Bay Area Cancer Target Discovery and Development

项目总结 我们的总体战略是利用我们开发的新工具和方法 在我们的头两个CTD^2资助期--更具体地说，开创和应用了CRISPR 有助于发现和表征新的癌症靶点及其调节剂的技术- 使用创新的高通量技术。我们的最终目标是发现 有可能消灭所有癌细胞的靶点，尽管它们具有克隆性和异质性 环境背景。这就要求我们更好地理解肿瘤的生物发生，即 驱动肿瘤发生的基因组合，以及使疗效复杂化的肿瘤异质性 治疗性治疗。 在这项建议中，我们建立了激动型系统，允许我们对基因和表型细胞进行量化 细胞培养和体内的异质性。总体目标是识别合成的基因组合。 对临床耐药是必要的，并与肿瘤内和肿瘤内的异质性有关。我们假设 改变细胞状态，如炎症表型和谱系可塑性，增加了治疗耐受性 和抵抗。我们应用单细胞方法和尖端的血统追踪工具来研究 致病细胞状态改变的起源和使用遗传筛选、计算和 药理学方法和临床相关的体外和体内肿瘤模型的鉴定 机械校准的、特定的治疗脆弱性。这些方法将应用于两个 癌症、肺癌和乳房腺癌。 肿瘤的生物发生和进化是一个具有挑战性的研究领域，很大程度上是由于细胞的复杂性 类型和行为以及驱动癌症类型和亚型的基因组合很差 明白了。我们已经开发了新一代GEMM来询问基因组合 促进癌症。为了达到这个目的，将产生包含遗传基因组合的小鼠模型 排名前30位的TCGA反复突变的扰动。这些研究将把 具有特定细胞状态的扰动剂，尽管它们具有克隆异质性和细胞状态，并奠定了 确定哪些复发基因组合对哪种治疗有效的基础，因此 帮助对病人进行分层。研究计划的这一部分侧重于肺癌，因为它协同作用 该提案的其他部分。我们应用了一种进化的血统追踪技术， 细胞RNA-seq读数，让我们以前所未有的分辨率跟踪肿瘤的进化。这些研究 将帮助我们理解肿瘤的可塑性是如何使癌症逃避治疗挑战的。和 重要的是，肿瘤抑制基因或基因组合的丢失如何改变首选的 单个转化细胞达到侵袭性和转移性状态所采用的进化路径。

PROJECT SUMMARY Our general strategy is to take advantage of novel tools and methodologies that we have developed during our first two CTD^2 funding periods– more specifically pioneering and applying CRISPR based technologies to aid the discovery and characterization of novel cancer targets and their modulators– using innovative high throughput technologies. Our end goal is to uncover optimal combinations of targets with the potential to eliminate all cancer cells, despite their clonal heterogeneity and environmental context. This requires us to better understand tumor biogenesis, namely the combinations of genes that drive oncogenesis, and tumor heterogeneity which complicates effective therapeutic treatment. In this proposal we build upon exciting systems allowing us to quantitate genotypic and phenotypic cell heterogeneity in cell culture and in vivo. The overall goal is to identify synthetic gene combinations necessary for clinical resistance and related to inter- and intra-tumor heterogeneity. We hypothesize that altered cell states such as inflammatory phenotypes and lineage plasticity fuels therapy tolerance and resistance. We apply single-cell approaches and cutting-edge lineage tracing tools to investigate the genesis of pathogenic cellular state changes and use genetic screening, computational and pharmacologic approaches, and clinically relevant in vitro and in vivo tumor models to identify mechanistically calibrated, specific therapeutic vulnerabilities. These approaches will be applied to two cancer, lung and breast adenocarcinoma. Tumor biogenesis and evolution is a challenging area of research, largely due to the complexity of cell types and behaviors and the combinations of genes that drive cancer types and subtypes is poorly understood. We have developed next generation GEMMs to interrogate gene combinations that promote cancer. In this aim, mouse models will be generated that contain combinations of genetic perturbations of the top 30 TCGA recurrent mutations. These studies will associate the combination of perturbagens with specific cell states, despite their clonal heterogeneity and cell state and lay a solid foundation for identifying which combinations of recurrent genes respond to which therapy, thus helping to stratify patients. This part of the research program focuses on lung cancer as it synergizes with other components of the proposal. We apply an evolved lineage tracing technology with single cell RNA-seq readout that lets us follow tumor evolution with unprecedented resolution. These studies will help us understand how tumor plasticity enables cancers to evade therapeutic challenges. And importantly, how the loss of tumor suppressor genes or gene combinations, alters the preferred evolutionary paths a single transformed cell takes to reach aggressive and metastatic states.