Credentialing murine models for glioblastoma preclinical drug development

摘要 精准医学有望通过将药物靶向特定突变来彻底改变肿瘤学。然而，在这方面， 靶向药物在作为单一药物使用时未能产生持久的临床反应， 胶质母细胞瘤（GBM），最常见和致命的原发性脑肿瘤。遗传工程小鼠 (GEM)模型对于此类突变的功能验证是必不可少的，但技术限制 阻止了它们在临床前癌症药物开发中的广泛使用。米勒实验室已经开发出非- 生殖系GEM（nGEM）模型。Berens实验室进行了全面的基因组和 一组遗传多样性和忠实的患者源性人异种移植物的化学易感性分析 (PDX)模型约翰逊实验室开发了一种新的化学蛋白质组学方法，多重抑制剂 微珠结合质谱（MIB-MS），以评估细胞激酶组基因的激活状态。 Ketchand已经表明，动态激酶组重编程有助于靶向耐药性。在这 多PI项目，我们将联合收割机我们的专业知识，以解决以下目标：（1）认证PDX模型 （2）建立与人GBM基因匹配的nGEM模型， 不同来源的细胞;和（3）通过动态激酶组分析来验证PDX和nGEM模型。我们将 开发一组遗传多样性的nGEM模型，具有定义的驱动突变和细胞起源， 将是PDX在临床前药物开发中的有用辅助手段。然后，我们将对PDX和nGEM进行认证 使用跨物种基因组、转录组和激酶组对切除的GBM标本建立模型，以及 药物反应分析。模型将在基因组上与人类配对，并用于 开发合理的联合疗法，在基因组学上对抗单一药物耐药机制， 定义肿瘤亚型。因此，这项工作将有助于实现神经系统精准医学的承诺， 肿瘤学

ABSTRACT Precision medicine promises to revolutionize oncology by targeting drugs to specific mutations. However, targeted drugs have failed to produce durable clinical responses when used as single agents in glioblastoma (GBM), the most common and deadly primary brain tumor. Genetically engineered mouse (GEM) models are essential for functional validation of such mutations, but technical limitations have prevented their widespread use in preclinical cancer drug development. The Miller Lab has developed non- germline GEM (nGEM) models. The Berens Lab has performed comprehensive genomic and chemovulnerability profiling in a genetically diverse and faithful panel of patient-derived human xenograft (PDX) models. The Johnson Lab has developed a novel chemical proteomics method, multiplex inhibitor beads coupled with mass spectrometry (MIB-MS), to assess the activation state of the cellular kinome en masse and has shown that dynamic kinome reprogramming contributes to targeted drug resistance. In this Multi-PI project, we will combine our expertise to address the following Aims: (1) To credential PDX models against human GBM by kinome proteomics; (2) To develop genetically-matched nGEM models from distinct cells of origin; and (3) To credential PDX and nGEM models by dynamic kinome profiling. We will develop a genetically diverse panel of nGEM models with defined driver mutations and cellular origins that will be useful adjunct to PDX for preclinical drug development. We will then credential both PDX and nGEM models against resected GBM specimens using cross-species genome, transcriptome, and kinome, and drug response profiling. Models will be genomically matched to their human counterparts and used to develop rational combination therapies that combat single agent resistance mechanisms in genomically- defined tumor subtypes. This work will therefore help realize the promise of precision medicine in neuro- oncology.