PT  - JOURNAL ARTICLE
AU  - Grimes, Mark
AU  - Hall, Benjamin
AU  - Foltz, Lauren
AU  - Levy, Tyler
AU  - Rikova, Klarisa
AU  - Gaiser, Jeremiah
AU  - Cook, William
AU  - Smirnova, Ekaterina
AU  - Wheeler, Travis
AU  - Clark, Neil R.
AU  - Lachmann, Alexander
AU  - Zhang, Bin
AU  - Hornbeck, Peter
AU  - Ma’ayan, Avi
AU  - Comb, Michael
TI  - Integration of protein phosphorylation, acetylation, and methylation data sets to outline lung cancer signaling networks
AID  - 10.1126/scisignal.aaq1087
DP  - 2018 May 22
TA  - Science Signaling
PG  - eaaq1087
VI  - 11
IP  - 531
4099  - http://stke.sciencemag.org/content/11/531/eaaq1087.short
4100  - http://stke.sciencemag.org/content/11/531/eaaq1087.full
SO  - Sci. Signal.2018 May 22; 11
AB  - Various “omics” analyses of cells provide insight into cellular health and behavior. Phosphoproteomic analysis has informed much of our current knowledge of cell signaling networks and facilitated drug development. Less appreciated are the inputs of other posttranslational modifications (PTMs). Grimes et al. integrated genomic, proteomic, phosphoproteomic, acetylomic, and methylomic data from lung cancer cells versus those in normal lung tissue and explored various regulatory patterns. The authors found that many PTMs are exclusive, in that as phosphorylation increased, acetylation decreased; that the drug geldanamycin broadly alters the PTM landscape and, thus, has effects far beyond its target; and that RNA binding proteins appear to be critical effectors of many signaling paths. These networks may inform new drug development for lung cancer patients and exemplify how cell signaling is regulated by far more extensive PTM networks than was previously appreciated.Protein posttranslational modifications (PTMs) have typically been studied independently, yet many proteins are modified by more than one PTM type, and cell signaling pathways somehow integrate this information. We coupled immunoprecipitation using PTM-specific antibodies with tandem mass tag (TMT) mass spectrometry to simultaneously examine phosphorylation, methylation, and acetylation in 45 lung cancer cell lines compared to normal lung tissue and to cell lines treated with anticancer drugs. This simultaneous, large-scale, integrative analysis of these PTMs using a cluster-filtered network (CFN) approach revealed that cell signaling pathways were outlined by clustering patterns in PTMs. We used the t-distributed stochastic neighbor embedding (t-SNE) method to identify PTM clusters and then integrated each with known protein-protein interactions (PPIs) to elucidate functional cell signaling pathways. The CFN identified known and previously unknown cell signaling pathways in lung cancer cells that were not present in normal lung epithelial tissue. In various proteins modified by more than one type of PTM, the incidence of those PTMs exhibited inverse relationships, suggesting that molecular exclusive “OR” gates determine a large number of signal transduction events. We also showed that the acetyltransferase EP300 appears to be a hub in the network of pathways involving different PTMs. In addition, the data shed light on the mechanism of action of geldanamycin, an HSP90 inhibitor. Together, the findings reveal that cell signaling pathways mediated by acetylation, methylation, and phosphorylation regulate the cytoskeleton, membrane traffic, and RNA binding protein–mediated control of gene expression.