AN INTEGRATED PLATFORM FOR NOVEL PERSONALIZED LIVER CANCER THERAPEUTICS

新型个性化肝癌治疗的综合平台

基本信息

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
项目类别：
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

项目摘要

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.

概括目前，肝癌是全球癌症相关死亡的第四大原因。新兴的免疫检查点抑制剂，少数结构相关的激酶抑制剂（KI）批准用于治疗晚期肝细胞癌（HCC），这是最常见的肝癌形式，虽然很重要，但这些药物对生存药物（通常是几个月）提供了适度的改善，并且通常以显着的成本为代价。索拉非尼、瑞戈非尼、卡博替尼和乐伐替尼这些药物都是多靶点 KI，毒性较差。因此，这些药物在给予 HCC 患者时没有任何考虑。肿瘤内的特异性突变是一个艰巨的挑战，没有明确的目标或机制。存在明确的路径来指导 HCC 改进疗法的开发。在这个提案中，我们结合化学生物学方法来修改临床的目标偏好批准 HCC KI 和表观遗传工具化合物，我们开发精准基因工程小鼠模型和 3D 肿瘤类器官在一个集成平台中，以确定新的药物靶点和治疗方法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。通过化学遗传筛选，我们已经在肿瘤类器官系中影响了药物空间。鉴定出的先导化合物要么在所有测试的 HCC 基因型中具有泛活性，要么有一些是针对特定遗传背景的选择性（例如，针对 WNT/β-Catenin 驱动的肿瘤的 WNTinib1）。 WNTinib1 的化学、蛋白质组和靶点参与数据，我们已经确定了 Ezh2 的独特 p38a/b 信号轴作为拮抗突变β-连环蛋白活性的关键和选择性依赖性。我们试图测试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 HCC 癌症驱动因素建立的通路具有差异性，赋予对特定目标的敏感性通过利用驱动诱导的癌症小鼠模型、小鼠和人类肿瘤。类器官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针对 HCC 的更有效的定制疗法该提案的长期目标是识别和表征。在机制层面上，信号通路和靶标能够实现 (i) 跨多种 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) 协同肿瘤重要的是，我们已经鉴定出强效小分子。包括 WNTinhib1 在内的先导药物在多种 HCC 中表现出优于标准护理 KI 的疗效模型，包括人体样本。主要交付成果包括从经过充分验证的化学起始衍生的药物发现新工具和线索 HCC 患者分层和治疗的要点和机制见解。