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Spatial Transcriptomics for Tumor Heterogeneity Analysis

The molecular heterogeneity of cancer is one of the major causes of drug resistance that leads to treatment failure. Thus, better understanding the heterogeneity of cancer will contribute to more precise diagnosis and improved patient outcomes. Although single-cell sequencing has become an important...

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Detalles Bibliográficos
Autores principales: Li, Qiongyu, Zhang, Xinya, Ke, Rongqin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9309247/
https://www.ncbi.nlm.nih.gov/pubmed/35899203
http://dx.doi.org/10.3389/fgene.2022.906158
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author Li, Qiongyu
Zhang, Xinya
Ke, Rongqin
author_facet Li, Qiongyu
Zhang, Xinya
Ke, Rongqin
author_sort Li, Qiongyu
collection PubMed
description The molecular heterogeneity of cancer is one of the major causes of drug resistance that leads to treatment failure. Thus, better understanding the heterogeneity of cancer will contribute to more precise diagnosis and improved patient outcomes. Although single-cell sequencing has become an important tool for investigating tumor heterogeneity recently, it lacks the spatial information of analyzed cells. In this regard, spatial transcriptomics holds great promise in deciphering the complex heterogeneity of cancer by providing localization-indexed gene expression information. This study reviews the applications of spatial transcriptomics in the study of tumor heterogeneity, discovery of novel spatial-dependent mechanisms, tumor immune microenvironment, and matrix microenvironment, as well as the pathological classification and prognosis of cancer. Finally, future challenges and opportunities for spatial transcriptomics technology’s applications in cancer are also discussed.
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spelling pubmed-93092472022-07-26 Spatial Transcriptomics for Tumor Heterogeneity Analysis Li, Qiongyu Zhang, Xinya Ke, Rongqin Front Genet Genetics The molecular heterogeneity of cancer is one of the major causes of drug resistance that leads to treatment failure. Thus, better understanding the heterogeneity of cancer will contribute to more precise diagnosis and improved patient outcomes. Although single-cell sequencing has become an important tool for investigating tumor heterogeneity recently, it lacks the spatial information of analyzed cells. In this regard, spatial transcriptomics holds great promise in deciphering the complex heterogeneity of cancer by providing localization-indexed gene expression information. This study reviews the applications of spatial transcriptomics in the study of tumor heterogeneity, discovery of novel spatial-dependent mechanisms, tumor immune microenvironment, and matrix microenvironment, as well as the pathological classification and prognosis of cancer. Finally, future challenges and opportunities for spatial transcriptomics technology’s applications in cancer are also discussed. Frontiers Media S.A. 2022-07-05 /pmc/articles/PMC9309247/ /pubmed/35899203 http://dx.doi.org/10.3389/fgene.2022.906158 Text en Copyright © 2022 Li, Zhang and Ke. 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 Genetics
Li, Qiongyu
Zhang, Xinya
Ke, Rongqin
Spatial Transcriptomics for Tumor Heterogeneity Analysis
title Spatial Transcriptomics for Tumor Heterogeneity Analysis
title_full Spatial Transcriptomics for Tumor Heterogeneity Analysis
title_fullStr Spatial Transcriptomics for Tumor Heterogeneity Analysis
title_full_unstemmed Spatial Transcriptomics for Tumor Heterogeneity Analysis
title_short Spatial Transcriptomics for Tumor Heterogeneity Analysis
title_sort spatial transcriptomics for tumor heterogeneity analysis
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9309247/
https://www.ncbi.nlm.nih.gov/pubmed/35899203
http://dx.doi.org/10.3389/fgene.2022.906158
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AT zhangxinya spatialtranscriptomicsfortumorheterogeneityanalysis
AT kerongqin spatialtranscriptomicsfortumorheterogeneityanalysis