Speaker
Description
Melanoma is an aggressive skin cancer driven by a phenotypically heterogeneous cell population. While a full mechanistic understanding is currently lacking, the leading micropthalmia-associated transcription factor (MITF) rheostat theory asserts that the downstream activity of MITF regulates transitions between differentiated, proliferative and invasive states. The population dynamics implied by the MITF rheostat and the conditions for which these dynamics are consistent with published data are currently unknown. To address this, we have developed a phenotype-structured model for melanoma cell populations in vivo. In this talk, I first introduce a subcellular SDE system that illustrates how stochastic fluctuations in MITF RNA and protein concentrations propagate to a downstream phenotype variable. By exploiting a timescale separation, we reduce the coupled SDEs to an effective phenotype flux that informs the full structured population model. Numerical solutions indicate that the model population transitions from a balanced exponential growth phase with mainly differentiated and proliferative cells to either a steady state or limit cycle. Both long-term behaviours exhibit a substantial proportion of invasive cells. Parameter value calibration via Bayesian inference indicates that the "window" of proliferative phenotypes must be small for consistency with data. Together, these results clarify the role of MITF in shaping the phenotype heterogeneity of melanoma cell populations.
