HITS: Metabolic signaling as new concept for breast cancer risk estimation
HITS is partner of the international research consortium “MESI-STRAT” that explores the interplay of breast cancer metabolism and oncogenic signaling by systems medicine. The consortium was awarded by the European Union €6 million for five years. The main goal of the five-years project is to develop new models for knowledge-based stratification of patients into subgroups to guide targeted interventions. The Scientific Databases and Visualization (SDBV) group at HITS takes care of the model and data management platform.
Breast cancer is a complex disease with high prevalence in the European Union and world-wide. 75-80% of the patients have estrogen receptor (ER)-positive tumors and are treated with endocrine therapies. Endocrine therapies, which block ER-driven tumor growth, show high efficacy. Yet, a significant proportion of the patients will eventually relapse with metastatic breast cancer, and the recurrence rates remain almost constant for up to 20 years.
Breast cancer metabolism – a new concept for patient stratification
MESI-STRAT develops metabolite marker panels measurable in biological fluids to enable patient stratification, resistance monitoring and clinical decision-making throughout endocrine therapy. This is a new concept as breast cancer metabolism is poorly explored for diagnostics and therapy. Upon successful validation in preclinical models, the predictive marker panels and related treatments will be jointly investigated by MESI-STRAT’s clinical and industrial partners. A unique collection of matched breast cancer tissue, serum, and >10 years follow-up from the patient organization and MESI-STRAT co-coordinator “Patients’ Tumor Bank of Hope” (PATH, http://path-biobank.org/index.php/en/) is essential for the longitudinal analysis of endocrine therapy resistance and relapse.
Research aims and approach
The MESI-STRAT consortium explores the interplay of breast cancer metabolism and oncogenic signaling (MEtabolic SIgnaling) by systems medicine approaches. MESI-STRAT develops new models for knowledge-based stratification of patients into subgroups with different endocrine therapy resistance mechanisms. MESI-STRAT aims to establish predictive pipelines for (i) patient stratification prior and during endocrine therapy; (ii) recurrence risk assessment when ending endocrine therapy; (iii) marker panels to guide established targeted therapies for endocrine therapy-resistant patients; and (iv) novel resistance mechanism-based therapy design.
A pan-European team of oncologists, modelers, bioinformaticians and experimentalists will develop new computational models in combination with network analyses and pharmacogenomics, to integrate multi-omics data and explore metabolic and signaling networks driving endocrine therapy resistance.