Accelerating technological advances have allowed the widespread genomic profiling of tumors. As yet, however, the vast catalogues of mutations that have been identified have made only a modest impact on clinical medicine. Massively parallel sequencing has informed our understanding of the genetic evolution and heterogeneity of cancers, allowing us to place these mutational catalogues into a meaningful context. Here, we review the methods used to measure tumor evolution and heterogeneity, and the potential and challenges for translating the insights gained to achieve clinical impact for cancer therapy, monitoring, early detection, risk stratification, and prevention. We discuss how tumor evolution can guide cancer therapy by targeting clonal and subclonal mutations both individually and in combination. Circulating tumor DNA and circulating tumor cells can be leveraged for monitoring the efficacy of therapy and for tracking the emergence of resistant subclones. The evolutionary history of tumors can be deduced for late-stage cancers, either directly by sampling precursor lesions or by leveraging computational approaches to infer the timing of driver events. This approach can identify recurrent early driver mutations that represent promising avenues for future early detection strategies. Emerging evidence suggests that mutational processes and complex clonal dynamics are active even in normal development and aging. This will make discriminating developing malignant neoplasms from normal aging cell lineages a challenge. Furthermore, insight into signatures of mutational processes that are active early in tumor evolution may allow the development of cancer-prevention approaches. Research and clinical studies that incorporate an appreciation of the complex evolutionary patterns in tumors will not only produce more meaningful genomic data, but also better exploit the vulnerabilities of cancer, resulting in improved treatment outcomes.

中文翻译：

---

将对肿瘤进化的见解转化为临床实践：承诺和挑战。

加速的技术进步已经允许对肿瘤进行广泛的基因组分析。然而，迄今为止，已确定的大量突变目录对临床医学的影响不大。大规模平行测序让我们了解了癌症的遗传进化和异质性，使我们能够将这些突变目录置于有意义的背景中。在这里，我们回顾了用于测量肿瘤进化和异质性的方法，以及转化所获得的见解以实现对癌症治疗、监测、早期检测、风险分层和预防的临床影响的潜力和挑战。我们讨论了肿瘤进化如何通过单独和联合靶向克隆和亚克隆突变来指导癌症治疗。循环肿瘤 DNA 和循环肿瘤细胞可用于监测治疗效果和跟踪耐药亚克隆的出现。对于晚期癌症，可以直接通过采样前体病变或通过利用计算方法推断驱动事件的时间来推断肿瘤的进化历史。这种方法可以识别复发的早期驱动突变，这些突变代表了未来早期检测策略的有希望的途径。新出现的证据表明，即使在正常发育和衰老过程中，突变过程和复杂的克隆动力学也很活跃。这将使从正常衰老细胞谱系中区分发展中的恶性肿瘤成为一项挑战。此外，深入了解在肿瘤进化早期活跃的突变过程的特征可能有助于开发癌症预防方法。纳入对肿瘤复杂进化模式的评价的研究和临床研究不仅会产生更有意义的基因组数据，而且会更好地利用癌症的脆弱性，从而改善治疗结果。