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.

项目总结/摘要 癌症基因组研究已经确定了大量的突变，包括点突变， 插入/缺失（indel），以及编码和调控区中的结构变体。对于许多 然而，由于这些突变没有被描述，它们如何促进肿瘤生长和对治疗的抵抗仍然是一个谜。在 体内功能验证是鉴定合适的干预和生物标志物的先决条件。快速和 因此，需要灵活的基因组编辑平台来构建和验证精确的小鼠模型， 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模拟成人癌症突变 小鼠组织，绕过了对生殖系小鼠模型的需要。目前基于CRISPR的方法 或者效率低（例如，同源定向修复）或不能用于模拟所有类型的突变（例如， 基础编辑）。需要一个更灵活的基因组编辑平台来加速体细胞癌的产生 小鼠模型。 我们已经开始优化prime编辑，作为一种精确建模各种癌症突变的方法， 小鼠Prime editor（PE）-Cas9切口酶融合到逆转录酶-利用延伸的指导RNA（称为 pegRNA），其兼作逆转录酶的模板以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 设计了一种双PE方法，以精确地引入具有短插入的大缺失（高达~10 kb）。这 这项工作为进一步优化PE向小鼠的递送和扩大其应用提供了基础。 应用于癌症小鼠模型。 本项目的目标是开发和优化新的PE工具，以加快两者的生成 肝癌和肺癌的组成型和诱导型体细胞小鼠模型。Aim 1将定义最佳的 pegRNA设计同时验证100种癌症相关突变，为体细胞癌症建立平台 体内建模，定义PE模型的临床前特征，并开发用于多重预充的递送载体 在小鼠肺中进行编辑。Aim 2将开发用于诱导性癌症模型的主要编辑工具。双PE方法 将用于在小鼠肝脏中产生可诱导的等位基因和floxed等位基因。我们还将产生高效的PE 模型来重现人类癌症中的大基因组缺失。该项目将产生新的小鼠模型 验证肝癌和肺癌中的驱动突变，并将提供一个灵活的平台， 小鼠癌症模型的翻译效用。