Application of Technologies for Interactome Network Analyses of Cancer Mutations

癌症突变相互作用组网络分析技术的应用

基本信息

批准号：
7847547
负责人：
Marc Vidal
金额：
$ 60.62万
依托单位：
DANA-FARBER CANCER INST
依托单位国家：
美国
项目类别：
财政年份：
2008
资助国家：
美国
起止时间：
2008-06-05 至 2012-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7847547
关键词：
2-cyclopentyl-5-(5-isoquinolylsulfonyl)-6-nitro-1H-benzo(D)imidazole Address Alleles Amino Acids Attention Biological Biological Process Cancer Etiology Cells Complex DNA-Protein Interaction Data Set Development Disease Drug effect disorder Generations Genes Goals Human Human Genome Light Malignant Neoplasms Maps Mediating Medicine Modeling Molecular Molecular Biology Molecular Models Molecular Profiling Mutate Mutation Oncogenes Pathogenesis Property Proteins Proteome Proteomics System Systems Analysis Systems Biology Technology Time Tumor Suppressor Genes cancer genome cost functional genomics genome sequencing genome-wide in vivo innovative technologies interest molecular modeling neoplastic cell network models new technology novel novel therapeutics predictive modeling protein protein interaction research study success tumorigenesis

项目摘要

DESCRIPTION (provided by applicant): The molecular mechanisms underlying cancer have been mainly studied one or a few "cancer genes" at-a-time. However, it is thought that combinations of mutated or aberrantly expressed tumor suppressor- and oncogenes may be responsible for advancing cells through most steps of tumorigenesis. Many cancer causing mutations are disrupting interactions and these alterations are often directly related to the mechanism of pathogenesis. Thus, altered protein-protein interactions may directly point to a mechanism for cancerogenesis. More importantly, since it is becoming increasingly clear that genes and their products interact in complex biological networks with local and global properties, it is possible that perturbations of these networks contribute to cancer formation. We propose that a further understanding of the mechanisms involved in cancer, and the development of new therapeutic strategies, can be gained by i) studying genes and their products in the context of the molecular networks in which they function, and ii) investigating how such networks are altered in tumor cells compared to their unaffected counterparts. In addition to the information available from several drafts of the human genome sequence, genome- wide experimental strategies have been developed that will help us understand the effects of cancer mutations in the context of molecular networks: i) protein-protein and DNA-protein interaction networks or "interactome" networks are being mapped at an increasing pace, producing datasets with ever increasing quality and decreasing costs, and ii) large numbers of cancer-associated mutations are being discovered in the context of the human cancer genome project. Here we propose to develop a genome-wide application for a new technology platform that we have recently initiated to systematically study the effects of cancer-associated mutations on the physical and functional interactions mediated by the products encoded by cancer genes in the context of global interactome models. Our specific aims are to apply our experimental and computational technology platforms to: i) clone large numbers of cancer-associated missense or single amino acid change (SAC) alleles, ii) identify and characterize the interaction properties of large numbers of SAC alleles, iii) analyze the effects of SAC alleles on the local and global properties of interactome networks.

描述（由申请人提供）：癌症的分子机制主要是一次研究一个或几个“癌症基因”。然而，人们认为突变或异常表达的肿瘤抑制基因和癌基因的组合可能是细胞通过肿瘤发生的大多数步骤前进的原因。许多致癌突变正在破坏相互作用，这些改变通常与发病机制直接相关。因此，蛋白质-蛋白质相互作用的改变可能直接指向癌症发生的机制。更重要的是，由于越来越清楚的是，基因及其产物在具有局部和全局特性的复杂生物网络中相互作用，因此这些网络的扰动可能会导致癌症的形成。我们建议，通过以下方式可以进一步了解癌症涉及的机制，并开发新的治疗策略：i) 在基因及其产物发挥作用的分子网络背景下研究它们，以及 ii) 研究这些基因如何发挥作用。与未受影响的细胞相比，肿瘤细胞中的网络发生了改变。除了从人类基因组序列的几个草稿中获得的信息外，还开发了全基因组实验策略，这将帮助我们了解分子网络背景下癌症突变的影响：i）蛋白质-蛋白质和DNA-蛋白质相互作用网络或“交互组”网络正在以越来越快的速度进行绘制，产生质量不断提高且成本不断降低的数据集，并且ii）在人类癌症基因组计划的背景下发现了大量与癌症相关的突变。在这里，我们建议为新技术平台开发全基因组应用程序，我们最近启动了该平台，以在全球相互作用组的背景下系统地研究癌症相关突变对癌症基因编码产物介导的物理和功能相互作用的影响模型。我们的具体目标是应用我们的实验和计算技术平台来：i) 克隆大量与癌症相关的错义或单氨基酸改变 (SAC) 等位基因，ii) 识别和表征大量 SAC 等位基因的相互作用特性，iii ）分析 SAC 等位基因对相互作用组网络局部和全局特性的影响。