Cancers progress through the accumulation of somatic mutations which accrue during tumour evolution, allowing some cells to proliferate in an uncontrolled fashion. This growth process is intimately related to latent evolutionary forces moulding the genetic and epigenetic composition of tumour subpopulations. Understanding cancer requires therefore the understanding of these selective pressures. The adoption of widespread next-generation sequencing technologies opens up for the possibility of measuring molecular profiles of cancers at multiple resolutions, across one or multiple patients. In this review we discuss how cancer genome sequencing data from a single tumour can be used to understand these evolutionary forces, overviewing mathematical models and inferential methods adopted in field of Cancer Evolution.

中文翻译：

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通过基因组测序测量进化癌症的动力学，一次一名患者

癌症通过在肿瘤进化过程中累积的体细胞突变的积累而进展，从而使某些细胞以不受控制的方式增殖。这种生长过程与潜在的进化力密切相关，这些潜在的进化力塑造了肿瘤亚群的遗传和表观遗传组成。因此，了解癌症需要了解这些选择性压力。广泛采用的下一代测序技术为在一个或多个患者中以多种分辨率测量癌症分子谱的可能性开辟了道路。在这篇综述中，我们讨论了如何将单个肿瘤的癌症基因组测序数据用于理解这些进化力，并概述了癌症进化领域采用的数学模型和推论方法。