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Integrating bulk and single-cell RNA sequencing data reveals the relationship between intratumor microbiome signature and host metabolic heterogeneity in breast cancer

INTRODUCTION: Nowadays, it has been recognized that gut microbiome can indirectly modulate cancer susceptibility or progression. However, whether intratumor microbes are parasitic, symbiotic, or merely bystanders in breast cancer is not fully understood. Microbial metabolite plays a pivotal role in...

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Autores principales: Chen, Fangyue, Yang, Jun, Guo, Youxiang, Su, Dongwei, Sheng, Yuan, Wu, Yanmei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10049788/
https://www.ncbi.nlm.nih.gov/pubmed/36999009
http://dx.doi.org/10.3389/fimmu.2023.1140995
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author Chen, Fangyue
Yang, Jun
Guo, Youxiang
Su, Dongwei
Sheng, Yuan
Wu, Yanmei
author_facet Chen, Fangyue
Yang, Jun
Guo, Youxiang
Su, Dongwei
Sheng, Yuan
Wu, Yanmei
author_sort Chen, Fangyue
collection PubMed
description INTRODUCTION: Nowadays, it has been recognized that gut microbiome can indirectly modulate cancer susceptibility or progression. However, whether intratumor microbes are parasitic, symbiotic, or merely bystanders in breast cancer is not fully understood. Microbial metabolite plays a pivotal role in the interaction of host and microbe via regulating mitochondrial and other metabolic pathways. And the relationship between tumor-resident microbiota and cancer metabolism remains an open question. METHODS: 1085 breast cancer patients with normalized intratumor microbial abundance data and 32 single-cell RNA sequencing samples were retrieved from public datasets. We used the gene set variation analysis to evaluate the various metabolic activities of breast cancer samples. Furthermore, we applied Scissor method to identify microbe-associated cell subpopulations from single-cell data. Then, we conducted comprehensive bioinformatic analyses to explore the association between host and microbe in breast cancer. RESULTS: Here, we found that the metabolic status of breast cancer cells was highly plastic, and some microbial genera were significantly correlated with cancer metabolic activity. We identified two distinct clusters based on microbial abundance and tumor metabolism data. And dysregulation of the metabolic pathway was observed among different cell types. Metabolism-related microbial scores were calculated to predict overall survival in patients with breast cancer. Furthermore, the microbial abundance of the specific genus was associated with gene mutation due to possible microbe-mediated mutagenesis. The infiltrating immune cell compositions, including regulatory T cells and activated NK cells, were significantly associated with the metabolism-related intratumor microbes, as indicated in the Mantel test analysis. Moreover, the mammary metabolism-related microbes were related to T cell exclusion and response to immunotherapy. CONCLUSIONS: Overall, the exploratory study shed light on the potential role of the metabolism-related microbiome in breast cancer patients. And the novel treatment will be realized by further investigating the metabolic disturbance in host and intratumor microbial cells.
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spelling pubmed-100497882023-03-29 Integrating bulk and single-cell RNA sequencing data reveals the relationship between intratumor microbiome signature and host metabolic heterogeneity in breast cancer Chen, Fangyue Yang, Jun Guo, Youxiang Su, Dongwei Sheng, Yuan Wu, Yanmei Front Immunol Immunology INTRODUCTION: Nowadays, it has been recognized that gut microbiome can indirectly modulate cancer susceptibility or progression. However, whether intratumor microbes are parasitic, symbiotic, or merely bystanders in breast cancer is not fully understood. Microbial metabolite plays a pivotal role in the interaction of host and microbe via regulating mitochondrial and other metabolic pathways. And the relationship between tumor-resident microbiota and cancer metabolism remains an open question. METHODS: 1085 breast cancer patients with normalized intratumor microbial abundance data and 32 single-cell RNA sequencing samples were retrieved from public datasets. We used the gene set variation analysis to evaluate the various metabolic activities of breast cancer samples. Furthermore, we applied Scissor method to identify microbe-associated cell subpopulations from single-cell data. Then, we conducted comprehensive bioinformatic analyses to explore the association between host and microbe in breast cancer. RESULTS: Here, we found that the metabolic status of breast cancer cells was highly plastic, and some microbial genera were significantly correlated with cancer metabolic activity. We identified two distinct clusters based on microbial abundance and tumor metabolism data. And dysregulation of the metabolic pathway was observed among different cell types. Metabolism-related microbial scores were calculated to predict overall survival in patients with breast cancer. Furthermore, the microbial abundance of the specific genus was associated with gene mutation due to possible microbe-mediated mutagenesis. The infiltrating immune cell compositions, including regulatory T cells and activated NK cells, were significantly associated with the metabolism-related intratumor microbes, as indicated in the Mantel test analysis. Moreover, the mammary metabolism-related microbes were related to T cell exclusion and response to immunotherapy. CONCLUSIONS: Overall, the exploratory study shed light on the potential role of the metabolism-related microbiome in breast cancer patients. And the novel treatment will be realized by further investigating the metabolic disturbance in host and intratumor microbial cells. Frontiers Media S.A. 2023-03-14 /pmc/articles/PMC10049788/ /pubmed/36999009 http://dx.doi.org/10.3389/fimmu.2023.1140995 Text en Copyright © 2023 Chen, Yang, Guo, Su, Sheng and Wu https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Immunology
Chen, Fangyue
Yang, Jun
Guo, Youxiang
Su, Dongwei
Sheng, Yuan
Wu, Yanmei
Integrating bulk and single-cell RNA sequencing data reveals the relationship between intratumor microbiome signature and host metabolic heterogeneity in breast cancer
title Integrating bulk and single-cell RNA sequencing data reveals the relationship between intratumor microbiome signature and host metabolic heterogeneity in breast cancer
title_full Integrating bulk and single-cell RNA sequencing data reveals the relationship between intratumor microbiome signature and host metabolic heterogeneity in breast cancer
title_fullStr Integrating bulk and single-cell RNA sequencing data reveals the relationship between intratumor microbiome signature and host metabolic heterogeneity in breast cancer
title_full_unstemmed Integrating bulk and single-cell RNA sequencing data reveals the relationship between intratumor microbiome signature and host metabolic heterogeneity in breast cancer
title_short Integrating bulk and single-cell RNA sequencing data reveals the relationship between intratumor microbiome signature and host metabolic heterogeneity in breast cancer
title_sort integrating bulk and single-cell rna sequencing data reveals the relationship between intratumor microbiome signature and host metabolic heterogeneity in breast cancer
topic Immunology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10049788/
https://www.ncbi.nlm.nih.gov/pubmed/36999009
http://dx.doi.org/10.3389/fimmu.2023.1140995
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