Abstract

Abstract Most deaths from cancer are explained by metastasis, and yet large-scale metastasis research has been impractical due to the inherent scale limitation of the in vivo models. Here we introduce an in vivo barcoding strategy capable of determining the metastatic potential of human cancer cell lines in murine xenografts at scale. We validated the robustness, scalability and reproducibility of the method, and applied it to 500 cell lines spanning 21 solid cancer types. We created a first-generation Metastasis Map (MetMap) that reveals organ-specific patterns of metastasis and allows relating those patterns to clinical and genomic features. We demonstrated the utility of MetMap by exploring the molecular basis of breast cancers capable of metastasizing to the brain - a principal cause of death in these patients. Breast cancers that were brain metastatic had unexpected genetic, expression, and metabolic evidence of altered lipid metabolism. Perturbing lipid metabolism curbed brain metastasis development and limited the outgrowth of cancer cells in the brain, suggesting a therapeutic strategy to combat the disease. These results illustrated the utility of MetMap as a step towards next-generation approach for high-throughput metastasis research. Citation Format: Xin Jin, Zelalem Demere, Karthik Nair, Ahmed Ali, Gino B. Ferraro, Ted Natoli, Amy Deik, Lia Petronio, Andrew A. Tang, Cong Zhu, Li Wang, Danny Rosenberg, Vamsi Mangena, Jennifer Roth, Kwanghun Chung, Rakesh K. Jain, Clary B. Clish, Matthew G. Vander Heiden, Todd R. Golub. A metastasis map of human cancer cell lines [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr NG10.

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