AN INTEGRATED PLATFORM FOR NOVEL PERSONALIZED LIVER CANCER THERAPEUTICS

摘要 肝癌是全球癌症相关死亡的第四大原因。目前，除了 新出现的免疫检查点抑制物，少量结构相关的激酶抑制物(KI)是 被批准用于晚期肝细胞癌(HCC)，这是最常见的肝癌形式。虽然很重要， 这些药物可以适度提高存活率--通常是几个月--而且往往是以显著的 毒性。药物索拉非尼、瑞格拉非尼、卡波赞替尼和兰瓦替尼均为多靶点KI，不良反应严重。 明确的行动机制。因此，这些药物是给肝细胞癌患者而不考虑任何 肿瘤内的特定突变。这是一项艰巨的挑战；没有明确的目标或机制，就没有 存在明确的途径来指导改进的肝癌治疗方法的发展。 在这个建议中，我们结合化学生物学方法来改变临床上的靶点偏好。 批准的肝细胞癌Kis和表观遗传工具化合物，我们开发了精密基因工程小鼠 一个集成平台中的模型和3D肿瘤器官，以确定新的药物靶点和治疗方法 肝细胞癌。我们的初步数据表明，不同的基因组驱动因素建立了独特的表观基因组景观 在肿瘤器官线内，影响可用药空间。通过化学基因筛查，我们有 已确定的先导化合物在所有被测试的肝癌基因型中都是泛活性的，其中一些是 对特定的遗传背景有选择性(例如，WNT/β-连环蛋白驱动的肿瘤的WNTinib1)。通过组合 WNTinib1的化学、蛋白质组和靶向参与数据，我们已经确定了Ezh2的一个独特的P38a/b 信号轴是拮抗突变型β-连环蛋白活性的关键和选择性依赖。少校 我们试图检验的假设是独特的表观基因组图景和对信号的依赖 由不同的肝癌癌驱动因素建立的通路对特定的靶点具有不同的敏感性 和小分子。通过利用司机诱导的小鼠癌症模型，小鼠和人类肿瘤 有机物和患者来源的异种移植物(PDX)，我们将能够建议分层策略并确定 更有效的针对肝细胞癌的量身定制疗法。这项提案的长期目标是确定和描述 在机制层面上，信号通路和靶点使得(I)跨各种肝癌的泛活动 亚型，(2)特定突变驱动的肿瘤背景下的选择性活性，(3)协同肿瘤 抑制与免疫治疗相结合的方法。重要的是，我们已经确定了强大的小分子 与标准护理KI相比，包括WNThib1在内的线索在几个肝癌中显示出更好的疗效 模型，包括人体样本。 关键交付成果包括从经过充分验证的化学物质开始的药物发现的新工具和线索 对肝细胞癌患者分层和治疗的观点和机械见解。

SUMMARY Liver cancer is the fourth leading cause of cancer related mortality worldwide. Currently, in addition to emerging immune checkpoint inhibitors, a small number of structurally related kinase inhibitors (KIs) are approved for advanced hepatocellular carcinoma (HCC), the most frequent form of liver cancer. While important, these drugs provide modest improvements in survival— typically months—and often at the cost of significant toxicity. The drugs, sorafenib, regorafenib, cabozantinib and lenvatinib are all multi-targeted KIs with poorly defined mechanisms of action. As such, these drugs are given to HCC patients without any consideration to a specific mutation within tumors. This presents a daunting challenge; without a clear target or mechanism, no clear path exists to guide the development of improved therapies for HCC. In this proposal, we combine chemical biology approaches to modify target preferences of clinically approved HCC KIs and epigenetic tool compounds, and we develop precision genetically-engineered mouse models and 3D tumor organoids in an integrated platform to identify new drug targets and therapeutics for HCC. Our preliminary data demonstrate that different genomic drivers establish unique epigenomic landscapes within tumor organoid lines, influencing the druggable space. Through chemical genetic screens, we have identified lead compounds that are either pan-active across all HCC genotypes tested and some which are selective to specific genetic backgrounds (e.g. WNTinib1 for WNT/β-Catenin driven tumors). By combining chemical, proteomic, and target engagement data for WNTinib1, we have identified an unique p38a/b to Ezh2 signalling axis as a key and selective dependency to antagonize the activity of mutant β-Catenin. The major hypothesis that we seek to test is that the unique epigenomic landscapes and dependencies on signaling pathways, which are established by different HCC cancer drivers, confer differential sensitivity to specific targets and small molecules. By taking advantage of driver-induced cancer mouse models, murine and human tumor organoids, and patient-derived xenografts (PDXs), we will be able to suggest stratification strategies and identify more effective tailored therapeutics for HCC. The long-term goal of this proposal is to identify and characterize at the mechanistic level, the signaling pathways and targets that enable (i) pan-activity across a variety of HCC sub-types, (ii) selective activity in the context of tumors driven by specific mutations, (iii) synergistic tumor inhibition in combination with immunotherapy approaches. Importantly, we have identified strong small molecule leads, including WNTinhib1, that display superior efficacy compared to standard-of-care KIs across several HCC models, including human samples. Key deliverables include new tools and leads for drug discovery derived from well-validated chemical starting points and mechanistic insights into patient stratification and therapeutics for HCC.