Kinome-wide decoding of network-attacking mutations rewiring cancer signaling.
Kinome-wide decoding of network-attacking mutations rewiring cancer signaling.
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DOI：
10.1016/j.cell.2015.08.056
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发表时间：
2015-09-24
期刊：
影响因子：
64.5
通讯作者：
Linding R
中科院分区：
文献类型：
--
作者：
Creixell P;Schoof EM;Simpson CD;Longden J;Miller CJ;Lou HJ;Perryman L;Cox TR;Zivanovic N;Palmeri A;Wesolowska-Andersen A;Helmer-Citterich M;Ferkinghoff-Borg J;Itamochi H;Bodenmiller B;Erler JT;Turk BE;Linding R
癌细胞通过积累扰乱信号网络的突变来获得病理表型。然而，目前对这些事件的全球分析是有限的。在这里，我们确定了六种类型的网络攻击突变(NAMS)，包括激酶和SH2调制的变化，网络重新连接，以及磷酸化位点的发生和灭绝。我们开发了一个识别NAMS的计算平台(ReKINect)，并系统地解释了五个卵巢癌细胞系的外显子组和定量(磷酸)蛋白质组以及全球癌症基因组库。我们鉴定并实验验证了几种NAM，包括PKCγM501I和PKD1D665N，它们编码的特异性开关类似于动态组中从头开始的激酶的出现。我们发现了突变的分子逻辑门，在癌症中朝着磷酸化苏氨酸信号的漂移，磷酸化基序的减弱，以及激酶失活的热点。我们的方法定位功能性NAM，根据癌症基因组和细胞信号的复杂性进行调整，并可能增强我们以肿瘤特异性网络为治疗靶点的能力。对扰乱信号网络的突变进行了系统的分类和解释，并在癌症中鉴定了几种这样的功能突变，并进行了实验验证。结果表明，单点突变可以产生深远的信号效应。对基因组数据的系统解释可能有助于未来的精确医学工作。对癌症基因组变异的系统分类揭示了扰乱信号网络的许多方式，包括重新连接和创建或破坏磷酸化位点。
Cancer cells acquire pathological phenotypes through accumulation of mutations that perturb signaling networks. However, global analysis of these events is currently limited. Here, we identify six types of network-attacking mutations (NAMs), including changes in kinase and SH2 modulation, network rewiring, and the genesis and extinction of phosphorylation sites. We developed a computational platform (ReKINect) to identify NAMs and systematically interpreted the exomes and quantitative (phospho-)proteomes of five ovarian cancer cell lines and the global cancer genome repository. We identified and experimentally validated several NAMs, including PKCγ M501I and PKD1 D665N, which encode specificity switches analogous to the appearance of kinases de novo within the kinome. We discover mutant molecular logic gates, a drift toward phospho-threonine signaling, weakening of phosphorylation motifs, and kinase-inactivating hotspots in cancer. Our method pinpoints functional NAMs, scales with the complexity of cancer genomes and cell signaling, and may enhance our capability to therapeutically target tumor-specific networks. Mutations perturbing signaling networks are systematically classified and interpreted Several such functional mutations are identified in cancer and experimentally validated The results suggest that a single point mutant can have profound signaling effects Systematic interpretation of genomic data may assist future precision-medicine efforts A systematic classification of genomic variants in cancer reveals the many ways in which signaling networks can be perturbed, including rewiring and the creation or destruction of phosphorylation sites.