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Published December 26, 2017 | Supplemental Material + Published
Journal Article Open

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

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 BRAF^(V600)-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.

Additional Information

© 2017 National Academy of Sciences. Published under the PNAS license. Edited by Herbert Levine, Rice University, Houston, TX, and approved November 14, 2017 (received for review July 6, 2017). Published online before print December 11, 2017. We acknowledge the following agencies and foundations for support: NIH Grants U54 CA199090 (to J.R.H., W.W., and A.R.), P01 CA168585 (to T.G.G. and A.R.), and R35 CA197633 (to A.R.); the Dr. Robert Vigen Memorial Fund, the Garcia-Corsini Family Fund, the Ressler Family Fund, and the Grimaldi Family Fund (A.R.); the Jean Perkins Foundation (J.R.H.); University of California, Los Angeles, Broad Stem Cell Research Center Seed Fund for Small Cell Cancer Pilot Studies, and the Phelps Family Foundation (W.W.); and ACS Research Scholar Award (RSG-12-257-01-TBE), MRA Established Investigator Award (20120279), and University of California, Los Angeles, Clinical and Translational Science Institute Grant UL1TR000124 (to T.G.G.). We acknowledge University of California, Los Angeles, Jonsson Comprehensive Cancer Center (JCCC) membership (NIH/NCI P30CA016042) for using the JCCC Flow Cytometry Core and Genomics Shared Resource. L.R. was supported by the V Foundation-Gil Nickel Family Endowed Fellowship and a scholarship from SEOM. J.T. was supported by NIH T32-CA009120. 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.

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Published - PNAS-2017-Su-13679-84.pdf

Supplemental Material - pnas.1712064115.sapp.pdf

Supplemental Material - pnas.1712064115.sd01.xlsx

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Additional details

Created:
August 21, 2023
Modified:
October 17, 2023