权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

Using Protein Interaction Networks and Combinatorial Screens to target KRAS driven cancer

使用蛋白质相互作用网络和组合筛选来靶向 KRAS 驱动的癌症

基本信息

批准号：
9315124
负责人：
MICHAEL C BASSIK
金额：
$ 66.32万
依托单位：
STANFORD UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2015
资助国家：
美国
起止时间：
2015-09-02 至 2019-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9315124
关键词：
Accounting Affinity Chromatography Biological Models CRISPR screen CRISPR/Cas technology Cancer Etiology Cell Line Cessation of life Data Disease Drug Targeting Enzymes Event FDA approved Gene Combinations Genes Genetic Genetic Engineering Genetic Predisposition to Disease Genetically Engineered Mouse Genotype Goals Guide RNA Human KRAS2 gene Knock-out Knowledge Libraries Link Malignant Neoplasms Malignant neoplasm of lung Maps Mass Spectrum Analysis Measures Medical Mutate Mutation Non-Small-Cell Lung Carcinoma Oncogenes Oncogenic Pathway interactions Patients Post-Translational Protein Processing Predisposition Protein Analysis Proteins Proteomics RNA library Research Personnel Resolution STK11 gene Signal Transduction Subfamily lentivirinae System TP53 gene Techniques Technology Testing Therapeutic Tissues Tumor Suppressor Proteins United States Validation Work Xenograft procedure clinically relevant combinatorial deep sequencing density human cancer mouse model in vivo innovation mouse model mutant novel novel strategies protein protein interaction public health relevance screening tumor tumorigenesis

项目摘要

DESCRIPTION (provided by applicant): Lung cancer is the leading cause of cancer deaths worldwide. The most prevalent type of lung cancer is Non- Small Cell Lung Cancer (NSCLC). In NSCLC, KRAS is one of the most frequently mutated oncogenes and yet there are currently no KRAS specific therapeutic approaches. The goal of this application is to implement a collaborative effort involving proteomics, combinatorial genetics (CRISPR/CAS9 screens), and mouse modeling (genetically engineered and human-in-mouse models) to identify and validate novel strategies to target KRAS specifically in NSCLC. We hypothesize that focused screens informed by the context (tissue of origin and secondary genetic changes) of oncogenic KRAS activity are likely to yield novel KRAS vulnerabilities. Given that KRAS acts through multiple, parallel downstream effectors, we also hypothesize that the search for vulnerabilities should emphasize (1) combinatorial effects, and (2) a careful analysis of protein-protein interactions in the Ras pathway. The proteomic analysis proposed here will use as a starting point previously identified and validated KRAS synthetic vulnerabilities. In Aim 1, we will utilize affinity purification/ mass spectrometry (AP/MS), to systematically identify oncogenic KRAS protein networks seeded on targets defined by previous synthetic lethal interaction screens. New proteomic technologies will also permit high-resolution identification of KRAS-specific post-translational modifications (PTMs). This work will define a set of high value KSL candidates. In Aim 2, we deploy a novel genetic interaction map approach to create combinatorial knockout libraries. This approach utilizes a unique version of the CRISPR-CAS9 system that expresses two guide RNAs (sgRNAs) from a single lentivirus. Deep sequencing of sgRNA pairs will identify critical genes that genetically interact with oncogenic KRAS or with components of the KRAS interaction network. Lastly, in Aim 3, we will test the functional significance of combinatorial synthetic lethal interactions using two approaches. First, we use 3 mouse models of human cancer that combine KRAS activation with loss of key tumor suppressors (LKB1, p53 or Keap1), thus accounting for a significant fraction of the "varieties" of KRAS activity in actual human tumors. Second, further validation and human relevance will be determined using a set of well-characterized patient-derived xenografts. We anticipate that our studies will identify novel strategies for targeting KRAS mutant lung cancer and potentially other cancers in which KRAS mutations are prevalent.