Li Lu, Sun Bo, Sun Yingpu
Center for Reproductive Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Henan Key Laboratory of Reproduction and Genetics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Front Genet. 2022 Sep 20;13:998417. doi: 10.3389/fgene.2022.998417. eCollection 2022.
Endometriosis (EMs), one of the most common gynecological diseases, seriously affects the health and wellness of women; however, the underlying pathogenesis remains unclear. This study focused on dysregulated genes and their predicted transcription factors (TFs) and miRNAs, which may provide ideas for further mechanistic research. The microarray expression dataset GSE58178, which included six ovarian endometriosis (OE) samples and six control samples, was downloaded from the Gene Expression Omnibus (GEO) to identify differentially expressed genes (DEGs). Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to study the cellular and organism-level functions of DEGs. The protein-protein interaction (PPI) network was built and visualized using Cytoscape, and modules and hub genes were explored using various algorithms. Furthermore, we predicted miRNAs and TFs of hub genes using online databases, and constructed the TF-miRNA-hub gene network. There were 124 upregulated genes and 66 downregulated genes in EMs tissues. GO enrichment analysis showed that DEGs were concentrated in reproductive structure development and collagen-containing extracellular matrix, while KEGG pathway analysis showed that glycolysis/gluconeogenesis and central carbon metabolism in cancer require further exploration. Subsequently, HIF1A, LDHA, PGK1, TFRC, and CD9 were identified as hub genes, 22 miRNAs and 34 TFs were predicted to be upstream regulators of hub genes, and these molecules were pooled together. In addition, we found three key feedback loops in the network, MYC-miR-34a-5p-LDHA, YY1-miR-155-5p-HIF1A, and RELA-miR-93-5p-HIF1A, which may be closely related to OE development. Taken together, our study structured a TF-miRNA-hub gene network to decipher the molecular mechanism of OE, which may provide novel insights for clinical diagnosis and treatment.
子宫内膜异位症（EMs）是最常见的妇科疾病之一，严重影响女性的健康；然而，其潜在的发病机制仍不清楚。本研究聚焦于失调基因及其预测的转录因子（TFs）和微小RNA（miRNAs），这可能为进一步的机制研究提供思路。从基因表达综合数据库（GEO）下载了包含六个卵巢子宫内膜异位症（OE）样本和六个对照样本的微阵列表达数据集GSE58178，以鉴定差异表达基因（DEGs）。进行基因本体（GO）富集分析和京都基因与基因组百科全书（KEGG）通路分析，以研究DEGs的细胞和生物体水平功能。使用Cytoscape构建并可视化蛋白质-蛋白质相互作用（PPI）网络，并使用各种算法探索模块和枢纽基因。此外，我们使用在线数据库预测枢纽基因的miRNAs和TFs，并构建TF-miRNA-枢纽基因网络。EMs组织中有124个上调基因和66个下调基因。GO富集分析表明，DEGs集中在生殖结构发育和含胶原细胞外基质中，而KEGG通路分析表明，癌症中的糖酵解/糖异生和中心碳代谢需要进一步探索。随后，鉴定出HIF1A、LDHA、PGK1、TFRC和CD9为枢纽基因，预测22个miRNAs和34个TFs为枢纽基因的上游调节因子，并将这些分子汇集在一起。此外，我们在网络中发现了三个关键反馈环，即MYC-miR-34a-5p-LDHA、YY1-miR-155-5p-HIF1A和RELA-miR-93-5p-HIF1A，它们可能与OE的发展密切相关。综上所述，我们的研究构建了一个TF-miRNA-枢纽基因网络来解读OE的分子机制，这可能为临床诊断和治疗提供新的见解。
