Nicholson Michael D, Antal Tibor
SUPA, School of Physics and Astronomy, University of Edinburgh, Edinburgh, EH9 3FD, UK.
School of Mathematics, University of Edinburgh, Edinburgh, EH9 3FD, UK.
Bull Math Biol. 2016 Nov;78(11):2243-2276. doi: 10.1007/s11538-016-0221-x. Epub 2016 Oct 20.
Deterministically growing (wild-type) populations which seed stochastically developing mutant clones have found an expanding number of applications from microbial populations to cancer. The special case of exponential wild-type population growth, usually termed the Luria-Delbrück or Lea-Coulson model, is often assumed but seldom realistic. In this article, we generalise this model to different types of wild-type population growth, with mutants evolving as a birth-death branching process. Our focus is on the size distribution of clones-that is the number of progeny of a founder mutant-which can be mapped to the total number of mutants. Exact expressions are derived for exponential, power-law and logistic population growth. Additionally, for a large class of population growth, we prove that the long-time limit of the clone size distribution has a general two-parameter form, whose tail decays as a power-law. Considering metastases in cancer as the mutant clones, upon analysing a data-set of their size distribution, we indeed find that a power-law tail is more likely than an exponential one.
确定性增长(野生型)群体中随机发展出突变克隆,这种情况在从微生物群体到癌症等领域有着越来越多的应用。指数型野生型群体增长的特殊情况,通常称为卢里亚 - 德尔布吕克或利 - 库尔森模型,虽常被假设但很少符合实际。在本文中,我们将此模型推广到不同类型的野生型群体增长情况,其中突变体作为生死分支过程演化。我们关注的是克隆的大小分布,即起始突变体的后代数量,它可映射到突变体的总数。我们推导出了指数型、幂律型和逻辑斯谛型群体增长的精确表达式。此外,对于一大类群体增长情况,我们证明克隆大小分布的长时间极限具有一般的双参数形式,其尾部以幂律形式衰减。将癌症中的转移瘤视为突变克隆,在分析其大小分布数据集时,我们确实发现幂律尾部比指数尾部更有可能出现。