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

(Pages: 386-393)
Ying Wang, Ph.D., 1,#,*Haibin Wei, M.Sc, 2,#Lizhi Song, M.Sc, 1Lu Xu, M.Sc, 1Jingyao Bao, B.Sc, 1Jiang Liu, Ph.D, 1,*
Institute of Aging Research, School of Medicine, Hangzhou Normal University, Hangzhou, Zhejiang, China
Department of Pathology, Zhejiang Cancer Hospital, Hangzhou, Zhejiang, China
Institute of Aging Research, School of Medicine, Hangzhou Normal University, Hangzhou, Zhejiang, China
Department of Pathology, Zhejiang Cancer Hospital, Hangzhou, Zhejiang, China
*Corresponding Address: Institute of Aging Research School of Medicine Hangzhou Normal University Hangzhou Zhejiang China Emails:flashingdancer@163.com,Jennings_L143@126.com

The first two authors equally contributed to this work.

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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.

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.