Extreme value statistics of mutation accumulation in renewing cell populations

被引:3
作者
Greulich, Philip [1 ,2 ]
Simons, Benjamin D. [3 ,4 ,5 ]
机构
[1] Univ Southampton, Math Sci, Southampton, Hants, England
[2] Univ Southampton, Inst Life Sci, Southampton, Hants, England
[3] Univ Cambridge, Cavendish Lab, Cambridge, England
[4] Univ Cambridge, Wellcome Trust CRUK Gurdon Inst, Cambridge, England
[5] Univ Cambridge, Cambridge Stem Cell Inst, Cambridge, England
基金
英国工程与自然科学研究理事会;
关键词
STEM-CELLS; CANCER; SELECTION; EVOLUTION; MODEL; WAVE;
D O I
10.1103/PhysRevE.98.050401
中图分类号
O35 [流体力学]; O53 [等离子体物理学];
学科分类号
070204 ; 080103 ; 080704 ;
摘要
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 we determine how the statistical distribution of maximum mutation numbers scales with age and cell population size.
引用
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页数:5
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