A Pharmacogenomic Approach Using Precision Models of Hepatocellular Carcinoma to Identify Novel Therapeutics

项目摘要： 该提案使用了一种多维方法，用于肝细胞癌中的靶点验证和药物发现。 癌症（HCC），专注于药物基因组学预测，一个专有的化学类似物库， 批准的HCC KI支架，以及HCC的多种精确模型的使用： 在完全免疫活性背景下诱导HCC。这将允许体内药物测试和评估 在肿瘤微环境中以及与检查点抑制剂组合的药物影响; 2） 源自这些相同小鼠模型的三维肿瘤类器官，其允许药物治疗的可扩展性。 筛选肿瘤类器官是方便的基于组学的肿瘤生物学分析的重大突破 和临床前药物发现，并被证明准确地概括了患者对抗癌药物的反应 药物; 3）患者来源的类器官和4）患者来源的异种移植物（PDX），允许测试药物 在遗传复杂的原发性人类肿瘤中的疗效。我们的亲密合作者，阿尔文达尔，已经成功地 将该方法应用于甲状腺髓样癌中涉及的激酶（Dar等人，《自然》，2012年; Sonoshita等人，Nature Chemical Biology，2018）。我们最近还采用了一种简化的方法， 证实了与标准治疗（索拉非尼）相比，新KI-AD 80的抗肿瘤活性增加， 实验HCC模型（Yu等，已接受）。到目前为止，还没有一项研究将多学科 本提案中提出的肝癌药物发现创新。这个项目的主要假设是 不同的HCC致癌驱动因素将在肿瘤类器官内建立独特的治疗弱点， 线通过使用多个精度模型和对KIs的知情修改，我们将能够建议 分层策略，并为HCC患者确定更好的治疗方法。这一理论目前 这在肝癌研究中是前所未有的。

Project Summary: This proposal uses a multidimensional approach for target validation and drug discovery in hepatocellular carcinoma (HCC) that focuses on pharmacogenomic predictions, a proprietary chemical analog library built on approved HCC KI scaffolds, and the use of multiple precision models of HCC: 1) Genetically defined murine HCCs induced in a fully immunocompetent background. This will allow for in vivo drug testing and to assess the drug impact in the context of the tumor microenvironment and in combination with checkpoint inhibitors; 2) Three-dimensional tumor organoids derived from these same murine models, which allow scalability for drug screening. Tumor organoids are a major breakthrough for convenient omics-based analyses of tumor biology and preclinical drug discovery, and are shown to accurately recapitulate patient responses to anticancer agents; 3) Patient derived organoids and 4) Patient derived xenografts (PDX), which allow testing of drug efficacy in genetically complex primary human tumors. Our close collaborator, Arvin Dar, has successfully applied aspects of this approach to kinases involved in medullary thyroid carcinoma (Dar et al., Nature, 2012; Sonoshita et al., Nature Chemical Biology, 2018). We have also recently applied a simplified approach and confirmed increased anti-tumoral activity of a new KI -AD80- compared to the standard-of-care (sorafenib) in experimental HCC models (Yu et al, accepted). To date, no single study has combined the multidisciplinary innovation presented in this proposal for drug discovery in liver cancer. The major hypothesis of this project is that different HCC oncogenic drivers will establish unique therapeutic vulnerabilities within tumor organoid lines. By using multiple precision models and informed modifications to KIs, we will be able to suggest stratification strategies and identify better therapeutics for HCC patients. This rationale is currently unprecedented in liver cancer research.