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Abstract Enteric glia have been recently recognized as key components of the colonic tumor microenvironment indicating their potential role in colorectal cancer pathogenesis. Although enteric glia modulate immune responses in other intestinal diseases, their interaction with the colorectal cancer immune cell compartment remains unclear. Through a combination of single-cell and bulk RNA-sequencing, both in murine models and patients, here we find that enteric glia acquire an immunomodulatory phenotype by bi-directional communication with tumor-infiltrating monocytes. The latter direct a reactive enteric glial cell phenotypic and functional switch via glial IL-1R signaling. In turn, tumor glia promote monocyte differentiation towards pro-tumorigenic SPP1+ tumor-associated macrophages by IL-6 release. Enteric glia cell abundancy correlates with worse disease outcomes in preclinical models and colorectal cancer patients. Thereby, our study reveals a neuroimmune interaction between enteric glia and tumor-associated macrophages in the colorectal tumor microenvironment, providing insights into colorectal cancer pathogenesis.

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.

T cells exercise a multitude of functions such as cytotoxicity, secretion of immunomodulating cytokines or regulation of tolerance, collectively resulting in an effective control of immune-related disease. Through the unique mechanism of V(D)J recombination, T cells express a highly specific receptor complex known as the T-cell receptor (TCR). Single-cell sequencing technologies have paved the road for interrogating the transcriptome and the paired αβ TCR repertoire of a single T cell in tandem. In contrast, conventional bulk methods are restricted to only one layer of information. This combination of transcriptomic- and repertoire information can provide novel insight into the functional character of T cell immunity. Recently, single-cell technologies have gained in popularity due to improvements in throughput, decrease in cost and the ability for multimodal experiments that integrate different information layers. Consequently, this prompts the need for the development of novel computational tools that integrate transcriptomic profiles and corresponding features of the TCR repertoire. Here we discuss the current progress in the field of single-cell T cell sequencing, with a focus on the multimodality of new approaches that allow the paired profiling of cellular phenotype and clonotype information. In addition, this review provides detailed descriptions of recent computational developments for analyzing single-cell TCR sequencing data in an integrative manner using novel computational approaches. Finally, we present an overview of the available software tools that can be used to perform integrative analysis of gene expression and TCR profiles.