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Functional proteomics outlines the complexity of breast cancer molecular subtypes

Breast cancer is a heterogeneous disease comprising a variety of entities with various genetic backgrounds. Estrogen receptor-positive, human epidermal growth factor receptor 2-negative tumors typically have a favorable outcome; however, some patients eventually relapse, which suggests some heteroge...

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Autores principales: Gámez-Pozo, Angelo, Trilla-Fuertes, Lucía, Berges-Soria, Julia, Selevsek, Nathalie, López-Vacas, Rocío, Díaz-Almirón, Mariana, Nanni, Paolo, Arevalillo, Jorge M., Navarro, Hilario, Grossmann, Jonas, Gayá Moreno, Francisco, Gómez Rioja, Rubén, Prado-Vázquez, Guillermo, Zapater-Moros, Andrea, Main, Paloma, Feliú, Jaime, Martínez del Prado, Purificación, Zamora, Pilar, Ciruelos, Eva, Espinosa, Enrique, Fresno Vara, Juan Ángel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5577137/
https://www.ncbi.nlm.nih.gov/pubmed/28855612
http://dx.doi.org/10.1038/s41598-017-10493-w
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author Gámez-Pozo, Angelo
Trilla-Fuertes, Lucía
Berges-Soria, Julia
Selevsek, Nathalie
López-Vacas, Rocío
Díaz-Almirón, Mariana
Nanni, Paolo
Arevalillo, Jorge M.
Navarro, Hilario
Grossmann, Jonas
Gayá Moreno, Francisco
Gómez Rioja, Rubén
Prado-Vázquez, Guillermo
Zapater-Moros, Andrea
Main, Paloma
Feliú, Jaime
Martínez del Prado, Purificación
Zamora, Pilar
Ciruelos, Eva
Espinosa, Enrique
Fresno Vara, Juan Ángel
author_facet Gámez-Pozo, Angelo
Trilla-Fuertes, Lucía
Berges-Soria, Julia
Selevsek, Nathalie
López-Vacas, Rocío
Díaz-Almirón, Mariana
Nanni, Paolo
Arevalillo, Jorge M.
Navarro, Hilario
Grossmann, Jonas
Gayá Moreno, Francisco
Gómez Rioja, Rubén
Prado-Vázquez, Guillermo
Zapater-Moros, Andrea
Main, Paloma
Feliú, Jaime
Martínez del Prado, Purificación
Zamora, Pilar
Ciruelos, Eva
Espinosa, Enrique
Fresno Vara, Juan Ángel
author_sort Gámez-Pozo, Angelo
collection PubMed
description Breast cancer is a heterogeneous disease comprising a variety of entities with various genetic backgrounds. Estrogen receptor-positive, human epidermal growth factor receptor 2-negative tumors typically have a favorable outcome; however, some patients eventually relapse, which suggests some heterogeneity within this category. In the present study, we used proteomics and miRNA profiling techniques to characterize a set of 102 either estrogen receptor-positive (ER+)/progesterone receptor-positive (PR+) or triple-negative formalin-fixed, paraffin-embedded breast tumors. Protein expression-based probabilistic graphical models and flux balance analyses revealed that some ER+/PR+ samples had a protein expression profile similar to that of triple-negative samples and had a clinical outcome similar to those with triple-negative disease. This probabilistic graphical model-based classification had prognostic value in patients with luminal A breast cancer. This prognostic information was independent of that provided by standard genomic tests for breast cancer, such as MammaPrint, OncoType Dx and the 8-gene Score.
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spelling pubmed-55771372017-09-01 Functional proteomics outlines the complexity of breast cancer molecular subtypes Gámez-Pozo, Angelo Trilla-Fuertes, Lucía Berges-Soria, Julia Selevsek, Nathalie López-Vacas, Rocío Díaz-Almirón, Mariana Nanni, Paolo Arevalillo, Jorge M. Navarro, Hilario Grossmann, Jonas Gayá Moreno, Francisco Gómez Rioja, Rubén Prado-Vázquez, Guillermo Zapater-Moros, Andrea Main, Paloma Feliú, Jaime Martínez del Prado, Purificación Zamora, Pilar Ciruelos, Eva Espinosa, Enrique Fresno Vara, Juan Ángel Sci Rep Article Breast cancer is a heterogeneous disease comprising a variety of entities with various genetic backgrounds. Estrogen receptor-positive, human epidermal growth factor receptor 2-negative tumors typically have a favorable outcome; however, some patients eventually relapse, which suggests some heterogeneity within this category. In the present study, we used proteomics and miRNA profiling techniques to characterize a set of 102 either estrogen receptor-positive (ER+)/progesterone receptor-positive (PR+) or triple-negative formalin-fixed, paraffin-embedded breast tumors. Protein expression-based probabilistic graphical models and flux balance analyses revealed that some ER+/PR+ samples had a protein expression profile similar to that of triple-negative samples and had a clinical outcome similar to those with triple-negative disease. This probabilistic graphical model-based classification had prognostic value in patients with luminal A breast cancer. This prognostic information was independent of that provided by standard genomic tests for breast cancer, such as MammaPrint, OncoType Dx and the 8-gene Score. Nature Publishing Group UK 2017-08-30 /pmc/articles/PMC5577137/ /pubmed/28855612 http://dx.doi.org/10.1038/s41598-017-10493-w Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Gámez-Pozo, Angelo
Trilla-Fuertes, Lucía
Berges-Soria, Julia
Selevsek, Nathalie
López-Vacas, Rocío
Díaz-Almirón, Mariana
Nanni, Paolo
Arevalillo, Jorge M.
Navarro, Hilario
Grossmann, Jonas
Gayá Moreno, Francisco
Gómez Rioja, Rubén
Prado-Vázquez, Guillermo
Zapater-Moros, Andrea
Main, Paloma
Feliú, Jaime
Martínez del Prado, Purificación
Zamora, Pilar
Ciruelos, Eva
Espinosa, Enrique
Fresno Vara, Juan Ángel
Functional proteomics outlines the complexity of breast cancer molecular subtypes
title Functional proteomics outlines the complexity of breast cancer molecular subtypes
title_full Functional proteomics outlines the complexity of breast cancer molecular subtypes
title_fullStr Functional proteomics outlines the complexity of breast cancer molecular subtypes
title_full_unstemmed Functional proteomics outlines the complexity of breast cancer molecular subtypes
title_short Functional proteomics outlines the complexity of breast cancer molecular subtypes
title_sort functional proteomics outlines the complexity of breast cancer molecular subtypes
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5577137/
https://www.ncbi.nlm.nih.gov/pubmed/28855612
http://dx.doi.org/10.1038/s41598-017-10493-w
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