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The prognostic value of tumor mutation burden (TMB) and its relationship with immune infiltration in breast cancer patients
OBJECTIVE: Although the tumor mutation burden (TMB) was reported as a biomarker for immunotherapy of various cancers, whether it can effectively predict the survival prognosis in breast cancer patients remains unclear. In this study, the prognostic value of TMB and its correlation with immune infilt...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9940352/ https://www.ncbi.nlm.nih.gov/pubmed/36805828 http://dx.doi.org/10.1186/s40001-023-01058-x |
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author | Cui, Shengjin Feng, Jingying Tang, Xi Lou, Shuang Guo, Weiquan Xiao, Xiaowei Li, Shuping Chen, Xue Huan, Yu Zhou, Yiwen Xiao, Lijia |
author_facet | Cui, Shengjin Feng, Jingying Tang, Xi Lou, Shuang Guo, Weiquan Xiao, Xiaowei Li, Shuping Chen, Xue Huan, Yu Zhou, Yiwen Xiao, Lijia |
author_sort | Cui, Shengjin |
collection | PubMed |
description | OBJECTIVE: Although the tumor mutation burden (TMB) was reported as a biomarker for immunotherapy of various cancers, whether it can effectively predict the survival prognosis in breast cancer patients remains unclear. In this study, the prognostic value of TMB and its correlation with immune infiltration were explored by using multigroup studies. METHODS: The somatic mutation data of 986 breast cancer patients were obtained from TCGA database. Breast cancer patients were divided into a low-TMB group and a high-TMB group according to the quartile of TMB scores. The differentially expressed genes (DEGs) were identified by the “limma” R program. The CIBERSORT algorithm was utilized to estimate the immune cell fraction of each sample. The TIMER database was utilized to evaluate the association between CNVs of immune genes and tumor immune cell infiltration and the prognostic value of the immune cells in breast cancer. RESULTS: In breast cancer, TP53, PIK3CA, TTN, CDH1 and other genes were the most important mutated genes. Higher survival rate of patients was found in the low-TMB group. Among the top 10 DEGs, three of them belong to the KRT gene family. GSEA enrichment analysis showed that MAPK, Hedgehog, mTOR, TGF-bate and GnRH signaling pathways were enriched in the low-TMB group. The infiltration levels of the most of immune cells were higher in the low-TMB group (P < 0.01). Higher expression of CCL18 and TRGC1 was correlated with poor prognosis. Breast cancer patients with CCL18 copy number variations, especially arm-level gains, showed significantly decreased immune cell infiltration. In the low B cell infiltration group, the survival prognosis of breast cancer patients was poor. CONCLUSIONS: TMB is a potential prognosis marker in breast cancer. Immune-related gene CCL18 and TRGC1 are biomarkers of poor prognosis while immune (B cell) infiltration is a biomarker of good prognosis. |
format | Online Article Text |
id | pubmed-9940352 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-99403522023-02-21 The prognostic value of tumor mutation burden (TMB) and its relationship with immune infiltration in breast cancer patients Cui, Shengjin Feng, Jingying Tang, Xi Lou, Shuang Guo, Weiquan Xiao, Xiaowei Li, Shuping Chen, Xue Huan, Yu Zhou, Yiwen Xiao, Lijia Eur J Med Res Research OBJECTIVE: Although the tumor mutation burden (TMB) was reported as a biomarker for immunotherapy of various cancers, whether it can effectively predict the survival prognosis in breast cancer patients remains unclear. In this study, the prognostic value of TMB and its correlation with immune infiltration were explored by using multigroup studies. METHODS: The somatic mutation data of 986 breast cancer patients were obtained from TCGA database. Breast cancer patients were divided into a low-TMB group and a high-TMB group according to the quartile of TMB scores. The differentially expressed genes (DEGs) were identified by the “limma” R program. The CIBERSORT algorithm was utilized to estimate the immune cell fraction of each sample. The TIMER database was utilized to evaluate the association between CNVs of immune genes and tumor immune cell infiltration and the prognostic value of the immune cells in breast cancer. RESULTS: In breast cancer, TP53, PIK3CA, TTN, CDH1 and other genes were the most important mutated genes. Higher survival rate of patients was found in the low-TMB group. Among the top 10 DEGs, three of them belong to the KRT gene family. GSEA enrichment analysis showed that MAPK, Hedgehog, mTOR, TGF-bate and GnRH signaling pathways were enriched in the low-TMB group. The infiltration levels of the most of immune cells were higher in the low-TMB group (P < 0.01). Higher expression of CCL18 and TRGC1 was correlated with poor prognosis. Breast cancer patients with CCL18 copy number variations, especially arm-level gains, showed significantly decreased immune cell infiltration. In the low B cell infiltration group, the survival prognosis of breast cancer patients was poor. CONCLUSIONS: TMB is a potential prognosis marker in breast cancer. Immune-related gene CCL18 and TRGC1 are biomarkers of poor prognosis while immune (B cell) infiltration is a biomarker of good prognosis. BioMed Central 2023-02-20 /pmc/articles/PMC9940352/ /pubmed/36805828 http://dx.doi.org/10.1186/s40001-023-01058-x Text en © The Author(s) 2023 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 | Research Cui, Shengjin Feng, Jingying Tang, Xi Lou, Shuang Guo, Weiquan Xiao, Xiaowei Li, Shuping Chen, Xue Huan, Yu Zhou, Yiwen Xiao, Lijia The prognostic value of tumor mutation burden (TMB) and its relationship with immune infiltration in breast cancer patients |
title | The prognostic value of tumor mutation burden (TMB) and its relationship with immune infiltration in breast cancer patients |
title_full | The prognostic value of tumor mutation burden (TMB) and its relationship with immune infiltration in breast cancer patients |
title_fullStr | The prognostic value of tumor mutation burden (TMB) and its relationship with immune infiltration in breast cancer patients |
title_full_unstemmed | The prognostic value of tumor mutation burden (TMB) and its relationship with immune infiltration in breast cancer patients |
title_short | The prognostic value of tumor mutation burden (TMB) and its relationship with immune infiltration in breast cancer patients |
title_sort | prognostic value of tumor mutation burden (tmb) and its relationship with immune infiltration in breast cancer patients |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9940352/ https://www.ncbi.nlm.nih.gov/pubmed/36805828 http://dx.doi.org/10.1186/s40001-023-01058-x |
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