On measuring selection in cancer from subclonal mutation frequencies
On measuring selection in cancer from subclonal mutation frequencies
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DOI：
10.1371/journal.pcbi.1007368
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发表时间：
2019-09-01
影响因子：
4.3
通讯作者：
Waclaw, Bartlomiej
中科院分区：
文献类型：
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作者：
Bozic, Ivana;Paterson, Chay;Waclaw, Bartlomiej
最近可用的癌症测序数据揭示了包含多种突变的癌症基因组的复杂视图，包括负责癌症进展的驱动程序和中性乘客。测量癌症的选择性，区分驾驶员和乘客，对开发新的治疗策略具有重要意义。最近有人认为，三分之一的癌症是中性进化的，因为它们的突变频谱遵循1/f幂律，这是在特定的中频范围内从中性进化中预期的。我们研究了癌症演变的随机模型，并推导出亚克隆驱动程序的癌细胞频率的概率分布公式，表明驱动程序频率偏向0和1。我们发现，很难在中间频率捕获驱动突变，因此由于缺乏这种驱动突变而导致的中性呼叫将显著高估中性进化肿瘤的数量。我们的方法在所有相关参数值的整个范围内提供了1/f统计量有效性的精确量化。我们还表明，我们的结论仍然适用于非指数模型：空间三维模型和S形生长，相关的早期和晚期阶段的癌症生长。
Recently available cancer sequencing data have revealed a complex view of the cancer genome containing a multitude of mutations, including drivers responsible for cancer progression and neutral passengers. Measuring selection in cancer and distinguishing drivers from passengers have important implications for development of novel treatment strategies. It has recently been argued that a third of cancers are evolving neutrally, as their mutational frequency spectrum follows a 1/f power law expected from neutral evolution in a particular intermediate frequency range. We study a stochastic model of cancer evolution and derive a formula for the probability distribution of the cancer cell frequency of a subclonal driver, demonstrating that driver frequency is biased towards 0 and 1. We show that it is difficult to capture a driver mutation at an intermediate frequency, and thus the calling of neutrality due to a lack of such driver will significantly overestimate the number of neutrally evolving tumors. Our approach provides precise quantification of the validity of the 1/f statistic across the entire range of all relevant parameter values. We also show that our conclusions remain valid for non-exponential models: spatial 3d model and sigmoidal growth, relevant for early- and late stages of cancer growth.