Developing novel technology for mapping dynamic oncoprotein interaction networks

开发绘制动态癌蛋白相互作用网络的新技术

基本信息

批准号：
8538899
负责人：
Zhenghe Wang
金额：
$ 22.47万
依托单位：
CASE WESTERN RESERVE UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2012
资助国家：
美国
起止时间：
2012-09-01 至 2015-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8538899
关键词：
Address Affinity Affinity Chromatography Alleles Antibodies Antibody Formation Asses Cancer cell line Cell Nucleus Cells Complex Cytosol DNA Detection Development Ectopic Expression Environment Epidermal Growth Factor Receptor Epitopes Feedback Genes Genetic Transcription Goals Human Knock-in Mouse Knock-out Knowledge Lead Light MADH4 gene Malignant Neoplasms Maps Mass Spectrum Analysis Mediating Methods Modeling Molecular Mutation Oncogene Proteins Oncogenic PIK3CA gene Physiological Protein Dynamics Proteins Proteolytic Processing Proteomics Reagent Recombinant Proteins Request for Proposals Role STAT3 gene Sensitivity and Specificity Set protein Signal Transduction Specificity Stimulus TP53 gene Techniques Technology Testing The Cancer Genome Atlas Therapeutic Time Tumor Suppressor Genes Work cancer cell cell type experience extracellular gain of function mutation gene function homologous recombination innovation mutant new technology new therapeutic target notch protein novel novel strategies protein complex protein expression protein protein interaction public health relevance response technology development tumor tumorigenesis

项目摘要

DESCRIPTION (provided by applicant): Many oncoproteins and tumor suppressive proteins shuttle between the cytosol and nucleus and thus interact with changing sets of protein partners in different sub-cellular compartments. Furthermore, increasing evidence indicates that oncogenic mutations of these proteins can result in alteration of cellular localization and rewirin of oncoprotein interaction networks. Characterization of the dynamic interaction network of oncoproteins and tumor suppressive proteins is therefore crucial to understand their roles in tumorigenesis. Robust technologies for mapping dynamic protein interaction networks under physiological conditions within the cell are not yet available. We propose to develop a novel approach for mapping dynamic oncoprotein interaction networks using endogenously epitope-tagged proteins for affinity- purification and quantitative proteomics for accurate network identification. This application builds upon our successful development of an innovative method to introduce epitope tag- encoding DNA into endogenous loci by homologous recombination-mediated knock-in in human cancer cells and our intensive experience in quantitative proteomics analysis. The endogenously tagged proteins are expressed at physiological levels and provide physiologically-relevant environments and compartments for protein complex identification and are therefore ideal for mapping dynamic protein networks. The goals of this application are twofold. First, we propose a detailed quantitative comparison of our technique in terms of distinguishing mutant and wild-type oncoprotein complexes against two conventional approaches for studying protein complexes. Second we test the potential of our new approach for studying the dynamic interactions that occur in response to cell signaling. Successful development of this technology will provide a platform for understanding the reconfigurations to protein interaction networks that result from oncogenic related translocation or mutation. As large-scale projects such as The Cancer Genome Atlas (TCGA) proceed, many more novel oncogenes and tumor suppressor genes will be discovered; our technology provides an important pipeline for understanding the function of these genes at the interaction network level by mapping their dynamic interaction networks.

描述（由申请人提供）：许多癌蛋白和肿瘤抑制蛋白在细胞质和细胞核之间穿梭，从而与不同亚细胞区室中不断变化的蛋白质伴侣相互作用。此外，越来越多的证据表明，这些蛋白质的致癌突变可能导致细胞定位的改变和癌蛋白相互作用网络的重新布线。因此，癌蛋白和肿瘤抑制蛋白动态相互作用网络的表征对于理解它们在肿瘤发生中的作用至关重要。目前还没有用于绘制细胞内生理条件下动态蛋白质相互作用网络的强大技术。我们建议开发一种新的方法来绘制动态癌蛋白相互作用网络，使用内源表位标记的蛋白质进行亲和纯化和定量蛋白质组学，以实现准确的网络识别。该应用建立在我们成功开发一种创新方法的基础上，该方法通过同源重组介导的人类癌细胞敲入将编码表位标签的 DNA 引入内源基因座，以及我们在定量蛋白质组学分析方面的丰富经验。内源标记的蛋白质在生理水平上表达，并为蛋白质复合物鉴定提供生理相关的环境和区室，因此非常适合绘制动态蛋白质网络。该应用程序的目标是双重的。首先，我们提出对我们的技术在区分突变型和野生型癌蛋白复合物方面与研究蛋白质复合物的两种常规方法进行详细的定量比较。其次，我们测试了新方法研究响应细胞信号传导而发生的动态相互作用的潜力。该技术的成功开发将为理解致癌相关易位或突变导致的蛋白质相互作用网络的重新配置提供一个平台。随着癌症基因组图谱（TCGA）等大型项目的开展，更多新的癌基因和抑癌基因将会被发现；我们的技术通过绘制基因的动态相互作用网络，为理解这些基因在相互作用网络水平上的功能提供了重要的途径。