Computational identification and analysis of early diagnostic biomarkers for kidney cancer.

Abstract

Renal cell carcinoma is one of the most common urinary system tumors in adults, it is usually asymptomatic in its early stage and the patients are often diagnosed late. MicroRNA has a higher diagnostic accuracy than traditional markers and may become a new type of early diagnostic biomarker for kidney cancer. Three computational methods and several bioinformatic methods including PPI network, overall survival analysis and enrichment analysis were used to identify the significant differentially expressed miRNAs. Thirteen miRNAs that were significantly differentially expressed in RCC patients were identified, 10 of them have been proved to be associated with kidney cancer in other studies, miR-576, miR-616 and miR-133a-2 are three newly discovered biomarkers of RCC in this study. We found that the target genes of miR-576 (CUL3 and RAC1) are involved in the regulation of multiple cancer-related biological pathways, and the target gene of miR-616 (ASB13 and FBXW2) has been reported to be associated with the development of other cancers. Our findings may have guiding significance for the early diagnosis of renal cell carcinoma.