A Rational Systematic Approach to Find Combinations of Pharmacologic and Immune Therapies that Target Identifiable Oncogenic States

寻找针对可识别致癌状态的药物和免疫疗法组合的合理系统方法

• 批准号: 10016089
• 负责人: Ezra Cohen
• 金额: $ 100.58万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-12 至 2022-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10016089
• 关键词: Anatomy; Antibodies; Bayesian Method; Cancer Vaccines; Cancer cell line; Catalogs; Cell Survival; Cells; Cellular immunotherapy; Clinical; Clinical Trials; Clustered Regularly Interspaced Short Palindromic Repeats; Communities; Complex; Computer Models; Data; Data Set; Development; Elements; Epitopes; Foundations; Gene Expression; Generations; Genetic; Genetically Engineered Mouse; Genomics; Human; Immune; Immune Targeting; Immune checkpoint inhibitor; Immunologics; Immunotherapy; Knock-out; Lead; Maintenance; Malignant Neoplasms; Mediating; Molecular Target; Mutation; Natural Killer Cells; Oncogenes; Oncogenic; Pathway interactions; Patients; Pattern; Pharmacology; Resistance; Resources; Signal Pathway; Solid Neoplasm; Source; System; T-Lymphocyte; Testing; Therapeutic Intervention; Treatment Efficacy; Xenograft procedure; anticancer research; base; biological heterogeneity; cancer cell; cancer classification; cancer genome; chimeric antigen receptor; clinical development; clinical heterogeneity; immune checkpoint; innovation; mouse model; mutational status; neoantigens; new therapeutic target; novel; precision medicine; predictive modeling; response; synergism; targeted treatment; treatment strategy; tumor; tumor heterogeneity; tumor microenvironment; tumor-immune system interactions

A Rational Systematic Approach to Identify Combinations of Pharmacologic and Immune Therapies that Target Identifiable Oncogenic States.   Abstract Efforts to sequence large number of human cancers have provided a rich catalog of the most common genetic alterations that driven cancer formation and maintenance. This increasingly accurate mutational landscape has led to the identification of novel targets for therapeutic interventions. However, there is widespread biological and clinical heterogeneity in tumors, even when they share the same driver oncogene mutation. In addition, a high degree of dynamic plasticity and adaptability makes cancers display complex patterns of acquired resistance that manifest clinically. In a similar way, the wide variability of clinical responses to immunotherapy and the onset of immune escape, are becoming a formidable obstacle to fully realize the potential of many new and potentially effective immunotherapies. In this project we will evaluate a rational systematic approach to characterize oncogenic states and their most salient genomic and immune hallmarks in order to infer optimal combinations of pharmacologic and immunological perturbagens that disrupt cancer cell and tumor microenvironment interaction and viability. Our approach is based on our preliminary data, which suggests that in each identifiable oncogenic state there is a close interplay between activation of oncogenic elements, cellular pathways and the immune microenvironment. The project will test this approach with three Specific Aims: Aim 1. Characterize 5-10 pan-cancer oncogenic states with well-defined genomic and immune hallmarks including their specific molecular targets and sensitivity to perturbagens. Aim 2. Computationally infer optimal combinations of pharmacological and immunological perturbagens. Aim 3. Experimentally validate single and combinations of perturbagens identified in Aim 2. This innovative approach will provide a rich source of CTD2 datasets and resources including a catalog of oncogenic states, their most salient genomic and immune hallmarks, associated targets and validated combinations of pharmacologic and immune therapies that are effective at targeting tumors. These results will lead directly to the development of clinical trials, novel treatment strategies and provide the foundation for a new generation of more comprehensive, functional-based, precision medicine approaches.

识别药理学和免疫组合的合理系统方法 针对可识别致癌状态的治疗。   抽象的 对大量人类癌症进行测序的努力提供了最丰富的目录 驱动癌症形成和维持的常见基因改变。这越来越 准确的突变景观导致了治疗新靶点的确定 干预措施。然而，肿瘤存在广泛的生物学和临床异质性，甚至 当它们共享相同的驱动癌基因突变时。此外，高度动态 可塑性和适应性使癌症表现出复杂的获得性耐药模式 临床上表现出来。同样，免疫治疗的临床反应也存在很大差异 和免疫逃逸的开始，正在成为充分实现这一目标的巨大障碍 许多新的和潜在有效的免疫疗法的潜力。在这个项目中我们将 评估合理的系统方法来表征致癌状态及其最显着的特征 基因组和免疫标志，以推断药理和免疫的最佳组合 破坏癌细胞和肿瘤微环境相互作用的免疫扰乱因素 和生存能力。我们的方法基于我们的初步数据，这表明在每个 可识别的致癌状态 致癌元素的激活之间存在密切的相互作用， 细胞通路和免疫微环境。该项目将测试这种方法 三个具体目标： 目标 1. 明确定义 5-10 种泛癌致癌状态 基因组和免疫标志，包括其特定的分子靶点和敏感性 扰乱者。目标 2. 通过计算推断药理和药物的最佳组合 免疫干扰物。目标 3. 通过实验验证单个和组合 目标 2 中确定的扰动物。这种创新方法将提供丰富的 CTD2 来源 数据集和资源，包括致癌状态目录、其最显着的基因组和 免疫标志、相关靶点以及经过验证的药理和药物组合 有效针对肿瘤的免疫疗法。这些结果将直接导致 临床试验的发展，新的治疗策略，并为新的治疗奠定基础 产生更全面、基于功能的精准医学方法。