Morphological profiling of T cells predicts clinical response to VLA-4-targeting natalizumab therapy in patients with multiple sclerosis

Morphological profiling of T cells predicts clinical response to VLA-4-targeting natalizumab therapy in patients with multiple sclerosis | 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 Article Morphological profiling of T cells predicts clinical response to VLA-4-targeting natalizumab therapy in patients with multiple sclerosis Beatriz Chaves, Juan Carlo Santos e Silva, Helder Nakaya, Matheus Almeida, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4536459/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 01 Jul, 2025 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Abstract Despite the efficacy of natalizumab in Multiple Sclerosis (MS) treatment, approximately 30% of patients do not respond favorably. Individual heterogeneity of T-cell response to VLA-4 natalizumab-mediated blockade may underlie disparities in treatment efficacy. Here, a high-content cell imaging (HCI) pipeline was implemented to profile the in vitro effects of natalizumab on VLA-4-stimulated leukocytes from MS patients prior to treatment. Unsupervised clustering of image data partially discriminated non-responder MS patients based on morphology, F-actin organization, and signaling-related features in CD8+ T cells. Treatment response was assessed through a Random Forest approach with predictive performance of 91% for a discovery cohort and 70% for a validation cohort. Unfavorable treatment response was associated with the inefficacy of natalizumab to impair the ability of pretreated CD8+ T cells to spread over VCAM-1. Our study unveils that CD8+ T cells from individual MS patients display heterogeneous susceptibility to natalizumab in vitro and highlights the potential of HCI-based pretreatment monitoring to assist individualized treatment prescription. Health sciences/Biomarkers/Predictive markers Biological sciences/Cell biology/Cytoskeleton/Actin Health sciences/Neurology/Neurological disorders/Multiple sclerosis Biological sciences/Immunology/Immunotherapy Biological sciences/Cell biology/Cell migration/Integrin signalling Multiple sclerosis T cells VLA-4 natalizumab high-content cell imaging pretreatment testing of drug efficacy Full Text Additional Declarations There is NO Competing Interest. Supplementary Files ChavesSupplMaterialsubmission20240605NatComms.pdf Supplementary Dataset 1 Cite Share Download PDF Status: Published Journal Publication published 01 Jul, 2025 Read the published version in Nature Communications → 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. 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-4536459","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":313239444,"identity":"a04ddfc6-ecb7-4d7e-a7cf-307b81d44d73","order_by":0,"name":"Beatriz 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