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Data set of the protein expression profiles of Luminal A, Claudin-low and overexpressing HER2(+) breast cancer cell lines by iTRAQ labelling and tandem mass spectrometry

Breast cancer is the most common and the leading cause of mortality in women worldwide. There is a dire necessity of the identification of novel molecules useful in diagnosis and prognosis. In this work we determined the differentially expression profiles of four breast cancer cell lines compared to...

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Detalles Bibliográficos
Autores principales: Calderón-González, Karla Grisel, Valero Rustarazo, Ma Luz, Labra-Barrios, Maria Luisa, Bazán-Méndez, César Isaac, Tavera-Tapia, Alejandra, Herrera-Aguirre, Marí;aEsther, Sánchez del Pino, Manuel M., Gallegos-Pérez, José Luis, González-Márquez, Humberto, Hernández-Hernández, Jose Manuel, León-Ávila, Gloria, Rodríguez-Cuevas, Sergio, Guisa-Hohenstein, Fernando, Luna-Arias, Juan Pedro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4510402/
https://www.ncbi.nlm.nih.gov/pubmed/26217805
http://dx.doi.org/10.1016/j.dib.2015.04.025
Descripción
Sumario:Breast cancer is the most common and the leading cause of mortality in women worldwide. There is a dire necessity of the identification of novel molecules useful in diagnosis and prognosis. In this work we determined the differentially expression profiles of four breast cancer cell lines compared to a control cell line. We identified 1020 polypeptides labelled with iTRAQ with more than 95% in confidence. We analysed the common proteins in all breast cancer cell lines through IPA software (IPA core and Biomarkers). In addition, we selected the specific overexpressed and subexpressed proteins of the different molecular classes of breast cancer cell lines, and classified them according to protein class and biological process. Data in this article is related to the research article “Determination of the protein expression profiles of breast cancer cell lines by Quantitative Proteomics using iTRAQ Labelling and Tandem Mass Spectrometry” (Calderón-González et al. [1] in press).