Using Protein Interaction Networks and Combinatorial Screens to target KRAS driven cancer
Using Protein Interaction Networks and Combinatorial Screens to target KRAS driven cancer
批准号:
9315124
负责人:
MICHAEL C BASSIK
金额:
$66.32万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2015
资助国家:
美国
项目状态:
已结题
起止时间:
2015-09-02 至 2019-07-31
关键词:
AccountingAffinity ChromatographyBiological ModelsCRISPR screenCRISPR/Cas technologyCancer EtiologyCell LineCessation of lifeDataDiseaseDrug TargetingEnzymesEventFDA approvedGene CombinationsGenesGeneticGenetic EngineeringGenetic Predisposition to DiseaseGenetically Engineered MouseGenotypeGoalsGuide RNAHumanKRAS2 geneKnock-outKnowledgeLibrariesLinkMalignant NeoplasmsMalignant neoplasm of lungMapsMass Spectrum AnalysisMeasuresMedicalMutateMutationNon-Small-Cell Lung CarcinomaOncogenesOncogenicPathway interactionsPatientsPost-Translational Protein ProcessingPredispositionProtein AnalysisProteinsProteomicsRNA libraryResearch PersonnelResolutionSTK11 geneSignal TransductionSubfamily lentivirinaeSystemTP53 geneTechniquesTechnologyTestingTherapeuticTissuesTumor Suppressor ProteinsUnited StatesValidationWorkXenograft procedureclinically relevantcombinatorialdeep sequencingdensityhuman cancer mouse modelin vivoinnovationmouse modelmutantnovelnovel strategiesprotein protein interactionpublic health relevancescreeningtumortumorigenesis
中文摘要
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英文摘要
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.
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