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Comparative Proteome Analysis Revealing an 11-Protein Signature for Aggressive Triple-Negative Breast Cancer

BACKGROUND: Clinical outcome of patients with triple-negative breast cancer (TNBC) is highly variable. This study aims to identify and validate a prognostic protein signature for TNBC patients to reduce unnecessary adjuvant systemic therapy. METHODS: Frozen primary tumors were collected from 126 lym...

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Autores principales: Liu, Ning Qing, Stingl, Christoph, Look, Maxime P., Smid, Marcel, Braakman, René B.H., De Marchi, Tommaso, Sieuwerts, Anieta M., Span, Paul N., Sweep, Fred C.G.J., Linderholm, Barbro K., Mangia, Anita, Paradiso, Angelo, Dirix, Luc Y., Van Laere, Steven J., Luider, Theo M., Martens, John W.M., Foekens, John A., Umar, Arzu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3952199/
https://www.ncbi.nlm.nih.gov/pubmed/24399849
http://dx.doi.org/10.1093/jnci/djt376
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author Liu, Ning Qing
Stingl, Christoph
Look, Maxime P.
Smid, Marcel
Braakman, René B.H.
De Marchi, Tommaso
Sieuwerts, Anieta M.
Span, Paul N.
Sweep, Fred C.G.J.
Linderholm, Barbro K.
Mangia, Anita
Paradiso, Angelo
Dirix, Luc Y.
Van Laere, Steven J.
Luider, Theo M.
Martens, John W.M.
Foekens, John A.
Umar, Arzu
author_facet Liu, Ning Qing
Stingl, Christoph
Look, Maxime P.
Smid, Marcel
Braakman, René B.H.
De Marchi, Tommaso
Sieuwerts, Anieta M.
Span, Paul N.
Sweep, Fred C.G.J.
Linderholm, Barbro K.
Mangia, Anita
Paradiso, Angelo
Dirix, Luc Y.
Van Laere, Steven J.
Luider, Theo M.
Martens, John W.M.
Foekens, John A.
Umar, Arzu
author_sort Liu, Ning Qing
collection PubMed
description BACKGROUND: Clinical outcome of patients with triple-negative breast cancer (TNBC) is highly variable. This study aims to identify and validate a prognostic protein signature for TNBC patients to reduce unnecessary adjuvant systemic therapy. METHODS: Frozen primary tumors were collected from 126 lymph node–negative and adjuvant therapy–naive TNBC patients. These samples were used for global proteome profiling in two series: an in-house training (n = 63) and a multicenter test (n = 63) set. Patients who remained free of distant metastasis for a minimum of 5 years after surgery were defined as having good prognosis. Cox regression analysis was performed to develop a prognostic signature, which was independently validated. All statistical tests were two-sided. RESULTS: An 11-protein signature was developed in the training set (median follow-up for good-prognosis patients = 117 months) and subsequently validated in the test set (median follow-up for good-prognosis patients = 108 months) showing 89.5% sensitivity (95% confidence interval [CI] = 69.2% to 98.1%), 70.5% specificity (95% CI = 61.7% to 74.2%), 56.7% positive predictive value (95% CI = 43.8% to 62.1%), and 93.9% negative predictive value (95% CI = 82.3% to 98.9%) for poor-prognosis patients. The predicted poor-prognosis patients had higher risk to develop distant metastasis than the predicted good-prognosis patients in univariate (hazard ratio [HR] = 13.15; 95% CI = 3.03 to 57.07; P = .001) and multivariable (HR = 12.45; 95% CI = 2.67 to 58.11; P = .001) analysis. Furthermore, the predicted poor-prognosis group had statistically significantly more breast cancer–specific mortality. Using our signature as guidance, more than 60% of patients would have been exempted from unnecessary adjuvant chemotherapy compared with conventional prognostic guidelines. CONCLUSIONS: We report the first validated proteomic signature to assess the natural course of clinical TNBC.
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spelling pubmed-39521992014-03-14 Comparative Proteome Analysis Revealing an 11-Protein Signature for Aggressive Triple-Negative Breast Cancer Liu, Ning Qing Stingl, Christoph Look, Maxime P. Smid, Marcel Braakman, René B.H. De Marchi, Tommaso Sieuwerts, Anieta M. Span, Paul N. Sweep, Fred C.G.J. Linderholm, Barbro K. Mangia, Anita Paradiso, Angelo Dirix, Luc Y. Van Laere, Steven J. Luider, Theo M. Martens, John W.M. Foekens, John A. Umar, Arzu J Natl Cancer Inst Article BACKGROUND: Clinical outcome of patients with triple-negative breast cancer (TNBC) is highly variable. This study aims to identify and validate a prognostic protein signature for TNBC patients to reduce unnecessary adjuvant systemic therapy. METHODS: Frozen primary tumors were collected from 126 lymph node–negative and adjuvant therapy–naive TNBC patients. These samples were used for global proteome profiling in two series: an in-house training (n = 63) and a multicenter test (n = 63) set. Patients who remained free of distant metastasis for a minimum of 5 years after surgery were defined as having good prognosis. Cox regression analysis was performed to develop a prognostic signature, which was independently validated. All statistical tests were two-sided. RESULTS: An 11-protein signature was developed in the training set (median follow-up for good-prognosis patients = 117 months) and subsequently validated in the test set (median follow-up for good-prognosis patients = 108 months) showing 89.5% sensitivity (95% confidence interval [CI] = 69.2% to 98.1%), 70.5% specificity (95% CI = 61.7% to 74.2%), 56.7% positive predictive value (95% CI = 43.8% to 62.1%), and 93.9% negative predictive value (95% CI = 82.3% to 98.9%) for poor-prognosis patients. The predicted poor-prognosis patients had higher risk to develop distant metastasis than the predicted good-prognosis patients in univariate (hazard ratio [HR] = 13.15; 95% CI = 3.03 to 57.07; P = .001) and multivariable (HR = 12.45; 95% CI = 2.67 to 58.11; P = .001) analysis. Furthermore, the predicted poor-prognosis group had statistically significantly more breast cancer–specific mortality. Using our signature as guidance, more than 60% of patients would have been exempted from unnecessary adjuvant chemotherapy compared with conventional prognostic guidelines. CONCLUSIONS: We report the first validated proteomic signature to assess the natural course of clinical TNBC. Oxford University Press 2014-01-07 /pmc/articles/PMC3952199/ /pubmed/24399849 http://dx.doi.org/10.1093/jnci/djt376 Text en © The Author 2014. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/), 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 Article
Liu, Ning Qing
Stingl, Christoph
Look, Maxime P.
Smid, Marcel
Braakman, René B.H.
De Marchi, Tommaso
Sieuwerts, Anieta M.
Span, Paul N.
Sweep, Fred C.G.J.
Linderholm, Barbro K.
Mangia, Anita
Paradiso, Angelo
Dirix, Luc Y.
Van Laere, Steven J.
Luider, Theo M.
Martens, John W.M.
Foekens, John A.
Umar, Arzu
Comparative Proteome Analysis Revealing an 11-Protein Signature for Aggressive Triple-Negative Breast Cancer
title Comparative Proteome Analysis Revealing an 11-Protein Signature for Aggressive Triple-Negative Breast Cancer
title_full Comparative Proteome Analysis Revealing an 11-Protein Signature for Aggressive Triple-Negative Breast Cancer
title_fullStr Comparative Proteome Analysis Revealing an 11-Protein Signature for Aggressive Triple-Negative Breast Cancer
title_full_unstemmed Comparative Proteome Analysis Revealing an 11-Protein Signature for Aggressive Triple-Negative Breast Cancer
title_short Comparative Proteome Analysis Revealing an 11-Protein Signature for Aggressive Triple-Negative Breast Cancer
title_sort comparative proteome analysis revealing an 11-protein signature for aggressive triple-negative breast cancer
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3952199/
https://www.ncbi.nlm.nih.gov/pubmed/24399849
http://dx.doi.org/10.1093/jnci/djt376
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