Cancer cells exist in a complex integrated environment that provides regulatory cues that can promote or inhibit cancer progression. We believe those regulatory events can be decoded and harnessed to improve cancer prevention and therapy. The metabolic environment of cancer cells, created by the local tissue environment and influenced by a person's overall health status and behaviors, is a ripe target for intervention. In particular, it is well known that the risk of breast cancer occurrence and progression, as well as the success of therapy, is strongly impacted by the metabolic state of the patient, but the molecular mechanisms underlying this truth are multifactorial and largely unknown. Similarly, the specific tissue environment of cancer cells in locations such as breast tissue or bone marrow and are known to regulate the likelihood of cancer cell growth, migration and dormancy and that metabolism plays a strong role by mechanisms that are complex and difficult to observe in vivo. We propose to develop a cohesive understanding of how metabolism at the cellular, tissue, and organismal scale regulate breast cancer progression using 1) advanced approaches to in-vivo single cell fluorescence imaging of novel reporters of metabolism and cell signaling, 2) cutting edge image analysis to extract multichannel metabolic and phenotypic information from complex 3-D dynamic imaging, and 3) innovative computational modeling to integrate multi-scale information.