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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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Xi'an Jiaotong University
2023
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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. |
format | Online Article Text |
id | pubmed-10499658 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Xi'an Jiaotong University |
record_format | MEDLINE/PubMed |
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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