Bioinformatic analysis of key pathways and genes shared between endometriosis and ovarian cancer

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).

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.

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.

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. Similar content being viewed by others Availability of data and material The datasets generated and/or analyzed during the current study are available in the [GEO] repository, through the following urls: (1) https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE7305; (2) https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE14407. Code availability The code used in this study is available from the corresponding author upon reasonable request.

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Consent to participate Not applicable. Consent for publication Not applicable. Additional information Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Rights and permissions About this article Cite this article Ni, L., Chen, Y., Yang, J. et al. Bioinformatic analysis of key pathways and genes shared between endometriosis and ovarian cancer. Arch Gynecol Obstet 305, 1329–1342 (2022). https://doi.org/10.1007/s00404-021-06285-3 Received: Accepted: Published: Version of record: Issue date: DOI: https://doi.org/10.1007/s00404-021-06285-3