Project 2: Functional Genetic Networks for Systems-Guided Precision Medicine

项目 2：系统引导精准医学的功能遗传网络

基本信息

批准号：
10704609
负责人：
Stephanie Irene Fraley
金额：
$ 50.14万
依托单位：
UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
依托单位国家：
美国
项目类别：
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/10704609
关键词：
Biological Assay Breast Cancer Patient CRISPR screen CRISPR/Cas technology Cell Line Cell Proliferation Cells Cessation of life Chromosome Mapping Clinical Clinical Trials Clustered Regularly Interspaced Short Palindromic Repeats Collection Data Development Disease Drug Interactions Drug Targeting Engineering Event Face Gene Deletion Gene Targeting Genes Genetic Genetic Epistasis Genetic Screening Genomics Head and Neck Squamous Cell Carcinoma Intervention Knock-out Libraries Link Logic Mali Malignant Neoplasms Maps Measurement Measures Methodology Methods Molecular Mutate PIK3CG gene Pathway interactions Patients Pharmaceutical Preparations Pharmacogenetics Phenotype Predisposition Protein-Protein Interaction Map Proteins Reporter Reporting Research Personnel Resistance Signal Transduction Squamous Cell Lung Carcinoma Squamous cell carcinoma System TP53 gene Technology Testing Time Treatment Efficacy arm cancer cell cancer subtypes cell behavior clinical translation combinatorial experimental study in vivo individualized medicine malignant breast neoplasm member new technology novel therapeutic intervention patient derived xenograft model precision medicine precision oncology prospective test response reverse genetics spatiotemporal synthetic lethal interaction therapeutic target tumor tumor progression tumorigenesis

项目摘要

CCMI v2.0 Project 2: Functional Genetic Networks for Systems-Guided Precision Medicine Project Leads: Prashant Mali and Stephanie Fraley; Co-Investigators: Alan Ashworth, Jennifer Grandis, Silvio Gutkind, Trey Ideker, and Laura van ’t Veer. SUMMARY Precision medicine aims to tailor therapies to the genetic and molecular background of a patient’s tumor. The development of such therapies faces numerous obstacles, many deriving from our ignorance of the genetic networks underlying tumorigenesis and the mechanisms of possible interventions. To clarify the genetic logic that governs therapeutic efficacy, Project 2 will use CRISPR/Cas9 genetic perturbation methodologies in an ensemble of combinatorial, functional, and mechanistic screens. Screens will focus on the PI3K pathway, the p53 tumor suppressor, and the protein systems mutated in invasive breast cancer (BRCA), head and neck squamous cell carcinoma (HNSCC), and lung squamous cell carcinoma (LUSC), pathways and diseases that together result in well over one million deaths each year worldwide. This focus will enable us to interrogate a broad collection of cell lines, experiments, and microenvironmental conditions. First, we will build on significant preliminary data to establish maps of synthetic lethal and epistatic genetic interactions centered on frequently mutated genes and therapeutic targets in the above pathways and cancer subtypes (Aim 1). Second, we will couple CRISPR/Cas9 screening to a panel of scalable functional assays for large-scale measurement of cancer phenotypes beyond cell proliferation (Aim 2). Third, we will pilot a new technology, STAG-CRISPR, to link CRISPR/Cas9 screening to real time molecular events in living cells, providing access to an even deeper array of phenotypes that have been recalcitrant to systems genetics thus far (Aim 3). Finally, to facilitate clinical translation of the identified gene-gene, gene-phenotype, gene-mechanism and gene-drug interactions, we will apply our extensive library of BRCA, HNSCC, and LUSC patient-derived xenograft (PDX) models to test compelling leads in vivo. We will also validate the identified interaction networks with patient data from the BRCA I-SPY 2 trial and from HNSCC patients at UCSD (Aim 4). Taken together, our integrated approach establishes a network of extensively validated interactions among genes, drugs and multiple phenotypic endpoints to advance the practice of precision oncology.

CCMI v2.0 项目 2：系统引导精准医学的功能遗传网络项目负责人：Prashant Mali 和 Stephanie Fraley；联合研究员：Alan Ashworth、Jennifer Grandis、西尔维奥·古特金德、特雷·艾德克和劳拉·范特·维尔。概括精准医学旨在根据患者肿瘤的遗传和分子背景制定治疗方案。此类疗法的开发面临着许多障碍，其中许多障碍源于我们对遗传的无知肿瘤发生的网络和可能的干预机制阐明遗传逻辑。为了控制治疗效果，项目 2 将使用 CRISPR/Cas9 遗传扰动方法组合、功能和机械筛选的集合将重点关注 PI3K 通路。 p53 肿瘤抑制因子以及浸润性乳腺癌 (BRCA)、头颈癌中的蛋白质系统突变鳞状细胞癌 (HNSCC) 和肺鳞状细胞癌 (LUSC)、途径和疾病全球每年导致超过一百万人死亡。这一重点将使我们能够审问一个问题。首先，我们将建立在重要的细胞系、实验和微环境条件的基础上。建立以频繁为中心的合成致死性和上位性遗传相互作用图谱的初步数据上述途径和癌症亚型中的突变基因和治疗靶点（目标 1）。将 CRISPR/Cas9 筛选与一组可扩展的功能结合起来，用于大规模测量癌症检测第三，我们将试验一种新技术，STAG-CRISPR，将其连接起来。 CRISPR/Cas9 筛选活细胞中的实时分子事件，提供更深入的阵列到目前为止，系统遗传学一直难以接受的表型（目标 3）。翻译已识别的基因-基因、基因-表型、基因-机制和基因-药物相互作用，我们将应用我们广泛的 BRCA、HNSCC 和 LUSC 患者来源的异种移植 (PDX) 模型库进行测试我们还将利用 BRCA 的患者数据验证已识别的相互作用网络。 I-SPY 2 试验和 UCSD 的 HNSCC 患者（目标 4）结合在一起，建立了我们的综合方法。基因、药物和多个表型终点之间经过广泛验证的相互作用网络推进精准肿瘤学实践。