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Promise of spatially resolved omics for tumor research

Tumors are spatially heterogeneous tissues that comprise numerous cell types with intricate structures. By interacting with the microenvironment, tumor cells undergo dynamic changes in gene expression and metabolism, resulting in spatiotemporal variations in their capacity for proliferation and meta...

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Detalles Bibliográficos
Autores principales: Zhou, Yanhe, Jiang, Xinyi, Wang, Xiangyi, Huang, Jianpeng, Li, Tong, Jin, Hongtao, He, Jiuming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Xi'an Jiaotong University 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10499658/
https://www.ncbi.nlm.nih.gov/pubmed/37719191
http://dx.doi.org/10.1016/j.jpha.2023.07.003
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author Zhou, Yanhe
Jiang, Xinyi
Wang, Xiangyi
Huang, Jianpeng
Li, Tong
Jin, Hongtao
He, Jiuming
author_facet Zhou, Yanhe
Jiang, Xinyi
Wang, Xiangyi
Huang, Jianpeng
Li, Tong
Jin, Hongtao
He, Jiuming
author_sort Zhou, Yanhe
collection PubMed
description Tumors are spatially heterogeneous tissues that comprise numerous cell types with intricate structures. By interacting with the microenvironment, tumor cells undergo dynamic changes in gene expression and metabolism, resulting in spatiotemporal variations in their capacity for proliferation and metastasis. In recent years, the rapid development of histological techniques has enabled efficient and high-throughput biomolecule analysis. By preserving location information while obtaining a large number of gene and molecular data, spatially resolved metabolomics (SRM) and spatially resolved transcriptomics (SRT) approaches can offer new ideas and reliable tools for the in-depth study of tumors. This review provides a comprehensive introduction and summary of the fundamental principles and research methods used for SRM and SRT techniques, as well as a review of their applications in cancer-related fields.
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spelling pubmed-104996582023-09-15 Promise of spatially resolved omics for tumor research Zhou, Yanhe Jiang, Xinyi Wang, Xiangyi Huang, Jianpeng Li, Tong Jin, Hongtao He, Jiuming J Pharm Anal Review Paper Tumors are spatially heterogeneous tissues that comprise numerous cell types with intricate structures. By interacting with the microenvironment, tumor cells undergo dynamic changes in gene expression and metabolism, resulting in spatiotemporal variations in their capacity for proliferation and metastasis. In recent years, the rapid development of histological techniques has enabled efficient and high-throughput biomolecule analysis. By preserving location information while obtaining a large number of gene and molecular data, spatially resolved metabolomics (SRM) and spatially resolved transcriptomics (SRT) approaches can offer new ideas and reliable tools for the in-depth study of tumors. This review provides a comprehensive introduction and summary of the fundamental principles and research methods used for SRM and SRT techniques, as well as a review of their applications in cancer-related fields. Xi'an Jiaotong University 2023-08 2023-07-13 /pmc/articles/PMC10499658/ /pubmed/37719191 http://dx.doi.org/10.1016/j.jpha.2023.07.003 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Review Paper
Zhou, Yanhe
Jiang, Xinyi
Wang, Xiangyi
Huang, Jianpeng
Li, Tong
Jin, Hongtao
He, Jiuming
Promise of spatially resolved omics for tumor research
title Promise of spatially resolved omics for tumor research
title_full Promise of spatially resolved omics for tumor research
title_fullStr Promise of spatially resolved omics for tumor research
title_full_unstemmed Promise of spatially resolved omics for tumor research
title_short Promise of spatially resolved omics for tumor research
title_sort promise of spatially resolved omics for tumor research
topic Review Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10499658/
https://www.ncbi.nlm.nih.gov/pubmed/37719191
http://dx.doi.org/10.1016/j.jpha.2023.07.003
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