Elucidating Mechanisms of Resistance using Genetically Engineered Mouse Models

使用基因工程小鼠模型阐明耐药机制

• 批准号: 8415139
• 负责人: LYNDA CHIN
• 金额: $ 29.4万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-03-12 至 2018-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8415139
• 关键词: BRAF gene; Behavior; Biological; Event; Genes; Genetic; Genetic Engineering; Genetically Engineered Mouse; Genomic Instability; Germ Lines; Human; Life; Modeling; Pathway interactions; Patients; Resistance; Testing; Therapeutic; Validation; in vivo; inhibitor/antagonist; melanoma; mouse model; mutant; novel; pre-clinical; resistance mechanism; response; tumor

Project 2: The single agent efficacy of selective mutant BRAF inhibitors in patients with advanced melanoma is uniformly short-lived, illustrating that therapeutic resistance is a paramount question in the field. Recognizing that micro-environmental context influences the biological behavior of a tumor, including response to therapy, a systematic and comprehensive effort to identify mechanisms of resistance. Thus, Project 2 brings to this P01 the uses of refined germline and non-germline genetically engineered models of BRAF-driven melanomas for discovery and validation of novel resistant genes as well as for preclinical therapeutic testing of combinations that can overcome resistance to selective BRAF inhibitor (BRAFi) in melanoma. The following 3 aims will be pursued: Aim 1: Identify genetic events conferring resistance to BRAFi in vivo. Here, using our refined BRAF^(R)¿¿^-driven genetically engineered mouse model (GEMM) ("iBIP"), we will generate a longitudinal cohort of sensitive and resistant melanomas upon long-term administration of BRAFi. These tumors will be subjected to deep genomic characterization to identify candidate lesions mediating resistance. Candidates will be prioritized and validated for/n wVo functional genetic screening based on statistical significance as well as evolutionary conservation through compahson with human genomic data from Project 1. Aim 2: Identify co-extinction targets for combination therapeutics against BRAF* melanoma. Complementing Aim 1, this aim will take a global and unbiased approach to the discovery of co-extinction targets. We will define the BRAF* regulated network in melanoma maintenance through kinetic transcriptome profiling of regressing melanomas upon genetic inactivation of mutant BF^F* in IBIP mice. Aim 3: Develop rational combination strategies for overcoming resistance to BRAFi in vivo. The goal of this aim is to generate sufficient preclinical efficacy data to motivate a novel Phase 18/11 clinical trial on a combination regimen that inhibits a co-extinction target along with BRAFi. Here, we will use mouse models to systematically screen potential combinations for efficacy; the best combination will then be tested in preclinical therapeutic trials in the IBIP GEMM. RELEVANCE (See instructions): Resistance to selective BRAF inhibitors in melanoma is a paramount challenge in the clinics today. Thus, elucidating the mechanisms modulating response and conferring resistance is timely and relevant. Bringing to bear on this challenge cutting-edged genomics and computational science as well as refined genetically engineered mouse models enable a discovery effort that is unbiased and comprehensive.

项目2：选择性突变BRAF抑制剂在晚期患者中的单药疗效 黑色素瘤是一致的短命，说明治疗耐药性是一个首要问题， 领域认识到微环境背景影响肿瘤的生物学行为，包括 对治疗的反应，一个系统和全面的努力，以确定耐药机制。因此，在本发明中， 项目2为P01带来了改良的生殖系和非生殖系基因工程模型的用途， BRAF驱动的黑色素瘤用于发现和验证新的耐药基因以及用于临床前 可以克服对选择性BRAF抑制剂（BRAFi）的抗性的组合的治疗测试 黑素瘤 将追求以下3个目标：目标1：鉴定在哺乳动物中赋予BRAFi抗性的遗传事件。 vivo.在这里，使用我们改进的BRAF^（R）â â ^驱动的基因工程小鼠模型（GEMM）（“iBIP”），我们 将在长期施用后产生敏感性和抗性黑素瘤的纵向队列， 布拉菲这些肿瘤将接受深基因组表征，以确定候选病变 介导阻力。将对候选人进行优先排序和功能遗传学验证 筛选的基础上，统计意义，以及通过比较进化保守 项目1的人类基因组数据。目标2：确定用于组合的共灭绝目标 针对BRAF* 黑素瘤的治疗剂。作为对目标1的补充，这一目标将采取一种全球性的、不带偏见的 发现共同灭绝目标的方法。我们将定义BRAF* 监管网络， 通过基因治疗后黑色素瘤消退的动力学转录组分析维持黑色素瘤 IBIP小鼠中突变型BF^F* 的失活。目标3：制定合理的组合战略， 克服体内对BRAFi的抗性。这一目标的目的是产生足够的临床前疗效 数据激发了一项关于抑制共灭绝的联合方案的新型18/11期临床试验 沿着瞄准BRAFi在这里，我们将使用小鼠模型来系统地筛选潜在的组合 最佳组合将在IBIP GEMM的临床前治疗试验中进行测试。 相关性（参见说明）： 黑色素瘤对选择性BRAF抑制剂的耐药性是当今临床的最大挑战。因此，在本发明中， 阐明调节反应和赋予抗性的机制是及时和相关的。带来 为了应对这一挑战，尖端的基因组学和计算科学以及基因工程学， 工程小鼠模型使得发现工作能够是公正和全面的。