Understanding how oncogenic mutations rewire regulatory-protein networks is important for rationalizing the mechanisms of oncogenesis and for individualizing anticancer treatments. We report a chemical phosphoproteomics method to elucidate the topology of kinase-signaling networks in mammalian cells. We identified >6,000 protein phosphorylation sites that can be used to infer >1,500 kinase–kinase interactions and devised algorithms that can reconstruct kinase network topologies from these phosphoproteomics data. Application of our methods to primary acute myeloid leukemia and breast cancer tumors quantified the relationship between kinase expression and activity, and enabled the identification of hitherto unknown kinase network topologies associated with drug-resistant phenotypes or specific genetic mutations. Using orthogonal methods we validated that PIK3CA wild-type cells adopt MAPK-dependent circuitries in breast cancer cells and that the kinase TTK is important in acute myeloid leukemia. Our phosphoproteomic signatures of network circuitry can identify kinase topologies associated with both phenotypes and genotypes of cancer cells.

了解致癌突变如何重新连接调节蛋白网络对于合理化肿瘤发生机制和个体化抗癌治疗非常重要。我们报告了一种化学磷酸蛋白质组学方法来阐明哺乳动物细胞中激酶信号网络的拓扑结构。我们确定了超过 6,000 个蛋白质磷酸化位点，可用于推断超过 1,500 个激酶-激酶相互作用，并设计了可以根据这些磷酸化蛋白质组数据重建激酶网络拓扑的算法。将我们的方法应用于原发性急性髓性白血病和乳腺癌肿瘤，量化了激酶表达和活性之间的关系，并能够识别与耐药表型或特定基因突变相关的迄今为止未知的激酶网络拓扑。使用正交方法，我们验证了PIK3CA野生型细胞在乳腺癌细胞中采用 MAPK 依赖性电路，并且激酶 TTK 在急性髓系白血病中很重要。我们的网络电路磷酸化蛋白质组特征可以识别与癌细胞表型和基因型相关的激酶拓扑。