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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...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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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. |
format | Online Article Text |
id | pubmed-6721506 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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