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A Tyrosine Kinase Expression Signature Predicts the Post-Operative Clinical Outcome in Triple Negative Breast Cancers

Triple negative breast cancer (TNBC) represent 15% of breast cancers. Histoclinical features and marketed prognostic gene expression signatures (GES) failed to identify good- and poor-prognosis patients. Tyrosine kinases (TK) represent potential prognostic and/or therapeutic targets for TNBC. We sou...

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Autores principales: de Nonneville, Alexandre, Finetti, Pascal, Adelaide, José, Lambaudie, Éric, Viens, Patrice, Gonçalves, Anthony, Birnbaum, Daniel, Mamessier, Emilie, Bertucci, François
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6721506/
https://www.ncbi.nlm.nih.gov/pubmed/31412533
http://dx.doi.org/10.3390/cancers11081158
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author de Nonneville, Alexandre
Finetti, Pascal
Adelaide, José
Lambaudie, Éric
Viens, Patrice
Gonçalves, Anthony
Birnbaum, Daniel
Mamessier, Emilie
Bertucci, François
author_facet de Nonneville, Alexandre
Finetti, Pascal
Adelaide, José
Lambaudie, Éric
Viens, Patrice
Gonçalves, Anthony
Birnbaum, Daniel
Mamessier, Emilie
Bertucci, François
author_sort de Nonneville, Alexandre
collection PubMed
description Triple negative breast cancer (TNBC) represent 15% of breast cancers. Histoclinical features and marketed prognostic gene expression signatures (GES) failed to identify good- and poor-prognosis patients. Tyrosine kinases (TK) represent potential prognostic and/or therapeutic targets for TNBC. We sought to define a prognostic TK GES in a large series of TNBC. mRNA expression and histoclinical data of 6379 early BCs were collected from 16 datasets. We searched for a TK-based GES associated with disease-free survival (DFS) and tested its robustness in an independent validation set. A total of 1226 samples were TNBC. In the learning set of samples (N = 825), we identified a 13-TK GES associated with DFS. This GES was associated with cell proliferation and immune response. In multivariate analysis, it outperformed the previously published GESs and classical prognostic factors in the validation set (N = 401), in which the patients classified as “low-risk” had a 73% 5-year DFS versus 53% for “high-risk” patients (p = 1.85 × 10(−3)). The generation of 100,000 random 13-gene signatures by a resampling scheme showed the non-random nature of our classifier, which was also prognostic for overall survival in multivariate analysis. We identified a robust and non-random 13-TK GES that separated TNBC into subgroups of different prognosis. Clinical and functional validations are warranted.
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spelling pubmed-67215062019-09-10 A Tyrosine Kinase Expression Signature Predicts the Post-Operative Clinical Outcome in Triple Negative Breast Cancers de Nonneville, Alexandre Finetti, Pascal Adelaide, José Lambaudie, Éric Viens, Patrice Gonçalves, Anthony Birnbaum, Daniel Mamessier, Emilie Bertucci, François Cancers (Basel) Article Triple negative breast cancer (TNBC) represent 15% of breast cancers. Histoclinical features and marketed prognostic gene expression signatures (GES) failed to identify good- and poor-prognosis patients. Tyrosine kinases (TK) represent potential prognostic and/or therapeutic targets for TNBC. We sought to define a prognostic TK GES in a large series of TNBC. mRNA expression and histoclinical data of 6379 early BCs were collected from 16 datasets. We searched for a TK-based GES associated with disease-free survival (DFS) and tested its robustness in an independent validation set. A total of 1226 samples were TNBC. In the learning set of samples (N = 825), we identified a 13-TK GES associated with DFS. This GES was associated with cell proliferation and immune response. In multivariate analysis, it outperformed the previously published GESs and classical prognostic factors in the validation set (N = 401), in which the patients classified as “low-risk” had a 73% 5-year DFS versus 53% for “high-risk” patients (p = 1.85 × 10(−3)). The generation of 100,000 random 13-gene signatures by a resampling scheme showed the non-random nature of our classifier, which was also prognostic for overall survival in multivariate analysis. We identified a robust and non-random 13-TK GES that separated TNBC into subgroups of different prognosis. Clinical and functional validations are warranted. MDPI 2019-08-13 /pmc/articles/PMC6721506/ /pubmed/31412533 http://dx.doi.org/10.3390/cancers11081158 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
de Nonneville, Alexandre
Finetti, Pascal
Adelaide, José
Lambaudie, Éric
Viens, Patrice
Gonçalves, Anthony
Birnbaum, Daniel
Mamessier, Emilie
Bertucci, François
A Tyrosine Kinase Expression Signature Predicts the Post-Operative Clinical Outcome in Triple Negative Breast Cancers
title A Tyrosine Kinase Expression Signature Predicts the Post-Operative Clinical Outcome in Triple Negative Breast Cancers
title_full A Tyrosine Kinase Expression Signature Predicts the Post-Operative Clinical Outcome in Triple Negative Breast Cancers
title_fullStr A Tyrosine Kinase Expression Signature Predicts the Post-Operative Clinical Outcome in Triple Negative Breast Cancers
title_full_unstemmed A Tyrosine Kinase Expression Signature Predicts the Post-Operative Clinical Outcome in Triple Negative Breast Cancers
title_short A Tyrosine Kinase Expression Signature Predicts the Post-Operative Clinical Outcome in Triple Negative Breast Cancers
title_sort tyrosine kinase expression signature predicts the post-operative clinical outcome in triple negative breast cancers
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6721506/
https://www.ncbi.nlm.nih.gov/pubmed/31412533
http://dx.doi.org/10.3390/cancers11081158
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