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Published on: January 12, 2020
Bioinformatic analysis of key pathways and genes shared between endometriosis and ovarian cancer
Leyi Ni1, Yumei Chen1, Jie Yang1
1Department of Gynecology and Obstetrics, Wenzhou People's Hospital, The Wenzhou Third Clinical Institute Affiliated To Wenzhou Medical University, 57 Canghou Street, Wuma Street, Lucheng District, Wenzhou, 325000, China.
Purpose:
The purpose of the study is to identify potential key genes and pathways, using bioinformatics, underlying the potentially common molecular mechanisms between endometriosis (EMS) and ovarian cancer (OC).
Methods:
Two datasets were collected from the Gene Expression Omnibus database, and the limma package identified common differentially expressed genes (DEGs) in the EMS and OC groups compared to controls. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, gene interaction network, and module analyses identified the enriched pathways associated with DEGs. A protein-protein interaction (PPI) network was then constructed, and the CytoHubba plugin of Cytoscape was used to calculate the degree of connectivity for proteins in the PPI network.
Results:
A total of 571 overlapping DEGs were identified between EMS and OC (vs. controls). Enriched DEGs were associated with 36 gene ontology terms and 7 Kyoto Encyclopedia of Genes and Genomes pathways, which were mainly associated with deactivation of the p53 signaling pathway. The Kaplan-Meier plotter platform confirmed the expression of the identified hub genes, and survival analysis suggested that CCNB1, CCNB2, BUB1B, CCNA2, KIF2C, and TOP2A are associated with decreased survival and disease-free survival rates of OC.
Conclusion:
The key pathways identified herein elucidate the possible mechanism by which EMS evolves into OC; further, the identified hub genes may serve as potential biomarkers to predict OC occurrence and prognosis.
