A Novel Mirna-Based Model Can Predict The Prognosis Of Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is one of the most prevalent renal malignant cancer, whose survival rate and quality of life of patients are still not satisfactory. Nevertheless, the TNM staging system currently used in clinical cannot make accurate survival predictions and precise treatment decisions for ccRCC patients. Therefore, there is an urgent need for more reliable biomarkers to identify high-risk subgroups of ccRCC patients to guide timely intervention and treatment. Recently, MiRNAs have been shown to be closely related to the procession of a variety of tumors, and they have high stability in various tissues, which makes them suggested to have the potential as a prognostic biomarker of ccRCC. In this study, by analyzing and processing the miRNAs expression profile of ccRCC patients from the TCGA database, we finally constructed an excellent miRNAs signature and verified it through a variety of methods. In order to build a more accurate and reliable clinical predictive model, we integrated the miRNAs signature with other prognostic-related clinical parameters to construct a nomogram. Functional enrichment analysis showed that miRNAs in the signature may regulate the genes involved in the Hippo signaling pathway, Tight junction, and Wnt signaling pathway to cause different prognoses of ccRCC patients, which may provide a reference for subsequent basic research and targeted therapy. To conclude, our study constructed a useful miRNAs signature, which allows the prognosis stratification for ccRCC patients and thereby guides the timely and effective interventions on high-risk patients. At the same time, this study also found the potential biological pathways involved in the procession of ccRCC.