Mapping the immune landscape in metastatic melanoma reveals localized cell-cell interactions correlating to immunotherapy responsiveness

Mapping the immune landscape in metastatic melanoma reveals localized cell-cell interactions correlating to immunotherapy responsiveness | 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 Mapping the immune landscape in metastatic melanoma reveals localized cell-cell interactions correlating to immunotherapy responsiveness Francesca Bosisio, Asier Antoranz, Yannick Van Herck, Maddalena Bolognesi, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1236531/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 While immune checkpoint-based immunotherapy (ICI) shows spectacular clinical results in cancer patients, only a subset of the these respond favorably to such treatment. Response to ICI is dictated by the integration of complex networks of cellular interactions between malignant and non-malignant cells. Although new insights into the mechanisms that modulate the pivotal anti-tumoral activity of cytotoxic T-cells (Tcy) have recently been gained, much of what we have learned is based on single-cell analyses of dissociated tumor samples; therefore, we lack critical information about the spatial distribution of the relevant cell types. Here, we used multiplexed immunohistochemistry to spatially characterize the immune landscape of metastatic melanoma from responders vs non-responders to ICI. By creating such high-dimensional pathology maps, we show that Tcy gradually evolve towards an exhausted phenotype as they approach and infiltrate the tumor. Moreover, our analysis revealed a key cellular interaction network that functionally links Tcy and PD-L1+ macrophages. Critically, mapping the respective spatial distribution of these two cell populations predict response to anti-PD-1 immunotherapy with high confidence. We conclude that baseline measurements of the spatial context should be integrated in the design of predictive biomarkers to identify patients likely to benefit from ICI. Full Text Additional Declarations There is NO Competing Interest. Supplementary Files SupplementaryTable1Overviewclinicalsamplesincludedforanalysis.docx Supplementary Table 1 SupplementaryTable2OverviewantibodiesusedforMILAN.docx Supplementary Table 2 SupplementaryTable3Cellcomposition.docx Supplementary Table 3 SupplementaryTable4GLSNanostring.xlsx Supplementary Table 4 SupplementaryTable5GSANanostring.xlsx Supplementary Table 5 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. 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-1236531","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":79412193,"identity":"cd974534-d1f9-4e12-932c-b2107bad5023","order_by":0,"name":"Francesca 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