What is the problem/issue being addressed?
Some patients do and others do not benefit from combination therapies (chemotherapy combined with immune therapy or with targeted anti-angiogenesis treatment). We will study this by integrating multi-omics data from clinical trials (treatment resistance signatures) and use this information to predict response up front and to design effective combination therapies.
Why is it important for society?
Breast cancer is the most common type of cancer among women. A fraction of the breast cancers has either no good therapeutic offer (TNBC) or experience a late relapse often presenting with metastatic disease. This is a small fraction of all breast cancers, but on the overall a large number of cases. Our trial study the most common treatment modalities, chemotherapy and hormonal therapy. The revenue of Arimidex alone is millions of US dollars yearly. The most expensive drug is the one that does not work. Identifying the best combination and dosage for every woman will safe money and lives.
What are the overall objectives?
The general objective of this project is to discover effective treatment combinations for individual/subgroups of breast cancer patients through the assessment and validation in vivo, in vitro, and in silico of mechanisms of treatment resistance at cellular/sub-cellular level. RESCUER will integrate and analyze existing and newly generated clinical and multi-omic data and biological samples from ongoing clinical trials to identify the physiological characteristics of non-responders vs. responders and to suggest clinically effective personalized drugs combinations.
Identify which new combinations of existing drugs have a high probability to work on individual or thin strata of patients and propose them for further investigation.
