Massively Parallel Molecular Profiling of Breast Cancer
EMSL Project ID
48668
Abstract
Molecular profiling of breast cancer into subcategories based on functional ER expression and amplification of HER2 has significantly enhanced our understanding of the disease, and has pointed the way to broad categories of therapeutic intervention. However, even within the currently recognized subtypes significant levels of heterogeneity are observed in outcomes and response to therapy, particularly in those subtypes resistant to hormonal therapy; e.g. the ‘triple negative’ (ER negative PR negative HER2 negative, or ER-PR-HER2- ) subtype, the ER negative HER2 positive (ER- HER2+) subtype, and the Luminal B subtype. We hypothesize that the clinical heterogeneity of functionally ER- breast cancers is a manifestation of not only differences in gene expression, but also in the functional status and post-translational modifications of the associated proteins that are reflective of the combined effects of population and disease heterogeneity. Thus, robust integration of genomic and broad proteomic data (including global proteomics, phosphoproteomics, O-GlcNAc proteomics, peptidomics and glycomics) from the same patient samples, procured and analyzed under defined protocols, has the potential to provide more effective stratification of patients for prognosis and therapy.
Project Details
Start Date
2014-11-03
End Date
2017-09-30
Status
Closed
Released Data Link
Team
Principal Investigator
Team Members
Related Publications
Wu C, ME Monroe, Z Xu, GW Slysz, SH Payne, KD Rodland, T Liu, and RD Smith. 2015. "An Optimized Informatics Pipeline for Mass Spectrometry-Based Peptidomics." Journal of the American Society for Mass Spectrometry . doi:10.1007/s13361-015-1169-z [In Press]