Polycystic Ovary Syndrome (PCOS) is a complex endocrine disorder with elusive molecular mechanisms. This study explores the competitive endogenous RNA (ceRNA) regulatory network in the cumulus cells of PCOS patients. ceRNAs are transcripts like mRNAs, miRNAs, and lncRNAs that competitively bind shared miRNAs, regulating gene expression post-transcriptionally. We analyzed mRNA, microRNA (miRNA), and long non-coding RNA (lncRNA) from two cohorts: 12 PCOS patients and 11 healthy controls (dataset GSE10946), and 5 PCOS patients and 5 healthy controls (dataset GSE72274). These microarray datasets, obtained from the Gene Expression Omnibus (GEO), helped us identify differentially expressed mRNAs, miRNAs, and lncRNAs. Our analysis revealed a significant ceRNA network, which may play a crucial role in the pathophysiology of PCOS. In this network, 5 lncRNAs, 3 miRNAs, and 36 mRNAs were identified as differentially expressed. These elements form a complex regulatory schema influencing key cellular processes related to the disease, such as cell cycle regulation and response to estrogen. The HOXA11-AS-hsa-miR-454-3p-CCND2 network emerged as a potentially valuable biomarker for PCOS diagnosis, supported by Receiver Operating Characteristic (ROC) curve analysis indicating strong predictive power. Our findings suggest that the ceRNA interactions in PCOS cumulus cells provide a deeper understanding of the disease's molecular basis and offer new avenues for therapeutic intervention. This in silico study lays the groundwork for further experimental validation of these ceRNA networks as targets for PCOS treatment.
Keywords: Bioinformatics analysis; CCND2; CeRNA; Cumulus cells; HOXA11-AS; PCOS.
Copyright © 2024 Society for Biology of Reproduction & the Institute of Animal Reproduction and Food Research of Polish Academy of Sciences in Olsztyn. Published by Elsevier B.V. All rights reserved.