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Characterization of Exosome-Related Gene Risk Model to Evaluate the Tumor Immune Microenvironment and Predict Prognosis in Triple-Negative Breast Cancer

BACKGROUND: As a kind of small membrane vesicles, exosomes are secreted by most cell types from multivesicular endosomes, including tumor cells. The relationship between exosomes and immune response plays a vital role in the occurrence and development of tumors. Nevertheless, the interaction between...

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Autores principales: Qiu, Pengjun, Guo, Qiaonan, Yao, Qingzhi, Chen, Jianpeng, Lin, Jianqing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8517454/
https://www.ncbi.nlm.nih.gov/pubmed/34659224
http://dx.doi.org/10.3389/fimmu.2021.736030
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author Qiu, Pengjun
Guo, Qiaonan
Yao, Qingzhi
Chen, Jianpeng
Lin, Jianqing
author_facet Qiu, Pengjun
Guo, Qiaonan
Yao, Qingzhi
Chen, Jianpeng
Lin, Jianqing
author_sort Qiu, Pengjun
collection PubMed
description BACKGROUND: As a kind of small membrane vesicles, exosomes are secreted by most cell types from multivesicular endosomes, including tumor cells. The relationship between exosomes and immune response plays a vital role in the occurrence and development of tumors. Nevertheless, the interaction between exosomes and the microenvironment of tumors remains unclear. Therefore, we set out to study the influence of exosomes on the triple-negative breast cancer (TNBC) microenvironment. METHOD: One hundred twenty-one exosome-related genes were downloaded from ExoBCD database, and IVL, CXCL13, and AP2S1 were final selected because of the association with TNBC prognosis. Based on the sum of the expression levels of these three genes, provided by The Cancer Genome Atlas (TCGA), and the regression coefficients, an exosome risk score model was established. With the median risk score value, the patients in the two databases were divided into high- and low-risk groups. R clusterProfiler package was employed to compare the different enrichment ways between the two groups. The ESTIMATE and CIBERSORT methods were employed to analyze ESTIMATE Score and immune cell infiltration. Finally, the correlation between the immune checkpoint-related gene expression levels and exosome-related risk was analyzed. The relationship between selected gene expression and drug sensitivity was also detected. RESULTS: Different risk groups exhibited distinct result of TNBC prognosis, with a higher survival rate in the low-risk group than in the high-risk group. The two groups were enriched by immune response and biological process pathways. A better overall survival (OS) was demonstrated in patients with high scores of immune and ESTIMATE rather than ones with low scores. Subsequently, we found that CD4(+)-activated memory T cells and M1 macrophages were both upregulated in the low-risk group, whereas M2 macrophages and activated mast cell were downregulated in the low-risk group in patients from the TCGA and GEO databases, respectively. Eventually, four genes previously proposed to be targets of immune checkpoint inhibitors were evaluated, resulting in the expression levels of CD274, CTLA4, LAG3, and TIM3 being higher in the low-risk group than high-risk group. CONCLUSION: The results of our study suggest that exosome-related risk model was related to the prognosis and ratio of immune cell infiltration in patients with TNBC. This discovery may make contributions to improve immunotherapy for TNBC.
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spelling pubmed-85174542021-10-16 Characterization of Exosome-Related Gene Risk Model to Evaluate the Tumor Immune Microenvironment and Predict Prognosis in Triple-Negative Breast Cancer Qiu, Pengjun Guo, Qiaonan Yao, Qingzhi Chen, Jianpeng Lin, Jianqing Front Immunol Immunology BACKGROUND: As a kind of small membrane vesicles, exosomes are secreted by most cell types from multivesicular endosomes, including tumor cells. The relationship between exosomes and immune response plays a vital role in the occurrence and development of tumors. Nevertheless, the interaction between exosomes and the microenvironment of tumors remains unclear. Therefore, we set out to study the influence of exosomes on the triple-negative breast cancer (TNBC) microenvironment. METHOD: One hundred twenty-one exosome-related genes were downloaded from ExoBCD database, and IVL, CXCL13, and AP2S1 were final selected because of the association with TNBC prognosis. Based on the sum of the expression levels of these three genes, provided by The Cancer Genome Atlas (TCGA), and the regression coefficients, an exosome risk score model was established. With the median risk score value, the patients in the two databases were divided into high- and low-risk groups. R clusterProfiler package was employed to compare the different enrichment ways between the two groups. The ESTIMATE and CIBERSORT methods were employed to analyze ESTIMATE Score and immune cell infiltration. Finally, the correlation between the immune checkpoint-related gene expression levels and exosome-related risk was analyzed. The relationship between selected gene expression and drug sensitivity was also detected. RESULTS: Different risk groups exhibited distinct result of TNBC prognosis, with a higher survival rate in the low-risk group than in the high-risk group. The two groups were enriched by immune response and biological process pathways. A better overall survival (OS) was demonstrated in patients with high scores of immune and ESTIMATE rather than ones with low scores. Subsequently, we found that CD4(+)-activated memory T cells and M1 macrophages were both upregulated in the low-risk group, whereas M2 macrophages and activated mast cell were downregulated in the low-risk group in patients from the TCGA and GEO databases, respectively. Eventually, four genes previously proposed to be targets of immune checkpoint inhibitors were evaluated, resulting in the expression levels of CD274, CTLA4, LAG3, and TIM3 being higher in the low-risk group than high-risk group. CONCLUSION: The results of our study suggest that exosome-related risk model was related to the prognosis and ratio of immune cell infiltration in patients with TNBC. This discovery may make contributions to improve immunotherapy for TNBC. Frontiers Media S.A. 2021-10-01 /pmc/articles/PMC8517454/ /pubmed/34659224 http://dx.doi.org/10.3389/fimmu.2021.736030 Text en Copyright © 2021 Qiu, Guo, Yao, Chen and Lin 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
Qiu, Pengjun
Guo, Qiaonan
Yao, Qingzhi
Chen, Jianpeng
Lin, Jianqing
Characterization of Exosome-Related Gene Risk Model to Evaluate the Tumor Immune Microenvironment and Predict Prognosis in Triple-Negative Breast Cancer
title Characterization of Exosome-Related Gene Risk Model to Evaluate the Tumor Immune Microenvironment and Predict Prognosis in Triple-Negative Breast Cancer
title_full Characterization of Exosome-Related Gene Risk Model to Evaluate the Tumor Immune Microenvironment and Predict Prognosis in Triple-Negative Breast Cancer
title_fullStr Characterization of Exosome-Related Gene Risk Model to Evaluate the Tumor Immune Microenvironment and Predict Prognosis in Triple-Negative Breast Cancer
title_full_unstemmed Characterization of Exosome-Related Gene Risk Model to Evaluate the Tumor Immune Microenvironment and Predict Prognosis in Triple-Negative Breast Cancer
title_short Characterization of Exosome-Related Gene Risk Model to Evaluate the Tumor Immune Microenvironment and Predict Prognosis in Triple-Negative Breast Cancer
title_sort characterization of exosome-related gene risk model to evaluate the tumor immune microenvironment and predict prognosis in triple-negative breast cancer
topic Immunology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8517454/
https://www.ncbi.nlm.nih.gov/pubmed/34659224
http://dx.doi.org/10.3389/fimmu.2021.736030
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