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

Autor: Ying Wang, Haibin Wei, Lizhi Song, Lu Xu, Jingyao Bao, Jiang Liu
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Cell Journal, Vol 22, Iss 3, Pp 386-393 (2020)
Druh dokumentu: article
ISSN: 2228-5806
2228-5814
DOI: 10.22074/cellj.2020.6561
Popis: Objective: We aimed to explore potential molecular mechanisms of clear cell renal cell carcinoma (ccRCC) and provide candidate target genes for ccRCC gene therapy. Material 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.
Databáze: Directory of Open Access Journals
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