lipid, amino acid and glucose metabolism, and various signaling pathways associated with disease. Although the mechanisms of ferroptosis and cuproptosis are not yet fully understood, there is no doubt that ion overload plays a crucial act in these metal-dependent cell deaths. In this review, we discussed the core roles of ion overload in ferroptosis and cuproptosis, the association between metabolism imbalance and ferroptosis and cuproptosis, the extract the diseases caused by ion overload and current treatment modalities.
10.1007/s10495-023-01928-z
Identification of cuproptosis-related lncRNAs signature for predicting the prognosis in patients with kidney renal clear cell carcinoma.
Journal, genetic engineering & biotechnology
BACKGROUND:Kidney renal clear cell carcinoma (KIRC), with low survival rate, is the most frequent subtype of renal cell carcinoma. Recently, more and more studies indicate that cuproptosis-related genes (CRGs) and long non-coding RNAs (lncRNAs) play a vital role in the occurrence and development of many types of cancers. However, the roles of cuproptosis-related lncRNAs (CRlncRNAs) in the KIRC was uncertain. RESULTS:In our study, CRlncRNAs were obtained by coexpression between differentially expressed and prognostic CRGs and differentially expressed and prognostic lncRNAs, and an 8-CRlncRNAs (AC007743.1, AC022915.1, AP005136.4, APCDD1L-DT, HAGLR, LINC02027, MANCR and SMARCA5-AS1) risk model was established according to least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression. This risk model could differentiate immune cell infiltration, immune function and gene mutation. CONCLUSIONS:This 8-CRlncRNAs risk model may be promising for the clinical prediction of prognoses, tumor immune, immunotherapy response and chemotherapeutic response in KIRC patients.
10.1016/j.jgeb.2023.100338
Comprehensive analysis of the prognostic signature and tumor microenvironment infiltration characteristics of cuproptosis-related lncRNAs for patients with colon adenocarcinoma.
Frontiers in oncology
Background:Cuproptosis, a newly described method of regulatory cell death (RCD), may be a viable new therapy option for cancers. Long noncoding RNAs (lncRNAs) have been confirmed to be correlated with epigenetic controllers and regulate histone protein modification or DNA methylation during gene transcription. The roles of cuproptosis-related lncRNAs (CRLs) in Colon adenocarcinoma (COAD), however, remain unknown. Methods:COAD transcriptome data was obtained from the TCGA database. Thirteen genes associated to cuproptosis were identified in published papers. Following that, correlation analysis was used to identify CRLs. The cuproptosis associated prognostic signature was built and evaluated using Lasso regression and COX regression analysis. A prognostic signature comprising six CRLs was established and the expression patterns of these CRLs were analyzed by qRT-PCR. To assess the clinical utility of prognostic signature, we performed tumor microenvironment (TME) analysis, mutation analysis, nomogram generation, and medication sensitivity analysis. Results:We identified 49 prognosis-related CRLs in COAD and constructed a prognostic signature consisting of six CRLs. Each patient can be calculated for a risk score and the calculation formula is: Risk score =TNFRSF10A-AS1 * (-0.2449) + AC006449.3 * 1.407 + AC093382.1 *1.812 + AC099850.3 * (-0.0899) + ZEB1-AS1 * 0.4332 + NIFK-AS1 * 0.3956. Six CRLs expressions were investigated by qRT-PCR in three colorectal cancer cell lines. In three cohorts, COAD patients were identified with different risk groups, with the high-risk group having a worse prognosis than the low-risk group. Furthermore, there were differences in immune cell infiltration and tumor mutation burden (TMB) between the two risk groups. We also identified certain drugs that were more sensitive to the high-risk group: Paclitaxel, Vinblastine, Sunitinib and Elescloml. Conclusions:Our findings may be used to further investigate RCD, comprehension of the prognosis and tumor microenvironment infiltration characteristics in COAD.
10.3389/fonc.2022.1007918
Identification of immune characteristic biomarkers and therapeutic targets in cuproptosis for sepsis by integrated bioinformatics analysis and single-cell RNA sequencing analysis.
Heliyon
Background:Cuproptosis is a copper-dependent cell death that is connected to the development and immune response of multiple diseases. However, the function of cuproptosis in the immune characteristics of sepsis remains unclear. Method:We obtained two sepsis datasets (GSE9960 and GSE134347) from the GEO database and classified the raw data with R packages. Cuproptosis-related genes were manually curated, and differentially expressed cuproptosis-related genes (DECuGs) were identified. Afterwards, we applied enrichment analysis and identified key DECuGs by performing machine learning techniques. Then, the immune cell infiltrations and correlation between DECuGs and immunocyte features were created by the CIBERSORT algorithm. Subsequently, unsupervised hierarchical clustering analysis was performed based on key DECuGs. We then constructed a ceRNA network based on key DECuGs by using multi-step computational strategies and predicted potential drugs in the DrugBank database. Finally, the role of these key genes in immune cells was validated at the single-cell RNA level between septic patients and healthy controls. Results:Overall, 16 DECuGs were obtained, and most of them had lower expression levels in sepsis samples. Afterwards, we obtained six key DECuGs by performing machine learning. Then, the LIPT1-T-cell CD4 memory resting was the most positively correlated DECuG-immunocyte pair. Subsequently, two different subclusters were identified by six DECuGs. Bioinformatics analysis revealed that there were different immune characteristics between the two subclusters. Moreover, we identified the key lncRNA OIP5-AS1 within the ceRNA network and obtained 4 drugs that may represent novel drugs for sepsis. Finally, these key DECuGs were statistically significantly dysregulated in another validation set and showed a major distribution in monocytes, T cells, B cells, NK cells and platelets at the single-cell RNA level. Conclusion:These findings suggest that cuproptosis might promote the progression of sepsis by affecting the immune system and metabolic dysfunction, which provides a new direction for understanding potential pathogenic processes and therapeutic targets in sepsis.
10.1016/j.heliyon.2024.e27379
A novel risk model construction and immune landscape analysis of gastric cancer based on cuproptosis-related long noncoding RNAs.
Frontiers in oncology
Recent studies have identified cuproptosis, a new mechanism of regulating cell death. Accumulating evidence suggests that copper homeostasis is associated with tumorigenesis and tumor progression, however, the clinical significance of cuproptosis in gastric cancer (GC) is unclear. In this study, we obtained 26 prognostic cuproptosis-related lncRNAs (CRLs) based on 19 cuproptosis-related genes (CRGs) Pearson correlation analysis, differential expression analysis, and univariate Cox analysis. A risk model based on 10 CRLs was established with the least absolute shrinkage and selection operator (LASSO) Cox regression analysis and multivariate Cox proportional hazards model to predict the prognosis and immune landscape of GC patients from The Cancer Genome Atlas (TCGA). The risk model has excellent accuracy and efficiency in predicting prognosis of GC patients (Area Under Curve (AUC) = 0.742, 0.803, 0.806 at 1,3,5 years, respectively, ). In addition, we found that the risk score was negatively correlated with the infiltration of natural killer (NK) cells and helper T cells, while positively correlated with the infiltration of monocytes, macrophages, mast cells, and neutrophils. Moreover, we evaluated the difference in drug sensitivity of patients with different risk patterns. Furthermore, low-risk patients showed higher tumor mutation burden (TMB) and better immunotherapy response than high-risk patients. In the end, we confirmed the oncogenic role of AL121748.1 which exhibited the highest Hazard Ratio (HR) value among 10 CRLs in GC cellular functional experiments. In conclusion, our risk model shows a significant role in tumor immunity and could be applied to predict the prognosis of GC patients.
10.3389/fonc.2022.1015235
Association of cuproptosis-related signature with the prognosis of patients with head and neck squamous cell carcinoma.
Journal of biomolecular structure & dynamics
Patients with head and neck squamous cell carcinoma (HNSCC) have a poor prognosis because of their high recurrence and metastasis rates. Cuproptosis is a novel type of copper-dependent cell death that differs from apoptosis, necroptosis, and cytosolic scorch death. We designed and validated an individualized cuproptosis-related gene (CRG) signature for risk evaluation and prognostic prediction in HNSCC patients. Ninety differentially expressed CRGs were found in HNSCC. Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway analyses were performed to investigate the functional involvement of CRGs in the Cancer Genome Atlas (TCGA) HNSCC cohort. A CRG signature was created using 10 genes after univariate and multivariate analysis. Kaplan Meier (KM) analysis showed that the survival rate of the high-risk group was significantly lower than that of the low-risk group. Multivariate regression analysis identified risk scores based on prognostic characteristics as independent prognostic indicators of HNSCC. Moreover, risk models are related to tumor mutational burden (TMB), tumor-infiltrating immune cells (TICs), immune checkpoints, clinical characteristics, and antitumor drug susceptibility. Furthermore, we found that CuCl treatment promoted cuproptosis in HNSCC cells, and that the expression levels of cuproptosis-related genes were altered by different doses of CuCl. In summary, understanding the detailed molecular mechanisms of cuproptosis and its impact on overall survival (OS), and identifying potential therapeutic targets for HNSCC will provide potential insights for treatment.Communicated by Ramaswamy H. Sarma.
10.1080/07391102.2024.2308776
Exploring prognostic markers for patients with acute myeloid leukemia based on cuproptosis related genes.
Translational cancer research
Background:Acute myeloid leukemia (AML), a common form of acute leukemia, is due to tumor changes and clonal proliferation caused by genetic variants. Cuproptosis is a novel form of regulated cell death. This study aimed to explore the role of cuproptosis-related genes (CRGs) in AML. Methods:Initially, differentially expressed genes (DEGs) between AML samples and normal samples were obtained by differential analysis, which were further intersected with the cuproptosis score-related genes (CSRGs) acquired by weighted gene co-expression network analysis (WGCNA) to obtain cuproptosis score-related differentially expressed genes (CS-DEGs). Then, a risk model was constructed by Cox analysis and least absolute shrinkage and selection operator (LASSO) analysis. Finally, immune infiltration analysis was performed and the functions and pathways of model genes were explored by single sample gene set enrichment analysis (ssGSEA). Results:Thirty-two CS-DEGs were obtained by overlapping 11,160 DEGs and 132 CSRGs. These 32 CS-DEGs were mainly enriched to cytoplasmic microtubule organization, RNA methylation, mTOR signaling pathway, and notch signaling pathway. Two model genes, and , were finally screened for the construction of the risk model. In addition, and were significantly positively correlated with activated B cells, CD56dim natural killer (NK) cells, and negatively correlated with effector memory CD4 T cells and activated CD4 T cells. gene was significantly enriched to inositol phosphate metabolism, histone modification, etc. was mainly enriched to ncRNA metabolic process, 2-oxocarboxylic acid metabolism, and other pathways. Conclusions:A cuproptosis-related risk model consisting of and was built, which provided a new direction for the diagnosis and treatment of AML.
10.21037/tcr-23-85
Molecular subtypes and tumor microenvironment infiltration signatures based on cuproptosis-related genes in colon cancer.
Frontiers in oncology
Background:Colon cancer is one of the common cancers, and its prognosis remains to be improved. The role of cuproptosis as a newly discovered form of cell death in the development of colon cancer has not been determined. Methods:Based on 983 colon cancer samples in the TCGA database and the GEO database, we performed a comprehensive genomic analysis to explore the molecular subtypes mediated by cuproptosis-related genes. Single-sample gene set enrichment analysis (ssGSEA) was utilized to quantify the relative abundance of each cell infiltrate in the TME. A risk score was established using least absolute shrinkage and selection operator regression (LASSO), and its predictive ability for colon cancer patients was verified to explore its guiding value for treatment. Results:We identified two distinct cuproptosis-related molecular subtypes in colon cancer. These two distinct molecular subtypes can predict clinicopathological features, prognosis, TME activity, and immune-infiltrating cells. A risk model was developed and its predictive ability was verified. Compared with patients in the high-risk score group, patients in the low-risk score group were characterized by lower tumor microenvironment score, higher stem cell activity, lower tumor mutational burden, lower microsatellite instability, higher sensitivity to chemotherapeutics, and better immunotherapy efficacy. Conclusion:This study contributes to understanding the molecular characteristics of cuproptosis-related subtypes. We demonstrate a critical role for cuproptosis genes in colon cancer s in the TME. Our study contributes to the development of individualized treatment regimens for colon cancer.
10.3389/fonc.2023.999193
A novel ferroptosis-related gene signature associated with cuproptosis for predicting overall survival in breast cancer patients.
Acta biochimica Polonica
Purpose Ferroptosis and cuproptosis are both metal-dependent regulated cell death that play an important role in cancer. However, the expression patterns and the prognostic values of ferroptosis-related genes (FRGs) associated with cuproptosis in breast cancer (BC) are largely unknown. This study aims to explore the prognostic value of cuproptosis-related FRGs and their relationship with tumor microenvironments in BC. Methods The clinical and RNA sequencing data of BC patients from TCGA, METABRIC and GEO databases were analyzed. The least absolute shrinkage and selection operator regression analysis was used to establish prognostic signatures based on cuproptosis-related FRGs. The overall survival between risk subgroups was assessed by Kaplan-Meier analysis. The changes in risk score during neoadjuvant chemotherapy, and differences in immune cells, immune checkpoints, and drug sensitivity between risk subgroups were also analyzed in this study. Results A successful development of a prognostic signature based on cuproptosis-related FRGs in the TCGA cohort was achieved and it was validated in the METABRIC cohort. Gene set enrichment analysis results revealed the enrichment of steroid biosynthesis and ABC transporters in the high-risk group. Moreover, the signature was also found to be associated with immune cells and immune checkpoints. Lower risk score in patients after neoadjuvant chemotherapy and higher sensitivity of the high-risk group to AKT inhibitor VIII and cisplatin was also observed. Conclusion Cuproptosis-related FRGs can be used as a novel prognostic signature for predicting the overall survival of BC patients. This can provide meaningful insights into the selection of immunotherapy and antitumor drugs for BC.
10.18388/abp.2020_6722
A prognostic and immunotherapy effectiveness model for pancreatic adenocarcinoma based on cuproptosis-related lncRNAs signature.
Medicine
Pancreatic adenocarcinoma (PAAD) results in one of the deadliest solid tumors with discouraging clinical outcomes. Growing evidence suggests that long non-coding RNAs (lncRNAs) play a crucial role in altering the growth, prognosis, migration, and invasion of pancreatic cancer cells. Cuproptosis is a novel type of cell death induced by copper (Cu) and is associated with mitochondrial respiration during the tricarboxylic acid cycle. However, the relationship between lncRNAs related to cuproptosis and PAAD is poorly studied. In this study, we investigated the association between a signature of cuproptosis-related lncRNAs and the diagnosis of PAAD. Genomic data and clinical information were obtained using the TCGA dataset, while cuproptosis-related genes (CRGs) from previous studies. Co-expression analysis was utilized to identify lncRNAs associated with cuproptosis. We developed and verified a prognostic risk model following a classification of patients into high- and low-risk categories. The prediction capacity of the risk model was assessed using a number of methods including Kaplan-Meier analysis, receiver operating characteristic (ROC) curves, nomograms, and principal component analysis (PCA). Furthermore, differentially expressed genes (DEGs) were used to perform functional enrichment analyses, and to examine the behaviors of various risk groups in terms of immune-related activities and medication sensitivity. We identified 7 cuproptosis-related lncRNA signatures, including CASC19, FAM83A-AS1, AC074099.1, AC007292.2, AC026462.3, AL358944.1, and AC009019.1, as overall survival (OS) predictors. OS and progression-free survival (PFS) showed significant differences among patients in different risk groups. Independent prognostic analysis revealed that the cuproptosis-related lncRNA signatures can independently achieve patient prognosis. The risk model demonstrated strong predictive ability for patient outcomes, as evidenced by ROC curves, nomograms, and PCA. Higher tumor mutation burden (TMB) and lower tumor immune dysfunction and exclusion (TIDE) scores were observed in the high-risk group. Additionally, the low-risk group was hypersensitive to 3 anti-cancer medications, whereas the high-risk group was hypersensitive to one. A prognostic risk model with a good predictive ability based on cuproptosis-related lncRNAs was developed, providing a theoretical basis for personalized treatment and immunotherapeutic responses in pancreatic cancer.
10.1097/MD.0000000000035167
Identification of cuproptosis-related gene clusters and immune cell infiltration in major burns based on machine learning models and experimental validation.
Frontiers in immunology
Introduction:Burns are a global public health problem. Major burns can stimulate the body to enter a stress state, thereby increasing the risk of infection and adversely affecting the patient's prognosis. Recently, it has been discovered that cuproptosis, a form of cell death, is associated with various diseases. Our research aims to explore the molecular clusters associated with cuproptosis in major burns and construct predictive models. Methods:We analyzed the expression and immune infiltration characteristics of cuproptosis-related factors in major burn based on the GSE37069 dataset. Using 553 samples from major burn patients, we explored the molecular clusters based on cuproptosis-related genes and their associated immune cell infiltrates. The WGCNA was utilized to identify cluster-specific genes. Subsequently, the performance of different machine learning models was compared to select the optimal model. The effectiveness of the predictive model was validated using Nomogram, calibration curves, decision curves, and an external dataset. Finally, five core genes related to cuproptosis and major burn have been was validated using RT-qPCR. Results:In both major burn and normal samples, we determined the cuproptosis-related genes associated with major burns through WGCNA analysis. Through immune infiltrate profiling analysis, we found significant immune differences between different clusters. When K=2, the clustering number is the most stable. GSVA analysis shows that specific genes in cluster 2 are closely associated with various functions. After identifying the cross-core genes, machine learning models indicate that generalized linear models have better accuracy. Ultimately, a generalized linear model for five highly correlated genes was constructed, and validation with an external dataset showed an AUC of 0.982. The accuracy of the model was further verified through calibration curves, decision curves, and modal graphs. Further analysis of clinical relevance revealed that these correlated genes were closely related to time of injury. Conclusion:This study has revealed the intricate relationship between cuproptosis and major burns. Research has identified 15 cuproptosis-related genes that are associated with major burn. Through a machine learning model, five core genes related to cuproptosis and major burn have been selected and validated.
10.3389/fimmu.2024.1335675
Dry and wet experiments reveal diagnostic clustering and immune landscapes of cuproptosis patterns in patients with ankylosing spondylitis.
International immunopharmacology
Cuproptosis is a new manner of mitochondrial cell death induced by copper. There is evidence that serum copper has a crucial impact on ankylosing spondylitis (AS) by copper-induced inflammatory response. However, the molecular mechanisms of cuproptosis modulators in AS remain unknown. We aimed to use a bioinformatics-based method to comprehensively investigate cuproptosis-related subtype identification and immune microenvironment infiltration of AS. Additionally, we further verified the results by in vitro experiments, in which peripheral blood and fibroblast cells from AS patients were used to evaluate the functions of significant cuproptosis modulators on AS. Finally, eight significant cuproptosis modulators were identified by analysis of differences between controls and AS cases from GSE73754 dataset. Eight prognostic cuproptosis modulators (LIPT1, DLD, PDHA1, PDHB, SLC31A1, ATP7A, MTF1, CDKN2A) were identified using a random forest model for prediction of AS risk. A nomogram model of the 8 prognostic cuproptosis modulators was then constructed; the model could be beneficial in clinical settings, as indicated by decision curve analysis. Consensus clustering analysis was used to divide AS patients into two cuproptosis subtypes (clusterA & B) according to significant cuproptosis modulators. The cuproptosis score of each sample was calculated by principal component analysis to quantify cuproptosis subtypes. The cuproptosis scores were higher in clusterB than in clusterA. Additionally, cases in clusterA were closely associated with the immunity of activated B cells, Activated CD4 T cell, Type17 T helper cell and Type2 T helper cell, while cases in clusterB were linked to Mast cell, Neutrophil, Plasmacytoid dendritic cell immunity, indicating that clusterB may be more correlated with AS. Notably, key cuproptosis genes including ATP7A, MTF1, SLC31A1 detected by RT-qPCR with peripheral blood exhibited significantly higher expression levels in AS cases than controls; LIPT1 showed the opposite results; High MTF1 expression is correlated with increased osteogenic capacity. In general, this study of cuproptosis patterns may provide promising biomarkers and immunotherapeutic strategies for future AS treatment.
10.1016/j.intimp.2023.111326
Multi-omics analysis reveals prognostic and therapeutic value of cuproptosis-related lncRNAs in oral squamous cell carcinoma.
Frontiers in genetics
Extensive research revealed copper and lncRNA can regulate tumor progression. Additionally, cuproptosis has been proven can cause cell death that may affect the development of tumor. However, there is little research focused on the potential prognostic and therapeutic role of cuproptosis-related lncRNA in OSCC patients. Data used were for bioinformatics analyses were downloaded from both the TCGA database and GEO database. The R software were used for statistical analysis. Mapping was done using the tool of FigureYa. The signature consist of 7 cuproptosis-related lncRNA was identified through lasso and Cox regression analysis and a nomogram was developed. In addition, we performed genomic analyses including pathway enrichment analysis and mutation analysis between two groups. It was found that OSCC patients were prone to TP53, TTN, FAT1 and NOTCH1 mutations and a difference of mutation analysis between the two groups was significant. Results of TIDE analysis indicating that patients in low risk group were more susceptible to immunotherapy. Accordingly, results of subclass mapping analysis confirmed our findings, which revealed that patients with low riskscore were more likely to respond to immunotherapy. We have successfully identified and validated a novel prognostic signature with a strong independent predictive capacity. And we have found that patients with low riskscore were more susceptible to immunotherapy, especially PD-1 inhibitor therapy.
10.3389/fgene.2022.984911
Integrated bioinformatics and experiment revealed that cuproptosis is the potential common pathogenesis of three kinds of primary cardiomyopathy.
Aging
Cuproptosis is a recently reported new mode of programmed cell death which might be a potential co-pathogenesis of three kinds of primary cardiomyopathy. However, no investigation has reported a clear relevance between primary cardiomyopathy and cuproptosis. In this study, the differential cuproptosis-related genes (CRGs) shared by three kinds of primary cardiomyopathy were identified in training sets. As a result, four CRGs shared by three kinds of primary cardiomyopathy were acquired and they were mainly related to biological processes such as cell death and immuno-inflammatory response through differential analysis, correlation analysis, GSEA, GSVA and immune cell infiltration analysis. Then, three key CRGs (K-CRGs) with high diagnostic value were identified by LASSO regression. The results of nomogram, machine learning, ROC analysis, calibration curve and decision curve indicated that the K-CRGs exhibited outstanding performance in the diagnosis of three kinds of primary cardiomyopathy. After that, in each disease, two molecular subtypes clusters were distinguished. There were many differences between different clusters in the biological processes associated with cell death and immunoinflammation and K-CRGs had excellent molecular subtype identification efficacy. Eventually, results from validation datasets and experiments verified the role of K-CRGs in diagnosis of primary cardiomyopathy, identification of primary cardiomyopathic molecular subtypes and pathogenesis of cuproptosis. In conclusion, this study found that cuproptosis might be the potential common pathogenesis of three kinds of primary cardiomyopathy and K-CRGs might be promising biomarkers for the diagnosis and molecular subtypes identification of primary cardiomyopathy.
10.18632/aging.205298
Identification of molecular subtypes and a six-gene risk model related to cuproptosis for triple negative breast cancer.
Frontiers in genetics
Breast cancer is the mostly diagnosed cancer worldwide, and triple negative breast cancer (TNBC) has the worst prognosis. Cuproptosis is a newly identified form of cell death, whose mechanism has not been fully explored in TNBC. This study thought to unveil the potential association between cuproptosis and TNBC. Gene expression files with clinical data of TNBC downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were included in this study. Consensus clustering was utilized to perform molecular subtyping based on cuproptosis-associated genes. Limma package was applied to distinguish differentially expressed genes. Univariate Cox regression was used to identify prognostic genes. Least absolute shrinkage and selection operator and stepwise Akaike information criterion optimized and established a risk model. We constructed three molecular subtypes based on cuproptosis-associated genes, and the cuproptosis-based subtyping showed a robustness in different datasets. Clust2 showed the worst prognosis and immune-related pathways such as chemokine signaling pathway were significantly activated in clust2. Clust2 also exhibited a high possibility of immune escape to immune checkpoint blockade. In addition, a six-gene risk model was established manifesting a high AUC score over 0.85 in TCGA dataset. High- and low-risk groups had distinct prognosis and immune infiltration. Finally, a nomogram was constructed with strong performance in predicting TNBC prognosis than the staging system. The molecular subtyping system related to cuproptosis had a potential in guiding immunotherapy for TNBC patients. Importantly, the six-gene risk model was effective and reliable to predict TNBC prognosis.
10.3389/fgene.2022.1022236
Nucleophosmin 1 is a prognostic marker of gastrointestinal cancer and is associated with m6A and cuproptosis.
Frontiers in pharmacology
NPM1 is highly expressed in a variety of solid tumors and promotes tumor development. However, there are few comprehensive studies on NPM1 analysis in gastrointestinal cancer. We used bioinformatics tools to study the expression difference of NPM1 between gastrointestinal cancer and control group, and analyzed the relationship between its expression level and the diagnosis, prognosis, functional signaling pathway, immune infiltration, m6A and cuproptosis related genes of gastrointestinal cancer. At the same time, the expression difference of NPM1 between esophageal carcinoma (ESCA) samples and control samples was verified by experiments. NPM1 was overexpressed in gastrointestinal cancer. experiments confirmed that the expression of NPM1 in ESCA samples was higher than that in normal samples. The expression of NPM1 has high accuracy in predicting the outcome of gastrointestinal cancer. The expression of NPM1 is closely related to the prognosis of multiple gastrointestinal cancers. Go and KEGG enrichment analysis showed that NPM1 co-expressed genes involved in a variety of biological functions. NPM1 expression is potentially associated with a variety of immune cell infiltration, m6A and cuproptosis related genes in gastrointestinal cancers. NPM1 can be used as a diagnostic and prognostic marker of gastrointestinal cancer, which is related to the immune cell infiltration and the regulation of m6A and cuproptosis.
10.3389/fphar.2022.1010879
Bioinformatic profiling identifies the glutaminase to be a potential novel cuproptosis-related biomarker for glioma.
Frontiers in cell and developmental biology
Glioma is the most common tumour of the central nervous system, with a poor prognosis and an increasing trend of incidence in recent years; it is also beginning to affect younger age groups more. Added to this, cuproptosis is a new form of cell death. Indeed, when a certain amount of copper accumulates in a cell, it affects specific mitochondrial metabolic enzymes in that cell and leads to cell death-a phenomenon known as cuproptosis. In this study, we applied bioinformatics analysis, and, according to the results of the study analysis and Gene Ontology (GO), as well as the Kyoto Encyclopedia of Genes and Genomes KyotoEncyclopediaofGenesandGenomes, the glutaminase (GLS) genes affect the prognosis and tumour mutation of glioma patients through cuproptosis. Interestingly, however, GLS is not involved in the immune escape of glioma. Glutaminase genes are a class of glucose metabolism-related genes that are involved in the tricarboxylic acid cycle of cells. At the same time, the expression of the glutaminase gene was positively correlated with the degree of immune cell infiltration and the expression of various immune cell markers, and thus affected the prognosis of glioma patients. Therefore, we believe that the cuproptosis-related glutaminase gene can be an important factor in determining the prognosis of glioma patients.
10.3389/fcell.2022.982439