Hypoxia-related radiotherapy resistance in tumors: treatment efficacy investigation in an eco-evolutionary perspective - Chiari, Giulia; Fiandaca, Giada; Delitala, Marcello Edoardo (Frontiers in Applied Mathematics and Statistics, 2023)
In the study of therapeutic strategies for the treatment of cancer, eco-evolutionary dynamics are of particular interest, since characteristics of the tumour population, interaction with the environment and effects of the treatment, influence the geometric and epigenetic characterization of the tumour with direct consequences on the efficacy of the therapy and possible relapses. In particular, when considering radiotherapy, oxygen concentration plays a central role both in determining the effectiveness of the treatment and the selective pressure due to hypoxia. We propose a mathematical model, settled in the framework of epigenetically-structured population dynamics and formulated in terms of systems of coupled non-linear integro-differential equations, that aims to catch these phenomena and to provide a predictive tool for the tumour mass evolution and therapeutic effects. The outcomes of the simulations show how the model is able to explain the impact of environmental selection and therapies on the evolution of the mass, motivating observed dynamics such as relapses and therapeutic failures. Furthermore it offers a first hint for the development of therapies which can be adapted to overcome problems of resistance and relapses.