CIBERSORT analysis of TCGA and METABRIC identifies subgroups with better outcomes in triple negative breast cancer

Abstract Studies have shown that the presence of tumor infiltrating lymphocytes (TILs) in Triple Negative Breast Cancer (TNBC) is associated with better prognosis. However, the molecular mechanisms underlying these immune cell differences are not well delineated. In this study, analysis of hematoxyl...

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Autores principales:	Kelly E. Craven, Yesim Gökmen-Polar, Sunil S. Badve
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/d7464211fb4844b0b58056045ba5e363
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spelling	oai:doaj.org-article:d7464211fb4844b0b58056045ba5e3632021-12-02T15:53:59ZCIBERSORT analysis of TCGA and METABRIC identifies subgroups with better outcomes in triple negative breast cancer10.1038/s41598-021-83913-72045-2322https://doaj.org/article/d7464211fb4844b0b58056045ba5e3632021-02-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-83913-7https://doaj.org/toc/2045-2322Abstract Studies have shown that the presence of tumor infiltrating lymphocytes (TILs) in Triple Negative Breast Cancer (TNBC) is associated with better prognosis. However, the molecular mechanisms underlying these immune cell differences are not well delineated. In this study, analysis of hematoxylin and eosin images from The Cancer Genome Atlas (TCGA) breast cancer cohort failed to show a prognostic benefit of TILs in TNBC, whereas CIBERSORT analysis, which quantifies the proportion of each immune cell type, demonstrated improved overall survival in TCGA TNBC samples with increased CD8 T cells or CD8 plus CD4 memory activated T cells and in Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) TNBC samples with increased gamma delta T cells. Twenty-five genes showed mutational frequency differences between the TCGA high and low T cell groups, and many play important roles in inflammation or immune evasion (ATG2B, HIST1H2BC, PKD1, PIKFYVE, TLR3, NOTCH3, GOLGB1, CREBBP). Identification of these mutations suggests novel mechanisms by which the cancer cells attract immune cells and by which they evade or dampen the immune system during the cancer immunoediting process. This study suggests that integration of mutations with CIBERSORT analysis could provide better prediction of outcomes and novel therapeutic targets in TNBC cases.Kelly E. CravenYesim Gökmen-PolarSunil S. BadveNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-19 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Kelly E. Craven Yesim Gökmen-Polar Sunil S. Badve CIBERSORT analysis of TCGA and METABRIC identifies subgroups with better outcomes in triple negative breast cancer
description	Abstract Studies have shown that the presence of tumor infiltrating lymphocytes (TILs) in Triple Negative Breast Cancer (TNBC) is associated with better prognosis. However, the molecular mechanisms underlying these immune cell differences are not well delineated. In this study, analysis of hematoxylin and eosin images from The Cancer Genome Atlas (TCGA) breast cancer cohort failed to show a prognostic benefit of TILs in TNBC, whereas CIBERSORT analysis, which quantifies the proportion of each immune cell type, demonstrated improved overall survival in TCGA TNBC samples with increased CD8 T cells or CD8 plus CD4 memory activated T cells and in Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) TNBC samples with increased gamma delta T cells. Twenty-five genes showed mutational frequency differences between the TCGA high and low T cell groups, and many play important roles in inflammation or immune evasion (ATG2B, HIST1H2BC, PKD1, PIKFYVE, TLR3, NOTCH3, GOLGB1, CREBBP). Identification of these mutations suggests novel mechanisms by which the cancer cells attract immune cells and by which they evade or dampen the immune system during the cancer immunoediting process. This study suggests that integration of mutations with CIBERSORT analysis could provide better prediction of outcomes and novel therapeutic targets in TNBC cases.
format	article
author	Kelly E. Craven Yesim Gökmen-Polar Sunil S. Badve
author_facet	Kelly E. Craven Yesim Gökmen-Polar Sunil S. Badve
author_sort	Kelly E. Craven
title	CIBERSORT analysis of TCGA and METABRIC identifies subgroups with better outcomes in triple negative breast cancer
title_short	CIBERSORT analysis of TCGA and METABRIC identifies subgroups with better outcomes in triple negative breast cancer
title_full	CIBERSORT analysis of TCGA and METABRIC identifies subgroups with better outcomes in triple negative breast cancer
title_fullStr	CIBERSORT analysis of TCGA and METABRIC identifies subgroups with better outcomes in triple negative breast cancer
title_full_unstemmed	CIBERSORT analysis of TCGA and METABRIC identifies subgroups with better outcomes in triple negative breast cancer
title_sort	cibersort analysis of tcga and metabric identifies subgroups with better outcomes in triple negative breast cancer
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/d7464211fb4844b0b58056045ba5e363
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CIBERSORT analysis of TCGA and METABRIC identifies subgroups with better outcomes in triple negative breast cancer

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