The I-SPY2 trial is a multicenter, Phase II neoadjuvant platform trial for high risk, early-stage breast cancer designed to rapidly identify new treatments and treatment combinations with increased efficacy on a standard-of-care background (sequential weekly paclitaxel followed by doxorubicin/cyclophosphamide (T-AC) chemotherapy). It is considered the archetype of the adaptive platform trial, enabling multiple novel treatment regimens to be evaluated simultaneously, targeting treatment to breast cancer subtypes defined by on hormone receptor (HR) and Human Epidermal Growth Factor Receptor-2 (HER2) expression, and MammaPrint (prognosis signature) high risk status. Since launching in 2010, 24 new therapies or combinations have been tested, and 7 found to significantly improve pathologic complete response (pCR), leading to several definitive phase III trials. However, with this success came the realization that within the 8 predefined subtypes not everyone benefitted. Through this program project we designed and implemented a next generation I-SPY2.2 trial to advanced personalized medicine in early breast cancer treatment with a patient-centric approach to clinical drug development. I-SPY2.2 allows the optimization of individual treatments by escalation or de-escalation of therapy based on treatment response measured by an MRI-based assessment, doing so in the context of a trial that efficiently evaluates novel potential first-line regimens. Project 3 has been instrumental in advancing our understanding of the dynamics of the biology of response and treatment resistance and enhancing our ability to better target agents to individual biology by improving stratification of high-risk tumor biology. In collaboration with Project 4, we developed more refined response- predictive subtypes, ‘RPS,’ that modelling suggests will result in improvements in pCR rates of over 15%. Characterizing and understanding the biology and dynamics of treatment non-response in stage 2 and 3 breast cancer provides the mechanistic basis for the rational design of treatment switching strategies and development of composite measures to assess treatment response and recurrence risk to guide clinical decision-making. In our current proposal and based of our earlier work in the program project and beyond, we now hypothesize that a comprehensive approach to understand non- response across multiple omics levels (Aim 1) and integrated with dynamic imaging features (from Project 2), will provide the best strategy for robust results for either escalation or de-escalation in the course of the trial treatment (Aim 2; for Project 1). We have extended our experimental platforms with several that are based on liquid biopsies (such as ctDNA, immune cytokine typing and exosome analyses of protein/phosphoproteins). This, in combination with an extension of our technologies already employed in our current grant, will give us the best option to prioritize alternative therapies in case of early, ...