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Multiplexed single-cell analysis reveals prognostic and nonprognostic T cell types in human colorectal cancer

Authors :
Kazuya Masuda
Adam Kornberg
Jonathan Miller
Sijie Lin
Nathan Suek
Theo Botella
Kerim A. Secener
Alyssa M. Bacarella
Liang Cheng
Matthew Ingham
Vilma Rosario
Ahmed M. Al-Mazrou
Steven A. Lee-Kong
Ravi P. Kiran
Marlon Stoeckius
Peter Smibert
Armando Del Portillo
Paul E. Oberstein
Peter A. Sims
Kelley S. Yan
Arnold Han
Source :
JCI Insight, Vol 7, Iss 7 (2022)
Publication Year :
2022
Publisher :
American Society for Clinical investigation, 2022.

Abstract

Clinical outcomes in colorectal cancer (CRC) correlate with T cell infiltrates, but the specific contributions of heterogenous T cell types remain unclear. To investigate the diverse function of T cells in CRC, we profiled 37,931 T cells from tumors and adjacent normal colon of 16 patients with CRC with respect to transcriptome, TCR sequence, and cell surface markers. Our analysis identified phenotypically and functionally distinguishable effector T cell types. We employed single-cell gene signatures from these T cell subsets to query the TCGA database to assess their prognostic significance. We found 2 distinct cytotoxic T cell types. GZMK+KLRG1+ cytotoxic T cells were enriched in CRC patients with good outcomes. GNLY+CD103+ cytotoxic T cells with a dysfunctional phenotype were not associated with good outcomes, despite coexpression of CD39 and CD103, markers that denote tumor reactivity. We found 2 distinct Treg subtypes associated with opposite outcomes. While total Tregs were associated with good outcomes, CD38+ Tregs were associated with bad outcomes independently of stage and possessed a highly suppressive phenotype, suggesting that they inhibit antitumor immunity in CRC. These findings highlight the potential utility of these subpopulations in predicting outcomes and support the potential for novel therapies directed at CD38+ Tregs or CD8+CD103+ T cells.

Subjects

Subjects :
Immunology
Medicine

Details

Language :
English
ISSN :
23793708
Volume :
7
Issue :
7
Database :
Directory of Open Access Journals
Journal :
JCI Insight
Publication Type :
Academic Journal
Accession number :
edsdoj.994919d65984adfb8344af434a112be
Document Type :
article
Full Text :
https://doi.org/10.1172/jci.insight.154646