Extreme value statistics of mutation accumulation in renewing cell populations
Extreme value statistics of mutation accumulation in renewing cell populations
The emergence of a predominant phenotype within a cell population is often triggered by the chance accumulation of a sequence of rare genomic DNA mutations within a single cell. For example, tumors may be initiated by a single cell in which multiple mutations cooperate to bypass their natural defense mechanism. The risk of such an event is thus determined by the extremal accumulation of mutations across tissue cells. To address this risk, here we study the statistics of the maximum mutation numbers in a generic, but tested, model of a renewing cell population. By drawing an analogy between the genealogy of a cell population and the theory of branching random walks, we obtain analytical estimates for the probability of exceeding a threshold number of mutations to trigger a proliferative advantage of a cell over its neighbors, and determine how the statistical distribution of maximum mutation numbers scales with age and cell population size.
Greulich, Philip
65da32ad-a73a-435a-86e0-e171437430a9
Simons, Benjamin D.
02e0ea52-9b7f-4b80-a856-a22cc1991ba3
16 November 2018
Greulich, Philip
65da32ad-a73a-435a-86e0-e171437430a9
Simons, Benjamin D.
02e0ea52-9b7f-4b80-a856-a22cc1991ba3
Greulich, Philip and Simons, Benjamin D.
(2018)
Extreme value statistics of mutation accumulation in renewing cell populations.
Physical Review E, 98 (5), [050401(R)].
(doi:10.1103/PhysRevE.98.050401).
Abstract
The emergence of a predominant phenotype within a cell population is often triggered by the chance accumulation of a sequence of rare genomic DNA mutations within a single cell. For example, tumors may be initiated by a single cell in which multiple mutations cooperate to bypass their natural defense mechanism. The risk of such an event is thus determined by the extremal accumulation of mutations across tissue cells. To address this risk, here we study the statistics of the maximum mutation numbers in a generic, but tested, model of a renewing cell population. By drawing an analogy between the genealogy of a cell population and the theory of branching random walks, we obtain analytical estimates for the probability of exceeding a threshold number of mutations to trigger a proliferative advantage of a cell over its neighbors, and determine how the statistical distribution of maximum mutation numbers scales with age and cell population size.
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Accepted/In Press date: 2 October 2018
e-pub ahead of print date: 16 November 2018
Published date: 16 November 2018
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Accepted as Physical Review E: Rapid Communication
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Local EPrints ID: 414967
URI: http://eprints.soton.ac.uk/id/eprint/414967
ISSN: 1539-3755
PURE UUID: 07b7db5c-49eb-4242-96a5-33c723a966e4
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Date deposited: 18 Oct 2017 16:30
Last modified: 16 Mar 2024 04:17
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Benjamin D. Simons
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