Looking for Partners in Crime: Identification of Protein Complexes and Post-Translational Modifications Associated with Drug-Resistance in Breast Cancer
EMSL Project ID
40132
Abstract
Drug resistance of metastatic tumor cells is the major cause of death in breast cancer patients. Through a previous EMSL collaboration, EMMPRIN (extracellular matrix metalloproteinase inducer) was identified as a predictor of hormonal therapy resistance and associated with poor survival. EMMPRIN is involved in multidrug resistance through interaction with drug transporter complexes and downstream signaling pathways. EMMPRIN binding partners have been largely identified in in vitro cellular models thus, their in vivo clinical relevance is essentially unknown. Furthermore, the role of EMMPRIN in therapy response prediction is established using protein abundance instead of protein activity. In addition, little is known about the metabolic changes associated with drug resistance. For these reasons herein we propose to: 1. Identify (new) EMMPRIN protein partners in cell lines and verify their clinical significance using breast cancer tissues. 2. Determine activity and composition of EMMRPIN protein complexes in response to drug treatment. 3. Identify metabolic profiles that associate with drug resistance. Work plan (see figure 1): Ad 1: Individual components of EMMPRIN protein complexes will be identified in drug treated breast cancer cell lines using immunoprecipitation mass spectrometry (MS). Clinical relevance of interactions will be determined in tissues using recently developed in situ Proximity Ligation Assay (PLA). This powerful tool enables detection of protein interactions and their cellular localization in archived clinical specimen. Ad 2: Post-translational modifications (e.g. phosphorylation) determine protein activity. Multisite phosphorylation will be measured at the intact protein level using a newly developed, comprehensive LC-MS approach. Ad 3: Changes in metabolic profiles will be monitored in breast cancer cell lines treated with a panel of clinically relevant drugs, using nuclear magnetic resonance (NMR) and LC-MS. Predictive metabolic profiles will be validated in clinical specimens. Relevance: Correct prediction of drug response and reversal of drug resistance by interfering with key players will enable personalized treatment and prolong survival of breast cancer patients.
Project Details
Project type
Large-Scale EMSL Research
Start Date
2010-10-12
End Date
2011-10-16
Status
Closed
Released Data Link
Team
Principal Investigator