Department of Medicine, Division of Oncology, Washington University School of Medicine, St. Louis, MO 63110, USA; The Genome Institute, Washington University School of Medicine, St. Louis, MO 63108, USA; Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Genetics, Washington University School of Medicine, St. Louis, MO 63108, USA.
Cancer Lett. 2013 Nov 1;340(2):212-9. doi: 10.1016/j.canlet.2012.12.028. Epub 2013 Jan 23.
The "clonal evolution" model of cancer emerged and "evolved" amid ongoing advances in technology, especially in recent years during which next generation sequencing instruments have provided ever higher resolution pictures of the genetic changes in cancer cells and heterogeneity in tumors. It has become increasingly clear that clonal evolution is not a single sequential process, but instead frequently involves simultaneous evolution of multiple subclones that co-exist because they are of similar fitness or are spatially separated. Co-evolution of subclones also occurs when they complement each other's survival advantages. Recent studies have also shown that clonal evolution is highly heterogeneous: different individual tumors of the same type may undergo very different paths of clonal evolution. New methodological advancements, including deep digital sequencing of a mixed tumor population, single cell sequencing, and the development of more sophisticated computational tools, will continue to shape and reshape the models of clonal evolution. In turn, these will provide both an improved framework for the understanding of cancer progression and a guide for treatment strategies aimed at the elimination of all, rather than just some, of the cancer cells within a patient.
癌症的“克隆进化”模型是在技术不断进步的背景下出现并“进化”的,尤其是近年来,下一代测序仪器为癌细胞的遗传变化和肿瘤异质性提供了越来越高的分辨率图像。越来越明显的是,克隆进化不是一个单一的顺序过程,而是经常涉及多个亚克隆的同时进化,这些亚克隆之所以共存,是因为它们具有相似的适应性,或者是空间上分离的。当亚克隆相互补充生存优势时,也会发生共同进化。最近的研究还表明,克隆进化具有高度的异质性:同一类型的不同个体肿瘤可能经历非常不同的克隆进化路径。新的方法学进展,包括混合肿瘤群体的深度数字测序、单细胞测序以及更复杂的计算工具的开发,将继续塑造和重塑克隆进化模型。反过来,这些将为理解癌症进展提供一个改进的框架,并为旨在消除患者体内所有(而不仅仅是部分)癌细胞的治疗策略提供指导。