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Neighbours of cancer-related proteins have key influence on pathogenesis and could increase the drug target space for anticancer therapies

机译:癌相关蛋白的邻居对发病机理有关键影响并可能增加抗癌治疗的药物靶标空间

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摘要

Even targeted chemotherapies against solid cancers show a moderate success increasing the need to novel targeting strategies. To address this problem, we designed a systems-level approach investigating the neighbourhood of mutated or differentially expressed cancer-related proteins in four major solid cancers (colon, breast, liver and lung). Using signalling and protein–protein interaction network resources integrated with mutational and expression datasets, we analysed the properties of the direct and indirect interactors (first and second neighbours) of cancer-related proteins, not found previously related to the given cancer type. We found that first neighbours have at least as high degree, betweenness centrality and clustering coefficient as cancer-related proteins themselves, indicating a previously unknown central network position. We identified a complementary strategy for mutated and differentially expressed proteins, where the affect of differentially expressed proteins having smaller network centrality is compensated with high centrality first neighbours. These first neighbours can be considered as key, so far hidden, components in cancer rewiring, with similar importance as mutated proteins. These observations strikingly suggest targeting first neighbours as a novel strategy for disrupting cancer-specific networks. Remarkably, our survey revealed 223 marketed drugs already targeting first neighbour proteins but applied mostly outside oncology, providing a potential list for drug repurposing against solid cancers. For the very central first neighbours, whose direct targeting would cause several side effects, we suggest a cancer-mimicking strategy by targeting their interactors (second neighbours of cancer-related proteins, having a central protein affecting position, similarly to the cancer-related proteins). Hence, we propose to include first neighbours to network medicine based approaches for (but not limited to) anticancer therapies.
机译:甚至针对实体癌的靶向化学疗法也显示出一定程度的成功,从而增加了对新型靶向策略的需求。为了解决这个问题,我们设计了一种系统级方法来研究四种主要实体癌(结肠癌,乳腺癌,肝癌和肺癌)中突变或差异表达的癌相关蛋白的邻域。利用整合了突变和表达数据集的信号和蛋白质-蛋白质相互作用网络资源,我们分析了与癌症相关的蛋白质的直接和间接相互作用因子(第一和第二邻居)的特性,而先前与给定的癌症类型无关。我们发现,第一个邻居至少具有与癌症相关蛋白本身一样高的程度,中间中心性和聚集系数,这表明以前未知的中心网络位置。我们确定了突变和差异表达蛋白的互补策略,其中具有较小中心网络中心的差异表达蛋白的影响被高中心性的第一邻居所补偿。这些第一个邻居可以被认为是癌症重新布线中的关键,迄今为止隐藏的组成部分,其重要性与突变蛋白相似。这些观察结果惊人地表明,以第一个邻居为目标是一种破坏癌症特异性网络的新策略。值得注意的是,我们的调查显示,市售的223种药物已经靶向第一个邻居蛋白,但主要应用于肿瘤学之外,为针对实体癌的药物用途提供了潜在清单。对于直接定位会导致多种副作用的非常中心的第一个邻居,我们建议通过靶向它们的相互作用因子(类似于癌症相关蛋白的第二邻居,具有与癌症相关蛋白相似的中心蛋白来影响位置)来模仿其癌症策略)。因此,我们建议包括第一批邻居,以网络为基础(但不限于)抗癌治疗的医学方法。

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