Modelling the spatial dynamics of oncolytic virotherapy in the presence of virus-resistant tumour cells

Author summary Oncolytic virotherapy is a promising form of cancer treatment that uses viruses to target, infect and kill cancer cells. Unfortunately, this form of therapy is often not effective, due to the occurrence of virus-resistant tumor cells. As it is challenging to assess the emergence and spread of resistance experimentally or in (pre)clinical studies, we designed a model that allows to study the spatial dynamics of virus-sensitive and virus-resistant tumor cells in various scenarios, and to predict the efficacy of virotherapy. By analysing the model systematically, we demonstrate the importance of 2D and 3D spatial interactions, the effects of viral properties (such as replication rate and range of infection), the properties of virus-resistant cancer cells (such as the cost of resistance), and the sensitivity of healthy (non-tumor) cells towards viral infection. Our goal is to provide a sound conceptual understanding of the mechanisms underlying therapeutic failure, which eventually may lead to the discovery of strategies that improve therapeutic efficacy. We therefore provide the reader with a graphical and a terminal interface of our model (executable on a local computer), allowing practitioners to reflect on their intuition regarding the complex yet fascinating dynamics of oncolytic virotherapy.