Project Summary Metabolic programs are particularly relevant during metastasis as it is an inefficient process comprising several consecutive steps, with only a small proportion of circulating tumor cells generating a metastatic lesion. The inefficiency is largely attributable to the host organ environments, which impose metabolic limitations on cancer cells. Indeed, cancer cells are frequently starved for nutrients and oxygen in distant organ environments due to poor vasculature. To endure unfavorable nutrient conditions during the metastatic cascade, disseminated tumor cells require substantial metabolic rewiring that enables them to grow at the primary and metastatic sites. Additionally, cancer cells metabolically interact with each other and with normal cell types or upregulate alternative pathways to overcome these metabolic limitations in their environment. Integration of nutrient availability from the local environment with metabolic adaptation signatures in cancer cells is key to understanding how cancer cells interact with the surrounding cells and extracellular nutrients. Furthermore, as re-population of cancer cells at a new organ site creates challenges for effective anti-tumor therapeutic strategies, there is an unmet basic and clinical need to better understand the molecular interplay between the metastatic site and tumor cells. Therefore, in this proposal, we will test the hypothesis that distant organ sites impose metabolic restrictions that cancer cells need to overcome for metastatic colonization. To address this, we will employ a comprehensive unbiased approach that combines multiple genetic, transcriptomic and metabolomics techniques. These approaches will enable us to dissect the metabolic heterogeneity of cancer cells and other cell types in distant organ sites. In the first aim, we will systematically map metabolic dependencies of breast cancer cells during colonization of the lung and liver using CRISPR-based loss and gain of function approaches. In our preliminary work, we have already identified potential candidates that are involved in breast cancer metastasis to lung. In the second aim, we will investigate the role of niche cells by combining cell-specific metabolomics and single-cell sequencing approaches in multiple metastasis models and in response to therapy. The Birsoy lab has recently pioneered the use of metabolism focused CRISPR screens to study multiple aspects of cellular metabolism in cancer models. The Cao and Saeed Tavazoie labs have expertise in single cell transcriptomics and computational biology. By integrating gene expression profiles and metabolomic information generated by this collaborative multidisciplinary effort, our work will provide entry points for identifying pathways that may be activated or repressed during the course of metastatic colonization and in response to therapy.