Evading resistance: measuring melanoma's adaptation rate in different drug environments to identify the best course of treatment

While specific resistance mechanisms to targeted inhibitors in BRAF-mutant cutaneous melanoma have been identified, surprisingly little is known about the rate at which resistance develops under different treatment options. There is increasing evidence that resistance arises from pre-existing clones rather than from de novo mutations, but there remains the need for a better understanding of how different drugs affect the fitness of clones within a tumor population and promote or delay the emergence of resistance. To this end, we have developed an assay that defines the in vitro rate of adaptation by analyzing the progressive change in sensitivity of a melanoma cell line to different treatments. We performed a proof-of-theory experiment based on the hypothesis that drugs that cause cell death (cytotoxic) impose a higher selection pressure for drug-resistant clones than drugs that cause cell-cycle arrest (cytostatic drugs), thereby resulting in a faster rate of adaptation. We tested this hypothesis by continuously treating the BRAFV600E melanoma cell line A375 with the cytotoxic MEK inhibitor E6201 and the cytostatic MEK inhibitor trametinib, both of which are known to be effective in the setting of constitutive oncogenic signaling driven by the BRAF mutation. While the identification of confounding factors prevented the direct comparison between E6201-treated and trametinib-treated cells, we observed that E6201-treated cells demonstrate decreased drug sensitivity compared to vehicle-treated cells as early as 18 days after treatment begins. We were able to quantify this rate of divergence at 2.6% per passage by measuring the increase over time in average viability difference between drug-treated and vehicle-treated cells within a DDR analysis. We argue that this value correlates to the rate of adaptation. Furthermore, this study includes efforts to establish a barcoded cell line to allow for individual clonal tracking and efforts to identify synergistic and antagonist drug combinations for use in future experiments. Ultimately, we describe here a novel system capable of quantifying adaptation rate in cancer cells undergoing treatment, and we anticipate that this assay will prove helpful in identifying treatment options that circumvent or delay resistance through future hypothesis-driven experiments.