Application of Technologies for Interactome Network Analyses of Cancer Mutations

描述(申请人提供)：癌症的分子机制一次主要研究一个或几个“癌症基因”。然而，人们认为，突变或异常表达的抑癌基因和癌基因的组合可能负责推动细胞通过大多数肿瘤发生的步骤。许多导致癌症的突变正在破坏相互作用，这些变化往往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，由于基因及其产物在具有局部和全球特性的复杂生物网络中相互作用变得越来越明显，这些网络的扰动可能会导致癌症的形成。我们认为，进一步了解癌症涉及的机制和开发新的治疗策略，可以通过i)在基因及其产物所在的分子网络的背景下研究基因及其产物，以及ii)研究这些网络在肿瘤细胞中与未受影响的细胞相比是如何改变的。除了从人类基因组序列的几个草稿中获得的信息外，还开发了全基因组的实验策略，这些策略将帮助我们在分子网络的背景下了解癌症突变的影响：i)蛋白质-蛋白质和DNA-蛋白质相互作用网络或“相互作用组”网络正在以越来越快的速度被绘制出来，产生质量不断提高和成本不断降低的数据集，以及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，我们建议开发一个新的技术平台的全基因组应用，我们最近启动了一个新的技术平台，在全球相互作用组模型的背景下，系统地研究癌症相关突变对由癌症基因编码的产物介导的物理和功能相互作用的影响。我们的具体目标是应用我们的实验和计算技术平台：i)克隆大量与癌症相关的错义或单一氨基酸改变(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的局部和全局特性的影响。

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.