先进测序技术 (AST) 彻底改变了作为罕见事件的癌症驱动突变 (CDM) 的定量，这在临床肿瘤学、癌症研究和癌症风险评估中具有实用性。本综述重点关注使用 AST 来表征携带 CDM 的细胞克隆扩增 (CE) 的研究，并阐明形成 CE 的选择压力。重要的是，高灵敏度 AST 使得在组织学正常组织样本中表征突变克隆和 CE 成为可能，从而提供了研究新生肿瘤发展的手段。一些 AST 可以在空间定义的环境中识别突变克隆；其他的能够将突变数据与基因表达分析相结合，从而详细阐述免疫、炎症、代谢和/或基质微环境对 CE 的影响。总的来说，这些研究清楚地表明，组织学正常组织中惊人的大部分细胞携带 CDM，CDM 可能赋予导致 CE 的特定环境选择优势，而只有一小部分携带 CDM 的细胞最终导致肿瘤形成。这些观察结果与有关克隆选择机制的现有文献相结合，以解释如何将 CDM 和 CE 的测量值解释为癌症风险的生物标志物。考虑到致癌的随机性、驱动突变的潜在功能潜伏期、潜在突变和微环境相互作用的复杂性，以及其他类型的遗传和表观遗传变化的参与，得出的结论是，基于 CDM 的测量应该被视为概率性的，而不是概率性的。确定性生物标志物。 CDM 水平样本间变异性的增加（CE 的结果）可能被解释为偏离正常组织稳态，并表明未来癌症风险增加，这一过程可能反映正常衰老或致癌物质暴露。因此，对 CDM 水平变异性的分析有可能支持现有的致癌性测试方法。由 Elsevier B.V. 出版。

Advanced sequencing technologies (ASTs) have revolutionized the quantitation of cancer driver mutations (CDMs) as rare events, which has utility in clinical oncology, cancer research, and cancer risk assessment. This review focuses on studies that have used ASTs to characterize clonal expansion (CE) of cells carrying CDMs and to explicate the selective pressures that shape CE. Importantly, high-sensitivity ASTs have made possible the characterization of mutant clones and CE in histologically normal tissue samples, providing the means to investigate nascent tumor development. Some ASTs can identify mutant clones in a spatially defined context; others enable integration of mutant data with analyses of gene expression, thereby elaborating immune, inflammatory, metabolic, and/or stromal microenvironmental impacts on CE. As a whole, these studies make it clear that a startlingly large fraction of cells in histologically normal tissues carry CDMs, CDMs may confer a context-specific selective advantage leading to CE, and only a small fraction of cells carrying CDMs eventually result in neoplasia. These observations were integrated with available literature regarding the mechanisms underlying clonal selection to interpret how measurements of CDMs and CE can be interpreted as biomarkers of cancer risk. Given the stochastic nature of carcinogenesis, the potential functional latency of driver mutations, the complexity of potential mutational and microenvironmental interactions, and involvement of other types of genetic and epigenetic changes, it is concluded that CDM-based measurements should be viewed as probabilistic rather than deterministic biomarkers. Increasing inter-sample variability in CDM levels (as a consequence of CE) may be interpretable as a shift away from normal tissue homeostasis and an indication of increased future cancer risk, a process that may reflect normal aging or carcinogen exposure. Consequently, analyses of variability in levels of CDMs have the potential to bolster existing approaches for carcinogenicity testing.Published by Elsevier B.V.