In vivo prime editing for precision cancer mouse models

精准癌症小鼠模型的体内 Prime 编辑

• 批准号: 10735971
• 负责人: Wen Xue
• 金额: $ 62.56万
• 依托单位: UNIV OF MASSACHUSETTS MED SCH WORCESTER
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-17 至 2028-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10735971
• 关键词: Address; Adult; Alleles; Biological Markers; Biotechnology; Bypass; CRISPR/Cas technology; Cancer Model; Clustered Regularly Interspaced Short Palindromic Repeats; Code; Communities; Complex; DNA Repair; Disease Progression; Dissection; Endonuclease I; Engineering; Enzymes; Foundations; Gene Targeting; Generations; Genes; Genome; Genomics; Goals; Guide RNA; Histology; Human; Intervention; Knock-in; Liver; LoxP-flanked allele; Lung; Malignant Neoplasms; Malignant neoplasm of liver; Malignant neoplasm of lung; Methods; Modeling; Molecular; Mus; Mutation; Non-Viral Vector; Nucleic Acid Regulatory Sequences; Oncogenes; Oncogenic; Organ; Phenotype; Point Mutation; RNA-Directed DNA Polymerase; Reagent; Research; Site; Speed; System; Technology; Testing; Time; Tissues; Validation; Variant; Viral Vector; Work; base; base editing; base editor; cancer genomics; cell type; delivery vehicle; design; driver mutation; drug sensitivity; flexibility; genome editing; human disease; human model; improved; in vivo; in vivo Model; insertion/deletion mutation; insight; liver cancer model; mouse model; new therapeutic target; oncogene addiction; pre-clinical; prime editing; prime editor; recombinase; repaired; therapy resistant; tool; translational cancer research; tumor growth

Project Summary/Abstract Cancer genomic studies have identified a large number of mutations, including point mutations, insertions/deletions (indels), and structural variants in coding and regulatory regions. For many uncharacterized mutations, how they contribute to tumor growth and resistance to therapy remains murky. In vivo functional validation is a pre-requisite for identifying suitable interventions and biomarkers. Rapid and flexible genome editing platforms are therefore needed to build and validate precision mouse models with translational value. Recent advances in CRISPR-based genome editing allow us to directly model cancer mutations in adult mouse tissues, bypassing the need for germline mouse models. Current CRISPR-based approaches however are either inefficient (e.g., homology directed repair) or cannot be used to model all types of mutations (e.g., base editing). A more flexible genome editing platform is needed to speed up the generation of somatic cancer mouse models. We have begun to optimize prime editing as a way to precisely model a wide variety of cancer mutations in mice. Prime editor (PE)—Cas9 nickase fused to reverse transcriptase—utilizes an extended guide RNA (called a pegRNA) that doubles as a template for reverse transcriptase to copy information into the genomic target. We have recently developed an optimized PE that can install cancer mutations in mouse liver. We also engineered a dual-PE approach to precisely introduce large deletions (up to ~10 kb) with short insertions. This work provides a foundation upon which to further optimize the delivery of PE to mice and to expand its application to cancer mouse models. The goal of this project is to develop and optimize new PE tools to speed up the generation of both constitutive and inducible somatic mouse models of liver and lung cancer. Aim 1 will define rules for optimal pegRNA design while validating 100 cancer-associated mutations, establish platforms for somatic cancer modeling in vivo, define pre-clinical features of PE models, and develop delivery vectors for multiplexed prime editing in mouse lung. Aim 2 will develop prime editing tools for inducible cancer models. Dual-PE approaches will be used to make inducible alleles and floxed alleles in mouse liver. We will also generate efficient PE models to recapitulate large genomic deletions in human cancer. This project will result in new mouse models that validate driver mutations in liver and lung cancer and will provide a flexible platform to enhance the translational utility of mouse models of cancer.

项目摘要/摘要 癌症基因组研究已经确定了大量突变，包括点突变， 插入/缺失（Indels）以及编码和调节区域中的结构变体。对于许多人 未表征的突变，它们如何促进肿瘤生长和对治疗的抗性仍然模糊。 体内功能验证是确定合适的干预措施和生物标志物的先决条件。快速 因此，需要灵活的基因组编辑平台来构建和验证使用Precision Mouse模型 翻译价值。 基于CRISPR的基因组编辑的最新进展使我们能够直接对成人的癌症突变进行建模 小鼠组织，绕过对种系小鼠模型的需求。但是当前基于CRISPR的方法 效率低下（例如同源性修复），或者不能用于建模所有类型的突变（例如， 基础编辑）。需要一个更灵活的基因组编辑平台来加快体细胞癌的产生 鼠标模型。 我们已经开始优化主要编辑，以精确模拟各种各样的癌症突变 老鼠。 Prime Editor（PE） - CAS9 Nickase融合到逆转录酶 - 使扩展指南RNA（称为） pegrna）将逆转录酶兼作将信息复制到基因组靶标中。 我们最近开发了一种优化的PE，可以在小鼠肝脏中安装癌症突变。我们也是 设计了一种双PE方法，可以精确地引入大型删除（最高约10 kb），并带有短插入。这 工作为进一步优化PE向小鼠提供并扩展其扩展的工作为基础提供了基础 应用于癌症小鼠模型。 该项目的目的是开发和优化新的PE工具，以加快两者的生成 肝癌和肺癌的组成型和可诱导的体细胞模型。 AIM 1将定义最佳规则 Pegrna设计在验证100个与癌症相关的突变时，建立了体细胞癌的平台 在体内建模，定义PE模型的临床前特征，并为多路复用质量开发递送向量 在小鼠肺中进行编辑。 AIM 2将开发用于诱导癌模型的主要编辑工具。双PE方法 将用于在小鼠肝脏中制作可诱导的等位基因和flox的等位基因。我们还将产生高效的PE 概括人类癌中大型基因组缺失的模型。该项目将导致新的鼠标模型 验证肝脏和肺癌中的驾驶员突变，并将提供一个灵活的平台来增强 癌症小鼠模型的翻译效用。