Dynamical modelling of somatic genomes (360G-Wellcome-209409_Z_17_Z)

<p>Cancers are complex and chaotic systems.&nbsp;It is becoming apparent that no two cells in a cancer are genetically identical or follow the same evolutionary trajectory.&nbsp;Chromosomal instability (CIN)&nbsp;is one way that cells generate this complexity and is&nbsp;a hallmark of all&nbsp;cancer and ageing. &nbsp;In cancer, it increases the level of variation available to cells and gives rise to intra-tumour&nbsp;genetic hetereogeneity, which makes the disease more agressive,&nbsp;drug tolerant, and harder to treat. We are still far from a complete understanding of how cells undergoing CIN evolve over time, in particular, we do not know how populations of cancer&nbsp;cells&nbsp;evolve and how selection acts to change these properties. Understanding&nbsp;this normal&nbsp;evolutionary behaviour will be key to separating&nbsp;the functional and non-functional aspects of&nbsp;intra-tumour heterogeneity. We will tackle this problem by understanding cancer as an emergent complex system, and use&nbsp;simple dynamic stochastic models to capture the essential biological&nbsp;features of the processes underlying CIN, including&nbsp;chromosome gain and loss, structural change, and genome doubling. We will&nbsp;use&nbsp;the vast amount of NGS data already available to fit these models using&nbsp;Bayesian inference and&nbsp;infer the evolutionary aspects of CIN in healthy and cancerous tissues.</p>

£1,273,968

28 Nov 2017