Forecasting tumor evolution: can the past reveal the future?

摘要 克隆进化是当前许多公共卫生问题背后的驱动力，如癌症和传染性疾病 疾病。然而，在治疗和预防这些疾病方面投入的努力有限。 进化论观点。关键的是，预测肿瘤演变的能力取决于相对贡献 确定性和随机性的过程。尽管对人类肿瘤进化的直接观察是 不切实际的是，肿瘤内细胞之间的体细胞变化模式忠实地报告了它们的过去 增殖史。出乎意料的是，我们最近发现，一些肿瘤在转化后，会在 缺乏严格的选择，与有效的中性进化相容。这导致我们描述了一个 肿瘤生长的新大爆炸模型，其中肿瘤生长为单个末端扩展，由 大量异质的、有效地同样适合的亚克隆。这一新模式与事实形成鲜明对比 序贯克隆扩增模型，并表明肿瘤启动事件既是必要的也是充分的 来传播随后的增长。此外，这些发现提出了一种诱人的可能性，即最早的 肿瘤生长过程中发生的事件塑造了其随后的进化轨迹。在这里，我们将严格测试这部小说 早期肿瘤进化是确定性的假设，并试图定义其偶然性。我们就这样表演 癌基因工程和野生型人类器官细胞条形码的克隆动力学研究 以及在体外肿瘤进化过程中适应性增强的功能决定因素。这一创新的谱系 跟踪策略使得能够直接测量人类细胞中的进化参数，同时呈现 在肿瘤进展过程中，全面的基因到表型的映射。同时，我们将推断出 转移扩散和评估转移表型是否早期明确通过 患者基因组数据的计算和数学建模。这种系统生物学的方法将 评估肿瘤演变对疾病预测模型发展的可预测性 并指导早期检测，从而降低与癌症相关的死亡率。 好了！ 好了！

Summary Clonal evolution is the driving force behind many current public health issues such as cancer and infectious disease. However, limited efforts have been invested in treating and preventing these conditions from an evolutionary perspective. Critically, the ability to forecast tumor evolution depends on the relative contribution of deterministic and stochastic processes. Although direct observations of human tumor evolution are impractical, patterns of somatic alterations amongst cells within a tumor faithfully report on their past proliferative history. Unexpectedly, we recently found that after transformation, some tumors grow in the absence of stringent selection, compatible with effectively neutral evolution. This led to our description of a novel Big Bang model of tumor growth where the tumor grows as a single terminal expansion populated by numerous heterogeneous—and effectively equally fit subclones. This new model contrasts with the de facto sequential clonal expansion model, and suggests that tumor-initiating events are both necessary and sufficient to propagate subsequent growth. Moreover, these findings raise the tantalizing possibility that the earliest events during tumor growth shape its subsequent evolutionary trajectory. Here we rigorously test the novel hypothesis that early tumor evolution is deterministic and seek to define its contingencies. We thus perform oncogene-engineering and cellular barcoding of wild-type human organoids to characterize clonal dynamics and the functional determinants of increased fitness during in vitro tumor evolution. This innovative lineage tracing strategy enables the direct measurement of evolutionary parameters in human cells, while rendering a comprehensive genotype to phenotype map during tumor progression. In parallel, we will infer the timing of metastatic dissemination and evaluate whether the metastatic phenotype is specified early through computational and mathematical modeling of patient genomic data. This systems biology approach will evaluate the predictability of tumor evolution towards the development of models to forecast disease progression and guide earlier detection, thereby reducing cancer related mortality. ! !