Uses of GEM models for Translational Cancer Research

描述（由申请人提供）：本申请的目标是利用癌症基因工程小鼠模型（GEMMs）的实验优点，用于基础和转化癌症科学。该应用程序将利用高度精细的恶性黑色素瘤和前列腺癌小鼠模型，其中包含人类疾病中存在的特征突变。这些模型概括了人类疾病的生物学、病理学和临床特征，包括转移。在项目1中，将设计诱导型NRAS*转移性黑色素瘤模型和高转移性PTEN/SMAD4前列腺癌模型，通过结合端粒酶缺陷来经历类似人类的癌症基因组不稳定性。使用全方位的多维基因组分析方法，我们将研究原发性和转移性肿瘤以及黑色素瘤中不依赖NRAS*信号的肿瘤或前列腺癌中雄激素依赖的肿瘤的获得性表观遗传和遗传事件。通过与人类癌症基因组图谱的比较，这些比较肿瘤基因组学研究将有助于发现人类癌症的关键驱动事件，并了解这些突变事件在转移、RAS信号和雄激素依赖的背景下的性质。在项目2中，我们将利用我们的转移性黑色素瘤和前列腺癌小鼠模型来确定转移性决定因素，这些决定因素可以预测哪些早期肿瘤是惰性的，哪些是积极的转移过程。具体来说，我们将利用每种肿瘤类型具有不同转移潜力的GEMMs来开发转移mRNA信号。然后，这些小鼠数据将与人类DNA拷贝数数据相结合，以确定跨物种保守的转移相关基因组事件，然后将其纳入功能验证筛选，以确定具有生物活性的转移决定因素。这些功能性转移决定因素将在结果注释的临床样本中进行测试，以确定其预测价值和指导早期黑色素瘤和前列腺癌最佳临床管理的能力。

DESCRIPTION (provided by applicant): The goal of this application is to exploit the experimental merits of genetically engineered mouse models (GEMMs) of cancer for use in basic and translational cancer science. This application will make use of high refined mouse models of malignant melanoma and prostate cancer harboring signature mutations that are present in the human disease. These models recapitulate the biological, pathological and clinical features of the human disease including metastasis. In Program 1, inducible NRAS* metastatic melanoma model and a high metastatic PTEN/SMAD4 prostate cancer model will be engineered to experience human-like cancer genome instability via incorporation of telomerase deficiency. Using a full range multi-dimensional genome profiling methodologies, we will examine the acquired epigenetic and genetic events in primary and metastatic tumors as well as tumors that have escaped dependence on NRAS* signaling in melanoma or androgen-dependence in prostate cancer. By comparison with human cancer genome atlas profiles, these comparative oncogenomics studies will serve to facilitate the discovery of key driver events in human cancer and understand the nature of these mutational events in the context of metastasis, RAS signaling and androgen dependence. In Program 2, we will utilize our mouse models of metastatic melanoma and prostate cancer to identify metastatic determinants that can predict which early stage tumors are programmed to remain indolent versus pursue an aggressive metastatic course. Specifically, we will take advantage of our GEMMs with differing metastatic potential for each tumor type to develop a metastasis mRNA signature. These murine data will then be interfaced with human DNA copy number data to identify cross-species conserved metastasis-associated genomic events that can then be enlisted into functional validation screens to identify biologically active metastasis determinants. These functional metastasis determinants will be tested in outcome-annotated clinical samples for their predictive value and capacity to guide the optimal clinical management of early stage melanoma and prostate cancers.