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

可快速扩展的平台，用于直接体内筛选致命癌症的功能驱动因素

基本信息

批准号：
9902374
负责人：
Sidi Chen
金额：
$ 40.7万
依托单位：
YALE UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-04-01 至 2022-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9902374
关键词：
Advanced Development Animals Bar Codes Brain Neoplasms CRISPR screen CTLA4 gene Cancer Model Cause of Death Cells Clinical Clustered Regularly Interspaced Short Palindromic Repeats Communities Complement Complex Data Development FDA approved Genes Genetic Genetic Models Genetic Screening Genetically Engineered Mouse Genome Glioblastoma Goals Heterogeneity Histopathology Human Immunocompetent Immunotherapy Lentivirus Vector Libraries Life Link Liver Malignant Neoplasms Maps Measurement Mediating Methods Modeling Molecular Mutation Names Nature Neurosciences Normal Cell Oncology Organ Outcome PIK3CG gene Pathology Patients Penetrance Performance Pharmaceutical Preparations Phenotype Preclinical Testing Primary carcinoma of the liver cells Protocols documentation Resource Sharing Savings Science Study models System Technology Testing Therapeutic Tissue Engineering Tissues Validation Variant anticancer research base behavioral study cancer genome cancer type causal variant clinically relevant cohort combinatorial comparative flexibility genetic variant high throughput screening human disease immune checkpoint blockade improved in vivo insight mutant new technology novel novel strategies pre-clinical preservation profiles in patients programmed cell death protein 1 promoter response screening sequencing platform standard of care tool translational cancer research treatment response trend tumor tumor heterogeneity tumor immunology tumor initiation tumor microenvironment tumor-immune system interactions tumorigenesis

项目摘要

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.

项目摘要：癌症是全世界死亡的主要原因，治愈挑战。这样的挑战主要是由于肿瘤异质性和可发展性的性质。因此，产生的能力功能驱动因素的无偏，定量和因果图及其在天然肿瘤中的组合微环境是加速治疗发现的关键。迄今为止，几乎没有做全面和组合测试人类患者中发现的突变的哪些可以在功能上驱动天然器官正常细胞的肿瘤发生。主要障碍包括准确的交货，精确的基因组操纵，有效的大规模平行扰动和无偏的高敏性定量读数，所有这些都必须在天然组织微环境中同时实现。我们最近建立了一种新型方法，名为Pooled AAV屏幕，具有针对性扩增子测序（意大利面）直接在体内筛查致病性癌症驱动因素和组合。此方法生成（1）自发从天然器官中肿瘤细胞自发发展的癌症模型微环境，（2）在完全免疫能力的动物中发展并保留免疫微环境，（3）在患者中发现的遗传模仿显着突变，（4）密切模仿人类的组织病理学疾病和临床特征，（5）包括高度的遗传和细胞异质性，（6）提供靶向任何靶基因的灵活性，并以合并的突变屏幕迅速扩展，（7）易于社区的使用。在这项研究中，我们将进行先进的开发，强大的验证和完整的建立此筛选系统。我们将首先建立技术参数以最佳性能该技术通过使用独立患者队列的两种致命癌类型的定量测量进行了定量测量：胶质母细胞瘤和肝肝细胞癌。然后，我们将扩展为因果驱动程序发现的实用程序在治疗环境中。最后，我们将促进基于慢病毒媒介的正交的开发打开更大的筛选功能的方法。这样的筛选系统和模型将迅速鉴定直接驱动健康细胞，肿瘤起步，进展的因素的鉴定和对治疗的治疗反应。更重要的是，与现有替代方案相比免疫能力的设置允许在遗传匹配的动物中对免疫疗法进行稳健的临床前测试化身，以及筛选调节对这些疗法反应的基因。结果和影响：该R33将提供优化和验证的意大利面 / plestass系统，以将病变基因与天然TME的肿瘤发生；在完全免疫能力的环境中启用自我防寒的免疫治疗屏幕用于鉴定调节对这些挽救生命药物的反应的靶标；并共享资源和社区的协议，共同产生肿瘤学的新颖和深远的见解。