TMPRSS2 Suppresses Metastasis in Endometriosis-Associated Ovarian Cancer: A Multi-Gene Prognostic Signature Construction and Functional Validation

TMPRSS2 Suppresses Metastasis in Endometriosis-Associated Ovarian Cancer: A Multi-Gene Prognostic Signature Construction and Functional Validation | 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 TMPRSS2 Suppresses Metastasis in Endometriosis-Associated Ovarian Cancer: A Multi-Gene Prognostic Signature Construction and Functional Validation Sipei Nie, Siyue Ren, Na Ni, Qian Zhu, Hongguo Dong, Qiaoling Liu, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-10110898/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Endometriosis (EMS) is a chronic and refractory disease affecting women of reproductive age, and it carries an increased risk of developing endometriosis-associated ovarian cancer (EAOC). Currently, highly specific biomarkers are lacking for the early identification of EAOC high-risk patients among those with EMS. This study aimed to identify candidate molecules and elucidate the mechanisms of malignant transformation from EMS to EAOC. By applying multiple bioinformatics methods on GSE157153 and GSE73614 datasets, we identified essential genes associated with EAOC. Then we built an EAOC-associated risk signature to evaluate patient prognosis. Cellular experiments and animal assays were performed to validate the gene function and molecular mechanism. We identified three EAOC-associated genes (ESRP2, RAB3D, and SPINT1) with high diagnostic value through LASSO and SVM-RFE algorithms. Extracellular matrix (ECM) remodeling was found to play a significant role in EAOC progression. Subsequently, a six‑gene risk signature (GAP43, RBBP8, ERCC6L, CST7, CNPY2, and TMPRSS2) was constructed and demonstrated strong prognostic predictive ability. Among these genes, we focused on TMPRSS2 and investigated its molecular function both in vitro and in vivo. Our results provide a reliable risk model for EAOC, and demonstrate that TMPRSS2 suppresses metastatic capacity in EAOC cells by modulating the EMT process. These findings provide a novel theoretical basis for understanding EAOC pathogenesis and may facilitate the development of targeted therapeutic strategies. Endometriosis-associated ovarian cancer (EAOC) Endometriosis (EMS) TMPRSS2 Gene risk-signature Extracellular matrix (ECM) Full Text Additional Declarations No competing interests reported. Supplementary Files SupplementaryTable1.docx Supplementaryfig1.tif Supplementaryfig2.tif Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 04 Jul, 2026 Reviewers invited by journal 23 Jun, 2026 Editor assigned by journal 23 Jun, 2026 Submission checks completed at journal 23 Jun, 2026 First submitted to journal 22 Jun, 2026 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-10110898","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":665769244,"identity":"4dff97fe-1f52-4c18-8d5c-d8a5b2090504","order_by":0,"name":"Sipei Nie","email":"","orcid":"","institution":"Women and Children's Hospital of Chongqing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Sipei","middleName":"","lastName":"Nie","suffix":""},{"id":665769246,"identity":"7402733d-c6bc-4880-a45e-c820128aab4b","order_by":1,"name":"Siyue Ren","email":"","orcid":"","institution":"Affiliated Jiangning Hospital of Nanjing 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