Functional proteomics outlines the complexity of breast cancer molecular subtypes
Arevalillo, Jorge M.
Moreno, Francisco G.
Gómez Rioja, Rubén
Martínez del Prado, Purificación
Fresno Vara, Juana A.
- Journal Article
Rights / licenseCreative Commons Attribution 4.0 International
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 Show more
Journal / seriesScientific Reports
Pages / Article No.
PublisherNature Publishing Group
Organisational unit02207 - Functional Genomics Center Zürich / Functional Genomics Center Zürich
02207 - Functional Genomics Center Zürich / Functional Genomics Center Zürich
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