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Unravelling triple-negative breast cancer molecular heterogeneity using an integrative multiomic analysis

BACKGROUND: Recent efforts of genome-wide gene expression profiling analyses have improved our understanding of the biological complexity and diversity of triple-negative breast cancers (TNBCs) reporting, at least six different molecular subtypes of TNBC namely Basal-like 1 (BL1), basal-like 2 (BL2)...

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Autores principales: Bareche, Y, Venet, D, Ignatiadis, M, Aftimos, P, Piccart, M, Rothe, F, Sotiriou, C
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5913636/
https://www.ncbi.nlm.nih.gov/pubmed/29365031
http://dx.doi.org/10.1093/annonc/mdy024
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author Bareche, Y
Venet, D
Ignatiadis, M
Aftimos, P
Piccart, M
Rothe, F
Sotiriou, C
author_facet Bareche, Y
Venet, D
Ignatiadis, M
Aftimos, P
Piccart, M
Rothe, F
Sotiriou, C
author_sort Bareche, Y
collection PubMed
description BACKGROUND: Recent efforts of genome-wide gene expression profiling analyses have improved our understanding of the biological complexity and diversity of triple-negative breast cancers (TNBCs) reporting, at least six different molecular subtypes of TNBC namely Basal-like 1 (BL1), basal-like 2 (BL2), immunomodulatory (IM), mesenchymal (M), mesenchymal stem-like (MSL) and luminal androgen receptor (LAR). However, little is known regarding the potential driving molecular events within each subtype, their difference in survival and response to therapy. Further insight into the underlying genomic alterations is therefore needed. PATIENTS AND METHODS: This study was carried out using copy-number aberrations, somatic mutations and gene expression data derived from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) and The Cancer Genome Atlas. TNBC samples (n = 550) were classified according to Lehmann’s molecular subtypes using the TNBCtype online subtyping tool (http://cbc.mc.vanderbilt.edu/tnbc/). RESULTS: Each subtype showed significant clinic-pathological characteristic differences. Using a multivariate model, IM subtype showed to be associated with a better prognosis (HR = 0.68; CI = 0.46–0.99; P = 0.043) whereas LAR subtype was associated with a worst prognosis (HR = 1.47; CI = 1.0–2.14; P = 0.046). BL1 subtype was found to be most genomically instable subtype with high TP53 mutation (92%) and copy-number deletion in genes involved in DNA repair mechanism (BRCA2, MDM2, PTEN, RB1 and TP53). LAR tumours were associated with higher mutational burden with significantly enriched mutations in PI3KCA (55%), AKT1 (13%) and CDH1 (13%) genes. M and MSL subtypes were associated with higher signature score for angiogenesis. Finally, IM showed high expression levels of immune signatures and check-point inhibitor genes such as PD1, PDL1 and CTLA4. CONCLUSION: Our findings highlight for the first time the substantial genomic heterogeneity that characterize TNBC molecular subtypes, allowing for a better understanding of the disease biology as well as the identification of several candidate targets paving novel approaches for the development of anticancer therapeutics for TNBC.
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spelling pubmed-59136362018-04-30 Unravelling triple-negative breast cancer molecular heterogeneity using an integrative multiomic analysis Bareche, Y Venet, D Ignatiadis, M Aftimos, P Piccart, M Rothe, F Sotiriou, C Ann Oncol Original Articles BACKGROUND: Recent efforts of genome-wide gene expression profiling analyses have improved our understanding of the biological complexity and diversity of triple-negative breast cancers (TNBCs) reporting, at least six different molecular subtypes of TNBC namely Basal-like 1 (BL1), basal-like 2 (BL2), immunomodulatory (IM), mesenchymal (M), mesenchymal stem-like (MSL) and luminal androgen receptor (LAR). However, little is known regarding the potential driving molecular events within each subtype, their difference in survival and response to therapy. Further insight into the underlying genomic alterations is therefore needed. PATIENTS AND METHODS: This study was carried out using copy-number aberrations, somatic mutations and gene expression data derived from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) and The Cancer Genome Atlas. TNBC samples (n = 550) were classified according to Lehmann’s molecular subtypes using the TNBCtype online subtyping tool (http://cbc.mc.vanderbilt.edu/tnbc/). RESULTS: Each subtype showed significant clinic-pathological characteristic differences. Using a multivariate model, IM subtype showed to be associated with a better prognosis (HR = 0.68; CI = 0.46–0.99; P = 0.043) whereas LAR subtype was associated with a worst prognosis (HR = 1.47; CI = 1.0–2.14; P = 0.046). BL1 subtype was found to be most genomically instable subtype with high TP53 mutation (92%) and copy-number deletion in genes involved in DNA repair mechanism (BRCA2, MDM2, PTEN, RB1 and TP53). LAR tumours were associated with higher mutational burden with significantly enriched mutations in PI3KCA (55%), AKT1 (13%) and CDH1 (13%) genes. M and MSL subtypes were associated with higher signature score for angiogenesis. Finally, IM showed high expression levels of immune signatures and check-point inhibitor genes such as PD1, PDL1 and CTLA4. CONCLUSION: Our findings highlight for the first time the substantial genomic heterogeneity that characterize TNBC molecular subtypes, allowing for a better understanding of the disease biology as well as the identification of several candidate targets paving novel approaches for the development of anticancer therapeutics for TNBC. Oxford University Press 2018-04 2018-01-22 /pmc/articles/PMC5913636/ /pubmed/29365031 http://dx.doi.org/10.1093/annonc/mdy024 Text en © The Author(s) 2018. Published by Oxford University Press on behalf of the European Society for Medical Oncology. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Original Articles
Bareche, Y
Venet, D
Ignatiadis, M
Aftimos, P
Piccart, M
Rothe, F
Sotiriou, C
Unravelling triple-negative breast cancer molecular heterogeneity using an integrative multiomic analysis
title Unravelling triple-negative breast cancer molecular heterogeneity using an integrative multiomic analysis
title_full Unravelling triple-negative breast cancer molecular heterogeneity using an integrative multiomic analysis
title_fullStr Unravelling triple-negative breast cancer molecular heterogeneity using an integrative multiomic analysis
title_full_unstemmed Unravelling triple-negative breast cancer molecular heterogeneity using an integrative multiomic analysis
title_short Unravelling triple-negative breast cancer molecular heterogeneity using an integrative multiomic analysis
title_sort unravelling triple-negative breast cancer molecular heterogeneity using an integrative multiomic analysis
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5913636/
https://www.ncbi.nlm.nih.gov/pubmed/29365031
http://dx.doi.org/10.1093/annonc/mdy024
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