The idea of cancer as an evolutionary disease is well established. Cancer development is driven by mutation and selective forces, including the action of the immune system, interspecific competition and therapies. Different tumour types exhibit resistance to the immune system suggesting the investigation of different aspects of the tumoural microenvironment to better understand cancer.
The tumoural tissue is composed of different phenotypes, occurred from genetic and epigenetic mutations and fixed by Darwinian selection. Evolutionary niches, set up by the competition-coexistence of different cancer clones and by the action of the immune system, can shape tumour form. An analysis of the tumoural morphology can help to classify cancer types, suggesting a ways to increase the effectiveness of the medical treatments.
The aim of this talk is to present a hybrid mathematical model comprising of an agent based model for the tumour-immune interaction and a system of delay differential equations for the T-cell activation cycle. Different tumour microenvironments are shown to influence the morphological evolution of the tumoural tissue and the genetic instability leading to crucial mutations. Shapes are correlated to different evolutionary outcomes that can be altered by therapies. Further, different treatments induce modifications to the environment and then to the final outcomes. In particular, immunotherapy cycles and molecular target therapy are studied. Finally, a statistical analysis of the model is used to discuss the reliability and the reproducibility of the outcomes.