Mathematical modeling and molecular imaging to maximize response while minimizing toxicities from systemic therapies in preclinical models of breast cancer

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PROJECT SUMMARY Our overarching goal is to utilize biology-based mathematical models and advanced molecular imaging to dramatically decrease systemic toxicities while either maintaining or accelerating tumor control in preclinical models of breast cancer. Advances in systemic therapies have improved long-term survival in patients with locally-advanced breast cancer, however there has been a concomitant increase in the associated their long-term side effects, including cognitive deficits and cardiac problems. We have developed practical, biology- based mathematical models capable of systematically investigating the timing, order, dosing, and sequencing of combination therapies to identify therapeutic regimens that can potentially maximize response while minimizing toxicity. Preliminary results (both experimental and mathematical) reveal that alternating the order and dosing of combination chemotherapy (doxorubicin) and targeted therapy (Herceptin) can significantly and synergistically enhance response while reducing the chemotherapy dose by 50%. Furthermore, using optimal control theory, we have identified therapeutic regimens suggesting we can achieve tumor control 1.6x faster without increasing the amount of chemotherapy. We propose to develop the mathematical formalism that allows for systematically determining, on a patient specific basis, therapeutic regimens that maximize tumor response and minimize side effects. We then select the most promising options and test them experimentally against established treatment regimens and test for superior outcomes and toxicity. We also seek to develop quantitative imaging technologies capable of characterizing the temporal alterations in brain and cardiac function—organs known to be adversely affected by chemotherapies. We plan to achieve this goal with the following Specific Aims. Aim 1 will validate mathematical predictions for maintaining tumor control with minimal chemotherapy dose by employing optimal control theory to identify and biologically validate (with immunohistochemistry and overall tumor burden measurements) the three most promising combination treatment strategies. Aim 2 will implement advanced molecular imaging to quantify toxicity changes in critical organs during therapy by employing cardiac imaging of membrane potential (18F-TTP+-PET) and brain imaging of microglia activation (TSPO, measured with 18F-DPA- 714-PET) to determine longitudinal differences between long-term effects in animals treated with the standard and the optimized regimens. Completion of these aims will deliver a practical, experimental-computational approach for identifying optimal treatment strategies in pre-clinical mouse models, and appropriate for prospective testing in phase 1 clinical trials. As toxicity is the main dose-limiting factor in cancer treatments, developing methods to control it will dramatically effect patient health.