Gene expression of the egf system—a prognostic model in non–small cell lung cancer patients without activating EGFR mutations

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Abstract

OBJECTIVES: Contradicting results have been demonstrated for the expression of the epidermal growth factor receptor (EGFR) as a prognostic marker in non–small cell lung cancer (NSCLC). The complexity of the EGF system with four interacting receptors and more than a dozen activating ligands is a likely explanation. The aim of this study is to demonstrate that the combined network of receptors and ligands from the EGF system is a prognostic marker. MATERIAL AND METHODS: Gene expression of the receptors EGFR, HER2, HER3, HER4, and the ligands AREG, HB-EGF, EPI, TGF-α, and EGF was measured by quantitative polymerase chain reaction in tumor samples from 100 NSCLC patients without EGFR activating mutations. Results were dichotomized into high or low levels of target expression. Coexpression of the ligands and receptors was observed, and a score was developed based on the summed effect of receptors and ligands. Akaike’s information criteria selected the optimal score. Results were correlated with age, sex, stage, histology, performance status, and overall survival. RESULTS: Patients were randomly split 1:1 to create test and validation cohorts. In multivariate analyses, the only individual prognostic marker was EPI (hazard ratio[HR] 0.38[0.20-0.72], P = .003). The optimal score in the test cohort was validated as a marker of inferior survival in the validation cohort and by bootstrapping. Multivariate analysis confirmed the combined score as a prognostic marker of inferior survival (HR 3.75[2.17-6.47], P < .00001). CONCLUSION: Our study has developed a model that takes the complexity of the EGF system into account and shows that this model is a strong prognostic marker in NSCLC patients.

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Sandfeld-Paulsen, B., Folkersen, B. H., Rasmussen, T. R., Meldgaard, P., & Sorensen, B. S. (2016). Gene expression of the egf system—a prognostic model in non–small cell lung cancer patients without activating EGFR mutations. Translational Oncology, 9(4), 306–312. https://doi.org/10.1016/j.tranon.2016.05.002

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