title: Network analysis of epidermal growth factor signaling using integrated genomic, proteomic and phosphorylation data.
abstract: To understand how integration of multiple data types can help decipher cellular responses at the systems level, we analyzed the mitogenic response of human mammary epithelial cells to epidermal growth factor (EGF) using whole genome microarrays, mass spectrometry-based proteomics and large-scale western blots with over 1000 antibodies. A time course analysis revealed significant differences in the expression of 3172 genes and 596 proteins, including protein phosphorylation changes measured by western blot. Integration of these disparate data types showed that each contributed qualitatively different components to the observed cell response to EGF and that varying degrees of concordance in gene expression and protein abundance measurements could be linked to specific biological processes. Networks inferred from individual data types were relatively limited, whereas networks derived from the integrated data recapitulated the known major cellular responses to EGF and exhibited more highly connected signaling nodes than networks derived from any individual dataset. While cell cycle regulatory pathways were altered as anticipated, we found the most robust response to mitogenic concentrations of EGF was induction of matrix metalloprotease cascades, highlighting the importance of the EGFR system as a regulator of the extracellular environment. These results demonstrate the value of integrating multiple levels of biological information to more accurately reconstruct networks of cellular response.
authors.affiliation: Computational Biology and Bioinformatics, Pacific Northwest National Laboratory, Richland, Washington, United States of America. katrina.waters@pnl.gov
authors.forename: Katrina M
authors.initials: KM
authors.lastname: Waters
authors.forename: Tao
authors.initials: T
authors.lastname: Liu
authors.forename: Ryan D
authors.initials: RD
authors.lastname: Quesenberry
authors.forename: Alan R
authors.initials: AR
authors.lastname: Willse
authors.forename: Somnath
authors.initials: S
authors.lastname: Bandyopadhyay
authors.forename: Loel E
authors.initials: LE
authors.lastname: Kathmann
authors.forename: Thomas J
authors.initials: TJ
authors.lastname: Weber
authors.forename: Richard D
authors.initials: RD
authors.lastname: Smith
authors.forename: H Steven
authors.initials: HS
authors.lastname: Wiley
authors.forename: Brian D
authors.initials: BD
authors.lastname: Thrall
mesh_terms: D002453:Cell Cycle; D002460:Cell Line; D004815:Epidermal Growth Factor / Q000235:genetics* / Q000378:metabolism*; D004847:Epithelial Cells / Q000166:cytology / Q000378:metabolism; D005786:Gene Expression Regulation; D023281:Genomics / Q000379:methods*; D006801:Humans; D042361:Mammary Glands, Human / Q000166:cytology / Q000378:metabolism; D013058:Mass Spectrometry / Q000379:methods; D040901:Proteomics / Q000379:methods*; D015398:Signal Transduction
chemical_list: D004815:Epidermal Growth Factor