Pan-cancer single-cell landscape of tumor-infiltrating T cells

Abstract

An atlas of cancer-associated T cells The tumor microenvironment contains many different kinds of immune cells, the composition, function, and roles of which are unclear. Using single-cell RNA sequencing of T cells in 21 cancer types from more than 300 patients, Zheng et al . identified differences in transcript composition that could be used to catalog different T cell types (see the Perspective by van der Leun and Schumacher). These annotations identified the different roles of specific types of CD4 + and CD8 + T cells among the different tumor types. Some of these clusters revealed evidence for two developmental paths for T cells, one of which shows a trajectory toward the “exhausted” T cell state, knowledge of which may be useful in developing future cancer immunotherapies. —LMZ

Comprehensive dissection of immune microenvironment in the progression of early gastric cancer at spatial and single-cell resolution

“…In addition to the existence of exhausted T cells, another natural inhibitory role in TME, Tregs, up-regulated transcriptional activity of HIVEP1 and STAT3 in NAG stage, while enhanced activities of IRF4 and IKZF2 in AG state, and possessed higher transcriptional activities of FOXP3, BATF, and PRDM1 in EGC period. Among them, HIVEP1 was a newly found TF in Tregs, it was just reported highly activated in TNFRSF9+ Treg cells, at a late part of the trajectory 86 , presenting a different pattern from our results. As previous reports, PRDM1 usually up-regulated transcriptional activity in advanced or end-stage, implying worse immune effects 87 88 .…”

Single-cell immunology: Past, present, and future

“…High patient-to-patient variability coupled with sampling biases because of the small number of cells have limited the discovery power of these studies. As throughput and resolution improved, deeper insights and mechanisms were detected (Zheng et al, 2021). Another major breakthrough achieved in 2016 was single-cell resolution in the context of cell engineering and pooled screening using CRISPR-CAS9 technology.…”

“…For example, the TREM2 pathway that was established by single-cell analysis as a major immune signaling hub in pathology is progressing in multiple pre-clinical programs to treat both neurodegenerative diseases and cancer (Deczkowska et al, 2020). Moreover, massive immune atlases generated from cancer patients will enable the detection of key immune populations and pathways participating in anti-tumor responses and development of effective biomarkers and the next generation of targets for immunotherapies (Zheng et al, 2021). Another example of the power of rapidly dissecting immune signatures using single-cell multiomics technologies is observed in the rapid advancement of characterization of acute respiratory syndrome coronavirus (SARS-CoV-2).…”

TCR-sequencing in cancer and autoimmunity: barcodes and beyond

“…Using the TCR as a barcode in cancer The TCR has been used as a barcode to identify CD8 + T cells in peripheral blood that share TCRs with CD8 + tumor-infiltrating lymphocytes (TILs) in tumors (referred to as 'tumor matching'), as shown in mice with MC38 colon adenocarcinoma [27], as well as in patients with advanced melanoma and non-small cell lung cancer (NSCLC) [27][28][29][30]. The TCR has also been valuable for studying the dynamics of individual CD8 + T cell clones, including clone-by-clone comparisons of transcriptional states across tissues and inferring lineage relationships between populations of CD8 + T cells in mouse [including MC38, B16-F10, CT26, and a genetically engineered mouse model (GEMM) of lung adenocarcinoma caused by oncogenic Kras and loss of p53] and human tumors [including melanoma, NSCLC, colorectal cancer (CRC)] [27][28][29][30][31][32][33][34][35][36][37][38]. A recent study in humans used paired scRNA seq and scTCR seq to analyze CD4 + T cells and CD8 + T cells across 21 cancer types (including melanoma and breast, gastric, pancreatic, kidney, and esophageal cancers) from 316 patients; the study identified two major developmental trajectories that contributed to T cell exhaustion across multiple tumor types, based on transcriptional information [32].…”

“…The TCR has also been valuable for studying the dynamics of individual CD8 + T cell clones, including clone-by-clone comparisons of transcriptional states across tissues and inferring lineage relationships between populations of CD8 + T cells in mouse [including MC38, B16-F10, CT26, and a genetically engineered mouse model (GEMM) of lung adenocarcinoma caused by oncogenic Kras and loss of p53] and human tumors [including melanoma, NSCLC, colorectal cancer (CRC)] [27][28][29][30][31][32][33][34][35][36][37][38]. A recent study in humans used paired scRNA seq and scTCR seq to analyze CD4 + T cells and CD8 + T cells across 21 cancer types (including melanoma and breast, gastric, pancreatic, kidney, and esophageal cancers) from 316 patients; the study identified two major developmental trajectories that contributed to T cell exhaustion across multiple tumor types, based on transcriptional information [32]. Additionally, scTCR seq has been useful to inform mechanisms of response following PD-1-based immunotherapy in cancer patients [30,[36][37][38][39][40][41], as later discussed.…”