A metastasis map of human cancer cell lines

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

Research output: Contribution to journalArticlepeer-review

103 Citations (Scopus)


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 lines1,2 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.

Original languageEnglish
Pages (from-to)331-336
Number of pages6
Issue number7837
Publication statusPublished - 2020 Dec 10

Bibliographical note

Funding Information:
Acknowledgements We thank J. L. Goldstein for suggestions; A. Regev, N. Marjanovic and A. Bankapur for assistance with single-cell RNA-seq and analysis; Z. Herbert for assistance with RNA-seq; T. Mason for assistance with next-generation sequencing; S. Kim and S. Roberge for assistance with animal work; B. Wong for suggestions on figure and portal designs; and G. Wei, U. Ben-David, S. Corsello, P. Tsvetkov, I. Tirosh, R. Hosking and C. Mader for discussions. X.J. and G.B.F. were Susan G. Komen Fellows. A.A. is a HHMI Medical Research Fellow. This work was supported by BroadNext10, Broad SharkTank grants (X.J.), HHMI (T.R.G.), and in part by Koch Institute/DFHCC Bridge project grant (M.G.V.H. and R.K.J.). R.K.J. acknowledges support from the NIH (R35CA197742, R01CA208205 and U01CA224173), National Foundation for Cancer Research; the Ludwig Center at Harvard; the Jane’s Trust Foundation; the Advanced Medical Research Foundation and by the U.S Department of Defense Breast Cancer Research Program Innovator Award W81XWH-10-1-0016.

Publisher Copyright:
© 2020, The Author(s), under exclusive licence to Springer Nature Limited.

All Science Journal Classification (ASJC) codes

  • General


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