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Mapping Spatiotemporal Heterogeneity in Tumor Profiles by Integrating High-Throughput Imaging and Omics Analysis
[Image: see text] Intratumoral heterogeneity associates with more aggressive disease progression and worse patient outcomes. Understanding the reasons enabling the emergence of such heterogeneity remains incomplete, which restricts our ability to manage it from a therapeutic perspective. Technologic...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9948167/ https://www.ncbi.nlm.nih.gov/pubmed/36844580 http://dx.doi.org/10.1021/acsomega.2c06659 |
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author | Patkulkar, Pooja Annasaheb Subbalakshmi, Ayalur Raghu Jolly, Mohit Kumar Sinharay, Sanhita |
author_facet | Patkulkar, Pooja Annasaheb Subbalakshmi, Ayalur Raghu Jolly, Mohit Kumar Sinharay, Sanhita |
author_sort | Patkulkar, Pooja Annasaheb |
collection | PubMed |
description | [Image: see text] Intratumoral heterogeneity associates with more aggressive disease progression and worse patient outcomes. Understanding the reasons enabling the emergence of such heterogeneity remains incomplete, which restricts our ability to manage it from a therapeutic perspective. Technological advancements such as high-throughput molecular imaging, single-cell omics, and spatial transcriptomics allow recording of patterns of spatiotemporal heterogeneity in a longitudinal manner, thus offering insights into the multiscale dynamics of its evolution. Here, we review the latest technological trends and biological insights from molecular diagnostics as well as spatial transcriptomics, both of which have witnessed burgeoning growth in the recent past in terms of mapping heterogeneity within tumor cell types as well as the stromal constitution. We also discuss ongoing challenges, indicating possible ways to integrate insights across these methods to have a systems-level spatiotemporal map of heterogeneity in each tumor and a more systematic investigation of the implications of heterogeneity for patient outcomes. |
format | Online Article Text |
id | pubmed-9948167 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-99481672023-02-24 Mapping Spatiotemporal Heterogeneity in Tumor Profiles by Integrating High-Throughput Imaging and Omics Analysis Patkulkar, Pooja Annasaheb Subbalakshmi, Ayalur Raghu Jolly, Mohit Kumar Sinharay, Sanhita ACS Omega [Image: see text] Intratumoral heterogeneity associates with more aggressive disease progression and worse patient outcomes. Understanding the reasons enabling the emergence of such heterogeneity remains incomplete, which restricts our ability to manage it from a therapeutic perspective. Technological advancements such as high-throughput molecular imaging, single-cell omics, and spatial transcriptomics allow recording of patterns of spatiotemporal heterogeneity in a longitudinal manner, thus offering insights into the multiscale dynamics of its evolution. Here, we review the latest technological trends and biological insights from molecular diagnostics as well as spatial transcriptomics, both of which have witnessed burgeoning growth in the recent past in terms of mapping heterogeneity within tumor cell types as well as the stromal constitution. We also discuss ongoing challenges, indicating possible ways to integrate insights across these methods to have a systems-level spatiotemporal map of heterogeneity in each tumor and a more systematic investigation of the implications of heterogeneity for patient outcomes. American Chemical Society 2023-02-07 /pmc/articles/PMC9948167/ /pubmed/36844580 http://dx.doi.org/10.1021/acsomega.2c06659 Text en © 2023 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by-nc-nd/4.0/Permits non-commercial access and re-use, provided that author attribution and integrity are maintained; but does not permit creation of adaptations or other derivative works (https://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Patkulkar, Pooja Annasaheb Subbalakshmi, Ayalur Raghu Jolly, Mohit Kumar Sinharay, Sanhita Mapping Spatiotemporal Heterogeneity in Tumor Profiles by Integrating High-Throughput Imaging and Omics Analysis |
title | Mapping Spatiotemporal
Heterogeneity in Tumor Profiles
by Integrating High-Throughput Imaging and Omics Analysis |
title_full | Mapping Spatiotemporal
Heterogeneity in Tumor Profiles
by Integrating High-Throughput Imaging and Omics Analysis |
title_fullStr | Mapping Spatiotemporal
Heterogeneity in Tumor Profiles
by Integrating High-Throughput Imaging and Omics Analysis |
title_full_unstemmed | Mapping Spatiotemporal
Heterogeneity in Tumor Profiles
by Integrating High-Throughput Imaging and Omics Analysis |
title_short | Mapping Spatiotemporal
Heterogeneity in Tumor Profiles
by Integrating High-Throughput Imaging and Omics Analysis |
title_sort | mapping spatiotemporal
heterogeneity in tumor profiles
by integrating high-throughput imaging and omics analysis |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9948167/ https://www.ncbi.nlm.nih.gov/pubmed/36844580 http://dx.doi.org/10.1021/acsomega.2c06659 |
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