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Recognition of Immune Microenvironment Landscape and Immune-Related Prognostic Genes in Breast Cancer
BACKGROUND: Breast cancer (BC) is the most common malignant tumor in women. The immunophenotype of tumor microenvironment (TME) has shown great therapeutic potential in tumor. METHOD: The transcriptome was obtained from TCGA and GEO data. Immune infiltration was analyzed by single-sample gene set en...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7683123/ https://www.ncbi.nlm.nih.gov/pubmed/33274208 http://dx.doi.org/10.1155/2020/3909416 |
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author | Wang, Huiling You, Shuo Fang, Meng Fang, Qian |
author_facet | Wang, Huiling You, Shuo Fang, Meng Fang, Qian |
author_sort | Wang, Huiling |
collection | PubMed |
description | BACKGROUND: Breast cancer (BC) is the most common malignant tumor in women. The immunophenotype of tumor microenvironment (TME) has shown great therapeutic potential in tumor. METHOD: The transcriptome was obtained from TCGA and GEO data. Immune infiltration was analyzed by single-sample gene set enrichment (ssGSEA). The immune feature was constructed by Cox regression analysis. In addition, the coexpression of differential expression genes (DEGs) was identified. Through enrichment analysis, the function and pathway of module genes were identified. The somatic mutations related to immune characteristics were analyzed by Maftools. By using the consistency clustering algorithm, the molecular subtypes were constructed, and the overall survival time (OS) was predicted. RESULTS: Immune landscape can be divided into low immune infiltration and high immune infiltration. Cox regression analysis identified seven immune cells as protective factors of BC. In the coexpression modules for DEGs of high and low immune infiltration, module 1 was related to T cells and high immune infiltration. In particular, the area under the curve (AUC) value of hub gene SASH3 was the highest, and the correlation with T cells was stronger in the high immune infiltration. Enrichment analysis found that oxidative stress, T cell aggregation, and apoptosis were observed in high immune infiltration. In addition, TP53 was identified as the most important somatic gene mutation related to immune characteristics. Importantly, we also constructed seven immune cell-based breast cancer subtypes to predict OS. CONCLUSION: We evaluated the immune landscape of BC and constructed the gene characteristics related to the immune landscape. The potential of T cells and SASH3 in immunotherapy of BC was revealed, which may guide the development of new clinical treatment strategies. |
format | Online Article Text |
id | pubmed-7683123 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-76831232020-12-02 Recognition of Immune Microenvironment Landscape and Immune-Related Prognostic Genes in Breast Cancer Wang, Huiling You, Shuo Fang, Meng Fang, Qian Biomed Res Int Research Article BACKGROUND: Breast cancer (BC) is the most common malignant tumor in women. The immunophenotype of tumor microenvironment (TME) has shown great therapeutic potential in tumor. METHOD: The transcriptome was obtained from TCGA and GEO data. Immune infiltration was analyzed by single-sample gene set enrichment (ssGSEA). The immune feature was constructed by Cox regression analysis. In addition, the coexpression of differential expression genes (DEGs) was identified. Through enrichment analysis, the function and pathway of module genes were identified. The somatic mutations related to immune characteristics were analyzed by Maftools. By using the consistency clustering algorithm, the molecular subtypes were constructed, and the overall survival time (OS) was predicted. RESULTS: Immune landscape can be divided into low immune infiltration and high immune infiltration. Cox regression analysis identified seven immune cells as protective factors of BC. In the coexpression modules for DEGs of high and low immune infiltration, module 1 was related to T cells and high immune infiltration. In particular, the area under the curve (AUC) value of hub gene SASH3 was the highest, and the correlation with T cells was stronger in the high immune infiltration. Enrichment analysis found that oxidative stress, T cell aggregation, and apoptosis were observed in high immune infiltration. In addition, TP53 was identified as the most important somatic gene mutation related to immune characteristics. Importantly, we also constructed seven immune cell-based breast cancer subtypes to predict OS. CONCLUSION: We evaluated the immune landscape of BC and constructed the gene characteristics related to the immune landscape. The potential of T cells and SASH3 in immunotherapy of BC was revealed, which may guide the development of new clinical treatment strategies. Hindawi 2020-11-15 /pmc/articles/PMC7683123/ /pubmed/33274208 http://dx.doi.org/10.1155/2020/3909416 Text en Copyright © 2020 Huiling Wang et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Wang, Huiling You, Shuo Fang, Meng Fang, Qian Recognition of Immune Microenvironment Landscape and Immune-Related Prognostic Genes in Breast Cancer |
title | Recognition of Immune Microenvironment Landscape and Immune-Related Prognostic Genes in Breast Cancer |
title_full | Recognition of Immune Microenvironment Landscape and Immune-Related Prognostic Genes in Breast Cancer |
title_fullStr | Recognition of Immune Microenvironment Landscape and Immune-Related Prognostic Genes in Breast Cancer |
title_full_unstemmed | Recognition of Immune Microenvironment Landscape and Immune-Related Prognostic Genes in Breast Cancer |
title_short | Recognition of Immune Microenvironment Landscape and Immune-Related Prognostic Genes in Breast Cancer |
title_sort | recognition of immune microenvironment landscape and immune-related prognostic genes in breast cancer |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7683123/ https://www.ncbi.nlm.nih.gov/pubmed/33274208 http://dx.doi.org/10.1155/2020/3909416 |
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