Core 1: Functional Genomics and Proteomics

核心1：功能基因组学和蛋白质组学

• 批准号: 10525592
• 负责人: Nevan J Krogan
• 金额: $ 32.62万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-14 至 2027-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10525592
• 关键词: Affinity; Affinity Chromatography; Atlas of Cancer Mortality in the United States; Bioinformatics; Biological Assay; Biological Sciences; Breast; CRISPR/Cas technology; Cancer Model; Cancer cell line; Cell Line; Cell model; Cells; Clustered Regularly Interspaced Short Palindromic Repeats; Collaborations; Complex; Computational Biology; Core Facility; Coupled; Cryoelectron Microscopy; Data; Dependence; Disease; Education; Education and Outreach; Generations; Genes; Genetic; Genetic Screening; Genomic medicine; Genomics; Goals; Head and Neck Squamous Cell Carcinoma; Head and neck structure; Infrastructure; Institutes; Knock-in; Knock-out; Lead; Lung; Mali; Malignant Neoplasms; Malignant neoplasm of lung; Maps; Mass Spectrum Analysis; Measures; Mentors; Modeling; Molecular; Mutate; Mutation; Outcome; Pathogenesis; Pathology; Pathway Analysis; Pathway interactions; Phenotype; Physiological; Point Mutation; Protein Complex Subunit; Proteins; Proteomics; Recurrence; Reproducibility; Research Personnel; Research Project Grants; Research Support; Specificity; Structure; Systems Biology; TP53 gene; Technical Expertise; Technology; Tertiary Protein Structure; Variant; base; cancer cell; cancer type; cell type; combinatorial; comparative; crosslink; experimental study; fitness; functional genomics; insight; interest; loss of function; migration; mutant; network models; novel; patient stratification; protein complex; protein expression; protein function; protein protein interaction; protein structure; reverse genetics; software infrastructure; stoichiometry; targeted cancer therapy; targeted treatment; tumor progression; tumorigenesis

CCMI v2.0 Core 1: Functional Genomics and Proteomics Core Core Lead: Nevan Krogan; Co-Investigator: Prashant Mali SUMMARY Systematic characterization of protein-protein interactions (PPIs) and genetic interaction networks of cancer drivers is critical for the identification of functional complexes for patient stratification and targeted cancer therapies. Proteomic approaches that determine PPIs and protein complex stoichiometry and topology can provide strategic insight into the dynamic cancer landscape and help guide tailored genetic screens to assess functional relevance of newly characterized PPIs. The Functional Genomics and Proteomics Core (Core 1) will provide the infrastructure and technical expertise essential to the completion of the overall CCMI objectives. With support of two Core facilities, the Functional Genomics and Proteomics Core will provide its expertise in CRISPR genetic screens (Institute for Genomic Medicine (IGM) Genomics Center, UCSD) and proteomic technologies (Thermo Fisher Scientific Proteomics Facility for Disease Target Discovery, UCSF, Quantitative Biosciences Institute (QBI), Gladstone Institute) for the generation of high-quality protein-protein (Aim 2; in support of Project 1) and genetic (Aim 1; in support of Project 2) interaction data, which will be integrated using systems biology approaches in Project 3 and Core 2. Our goal is to provide functional and structural characterization of cancer driver networks, model their functional interactions in three different cancers (breast, head and neck, lung cancer), and determine consequences of introducing point mutations. Finally, we will use a unique platform for Endogenous Network/Dynamic Structure (EN/DS) determination (Aim 3) that will use CRISPR-based genetics to introduce point mutations and FLAG-affinity tags into the endogenous loci of selected genes to study endogenous protein complex stoichiometry and structure using mass spectrometry and cryo-EM (in support of Project 1).

CCMI v2.0 核心 1：功能基因组学和蛋白质组学核心 核心负责人：Nevan Krogan；联合调查员：Prashant Mali 概括 蛋白质-蛋白质相互作用 (PPI) 和癌症遗传相互作用网络的系统表征 驱动因素对于识别患者分层和靶向癌症的功能复合物至关重要 疗法。确定 PPI 和蛋白质复合物化学计量和拓扑的蛋白质组学方法可以 提供对动态癌症格局的战略洞察，并帮助指导定制的基因筛查来评估 新表征的 PPI 的功能相关性。功能基因组学和蛋白质组学核心（核心 1） 将提供完成 CCMI 总体目标所必需的基础设施和技术专业知识。 在两个核心设施的支持下，功能基因组学和蛋白质组学核心将提供其专业知识 CRISPR 遗传筛选（基因组医学研究所 (IGM) 基因组学中心，加州大学圣地亚哥分校）和蛋白质组学 技术（Thermo Fisher Scientific 疾病靶标发现蛋白质组学设施、UCSF、定量 生物科学研究所 (QBI)、格莱斯顿研究所) 用于生成高质量的蛋白质-蛋白质（目标 2；在 支持项目 1）和遗传（目标 1；支持项目 2）交互数据，这些数据将使用 项目 3 和核心 2 中的系统生物学方法。我们的目标是提供功能和结构 癌症驱动网络的特征，模拟它们在三种不同癌症（乳腺癌、 头颈癌、肺癌），并确定引入点突变的后果。最后，我们将使用一个 用于内源网络/动态结构 (EN/DS) 测定（目标 3）的独特平台，将使用 基于 CRISPR 的遗传学将点突变和 FLAG 亲和标签引入选定的内源基因座 使用质谱和冷冻电镜研究内源蛋白质复合物化学计量和结构的基因 （支持项目1）。