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Accumulation of driver and passenger mutations during tumor progression

机译:肿瘤进展过程中驾驶员和乘客突变的积累

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摘要

Major efforts to sequence cancer genomes are now occurring throughout the world. Though the emerging data from these studies are illuminating, their reconciliation with epidemiologic and clinical observations poses a major challenge. In the current study, we provide a mathematical model that begins to address this challenge. We model tumors as a discrete time branching process that starts with a single driver mutation and proceeds as each new driver mutation leads to a slightly increased rate of clonal expansion.Using the model, we observe tremendous variation in the rate of tumor development-providing an understanding of the heterogeneity in tumor sizes and development times that have been observed by epidemiologists and clinicians. Furthermore, the model provides a simple formula for the number of driver mutations as a function of the total number of mutations in the tumor. Finally, when applied to recent experimental data, the model allows us to calculate the actual selective advantage provided by typical somatic mutations in human tumors in situ. This selective advantage is surprisingly small-0.004 ± 0.0004-and has major implications for experimental cancer research.
机译:现在,全世界都在致力于测序癌症基因组。尽管来自这些研究的新兴数据具有启发性,但它们与流行病学和临床观察的协调仍是一个重大挑战。在当前的研究中,我们提供了一个数学模型来开始应对这一挑战。我们将肿瘤建模为一个离散的时间分支过程,该过程从单个驱动程序突变开始,并随着每个新的驱动程序突变导致克隆扩展速率略有增加而进行。使用该模型,我们观察到了肿瘤发展速率的巨大差异,从而提供了流行病学家和临床医生观察到的对肿瘤大小和发育时间异质性的了解。此外,该模型提供了一个简单的公式,可将驱动程序突变的数量作为肿瘤中突变总数的函数。最后,当应用于最新的实验数据时,该模型允许我们计算原位人类肿瘤中典型的体细胞突变所提供的实际选择优势。这种选择性优势出乎意料地小至0.004±0.0004,对实验性癌症研究具有重要意义。

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  • 作者单位

    Program for Evolutionary Dynamics, Harvard University, Cambridge, MA 02138 Department of Mathematics, Harvard University, Cambridge, MA 02138;

    rnProgram for Evolutionary Dynamics, Harvard University, Cambridge, MA 02138 School of Mathematics, University of Edinburgh, Edinburgh EH9-3JZ, United Kingdom;

    rnDepartment of Value and Decision Science, Tokyo Institute of Technology, Tokyo 152-8552, Japan;

    rnDepartment of Biomedical Engineering, Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD 21218;

    rnDepartment of Biomedical Engineering, Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD 21218;

    rnDepartment of Biostatistics, School of Public Health, University of Medicine and Dentistry of New Jersey, Piscataway, NJ 08854;

    rnDepartment of Biomedical Engineering, Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD 21218;

    rnLudwig Center for Cancer Genetics and Therapeutics, and Howard Hudges Medical Institute at Johns Hopkins Kimmel Cancer Center, Baltimore, MD 21231;

    rnLudwig Center for Cancer Genetics and Therapeutics, and Howard Hudges Medical Institute at Johns Hopkins Kimmel Cancer Center, Baltimore, MD 21231;

    rnProgram for Evolutionary Dynamics, Harvard University, Cambridge, MA 02138 Department of Mathematics, Harvard University, Cambridge, MA 02138 Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138;

  • 收录信息 美国《科学引文索引》(SCI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    genetics; mathematical biology;

    机译:遗传学数学生物学;

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