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Mol Cell Proteomics ; 12(12): 3612-23, 2013 Dec.
Artículo en Inglés | MEDLINE | ID: mdl-23982162

RESUMEN

Tumor progression and prognosis in breast cancer patients are difficult to assess using current clinical and laboratory parameters, where a pathological grading is indicative of tumor aggressiveness. This grading is based on assessments of nuclear grade, tubule formation, and mitotic rate. We report here the first protein signatures associated with histological grades of breast cancer, determined using a novel affinity proteomics approach. We profiled 52 breast cancer tissue samples by combining nine antibodies and label-free LC-MS/MS, which generated detailed quantified proteomic maps representing 1,388 proteins. The results showed that we could define in-depth molecular portraits of histologically graded breast cancer tumors. Consequently, a 49-plex candidate tissue protein signature was defined that discriminated between histological grades 1, 2, and 3 of breast cancer tumors with high accuracy. Highly biologically relevant proteins were identified, and the differentially expressed proteins indicated further support for the current hypothesis regarding remodeling of the tumor microenvironment during tumor progression. The protein signature was corroborated using meta-analysis of transcriptional profiling data from an independent patient cohort. In addition, the potential for using the markers to estimate the likelihood of long-term metastasis-free survival was also indicated. Taken together, these molecular portraits could pave the way for improved classification and prognostication of breast cancer.


Asunto(s)
Biomarcadores de Tumor/genética , Neoplasias de la Mama/genética , Neoplasias de la Mama/patología , Carcinoma/genética , Carcinoma/patología , Regulación Neoplásica de la Expresión Génica , Adulto , Anciano , Neoplasias de la Mama/diagnóstico , Neoplasias de la Mama/mortalidad , Carcinoma/diagnóstico , Carcinoma/mortalidad , Progresión de la Enfermedad , Supervivencia sin Enfermedad , Femenino , Perfilación de la Expresión Génica , Humanos , Persona de Mediana Edad , Clasificación del Tumor , Pronóstico , Proteómica/métodos , Proteómica/estadística & datos numéricos , Transcriptoma , Microambiente Tumoral/genética
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