Kinases determine the phenotypes of many cancer cells, but the frequency with which individual kinases are activated in primary tumors remains largely unknown. We used a computational approach, termed kinase-substrate enrichment analysis (KSEA), to systematically infer the activation of given kinase pathways from mass spectrometry-based phosphoproteomic analysis of acute myeloid leukemia (AML) cells. Experiments conducted in cell lines validated the approach and, furthermore, revealed that DNA-dependent protein kinase (DNA-PK) was activated as a result of inhibiting the phosphoinositide 3-kinase (PI3K)-mammalian target of rapamycin (mTOR) signaling pathway. Application of KSEA to primary AML cells identified PI3K, casein kinases (CKs), cyclin-dependent kinases (CDKs), and p21-activated kinases (PAKs) as the kinase substrate groups most frequently enriched in this cancer type. Substrates phosphorylated by extracellular signal-regulated kinase (ERK) and cell division cycle 7 (CDC7) were enriched in primary AML cells that were resistant to inhibition of PI3K-mTOR signaling, whereas substrates of the kinases Abl, Lck, Src, and CDK1 were increased in abundance in inhibitor-sensitive cells. Modeling based on the abundances of these substrate groups accurately predicted sensitivity to a dual PI3K and mTOR inhibitor in two independent sets of primary AML cells isolated from patients. Thus, our study demonstrates KSEA as an untargeted method for the systematic profiling of kinase pathway activities and for increasing our understanding of diseases caused by the dysregulation of signaling pathways.
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