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: 10004824
• 负责人: Ezra Cohen
• 金额: $ 16.67万
• 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/10004824
• 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 Simulation; 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

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.

一种合理的系统方法来鉴定药理和免疫的组合 针对可识别的致癌状态的治疗方法。 -- 摘要 对大量人类癌症进行测序的努力提供了一个丰富的 导致癌症形成和维持的常见基因改变。这一点越来越多 准确的突变景观导致了新的治疗靶点的确定 干预措施。然而，在肿瘤中存在着广泛的生物学和临床异质性，甚至 当它们共享相同的致癌基因突变时。此外，高度的动态化 可塑性和适应性使癌症表现出复杂的获得性抵抗模式 在临床上表现出来。以类似的方式，免疫治疗的临床反应的广泛变异性 和免疫逃逸的开始，正在成为充分实现 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 评估一种合理的系统方法来表征致癌状态及其最显著的状态 基因组和免疫标志，以推断药理和免疫的最佳组合 干扰癌细胞与肿瘤微环境相互作用的免疫干扰物 和生存能力。我们的方法是基于我们的初步数据，这表明在每个 可识别的致癌状态在致癌元件的激活、 细胞途径和免疫微环境。该项目将通过以下方式测试此方法 三个具体目标：目标1.用明确的定义描述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对 微扰者。目标2.通过计算推断药理和药物的最佳组合 免疫微扰剂。目标3.通过实验验证单个和组合 目标2中确定的扰动因素。这种创新的方法将提供丰富的CTD2来源 数据集和资源，包括致癌状态目录、其最显著的基因组和 免疫标志、相关靶点和有效的药理和药物组合 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，新的治疗策略和提供了新的基础 产生更全面的、以功能为基础的、精确的医学方法。