Integration of protein phosphorylation, acetylation, and methylation data sets to outline lung cancer signaling networks

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.

PAG1 directs SRC-family kinase intracellular localization to mediate receptor tyrosine kinase-induced differentiation

“…PI3K and AKT signaling are important for coordinating proliferative growth factor signaling and metabolism (Bilanges et al, 2019;Manning and Toker, 2017), yet it may be that only low levels of AKT activity are required for neuronal differentiation. Nevertheless, given the interconnected nature of cell signaling pathways (Grimes et al, 2018;Zheng et al, 2013), we can predict coordination with other signaling pathways downstream of RTK activation during differentiation, such as PLC-g, PI3K, AKT, and mTOR complexes, which are also involved in endocytic trafficking and lysosomal degradation (Bilanges et al, 2019;Manning and Toker, 2017). In any case, our results support a role for SFKs, namely FYN and LYN, and control of their activity and intracellular localization by PAG1, as a mechanism to distinguish differentiation signals caused by the RTKs TRKA and RET.…”

“…Tandem mas tag mass spectrometry was performed on SH-SY5Y and PAG1 TMcells as previously described (Grimes et al, 2018). Briefly, cells were washed and harvested in PBS and cell pellets frozen in liquid nitrogen.…”

Advances of Proteomics in Novel PTM Discovery: Applications in Cancer Therapy

“…It is well recognized that proteins that regulate cell signaling events are highly dependent on PTMs. The introduction of PTMs can alter the physical properties of amino acid residues and regulate the binding of various proteins, which is crucial for all cellular physiological functions, including differentiation, proliferation, cell movement, and cell death . For example, positively charged lysine (Lys) residues frequently participate in protein–protein interactions; however, the acetylation of lysine residues neutralizes the positive charge and thus affects diverse aspects of protein function such as stability, subcellular localization, and the interaction with other proteins in the cell .…”

Pathway Commons: 2019 Update

“…PC has been used to analyze transcriptomics, proteomics, and metabolomics data in a large number of projects across diseases to further our understanding of human biology in health and disease (4,(11)(12)(13)(14)(15)(16)(17)(18) . Since our original report in 2011, significant advances have been made with regard to the breadth and volume of data available along with software tools to support data creation, validation, and accessibility in the wider research community.…”