AN INTEGRATED PLATFORM FOR NOVEL PERSONALIZED LIVER CANCER THERAPEUTICS

新型个性化肝癌治疗的综合平台

• 批准号: 10428670
• 负责人: Arvin Dar
• 金额: $ 61.78万
• 依托单位: ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-01 至 2026-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10428670
• 关键词: 3-Dimensional; Animals; BAY 54-9085; Binding; Biological; Biological Assay; Biology; CTNNB1 gene; Cancer Etiology; Cells; Cessation of life; Chemicals; Chromatin; Clinical; Complex; Critical Pathways; Data; Dependence; Development; Disease; Drug Design; Drug Targeting; Ensure; Enzymes; Epigenetic Process; FDA approved; Failure; Genetic; Genetic Screening; Genetic Transcription; Genetically Engineered Mouse; Genomics; Genotype; Goals; Growth; Heterogeneity; Histones; Human; Immune checkpoint inhibitor; Immune system; Immunotherapy; Incidence; Lead; Malignant Neoplasms; Malignant neoplasm of liver; Modeling; Mus; Mutation; Nature; Oncogenic; Organoids; Patients; Pharmaceutical Preparations; Phenotype; Phosphotransferases; Pre-Clinical Model; Precision therapeutics; Primary carcinoma of the liver cells; Proteomics; Publishing; Regulation; Research; Sampling; Signal Pathway; Signal Transduction; Site; Stratification; Structure-Activity Relationship; Testing; Therapeutic; Toxic effect; Validation; Xenograft procedure; base; beta catenin; biobank; chemical genetics; comparative efficacy; cost; drug development; drug discovery; epigenomics; gene repression; improved; insight; kinase inhibitor; liver cancer model; mortality; mouse model; multidisciplinary; mutant; new therapeutic target; novel; patient derived xenograft model; patient population; patient stratification; personalized therapeutic; preference; programmed cell death protein 1; small molecule; small molecule inhibitor; small molecule libraries; standard of care; synergism; targeted treatment; tool; tumor; tumor microenvironment

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.

总结 肝癌是全球癌症相关死亡率的第四大原因。目前除了 作为新兴的免疫检查点抑制剂，少数结构相关的激酶抑制剂（KI） 被批准用于晚期肝细胞癌（HCC），最常见的肝癌形式。虽然重要， 这些药物提供了适度的生存改善-通常是几个月-并且通常以显著的 毒性药物索拉非尼、瑞格非尼、卡博替尼和乐伐替尼都是多靶点KI， 明确的行动机制。因此，这些药物给予HCC患者时， 肿瘤内的特异性突变。这是一项艰巨的挑战;如果没有明确的目标或机制， 明确的路径存在，以指导肝癌的改进疗法的发展。 在这个建议中，我们联合收割机化学生物学方法来修改临床上的靶向偏好。 批准的HCC KIs和表观遗传工具化合物，我们开发了精确的基因工程小鼠 模型和3D肿瘤类器官，以确定新的药物靶点和治疗方法， HCC。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 在肿瘤类器官线内，影响可药用空间。通过化学遗传筛选，我们有 鉴定了先导化合物，其在所有测试的HCC基因型中是泛活性的，并且其中一些是 对特定遗传背景具有选择性（例如，WNT替尼1用于WNT/β-连环蛋白驱动的肿瘤）。通过组合 结合WNTinib 1的化学、蛋白质组学和靶点结合数据，我们鉴定了Ezh 2的独特p38 a/B 信号传导轴作为拮抗突变β-连环蛋白活性的关键和选择性依赖。主要 我们试图验证的假设是，独特的表观基因组景观和对信号传导的依赖性 由不同的HCC癌症驱动因素建立的通路赋予了对特定靶点的不同敏感性 和小分子。通过利用驾驶员诱导的癌症小鼠模型， 类器官和患者来源的异种移植物（PDX），我们将能够提出分层策略，并确定 更有效的肝癌定制疗法。本提案的长期目标是确定和描述 在机制水平上，信号通路和靶点使（i）跨各种HCC的泛活性 亚型，（ii）在特定突变驱动的肿瘤背景下的选择性活性，（iii）协同肿瘤 抑制与免疫治疗方法组合。重要的是，我们已经确定了强小分子 在几种HCC中，与标准治疗KI相比，显示出上级疗效的电极导线（包括WNTH 1） 模型，包括人体样本。 关键的交付成果包括来自经过充分验证的化学起始的药物发现的新工具和线索 点和机制的见解，病人分层和治疗肝癌。