title: Model-based analysis of HER activation in cells co-expressing EGFR, HER2 and HER3.
abstract: The HER/ErbB family of receptor tyrosine kinases drives critical responses in normal physiology and cancer, and the expression levels of the various HER receptors are critical determinants of clinical outcomes. HER activation is driven by the formation of various dimer complexes between members of this receptor family. The HER dimer types can have differential effects on downstream signaling and phenotypic outcomes. We constructed an integrated mathematical model of HER activation, and trafficking to quantitatively link receptor expression levels to dimerization and activation. We parameterized the model with a comprehensive set of HER phosphorylation and abundance data collected in a panel of human mammary epithelial cells expressing varying levels of EGFR/HER1, HER2 and HER3. Although parameter estimation yielded multiple solutions, predictions for dimer phosphorylation were in agreement with each other. We validated the model using experiments where pertuzumab was used to block HER2 dimerization. We used the model to predict HER dimerization and activation patterns in a panel of human mammary epithelial cells lines with known HER expression levels in response to stimulations with ligands EGF and HRG. Simulations over the range of expression levels seen in various cell lines indicate that: i) EGFR phosphorylation is driven by HER1-HER1 and HER1-HER2 dimers, and not HER1-HER3 dimers, ii) HER1-HER2 and HER2-HER3 dimers both contribute significantly to HER2 activation with the EGFR expression level determining the relative importance of these species, and iii) the HER2-HER3 dimer is largely responsible for HER3 activation. The model can be used to predict phosphorylated dimer levels for any given HER expression profile. This information in turn can be used to quantify the potencies of the various HER dimers, and can potentially inform personalized therapeutic approaches.
authors.affiliation: Computational Biology and Bioinformatics Group, Pacific Northwest National Laboratory, Richland, Washington, United States of America.
authors.forename: Harish
authors.initials: H
authors.lastname: Shankaran
authors.forename: Yi
authors.initials: Y
authors.lastname: Zhang
authors.forename: Yunbing
authors.initials: Y
authors.lastname: Tan
authors.forename: Haluk
authors.initials: H
authors.lastname: Resat
mesh_terms: D000911:Antibodies, Monoclonal; D002460:Cell Line; D003198:Computer Simulation; D004847:Epithelial Cells / Q000166:cytology / Q000201:enzymology / Q000378:metabolism; D066246:ErbB Receptors / Q000378:metabolism*; D006801:Humans; D020935:MAP Kinase Signaling System; D042361:Mammary Glands, Human / Q000166:cytology; D020928:Mitogen-Activated Protein Kinases / Q000378:metabolism; D008954:Models, Biological; D010766:Phosphorylation; D051057:Proto-Oncogene Proteins c-akt / Q000378:metabolism; D018719:Erb-b2 Receptor Tyrosine Kinases / Q000737:chemistry / Q000378:metabolism*; D020893:Receptor, ErbB-3 / Q000737:chemistry / Q000378:metabolism*; D015203:Reproducibility of Results
chemical_list: D000911:Antibodies, Monoclonal; D066246:ErbB Receptors; D020928:Mitogen-Activated Protein Kinases; D051057:Proto-Oncogene Proteins c-akt; D018719:Erb-b2 Receptor Tyrosine Kinases; D020893:Receptor, ErbB-3; C481039:2C4 antibody