Protein expression signatures for inhibition of epidermal growth factor receptor-mediated signaling

Abstract

Analysis of cellular signaling networks typically involves targeted measurements of phosphorylated protein intermediates. However, phosphoproteomic analyses usually require affinity enrichment of phosphopeptides and can be complicated by artifactual changes in phosphorylation caused by uncontrolled preanalytical variables, particularly in the analysis of tissue specimens. We asked whether changes in protein expression, which are more stable and easily analyzed, could reflect network stimulation and inhibition. We employed this approach to analyze stimulation and inhibition of the epidermal growth factor receptor (EGFR) by EGF and selective EGFR inhibitors. Shotgun analysis of proteomes from proliferating A431 cells, EGF-stimulated cells, and cells co-treated with the EGFR inhibitors cetuximab or gefitinib identified groups of differentially expressed proteins. Comparisons of these protein groups identified 13 proteins whose EGF-induced expression changes were reversed by both EGFR inhibitors. Targeted multiple reaction monitoring analysis verified differential expression of 12 of these proteins, which comprise a candidate EGFR inhibition signature. We then tested these 12 proteins by multiple reaction monitoring analysis in three other models: 1) a comparison of DiFi (EGFR inhibitor-sensitive) and HCT116 (EGFR-insensitive) cell lines, 2) in formalin-fixed, paraffin-embedded mouse xenograft DiFi and HCT116 tumors, and 3) in tissue biopsies from a patient with the gastric hyperproliferative disorder Ménétrier's disease who was treated with cetuximab. Of the proteins in the candidate signature, a core group, including c-Jun, Jagged-1, and Claudin 4, were decreased by EGFR inhibitors in all three models. Although the goal of these studies was not to validate a clinically useful EGFR inhibition signature, the results confirm the hypothesis that clinically used EGFR inhibitors generate characteristic protein expression changes. This work further outlines a prototypical approach to derive and test protein expression signatures for drug action on signaling networks.

Fig. 1.

Activation and inhibition of EGFR in A431 cells. A431 cells were serum-starved overnight before being treated with either 30 nm EGF (lanes E) for 4 h or co-treated first with cetuximab (A) or gefitinib (B) at the indicated concentrations for 30 min prior to 4 h of treatment with EGF. Proliferating cells (lanes P) were not serum-starved and serve as a reference control. Immunoblots were performed for total EGFR, sites of EGFR phosphorylation at Tyr(P)-1173 and Tyr(P)-998, and total tyrosine phosphorylation was detected with the 4G10 antibody. β-Actin was used as a loading control.

Fig. 2.

Filtering and comparison of A431 proteome data sets. Colored rectangles show protein identifications from global proteomic analyses of the four treatment groups. Dashed rectangles show number of proteins in comparison data sets that were filtered to have ≥11 spectral counts/protein across replicates. Comparisons of protein spectral counts between treatment groups were performed by quasi-likelihood analysis, and a p value and spectral count rate ratio (fold change) were generated. The colored circles represent lists of proteins differentially expressed (both up and down) between treatments with a fold change of ≥2.0 and quasi p values of ≤0.20. The resulting protein groups represent proteins differentially expressed in response to EGF (blue), EGF-induced protein changes reversed by gefitinib (green), and EGF-induced protein changes reversed by cetuximab (yellow). The Venn diagram comparison indicates proteins whose expression changes are shared by the different experimental conditions. The central overlap indicates the “EGFR inhibition signature,” which refers to EGF-stimulated protein expression changes reversed by both inhibitors.

Fig. 3.

Normalized MRM data and spectral count correlation of EGFR inhibition signature proteins. Each panel shows both MRM data (red bar) and spectral count data (teal bar) for each protein of interest across four A431 cell treatment conditions: proliferating cells (P), EGF-treated (E), EGF and gefitinib (G+E), and EGF and cetuximab (C+E). The left y axis is the NPA, which is the total MRM transition peak area for the target peptide divided by the peak area for the β-actin-labeled reference peptide. MRM data are representative of one unique peptide for each target protein across three separate cultures. Spectral counts (SC) are the total number of spectra identified for each protein across replicate analyses. *, significant difference compared with EGF treated cells as determined by Student's two-tailed, unpaired t test.

Fig. 4.

Summary of expression changes for EGFR inhibition signature proteins in cell lines and mouse xenograft models. Symbol colors indicate decreased expression (green); increased expression (red); detected, but no significant change (black) compared with EGF treatment in cells (c) or compared with vehicle control in xenografts (x); and not detected (white). Only cetuximab treatment was used in xenograft experiments.

Fig. 5.

MRM analyses of EGFR inhibition signature proteins in tissue biopsies from a Ménétrier's disease patient treated with cetuximab. Gastric tissue biopsies were collected from three separate locations prior to treatment (baseline control) and at 1 day and 1 week after treatment with cetuximab. The NPA, which is the total MRM transition peak area for the target peptide divided by the peak area for the β-actin-labeled reference peptide. The data points are representative of three separate biopsies taken from a single patient with mean and standard deviation shown. *, significant difference between baseline and time post initial treatment as determined by Student's two-tailed t test.