Módos Dezső, Bulusu Krishna C, Fazekas Dávid, Kubisch János, Brooks Johanne, Marczell István, Szabó Péter M, Vellai Tibor, Csermely Péter, Lenti Katalin, Bender Andreas, Korcsmáros Tamás
Department of Morphology and Physiology, Department of Health Science, Semmelweis University, Budapest, Hungary.
Department of Genetics, Eötvös Loránd University, Budapest, Hungary.
NPJ Syst Biol Appl. 2017 Jan 24;3:2. doi: 10.1038/s41540-017-0003-6.
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.
即使是针对实体癌的靶向化疗也仅取得了一定程度的成功,这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层面的方法,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症相关蛋白的邻域。利用与突变和表达数据集整合的信号传导和蛋白质 - 蛋白质相互作用网络资源,我们分析了癌症相关蛋白的直接和间接相互作用分子(第一和第二邻域)的特性,这些相互作用分子此前未被发现与给定的癌症类型相关。我们发现第一邻域分子具有与癌症相关蛋白本身至少同样高的度、介数中心性和聚类系数,这表明它们在网络中处于此前未知的核心位置。我们为突变和差异表达的蛋白确定了一种互补策略,即网络中心性较小的差异表达蛋白的影响可由高中心性的第一邻域分子来补偿。这些第一邻域分子可被视为癌症重布线中关键的、迄今隐藏的成分,其重要性与突变蛋白相似。这些观察结果强烈表明,将第一邻域分子作为破坏癌症特异性网络的新型策略。值得注意的是,我们的调查发现已有223种上市药物靶向第一邻域蛋白,但大多应用于肿瘤学之外,这为实体癌的药物重新利用提供了一份潜在清单。对于那些直接靶向会导致多种副作用的非常核心的第一邻域分子,我们建议通过靶向它们的相互作用分子(癌症相关蛋白的第二邻域分子,具有与癌症相关蛋白类似的影响中心蛋白位置的作用)来采用一种模拟癌症的策略。因此,我们建议将第一邻域分子纳入基于网络医学的方法(但不限于)用于抗癌治疗。