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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: https://doi.org/10.1101/2020.04.16.045245
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
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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
3Biological and Medical Informatics Graduate Program, University of California, San Francisco, San Francisco, CA, USA
4Integrative Program in Quantitative Biology, University of California, San Francisco, San Francisco, CA, USA
10Center for Computational Biology, University of California, Berkeley, Berkeley, CA, USA
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Ross A. Okimoto
5UCSF Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
6Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, California, USA
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Shigeki Nanjo
5UCSF Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
6Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, California, 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
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Nir Yosef
7Department of Electrical Engineering and Computer Science, University of California, Berkeley, Berkeley, CA, USA
8Chan Zuckerberg Biohub Investigator, San Francisco, CA, USA
9Ragon Institute of Massachusetts General Hospital, MIT and Harvard University, Cambridge, MA, USA
10Center for Computational Biology, University of California, Berkeley, Berkeley, CA, 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
5UCSF Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
6Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, California, 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
11Whitehead Institute, Cambridge, MA, USA
12Department 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

Cancer progression is characterized by rare, transient events which are nonetheless highly consequential to disease etiology and mortality. Detailed cell phylogenies can recount the history and chronology of these critical events – including metastatic seeding. Here, we applied our Cas9-based lineage tracer to study the subclonal dynamics of metastasis in a lung cancer xenograft mouse model, revealing the underlying rates, routes, and drivers of metastasis. We report deeply resolved phylogenies for tens of thousands of metastatically disseminated cancer cells. We observe surprisingly diverse metastatic phenotypes, ranging from metastasis-incompetent to aggressive populations. These phenotypic distinctions result from pre-existing, heritable, and characteristic differences in gene expression, and we demonstrate that these differentially expressed genes can drive invasiveness. Furthermore, metastases transit via diverse, multidirectional tissue routes and seeding topologies. Our work demonstrates the power of tracing cancer progression at unprecedented resolution and scale.

One Sentence Summary Single-cell lineage tracing and RNA-seq capture diverse metastatic behaviors and drivers in lung cancer xenografts in mice.

Competing Interest Statement

J.S.W. is an advisor and/or has equity in KSQ Therapeutics, Maze Therapeutics, Amgen, Tenaya, and 5 AM Ventures. T.G.B. is an advisor to Novartis, Astrazeneca, Revolution Medicines, Array, Springworks, Strategia, Relay, Jazz, Rain and receives research funding from Novartis and Revolution Medicines.

Footnotes

  • We now provide functional validation experiments showing that perturbation by CRISPRi or CRISPRa of metastasis-associated genes directly modulates invasion phenotypes in vitro in two distinct lung cancer cell lines (Fig.4). We also now show that transcriptional heterogeneity relating to metastatic phenotype that we observe in the mouse tumor cells is pre-existing in vitro, stably inherited over generations, and predictive of future metastatic capacity (Fig.5).

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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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
bioRxiv 2020.04.16.045245; doi: https://doi.org/10.1101/2020.04.16.045245
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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
bioRxiv 2020.04.16.045245; doi: https://doi.org/10.1101/2020.04.16.045245

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