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Unravelling the heterogeneity and dynamic relationships of tumor‐infiltrating T cells by single‐cell RNA sequencing analysis
T cells are crucial for the success of immune‐based cancer therapy. Reinvigorating antitumor T cell activity by blocking checkpoint inhibitory receptors has provided clinical benefits for many cancer patients. However, the efficacy of these treatments varies in cancer patients and the mechanisms und...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7317876/ https://www.ncbi.nlm.nih.gov/pubmed/32272497 http://dx.doi.org/10.1002/JLB.6MR0320-234R |
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author | Yu, Xin Zhang, Lei Chaudhry, Ashutosh Rapaport, Aaron S. Ouyang, Wenjun |
author_facet | Yu, Xin Zhang, Lei Chaudhry, Ashutosh Rapaport, Aaron S. Ouyang, Wenjun |
author_sort | Yu, Xin |
collection | PubMed |
description | T cells are crucial for the success of immune‐based cancer therapy. Reinvigorating antitumor T cell activity by blocking checkpoint inhibitory receptors has provided clinical benefits for many cancer patients. However, the efficacy of these treatments varies in cancer patients and the mechanisms underlying these diverse responses remain elusive. The density and status of tumor‐infiltrating T cells have been shown to positively correlate with patient response to checkpoint blockades. Therefore, further understanding of the heterogeneity, clonal expansion, migration, and effector functions of tumor‐infiltrating T cells will provide fundamental insights into antitumor immune responses. To this end, recent advances in single‐cell RNA sequencing technology have enabled profound and extensive characterization of intratumoral immune cells and have improved our understanding of their dynamic relationships. Here, we summarize recent progress in single‐cell RNA sequencing technology and current strategies to uncover heterogeneous tumor‐infiltrating T cell subsets. In particular, we discuss how the coupling of deep transcriptome information with T cell receptor (TCR)‐based lineage tracing has furthered our understanding of intratumoral T cell populations. We also discuss the functional implications of various T cell subsets in tumors and highlight the identification of novel T cell markers with therapeutic or prognostic potential. |
format | Online Article Text |
id | pubmed-7317876 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-73178762020-06-29 Unravelling the heterogeneity and dynamic relationships of tumor‐infiltrating T cells by single‐cell RNA sequencing analysis Yu, Xin Zhang, Lei Chaudhry, Ashutosh Rapaport, Aaron S. Ouyang, Wenjun J Leukoc Biol 17th International TNF Superfamily Conference 2019 T cells are crucial for the success of immune‐based cancer therapy. Reinvigorating antitumor T cell activity by blocking checkpoint inhibitory receptors has provided clinical benefits for many cancer patients. However, the efficacy of these treatments varies in cancer patients and the mechanisms underlying these diverse responses remain elusive. The density and status of tumor‐infiltrating T cells have been shown to positively correlate with patient response to checkpoint blockades. Therefore, further understanding of the heterogeneity, clonal expansion, migration, and effector functions of tumor‐infiltrating T cells will provide fundamental insights into antitumor immune responses. To this end, recent advances in single‐cell RNA sequencing technology have enabled profound and extensive characterization of intratumoral immune cells and have improved our understanding of their dynamic relationships. Here, we summarize recent progress in single‐cell RNA sequencing technology and current strategies to uncover heterogeneous tumor‐infiltrating T cell subsets. In particular, we discuss how the coupling of deep transcriptome information with T cell receptor (TCR)‐based lineage tracing has furthered our understanding of intratumoral T cell populations. We also discuss the functional implications of various T cell subsets in tumors and highlight the identification of novel T cell markers with therapeutic or prognostic potential. John Wiley and Sons Inc. 2020-04-09 2020-06 /pmc/articles/PMC7317876/ /pubmed/32272497 http://dx.doi.org/10.1002/JLB.6MR0320-234R Text en © 2020 Amgen Inc. Journal of Leukocyte Biology published by Wiley Periodicals LLC on behalf of Society for Leukocyte Biology This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | 17th International TNF Superfamily Conference 2019 Yu, Xin Zhang, Lei Chaudhry, Ashutosh Rapaport, Aaron S. Ouyang, Wenjun Unravelling the heterogeneity and dynamic relationships of tumor‐infiltrating T cells by single‐cell RNA sequencing analysis |
title | Unravelling the heterogeneity and dynamic relationships of tumor‐infiltrating T cells by single‐cell RNA sequencing analysis |
title_full | Unravelling the heterogeneity and dynamic relationships of tumor‐infiltrating T cells by single‐cell RNA sequencing analysis |
title_fullStr | Unravelling the heterogeneity and dynamic relationships of tumor‐infiltrating T cells by single‐cell RNA sequencing analysis |
title_full_unstemmed | Unravelling the heterogeneity and dynamic relationships of tumor‐infiltrating T cells by single‐cell RNA sequencing analysis |
title_short | Unravelling the heterogeneity and dynamic relationships of tumor‐infiltrating T cells by single‐cell RNA sequencing analysis |
title_sort | unravelling the heterogeneity and dynamic relationships of tumor‐infiltrating t cells by single‐cell rna sequencing analysis |
topic | 17th International TNF Superfamily Conference 2019 |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7317876/ https://www.ncbi.nlm.nih.gov/pubmed/32272497 http://dx.doi.org/10.1002/JLB.6MR0320-234R |
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