Cargando…
Deciphering cell–cell interactions and communication in the tumor microenvironment and unraveling intratumoral genetic heterogeneity via single-cell genomic sequencing
A tumor’s heterogeneity has important implications in terms of its clonal origin, progression, stemness, and drug resistance. Therefore, because of its significance in treatment, it is important to understand the gene expression pattern of a single cell, track gene expression or mutation in heteroge...
Autores principales: | , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Taylor & Francis
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10234225/ https://www.ncbi.nlm.nih.gov/pubmed/37105769 http://dx.doi.org/10.1080/21655979.2023.2185434 |
_version_ | 1785052439943053312 |
---|---|
author | Cao, Ya-Hong Ding, Jie Tang, Qing-Hai Zhang, Jie Huang, Zhong-Yan Tang, Xiao-Mei Liu, Ji-Bin Ma, Yu-Shui Fu, Da |
author_facet | Cao, Ya-Hong Ding, Jie Tang, Qing-Hai Zhang, Jie Huang, Zhong-Yan Tang, Xiao-Mei Liu, Ji-Bin Ma, Yu-Shui Fu, Da |
author_sort | Cao, Ya-Hong |
collection | PubMed |
description | A tumor’s heterogeneity has important implications in terms of its clonal origin, progression, stemness, and drug resistance. Therefore, because of its significance in treatment, it is important to understand the gene expression pattern of a single cell, track gene expression or mutation in heterogeneous cells, evaluate the clonal origin of cancer cells, and determine the selective evolution of different subpopulations of cancer cells. Researchers are able to trace a cell’s mutation and identify different types of tumor cells by measuring the whole transcriptome with single-cell sequencing (scRNA-seq). This technology provides a better understanding of the molecular mechanisms driving tumor growth than that offered by traditional RNA sequencing methods. In addition, it has revealed changes in the mutations and functions of somatic cells as a tumor evolves; it has also clarified immune cell infiltration and activation. Research on scRNA-seq technology has recently advanced significantly, suggesting new strategies for the treatment of cancer. In short, cancer researchers have become increasingly dependent on scRNA-seq. This paper reviews the development, detection principles, and processes of scRNA-seq technology and their application in tumor research. It also considers potential clinical applications. |
format | Online Article Text |
id | pubmed-10234225 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Taylor & Francis |
record_format | MEDLINE/PubMed |
spelling | pubmed-102342252023-06-02 Deciphering cell–cell interactions and communication in the tumor microenvironment and unraveling intratumoral genetic heterogeneity via single-cell genomic sequencing Cao, Ya-Hong Ding, Jie Tang, Qing-Hai Zhang, Jie Huang, Zhong-Yan Tang, Xiao-Mei Liu, Ji-Bin Ma, Yu-Shui Fu, Da Bioengineered Research Article A tumor’s heterogeneity has important implications in terms of its clonal origin, progression, stemness, and drug resistance. Therefore, because of its significance in treatment, it is important to understand the gene expression pattern of a single cell, track gene expression or mutation in heterogeneous cells, evaluate the clonal origin of cancer cells, and determine the selective evolution of different subpopulations of cancer cells. Researchers are able to trace a cell’s mutation and identify different types of tumor cells by measuring the whole transcriptome with single-cell sequencing (scRNA-seq). This technology provides a better understanding of the molecular mechanisms driving tumor growth than that offered by traditional RNA sequencing methods. In addition, it has revealed changes in the mutations and functions of somatic cells as a tumor evolves; it has also clarified immune cell infiltration and activation. Research on scRNA-seq technology has recently advanced significantly, suggesting new strategies for the treatment of cancer. In short, cancer researchers have become increasingly dependent on scRNA-seq. This paper reviews the development, detection principles, and processes of scRNA-seq technology and their application in tumor research. It also considers potential clinical applications. Taylor & Francis 2023-04-27 /pmc/articles/PMC10234225/ /pubmed/37105769 http://dx.doi.org/10.1080/21655979.2023.2185434 Text en © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent. |
spellingShingle | Research Article Cao, Ya-Hong Ding, Jie Tang, Qing-Hai Zhang, Jie Huang, Zhong-Yan Tang, Xiao-Mei Liu, Ji-Bin Ma, Yu-Shui Fu, Da Deciphering cell–cell interactions and communication in the tumor microenvironment and unraveling intratumoral genetic heterogeneity via single-cell genomic sequencing |
title | Deciphering cell–cell interactions and communication in the tumor microenvironment and unraveling intratumoral genetic heterogeneity via single-cell genomic sequencing |
title_full | Deciphering cell–cell interactions and communication in the tumor microenvironment and unraveling intratumoral genetic heterogeneity via single-cell genomic sequencing |
title_fullStr | Deciphering cell–cell interactions and communication in the tumor microenvironment and unraveling intratumoral genetic heterogeneity via single-cell genomic sequencing |
title_full_unstemmed | Deciphering cell–cell interactions and communication in the tumor microenvironment and unraveling intratumoral genetic heterogeneity via single-cell genomic sequencing |
title_short | Deciphering cell–cell interactions and communication in the tumor microenvironment and unraveling intratumoral genetic heterogeneity via single-cell genomic sequencing |
title_sort | deciphering cell–cell interactions and communication in the tumor microenvironment and unraveling intratumoral genetic heterogeneity via single-cell genomic sequencing |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10234225/ https://www.ncbi.nlm.nih.gov/pubmed/37105769 http://dx.doi.org/10.1080/21655979.2023.2185434 |
work_keys_str_mv | AT caoyahong decipheringcellcellinteractionsandcommunicationinthetumormicroenvironmentandunravelingintratumoralgeneticheterogeneityviasinglecellgenomicsequencing AT dingjie decipheringcellcellinteractionsandcommunicationinthetumormicroenvironmentandunravelingintratumoralgeneticheterogeneityviasinglecellgenomicsequencing AT tangqinghai decipheringcellcellinteractionsandcommunicationinthetumormicroenvironmentandunravelingintratumoralgeneticheterogeneityviasinglecellgenomicsequencing AT zhangjie decipheringcellcellinteractionsandcommunicationinthetumormicroenvironmentandunravelingintratumoralgeneticheterogeneityviasinglecellgenomicsequencing AT huangzhongyan decipheringcellcellinteractionsandcommunicationinthetumormicroenvironmentandunravelingintratumoralgeneticheterogeneityviasinglecellgenomicsequencing AT tangxiaomei decipheringcellcellinteractionsandcommunicationinthetumormicroenvironmentandunravelingintratumoralgeneticheterogeneityviasinglecellgenomicsequencing AT liujibin decipheringcellcellinteractionsandcommunicationinthetumormicroenvironmentandunravelingintratumoralgeneticheterogeneityviasinglecellgenomicsequencing AT mayushui decipheringcellcellinteractionsandcommunicationinthetumormicroenvironmentandunravelingintratumoralgeneticheterogeneityviasinglecellgenomicsequencing AT fuda decipheringcellcellinteractionsandcommunicationinthetumormicroenvironmentandunravelingintratumoralgeneticheterogeneityviasinglecellgenomicsequencing |