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High-throughput single-сell sequencing in cancer research
With advances in sequencing and instrument technology, bioinformatics analysis is being applied to batches of massive cells at single-cell resolution. High-throughput single-cell sequencing can be utilized for multi-omics characterization of tumor cells, stromal cells or infiltrated immune cells to...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9065032/ https://www.ncbi.nlm.nih.gov/pubmed/35504878 http://dx.doi.org/10.1038/s41392-022-00990-4 |
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author | Jia, Qingzhu Chu, Han Jin, Zheng Long, Haixia Zhu, Bo |
author_facet | Jia, Qingzhu Chu, Han Jin, Zheng Long, Haixia Zhu, Bo |
author_sort | Jia, Qingzhu |
collection | PubMed |
description | With advances in sequencing and instrument technology, bioinformatics analysis is being applied to batches of massive cells at single-cell resolution. High-throughput single-cell sequencing can be utilized for multi-omics characterization of tumor cells, stromal cells or infiltrated immune cells to evaluate tumor progression, responses to environmental perturbations, heterogeneous composition of the tumor microenvironment, and complex intercellular interactions between these factors. Particularly, single-cell sequencing of T cell receptors, alone or in combination with single-cell RNA sequencing, is useful in the fields of tumor immunology and immunotherapy. Clinical insights obtained from single-cell analysis are critically important for exploring the biomarkers of disease progression or antitumor treatment, as well as for guiding precise clinical decision-making for patients with malignant tumors. In this review, we summarize the clinical applications of single-cell sequencing in the fields of tumor cell evolution, tumor immunology, and tumor immunotherapy. Additionally, we analyze the tumor cell response to antitumor treatment, heterogeneity of the tumor microenvironment, and response or resistance to immune checkpoint immunotherapy. The limitations of single-cell analysis in cancer research are also discussed. |
format | Online Article Text |
id | pubmed-9065032 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-90650322022-05-04 High-throughput single-сell sequencing in cancer research Jia, Qingzhu Chu, Han Jin, Zheng Long, Haixia Zhu, Bo Signal Transduct Target Ther Review Article With advances in sequencing and instrument technology, bioinformatics analysis is being applied to batches of massive cells at single-cell resolution. High-throughput single-cell sequencing can be utilized for multi-omics characterization of tumor cells, stromal cells or infiltrated immune cells to evaluate tumor progression, responses to environmental perturbations, heterogeneous composition of the tumor microenvironment, and complex intercellular interactions between these factors. Particularly, single-cell sequencing of T cell receptors, alone or in combination with single-cell RNA sequencing, is useful in the fields of tumor immunology and immunotherapy. Clinical insights obtained from single-cell analysis are critically important for exploring the biomarkers of disease progression or antitumor treatment, as well as for guiding precise clinical decision-making for patients with malignant tumors. In this review, we summarize the clinical applications of single-cell sequencing in the fields of tumor cell evolution, tumor immunology, and tumor immunotherapy. Additionally, we analyze the tumor cell response to antitumor treatment, heterogeneity of the tumor microenvironment, and response or resistance to immune checkpoint immunotherapy. The limitations of single-cell analysis in cancer research are also discussed. Nature Publishing Group UK 2022-05-03 /pmc/articles/PMC9065032/ /pubmed/35504878 http://dx.doi.org/10.1038/s41392-022-00990-4 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Review Article Jia, Qingzhu Chu, Han Jin, Zheng Long, Haixia Zhu, Bo High-throughput single-сell sequencing in cancer research |
title | High-throughput single-сell sequencing in cancer research |
title_full | High-throughput single-сell sequencing in cancer research |
title_fullStr | High-throughput single-сell sequencing in cancer research |
title_full_unstemmed | High-throughput single-сell sequencing in cancer research |
title_short | High-throughput single-сell sequencing in cancer research |
title_sort | high-throughput single-сell sequencing in cancer research |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9065032/ https://www.ncbi.nlm.nih.gov/pubmed/35504878 http://dx.doi.org/10.1038/s41392-022-00990-4 |
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