Objectives: Polycystic ovary syndrome (PCOS), the primary cause of anovulatory infertility in women, may change the gene expression profile of cumulus cells. In human ART (assisted reproductive technology), gene expression profiling in cumulus cells, a non-invasive method, may be used to identify the most competent oocytes. We aim to identify key genes according to the network-based data and assess the suitability of these genes as markers to predict oocyte competence and PCOS diagnosis.
Materials And Methods: The GSE34526 microarray dataset was obtained from the Gene Expression Omnibus (GEO) database. The function and pathway enrichment analysis for DEGs were analyzed. A protein-protein interaction (PPI) network analysis and candidate gene screening were conducted. A two-layer network consisting of mRNA and lncRNA was constructed. Expression levels of hub genes were verified using quantitative RT-PCR (qRT-PCR).
Results: A total of 2721 DEGs were retained. The PPI network of selected genes associated with the biological process of "cell communication" was analyzed, and the first 10 key genes were determined by degree. Additionally, 2 hub genes and 2 hub lncRNAs, including , , , and , were selected from the lncRNA-mRNA network. Finally, expression levels of , , , and were significantly increased in the cumulus cells of PCOS patients compared to the control group (<0.05). However, there was no significant difference in expression between the pregnant and non-pregnant groups.
Conclusion: , , , and may serve as possible diagnostic markers for PCOS. However, further studies on a larger population are needed to validate this finding.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10510482 | PMC |
http://dx.doi.org/10.22038/IJBMS.2023.67564.14806 | DOI Listing |
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