A comprehensive quality control testing strategy for engineered cells

工程细胞的全面质量控制测试策略

基本信息

批准号：
10330008
负责人：
Christopher John Tompkins
金额：
$ 35.05万
依托单位：
KROMATID, INC.
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-01-15 至 2023-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10330008
关键词：
Address Alleles Aneuploidy Bioinformatics Biological Assay Biomedical Research CRISPR/Cas technology Cell Therapy Cells Chromatids Chromosomes Clinical Clinical Engineering Collaborations Collection Color Complex Contracts DNA Repair Data Data Set Defect Detection Development Disease Double Strand Break Repair Engineering Exhibits Funding G-Banding Genes Genome Genome engineering Genomic Hybridizations Genomics Goals Government Health Hereditary Disease Human In Situ Hybridization Individual Inherited Karyotype Karyotype determination procedure Knowledge Malignant Neoplasms Measurement Measures Medical Methods Modeling Monitor Nucleotides Outcome Paint Patients Pediatric Hospitals Pharmacologic Substance Polyploidy Population Process Provider Quality Control Research Resolution Risk Safety Saint Jude Children&apos s Research Hospital Sampling Sister Chromatid Exchange Site Source Speed Structure System Techniques Technology Testing Therapeutic Time Training Variant Work Writing base cellular engineering clinical application commercial application comparative data standards density design experience experimental study fluorophore gene therapy genome editing genome integrity genomic data high resolution imaging improved innovation insertion/deletion mutation patient safety predictive modeling programs reference genome research and development screening stem cells technological innovation therapeutic gene therapy development tool whole genome

项目摘要

ABSTRACT KromaTiD’s current commercial therapeutic gene editing customers have expressed the critical need for a standard approach to screening engineered cells for quality and safety that yields a comprehensive genomic dataset with improved resolution, localization, and speed. Directional Genomic Hybridization (dGH™) has been developed to efficiently screen cell populations for the presence of simple, complex, and heterogenous structural variants. In this project, A Comprehensive Quality Control Testing Strategy for Engineered Cells, by combining five-color, whole genome dGH with the fit for purpose sequencing methods of a clinically important genome engineering system, we propose an approach to assess, for the first time, the complete outcomes of gene editing: successful edits, unsuccessful edits, off-target edits, sequence variants, structural variants, and gross genome integrity. Furthermore, we propose to develop a standardized data specification integrating the data from these methods into a regulatory ready data package. dGH is an in-situ hybridization technique utilizes high-density chromatid paints to directly interrogate the structure of a genome in a single cell without bioinformatic interpretation, providing a complete toolset for hypothesis-free, single-cell measurement of SVs at edit sites, per chromosome, and across the whole genome. For companies developing therapies based on gene editing and other cell engineering approaches, understanding editing systems and mis-repair of DSBs are critical for patient safety and regulatory approval. Currently, batches of edited cells are screened for edit-site errors by sequencing. Because DSBs do not all occur at the edit site, SVs in batches of edited cells exhibit a complex, heterogenous mixture of edit-site and random breakpoints. G-banding can be used to screen for gross genome defects but cannot detect small or complex structural variants. dGH assays detect structural variation from a reference genome without target information, resolve SVs of 5Kb and larger, and provide improved genomic structural assessment capable of displacing standard karyotyping. The potential of genome editing approaches such as CRISPR/Cas9, for the treatment of diseases is widely recognized, and realization of the promise of such therapeutic approaches will rely on accurate confirmation of the presence and absence of potentially risky structural variants. For these reasons, comprehensive detection and characterization of structural variations is a necessary step toward understanding gene editing and other cell engineering systems. dGH combined with best-fit sequencing can provide a complete analysis of the outcomes of gene editing from SNVs and indels though large, complex SVs.

抽象的 KromaTiD 目前的商业治疗基因编辑客户表达了对筛选工程细胞的质量和安全性的标准方法，产生全面的基因组定向基因组杂交 (dGH™) 的数据集具有改进的分辨率、定位和速度。开发用于有效筛选细胞群中是否存在简单、复杂和异质的细胞在这个项目中，工程细胞的综合质量控制测试策略，作者：将五色全基因组 dGH 与临床重要的适合目的测序方法相结合基因组工程系统中，我们首次提出了一种评估完整结果的方法基因编辑：成功编辑、不成功编辑、脱靶编辑、序列变异、结构变异和此外，我们建议开发一个标准化的数据规范，整合将这些方法中的数据放入监管就绪的数据包中。 dGH 是一种原位杂交技术，利用高密度染色单体颜料直接询问单细胞基因组结构，无需生物信息解释，提供完整的工具集对编辑位点、每条染色体和整个基因组的 SV 进行无假设的单细胞测量。对于开发基于基因编辑和其他细胞工程方法的疗法的公司来说，了解 DSB 的编辑系统和误修复对于患者安全和监管批准至关重要。目前，通过测序筛选批量编辑的细胞是否存在编辑位点错误，因为 DSB 并非全部如此。由于发生在编辑位点，批量编辑细胞中的 SV 表现出编辑位点和编辑位点的复杂、异质混合物。随机断点可用于筛查总体基因组缺陷，但无法检测小缺陷或缺陷。复杂的结构变异检测来自没有目标的参考基因组的结构变异。信息，解析 5Kb 及更大的 SV，并提供改进的基因组结构评估，能够取代标准核型分析。 CRISPR/Cas9 等基因组编辑方法在治疗疾病方面的潜力已得到广泛认可认识到，并实现这种治疗方法的承诺将依赖于准确的确认由于这些原因，需要全面检测是否存在潜在风险的结构变异。结构变异的表征是理解基因编辑和其他技术的必要步骤细胞组合工程系统与最佳拟合测序可以提供完整的分析。通过大型、复杂的 SV 进行 SNV 和插入缺失的基因编辑的结果。