RESEARCH PROJECT 1: Enhancing Neoadjuvant Therapy To Prevent Breast Cancer Recurrence PROJECT SUMMARY Based on our strong preliminary and published data, our overarching hypothesis guiding the project is that agents that enhance response to neoadjuvant combination chemotherapy will decrease recurrence rates by reduction or elimination of minimal residual disease. These targeted agents may also function in combination with one another, which may allow elimination of cytotoxic systemic chemotherapy. We further hypothesize that response data can be used to refine computational methods for drug response prediction. Aside from study of frank resistance to chemotherapies, which is also possible using our combined PDX platform, study of minimal residual disease, as well as both local and distant recurrence is also important, particularly in PDX derived from racial groups whose disease outcomes are worse than those in Caucasian women (i.e. African American and Hispanic women). Under our current PDTC, we have already identified seven PDX as recurrent after apparent complete response (CR) to combination carboplatin/docetaxel. We will apply a refined set of computationally determined predictive signatures of differential response to carboplatin and taxanes (paclitaxel going forward to match an upcoming clinical trial) to the remainder of TNBC in our combined PDX collection, as well as to TNBC PDX to be created in both PDTC projects to identify PDX most likely to show complete response to the combination. Importantly, response to either carboplatin or docetaxel correlates with response to their combination 86% of the time. Existing and new PDX will be evaluated for CR and recurrence in response to combination chemotherapy in Aim 1, with the ultimate goal of identifying a total of at least 20, but optimally 30, recurrent PDX models for testing of the ability of targeted agents computationally predicted to augment chemotherapy response in Aim 2 to reduce or prevent recurrence in Aim 3.