Clara Riski Amanda , Fadilah , Andon Hestiantoro , Raden Muharam , Dwi Anita Suryandari , Togas Tulandi , Asmarinah
{"title":"综合生物信息分析揭示了子宫内膜异位症的基因特征、表观遗传作用和调控网络。","authors":"Clara Riski Amanda , Fadilah , Andon Hestiantoro , Raden Muharam , Dwi Anita Suryandari , Togas Tulandi , Asmarinah","doi":"10.1016/j.ejogrb.2024.09.026","DOIUrl":null,"url":null,"abstract":"<div><h3>Objectives</h3><div>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.</div></div><div><h3>Methods</h3><div>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 DEGs, miRNA, and lncRNA was constructed using STRING and Cytoscape, and then the top 15 hub genes in the PPI network were identified using CytoHubba.</div></div><div><h3>Results</h3><div>A total of 551 common DEGs were identified from four or more studies, including 292 upregulated and 259 downregulated genes. Besides alterations in protein-coding genes (mRNA), 16 miRNA (5 upregulated and 11 downregulated) were identified from all studies, along with 12 lncRNA (10 upregulated and 2 downregulated) 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.</div></div><div><h3>Conclusions</h3><div>Our in-depth bioinformatics analysis reveals the critical molecular basis underlying endometriosis. The role of identified hub genes, miRNA, and lncRNA may also have an opportunity to be explored as potential biomarkers for endometriosis diagnosis and prognosis.</div></div>","PeriodicalId":11975,"journal":{"name":"European journal of obstetrics, gynecology, and reproductive biology","volume":"302 ","pages":"Pages 216-224"},"PeriodicalIF":2.1000,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Integrated bioinformatic analysis reveals the gene signatures, epigenetic roles, and regulatory networks in endometriosis\",\"authors\":\"Clara Riski Amanda , Fadilah , Andon Hestiantoro , Raden Muharam , Dwi Anita Suryandari , Togas Tulandi , Asmarinah\",\"doi\":\"10.1016/j.ejogrb.2024.09.026\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Objectives</h3><div>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.</div></div><div><h3>Methods</h3><div>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 DEGs, miRNA, and lncRNA was constructed using STRING and Cytoscape, and then the top 15 hub genes in the PPI network were identified using CytoHubba.</div></div><div><h3>Results</h3><div>A total of 551 common DEGs were identified from four or more studies, including 292 upregulated and 259 downregulated genes. Besides alterations in protein-coding genes (mRNA), 16 miRNA (5 upregulated and 11 downregulated) were identified from all studies, along with 12 lncRNA (10 upregulated and 2 downregulated) 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.</div></div><div><h3>Conclusions</h3><div>Our in-depth bioinformatics analysis reveals the critical molecular basis underlying endometriosis. The role of identified hub genes, miRNA, and lncRNA may also have an opportunity to be explored as potential biomarkers for endometriosis diagnosis and prognosis.</div></div>\",\"PeriodicalId\":11975,\"journal\":{\"name\":\"European journal of obstetrics, gynecology, and reproductive biology\",\"volume\":\"302 \",\"pages\":\"Pages 216-224\"},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2024-09-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"European journal of obstetrics, gynecology, and reproductive biology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0301211524005219\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"OBSTETRICS & GYNECOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"European journal of obstetrics, gynecology, and reproductive biology","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0301211524005219","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"OBSTETRICS & GYNECOLOGY","Score":null,"Total":0}
Integrated bioinformatic analysis reveals the gene signatures, epigenetic roles, and regulatory networks in endometriosis
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 DEGs, miRNA, and lncRNA was constructed using STRING and Cytoscape, and then the top 15 hub genes in the PPI network were identified using CytoHubba.
Results
A total of 551 common DEGs were identified from four or more studies, including 292 upregulated and 259 downregulated genes. Besides alterations in protein-coding genes (mRNA), 16 miRNA (5 upregulated and 11 downregulated) were identified from all studies, along with 12 lncRNA (10 upregulated and 2 downregulated) 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 role of identified hub genes, miRNA, and lncRNA may also have an opportunity to be explored as potential biomarkers for endometriosis diagnosis and prognosis.
期刊介绍:
The European Journal of Obstetrics & Gynecology and Reproductive Biology is the leading general clinical journal covering the continent. It publishes peer reviewed original research articles, as well as a wide range of news, book reviews, biographical, historical and educational articles and a lively correspondence section. Fields covered include obstetrics, prenatal diagnosis, maternal-fetal medicine, perinatology, general gynecology, gynecologic oncology, uro-gynecology, reproductive medicine, infertility, reproductive endocrinology, sexual medicine and reproductive ethics. The European Journal of Obstetrics & Gynecology and Reproductive Biology provides a forum for scientific and clinical professional communication in obstetrics and gynecology throughout Europe and the world.