Characterizing the load of driver and passenger mutations in cancer

项目4：建模肿瘤进展和分析基因组数据，以表征驱动程序和 癌症的乘客突变。 癌症的发展可以被认为是一个生物体内部的进化过程。期间 当肿瘤进展时，细胞获得突变，竞争资源，并且是选择能力的对象。 在复杂多变的环境中快速成长。达尔文进化论的这些过程 用类似于统计力学中使用的方法系统地研究和数学建模 物理学的相关领域。作为体细胞微进化的结果， 多突变：一些对肿瘤进展至关重要的驱动突变，以及更多的乘客突变。 突变 群体遗传学的经典著作已经证明，突变的积累会导致 遗传负荷，即平均适应度的降低，并可能导致种群灭绝。我们的假设是 增加癌细胞群体中存在的突变的遗传负荷可以使群体 萎缩到灭绝，我们称之为克隆灭绝。这个想法可以为一个潜在的小说铺平道路 通过释放隐藏突变的有害影响的疗法来治疗癌症的方法。到 据我们所知，利用累积的突变将癌细胞群推向 灭绝还没有提出。我们建议通过一种独特的方法来测试这一假设， 发展肿瘤进化理论，分析新兴的大量癌症基因组学数据， 乘客突变及其对癌症发展影响的实验研究。实验将 复制了应用于癌细胞的鲁里亚-德尔布鲁克实验。我们的数据驱动理论方法是 植根于50年的进化遗传学思想的遗传负荷及其后果， 种群灭绝

Project 4: Modeling neoplastic progression and analyzing genomic data to characterize the load of driver and passenger mutations in cancer. The development ofcancer can be considered as an evolutionary process within an organism. During neoplastic progression, cells acquire mutations, compete for resources, and are subject of selection for ability to grow fast in a complex and dynamic environment. These processes of Darwinian evolution have been systematically studied and modeled mathematically by methods similar to those used in Statistical Mechanics and related fields of Physics. As a result of somatic micro-evolution a population of cancer cells harbors multiple mutations: a few driver mutations essential for neoplastic progression, and many more passenger mutations. Classical works in population genetics have demonstrated that accumulation of mutations lead to increased genetic load, i.e. reduction in the mean fitness, and can lead to population extinction. Our hypothesis is that increasing the genetic load of mutations present in the population of cancer cells can make the population shrink to extinction, a process that we call clonal extinction. This idea can pave a way to a potentially novel approach to cancer treatment by therapeutics that unleash the deleterious effects of harbored mutations. To the best of our knowledge the idea of exploiting accumulated mutations to push a population of cancer cells into extinction has not been put forward. We propose to test this hypothesis by a unique approach that combines development of a theory of neoplastic evolution, analysis of emerging massive cancer genomics data, and experimental study of passenger mutation and their impact of cancer development. The experiment will reproduce seminal Luria-Delbruck experiment applied to cancer cell. Our data-driven theoretical approach is rooted in fifty years of evolutionary genetic thought about the genetic load and its consequences for population extinction.