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A Single-Cell Atlas of the Tumor and Immune Ecosystem of Human Breast Cancer
Breast cancer is a heterogeneous disease. Tumor cells and associated healthy cells form ecosystems that determine disease progression and response to therapy. To characterize features of breast cancer ecosystems and their associations with clinical data, we analyzed 144 human breast tumor and 50 non...
Autores principales: | , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cell Press
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6526772/ https://www.ncbi.nlm.nih.gov/pubmed/30982598 http://dx.doi.org/10.1016/j.cell.2019.03.005 |
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author | Wagner, Johanna Rapsomaniki, Maria Anna Chevrier, Stéphane Anzeneder, Tobias Langwieder, Claus Dykgers, August Rees, Martin Ramaswamy, Annette Muenst, Simone Soysal, Savas Deniz Jacobs, Andrea Windhager, Jonas Silina, Karina van den Broek, Maries Dedes, Konstantin Johannes Rodríguez Martínez, Maria Weber, Walter Paul Bodenmiller, Bernd |
author_facet | Wagner, Johanna Rapsomaniki, Maria Anna Chevrier, Stéphane Anzeneder, Tobias Langwieder, Claus Dykgers, August Rees, Martin Ramaswamy, Annette Muenst, Simone Soysal, Savas Deniz Jacobs, Andrea Windhager, Jonas Silina, Karina van den Broek, Maries Dedes, Konstantin Johannes Rodríguez Martínez, Maria Weber, Walter Paul Bodenmiller, Bernd |
author_sort | Wagner, Johanna |
collection | PubMed |
description | Breast cancer is a heterogeneous disease. Tumor cells and associated healthy cells form ecosystems that determine disease progression and response to therapy. To characterize features of breast cancer ecosystems and their associations with clinical data, we analyzed 144 human breast tumor and 50 non-tumor tissue samples using mass cytometry. The expression of 73 proteins in 26 million cells was evaluated using tumor and immune cell-centric antibody panels. Tumors displayed individuality in tumor cell composition, including phenotypic abnormalities and phenotype dominance. Relationship analyses between tumor and immune cells revealed characteristics of ecosystems related to immunosuppression and poor prognosis. High frequencies of PD-L1(+) tumor-associated macrophages and exhausted T cells were found in high-grade ER(+) and ER(−) tumors. This large-scale, single-cell atlas deepens our understanding of breast tumor ecosystems and suggests that ecosystem-based patient classification will facilitate identification of individuals for precision medicine approaches targeting the tumor and its immunoenvironment. |
format | Online Article Text |
id | pubmed-6526772 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Cell Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-65267722019-05-28 A Single-Cell Atlas of the Tumor and Immune Ecosystem of Human Breast Cancer Wagner, Johanna Rapsomaniki, Maria Anna Chevrier, Stéphane Anzeneder, Tobias Langwieder, Claus Dykgers, August Rees, Martin Ramaswamy, Annette Muenst, Simone Soysal, Savas Deniz Jacobs, Andrea Windhager, Jonas Silina, Karina van den Broek, Maries Dedes, Konstantin Johannes Rodríguez Martínez, Maria Weber, Walter Paul Bodenmiller, Bernd Cell Article Breast cancer is a heterogeneous disease. Tumor cells and associated healthy cells form ecosystems that determine disease progression and response to therapy. To characterize features of breast cancer ecosystems and their associations with clinical data, we analyzed 144 human breast tumor and 50 non-tumor tissue samples using mass cytometry. The expression of 73 proteins in 26 million cells was evaluated using tumor and immune cell-centric antibody panels. Tumors displayed individuality in tumor cell composition, including phenotypic abnormalities and phenotype dominance. Relationship analyses between tumor and immune cells revealed characteristics of ecosystems related to immunosuppression and poor prognosis. High frequencies of PD-L1(+) tumor-associated macrophages and exhausted T cells were found in high-grade ER(+) and ER(−) tumors. This large-scale, single-cell atlas deepens our understanding of breast tumor ecosystems and suggests that ecosystem-based patient classification will facilitate identification of individuals for precision medicine approaches targeting the tumor and its immunoenvironment. Cell Press 2019-05-16 /pmc/articles/PMC6526772/ /pubmed/30982598 http://dx.doi.org/10.1016/j.cell.2019.03.005 Text en © 2019 The Authors http://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 | Article Wagner, Johanna Rapsomaniki, Maria Anna Chevrier, Stéphane Anzeneder, Tobias Langwieder, Claus Dykgers, August Rees, Martin Ramaswamy, Annette Muenst, Simone Soysal, Savas Deniz Jacobs, Andrea Windhager, Jonas Silina, Karina van den Broek, Maries Dedes, Konstantin Johannes Rodríguez Martínez, Maria Weber, Walter Paul Bodenmiller, Bernd A Single-Cell Atlas of the Tumor and Immune Ecosystem of Human Breast Cancer |
title | A Single-Cell Atlas of the Tumor and Immune Ecosystem of Human Breast Cancer |
title_full | A Single-Cell Atlas of the Tumor and Immune Ecosystem of Human Breast Cancer |
title_fullStr | A Single-Cell Atlas of the Tumor and Immune Ecosystem of Human Breast Cancer |
title_full_unstemmed | A Single-Cell Atlas of the Tumor and Immune Ecosystem of Human Breast Cancer |
title_short | A Single-Cell Atlas of the Tumor and Immune Ecosystem of Human Breast Cancer |
title_sort | single-cell atlas of the tumor and immune ecosystem of human breast cancer |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6526772/ https://www.ncbi.nlm.nih.gov/pubmed/30982598 http://dx.doi.org/10.1016/j.cell.2019.03.005 |
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