Gene Expression Microarray Data Meta-Analysis Identifies
Candidate Genes and Molecular Mechanism Associated
with Clear Cell Renal Cell Carcinoma
The first two authors equally contributed to this work.
Wang Y, Wei H, Song L, Xu L, Bao J, Liu J. Gene expression microarray data meta-analysis identifies candidate genes and molecular mechanism associated with clear cell renal cell carcinoma. Cell J. 2020; 22(3): 386-393. doi: 10.22074/cellj.2020.6561.
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.
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, IRF7 and PPARGC1A might play important roles in ccRCC via taking part in the immune system process.