Single cell multiomics unravel the transcription networks controlling the different EMT tumor states

Single cell multiomics unravel the transcription networks controlling the different EMT tumor states | 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 Single cell multiomics unravel the transcription networks controlling the different EMT tumor states Andrea Pérez González, Gabriel Windels, Kevin Bévant, Justine Lengrand, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9426544/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 Epithelial-to-mesenchymal transition (EMT) is a dynamic process during which cells lose their epithelial characteristics and acquire mesenchymal traits. In cancer, EMT is associated with tumor initiation, progression, invasion, metastasis, and therapy resistance. Rather than being a binary state switch, EMT encompasses a spectrum of tumor states with distinct functional properties. However, the transcription factors (TFs) that control the distinct EMT tumor state transitions remain poorly characterized. Here, using multi-omic approaches combining single-cell RNA-seq and single-cell ATAC-seq, we delineate the transcriptomic and chromatin landscapes of distinct EMT states in a mouse model of skin squamous cell carcinoma (SCC). Through CRISPR/Cas9-mediated loss-of-function studies coupled with in vitro and in vivo functional assays, we identify TFs regulating specific EMT states. Klf5 and Pitx1 control the early steps of EMT and are essential for metastasis formation. In contrast, Nfatc1 and Creb3l1 act at later stages of EMT. Similar EMT states and regulatory patterns are found in mouse pancreatic adenocarcinoma and patient derived xenograft of lung adenocarcinoma. Altogether, our study defines the transcriptional and chromatin landscape controlling EMT progression in mouse skin SCC, identifies EMT state-specific TFs and highlights their essential roles in regulating metastasis. Cancer Biology EMT metastasis skin SCC transcriptomics regulation Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Full Text Additional Declarations The authors declare no competing interests. Supplementary Files ExtendeddataPerezGonzalezetal.pdf Extended Data SuplementaryTables.xlsx Supplementary Tables 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. 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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-9426544","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":623631642,"identity":"da1de376-9513-4239-80dc-a02158ae0a4e","order_by":0,"name":"Andrea Pérez González","email":"","orcid":"","institution":"UNIVERSITÉ LIBRE DE BRUXELLES","correspondingAuthor":false,"prefix":"","firstName":"Andrea","middleName":"Pérez","lastName":"González","suffix":""},{"id":623631643,"identity":"09e935ce-9069-4887-a0ac-47bd9c9d982c","order_by":1,"name":"Gabriel Windels","email":"","orcid":"","institution":"UNIVERSITÉ LIBRE DE BRUXELLES","correspondingAuthor":false,"prefix":"","firstName":"Gabriel","middleName":"","lastName":"Windels","suffix":""},{"id":623631644,"identity":"8bfd4131-912a-4ccd-a45e-ac6618818425","order_by":2,"name":"Kevin Bévant","email":"","orcid":"","institution":"UNIVERSITÉ LIBRE DE BRUXELLES","correspondingAuthor":false,"prefix":"","firstName":"Kevin","middleName":"","lastName":"Bévant","suffix":""},{"id":623631645,"identity":"b7a037e7-030c-48a3-bbd8-b0dc67c741eb","order_by":3,"name":"Justine Lengrand","email":"","orcid":"","institution":"UNIVERSITÉ LIBRE DE BRUXELLES","correspondingAuthor":false,"prefix":"","firstName":"Justine","middleName":"","lastName":"Lengrand","suffix":""},{"id":623631646,"identity":"3c8cc8ea-922a-44d0-b4e5-3cc556ffe046","order_by":4,"name":"Sophie Lemaire","email":"","orcid":"","institution":"UNIVERSITÉ LIBRE DE BRUXELLES","correspondingAuthor":false,"prefix":"","firstName":"Sophie","middleName":"","lastName":"Lemaire","suffix":""},{"id":623631647,"identity":"2aa41044-2aaf-40ad-a1bd-0b87286eaf3f","order_by":5,"name":"Virginie Moers","email":"","orcid":"","institution":"UNIVERSITÉ LIBRE DE BRUXELLES","correspondingAuthor":false,"prefix":"","firstName":"Virginie","middleName":"","lastName":"Moers","suffix":""},{"id":623631648,"identity":"c49c62b9-c012-47d6-b9e5-24b3a24b9f42","order_by":6,"name":"Samuel Scozzaro","email":"","orcid":"","institution":"UNIVERSITÉ LIBRE DE BRUXELLES","correspondingAuthor":false,"prefix":"","firstName":"Samuel","middleName":"","lastName":"Scozzaro","suffix":""},{"id":623631649,"identity":"ac4d6519-ee5f-40ec-85ac-2f8059954e4c","order_by":7,"name":"Ulysse Debroux","email":"","orcid":"","institution":"UNIVERSITÉ LIBRE DE BRUXELLES","correspondingAuthor":false,"prefix":"","firstName":"Ulysse","middleName":"","lastName":"Debroux","suffix":""},{"id":623631650,"identity":"d0201a45-187a-41b1-94c8-3e0a19fd875a","order_by":8,"name":"Christine Dubois","email":"","orcid":"","institution":"UNIVERSITÉ LIBRE DE BRUXELLES","correspondingAuthor":false,"prefix":"","firstName":"Christine","middleName":"","lastName":"Dubois","suffix":""},{"id":623631651,"identity":"0874e502-21f4-400c-ad83-822db1cc55f9","order_by":9,"name":"Sebastiaan Vanuytven","email":"","orcid":"","institution":"UNIVERSITÉ LIBRE DE BRUXELLES","correspondingAuthor":false,"prefix":"","firstName":"Sebastiaan","middleName":"","lastName":"Vanuytven","suffix":""},{"id":623631652,"identity":"34007e95-b822-493e-988a-e8735c372cab","order_by":10,"name":"Cédric Blanpain","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA80lEQVRIiWNgGAWjYHACA4YEBoYEPihbjoGdh4GZKC1sULYxAzMxWhjgWhgYEhsIaeFvb9724UENQx4b+9ljD34U3EnfcJj3AHNBBW4tEmeOFc9IOMZQzMaTl27YY/Asd8NhvgTmGWfwuEoixxjoGIbENoYcMwkeg8NALTwGzLxteLTIv4Fq4X9jJvnH4HC6AVjLP3y28EC1SOSYSQNtSYBoacDnl7RihoRjEsVsEm/MjWUMDhvOBPrl8IxjuLXwtx/ezPijxiaPnz/H7OGbP4fl+Y73HnxcUINbC8wyEMEG5x4gqAEK2AgrGQWjYBSMghEJAD91Sdv+xrN9AAAAAElFTkSuQmCC","orcid":"","institution":"UNIVERSITÉ LIBRE DE BRUXELLES","correspondingAuthor":true,"prefix":"","firstName":"Cédric","middleName":"","lastName":"Blanpain","suffix":""}],"badges":[],"createdAt":"2026-04-15 11:52:53","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":true,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":true},"doi":"10.21203/rs.3.rs-9426544/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9426544/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107258993,"identity":"d0e8774e-d135-40cd-affb-17d96575e0ee","added_by":"auto","created_at":"2026-04-19 12:45:09","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1537847,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIdentification of distinct EMT tumor states in genetically induced skin SCC by single cell RNA-seq.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA: Uniform manifold approximation and projection (UMAP) plot of YFP+ tumor cells of the integration of 12 primary skin SCCs presenting different degree of EMT. Cells are colored by their inferred EMT state. B–F: UMAP plots colored by log-normalized expression levels of gene sets corresponding to epithelial (B), canonical EMT (C), early hybrid EMT (D), hybrid EMT (E), and late EMT (F) states. G: UMAP plot colored by the inferred cell-cycle state.\u003c/p\u003e","description":"","filename":"FigmainREV1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9426544/v1/8551857fb0685f9d92a9267d.jpg"},{"id":107483635,"identity":"5b202e4f-fda7-4c05-8763-3c6ea4bd7748","added_by":"auto","created_at":"2026-04-22 02:28:32","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1757975,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePredicted TFs regulating distinct EMT tumor states by SCENIC analysis.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA–B: UMAP plots of the integrated scRNA-seq atlas showing (from left to right): log-normalized expression, activating regulons (positive), and repressive regulons (negative) inferred by SCENIC for predicted transcription factor (TF) regulators associated with the four EMT states. A: Epithelial and early hybrid EMT-associated TFs. B: Hybrid and late EMT-associated TFs.\u003c/p\u003e","description":"","filename":"FigmainREV2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9426544/v1/84d583859aa472297fe3e657.jpg"},{"id":107484671,"identity":"8a8dbb7e-2670-42c1-8b10-166351464d54","added_by":"auto","created_at":"2026-04-22 02:32:42","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":884944,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTF binding motif enrichment in differentially accessible chromatin regions across distinct EMT states.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA: UMAP plot of YFP+ tumor cells of one representative primary tumor profiled by 10X Multiome (RNA modality) colored by the inferred EMT state (n=3). B: Single cell ATAC-seq profile of \u003cem\u003eEpcam\u003c/em\u003e in epithelial, early hybrid, hybrid and late EMT states, showing the appearance of open chromatin regions in the epithelial state that are closed in early hybrid, hybrid and late EMT states. C: Enriched TF motifs found in the single cell ATAC-seq peaks in each EMT state using known motifs; **de novo motifs, together with the list of TF family members that are expressed in the same corresponding tumor state.\u003c/p\u003e","description":"","filename":"FigmainREV3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9426544/v1/0ae641d2127dc213287dd3b1.jpg"},{"id":107484931,"identity":"680ddbfe-5ea4-4408-b2b7-c21ea058d717","added_by":"auto","created_at":"2026-04-22 02:33:19","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":767424,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSCENIC+ analysis of combined single cell RNA and ATAC-seq predicts key regulators of distinct EMT tumor states.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA: Heat map/dot-plot showing TF gene expression of the enhancer-driven regulons (eRegulon) shown on a color scale and Area Under Curve (AUC) scoring of the TF activity (target gene cistrome) as 0-1 size scaled across clusters from one 10X Multiome representative primary tumor (n=3). ‘Positive’ means positive correlation TF expression and regulon activity (i.e., activator); ‘negative’ refers to a negative correlation (i.e., repressor). B: Schematic representation of the SCENIC+ predicted TF-TF interactions. Green lines indicate activation; red lines indicate repression. C: Principal component analysis (PCA) of one 10X Multiome primary tumor (n=3) based on eRegulon activity. D: Heat map representing the shift along the principal component 0 (PC_0) of each EMT state after simulated SCENIC+ predicted TF loss of function.\u003c/p\u003e","description":"","filename":"FigmainREV4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9426544/v1/b0659c511ed2b40f2317c712.jpg"},{"id":107258998,"identity":"593296de-792d-4960-b9bf-15745933cefc","added_by":"auto","created_at":"2026-04-19 12:45:09","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":799742,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003ePitx1\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e and \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eKlf5\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003epromote epithelial and early hybrid EMT states \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ein vitro\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e and \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ein vivo\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eand regulate epithelial and mesenchymal transcriptional programs.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA-B: Cytospin immunostaining quantification of KRT14, KRT8 and Vimentin, assessed at day 8 of \u003cem\u003ein vitro\u003c/em\u003e experiments of mouse skin SCC-derived line control (n=7 independent experiments, with 2175 cells counted in total across independent experiments) vs. \u003cem\u003ePitx1\u003c/em\u003e KO (n=7 independent experiments, with 2457 cells counted in total across independent experiments) (A) and \u003cem\u003eKlf5\u003c/em\u003e KO (n=7 independent experiments, with 2227 cells counted in total across independent experiments per independent experiment) (B) treated with 0.5 ng/ml TGFβ1. Error bars showing s.e.m. Unpaired Welch’s t-test for significance. C-D: Cytospin immunostaining quantification of KRT14, KRT8 and Vimentin of tumor cells upon \u003cem\u003ein vivo\u003c/em\u003e subcutaneous transplantation into NOD/SCID/Il2Rγ-null mice of control cell line (n=5 tumors, with 605 cells counted in total across tumors), \u003cem\u003ePitx1\u003c/em\u003eKO (n=4 tumors, with 746 cells counted in total across tumors) (C) and \u003cem\u003eKlf5\u003c/em\u003eKO (n=5 tumors, with 578 cells counted in total across tumors) (D). Error bars showing s.e.m. Unpaired Welch’s t-test for significance. E-F: GSEA showing the distribution of the \u003cem\u003ePitx1\u003c/em\u003e KO \u003cem\u003eEpcam\u003c/em\u003e+ (E) and \u003cem\u003eKlf5\u003c/em\u003e KO \u003cem\u003eEpcam\u003c/em\u003e+ (F) upregulated genes (FC \u0026gt;2) within the rank order list of the epithelial signature (control Epcam+ cells) by bulk RNA-seq. The normalized enrichment score (NES) and p-value are shown. G-H: mRNA expression of genes downregulated within the epithelial signature in \u003cem\u003ePitx1\u003c/em\u003e KO \u003cem\u003eEpcam\u003c/em\u003e+ (G) and \u003cem\u003eKlf5\u003c/em\u003eKO \u003cem\u003eEpcam\u003c/em\u003e+ (H) cells vs control by bulk RNA-seq of \u003cem\u003eEpcam\u003c/em\u003e+ cells, after 8 days of TGFβ1 treatment of EPCAM+ tumor cells. Histograms represent mean; \u003cem\u003en\u003c/em\u003e = 2. I-J: GSEA showing the distribution of the \u003cem\u003ePitx1\u003c/em\u003e KO \u003cem\u003eEpcam\u003c/em\u003e- (I) and \u003cem\u003eKlf5\u003c/em\u003e KO \u003cem\u003eEpcam\u003c/em\u003e- (J) downregulated genes (FC\u0026gt;2) within the rank order list of the early hybrid and hybrid EMT signature (control \u003cem\u003eEpcam\u003c/em\u003e- cells) by bulk RNA-seq. The NES and p-value are shown. K-L: mRNA expression of mesenchymal genes upregulated in \u003cem\u003ePitx1\u003c/em\u003e KO \u003cem\u003eEpcam\u003c/em\u003e- (K) and \u003cem\u003eKlf5\u003c/em\u003eKO \u003cem\u003eEpcam\u003c/em\u003e- (L) cells vs control by bulk RNA-seq of \u003cem\u003eEpcam\u003c/em\u003e- cells, after 8 days of TGFβ1 administration to EPCAM+ tumor cells. Histograms represent mean; \u003cem\u003en\u003c/em\u003e = 2. M-P: mRNA expression of predicted target downregulated in \u003cem\u003ePitx1\u003c/em\u003e KO \u003cem\u003eEpcam\u003c/em\u003e+ (M), \u003cem\u003ePitx1\u003c/em\u003e KO \u003cem\u003eEpcam\u003c/em\u003e- (N), \u003cem\u003eKlf5\u003c/em\u003e KO \u003cem\u003eEpcam\u003c/em\u003e+ (O) and \u003cem\u003eKlf5\u003c/em\u003e KO \u003cem\u003eEpcam\u003c/em\u003e- (P) cells vs control by bulk RNA-seq of \u003cem\u003eEpcam\u003c/em\u003e- cells 8 days after plating of 100% EPCAM+ tumor cells. \u003cem\u003en\u003c/em\u003e = 2.\u003c/p\u003e","description":"","filename":"FigmainREV5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9426544/v1/0a4257028498e1d381d811a3.jpg"},{"id":107259002,"identity":"f1a30bdd-c352-4257-894f-8a6c7d580a77","added_by":"auto","created_at":"2026-04-19 12:45:09","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":700756,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eNfatc1\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eand \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eCreb3l1\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e regulate late EMT tumor state \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ein vitro\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e and \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ein vivo\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eand control genes associated with late EMT state.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA-B: Cytospin immunostaining quantification of KRT14, KRT8 and Vimentin, assessed at day 8 of \u003cem\u003ein vitro\u003c/em\u003e experiments of mouse skin SCC-derived line control (n=7 independent experiments, with 2175 cells counted in total across independent experiments) vs. \u003cem\u003eNfatc1\u003c/em\u003e KO (n=7 independent experiments, with 2378 cells counted in total across independent experiments) (A) and \u003cem\u003eCreb3l1\u003c/em\u003e KO (n=7 independent experiments, with 2087 cells counted in total across independent experiments) (B) treated with 0.5 ng/ml TGFβ1. Error bars showing s.e.m. Unpaired Welch’s t-test for significance. C-D: Cytospin immunostaining quantification of KRT14, KRT8 and Vimentin of tumor cells upon \u003cem\u003ein vivo\u003c/em\u003e subcutaneous transplantation into NOD/SCID/Il2Rγ-null mice of control cell line (n=5 tumors, with 605 cells counted in total across tumors), \u003cem\u003eNfatc1\u003c/em\u003eKO (n=3 tumors, with 526 cells counted in total across tumors) (C) and \u003cem\u003eCreb3l1\u003c/em\u003eKO (n=4 tumors, with 580 cells counted in total across tumors) (D). Error bars showing s.e.m. Unpaired Welch’s t-test for significance. E-F: GSEA showing the distribution of the \u003cem\u003eNfatc1\u003c/em\u003e KO \u003cem\u003eEpcam\u003c/em\u003e- (E) and \u003cem\u003eCreb3l1\u003c/em\u003e KO \u003cem\u003eEpcam\u003c/em\u003e- (F) upregulated genes (FC \u0026gt;2) by bulk RNA-seq within the rank order list of the epithelial signature (control \u003cem\u003eEpcam\u003c/em\u003e+ cells). The normalized enrichment score (NES) and p-value are shown. G-H: mRNA expression of genes upregulated within the epithelial signature in \u003cem\u003eNfatc1\u003c/em\u003e KO \u003cem\u003eEpcam\u003c/em\u003e- (G) and \u003cem\u003eCreb3l1\u003c/em\u003e KO \u003cem\u003eEpcam\u003c/em\u003e- (H) cells vs control by bulk RNA-seq of \u003cem\u003eEpcam\u003c/em\u003e- cells, after 8 days of TGFβ1 administration to EPCAM+ tumor cells. Histograms represent mean; \u003cem\u003en\u003c/em\u003e = 2. I-J: GSEA showing the distribution of the \u003cem\u003eNfatc1\u003c/em\u003e KO \u003cem\u003eEpcam\u003c/em\u003e- (I) and \u003cem\u003eCreb3l1\u003c/em\u003e KO \u003cem\u003eEpcam\u003c/em\u003e- (J) downregulated genes (FC\u0026gt;2) by bulk RNA-seq within the rank order list of the early hybrid and hybrid EMT signature (control \u003cem\u003eEpcam\u003c/em\u003e- cells). The NES and p-value are shown. K-L: mRNA expression of genes downregulated within the mesenchymal signature in \u003cem\u003eNfatc1\u003c/em\u003e KO \u003cem\u003eEpcam\u003c/em\u003e- (K) and \u003cem\u003eCreb3l1\u003c/em\u003eKO \u003cem\u003eEpcam\u003c/em\u003e- (L) cells vs control by bulk RNA-seq of \u003cem\u003eEpcam\u003c/em\u003e- cells, after 8 days of TGFβ1 administration to EPCAM+ tumor cells. Histograms represent mean; \u003cem\u003en\u003c/em\u003e = 2. M-N: mRNA expression of predicted target downregulated in \u003cem\u003eNfatc1\u003c/em\u003e KO \u003cem\u003eEpcam\u003c/em\u003e- (M) and \u003cem\u003eCreb3l1\u003c/em\u003e KO \u003cem\u003eEpcam\u003c/em\u003e- (N) cells vs control by bulk RNA-seq of Epcam- cells after 8 days of TGFβ1 administration to EPCAM+ tumor cells. \u003cem\u003en\u003c/em\u003e = 2.\u003c/p\u003e","description":"","filename":"FigmainREV6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9426544/v1/3ceb50a5e41e8d2f697c0e73.jpg"},{"id":107258999,"identity":"c89382a6-3b9c-437c-883a-61c65d94fd59","added_by":"auto","created_at":"2026-04-19 12:45:09","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":703846,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003ePitx1\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e and \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eKlf5\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e are key regulators of metastasis formation and outgrowth.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA: Representative images of one lung lobe per condition (control vs KO) showing the presence of YFP+ lung metastases after subcutaneous transplantation of TGFβ1-treated cells for 8 days \u003cem\u003ein vitro\u003c/em\u003e into NOD/SCID/Il2Rγ-null mice. Scale bars, 1.000 μm; Hoechst used as nuclear staining. B-C: Quantification showing the number of lung metastases (B) and the proportion of area of lungs with metastases (C) (n=6 control mice; n=7 KO mice). D: Immunostaining quantification of KRT14, KRT8 and Vimentin of metastatic cells in lungs with metastases for each condition. Error bars showing s.e.m. Unpaired Welch’s t-test for significance. E: Representative images of one lung lobe per condition (control vs KO) showing the presence of YFP+ lung metastases upon subcutaneous transplantation of Epcam+ cells into NOD/SCID/Il2Rγ-null mice. Scale bars, 1.000 μm; Hoechst used as nuclear staining. F-G: Quantification showing the number of lung metastases (F) and the proportion of area of lungs with metastases (G) (n=3 control mice; n=3-4 KO mice). H: Immunostaining quantification of KRT14, KRT8 and Vimentin of metastatic cells in lungs with metastases for each condition. Error bars showing s.e.m. Unpaired Welch’s t-test for significance.\u003c/p\u003e","description":"","filename":"FigmainREV7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9426544/v1/bbbcc6182ce98594a0747a30.jpg"},{"id":107259001,"identity":"d9ebf4a7-e4e3-466f-8033-13565746fd87","added_by":"auto","created_at":"2026-04-19 12:45:09","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":743028,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEMT states and their transcriptional regulation in human lung adenocarcinoma.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA: UMAP plots of the integrated single-cell RNA-seq atlas of genetically induced skin SCC colored by log-normalized expression levels of gene sets corresponding to human EMT signatures identified by Gavish \u003cem\u003eet al.\u003c/em\u003e\u003csup\u003e12\u003c/sup\u003e\u003cem\u003e: \u003c/em\u003eEMT-I (complete EMT) and EMT-III (intermediate EMT). B:\u003cem\u003e In situ\u003c/em\u003e co-immunostaining of PanCK, VIM and Ku80, using Hoechst as nuclear staining in a lung adenocarcinoma PDX grafted into NOD/SCID mice, revealing the presence of epithelial, hybrid EMT and late EMT cells. Scale bars, 20 μm. The yellow * marks late EMT. C: Uniform manifold approximation and projection (UMAP) plot of tumor cells originating from lung adenocarcinoma PDX profiled by single-cell RNA-seq. Cells are colored by their inferred tumor state. D-H: UMAP plots colored by log-normalized expression levels of gene sets corresponding to epithelial (D), early hybrid EMT (E), hybrid EMT (F), hypoxia (G) and late EMT (H) states. I: UMAP plots of lung adenocarcinoma PDX colored by log-normalized expression levels of gene sets corresponding to human EMT signatures identified by Gavish \u003cem\u003eet al.\u003c/em\u003e\u003csup\u003e 12\u003c/sup\u003e\u003cem\u003e: \u003c/em\u003eEMT-I (complete EMT), EMT-III (intermediate EMT) and hypoxia. J: Heat map/dot-plot showing TF gene expression and regulon activity of the predicted regulons inferred by SCENIC analysis on a lung adenocarcinoma PDX.\u003c/p\u003e","description":"","filename":"FigmainREV8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9426544/v1/8d204a0324f8f88d62e3dbab.jpg"},{"id":107487235,"identity":"57c0ef6c-3ebf-4985-8052-c0f615b1cbf9","added_by":"auto","created_at":"2026-04-22 02:40:08","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":8405040,"visible":true,"origin":"","legend":"","description":"","filename":"ManuscriptrevisedfinalPerezGonzalezetalv4.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9426544/v1_covered_3138a906-b0b3-4a07-bfc3-ae829e84adfe.pdf"},{"id":107483235,"identity":"7f8fd3f7-a0b8-49fc-b249-592fdd12932b","added_by":"auto","created_at":"2026-04-22 02:26:54","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":11423839,"visible":true,"origin":"","legend":"\u003cp\u003eExtended Data\u003c/p\u003e","description":"","filename":"ExtendeddataPerezGonzalezetal.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9426544/v1/f108a69646fdd263f2ccf502.pdf"},{"id":107258994,"identity":"366d552f-dfb0-4964-90e0-2a57f90acec1","added_by":"auto","created_at":"2026-04-19 12:45:09","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":720403,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Tables\u003c/p\u003e","description":"","filename":"SuplementaryTables.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-9426544/v1/1076133be18bfb47523ae177.xlsx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eSingle cell multiomics unravel the transcription networks controlling the different EMT tumor states\u003c/strong\u003e\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Université Libre de Bruxelles","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":"EMT, metastasis, skin SCC, transcriptomics, regulation","lastPublishedDoi":"10.21203/rs.3.rs-9426544/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9426544/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eEpithelial-to-mesenchymal transition (EMT) is a dynamic process during which cells lose their epithelial characteristics and acquire mesenchymal traits. In cancer, EMT is associated with tumor initiation, progression, invasion, metastasis, and therapy resistance. Rather than being a binary state switch, EMT encompasses a spectrum of tumor states with distinct functional properties. However, the transcription factors (TFs) that control the distinct EMT tumor state transitions remain poorly characterized. Here, using multi-omic approaches combining single-cell RNA-seq and single-cell ATAC-seq, we delineate the transcriptomic and chromatin landscapes of distinct EMT states in a mouse model of skin squamous cell carcinoma (SCC). Through CRISPR/Cas9-mediated loss-of-function studies coupled with \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003efunctional assays, we identify TFs regulating specific EMT states. \u003cem\u003eKlf5\u003c/em\u003eand \u003cem\u003ePitx1\u003c/em\u003e control the early steps of EMT and are essential for metastasis formation. In contrast, \u003cem\u003eNfatc1\u003c/em\u003e and \u003cem\u003eCreb3l1\u003c/em\u003e act at later stages of EMT. Similar EMT states and regulatory patterns are found in mouse pancreatic adenocarcinoma and patient derived xenograft of lung adenocarcinoma. Altogether, our study defines the transcriptional and chromatin landscape controlling EMT progression in mouse skin SCC, identifies EMT state-specific TFs and highlights their essential roles in regulating metastasis.\u003c/p\u003e","manuscriptTitle":"Single cell multiomics unravel the transcription networks controlling the different EMT tumor states","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-19 12:45:00","doi":"10.21203/rs.3.rs-9426544/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":"887a4e0b-5239-4f84-a94b-0206eb45ecaf","owner":[],"postedDate":"April 19th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":66370796,"name":"Cancer Biology"}],"tags":[],"updatedAt":"2026-04-19T12:45:00+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-19 12:45:00","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9426544","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9426544","identity":"rs-9426544","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}