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Convergence Drug Combinations

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The SU2C – National Science Foundation- V Foundation Drug Combination Convergence Translational Research

Team Leader

  • Anthony Letai, MD, PhD

    Team Leader
    Associate Professor of Medicine, Medical Oncology, Dana-Farber Cancer Institute
    + Full Bio

About This Team’s Research

Decades of cancer research and therapeutic development have made it clear that achieving durable control of metastatic solid tumors will usually require high-order therapeutic combinations.  However, it has proven difficult to design such combinations.  Unfortunately, combinatorial regimen design and delivery cannot be solved through empirical trial and error.  Instead, new conceptual frameworks and approaches are needed to bring forth guiding principles for high-order therapeutic design/delivery.  To address this urgent need, we assembled a collaborative team that includes theoretical physicists and clinical investigators to integrate dynamic network modeling and evolutionary analyses with systematic cell death and therapeutic resistance data to predict high-order combinations and nominate dosing/scheduling principles.  This approach addresses the following:  i) leverages both functional data from preclinical systems and genomic/molecular data from drug-sensitive and drug-resistant tumors; ii) incorporates the multifactorial nature of cancer drug resistance into robust network models; iii) determines the extent to which inhibition of various network components induces cell death; iv) interrogates resistance heterogeneity by modeling all possible resistant states; and v) blends network dynamics and tumor evolutionary patterns. The team will construct dynamic models for estrogen-receptor positive breast cancer; will test the robustness of the models; and using molecular data obtained from breast cancer patients, will characterize and interpret the main evolutionary paths of sensitivity and resistance.

Click here to see a full list of Dream Team members