Development and Validation of Nine-RNA Binding Protein Signature Predicting Overall Survival for Kidney Renal Clear Cell Carcinoma - Zhong, Weimin; Huang, Chaoqun; Lin, Jianqiong; Zhu, Maoshu; Zhong, Hongbin; Chiang, Ming-Hsien; Chiang, Huei-Shien; Hui, Mei-Sau; Lin, Yao; Huang, Jiyi (Frontiers in Genetics, 2020)
Cumulative studies have shown that RNA binding proteins (RBPs) play an important role in numerous malignant tumors and related to the occurrence and progression of tumors. However, the role of RBPs in the kidney renal clear cell carcinoma (KIRC) has been not fully understood. In this study, we firstly downloaded gene expression data and corresponding clinical information of KIRC from the Cancer Genome Atlas (TCGA) database and International Cancer Genome Consortium (ICGC), respectively. A total of 137 differentially expressed RBPs (DERBPs) were then identified between normal and tumor tissue, including 38 down regulated RBPs and 99 up-regulated RBPs. Nine RBPs (EIF4A1, RPL36A, EXOSC5, RPL28, RPL13, RPS19, RPS2, EEF1A2, OASL) were served as prognostic genes and exploited to construct a prognostic model through survival analysis. The Kaplan-Meier curves analysis showed that low risk group had a better survival outcome when compared with high risk group. The area under curve (AUC) value of the prognostic model was 0.713 in TCGA dataset (train dataset) and 0.706 in ICGC dataset (validation dataset), respectively, confirming a good prognostic model. The prognostic model was also identified an independent prognostic factor for KIRC survival by performing cox regression analysis. In addition, we also built a nomogram rely on age and prognostic model, and internal validation in the TCGA data set. The clinical benefit of the prognostic model was revealed by decision curve analysis (DCA). Gene set enrichment analysis revealed several crucial pathways (ERBB signaling pathway, pathways in cancer, MTOR signaling pathway, WNT signaling pathway and TGF BETA signaling pathway) that may explain the underlying mechanisms of KIRC. Furthermore, potential drugs for KIRC treatment were predicted by Connectivity Map (Cmap) database based on DERBPs, and several important drugs such as depudecin and vorinostat that could reverse KIRC gene expression, which may provide reference for the treatment of KIRC. In summary, we developed and validated a robust Nine-RBP signature for KIRC prognosis prediction. A nomogram with risk score and age can be applied to promote the individualized prediction of overall survival in patients with KIRC. Moreover, the two drugs including depudecin and vorinostat may contribute to KIRC treatment.