The use of systemic chemotherapy for breast cancer has contributed to the recent decline in breast cancer mortality;however, an unacceptable number of patients fail systemic therapy and die of disseminated disease. Identifying factors important in resistance and directing patients towards more effective treatment is the translational goal of Project 3. Using quantitative PET imaging to measure glucose metabolism, and more recently dynamic contrast-enhanced (DCE) MRI to measure blood flow, we have identified an in vivo metabolic signature for locally advanced breast cancer (LABC) resistant to neoadjuvant chemotherapy as (1) a pre-therapy mismatch between metabolism and perfusion, (2) persistent or even increased tumor perfusion despite treatment, and (3) an altered pattern of glucose metabolism relative to glucose delivery after treatment. This pattern predicts incomplete response, early relapse and death independent of established prognostic factors, including pathologic primary tumor and nodal pathologic response. We have also found this pattern is more profoundly associated with triple-negative (TN, ER/PR/HER2 negative) tumors versus those that express ER/PR and/or over-express HER2. We now propose to translate our clinical, in vivo findings in patients back into the laboratory to identify the biologic features of tumors underlying these findings. In a cohort of LABC patients undergoing neoadjuvant chemotherapy, we will (1) compare imaging findings to tumor phenotype determined by IHC and expression microarrays to determine which molecular pathways are most involved In the resistant imaging phenotype, (2) determine the role ofthe tumor microenvironment, specifically tumor hypoxia measured by FMISO PET and the expression ofthe hypoxic tissue markers measured by IHC, and (3) relate macroscopic metabolic properties measured by imaging to cellular metabolism in biopsy specimens and a panel of cell lines using ToF-SIMS, with the goal of relating findings on metabolic pathways measured in cell lines to the resistant phenotype seen in patients. Successful completion of the studies will identify breast cancer patients likely to fail systemic chemotherapy and direct therapy towards those biologic targets most likely to overcome resistance.