Fifteen hub genes associated with progression and prognosis of clear cell renal cell carcinoma identified by coexpression analysis. Issue 7 (11th November 2018)

• Record Type: Journal Article
• Authors: Wang, Yejinpeng; Chen, Liang; Wang, Gang; Cheng, Songtao; Qian, Kaiyu; Liu, Xuefeng; Wu, Chin‐Lee; Xiao, Yu; Wang, Xinghuan
• Is Part Of: Journal of cellular physiology. Volume 234:Issue 7(2019:Jul.)
• Page Start: 10225
• Page End: 10237
• Publication Date: 2018-11-11
• Subjects: clear cell renal cell carcinoma -- coexpression network analysis -- protein–protein interaction -- single‐samples gene‐set enrichment analysis; Physiology -- Periodicals; Cell physiology -- Periodicals; 571.6
• DOI: 10.1002/jcp.27692
• Languages: English
• ISSNs: 0021-9541

Abstract

Abstract: Renal cell carcinoma (RCC) is the most common type of renal tumor, and the clear cell renal cell carcinoma (ccRCC) is the most frequent subtype. In this study, our aim is to identify potential biomarkers that could effectively predict the prognosis and progression of ccRCC. First, we used The Cancer Genome Atlas (TCGA) RNA‐sequencing (RNA‐seq) data of ccRCC to identify 2370 differentially expressed genes (DEGs). Second, the DEGs were used to construct a coexpression network by weighted gene coexpression network analysis (WGCNA). Moreover, we identified the yellow module, which was strongly related to the histologic grade and pathological stage of ccRCC. Then, the functional annotation of the yellow module and single‐samples gene‐set enrichment analysis of DEGs were performed and mainly enriched in cell cycle. Subsequently, 18 candidate hub genes were screened through WGCNA and protein–protein interaction (PPI) network analysis. After verification of TCGA's ccRCC data set, Gene Expression Omnibus (GEO) data set (GSE73731) and tissue validation, we finally identified 15 hub genes that can actually predict the progression of ccRCC. In addition, by using survival analysis, we found that patients of ccRCC with high expression of each hub gene were more likely to have poor prognosis than those with low expression. The receiver operating characteristic curve showed that each hub gene could effectively distinguish between localized and advanced ccRCC. In summary, our study indicates that 15 hub genes have great predictive value for the prognosis and progression of ccRCC, and may contribute to the exploration of the pathogenesis of ccRCC. Abstract : We constructed a scale‐free weighted gene coexpression network analysis coexpression network, after a series of rigorous analysis and verification, we finally selected 15 hub genes, which are significantly related to the progress and prognosis of clear cell renal cell carcinoma (ccRCC), as well as could also significantly differentiate between localized and advanced ccRCC. Our study providing new research objects for studying the pathogenesis of ccRCC, they are also new potential therapeutic targets for ccRCC.