A metastasis map of human cancer cell lines Xin Jin 1,*, Zelalem Demere 1, Karthik Nair 1, Ahmed Ali 1,2, Gino B. Ferraro 3, Ted Natoli 1, Amy Deik 1, Lia Petronio 1, Andrew A. Tang 1, Cong Zhu 1, Li Wang 1, Danny Rosenberg 1, Vamsi Mangena 4, Jennifer Roth 1, Kwanghun Chung 1,4, Rakesh K. Jain 3,5, Clary B. Clish 1, Matthew G. Vander Heiden 1,2,6, Todd R. Golub 1,5,6,* 1. Broad Institute of MIT and Harvard, Cambridge, MA, USA 2. Koch Institute for Integrative Cancer Research, Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA 3. Edwin L. Steele Laboratories, Department of Radiation Oncology, Massachusetts General Hospital, Boston, MA, USA 4. Institute for Medical Engineering and Science, Picower Institute for Learning and Memory, Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA 5. Harvard Medical School, Boston, MA, USA 6. Dana-Farber Cancer Institute, Boston, MA, USA * Correspondence to Xin Jin (email@example.com) or Todd R. Golub (firstname.lastname@example.org) Most deaths from cancer are explained by metastasis, and yet large-scale metastasis research has been impractical owing to the complexity of in vivo models. Here we introduce an in vivo barcoding strategy capable of determining the metastatic potential of human cancer cell lines in mouse xenografts at scale. We validated the robustness, scalability and reproducibility of the method and applied it to 500 cell lines spanning 21 types of solid tumor. We created a first-generation metastasis map (MetMap) that reveals organ-specific patterns of metastasis, enabling these patterns to be associated with clinical and genomic features. We demonstrate the utility of MetMap by investigating the molecular basis of breast cancers capable of metastasizing to the brain—a principal cause of death in patients with this type of cancer. Breast cancers capable of metastasizing to the brain showed evidence of altered lipid metabolism. Perturbation of lipid metabolism in these cells curbed brain metastasis development, suggesting a therapeutic strategy to combat the disease and demonstrating the utility of MetMap as a resource to support metastasis research.