Forecasting tumor evolution: can the past reveal the future?

预测肿瘤进化：过去能否揭示未来？

• 批准号: 10455013
• 负责人: Christina N Curtis
• 金额: $ 109.9万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-30 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10455013
• 关键词: 3-Dimensional; Bar Codes; Big Bang Cosmology; Cells; Clonal Evolution; Clonal Expansion; Communicable Diseases; Computer Models; Coupled; Disease Progression; Early Diagnosis; Engineering; Event; Evolution; Future; Genotype; Growth; Human; In Vitro; Malignant Neoplasms; Maps; Measurement; Modeling; Mutation; Oncogenes; Organoids; Patients; Pattern; Phenotype; Public Health; Recording of previous events; Reporting; Shapes; Specific qualifier value; Stochastic Processes; Systems Biology; Testing; Tumor stage; disorder control; driving force; fitness; genomic data; innovation; mathematical model; model development; mortality; novel; predictive modeling; prevent; tumor; tumor growth; tumor progression

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. ! !

概括 克隆进化是当前许多公共卫生问题（例如癌症和传染病）背后的驱动力 疾病。然而，在治疗和预防这些疾病方面投入的努力有限 进化论的观点。至关重要的是，预测肿瘤进化的能力取决于相对贡献 确定性过程和随机过程。尽管对人类肿瘤进化的直接观察 不切实际，肿瘤内细胞之间的体细胞改变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，转化后，一些肿瘤在 缺乏严格的选择，与有效的中性进化兼容。这导致我们描述了一个 新颖的肿瘤生长大爆炸模型，其中肿瘤生长为单个终端扩展，其中填充有 许多异质且有效地同样适合的亚克隆。这个新模型与事实形成鲜明对比 连续克隆扩增模型，并表明肿瘤起始事件是必要且充分的 以促进后续的生长。此外，这些发现提出了一种诱人的可能性，即最早的 肿瘤生长过程中的事件塑造了其随后的进化轨迹。下面我们对小说进行严格测试 假设早期肿瘤进化是确定性的，并试图定义其偶然性。我们因此执行 野生型人类类器官的癌基因工程和细胞条形码以表征克隆动态 以及体外肿瘤进化过程中适应性增加的功能决定因素。这个创新的血统 追踪策略能够直接测量人类细胞的进化参数，同时呈现 肿瘤进展过程中全面的基因型到表型图谱。同时，我们将推断时间 转移扩散并评估转移表型是否通过早期指定 患者基因组数据的计算和数学建模。这种系统生物学方法将 评估肿瘤进化的可预测性，以开发预测疾病的模型 进展并指导早期检测，从而降低癌症相关死亡率。 ！ ！

项目成果

PhyloVelo enhances transcriptomic velocity field mapping using monotonically expressed genes.

• DOI: 10.1038/s41587-023-01887-5
• 发表时间: 2023-07
• 期刊: Nature biotechnology
• 影响因子: 46.9
• 作者: Kun Wang;Liangzhen Hou;Xin Wang;Xiangwei Zhai;Zhaolian Lu;Zhike Zi;Weiwei Zhai;Xionglei He;C. Curtis;Danya Zhou;Zheng Hu

Germline-mediated immunoediting sculpts breast cancer subtypes and metastatic proclivity.

种系介导的免疫编辑塑造乳腺癌亚型和转移倾向。

• DOI: 10.1101/2023.03.15.532870
• 发表时间: 2023
• 期刊: bioRxiv : the preprint server for biology
• 作者: Houlahan,KathleenE;Khan,Aziz;Greenwald,NoahF;West,RobertB;Angelo,Michael;Curtis,Christina
• 通讯作者: Curtis,Christina