LGALS2 and EGR1: markers of endometriosis for predictive, preventive and personalized medicine

LGALS2 and EGR1: markers of endometriosis for predictive, preventive and personalized medicine | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article LGALS2 and EGR1: markers of endometriosis for predictive, preventive and personalized medicine Hong Jiang, Qinkun Sun, Zhixiong Huang, Hui Chen, Lihong Chen, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2726180/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Endometriosis (EM) is a chronic gynecological disorder that causes infertility and chronic pelvic pain. The aim of the current study was to identify markers of efferocytosis with utility for EM diagnosis.RNA sequencing profile and single-cell sequencing (scRNA-seq) data were collated from the Gene Expression Omnibus (GEO) database and 46 efferocytosis-related genes (ERGs) from Genecards. Results of single-cell, differential expression and Weighted Gene Co-expression Network Analysis (WGCNA) were combined into a Venn diagram to identify 41 intersecting genes. LGALS2, EGR1 and CLINT1 were shown to be key EM markers by least absolute shrinkage and selection operator (LASSO) and support vector machine-recursive feature elimination (SVM-RFE) algorithms. Area under the curve (AUC) values were 0.9 for LGALS2, 0.81 for EGR1 and 0.76 for CLINT1, indicating good diagnostic efficacy. Functional annotation analysis revealed the markers to be enriched in cell cycle, DNA repair, neuroactive ligand-receptor interactions, cell cycle, chromosomal segregation and other pathways. Drug-gene interaction network indicated that beta-D-glucose, pseudoephedrine and fostamatinib were potential therapeutic agents, exposing the possibility of personalized medicine for EM. RT-qPCR showed LGALS2 and EGR1 to be more highly expressed in ectopic than in eutopic endometrium. LGALS2 and EGR1 are introduced as potential novel targets for risk prediction, non-invasive diagnosis and health care personalization in EM. The potential for personalized medicine (PPPM) to treat EM patients is illuminated. endometriosis scRNA ectopic eutopic personalized medicine biomarkers Full Text Supplementary Files SupplementaryInformation.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-2726180","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":190190870,"identity":"24fcb0b8-0b0c-40fa-bbe1-01cadd4d686b","order_by":0,"name":"Hong 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The aim of the current study was to identify markers of efferocytosis with utility for EM diagnosis.RNA sequencing profile and single-cell sequencing (scRNA-seq) data were collated from the Gene Expression Omnibus (GEO) database and 46 efferocytosis-related genes (ERGs) from Genecards. Results of single-cell, differential expression and Weighted Gene Co-expression Network Analysis (WGCNA) were combined into a Venn diagram to identify 41 intersecting genes. LGALS2, EGR1 and CLINT1 were shown to be key EM markers by least absolute shrinkage and selection operator (LASSO) and support vector machine-recursive feature elimination (SVM-RFE) algorithms. Area under the curve (AUC) values were 0.9 for LGALS2, 0.81 for EGR1 and 0.76 for CLINT1, indicating good diagnostic efficacy. Functional annotation analysis revealed the markers to be enriched in cell cycle, DNA repair, neuroactive ligand-receptor interactions, cell cycle, chromosomal segregation and other pathways. Drug-gene interaction network indicated that beta-D-glucose, pseudoephedrine and fostamatinib were potential therapeutic agents, exposing the possibility of personalized medicine for EM. RT-qPCR showed LGALS2 and EGR1 to be more highly expressed in ectopic than in eutopic endometrium. LGALS2 and EGR1 are introduced as potential novel targets for risk prediction, non-invasive diagnosis and health care personalization in EM. 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