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Applications of Single-Cell Omics in Tumor Immunology
The tumor microenvironment (TME) is an ecosystem that contains various cell types, including cancer cells, immune cells, stromal cells, and many others. In the TME, cancer cells aggressively proliferate, evolve, transmigrate to the circulation system and other organs, and frequently communicate with...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8221107/ https://www.ncbi.nlm.nih.gov/pubmed/34177965 http://dx.doi.org/10.3389/fimmu.2021.697412 |
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author | Liu, Junwei Qu, Saisi Zhang, Tongtong Gao, Yufei Shi, Hongyu Song, Kaichen Chen, Wei Yin, Weiwei |
author_facet | Liu, Junwei Qu, Saisi Zhang, Tongtong Gao, Yufei Shi, Hongyu Song, Kaichen Chen, Wei Yin, Weiwei |
author_sort | Liu, Junwei |
collection | PubMed |
description | The tumor microenvironment (TME) is an ecosystem that contains various cell types, including cancer cells, immune cells, stromal cells, and many others. In the TME, cancer cells aggressively proliferate, evolve, transmigrate to the circulation system and other organs, and frequently communicate with adjacent immune cells to suppress local tumor immunity. It is essential to delineate this ecosystem’s complex cellular compositions and their dynamic intercellular interactions to understand cancer biology and tumor immunology and to benefit tumor immunotherapy. But technically, this is extremely challenging due to the high complexities of the TME. The rapid developments of single-cell techniques provide us powerful means to systemically profile the multiple omics status of the TME at a single-cell resolution, shedding light on the pathogenic mechanisms of cancers and dysfunctions of tumor immunity in an unprecedently resolution. Furthermore, more advanced techniques have been developed to simultaneously characterize multi-omics and even spatial information at the single-cell level, helping us reveal the phenotypes and functionalities of disease-specific cell populations more comprehensively. Meanwhile, the connections between single-cell data and clinical characteristics are also intensively interrogated to achieve better clinical diagnosis and prognosis. In this review, we summarize recent progress in single-cell techniques, discuss their technical advantages, limitations, and applications, particularly in tumor biology and immunology, aiming to promote the research of cancer pathogenesis, clinically relevant cancer diagnosis, prognosis, and immunotherapy design with the help of single-cell techniques. |
format | Online Article Text |
id | pubmed-8221107 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-82211072021-06-24 Applications of Single-Cell Omics in Tumor Immunology Liu, Junwei Qu, Saisi Zhang, Tongtong Gao, Yufei Shi, Hongyu Song, Kaichen Chen, Wei Yin, Weiwei Front Immunol Immunology The tumor microenvironment (TME) is an ecosystem that contains various cell types, including cancer cells, immune cells, stromal cells, and many others. In the TME, cancer cells aggressively proliferate, evolve, transmigrate to the circulation system and other organs, and frequently communicate with adjacent immune cells to suppress local tumor immunity. It is essential to delineate this ecosystem’s complex cellular compositions and their dynamic intercellular interactions to understand cancer biology and tumor immunology and to benefit tumor immunotherapy. But technically, this is extremely challenging due to the high complexities of the TME. The rapid developments of single-cell techniques provide us powerful means to systemically profile the multiple omics status of the TME at a single-cell resolution, shedding light on the pathogenic mechanisms of cancers and dysfunctions of tumor immunity in an unprecedently resolution. Furthermore, more advanced techniques have been developed to simultaneously characterize multi-omics and even spatial information at the single-cell level, helping us reveal the phenotypes and functionalities of disease-specific cell populations more comprehensively. Meanwhile, the connections between single-cell data and clinical characteristics are also intensively interrogated to achieve better clinical diagnosis and prognosis. In this review, we summarize recent progress in single-cell techniques, discuss their technical advantages, limitations, and applications, particularly in tumor biology and immunology, aiming to promote the research of cancer pathogenesis, clinically relevant cancer diagnosis, prognosis, and immunotherapy design with the help of single-cell techniques. Frontiers Media S.A. 2021-06-09 /pmc/articles/PMC8221107/ /pubmed/34177965 http://dx.doi.org/10.3389/fimmu.2021.697412 Text en Copyright © 2021 Liu, Qu, Zhang, Gao, Shi, Song, Chen and Yin https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Immunology Liu, Junwei Qu, Saisi Zhang, Tongtong Gao, Yufei Shi, Hongyu Song, Kaichen Chen, Wei Yin, Weiwei Applications of Single-Cell Omics in Tumor Immunology |
title | Applications of Single-Cell Omics in Tumor Immunology |
title_full | Applications of Single-Cell Omics in Tumor Immunology |
title_fullStr | Applications of Single-Cell Omics in Tumor Immunology |
title_full_unstemmed | Applications of Single-Cell Omics in Tumor Immunology |
title_short | Applications of Single-Cell Omics in Tumor Immunology |
title_sort | applications of single-cell omics in tumor immunology |
topic | Immunology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8221107/ https://www.ncbi.nlm.nih.gov/pubmed/34177965 http://dx.doi.org/10.3389/fimmu.2021.697412 |
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