Alexander T F Bell, Jacob T Mitchell, Ashley L Kiemen, Melissa Lyman, Kohei Fujikura, Jae W Lee, Erin Coyne, Sarah M Shin, Sushma Nagaraj, Atul Deshpande, Pei-Hsun Wu, Dimitrios N Sidiropoulos, Rossin Erbe, Jacob Stern, Rena Chan, Stephen Williams, James M Chell, Lauren Ciotti, Jacquelyn W Zimmerman, Denis Wirtz, Won Jin Ho, Neeha Zaidi, Elizabeth Thompson, Elizabeth M Jaffee, Laura D Wood, Elana J Fertig, Luciane T Kagohara
{"title":"通过空间数据整合揭示胰腺癌发生过程中的 PanIN 和 CAF 转变。","authors":"Alexander T F Bell, Jacob T Mitchell, Ashley L Kiemen, Melissa Lyman, Kohei Fujikura, Jae W Lee, Erin Coyne, Sarah M Shin, Sushma Nagaraj, Atul Deshpande, Pei-Hsun Wu, Dimitrios N Sidiropoulos, Rossin Erbe, Jacob Stern, Rena Chan, Stephen Williams, James M Chell, Lauren Ciotti, Jacquelyn W Zimmerman, Denis Wirtz, Won Jin Ho, Neeha Zaidi, Elizabeth Thompson, Elizabeth M Jaffee, Laura D Wood, Elana J Fertig, Luciane T Kagohara","doi":"10.1016/j.cels.2024.07.001","DOIUrl":null,"url":null,"abstract":"<p><p>This study introduces a new imaging, spatial transcriptomics (ST), and single-cell RNA-sequencing integration pipeline to characterize neoplastic cell state transitions during tumorigenesis. We applied a semi-supervised analysis pipeline to examine premalignant pancreatic intraepithelial neoplasias (PanINs) that can develop into pancreatic ductal adenocarcinoma (PDAC). Their strict diagnosis on formalin-fixed and paraffin-embedded (FFPE) samples limited the single-cell characterization of human PanINs within their microenvironment. We leverage whole transcriptome FFPE ST to enable the study of a rare cohort of matched low-grade (LG) and high-grade (HG) PanIN lesions to track progression and map cellular phenotypes relative to single-cell PDAC datasets. We demonstrate that cancer-associated fibroblasts (CAFs), including antigen-presenting CAFs, are located close to PanINs. We further observed a transition from CAF-related inflammatory signaling to cellular proliferation during PanIN progression. We validate these findings with single-cell high-dimensional imaging proteomics and transcriptomics technologies. Altogether, our semi-supervised learning framework for spatial multi-omics has broad applicability across cancer types to decipher the spatiotemporal dynamics of carcinogenesis.</p>","PeriodicalId":93929,"journal":{"name":"Cell systems","volume":" ","pages":"753-769.e5"},"PeriodicalIF":0.0000,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11409191/pdf/","citationCount":"0","resultStr":"{\"title\":\"PanIN and CAF transitions in pancreatic carcinogenesis revealed with spatial data integration.\",\"authors\":\"Alexander T F Bell, Jacob T Mitchell, Ashley L Kiemen, Melissa Lyman, Kohei Fujikura, Jae W Lee, Erin Coyne, Sarah M Shin, Sushma Nagaraj, Atul Deshpande, Pei-Hsun Wu, Dimitrios N Sidiropoulos, Rossin Erbe, Jacob Stern, Rena Chan, Stephen Williams, James M Chell, Lauren Ciotti, Jacquelyn W Zimmerman, Denis Wirtz, Won Jin Ho, Neeha Zaidi, Elizabeth Thompson, Elizabeth M Jaffee, Laura D Wood, Elana J Fertig, Luciane T Kagohara\",\"doi\":\"10.1016/j.cels.2024.07.001\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>This study introduces a new imaging, spatial transcriptomics (ST), and single-cell RNA-sequencing integration pipeline to characterize neoplastic cell state transitions during tumorigenesis. We applied a semi-supervised analysis pipeline to examine premalignant pancreatic intraepithelial neoplasias (PanINs) that can develop into pancreatic ductal adenocarcinoma (PDAC). Their strict diagnosis on formalin-fixed and paraffin-embedded (FFPE) samples limited the single-cell characterization of human PanINs within their microenvironment. We leverage whole transcriptome FFPE ST to enable the study of a rare cohort of matched low-grade (LG) and high-grade (HG) PanIN lesions to track progression and map cellular phenotypes relative to single-cell PDAC datasets. We demonstrate that cancer-associated fibroblasts (CAFs), including antigen-presenting CAFs, are located close to PanINs. We further observed a transition from CAF-related inflammatory signaling to cellular proliferation during PanIN progression. We validate these findings with single-cell high-dimensional imaging proteomics and transcriptomics technologies. Altogether, our semi-supervised learning framework for spatial multi-omics has broad applicability across cancer types to decipher the spatiotemporal dynamics of carcinogenesis.</p>\",\"PeriodicalId\":93929,\"journal\":{\"name\":\"Cell systems\",\"volume\":\" \",\"pages\":\"753-769.e5\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-08-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11409191/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cell systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1016/j.cels.2024.07.001\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/8/7 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cell systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.cels.2024.07.001","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/8/7 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
PanIN and CAF transitions in pancreatic carcinogenesis revealed with spatial data integration.
This study introduces a new imaging, spatial transcriptomics (ST), and single-cell RNA-sequencing integration pipeline to characterize neoplastic cell state transitions during tumorigenesis. We applied a semi-supervised analysis pipeline to examine premalignant pancreatic intraepithelial neoplasias (PanINs) that can develop into pancreatic ductal adenocarcinoma (PDAC). Their strict diagnosis on formalin-fixed and paraffin-embedded (FFPE) samples limited the single-cell characterization of human PanINs within their microenvironment. We leverage whole transcriptome FFPE ST to enable the study of a rare cohort of matched low-grade (LG) and high-grade (HG) PanIN lesions to track progression and map cellular phenotypes relative to single-cell PDAC datasets. We demonstrate that cancer-associated fibroblasts (CAFs), including antigen-presenting CAFs, are located close to PanINs. We further observed a transition from CAF-related inflammatory signaling to cellular proliferation during PanIN progression. We validate these findings with single-cell high-dimensional imaging proteomics and transcriptomics technologies. Altogether, our semi-supervised learning framework for spatial multi-omics has broad applicability across cancer types to decipher the spatiotemporal dynamics of carcinogenesis.