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PLoS Comput Biol. 2019 Apr 15;15(4):e1006866. doi: 10.1371/journal.pcbi.1006866. eCollection 2019 Apr.

Competing evolutionary paths in growing populations with applications to multidrug resistance.

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School of Physics and Astronomy, University of Edinburgh, Edinburgh, Scotland.
School of Mathematics, University of Edinburgh, Edinburgh, Scotland.


Investigating the emergence of a particular cell type is a recurring theme in models of growing cellular populations. The evolution of resistance to therapy is a classic example. Common questions are: when does the cell type first occur, and via which sequence of steps is it most likely to emerge? For growing populations, these questions can be formulated in a general framework of branching processes spreading through a graph from a root to a target vertex. Cells have a particular fitness value on each vertex and can transition along edges at specific rates. Vertices represent cell states, say genotypes or physical locations, while possible transitions are acquiring a mutation or cell migration. We focus on the setting where cells at the root vertex have the highest fitness and transition rates are small. Simple formulas are derived for the time to reach the target vertex and for the probability that it is reached along a given path in the graph. We demonstrate our results on several scenarios relevant to the emergence of drug resistance, including: the orderings of resistance-conferring mutations in bacteria and the impact of imperfect drug penetration in cancer.

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