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Single-cell analysis resolves the cell state transition and signaling dynamics associated with melanoma drug-induced resistance

Yapeng Su, Wei Wei, Lidia Robert, Min Xue, Jennifer Tsoi, Angel Garcia-Diaz, Blanca Homet Moreno, Jungwoo Kim, Rachel H. Ng, Jihoon W. Lee, Richard C. Koya, Begonya Comin-Anduix, Thomas G. Graeber, Antoni Ribas, and James R. Heath
PNAS December 26, 2017 114 (52) 13679-13684; published ahead of print December 11, 2017 https://doi.org/10.1073/pnas.1712064115
Yapeng Su
aNanoSystems Biology Cancer Center, California Institute of Technology, Pasadena, CA 91125;bDivision of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA 91125;
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Wei Wei
aNanoSystems Biology Cancer Center, California Institute of Technology, Pasadena, CA 91125;cDepartment of Molecular and Medical Pharmacology, University of California, Los Angeles, CA 90095;dJonsson Comprehensive Cancer Center, University of California, Los Angeles, CA 90095;
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  • ORCID record for Wei Wei
  • For correspondence: weiwei@mednet.ucla.eduaribas@mednet.ucla.eduheath@caltech.edu
Lidia Robert
eDepartment of Medicine, University of California, Los Angeles, CA 90095;
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Min Xue
aNanoSystems Biology Cancer Center, California Institute of Technology, Pasadena, CA 91125;bDivision of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA 91125;
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Jennifer Tsoi
cDepartment of Molecular and Medical Pharmacology, University of California, Los Angeles, CA 90095;
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Angel Garcia-Diaz
eDepartment of Medicine, University of California, Los Angeles, CA 90095;
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Blanca Homet Moreno
eDepartment of Medicine, University of California, Los Angeles, CA 90095;fDivision of Translational Oncology, Carlos III Health Institute, 28029 Madrid, Spain;
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Jungwoo Kim
aNanoSystems Biology Cancer Center, California Institute of Technology, Pasadena, CA 91125;bDivision of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA 91125;
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  • ORCID record for Jungwoo Kim
Rachel H. Ng
aNanoSystems Biology Cancer Center, California Institute of Technology, Pasadena, CA 91125;bDivision of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA 91125;
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Jihoon W. Lee
aNanoSystems Biology Cancer Center, California Institute of Technology, Pasadena, CA 91125;bDivision of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA 91125;
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Richard C. Koya
gDepartment of Surgery, Division of Surgical-Oncology, University of California, Los Angeles, CA 90095;
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Begonya Comin-Anduix
dJonsson Comprehensive Cancer Center, University of California, Los Angeles, CA 90095;gDepartment of Surgery, Division of Surgical-Oncology, University of California, Los Angeles, CA 90095;
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Thomas G. Graeber
cDepartment of Molecular and Medical Pharmacology, University of California, Los Angeles, CA 90095;dJonsson Comprehensive Cancer Center, University of California, Los Angeles, CA 90095;hCrump Institute for Molecular Imaging, University of California, Los Angeles, CA 90095
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Antoni Ribas
cDepartment of Molecular and Medical Pharmacology, University of California, Los Angeles, CA 90095;dJonsson Comprehensive Cancer Center, University of California, Los Angeles, CA 90095;eDepartment of Medicine, University of California, Los Angeles, CA 90095;gDepartment of Surgery, Division of Surgical-Oncology, University of California, Los Angeles, CA 90095;
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  • For correspondence: weiwei@mednet.ucla.eduaribas@mednet.ucla.eduheath@caltech.edu
James R. Heath
aNanoSystems Biology Cancer Center, California Institute of Technology, Pasadena, CA 91125;bDivision of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA 91125;dJonsson Comprehensive Cancer Center, University of California, Los Angeles, CA 90095;
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  • For correspondence: weiwei@mednet.ucla.eduaribas@mednet.ucla.eduheath@caltech.edu
  1. Edited by Herbert Levine, Rice University, Houston, TX, and approved November 14, 2017 (received for review July 6, 2017)

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Significance

This work provides biophysical insights into how BRAF mutant melanoma cells adapt to the stress of MAPK inhibition via a series of reversible phenotypic transitions toward drug-tolerant or drug-resistant cell states enriched for neural-crest factors and mesenchymal signatures. This adaptation is influenced by cell phenotype-specific drug selection and cell state interconversion, but not selection of genetically resistant clones. A panel of functional proteins, analyzed at the single-cell level, pointed to signaling network hubs that drive the initiation of the melanoma cell adaptive transition. Targeting those hubs halted the transition and arrested resistance development.

Abstract

Continuous BRAF inhibition of BRAF mutant melanomas triggers a series of cell state changes that lead to therapy resistance and escape from immune control before establishing acquired resistance genetically. We used genome-wide transcriptomics and single-cell phenotyping to explore the response kinetics to BRAF inhibition for a panel of patient-derived BRAFV600-mutant melanoma cell lines. A subset of plastic cell lines, which followed a trajectory covering multiple known cell state transitions, provided models for more detailed biophysical investigations. Markov modeling revealed that the cell state transitions were reversible and mediated by both Lamarckian induction and nongenetic Darwinian selection of drug-tolerant states. Single-cell functional proteomics revealed activation of certain signaling networks shortly after BRAF inhibition, and before the appearance of drug-resistant phenotypes. Drug targeting those networks, in combination with BRAF inhibition, halted the adaptive transition and led to prolonged growth inhibition in multiple patient-derived cell lines.

  • single-cell analysis
  • cell state transition
  • adaptive resistance
  • Markov chain model
  • melanoma

Footnotes

  • ↵1Y.S., W.W., and L.R. contributed equally to this work.

  • ↵2To whom correspondence should be addressed. Email: weiwei{at}mednet.ucla.edu, aribas{at}mednet.ucla.edu, or heath{at}caltech.edu.
  • Author contributions: W.W., A.R., and J.R.H. designed research; Y.S., W.W., L.R., M.X., J.T., A.G.-D., B.H.M., J.K., R.H.N., J.W.L., R.C.K., and B.C.-A. performed research; Y.S. and W.W. developed the computational model; Y.S., W.W., L.R., M.X., J.T., A.G.-D., B.H.M., T.G.G., A.R., and J.R.H. analyzed data; W.W., A.R., and J.R.H. supervised the study; and Y.S., W.W., L.R., M.X., A.R., and J.R.H. wrote the paper.

  • Conflict of interest statement: J.R.H. and A.R. are affiliated with Isoplexis, which is seeking to commercialize the single-cell barcode chip technology.

  • This article is a PNAS Direct Submission.

  • Data deposition: The RNA-seq data reported in this paper have been deposited in the ArrayExpress database (accession no. E-MTAB-5493).

  • This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1712064115/-/DCSupplemental.

Published under the PNAS license.

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Single-cell analysis resolves melanoma resistance
Yapeng Su, Wei Wei, Lidia Robert, Min Xue, Jennifer Tsoi, Angel Garcia-Diaz, Blanca Homet Moreno, Jungwoo Kim, Rachel H. Ng, Jihoon W. Lee, Richard C. Koya, Begonya Comin-Anduix, Thomas G. Graeber, Antoni Ribas, James R. Heath
Proceedings of the National Academy of Sciences Dec 2017, 114 (52) 13679-13684; DOI: 10.1073/pnas.1712064115

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Single-cell analysis resolves melanoma resistance
Yapeng Su, Wei Wei, Lidia Robert, Min Xue, Jennifer Tsoi, Angel Garcia-Diaz, Blanca Homet Moreno, Jungwoo Kim, Rachel H. Ng, Jihoon W. Lee, Richard C. Koya, Begonya Comin-Anduix, Thomas G. Graeber, Antoni Ribas, James R. Heath
Proceedings of the National Academy of Sciences Dec 2017, 114 (52) 13679-13684; DOI: 10.1073/pnas.1712064115
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