Targeting the Immune System in Mouse Models of Lung Adenocarcinoma

 描述(申请人提供)：癌症免疫疗法正在成为治疗实体肿瘤的一种有用的策略，并可能成为未来许多肿瘤治疗方案的核心。我们建议认证公认的肺腺癌(LUAD)基因工程小鼠(GEM)模型，作为对肿瘤免疫微环境进行表型的工具，并测试和设计结合免疫疗法的治疗干预措施，目的是优先进行临床测试研究。LUAD是一种破坏性疾病，5年存活率为16.8%(SEER数据2004-2010)。这些令人沮丧的数据强调了治疗这种疾病的新的、变革性的方法的必要性。在过去的十年中，出现了两种有可能显著提高LUAD患者存活率的治疗方法：靶向治疗和免疫治疗。事实上，我们对LUAD分子遗传学的了解的进步，已经导致在&gt；60%的LUAD中发现了“驱动”癌基因的突变。利用埃洛替尼(EGFR)和克里佐替尼(EML4-ALK)等特定的小分子激酶抑制剂成功地靶向了这些突变体的子集的蛋白质产物，这些药物通常用于临床治疗患者。然而，靶向治疗受到几乎不可避免的耐药性发展的限制，平均而言，在开始治疗的一年内。因此，有必要找到优化使用靶向疗法和/或找到治疗这种疾病的新方法的方法。通过癌症免疫疗法调节免疫细胞功能也可以激发抗肿瘤反应，正在成为治疗晚期肺癌的一种有前途的方法。随着这些疗法的开发和临床使用的测试，有必要确定谁可能对这些药物有反应，以及如何在临床上优化它们的使用。在这里，我们建议验证LUAD的GEM模型，该模型代表了疾病的主要分子亚集，用于免疫肿瘤学研究。为此，我们将：1)表征常见体细胞遗传改变诱导的LUAD GEM模型中的免疫微环境；2)建立LUAD GEM模型中免疫系统组件在肿瘤发生和肿瘤消退中的功能作用；3)使用LUAD GEM模型来评估和优化癌症免疫治疗的疗效。这些研究将使我们对LUAD的免疫微环境有一个全面的了解，并使我们能够确定可以作为治疗干预目标的脆弱性。此外，这项工作将使我们能够开发可传播的试剂和分析方法，以标准化分析和使用GEMS，在NCI的肿瘤模型论坛内外评估癌症免疫疗法。

 DESCRIPTION (provided by applicant): Cancer immunotherapy is emerging as a useful strategy to treat solid tumors and is likely to become central to many oncology treatment regimens in the future. We propose to credential well-established genetically engineered mouse (GEM) models of lung adenocarcinoma (LUAD) as tools to phenotype the tumor immune microenvironment and to test and design therapeutic interventions that incorporate immunotherapies with the objective of prioritizing studies for clinical testing. LUAD is a devastating disease with a 16.8% 5-year survival rate (SEER data 2004-2010). These dismal data underscore the need for novel, transformational approaches to treat this disease. During the past decade, two types of therapeutic approaches have emerged that have the potential to significantly improve survival for patients with LUAD: targeted therapies and immunotherapies. Indeed, advances in our understanding of the molecular genetics of LUAD, have led to the identification of mutations in "driver" oncogenes in >60% of LUADs. The protein products of a subset of these mutants have been successfully targeted using specific small molecule kinase inhibitors such as erlotinib (EGFR) and crizotinib (EML4-ALK) and these are routinely used in the clinic to treat patients. Targeted therapies, however, are limited by the almost inevitable development of drug resistance on average within a year of starting treatment. Therefore, it is necessary to find ways of optimizing the use of targeted therapies and/or finding new ways of treating the disease. Modulation of immune cell function using cancer immunotherapies can also evoke anti-tumor responses and is emerging as a promising approach to treat advanced lung cancer. As these therapies are being developed and tested for clinical use, it is necessary to determine who is likely to respond to these agents and how to optimize their use in the clinic. Here, we propose to validate GEM models of LUAD representing the main molecular subsets of the disease for studies of immuno-oncology. To do this, we will: 1) Characterize the immune microenvironment in LUAD GEM models induced by common somatic genetic alterations, 2) Establish the functional role of components of the immune system for tumorigenesis and tumor regression in LUAD GEM models and 3) Use LUAD GEM models to evaluate and optimize the efficacy of cancer immunotherapies. These studies will provide us with a comprehensive understanding of the immune microenvironment in LUAD and allow us to identify vulnerabilities that can be targeted for therapeutic intervention. Further, this work will enable us to develop reagents and assays that can be disseminated to standardize the analysis and use of GEMs for the evaluation of cancer immunotherapies both within and outside of the NCI's Oncology Models Forum.