BackgroundMelanoma is a heterogeneous tumour, but the impact of this heterogeneity upon therapeutic response is not well understood.MethodsSingle cell mRNA analysis was used to define the transcriptional heterogeneity of melanoma and its dynamic response to BRAF inhibitor therapy and treatment holidays. Discrete transcriptional states were defined in cell lines and melanoma patient specimens that predicted initial sensitivity to BRAF inhibition and the potential for effective re-challenge following resistance. A mathematical model was developed to maintain competition between the drug-sensitive and resistant states, which was validated in vivo.FindingsOur analyses showed melanoma cell lines and patient specimens to be composed of >3 transcriptionally distinct states. The cell state composition was dynamically regulated in response to BRAF inhibitor therapy and drug holidays. Transcriptional state composition predicted for therapy response. The differences in fitness between the different transcriptional states were leveraged to develop a mathematical model that optimized therapy schedules to retain the drug sensitive population. In vivo validation demonstrated that the personalized adaptive dosing schedules outperformed continuous or fixed intermittent BRAF inhibitor schedules.InterpretationOur study provides the first evidence that transcriptional heterogeneity at the single cell level predicts for initial BRAF inhibitor sensitivity. We further demonstrate that manipulating transcriptional heterogeneity through personalized adaptive therapy schedules can delay the time to resistance.FundingThis work was funded by the . The funder played no role in assembly of the manuscript.

Patients with BRAF V600E mutant melanoma are typically treated with targeted BRAF kinase inhibitors, such as vemurafenib and dabrafenib. Although these drugs are initially effective, they are not curative. Most of the focus to date has been upon genetic mechanisms of acquired resistance; therefore, we must better understand the global signaling adaptations that mediate escape from BRAF inhibition. In the current study, we have used activity-based protein profiling (ABPP) with ATP-analogue probes to enrich kinases and other enzyme classes that contribute to BRAF inhibitor (BRAFi) resistance in four paired isogenic BRAFi-naïve/resistant cell line models. Our analysis showed these cell line models, which differ in their PTEN status, have considerable heterogeneity in their kinase ATP probe uptake in comparing naïve cells and adaptations to chronic drug exposure. A number of kinases including FAK1, SLK and TAOK2 had increased ATP probe uptake in BRAFi resistant cells, while KHS1 (M4K5) and BRAF had decreased ATP probe uptake in the BRAFi-resistant cells. Gene ontology (GO) enrichment analysis revealed BRAFi resistance is associated with a significant enhancement in ATP probe uptake in proteins implicated in cytoskeletal organization and adhesion, and decreases in ATP probe uptake in proteins associated with cell metabolic processes. The ABPP approach was able to identify key phenotypic mediators critical for each BRAFi resistant cell line. Together, these data show that common phenotypic adaptations to BRAF inhibition can be mediated through very different signaling networks, suggesting considerable redundancy within the signaling of BRAF mutant melanoma cells.

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