Quantifying replication dynamics to predict clonal evolution and drug sensitivity in cancer cells using single-cell whole genome sequencing

使用单细胞全基因组测序量化复制动态以预测癌细胞的克隆进化和药物敏感性

• 批准号: 10603140
• 负责人: Adam Clayton Weiner
• 金额: $ 4.77万
• 依托单位: WEILL MEDICAL COLL OF CORNELL UNIV
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-02-24 至 2026-02-23
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10603140
• 关键词: Address; BRCA1 gene; BRCA2 gene; Basic Science; Bayesian Modeling; Biological Markers; Cell Count; Cell Cycle; Cell Line; Cells; Clinical; Clinical Management; Clonal Evolution; Computing Methodologies; DNA; DNA Damage; DNA Repair; DNA biosynthesis; DNA replication fork; Data; Data Set; Development; Drug resistance; Ensure; Evolution; Exposure to; Fire - disasters; Genes; Genetic; Genome; Genomic Instability; Genomics; Goals; Grant; Heritability; Heterogeneity; Libraries; Literature; Malignant Neoplasms; Malignant neoplasm of ovary; Measures; Methods; Modeling; Mutation; Neoplasm Metastasis; Parents; Pathologist; Patients; Pattern; Phenotype; Phylogenetic Analysis; Platinum; Positioning Attribute; Preparation; Process; Proliferating; Property; Proxy; Research Personnel; Resolution; Role; S phase; S-Phase Fraction; Sampling; Series; Somatic Mutation; Stress; TP53 gene; Technology; Testing; Time; Work; cancer cell; cancer therapy; cell type; chemotherapy; computer framework; daughter cell; drug development; drug sensitivity; fitness; genetically modified cells; genome sequencing; improved; inhibitor; insight; malignant breast neoplasm; next generation; patient derived xenograft model; patient stratification; prospective; replication stress; response; stressor; targeted treatment; therapeutic development; treatment response; tumor; tumor heterogeneity; whole genome

Project Summary Recent developments in single-cell whole genome sequencing (scWGS) such as direct library preparation (DLP) have enabled rich interrogation into the genomic diversity of hard-to-treat breast and ovarian cancers. Studies from the Shah Lab have used DLP to infer clonal fitness from time-series sampling and assess the impact of mutational processes on structural genomic plasticity; however, these studies only looked at genomes from non-replicating cells. The proposed project leverages S-phase cells captured by DLP to prospectively predict clonal fitness and chemosensitivity using data from a single time point (Aim 1) and, separately, to measure the contribution of aberrant replication towards the accumulation of copy number aberrations (CNAs) across cancers of various genetic context (Aim 2). For my first aim, I propose a computational framework for assigning S-phase cells to phylogenetically inferred clones and subsequently calculating the S-phase fraction (SPF) within each clone. For my second aim, I propose a Bayesian model to estimate single-cell replication timing in a manner that is robust to somatic CNAs. I hypothesize that SPF will be a proxy for proliferation rate and thus high SPF clones will have higher treatment-naïve fitness and sensitivity to platinum-based chemotherapy than their low SPF counterparts. I further hypothesize that heterogeneous replication timing will correlate with the extent of replication stress in a particular DLP sample. Investigating both hypotheses will be important for extending the clinical utility of DLP since identifying which clones will respond to chemotherapy will help guide clinical management and identifying the presence of replication stress will help stratify patients for next-generation targeted therapies, such as ATR inhibitors, that selectively kill cancer cells undergoing replication stress. In summary, the proposed computational methods will extend the utility of scWGS technologies which capture replicating cells by connecting replication dynamics to clonal fitness, replication stress, CNA patterns, and drug sensitivities in genomically unstable cancers.

项目摘要 单细胞全基因组测序（SCWG）的最新发展，例如直接库制备 （DLP）使乳腺癌和卵巢癌的基因组多样性有丰富的质疑。 SHAH实验室的研究使用DLP来推断时间序列抽样和评估的克隆适应性 突变过程对结构基因组可塑性的影响；但是，这些研究只看了 来自非复制细胞的基因组。提出的项目利用DLP捕获的S期单元 前瞻性地预测利用来自单个时间点（AIM 1）的数据，并预测克隆的适应性和化学敏感性 分别衡量异常复制对拷贝数积累的贡献 各种遗传环境的癌症的畸变（CNA）（AIM 2）。为了我的第一个目标，我建议 用于将S相细胞分配给系统发育的克隆的计算框架，然后 计算每个克隆中的S相分数（SPF）。为了我的第二个目标，我提出了一个贝叶斯模型 以适合体细胞CNA的方式估算单细胞复制时间。我假设SPF会 成为增殖率的代理，因此，高SPF克隆将具有更高的治疗能力，并且 对基于铂的化学疗法的敏感性比其低SPF对应物的敏感性。我进一步假设 异质复制时机将与特定DLP样本中的复制应力程度相关。 研究这两个假设对于扩展DLP的临床实用性至关重要，因为 克隆将对化学疗法做出反应，将有助于指导临床管理并确定 复制应力将有助于对患者进行下一代靶向疗法（例如ATR抑制剂）的分层，以便将患者分层 有选择地杀死接受复制应力的癌细胞。总之，提出的计算方法 将扩展SCWGS技术的效用，该技术通过连接复制动力学来捕获复制单元格 克隆适应性，复制应力，CNA模式和药物敏感性在基因组上不稳定的癌症中。