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

Jeffrey J. Quinn; Matthew G. Jones; Ross A. Okimoto; Shigeki Nanjo; Michelle M. Chan; Nir Yosef; Trever G. Bivona; Jonathan S. Weissman

doi:10.1126/science.abc1944

Research Article

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

View ORCID ProfileJeffrey J. Quinn ¹,²,³,*,
View ORCID ProfileMatthew G. Jones ¹,²,⁴,⁵,⁶,*,
View ORCID ProfileRoss A. Okimoto⁷,⁸,
View ORCID ProfileShigeki Nanjo⁷,⁸,
View ORCID ProfileMichelle M. Chan¹,²,⁹,
View ORCID ProfileNir Yosef ⁶,¹⁰,¹¹,¹²,†,
View ORCID ProfileTrever G. Bivona ¹,⁷,⁸,†,
View ORCID ProfileJonathan S. Weissman ¹,²,¹³,¹⁴,†

¹Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA, USA.
²Howard Hughes Medical Institute, University of California, San Francisco, San Francisco, CA, USA.
³Inscripta, Inc., Boulder, CO, USA.
⁴Biological and Medical Informatics Graduate Program, University of California, San Francisco, San Francisco, CA, USA.
⁵Integrative Program in Quantitative Biology, University of California, San Francisco, San Francisco, CA, USA.
⁶Center for Computational Biology, University of California, Berkeley, Berkeley, CA, USA.
⁷UCSF Department of Medicine, University of California, San Francisco, San Francisco, CA, USA.
⁸Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA.
⁹Department of Molecular Biology, Princeton University, Princeton, NJ, USA.
¹⁰Department of Electrical Engineering and Computer Science, University of California, Berkeley, Berkeley, CA, USA.
¹¹Chan Zuckerberg Biohub Investigator, San Francisco, CA, USA.
¹²Ragon Institute of Massachusetts General Hospital, MIT and Harvard University, Cambridge, MA, USA.
¹³Whitehead Institute, Cambridge, MA, USA.
¹⁴Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA.

↵†Corresponding authors. Email: weissman{at}wi.mit.edu (J.S.W.); trever.bivona{at}ucsf.edu (T.G.B.); niryosef{at}berkeley.edu (N.Y.)

↵* These authors contributed equally to this work.

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Science 21 Jan 2021:
eabc1944
DOI: 10.1126/science.abc1944

Jeffrey J. Quinn

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

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

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

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ORCID record for Jeffrey J. Quinn

Matthew G. Jones

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

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

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

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

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

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ORCID record for Matthew G. Jones

Ross A. Okimoto

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

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

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Shigeki Nanjo

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

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

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Michelle M. Chan

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

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

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

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Nir Yosef

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

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

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

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

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For correspondence: weissman@wi.mit.edu trever.bivona@ucsf.edu niryosef@berkeley.edu

Trever G. Bivona

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

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

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

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For correspondence: weissman@wi.mit.edu trever.bivona@ucsf.edu niryosef@berkeley.edu

Jonathan S. Weissman

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

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

13Whitehead Institute, Cambridge, MA, USA.

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

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For correspondence: weissman@wi.mit.edu trever.bivona@ucsf.edu niryosef@berkeley.edu

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Abstract

Detailed phylogenies of tumor populations can recount the history and chronology of critical events during cancer progression, such as metastatic dissemination. We applied a Cas9-based, single-cell lineage tracer to study the rates, routes, and drivers of metastasis in a lung cancer xenograft mouse model. We report deeply resolved phylogenies for tens of thousands of cancer cells traced over months of growth and dissemination. This revealed stark heterogeneity in metastatic capacity, arising from pre-existing and heritable differences in gene expression. We demonstrate that these identified genes can drive invasiveness, and uncovered an unanticipated suppressive role for KRT17. We also show that metastases disseminated via multidirectional tissue routes and complex seeding topologies. Overall, we demonstrate the power of tracing cancer progression at subclonal resolution and vast scale.

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

Abstract

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