Jin, XinDemere, ZelalemNair, KarthikAli, AhmedFerraro, Gino BNatoli, TedDeik, AmyPetronio, LiaTang, Andrew AZhu, CongWang, LiRosenberg, DannyMangena, VamsiRoth, JenniferChung, KwanghunJain, Rakesh KClish, Clary BVander Heiden, Matthew GGolub, Todd RengEnglandNature. 2020 Dec;588(7837):331-336. doi: 10.1038/s41586-020-2969-2. Epub 2020 Dec 9.
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 that is 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(1,2) spanning 21 types of solid tumour. 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.