Identifying and characterising the impact of excitability in a mathematical model of tumour-immune interactions. (21st September 2020) - Osojnik, Ana; Gaffney, Eamonn A.; Davies, Michael; Yates, James W.T.; Byrne, Helen M.
Highlights: New study of classical tumour-immune interactions model by Kuznetsov et al. (1994). By exploiting a separation of timescales, a new asymptotic model is derived. The reduced long-timescale model is excitable and has a rich bifurcation structure. Heterogeneous outcomes, consistent with immunoediting, are observed. Parameter sensitivity analysis used to compare tumour responses to immunotherapy. Abstract: We study a five-compartment mathematical model originally proposed by Kuznetsov et al. (1994) to investigate the effect of nonlinear interactions between tumour and immune cells in the tumour microenvironment, whereby immune cells may induce tumour cell death, and tumour cells may inactivate immune cells. Exploiting a separation of timescales in the model, we use the method of matched asymptotics to derive a new two-dimensional, long-timescale, approximation of the full model, which differs from the quasi-steady-state approximation introduced by Kuznetsov et al. (1994), but is validated against numerical solutions of the full model. Through a phase-plane analysis, we show that our reduced model is excitable, a feature not traditionally associated with tumour-immune dynamics. Through a systematic parameter sensitivity analysis, we demonstrate that excitability generates complex bifurcating dynamics in the model. These are consistent with a variety of clinically observed phenomena, and suggest that excitability may underpin tumour-immune interactions. The model exhibits the three stages of immunoediting – elimination, equilibrium, and escape, via stable steady states with different tumour cell concentrations. Such heterogeneity in tumour cell numbers can stem from variability in initial conditions and/or model parameters that control the properties of the immune system and its response to the tumour. We identify different biophysical parameter targets that could be manipulated with immunotherapy in order to control tumour size, and we find that preferred strategies may differ between patients depending on the strength of their immune systems, as determined by patient-specific values of associated model parameters.