Integrated Bioinformatic Analysis Reveals the Gene Signatures, Epigenetic Roles, and Regulatory Networks in Endometriosis

Abstract

Objectives: Endometriosis is a common gynecological disease with a significant economic burden. Growing evidence has suggested the role of aberrant gene expression and epigenetic mechanisms in the pathogenesis of endometriosis. This study aims to identify potential key genes, epigenetic features, and regulatory networks in endometriosis using an integrated bioinformatic approach. Methods: Six microarray and RNA-sequencing datasets (GSE23339, GSE7305, GSE25628, GSE51981, GSE120103, GSE87809) were downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) of each dataset were analyzed using the GEO2R tool, and their mRNA, miRNA, and lncRNA components were identified subsequently. The common DEGs between datasets were combined, and the Gene ontology (GO) and pathway enrichment were analyzed using the ShinyGo. The protein-protein interaction (PPI) network of differentially expressed genes, miRNA, and lncRNA was constructed using STRING and Cytoscape, then the top 15 hub genes in the PPI network were identified using the CytoHubba. Results: A total of 551 common DEGs were identified among four or more studies, including 292 upregulated and 259 downregulated genes. Besides alterations in protein-coding genes (mRNA), 16 miRNA were identified from all studies, along with 12 lncRNA that were common in at least three studies. Enriched DEGs were mainly associated with extracellular matrix (ECM) interaction, P53 signaling pathway, and focal adhesion, which are suggested to play vital roles in the pathogenesis of endometriosis. Through PPI network construction of common DEGs, 178 nodes and 683 edges were obtained, from which 15 hub genes were identified, including CDK1, CCNB1, KIF11, CCNA2, BUB1B, DLGAP5, BUB1, TOP2A, ASPM, CEP55, CENPF, TPX2, CCNB2, KIFC, NCAPG. Conclusions: Our in-depth bioinformatics analysis reveals the critical molecular basis underlying endometriosis. The identified hub genes, miRNA, and lncRNA may also serve as potential biomarkers to predict the occurrence and prognosis of endometriosis.