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The promising application of cell-cell interaction analysis in cancer from single-cell and spatial transcriptomics

Cell-cell interactions instruct cell fate and function. These interactions are hijacked to promote cancer development. Single-cell transcriptomics and spatial transcriptomics have become powerful new tools for researchers to profile the transcriptional landscape of cancer at unparalleled genetic dep...

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Detalles Bibliográficos
Autores principales: Wang, Xinyi, Almet, Axel A., Nie, Qing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10627116/
https://www.ncbi.nlm.nih.gov/pubmed/37454878
http://dx.doi.org/10.1016/j.semcancer.2023.07.001
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author Wang, Xinyi
Almet, Axel A.
Nie, Qing
author_facet Wang, Xinyi
Almet, Axel A.
Nie, Qing
author_sort Wang, Xinyi
collection PubMed
description Cell-cell interactions instruct cell fate and function. These interactions are hijacked to promote cancer development. Single-cell transcriptomics and spatial transcriptomics have become powerful new tools for researchers to profile the transcriptional landscape of cancer at unparalleled genetic depth. In this review, we discuss the rapidly growing array of computational tools to infer cell-cell interactions from non-spatial single-cell RNA-sequencing and the limited but growing number of methods for spatial transcriptomics data. Downstream analyses of these computational tools and applications to cancer studies are highlighted. We finish by suggesting several directions for further extensions that anticipate the increasing availability of multi-omics cancer data.
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spelling pubmed-106271162023-11-05 The promising application of cell-cell interaction analysis in cancer from single-cell and spatial transcriptomics Wang, Xinyi Almet, Axel A. Nie, Qing Semin Cancer Biol Article Cell-cell interactions instruct cell fate and function. These interactions are hijacked to promote cancer development. Single-cell transcriptomics and spatial transcriptomics have become powerful new tools for researchers to profile the transcriptional landscape of cancer at unparalleled genetic depth. In this review, we discuss the rapidly growing array of computational tools to infer cell-cell interactions from non-spatial single-cell RNA-sequencing and the limited but growing number of methods for spatial transcriptomics data. Downstream analyses of these computational tools and applications to cancer studies are highlighted. We finish by suggesting several directions for further extensions that anticipate the increasing availability of multi-omics cancer data. 2023-10 2023-07-15 /pmc/articles/PMC10627116/ /pubmed/37454878 http://dx.doi.org/10.1016/j.semcancer.2023.07.001 Text en https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ).
spellingShingle Article
Wang, Xinyi
Almet, Axel A.
Nie, Qing
The promising application of cell-cell interaction analysis in cancer from single-cell and spatial transcriptomics
title The promising application of cell-cell interaction analysis in cancer from single-cell and spatial transcriptomics
title_full The promising application of cell-cell interaction analysis in cancer from single-cell and spatial transcriptomics
title_fullStr The promising application of cell-cell interaction analysis in cancer from single-cell and spatial transcriptomics
title_full_unstemmed The promising application of cell-cell interaction analysis in cancer from single-cell and spatial transcriptomics
title_short The promising application of cell-cell interaction analysis in cancer from single-cell and spatial transcriptomics
title_sort promising application of cell-cell interaction analysis in cancer from single-cell and spatial transcriptomics
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10627116/
https://www.ncbi.nlm.nih.gov/pubmed/37454878
http://dx.doi.org/10.1016/j.semcancer.2023.07.001
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