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Prognostic correlations with the microbiome of breast cancer subtypes
Alterations to the natural microbiome are linked to different diseases, and the presence or absence of specific microbes is directly related to disease outcomes. We performed a comprehensive analysis with unique cohorts of the four subtypes of breast cancer (BC) characterized by their microbial sign...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8418604/ https://www.ncbi.nlm.nih.gov/pubmed/34482363 http://dx.doi.org/10.1038/s41419-021-04092-x |
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author | Banerjee, Sagarika Wei, Zhi Tian, Tian Bose, Dipayan Shih, Natalie N. C. Feldman, Michael D. Khoury, Thaer De Michele, Angela Robertson, Erle S. |
author_facet | Banerjee, Sagarika Wei, Zhi Tian, Tian Bose, Dipayan Shih, Natalie N. C. Feldman, Michael D. Khoury, Thaer De Michele, Angela Robertson, Erle S. |
author_sort | Banerjee, Sagarika |
collection | PubMed |
description | Alterations to the natural microbiome are linked to different diseases, and the presence or absence of specific microbes is directly related to disease outcomes. We performed a comprehensive analysis with unique cohorts of the four subtypes of breast cancer (BC) characterized by their microbial signatures, using a pan-pathogen microarray strategy. The signature (includes viruses, bacteria, fungi, and parasites) of each tumor subtype was correlated with clinical data to identify microbes with prognostic potential. The subtypes of BC had specific viromes and microbiomes, with ER+ and TN tumors showing the most and least diverse microbiome, respectively. The specific microbial signatures allowed discrimination between different BC subtypes. Furthermore, we demonstrated correlations between the presence and absence of specific microbes in BC subtypes with the clinical outcomes. This study provides a comprehensive map of the oncobiome of BC subtypes, with insights into disease prognosis that can be critical for precision therapeutic intervention strategies. |
format | Online Article Text |
id | pubmed-8418604 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-84186042021-09-08 Prognostic correlations with the microbiome of breast cancer subtypes Banerjee, Sagarika Wei, Zhi Tian, Tian Bose, Dipayan Shih, Natalie N. C. Feldman, Michael D. Khoury, Thaer De Michele, Angela Robertson, Erle S. Cell Death Dis Article Alterations to the natural microbiome are linked to different diseases, and the presence or absence of specific microbes is directly related to disease outcomes. We performed a comprehensive analysis with unique cohorts of the four subtypes of breast cancer (BC) characterized by their microbial signatures, using a pan-pathogen microarray strategy. The signature (includes viruses, bacteria, fungi, and parasites) of each tumor subtype was correlated with clinical data to identify microbes with prognostic potential. The subtypes of BC had specific viromes and microbiomes, with ER+ and TN tumors showing the most and least diverse microbiome, respectively. The specific microbial signatures allowed discrimination between different BC subtypes. Furthermore, we demonstrated correlations between the presence and absence of specific microbes in BC subtypes with the clinical outcomes. This study provides a comprehensive map of the oncobiome of BC subtypes, with insights into disease prognosis that can be critical for precision therapeutic intervention strategies. Nature Publishing Group UK 2021-09-04 /pmc/articles/PMC8418604/ /pubmed/34482363 http://dx.doi.org/10.1038/s41419-021-04092-x Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Banerjee, Sagarika Wei, Zhi Tian, Tian Bose, Dipayan Shih, Natalie N. C. Feldman, Michael D. Khoury, Thaer De Michele, Angela Robertson, Erle S. Prognostic correlations with the microbiome of breast cancer subtypes |
title | Prognostic correlations with the microbiome of breast cancer subtypes |
title_full | Prognostic correlations with the microbiome of breast cancer subtypes |
title_fullStr | Prognostic correlations with the microbiome of breast cancer subtypes |
title_full_unstemmed | Prognostic correlations with the microbiome of breast cancer subtypes |
title_short | Prognostic correlations with the microbiome of breast cancer subtypes |
title_sort | prognostic correlations with the microbiome of breast cancer subtypes |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8418604/ https://www.ncbi.nlm.nih.gov/pubmed/34482363 http://dx.doi.org/10.1038/s41419-021-04092-x |
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