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蛋白质相互作用网络中的动态模块化可预测乳腺癌预后。

Dynamic modularity in protein interaction networks predicts breast cancer outcome.

作者信息

Taylor Ian W, Linding Rune, Warde-Farley David, Liu Yongmei, Pesquita Catia, Faria Daniel, Bull Shelley, Pawson Tony, Morris Quaid, Wrana Jeffrey L

机构信息

Samuel Lunenfeld Research Institute, Mount Sinai Hospital, 600 University Ave., Toronto, Ontario M5G 1X5, Canada.

出版信息

Nat Biotechnol. 2009 Feb;27(2):199-204. doi: 10.1038/nbt.1522. Epub 2009 Feb 1.

Abstract

Changes in the biochemical wiring of oncogenic cells drives phenotypic transformations that directly affect disease outcome. Here we examine the dynamic structure of the human protein interaction network (interactome) to determine whether changes in the organization of the interactome can be used to predict patient outcome. An analysis of hub proteins identified intermodular hub proteins that are co-expressed with their interacting partners in a tissue-restricted manner and intramodular hub proteins that are co-expressed with their interacting partners in all or most tissues. Substantial differences in biochemical structure were observed between the two types of hubs. Signaling domains were found more often in intermodular hub proteins, which were also more frequently associated with oncogenesis. Analysis of two breast cancer patient cohorts revealed that altered modularity of the human interactome may be useful as an indicator of breast cancer prognosis.

摘要

致癌细胞生化连接的变化驱动了直接影响疾病结果的表型转变。在此,我们研究人类蛋白质相互作用网络(互作组)的动态结构,以确定互作组组织的变化是否可用于预测患者的预后。对枢纽蛋白的分析确定了以组织限制方式与其相互作用伙伴共表达的模块间枢纽蛋白,以及在所有或大多数组织中与其相互作用伙伴共表达的模块内枢纽蛋白。观察到这两种类型的枢纽在生化结构上存在显著差异。信号域在模块间枢纽蛋白中更常见,这些蛋白也更频繁地与肿瘤发生相关。对两个乳腺癌患者队列的分析表明,人类互作组模块性的改变可能作为乳腺癌预后的一个指标。

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