Gene Expression Microarray Data Meta-Analysis Identifies Candidate Genes and Molecular Mechanism Associated with Clear Cell Renal Cell Carcinoma

Cell J. 2020 Oct;22(3):386-393. doi: 10.22074/cellj.2020.6561. Epub 2019 Dec 15.

Abstract

Objective: We aimed to explore potential molecular mechanisms of clear cell renal cell carcinoma (ccRCC) and provide candidate target genes for ccRCC gene therapy.

Materials and methods: This is a bioinformatics-based study. Microarray datasets of GSE6344, GSE781 and GSE53000 were downloaded from Gene Expression Omnibus database. Using meta-analysis, differentially expressed genes (DEGs) were identified between ccRCC and normal samples, followed by Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) function analyses. Then, protein-protein interaction (PPI) networks and modules were investigated. Furthermore, miRNAs-target gene regulatory network was constructed.

Results: Total of 511 up-regulated and 444 down-regulated DEGs were determined in the present gene expression microarray data meta-analysis. These DEGs were enriched in functions like immune system process and pathways like Toll-like receptor signaling pathway. PPI network and eight modules were further constructed. A total of 10 outstanding DEGs including TYRO protein tyrosine kinase binding protein (TYROBP), interferon regulatory factor 7 (IRF7) and PPARG co-activator 1 alpha (PPARGC1A) were detected in PPI network. Furthermore, the miRNAs-target gene regulation analyses showed that miR-412 and miR-199b respectively targeted IRF7 and PPARGC1A to regulate the immune response in ccRCC.

Conclusion: TYROBP, IRF7 and PPARGC1A might play important roles in ccRCC via taking part in the immune system process.

Keywords: Clear Cell Renal Cell Carcinoma; Immune Response; Protein-Protein Interaction Network.