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Abstract
CD8+ T cell activation via immune checkpoint blockade (ICB) is successful in microsatellite instable (MSI) colorectal cancer (CRC) patients. By comparison, the success of immunotherapy against microsatellite stable (MSS) CRC is limited. Little is known about the most critical features of CRC CD8+ T cells that together determine the diverse immune landscapes and contrasting ICB responses. Hence, we pursued a deep single cell mapping of CRC CD8+ T cells on transcriptomic and T cell receptor (TCR) repertoire levels in a diverse patient cohort, with additional surface proteome validation. This revealed that CRC CD8+ T cell dynamics are underscored by complex interactions between interferon-γ signaling, tumor reactivity, TCR repertoire, (predicted) TCR antigen-specificities, and environmental cues like gut microbiome or colon tissue-specific ‘self-like’ features. MSI CRC CD8+ T cells showed tumor-specific activation reminiscent of canonical ‘T cell hot’ tumors, whereas the MSS CRC CD8+ T cells exhibited tumor unspecific or bystander-like features. This was accompanied by inflammation reminiscent of ‘pseudo-T cell hot’ tumors. Consequently, MSI and MSS CRC CD8+ T cells showed overlapping phenotypic features that differed dramatically in their TCR antigen-specificities. Given their high discriminating potential for CD8+ T cell features/specificities, we used the single cell tumor-reactive signaling modules in CD8+ T cells to build a bulk tumor transcriptome classification for CRC patients. This “Immune Subtype Classification” (ISC) successfully distinguished various tumoral immune landscapes that showed prognostic value and predicted immunotherapy responses in CRC patients. Thus, we deliver a unique map of CRC CD8+ T cells that drives a novel tumor immune landscape classification, with relevance for immunotherapy decision-making.
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1 KU Leuven, Cell Stress and Immunity (CSI) Lab, Department of Cellular and Molecular Medicine, Leuven, Belgium (GRID:grid.5596.f) (ISNI:0000 0001 0668 7884)
2 KU Leuven, Digestive Oncology, Department of Oncology, Leuven, Belgium (GRID:grid.5596.f) (ISNI:0000 0001 0668 7884)
3 Universität Innsbruck, Department of Molecular Biology, Digital Science Center (DiSC), Innsbruck, Austria (GRID:grid.5771.4) (ISNI:0000 0001 2151 8122)
4 Medical University of Innsbruck, Biocenter, Institute of Bioinformatics, Innsbruck, Austria (GRID:grid.5361.1) (ISNI:0000 0000 8853 2677)
5 Sungkyunkwan University, Department of Health Sciences and Technology, Samsung Advanced Institute for Health Science and Technology, Seoul, Republic of Korea (GRID:grid.264381.a) (ISNI:0000 0001 2181 989X); Sungkyunkwan University, Samsung Genome Institute, Samsung Medical Center, Seoul, Republic of Korea (GRID:grid.264381.a) (ISNI:0000 0001 2181 989X)
6 University Hospitals Leuven, Department of Pathology, Leuven, Belgium (GRID:grid.410569.f) (ISNI:0000 0004 0626 3338)
7 University Hospitals Leuven, Department of Abdominal Surgery, Leuven, Belgium (GRID:grid.410569.f) (ISNI:0000 0004 0626 3338)