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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Published inJournal of pharmaceutical analysis Vol. 13; no. 8; pp. 851 - 861
Main Authors Zhou, Yanhe, Jiang, Xinyi, Wang, Xiangyi, Huang, Jianpeng, Li, Tong, Jin, Hongtao, He, Jiuming
Format Journal Article
LanguageEnglish
Published Xi'an Elsevier B.V 01.08.2023
Xi'an Jiaotong University, Journal of Pharmaceutical Analysis
Xi'an Jiaotong University
Elsevier
Subjects
Bar codes
Cancer
Gene expression
Lipids
Mass spectrometry
Medical research
Metabolism
Metabolites
Metabolomics
Metastases
Metastasis
Microenvironments
Peptides
Proteins
Review Paper
Scientific imaging
Spatially resolved metabolomics
Spatially resolved transcriptomics
Transcriptomics
Tumor
Tumor cells
Tumors
Spatially resolved transcriptomics
Spatially resolved metabolomics
Tumor
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Abstract 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. [Display omitted] •The principles and characteristics of SRT and SRM techniques are summarized.•Tumors show spatiotemporal variation via microenvironment interactions.•Single-cell spatially resolved omics reveals tumor heterogeneity.
AbstractList 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.
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. [Display omitted] •The principles and characteristics of SRT and SRM techniques are summarized.•Tumors show spatiotemporal variation via microenvironment interactions.•Single-cell spatially resolved omics reveals tumor heterogeneity.
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. Image 1 • The principles and characteristics of SRT and SRM techniques are summarized. • Tumors show spatiotemporal variation via microenvironment interactions. • Single-cell spatially resolved omics reveals tumor heterogeneity.
Author Li, Tong
Huang, Jianpeng
Zhou, Yanhe
Jin, Hongtao
He, Jiuming
Jiang, Xinyi
Wang, Xiangyi
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Keywords Spatially resolved transcriptomics
Spatially resolved metabolomics
Tumor
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Snippet Tumors are spatially heterogeneous tissues that comprise numerous cell types with intricate structures. By interacting with the microenvironment, tumor cells...
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SubjectTerms Bar codes
Cancer
Gene expression
Lipids
Mass spectrometry
Medical research
Metabolism
Metabolites
Metabolomics
Metastases
Metastasis
Microenvironments
Peptides
Proteins
Review Paper
Scientific imaging
Spatially resolved metabolomics
Spatially resolved transcriptomics
Transcriptomics
Tumor
Tumor cells
Tumors
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Title Promise of spatially resolved omics for tumor research
URI https://dx.doi.org/10.1016/j.jpha.2023.07.003
https://www.proquest.com/docview/2883818029
https://search.proquest.com/docview/2866109294
https://pubmed.ncbi.nlm.nih.gov/PMC10499658
https://doaj.org/article/35740b452582448480e62c512e53619f
Volume 13
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