Rapidly scalable platforms for direct in vivo screening of functional drivers in lethal cancers

项目概述：癌症是世界范围内的一个主要死亡原因，治疗方面面临着巨大的挑战。是这样的 挑战主要是由于肿瘤的异质性和进化性的性质。因此，能够产生 天然肿瘤中功能驱动因素及其组合的无偏、定量和因果关系图 微环境是加速治疗发现的关键。到目前为止，几乎没有采取什么措施 综合和组合测试在人类患者中发现的哪些突变确实可以 在功能上推动天然器官中正常细胞的肿瘤发生。主要的障碍包括准确的交付， 精确的基因组操作，高效的大规模并行扰动，以及公正、高灵敏度 定量读出，所有这些都必须在自然组织微环境中同时实现。 我们最近建立了一种新的方法，称为靶向扩增序列的池式AAV筛选 (意大利面)用于直接体内筛查致癌驱动因素和组合。此方法生成 癌症的精确模型：(1)从天然器官中的肿瘤起源细胞自发发展而来 微环境，(2)在完全具有免疫能力的动物中发展，并保存免疫微环境， (3)从基因上模仿患者身上发现的显著突变；(4)与人类的组织病理学非常接近 疾病和临床特征，(5)包括高度的遗传和细胞异质性，(6)提供 灵活地针对任何选择的目标基因，并可作为集合突变筛选快速扩展，以及(7)很容易 由社区使用。在这项研究中，我们将进行高级开发、健壮的验证和完整的 建立这一筛查制度。我们将首先建立最佳性能的技术参数 这项技术通过使用两种致命癌症类型的独立患者队列进行定量测量： 胶质母细胞瘤和肝细胞癌。然后，我们将扩展用于因果驱动程序发现的实用程序 在治疗环境中。最后，我们将推进基于慢病毒载体的正交病毒的开发 开发更大的筛查能力的方法。这种筛查系统和模型将使快速 识别直接驱动健康细胞转化、肿瘤发生、发展的致病因素 以及对治疗的反应。更重要的是，与现有的替代方案相比，完全 免疫能力设置允许在基因匹配的动物中进行强大的临床前免疫疗法测试 化身，以及筛选调节对这些疗法的反应的基因。结果和影响： R33将提供经过优化和验证的PASAS/PLeSTASS系统，将致病基因链接到 原生TME的致癌作用；使原生免疫治疗能够在完全免疫活性的环境下进行筛查 确定调节对这些救命药物的反应的目标；并分享资源和 为社区集体提供新的和深远的肿瘤学见解的协议。

Project Summary: Cancer is a major cause of death worldwide with outstanding challenges for a cure. Such challenges are primarily due to the nature of tumor heterogeneity and evolvability. Thus, the ability to generate unbiased, quantitative and causal maps of functional drivers and their combinations in native tumor microenvironment is a key to accelerate therapeutic discovery. To date, little has been done to comprehensively and combinatorially test which of the mutations identified in human patients can indeed functionally drive tumorigenesis of normal cells in native organs. The major barriers include accurate delivery, precise genome manipulation, efficient massively parallel perturbation, and unbiased, high-sensitivity quantitative readout, all of which have to be achieved simultaneously in the native tissue microenvironment. We recently established a novel approach named Pooled AAV Screen with Targeted Amplicon Sequencing (PASTAS) for direct in vivo screening of causative cancer drivers and combinations. This method generates precision models of cancer that (1) spontaneously develop from tumor-originating cells in the native organ microenvironment, (2) develop in fully immunocompetent animals and preserve the immune microenvironment, (3) genetically mimic significant mutations found in patients, (4) closely mimic the histopathology of human disease and clinical features, (5) encompass high degree of genetic and cellular heterogeneity, (6) offer flexibility to target any choice of target genes and rapidly scalable as pooled mutant screens, and (7) is easy to use by the community. In this study, we will conduct advanced development, robust validation and full establishment of this screening system. We will first establish technical parameters for optimal performance of this technology by quantitative measurements using independent patient cohorts with two lethal cancer types: glioblastoma and liver hepatocellular carcinoma. Then, we will extend the utility for causative driver discovery in therapeutic settings. Finally, we will advance the development of a lentiviral vector-based orthogonal approach to open up larger screening capabilities. Such screening systems and models will enable rapid identification of causative factors that directly drive transformation of healthy cells, tumor initiation, progression and therapeutic responses to treatments. More importantly, compared to existing alternatives, the fully immunocompetent setting allows robust pre-clinical testing of immunotherapies, in genetically matched animal avatars, as well as screening for genes that modulate the response to these therapies. Outcome and impact: This R33 will deliver optimized and validated PASTAS / PLeSTASS systems to link causative genes to oncogenesis in native TME; to enable autochthonous immunotherapy screen in fully immunocompetent setting for identification of targets that modulate the response to these life-saving drugs; and to share resources and protocols for the community to collectively yield novel and far-reaching insights in oncology.