Abstract
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.
| Original language | English |
|---|---|
| Article number | eaaq1087 |
| Journal | Science Signaling |
| Volume | 11 |
| Issue number | 531 |
| DOIs | |
| State | Published - May 22 2018 |
Funding
M.G. and M.C. dedicate this paper to the memory of E. Herbert. We thank S. Beausoleil for data wrangling and discussions, A. Guo for antibody information, N. Fernandez for the gene expression clustergrammer visualization, and J. Syrenne for comments on the manuscript. Experimental data were obtained at Cell Signaling Technology. This work was supported by the NIH grants BD2K LINCS Data Coordination and Integration Center (grant number U54HL127624) and Knowledge Management Center for the Illuminating the Druggable Genome project (grant number U24CA224260).
| Funder number |
|---|
| BD2K LINCS |
| U24CA224260 |
| U54HL127624 |