Integrated analysis of a competing endogenous RNA network in renal cell carcinoma using bioinformatics tools

Background: Circular RNAs (circRNAs) are known to be closely involved in tumorigenesis and cancer progression. Nevertheless, their function and underlying mechanisms in renal cell carcinoma (RCC) remain largely unknown. The aim of the present study was to explore their expression, functions, and molecular mechanisms in RCC. Methods: We downloaded the circRNA expression profiles from Gene Expression Omnibus (GEO) database, and RNA expression profiles from The Cancer Genome Atlas (TCGA) database. A ceRNA network was constructed based on circRNA–miRNA pairs and miRNA–mRNA pairs. Interactions between proteins were analyzed using the STRING database, and hub genes were identified using the cytoHubba app. We also constructed a circRNA–miRNA–hub gene regulatory module. Functional and pathway enrichment analyses were conducted using “DAVID 6.8” and R package “clusterProfiler”. Results: About 6 DEcircRNAs, 17 DEmiRNAs, and 134 DEmRNAs were selected for the construction of ceRNA network of RCC. Protein–protein interaction network and module analysis identified 8 hub genes. A circRNA–miRNA–hub gene sub-network was constructed based on 3 DEcircRNAs, 4 DEmiRNAs, and 8 DEmRNAs. GO and KEGG pathway analysis indicated the possible association of DEmRNAs with RCC onset and progression. Conclusions: These findings together provide a deeper understanding of the pathogenesis of RCC and suggest potential therapeutic targets.