Neutrophil Extracellularr Trap-Associated Genes Define Molecular Subtypes and Immune Microenvironment in Pancreatic Ductal Adenocarcinoma

Neutrophil Extracellularr Trap-Associated Genes Define Molecular Subtypes and Immune Microenvironment in Pancreatic Ductal Adenocarcinoma | 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 Neutrophil Extracellularr Trap-Associated Genes Define Molecular Subtypes and Immune Microenvironment in Pancreatic Ductal Adenocarcinoma Xinglong Wang, Kai Chen, Xiaodong Tian This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8278458/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Background: Pancreatic ductal adenocarcinoma (PDAC) is an aggressive cancer with poor progno-sis. Neutrophil extracellular traps (NETs) influence the tumor microenvironment and promote PDAC progression, yet their diagnostic relevance and roles in molecular subtyping remain insufficiently defined. Methods: Six GEO transcriptomic datasets were integrated, normalized, and batch-corrected to identify differentially expressed genes (DEGs). Candidate NETs-related genes were obtained by intersecting DEGs, key WGCNA module genes, and NETs genes curated from GeneCards and the literature. A diagnostic model was built using 113 combinations of machine-learning algorithms and validated in independent GEO datasets and the TCGA-PAAD cohort. Molecular subtypes were identified with ConsensusClusterPlus and characterized using ESTIMATE, CIBERSORT, TIDE, and immune checkpoint analyses. Single-cell RNA-seq data from 15 PDAC samples were used to explore gene localization and functional pathways. Results: We identified 749 DEGs and one PDAC-associated WGCNA module, leading to 22 can-didate genes and eight core NETs-related genes (CARD11, CXCL10, IL1A, ITGA2, LAMC2, MYC, SLC2A1, XDH). The Lasso+glmBoost model showed strong diagnostic accuracy across all datasets (AUC 0.919–0.998). Two molecular subtypes (C1 and C2) were defined: C2 exhibited stronger immune infiltration and better survival, while C1 showed elevated TIDE scores, more regulatory T cells, and enhanced immune evasion. Single-cell analyses revealed predominant expression of NETs core genes in ductal cells, enriched in epithelial–mesenchymal transition (EMT) and pro-tumorigenic pathways. Conclusions: This study identifies eight NETs-related diagnostic genes and proposes a robust diagnostic model and molecular subtyping system that capture PDAC heterogeneity and provide insights for precision immunotherapy. Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 21 Jan, 2026 Reviews received at journal 17 Jan, 2026 Reviews received at journal 10 Jan, 2026 Reviewers agreed at journal 08 Jan, 2026 Reviewers agreed at journal 06 Jan, 2026 Reviewers invited by journal 06 Jan, 2026 Editor assigned by journal 12 Dec, 2025 Submission checks completed at journal 11 Dec, 2025 First submitted to journal 11 Dec, 2025 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. 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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-8278458","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":570854129,"identity":"341492a4-af55-4935-88cb-def214dc9094","order_by":0,"name":"Xinglong Wang","email":"","orcid":"","institution":"Peking University First Hospital","correspondingAuthor":false,"prefix":"","firstName":"Xinglong","middleName":"","lastName":"Wang","suffix":""},{"id":570854130,"identity":"f070cdc4-032c-4df7-8c9b-2181011fa3df","order_by":1,"name":"Kai Chen","email":"","orcid":"","institution":"Peking University First 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Adenocarcinoma\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"dion","sideBox":"Learn more about [Discover Oncology](https://www.springer.com/12672)","snPcode":"","submissionUrl":"","title":"Discover Oncology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-8278458/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8278458/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003ePancreatic ductal adenocarcinoma (PDAC) is an aggressive cancer with poor progno-sis. Neutrophil extracellular traps (NETs) influence the tumor microenvironment and promote PDAC progression, yet their diagnostic relevance and roles in molecular subtyping remain insufficiently defined.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eSix GEO transcriptomic datasets were integrated, normalized, and batch-corrected to identify differentially expressed genes (DEGs). Candidate NETs-related genes were obtained by intersecting DEGs, key WGCNA module genes, and NETs genes curated from GeneCards and the literature. A diagnostic model was built using 113 combinations of machine-learning algorithms and validated in independent GEO datasets and the TCGA-PAAD cohort. Molecular subtypes were identified with ConsensusClusterPlus and characterized using ESTIMATE, CIBERSORT, TIDE, and immune checkpoint analyses. Single-cell RNA-seq data from 15 PDAC samples were used to explore gene localization and functional pathways.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eWe identified 749 DEGs and one PDAC-associated WGCNA module, leading to 22 can-didate genes and eight core NETs-related genes (CARD11, CXCL10, IL1A, ITGA2, LAMC2, MYC, SLC2A1, XDH). The Lasso+glmBoost model showed strong diagnostic accuracy across all datasets (AUC 0.919–0.998). Two molecular subtypes (C1 and C2) were defined: C2 exhibited stronger immune infiltration and better survival, while C1 showed elevated TIDE scores, more regulatory T cells, and enhanced immune evasion. Single-cell analyses revealed predominant expression of NETs core genes in ductal cells, enriched in epithelial–mesenchymal transition (EMT) and pro-tumorigenic pathways.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eThis study identifies eight NETs-related diagnostic genes and proposes a robust diagnostic model and molecular subtyping system that capture PDAC heterogeneity and provide insights for precision immunotherapy.\u003c/p\u003e","manuscriptTitle":"Neutrophil Extracellularr Trap-Associated Genes Define Molecular Subtypes and Immune Microenvironment in Pancreatic Ductal Adenocarcinoma","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-08 05:11:50","doi":"10.21203/rs.3.rs-8278458/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-01-21T08:10:15+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-17T07:30:22+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-11T00:06:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"117817295820971604940794161673355506315","date":"2026-01-08T14:21:39+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"76198156430469190567803392998486928878","date":"2026-01-06T14:16:34+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-06T13:24:29+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-13T04:34:17+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-11T16:00:30+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Oncology","date":"2025-12-11T15:50:13+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"dion","sideBox":"Learn more about [Discover Oncology](https://www.springer.com/12672)","snPcode":"","submissionUrl":"","title":"Discover Oncology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"dbedbab7-75f8-469a-a654-557a87f96789","owner":[],"postedDate":"January 8th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-01-28T10:00:16+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-08 05:11:50","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8278458","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8278458","identity":"rs-8278458","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}