生物
快照(计算机存储)
进化生物学
基因组不稳定性
进化动力学
肿瘤异质性
癌症的体细胞进化
癌症
基因组学
计算生物学
遗传异质性
表型
遗传学
基因
基因组
人口
计算机科学
DNA损伤
社会学
人口学
操作系统
DNA
作者
Samra Turajlic,Andrea Sottoriva,Trevor A. Graham,Charles Swanton
标识
DOI:10.1038/s41576-019-0114-6
摘要
To a large extent, cancer conforms to evolutionary rules defined by the rates at which clones mutate, adapt and grow. Next-generation sequencing has provided a snapshot of the genetic landscape of most cancer types, and cancer genomics approaches are driving new insights into cancer evolutionary patterns in time and space. In contrast to species evolution, cancer is a particular case owing to the vast size of tumour cell populations, chromosomal instability and its potential for phenotypic plasticity. Nevertheless, an evolutionary framework is a powerful aid to understand cancer progression and therapy failure. Indeed, such a framework could be applied to predict individual tumour behaviour and support treatment strategies. Recent next-generation sequencing studies have captured the spatial and temporal evolutionary patterns that shape cancer. This Review provides an overview of the theoretical models of tumour evolution and discusses what to consider when inferring evolutionary dynamics from genomic data.
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