Integrated Analysis Revealed the MicroRNA-Based Prognostic Predicting Signature for Papillary Renal Cell Carcinoma

Renal cell carcinoma (RCC) is one of the most frequently occurring tumors worldwide. Herein, we established a microRNA (miRNA) predicting signature to assess the prognosis of papillary-type RCC (PRCC) patients. miR-1293, miR-34a, miR-551b, miR-937, miR-299, and miR-3199-2 were used in building the overall survival (OS)-related signature, whereas miR-7156, miR-211, and miR-301b were used to construct the formula of recurrence-free survival (RFS) with the help of LASSO Cox regression analysis. The Kaplan-Meier and receiver operating characteristic curves indicated good discrimination and efficiency of the two signatures. Functional annotation for the downstream genes of the OS/RFS-related miRNAs exposed the potential mechanisms of PRCC. Notably, the multivariate analyses suggested that the two signatures were independent risk factors for PRCC patients and had better prognostic capacity than any other classifier. In addition, the nomogram indicated synthesis effects and showed better predictive performance than clinicopathologic features and our signatures. We validated the OS and RFS prediction formulas in clinical samples and met our expectations. Finally, we established two novel miRNA-based OS and RFS predicting signatures for PRCC, which are reliable tools for assessing the prognosis of PRCC patients.