Dataset Information

Early Signaling Dynamics of EGFR

ABSTRACT: Despite extensive study of the epidermal growth factor receptor (EGFR) signaling network, the immediate post-translational changes that occur in response to growth factor stimulation remain poorly characterized; as a result, the biological mechanisms underlying signaling initiation remain obscured. To address this deficiency, we have used a mass spectrometry-based approach to measure system-wide phosphorylation changes throughout the network with 10 second resolution in the 80 seconds after stimulation in response to a range of 8 growth factor concentrations. Significant changes were observed on proteins far downstream in the network as early as 10 seconds after stimulation, indicating a system capable of transmitting information quickly. Meanwhile, canonical members of the EGFR signaling network fall into clusters with distinct activation patterns. Shc and PI3K phosphorylation levels increase rapidly, but equilibrate within 20 s, while proteins like Gab1 and SHP2 show slower, sustained increases. Proximity ligation assays reveal that Shc and Gab1 phosphorylation patterns are representative of separate timescales for physical association with the receptor. Inhibition of phosphatases with vanadate reveals site-specific regulatory mechanisms, and also uncovers primed activating components in the network, including Src family kinases, whose inhibition impacts only a subset of proteins within the network. The results presented highlight the complexity of signaling initiation, and provide a window into exploring mechanistic hypotheses about RTK biology.

INSTRUMENT(S): Q Exactive

ORGANISM(S): Homo Sapiens (ncbitaxon:9606)

SUBMITTER: Forest White

PROVIDER: MSV000080800 | MassIVE | Wed Mar 29 17:42:00 BST 2017

SECONDARY ACCESSION(S): PXD003660

REPOSITORIES: MassIVE

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Early signaling dynamics of the epidermal growth factor receptor.

Reddy Raven J RJ Gajadhar Aaron S AS Swenson Eric J EJ Rothenberg Daniel A DA Curran Timothy G TG White Forest M FM

Proceedings of the National Academy of Sciences of the United States of America 20160229 11

Despite extensive study of the EGF receptor (EGFR) signaling network, the immediate posttranslational changes that occur in response to growth factor stimulation remain poorly characterized; as a result, the biological mechanisms underlying signaling initiation remain obscured. To address this deficiency, we have used a mass spectrometry-based approach to measure system-wide phosphorylation changes throughout the network with 10-s resolution in the 80 s after stimulation in response to a range o ...[more]

PMID: 26929352

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Project description:Kholodenko1999 - EGFR signaling This model has been generated by the JWS Online project by Jacky Snoep using PySCeS Run this model online at http://jjj.biochem.sun.ac.za To cite JWS Online please refer to: Olivier, B.G. and Snoep, J.L. (2004) Web-based modelling using JWS Online , Bioinformatics, 20:2143-2144 This model is described in the article: Quantification of short term signaling by the epidermal growth factor receptor. Kholodenko BN, Demin OV, Moehren G, Hoek JB J. Biol. Chem. 1999 Oct; 274(42): 30169-30181 Abstract: During the past decade, our knowledge of molecular mechanisms involved in growth factor signaling has proliferated almost explosively. However, the kinetics and control of information transfer through signaling networks remain poorly understood. This paper combines experimental kinetic analysis and computational modeling of the short term pattern of cellular responses to epidermal growth factor (EGF) in isolated hepatocytes. The experimental data show transient tyrosine phosphorylation of the EGF receptor (EGFR) and transient or sustained response patterns in multiple signaling proteins targeted by EGFR. Transient responses exhibit pronounced maxima, reached within 15-30 s of EGF stimulation and followed by a decline to relatively low (quasi-steady-state) levels. In contrast to earlier suggestions, we demonstrate that the experimentally observed transients can be accounted for without requiring receptor-mediated activation of specific tyrosine phosphatases, following EGF stimulation. The kinetic model predicts how the cellular response is controlled by the relative levels and activity states of signaling proteins and under what conditions activation patterns are transient or sustained. EGFR signaling patterns appear to be robust with respect to variations in many elemental rate constants within the range of experimentally measured values. On the other hand, we specify which changes in the kinetic scheme, rate constants, and total amounts of molecular factors involved are incompatible with the experimentally observed kinetics of signal transfer. Quantitation of signaling network responses to growth factors allows us to assess how cells process information controlling their growth and differentiation. The model correctly reproduces all the figures from the paper. The curation has been done using SBMLodeSolver. This model is hosted on BioModels Database and identified by: BIOMD0000000048 . To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models . To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Project description:Mutations in the epidermal growth factor receptor (EGFR) kinase domain occur in 10-30% of lung adenocarcinoma. Leucine to arginine substitution at amino acid position 858 (L858R) accounts for around 50% of EGFR-tyrosine kinase inhibitor (TKI) sensitizing mutations. A second site mutation in the gatekeeper residue (T790M) accounts for around 60% of acquired resistance to EGFR-TKIs. We sought to identify the immediate direct and indirect targets of these mutant EGFRs in lung adenocarcinoma and their modulation by erlotinib, the first generation, and most widely used EGFR-directed TKI. We undertook stable isotope labeling of amino acids in cell culture (SILAC), phosphopeptide enrichment, and quantitative mass spectrometry to identify dynamic changes of phosphorylation downstream of mutant EGFRs in lung adenocarcinoma cells harboring L858R or L858R/T790M mutations and their modulation by erlotinib inhibition. Phosphorylation at the majority of phosphosites identified exhibited no change upon either EGF stimulation or erlotinib inhibition. Only around 7% of phosphosites identified and quantified showed increased phosphorylation upon EGF stimulation in either cell line. However, while phosphorylation at 61% of these phosphosites decreased upon erlotinib inhibition in the TKI sensitive H3255 cells, only 24% of such sites exhibited decreased phosphorylation upon erlotinib inhibition in the TKI resistant H1975 cells. Top canonical pathways that were inhibited upon erlotinib treatment in sensitive cells, but not the resistant cells include EGFR, Insulin receptor, HGF, MAPK, mTOR, p70S6K and JAK/STAT signaling. We identified phosphosites in proteins of the autophagy network, such as ULK1 (S623) that is constitutive phosphorylated in these lung adenocarcinoma cells, but phosphorylation is inhibited upon erlotinib treatment in sensitive cells, but not resistant cells. Finally, kinase-substrate prediction analysis from our data indicated that substrates of basophilic kinase families, AGC, CAMK and STE were significantly enriched and those of proline directed kinase families, CMGC and CK were significantly depleted among substrates that exhibit increased phosphorylation upon EGF stimulation and reduced phosphorylation upon TKI inhibition. This is the first study to date to examine global phosphorylation changes upon erlotinib treatment of lung adenocarcinoma cells and results from this study provide new insights into signaling downstream of mutant EGFRs in lung adenocarcinoma.