Forecasting tumor evolution: can the past reveal the future?

预测肿瘤进化：过去能否揭示未来？

基本信息

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
项目类别：
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

项目摘要

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）背后的驱动力然而，在治疗和预防这些疾病方面投入的努力有限。至关重要的是，预测肿瘤进化的能力取决于相对贡献。尽管对人类肿瘤进化的直接观察是确定性和随机过程的。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出乎意料的是，我们最近发现转化后，一些肿瘤在体内生长。缺乏严格的选择，与有效的中性进化相兼容，这导致了我们对a的描述。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这种新模型与事实上的模型形成鲜明对比。连续克隆扩增模型，并表明肿瘤起始事件是必要且充分的此外，这些发现提出了最早的可能性。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，我们严格测试了这部小说。我们假设早期肿瘤进化是确定性的，并试图定义其偶然性。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强的功能决定因素。追踪策略能够直接测量人类细胞的进化参数，同时呈现同时，我们将推断肿瘤进展过程中的综合基因型到表型图谱。转移扩散并评估转移表型是否通过早期指定这种系统生物学方法将对患者基因组数据进行计算和数学建模。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

期刊论文数量（6）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

PhyloVelo enhances transcriptomic velocity field mapping using monotonically expressed genes.

PhyloVelo 使用单调表达的基因增强转录组速度场图谱。

DOI：
10.1038/s41587-023-01887-5
发表时间：
2023-07-31
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
通讯作者：
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：
发表时间：
2023-03-16
期刊：
影响因子：
0
作者：
Houlahan, Kathleen E;Khan, Aziz;Greenwald, Noah F;West, Robert B;Angelo, Michael;Curtis, Christina
通讯作者：
Curtis, Christina

Dynamics of breast-cancer relapse reveal late-recurring ER-positive genomic subgroups.

乳腺癌复发的动态揭示了晚期复发的 ER 阳性基因组亚群。

DOI：
发表时间：
2019
期刊：
影响因子：
64.8
作者：
Rueda, Oscar M;Sammut, Stephen;Seoane, Jose A;Chin, Suet;Caswell;Callari, Maurizio;Batra, Rajbir;Pereira, Bernard;Bruna, Alejandra;Ali, H Raza;Provenzano, Elena;Liu, Bin;Parisien, Michelle;Gillett, Cheryl;McKinney
通讯作者：
McKinney

A microwell platform for high-throughput longitudinal phenotyping and selective retrieval of organoids.

用于高通量纵向表型分析和选择性检索类器官的微孔平台。

DOI：
发表时间：
2023-09-20
期刊：
影响因子：
9.3
作者：
Sockell, Alexandra;Wong, Wing;Longwell, Scott;Vu, Thy;Karlsson, Kasper;Mokhtari, Daniel;Schaepe, Julia;Lo, Yuan;Cornelius, Vincent;Kuo, Calvin;Van Valen, David;Curtis, Christina;Fordyce, Polly M
通讯作者：
Fordyce, Polly M

Looking backward in time to define the chronology of metastasis.

回顾过去来定义转移的时间顺序。