Speaker
Description
Mathematical modelling of cancer has a long history but it traditionally focused on replicating growth laws observed for different tumours, the role of angiogenesis, or predicting the outcome of chemotherapy. Recently, advances in genomics have made it possible to investigate Darwinian evolution in populations of cancer cells. This has opened up many
interesting questions. In particular, as the cancerous tumour grows, cells accumulate further mutations. Are these mutations neutral “passengers” (i.e. they do not change the net growth rate) or are some of them “driver mutations” that increase the growth rate? Is there evidence of selection
acting on certain traits of cancer cells? How genetically diverse a typical tumour is? How is evolution affected by the spatial structure of the tumour?
In this talk I will show how computer models can be used to shed light on these questions. I will discuss models of increasing complexity: well-mixed, 3d lattice-based, and 3d off-lattice models. I will show how different
processes: replication, death, migration, and mechanical interactions between cells in a tumour affect its structure and genetic composition. I will also discuss how different models compare to experimental data, and implications for cancer therapy.
