RNA binding protein (RBPs) dysregulation has been reported in various malignant tumors and plays a pivotal role in tumor carcinogenesis and progression. However, the underlying mechanisms in renal cell carcinoma (RCC) are still unknown. In the present study, we performed a bioinformatics analysis using data from TCGA database to explore the expression and prognostic value of RBPs. We identified 125 differently expressed RBPs between tumor and normal tissue in RCC patients, including 87 upregulated and 38 downregulated RBPs. Eight RBPs (RPL22L1, RNASE2, RNASE3, EZH2, DDX25, DQX1, EXOSC5, DDX47) were selected as prognosis-related RBPs and used to construct a risk score model. In the risk score model, the high-risk subgroup had a poorer overall survival (OS) than the low-risk subgroup, and we divided the 539 RCC patients into two groups and conducted a time-dependent receiver operating characteristic (ROC) analysis to further test the prognostic ability of the eight hub RBPs. The area under the curve (AUC) of the ROC curve was 0.728 in train-group and 0.688 in test-group, indicating a good prognostic model. More importantly, we established a nomogram based on the selected eight RBPs. The eight selected RBPS have predictive value for RCC patients, with potential applications in clinical decision-making and individualized treatment.
Keywords: Overall survival; Prognostic model; RNA binding proteins; Renal cell carcinoma.
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