In Vivo Base Editing for Precision Oncology Models

精准肿瘤模型的体内碱基编辑

基本信息

批准号：
9893848
负责人：
LUKAS Edward DOW
金额：
$ 62.31万
依托单位：
WEILL MEDICAL COLL OF CORNELL UNIV
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 2024-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9893848
关键词：
Address Adenine Alleles Animal Model Bioinformatics Biological Biological Assay Biological Models Biology Cancer Cell Growth Cancer Model Cell Therapy Cells Clinical Clinical Trials Clustered Regularly Interspaced Short Palindromic Repeats Colorectal Cancer Complex Cytidine Cytidine Deaminase DNA DNA Binding DNA Sequence Alteration Data Deaminase Development Disease Disease model Enzymes Fluorescence Generations Genes Genetic Genetic Models Genetically Engineered Mouse Genome Genome engineering Genomic Segment Genomics Goals Human Human Biology Individual Knock-in Malignant Neoplasms Missense Mutation Modeling Modification Mouse Strains Mus Mutagenesis Mutate Mutation Nonsense Mutation Oncogenes Oncogenic Oncology Patients Positioning Attribute Pre-Clinical Model Property Publishing Recurrence Recurrent Malignant Neoplasm Reporter Resistance Resources Single Nucleotide Polymorphism Site Speed System TP53 gene Technology Time Tissues Transgenic Mice Translational Research Tumor Biology Validation Work base cancer type clinical sequencing design effective therapy exceptional responders flexibility gene function genome editing human disease human model in vivo in vivo Model individual response insertion/deletion mutation mutant novel pancreatic cancer model personalized medicine precision oncology predictive test repaired response screening sensor targeted treatment tool translational model tumor tumor initiation tumor progression tumorigenesis

项目摘要

PROJECT SUMMARY Genetic mutation is the predominant driver of cancer cell growth and therapy resistance. In fact, a major goal of personalized medicine is to identify specific genetic changes in individual tumors with the notion that defining these changes will guide more effective and targeted treatment. While this precision oncology approach shows clinical promise, ongoing tumor sequencing efforts continue to identify potential new disease drivers and new mutations. How these uncharacterized mutant alleles contribute to disease is often not obvious, and requires functional examination. Genetically engineered mouse models (GEMMs) provide an ideal tool to investigate the consequences of genetic changes on tumor biology, yet existing approaches are not fast or precise enough to recreate the spectrum of genetic alterations seen in human cancer. We and others have used CRISPR-based genome editing to accelerate the generation of complex, genetically defined animal models. Yet, while CRISPR systems are fast and simple, the basic tools are imprecise in that they cause insertions and deletions that ablate gene function but cannot mimic the single nucleotide variants most often seen in human cancer. To build in vivo systems that recapitulate specific human cancer-associated mutations, our project exploits new CRISPR tools that couple Cas9 to cytidine deaminase enzymes and enable direct DNA mutagenesis at defined genomic regions. ‘Base editing’ (BE) technology offers far greater efficiency and flexibility than existing homology directed repair (HDR) approaches by eliminating the need to deliver exogenous DNA templates. We have systematically optimized the expression and activity of BE enzymes to increase the efficiency of genome modification and established a bioinformatic and experimental pipeline to predict and validate BE tools that recreate known and novel cancer mutations. In Aim 1, building from extensively optimized BE enzymes, we will generate a range of knock-in transgenic mice to maximize the number of possible genomic regions that can be mutated using BE, and validate the activity of these mice using a new fluorescence-based reporter system. Further, using a novel sensor assay, we will identify all human and mouse sgRNAs that can target recurrent cancer-associated mutation sites. Together, this work will define the BE efficiency of thousands of independent sgRNAs, and establish the first in vivo somatic base editing platforms. In Aim 2 we will use our in vivo BE tools to generate novel animal models of pancreatic and colorectal cancer, and examine the consequences of distinct cancer-associated mutations in each disease. This work will not only offer a new understanding of key oncogenic mutations, it will provide critical validation of the utility of in vivo BE in multiple cancer settings. By providing an easy and efficient path to capture the diversity of human disease alleles, we believe this new precision editing platform has the potential to fundamentally change the way we design and implement mouse cancer models for translational research.

项目概要基因突变是癌细胞生长和治疗耐药性的主要驱动因素。事实上，这是癌症治疗的一个主要目标。个性化医疗是识别个体肿瘤的特定基因变化，其概念是定义这些变化将指导更有效和有针对性的治疗，而这种精准肿瘤学方法表明。临床前景，正在进行的肿瘤测序工作继续识别潜在的新疾病驱动因素和新的这些未表征的突变等位基因如何导致疾病通常并不明显，并且需要研究。基因工程小鼠模型（GEMM）提供了研究功能的理想工具。遗传变化对肿瘤生物学的影响，但现有方法不够快或不够精确我们和其他人已经使用基于 CRISPR 的技术重现了人类癌症中所见的遗传改变谱。然而，基因组编辑可加速复杂的、基因定义的动物模型的生成。系统快速而简单，基本工具不精确，因为它们会导致插入和删除，从而消除基因功能，但不能模拟人类癌症中最常见的单核苷酸变异。为了构建重现特定人类癌症相关突变的体内系统，我们的项目利用了新的 CRISPR 工具可将 Cas9 与胞苷脱氨酶偶联，并在指定的位置实现直接 DNA 诱变 “碱基编辑”（BE）技术比现有同源性提供更高的效率和灵活性。我们拥有直接修复 (HDR) 方法，无需提供外源 DNA 模板。系统优化BE酶的表达和活性，提高基因组效率修改并建立了生物信息学和实验管道来预测和验证 BE 工具重现已知和新的癌症突变。在目标 1 中，我们将通过主要优化的 BE 酶构建一系列敲入转基因小鼠最大化可以使用 BE 突变的可能基因组区域的数量，并验证这些小鼠使用新的基于荧光的报告系统，此外，我们将使用新型传感器测定来识别。所有能够靶向复发性癌症相关突变位点的人类和小鼠 sgRNA 共同发挥作用。将定义数千个独立sgRNA的BE效率，并建立第一个体内体细胞碱基在目标 2 中，我们将使用我们的体内 BE 工具生成胰腺和胰腺的新型动物模型。结直肠癌，并检查每种疾病中不同癌症相关突变的后果。这项工作不仅将提供对关键致癌突变的新认识，还将提供关键的验证体内BE在多种癌症环境中的效用。通过提供一种简单有效的途径来捕获人类疾病等位基因的多样性，我们相信这种新方法精确编辑平台有可能从根本上改变我们设计和实现鼠标的方式用于转化研究的癌症模型。