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：
8432550
负责人：
Zhenghe Wang
金额：
$ 23.9万
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 2014-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8432550
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 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. PUBLIC HEALTH RELEVANCE: Cancer development is driven by mutations in oncogenes and tumor suppressor genes. We aim to develop an innovative approach to facilitate studies of how these gene products function in cancer cells. Such studies will provide the fundamental knowledge required for the development of novel cancer therapeutic approaches.

描述（由申请人提供）：细胞质和核之间的许多癌蛋白和肿瘤抑制蛋白穿梭，因此与不同细胞隔室中蛋白质伴侣的变化集相互作用。此外，越来越多的证据表明，这些蛋白质的致癌突变会导致细胞定位和癌蛋白相互作用网络的rewirin的改变。因此，癌蛋白和肿瘤抑制蛋白的动态相互作用网络的表征对于了解其在肿瘤发生中的作用至关重要。在细胞内生理条件下绘制动态蛋白质相互作用网络的强大技术尚不可用。我们建议使用内源性表位标记的蛋白质来映射动态癌蛋白相互作用网络的新方法，以实现亲和力 - 纯化和定量蛋白质组学，以进行准确的网络鉴定。该应用是基于我们成功开发一种创新方法，该方法通过同源重组介导的人类癌细胞中的同源性重组介导的敲入以及我们在定量蛋白质组学分析方面的丰富经验，将表位标签编码为内源基因座。内源标记的蛋白在生理水平上表达，并为蛋白质复合物鉴定提供与生理相关的环境和隔室，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，我们在区分突变体和野生型癌蛋白复合物与研究蛋白质复合物的两种常规方法方面对我们的技术进行了详细的定量比较。其次，我们测试了研究对细胞信号传导响应的动态相互作用的新方法的潜力。该技术的成功开发将为理解由致癌相关的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。随着大规模的癌症基因组图集（TCGA）的进行，将发现更多新型的肿瘤基因和肿瘤抑制基因。我们的技术通过映射它们的动态交互网络，提供了一个重要的管道，可以通过映射它们的动态交互网络来理解这些基因的功能。公共卫生相关性：癌症发展是由癌基因和肿瘤抑制基因的突变驱动的。我们旨在开发一种创新的方法，以促进这些基因产物如何在癌细胞中起作用。这样的研究将提供开发新型癌症治疗方法所需的基本知识。