Transcriptional states of lung cancer microenvironment reveal macrophage subtype dynamics linked to disease progression

Transcriptional states of lung cancer microenvironment reveal macrophage subtype dynamics linked to disease progression | 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 Transcriptional states of lung cancer microenvironment reveal macrophage subtype dynamics linked to disease progression Yasin Kaymaz, Duygu Keremitci, Ozlem Tuna, Aissa Houdjedj, Hilal Kazan This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6719524/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 The tumor microenvironment (TME) plays a pivotal role in shaping immune responses and therapeutic outcomes in lung cancer, yet the diversity and functional specialization of tumor-associated macrophages (TAMs) remain poorly resolved. Here, we present a refined classification of TAM subtypes across large cohorts of cancer datasets using integrative analysis of single-cell RNA sequencing, spatial transcriptomics, and clinical datasets from lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). By combining cell-based gene scoring with hierarchical classification, we defined seven macrophage subtypes—each with distinct transcriptional programs and abundances. Notably, lipid-associated TAMs expand with disease progression and exhibit immunosuppressive and pro-tumorigenic features, while tissue-resident macrophages decline. Spatial and survival analyses reveal that an increased LA/RTM ratio correlates with advanced disease and poor prognosis. Given that spatial transcriptomic assays rely on deconvolution techniques to infer cell type compositions, accurate gene expression signatures are essential, especially for fine-grained sub-populations of TAMs. Our refined subtype-specific signatures address this bottleneck and enhance the resolution of spatial mapping efforts. These findings offer new insights into macrophage heterogeneity and highlight LA_TAMs as potential biomarkers and therapeutic targets in lung cancer. Biological sciences/Genetics/Gene expression Biological sciences/Immunology/Innate immune cells/Monocytes and macrophages/Alveolar macrophages Figures Figure 1 Figure 2 Figure 3 Figure 4 Full Text Additional Declarations There is NO conflict of interest to disclose. We declare no conflict of interest Supplementary Files Supplemantfigures.pdf Supplemental Figures 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. 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-6719524","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":460096428,"identity":"857223f7-e145-426c-8847-92bc12e42340","order_by":0,"name":"Yasin Kaymaz","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7UlEQVRIie2PsQrCMBRFWwJxCbpaVPQTCt0V/6ShoEsHwUkcFAT9BX/C9c2FQLMUuga6GAVdHBQRdDPRPdVNMCdwX4Z7eInjWCw/SqKOxt2qINVvFORrBX+6R4Prrywr+5xLNsq6dLPih8kt7jaxg+ROmJQs9tlaRBSycFC0IFIPw0EQm5Qkdhg5IwpJmBYeIKUQ3DAq+XGrlBmFXC7HHsw+UEToMyIYBRFh9wKsXPHESSkZD0AcUMMFTjAq+Us1H+6vJJ22IB/KywOmvVplIfcmpZO8Z3+uAhF9RYa6pj1/z54O917Stlgslv/kCdAKUyrK31tcAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-9725-7536","institution":"Ege University","correspondingAuthor":true,"prefix":"","firstName":"Yasin","middleName":"","lastName":"Kaymaz","suffix":""},{"id":460096429,"identity":"5969bee2-e911-48b0-afe7-2fd50f4e6a40","order_by":1,"name":"Duygu Keremitci","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Duygu","middleName":"","lastName":"Keremitci","suffix":""},{"id":460096430,"identity":"954feca1-7e56-4d9d-afad-569280ed37f0","order_by":2,"name":"Ozlem Tuna","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Ozlem","middleName":"","lastName":"Tuna","suffix":""},{"id":460096431,"identity":"2f1e5b5f-eb95-4544-a06b-920bfa71e3d4","order_by":3,"name":"Aissa Houdjedj","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Aissa","middleName":"","lastName":"Houdjedj","suffix":""},{"id":460096432,"identity":"ba1ed551-1c97-4748-890a-7a64800e649e","order_by":4,"name":"Hilal Kazan","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Hilal","middleName":"","lastName":"Kazan","suffix":""}],"badges":[],"createdAt":"2025-05-21 21:25:33","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6719524/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6719524/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":83319238,"identity":"c904c933-8d08-4c8e-be89-0090cc4a2f1d","added_by":"auto","created_at":"2025-05-23 03:07:45","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1141151,"visible":true,"origin":"","legend":"\u003cp\u003eIdentification and classification of macrophage subtypes in the lung cancer single-cell atlas. A total of 1.3 million cells from a comprehensive lung cancer single-cell atlas were re-analyzed, and macrophages \u0026nbsp;from LUAD, LUSC, and healthy donor samples were extracted (n = 179,689 cells). AUCell-assisted scoring for 7 \u0026nbsp;predefined macrophage subtypes helped to detect the top 250 high-scoring cells per subtype, which provided reference \u0026nbsp;data to train a hierarchical random forest classifier (HieRFIT). The out-of-bag classification accuracies are noted on \u0026nbsp;each branching point of the de novo hierarchical tree created by the tool (10x-cross validation). Following the classification of all macrophages, downstream compositional and pseudo-bulk-based differential gene expression \u0026nbsp;analyses were performed.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-6719524/v1/b551ad8b9496f0a00433d1f4.png"},{"id":83319235,"identity":"854dfce9-988f-4404-97b8-eca28bc08ded","added_by":"auto","created_at":"2025-05-23 03:07:45","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":539523,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution and polarization signatures of macrophage subtypes across lung cancer progression. A) Clustering heatmap of known marker gene expression profiles across tumor-associated macrophage subtypes. Expression values are scaled to z-scores across all cells in each group. B) Heatmap of polarization scores (M1 and \u0026nbsp;M2) across macrophage subtypes. C) Boxplot showing the proportions of macrophage subtypesin each sample among \u0026nbsp;all macrophages stratified by disease status (non-cancer, early stage, and advanced stage). D) Subtype proportions \u0026nbsp;further stratified by UICC cancer stage (non-cancer through stage IV, including primary and metastatic tumors). E) \u0026nbsp;Density plots showing the relationship between lipid-associated and tissue-resident macrophages across UICC stages. Higher proportions of tissue-resident macrophages dominate non-cancerous tissues, while advanced stages show \u0026nbsp;enrichment of lipid-associated macrophages.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-6719524/v1/33cada7516b12a9ebc7e3be7.png"},{"id":83319239,"identity":"ff0ff933-bbc6-46c2-a60a-8715ea994a80","added_by":"auto","created_at":"2025-05-23 03:07:45","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":755085,"visible":true,"origin":"","legend":"\u003cp\u003eSpatial localization and tissue-level validation of macrophage subtypes in lung tissues. Spatial transcriptomics maps showing predictions of cell type composition in (A) healthy donor lung tissue, (B) a lung \u0026nbsp;adenocarcinoma tissue. Cell types were deconvoluted using reference signatures, and macrophage-containing spots \u0026nbsp;are shown separately on the right panels. C) Boxplots show the proportions of seven TAM subtypes across three tissue \u0026nbsp;types: healthy, background, and tumor. Each point represents a single spatial spot from the dataset. Statistical \u0026nbsp;comparisons were performed using the Kruskal–Wallis test, followed by Dunn's post-hoc test with Bonferroni \u0026nbsp;correction (* p \u0026lt; 0.05, ** p \u0026lt; 0.01, *** p \u0026lt; 0.001). D) Density plots comparing the ratio of lipid-associated (LA) to \u0026nbsp;tissue-resident (RTM) macrophages across tissue types for LUAD (left) and LUSC (right).\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-6719524/v1/c6853e9c465e77fbc426f3b5.png"},{"id":83319717,"identity":"d927ecb5-77f3-4153-9a80-f1fbc023aa04","added_by":"auto","created_at":"2025-05-23 03:15:45","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":173201,"visible":true,"origin":"","legend":"\u003cp\u003eLipid-associated and angiogenic TAM signatures are linked to poor prognosis in lung cancer. A) Heatmap showing the average gene expressions (z-scored) of LA_TAM DEGs across TAM subtypes. B) Kaplan– Meier survival curves showing the association between LA_TAM signature scores and patient survival in lung \u0026nbsp;squamous cell carcinoma (top, unfavorable, p=0.00057) and lung adenocarcinoma (bottom, favorable, p=0.012). C) \u0026nbsp;Survival analysis of Angio_TAM signature scores in lung squamous cell carcinoma (top, unfavorable, p=0.0047) and \u0026nbsp;adenocarcinoma (bottom, unfavorable, p=0.034).\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-6719524/v1/2d1ab625c2979b9a44dd2f07.png"},{"id":83832715,"identity":"49028b2e-fb7f-4655-aec4-4d361379e9c6","added_by":"auto","created_at":"2025-06-03 12:19:09","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3344970,"visible":true,"origin":"","legend":"Article File","description":"","filename":"Keremitcietal2025.manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6719524/v1_covered_481e360e-792b-4b9a-990b-0433c0135b28.pdf"},{"id":83319240,"identity":"891e04ab-b990-44fb-9fac-58bd92bfeacd","added_by":"auto","created_at":"2025-05-23 03:07:45","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":8054527,"visible":true,"origin":"","legend":"Supplemental Figures","description":"","filename":"Supplemantfigures.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6719524/v1/a6de3f948fd9af65dd03cbc6.pdf"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e conflict of interest to disclose.\nWe declare no conflict of interest","formattedTitle":"Transcriptional states of lung cancer microenvironment reveal macrophage subtype dynamics linked to disease progression","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6719524/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6719524/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"The tumor microenvironment (TME) plays a pivotal role in shaping immune responses and therapeutic outcomes in lung cancer, yet the diversity and functional specialization of tumor-associated macrophages (TAMs) remain poorly resolved. Here, we present a refined classification of TAM subtypes across large cohorts of cancer datasets using integrative analysis of single-cell RNA sequencing, spatial transcriptomics, and clinical datasets from lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). By combining cell-based gene scoring with hierarchical classification, we defined seven macrophage subtypes—each with distinct transcriptional programs and abundances. Notably, lipid-associated TAMs expand with disease progression and exhibit immunosuppressive and pro-tumorigenic features, while tissue-resident macrophages decline. Spatial and survival analyses reveal that an increased LA/RTM ratio correlates with advanced disease and poor prognosis. Given that spatial transcriptomic assays rely on deconvolution techniques to infer cell type compositions, accurate gene expression signatures are essential, especially for fine-grained sub-populations of TAMs. Our refined subtype-specific signatures address this bottleneck and enhance the resolution of spatial mapping efforts. These findings offer new insights into macrophage heterogeneity and highlight LA_TAMs as potential biomarkers and therapeutic targets in lung cancer.","manuscriptTitle":"Transcriptional states of lung cancer microenvironment reveal macrophage subtype dynamics linked to disease progression","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-23 03:07:40","doi":"10.21203/rs.3.rs-6719524/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7548e818-75d9-4d8c-a7f6-3ee4d4bb71e7","owner":[],"postedDate":"May 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":48876221,"name":"Biological sciences/Genetics/Gene expression"},{"id":48876222,"name":"Biological sciences/Immunology/Innate immune cells/Monocytes and macrophages/Alveolar macrophages"}],"tags":[],"updatedAt":"2025-06-03T12:10:54+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-23 03:07:40","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6719524","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6719524","identity":"rs-6719524","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}