Research Paper Volume 13, Issue 3 pp 3926—3944

Development of prognostic signature based on RNA binding proteins related genes analysis in clear cell renal cell carcinoma

Qiang Chen1, *, , Zhi-Long Li1, *, , Sheng-Qiang Fu1, , Si-Yuan Wang1, , Yu-Tang Liu1, , Ming Ma1, , Xiao-Rong Yang1, , Wen-Jie Xie1, , Bin-Bin Gong1, , Ting Sun1, ,

  • 1 Department of Urology, The First Affiliated Hospital of Nanchang University, Nanchang 330006, Jiangxi Province, China
* Equal contribution

Received: August 31, 2020       Accepted: November 20, 2020       Published: January 10, 2021
How to Cite

Copyright: © 2021 Chen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


RNA binding proteins (RBPs) play significant roles in the development of tumors. However, a comprehensive analysis of the biological functions of RBPs in clear cell renal cell carcinoma (ccRCC) has not been performed. Our study aimed to construct an RBP-related risk model for prognosis prediction in ccRCC patients. First, RNA sequencing data of ccRCC were downloaded from The Cancer Genome Atlas (TCGA) database. Three RBP genes (EIF4A1, CARS, and RPL22L1) were validated as prognosis-related hub genes by univariate and multivariate Cox regression analyses and were integrated into a prognostic model by least absolute shrinkage and selection operator (LASSO) Cox regression analysis. According to this model, patients with high risk scores displayed significantly worse overall survival (OS) than those with low risk scores. Moreover, the multivariate Cox analysis results indicated that risk score, tumor grade, and tumor stage were significantly correlated with patient OS. A nomogram was constructed based on the three RBP genes and showed a good ability to predict outcomes in ccRCC patients. In conclusion, this study identified a three-RBP gene risk model for predicting the prognosis of patients, which is conducive to the identification of novel diagnostic and prognostic molecular markers.


ccRCC: clear cell renal cell carcinoma; AJCC: American Joint Committee on Cancer; TCGA: The Cancer Genome Atlas; OS: overall survival; FC: fold change; GO: Gene Ontology; KEGG: Kyoto Encyclopedia of Genes and Genomes; BP: biological process; CC: cellular components; MF: molecular functions; ROC: receiver operating characteristic; AUC: area under the ROC curve; GSEA: Gene Set Enrichment Analysis.