Branching process models for cancer evolution: overview and an application to colorectal cancer initiation

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Zhang, Ruibo

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Abstract

We study a multi-type branching process model associated with a transitional network between types. In particular, we are interested in determining the waiting time to each type in the network, employing an approximation of the process by its large time limit. We first present a literature review of results on large time limits and classify the dynamics of branching processes by their mean value matrices. For the special case when the transitional network is a single pathway, we present two approaches regarding approximating the waiting time for each type. To apply our theory to a real world problem, we use a multi-type branching process to model the development of colorectal cancer from initially healthy tissue. The model incorporates a complex sequence of driver gene alterations, some of which result in immediate growth advantage, while others have initially neutral effects. We derive analytic estimates for the sizes of premalignant subpopulations, and use these results to compute the waiting time distributions of novel driver mutations.

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Thesis (Master's)--University of Washington, 2022

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