Single-cell lineages reveal the rates, routes, and drivers of metastasis in cancer xenografts

Author:

Quinn Jeffrey J.123ORCID,Jones Matthew G.12456ORCID,Okimoto Ross A.78ORCID,Nanjo Shigeki78ORCID,Chan Michelle M.129ORCID,Yosef Nir6101112ORCID,Bivona Trever G.178ORCID,Weissman Jonathan S.121314ORCID

Affiliation:

1. Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA, USA.

2. Howard Hughes Medical Institute, University of California, San Francisco, San Francisco, CA, USA.

3. Inscripta, Inc., Boulder, CO, USA.

4. Biological and Medical Informatics Graduate Program, University of California, San Francisco, San Francisco, CA, USA.

5. Integrative Program in Quantitative Biology, University of California, San Francisco, San Francisco, CA, USA.

6. Center for Computational Biology, University of California, Berkeley, Berkeley, CA, USA.

7. UCSF Department of Medicine, University of California, San Francisco, San Francisco, CA, USA.

8. Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA.

9. Department of Molecular Biology, Princeton University, Princeton, NJ, USA.

10. Department of Electrical Engineering and Computer Science, University of California, Berkeley, Berkeley, CA, USA.

11. Chan Zuckerberg Biohub Investigator, San Francisco, CA, USA.

12. Ragon Institute of Massachusetts General Hospital, MIT and Harvard University, Cambridge, MA, USA.

13. Whitehead Institute, Cambridge, MA, USA.

14. Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA.

Abstract

Following cancer through the body The heterogeneity of mammalian tumors has been well documented, but it remains unknown how differences between individual cells lead to metastasis and spread throughout the body. Quinn et al. created a Cas9-based lineage tracer and used single-cell sequencing to generate phylogenies and follow the movement of metastatic human cancer cells implanted in the lung of a mouse xenograph model. Using this model, they found that within the same cell line, cancer cells exhibited diverse metastatic phenotypes. These subclones exhibited differential gene expression profiles, some of which were previously associated with metastasis. Science , this issue p. eabc1944

Funder

National Institutes of Health

Howard Hughes Medical Institute

National Institute of Allergy and Infectious Diseases

Pew Charitable Trusts

Alexander and Margaret Stewart Trust

Chan Zuckerberg Initiative

National Institute of General Medical Sciences

University of California, San Francisco Discovery Fellowship

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Multidisciplinary

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