Cancer Essential Genes Stratified Lung Adenocarcinoma Patients with Distinct Survival Outcomes and Identified a Subgroup from the Terminal Respiratory Unit Type with Different Proliferative Signatures in Multiple Cohorts.
Ho Kuo-Hao,Huang Tzu-Wen,Liu Ann-Jeng,Shih Chwen-Ming,Chen Ku-Chung
: Heterogeneous features of lung adenocarcinoma (LUAD) are used to stratify patients into terminal respiratory unit (TRU), proximal-proliferative (PP), and proximal-inflammatory (PI) subtypes. A more-accurate subtype classification would be helpful for future personalized medicine. However, these stratifications are based on genes with variant expression levels without considering their tumor-promoting roles. We attempted to identify cancer essential genes for LUAD stratification and their clinical and biological differences. : Essential genes in LUAD were identified using genome-scale CRIPSR screening of RNA sequencing data from Project Achilles and The Cancer Genome Atlas (TCGA). Patients were stratified using consensus clustering. Survival outcomes, genomic alterations, signaling activities, and immune profiles within clusters were investigated using other independent cohorts. : Thirty-six genes were identified as essential to LUAD, and there were used for stratification. Essential gene-classified clusters exhibited distinct survival rates and proliferation signatures across six cohorts. The cluster with the worst prognosis exhibited TP53 mutations, high E2F target activities, and high tumor mutation burdens, and harbored tumors vulnerable to topoisomerase I and poly(ADP ribose) polymerase inhibitors. TRU-type patients could be divided into clinically and molecularly different subgroups based on these essential genes. : Our study showed that essential genes to LUAD not only defined patients with different survival rates, but also refined preexisting subtypes.
Expression and clinical prognostic value of m6A RNA methylation modification in breast cancer.
Zheng Fangchao,Du Feng,Qian Haili,Zhao Jiuda,Wang Xue,Yue Jian,Hu Nanlin,Si Yiran,Xu Binghe,Yuan Peng
BACKGROUND:N6-methyladenosine(m6A) methylation modification affects the tumorigenesis, progression, and metastasis of breast cancer (BC). However, the expression characteristics and prognostic value of m6A modification in BC are still unclear. We aimed to evaluate the relationship between m6A modification and clinicopathological characteristics, and to explore the underlying mechanisms. METHODS:Three public cohorts and our clinical cohort were included: 1091 BC samples and 113 normal samples from the TCGA database, 1985 BC samples from the METABRIC database, 1764 BC samples from the KM Plotter website, and 134 BC samples of our clinical cohort. We collected date from these cohorts and analyzed the genetic expression, gene-gene interactions, gene mutations, copy number variations (CNVs), and clinicopathological and prognostic features of 28 m6A RNA regulators in BC. RESULTS:This study demonstrated that some m6A regulators were significantly differenially expressed in BCs and their adjacent tissues, and also different in various molecular types. All 28 studied m6A regulators exhibited interactions. KIAA1429 had the highest mutation frequency. CNVs of m6A regulators were observed in BC patients. The expression of the m6A regulators was differentially associated with survival of BC. Higher CBLL1 expression was associated with a better prognosis in BC than lower CBLL1 expression. Functional analysis showed that CBLL1 was related to the ESR1-related pathway, apoptosis-related pathway, cell cycle pathway and immune-related pathway in BC. CONCLUSIONS:m6A RNA modification modulated gene expression and thereby affected clinicopathological features and survival outcomes in BC. CBLL1 may be a promising prognostic biomarker for BC patients.
Four Novel Prognostic Genes Related to Prostate Cancer Identified Using Co-expression Structure Network Analysis.
Feng Tao,Wei Dechao,Li Qiankun,Yang Xiaobing,Han Yili,Luo Yong,Jiang Yongguang
Frontiers in genetics
Prostate cancer (PCa) is one of the most common malignancies for males, but very little is known about its pathogenesis. This study aimed to identify novel biomarkers associated with PCa prognosis and elucidate the underlying molecular mechanism. First, The Cancer Genome Atlas (TCGA) RNA-sequencing data were utilized to identify differentially expressed genes (DEGs) between tumor and normal samples. The DEGs were then applied to construct a co-expression and mined using structure network analysis. The magenta module that was highly related to the Gleason score ( = 0.46, = 3e-26) and tumor stage ( = 0.38, = 2e-17) was screened. Subsequently, all genes of the magenta module underwent function annotation. From the key module, CCNA2, CKAP2L, NCAPG, and NUSAP1 were chosen as the four candidate genes. Finally, internal (TCGA) and external data sets (GSE32571, GSE70770, and GSE141551) were combined to validate and predict the value of real hub genes. The results show that the above genes are up-regulated in PCa samples, and higher expression levels show significant association with higher Gleason scores and tumor T stage. Moreover, receiver operating characteristic curve and survival analysis validate the excellent value of hub genes in PCa progression and prognosis. In addition, the protein levels of these four genes also remain higher in tumor tissues when compared with normal tissues. Gene set enrichment analysis and gene set variation analysis for a single gene reveal the close relation with cell proliferation. Meanwhile, 11 small molecular drugs that have the potential to treat PCa were also screened. In conclusion, our research identified four potential prognostic genes and several candidate molecular drugs for treating PCa.
A Panel of Five-lncRNA Signature as a Potential Biomarker for Predicting Survival in Gastric and Thoracic Cancers.
Shao Jiayue,Lyu Wei,Zhou Jiehao,Xu Wenhui,Wang Dandan,Liang Shanshan,Zhao Jiayin,Qin Yujing
Frontiers in genetics
Dysfunctional long non-coding RNAs (lncRNAs) have been found to have carcinogenic and/or tumor inhibitory effects in the development and progression of cancer, suggesting their potential as new independent biomarkers for cancer diagnosis and prognosis. The exploration of the relationship between lncRNAs and the overall survival (OS) of different cancers opens up new prospects for tumor diagnosis and treatment. In this study, we established a five-lncRNA signature and explored its prognostic efficiency in gastric cancer (GC) and several thoracic malignancies, including breast invasive carcinoma (BRCA), esophageal carcinoma, lung adenocarcinoma, lung squamous cell carcinoma (LUSC), and thymoma (THYM). Cox regression analysis and lasso regression were used to evaluate the relationship between lncRNA expression and survival in different cancer datasets from GEO and TCGA. Kaplan-Meier survival curves indicated that risk scores characterized by a five-lncRNA signature were significantly associated with the OS of GC, BRCA, LUSC, and THYM patients. Functional enrichment analysis showed that these five lncRNAs are involved in known biological pathways related to cancer pathology. In conclusion, the five-lncRNA signature can be used as a prognostic marker to promote the diagnosis and treatment of GC and thymic malignancies.
Integrated analysis and identification of nine-gene signature associated to oral squamous cell carcinoma pathogenesis.
Yadav Monika,Pradhan Dibyabhaba,Singh Rana P
Oral squamous cell carcinoma (OSCC) is one of the leading cancers with poor disease survival rate. Herein, we explored molecular basis, in silico identification and in vitro verification of genes associated with OSCC. Five gene expression series including, GSE30784, GSE13601, GSE9844, GSE23558 and GSE37991 were screened for differentially expressed genes (DEGs). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were enriched by cluster Profiler. Further, protein-protein interaction network was analysed and hub genes were verified. A total of 6476 (up-regulated: 2848; down-regulated: 3628) DEGs were identified among OSCC patients and healthy controls. Gene Ontology analysis indicated DEGs enrichment in cellular motility, invasion and adhesion processes. KEGG analysis revealed enrichment of PI3K-Akt signalling, focal adhesion and regulation of actin cytoskeleton pathways. Subsequently, nine DEGs including were correlated with TCGA expression data along with significant association towards patient's survival, recognized as hub genes. This dysregulated mRNA signature of genes was validated in two OSCC cell lines with an anti-cancer agent, fisetin. Fisetin inhibited the expression of and upregulated the expression of gene which were associated with growth inhibition of both the OSCC cell lines. The regulatory effect of fisetin supported crucial role of nine hub genes identified in OSCC. This study signified that hub genes and pathways might influence the aggressiveness of OSCC. Thus, the proposed hub genes could be potential diagnostic biomarker and drug targets for OSCC. Supplementary Information:The online version contains supplementary material available at 10.1007/s13205-021-02737-4.
An Immune-Related Gene Pairs Signature Predicts Prognosis and Immune Heterogeneity in Glioblastoma.
Zhang Nijia,Ge Ming,Jiang Tao,Peng Xiaoxia,Sun Hailang,Qi Xiang,Zou Zhewei,Li Dapeng
Frontiers in oncology
Purpose:Glioblastoma is one of the most aggressive nervous system neoplasms. Immunotherapy represents a hot spot and has not been included in standard treatments of glioblastoma. So in this study, we aim to filtrate an immune-related gene pairs (IRGPs) signature for predicting survival and immune heterogeneity. Methods:We used gene expression profiles and clinical information of glioblastoma patients in the TCGA and CGGA datasets, dividing into discovery and validation cohorts. IRGPs significantly correlative with prognosis were selected to conduct an IRGPs signature. Low and high risk groups were separated by this IRGPs signature. Univariate and multivariate cox analysis were adopted to check whether risk can be a independent prognostic factor. Immune heterogeneity between different risk groups was analyzed immune infiltration and gene set enrichment analysis (GSEA). Some different expressed genes between groups were selected to determine their relationship with immune cells and immune checkpoints. Results:We found an IRGPs signature consisting of 5 IRGPs. Different risk based on IRGPs signature is a independent prognostic factor both in the discovery and validation cohorts. High risk group has some immune positive cells and more immune repressive cells than low risk group by means of immune infiltration. We discovered some pathways are more active in the high risk group, leading to immune suppression, drug resistance and tumor evasion. In two specific signaling, some genes are over expressed in high risk group and positive related to immune repressive cells and immune checkpoints, which indicate aggression and immunotherapy resistance. Conclusion:We identified a robust IRGPs signature to predict prognosis and immune heterogeneity in glioblastoma patients. Some potential targets and pathways need to be further researched to make different patients benefit from personalized immunotherapy.
High Expression of microRNA-223 Indicates a Good Prognosis in Triple-Negative Breast Cancer.
Chen Li,Zhu Xiuzhi,Han Boyue,Ji Lei,Yao Ling,Wang Zhonghua
Frontiers in oncology
Purpose:MicroRNAs can influence many biological processes and have shown promise as cancer biomarkers. Few studies have focused on the expression of microRNA-223 (miR-223) and its precise role in breast cancer (BC). We aimed to examine the expression level of miR-223 and its prognostic value in BC. Methods:Tissue microarray (TMA)-based miRNA detection hybridization (ISH) with a locked nucleic acid (LNA) probe was used to detect miR-223 expression in 450 BC tissue samples. Overall survival (OS) and disease-free survival (DFS) were compared between two groups using the Kaplan-Meier method and Cox regression model. Results:OS and DFS were prolonged in the high miR-223 expression group compared to the low miR-223 expression group (p < 0.0001 and p = 0.017, respectively), especially in patients with the triple-negative breast cancer (TNBC) subtype (p = 0.046 and p < 0.001, respectively). Univariate and multivariate Cox regression analyses revealed that TNM stage (p = 0.008), the molecular subtype (p = 0.049), and miR-223 (p < 0.001) were independently associated with OS and DFS. External validation was performed with the METABRIC and The Cancer Genome Atlas (TCGA) databases online webtools and was consistent with the data described above. Conclusions:This study provides evidence that high miR-223 expression at diagnosis is associated with improved DFS and OS for BC patients, especially those with the TNBC subtype. miR-223 is a valid and independent prognostic biomarker in BC.