Analyses of ancient dog DNA suggest that dogs were likely domesticated from Eurasian wolves around 23,000 years ago, possibly in Siberia.
Image credit: Pixabay/Chiemsee2016.
Edited by Herbert Levine, Rice University, Houston, TX, and approved November 14, 2017 (received for review July 6, 2017)
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.
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.
Single-cell analysis resolves melanoma resistance
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