In Vivo Base Editing for Precision Oncology Models

精准肿瘤模型的体内碱基编辑

• 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
• 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

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.

项目摘要 遗传突变是癌细胞生长和耐药性的主要驱动力。实际上，一个主要目标 个性化医学是通过定义的观念来确定个体肿瘤中的特定遗传变化 这些变化将指导更有效和有针对性的治疗。虽然这种精确的肿瘤学方法显示 临床承诺，正在进行的肿瘤测序工作继续确定潜在的新疾病驱动因素和新的疾病驱动力 突变。这些未表征的突变等位基因如何对疾病造成疾病的贡献通常不明显，并且需要 功能检查。基因工程的鼠标模型（GEMM）提供了研究的理想工具 遗传变化对肿瘤生物学的后果，但是现有方法的快速或精确性不足以使 重现人类癌症中看到的遗传改变的范围。我们和其他人使用了基于CRISPR的 基因组编辑以加速复杂的，遗传定义的动物模型的产生。但是，虽然Crispr 系统快速而简单，基本工具是暗示的，因为它们会导致插入和删除浪费的插入和删除 基因功能，但不能模仿人类癌中最常看到的单个核苷酸变体。 为了构建概括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 将CAS9与胞苷脱氨酶酶相对的CRISPR工具，并在定义时启用直接DNA诱变 基因组区域。与现有同源性相比，“基础编辑”（BE）技术具有更高的效率和灵活性 通过消除提供外源DNA模板的需要，定向修复（HDR）方法。我们有 系统地优化了BE酶的表达和活性以提高基因组的效率 修改并建立了生物信息学和实验性管道，以预测和验证是一种工具 重现已知和新颖的癌症突变。 在AIM 1中，通过广泛优化的Be酶建造，我们将生成一系列敲入转基因小鼠 为了最大化可以使用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记者系统。此外，使用新型的传感器测定法，我们将确定 所有可以针对复发癌症相关的突变位点的人和小鼠SGRNA。在一起，这项工作 将定义数千个独立sgrNA的效率，并建立第一个体内体细胞基础 编辑平台。在AIM 2中，我们将使用我们的体内工具来生成新型的胰腺动物模型和 结直肠癌，并检查每种疾病中与癌症相关的突变的后果。这 工作不仅将对关键的致癌突变提供新的理解，还将提供对 体内的效用在多个癌症环境中。 通过提供一条轻松有效的途径来捕捉人类疾病等位基因的多样性，我们相信这个新的 精确编辑平台有可能从根本上改变我们设计和实施鼠标的方式 转化研究的癌症模型。