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Single-cell and spatially resolved analysis uncovers cell heterogeneity of breast cancer

The heterogeneity and the complex cellular architecture have a crucial effect on breast cancer progression and response to treatment. However, deciphering the neoplastic subtypes and their spatial organization is still challenging. Here, we combine single-nucleus RNA sequencing (snRNA-seq) with a mi...

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Autores principales: Liu, Si-Qing, Gao, Zhi-Jie, Wu, Juan, Zheng, Hong-Mei, Li, Bei, Sun, Si, Meng, Xiang-Yu, Wu, Qi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8895670/
https://www.ncbi.nlm.nih.gov/pubmed/35241110
http://dx.doi.org/10.1186/s13045-022-01236-0
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author Liu, Si-Qing
Gao, Zhi-Jie
Wu, Juan
Zheng, Hong-Mei
Li, Bei
Sun, Si
Meng, Xiang-Yu
Wu, Qi
author_facet Liu, Si-Qing
Gao, Zhi-Jie
Wu, Juan
Zheng, Hong-Mei
Li, Bei
Sun, Si
Meng, Xiang-Yu
Wu, Qi
author_sort Liu, Si-Qing
collection PubMed
description The heterogeneity and the complex cellular architecture have a crucial effect on breast cancer progression and response to treatment. However, deciphering the neoplastic subtypes and their spatial organization is still challenging. Here, we combine single-nucleus RNA sequencing (snRNA-seq) with a microarray-based spatial transcriptomics (ST) to identify cell populations and their spatial distribution in breast cancer tissues. Malignant cells are clustered into distinct subpopulations. These cell clusters not only have diverse features, origins and functions, but also emerge to the crosstalk within subtypes. Furthermore, we find that these subclusters are mapped in distinct tissue regions, where discrepant enrichment of stromal cell types are observed. We also inferred the abundance of these tumorous subpopulations by deconvolution of large breast cancer RNA-seq cohorts, revealing differential association with patient survival and therapeutic response. Our study provides a novel insight for the cellular architecture of breast cancer and potential therapeutic strategies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13045-022-01236-0.
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spelling pubmed-88956702022-03-10 Single-cell and spatially resolved analysis uncovers cell heterogeneity of breast cancer Liu, Si-Qing Gao, Zhi-Jie Wu, Juan Zheng, Hong-Mei Li, Bei Sun, Si Meng, Xiang-Yu Wu, Qi J Hematol Oncol Letter to the Editor The heterogeneity and the complex cellular architecture have a crucial effect on breast cancer progression and response to treatment. However, deciphering the neoplastic subtypes and their spatial organization is still challenging. Here, we combine single-nucleus RNA sequencing (snRNA-seq) with a microarray-based spatial transcriptomics (ST) to identify cell populations and their spatial distribution in breast cancer tissues. Malignant cells are clustered into distinct subpopulations. These cell clusters not only have diverse features, origins and functions, but also emerge to the crosstalk within subtypes. Furthermore, we find that these subclusters are mapped in distinct tissue regions, where discrepant enrichment of stromal cell types are observed. We also inferred the abundance of these tumorous subpopulations by deconvolution of large breast cancer RNA-seq cohorts, revealing differential association with patient survival and therapeutic response. Our study provides a novel insight for the cellular architecture of breast cancer and potential therapeutic strategies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13045-022-01236-0. BioMed Central 2022-03-03 /pmc/articles/PMC8895670/ /pubmed/35241110 http://dx.doi.org/10.1186/s13045-022-01236-0 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Letter to the Editor
Liu, Si-Qing
Gao, Zhi-Jie
Wu, Juan
Zheng, Hong-Mei
Li, Bei
Sun, Si
Meng, Xiang-Yu
Wu, Qi
Single-cell and spatially resolved analysis uncovers cell heterogeneity of breast cancer
title Single-cell and spatially resolved analysis uncovers cell heterogeneity of breast cancer
title_full Single-cell and spatially resolved analysis uncovers cell heterogeneity of breast cancer
title_fullStr Single-cell and spatially resolved analysis uncovers cell heterogeneity of breast cancer
title_full_unstemmed Single-cell and spatially resolved analysis uncovers cell heterogeneity of breast cancer
title_short Single-cell and spatially resolved analysis uncovers cell heterogeneity of breast cancer
title_sort single-cell and spatially resolved analysis uncovers cell heterogeneity of breast cancer
topic Letter to the Editor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8895670/
https://www.ncbi.nlm.nih.gov/pubmed/35241110
http://dx.doi.org/10.1186/s13045-022-01236-0
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