Zhang Yan, Chen Xiujuan, Lin Yuan, Liu Xiaoqing, Xiong Xiumei
Department of Obstetrics and Gynecology, Fujian Maternity and Child Health Hospital College of Clinical Medicine for Obstetrics Gynecology and Pediatrics, Fujian Medical University, Fuzhou, China.
Front Mol Biosci. 2025 Jan 9;11:1504015. doi: 10.3389/fmolb.2024.1504015. eCollection 2024.
Polycystic ovary syndrome (PCOS) is a common endocrine and metabolic condition impacting millions of women worldwide. This study sought to identify granulosa cell endoplasmic reticulum stress (GCERS)-related differentially expressed genes (DEGs) between women with PCOS and those without PCOS using bioinformatics and to investigate the related molecular mechanisms.
Two datasets were downloaded from GEO and analysed using the limma package to identify DEGs in two groups-PCOS and normal granulosa cells. Enrichment analyses, including GO, KEGG, and GSEA, were then conducted on the DEGs. Differential immune infiltration was assessed using CIBERSORT and correlations with immune cell biomarkers were evaluated. Networks for protein-protein interactions, transcription factor-target genes, miRNA-target genes, and drug-target genes were constructed and visualized using Cytoscape to identify key hub gene nodes. Finally, key genes were analysed for differential expression and correlated.
Overall, 127 co-DEGs were identified in the two datasets. Our study revealed that these DEGs were primarily associated with cell cycle arrest, p53-mediated signal transduction, drug response, and gland development, with molecular functions enriched in growth factor binding, collagen binding, and receptor protein kinase activity. GSEA revealed that the co-DEGs were primarily associated with immune and inflammatory pathways. Eleven hub genes-, , , , , , , , , , and -were identified through the PPI, TF target genes, miRNA target genes, and drug target gene networks.
We identified several crucial genes and pathways linked to the onset and development of PCOS. Our findings offer a clear connection between PCOS and GCERS, clarify the molecular mechanisms driving PCOS progression, and offer new perspectives for discovering valuable therapeutic targets and potential biomarkers for the condition.
多囊卵巢综合征（PCOS）是一种常见的内分泌和代谢疾病，影响着全球数百万女性。本研究旨在利用生物信息学方法，识别PCOS女性与非PCOS女性之间颗粒细胞内质网应激（GCERS）相关的差异表达基因（DEGs），并研究相关分子机制。
从GEO下载两个数据集，使用limma软件包进行分析，以识别PCOS组和正常颗粒细胞组中的DEGs。然后对这些DEGs进行包括GO、KEGG和GSEA在内的富集分析。使用CIBERSORT评估差异免疫浸润，并评估与免疫细胞生物标志物的相关性。使用Cytoscape构建并可视化蛋白质-蛋白质相互作用、转录因子-靶基因、miRNA-靶基因和药物-靶基因网络，以识别关键的枢纽基因节点。最后，对关键基因进行差异表达分析和相关性分析。
总体而言，在两个数据集中共鉴定出127个共同的DEGs。我们的研究表明，这些DEGs主要与细胞周期停滞、p53介导的信号转导、药物反应和腺体发育相关，分子功能富集于生长因子结合、胶原蛋白结合和受体蛋白激酶活性。GSEA显示，共同的DEGs主要与免疫和炎症途径相关。通过蛋白质-蛋白质相互作用、转录因子靶基因、miRNA靶基因和药物靶基因网络鉴定出11个枢纽基因，分别为……（此处原文未完整列出基因名称）。
我们鉴定出了几个与PCOS发病和发展相关的关键基因和途径。我们的研究结果明确了PCOS与GCERS之间的联系，阐明了驱动PCOS进展的分子机制，并为发现该疾病有价值的治疗靶点和潜在生物标志物提供了新的视角。
