Zhihao Huang, Tim Mandelkow, Nicolaus F Debatin, Magalie C J Lurati, Julia Ebner, Jonas B Raedler, Elena Bady, Jan H Müller, Ronald Simon, Eik Vettorazzi, Anne Menz, Katharina Möller, Natalia Gorbokon, Guido Sauter, Maximilian Lennartz, Andreas M Luebke, Doris Höflmayer, Till Krech, Patrick Lebok, Christoph Fraune, Andrea Hinsch, Frank Jacobsen, Andreas H Marx, Stefan Steurer, Sarah Minner, David Dum, Sören Weidemann, Christian Bernreuther, Till S Clauditz, Eike Burandt, Niclas C Blessin
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{"title":"A Tc1- and Th1-T-lymphocyte-rich tumor microenvironment is a hallmark of MSI colorectal cancer.","authors":"Zhihao Huang, Tim Mandelkow, Nicolaus F Debatin, Magalie C J Lurati, Julia Ebner, Jonas B Raedler, Elena Bady, Jan H Müller, Ronald Simon, Eik Vettorazzi, Anne Menz, Katharina Möller, Natalia Gorbokon, Guido Sauter, Maximilian Lennartz, Andreas M Luebke, Doris Höflmayer, Till Krech, Patrick Lebok, Christoph Fraune, Andrea Hinsch, Frank Jacobsen, Andreas H Marx, Stefan Steurer, Sarah Minner, David Dum, Sören Weidemann, Christian Bernreuther, Till S Clauditz, Eike Burandt, Niclas C Blessin","doi":"10.1002/path.6415","DOIUrl":"https://doi.org/10.1002/path.6415","url":null,"abstract":"<p><p>Microsatellite instability is a strong predictor of response to immune checkpoint therapy and patient outcome in colorectal cancer. Although enrichment of distinct T-cell subpopulations has been determined to impact the response to immune checkpoint therapy and patient outcome, little is known about the underlying changes in the composition of the immune tumor microenvironment. To assess the density, composition, degree of functional marker expression, and spatial interplay of T-cell subpopulations, 79 microsatellite instable (MSI) and 1,045 microsatellite stable (MSS) colorectal cancers were analyzed. A tissue microarray and large sections were stained with 19 antibodies directed against T cells, antigen-presenting cells, functional markers, and structural proteins using our BLEACH&STAIN multiplex-fluorescence immunohistochemistry approach. A deep learning-based framework comprising >20 different convolutional neuronal networks was developed for image analysis. The composition of Type 1 (T-bet<sup>+</sup>), Type 2 (GATA3<sup>+</sup>), Type 17 (RORγT<sup>+</sup>), NKT-like (CD56<sup>+</sup>), regulatory (FOXP3<sup>+</sup>), follicular (BCL6<sup>+</sup>), and cytotoxic (CD3<sup>+</sup>CD8<sup>+</sup>) or helper (CD3<sup>+</sup>CD4<sup>+</sup>) T cells showed marked differences between MSI and MSS patients. For instance, the fraction of Tc1 and Th1 was significantly higher (p < 0.001 each), while the fraction of Tregs, Th2, and Th17 T cells was significantly lower (p < 0.05) in MSI compared to MSS patients. The degree of TIM3, CTLA-4, and PD-1 expression on most T-cell subpopulations was significantly higher in MSI compared to MSS patients (p < 0.05 each). Spatial analysis revealed increased interactions between Th1, Tc1, and dendritic cells in MSI patients, while in MSS patients the strongest interactions were found between Tregs, Th17, Th2, and dendritic cells. The additional analysis of 12 large sections revealed a divergent immune composition at the invasive margin. In summary, this study identified a higher fraction of Tc1 and Th1 T cells accompanied by a paucity of regulatory T-cell, Th17, and Th2 T-cell subpopulations, along with a distinct interaction profile, as a hallmark of MSI compared to MSS colorectal cancers. © 2025 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.</p>","PeriodicalId":232,"journal":{"name":"The Journal of Pathology","volume":" ","pages":""},"PeriodicalIF":5.6,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143778712","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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