Durrett Rick, Foo Jasmine, Leder Kevin, Mayberry John, Michor Franziska
Department of Mathematics, Cornell University, Ithaca, NY 14853, United States.
Theor Popul Biol. 2010 Aug;78(1):54-66. doi: 10.1016/j.tpb.2010.05.001. Epub 2010 May 19.
Most human tumors result from the accumulation of multiple genetic and epigenetic alterations in a single cell. Mutations that confer a fitness advantage to the cell are known as driver mutations and are causally related to tumorigenesis. Other mutations, however, do not change the phenotype of the cell or even decrease cellular fitness. While much experimental effort is being devoted to the identification of the functional effects of individual mutations, mathematical modeling of tumor progression generally considers constant fitness increments as mutations are accumulated. In this paper we study a mathematical model of tumor progression with random fitness increments. We analyze a multi-type branching process in which cells accumulate mutations whose fitness effects are chosen from a distribution. We determine the effect of the fitness distribution on the growth kinetics of the tumor. This work contributes to a quantitative understanding of the accumulation of mutations leading to cancer.
大多数人类肿瘤源于单个细胞中多种基因和表观遗传改变的积累。赋予细胞适应性优势的突变被称为驱动突变，与肿瘤发生存在因果关系。然而，其他突变并不会改变细胞的表型，甚至会降低细胞适应性。虽然目前有大量实验致力于确定单个突变的功能效应，但肿瘤进展的数学模型通常认为随着突变的积累，适应性会持续增加。在本文中，我们研究了具有随机适应性增加的肿瘤进展数学模型。我们分析了一个多类型分支过程，其中细胞积累的突变其适应性效应是从一个分布中选取的。我们确定了适应性分布对肿瘤生长动力学的影响。这项工作有助于对导致癌症的突变积累进行定量理解。
