TaqMan ® Low-Density Arrays and Analysis by Artificial Neuronal Networks Predict Response to Neoadjuvant Chemoradiation in Esophageal Cancer

Abstract

Neoadjuvant radiochemotherapy of locally advanced esophageal cancer is only effective for patients with major histopathological response. A total of 17 genes were selected to predict histopathologic tumor response to chemoradiation (cisplatin, 5-fluorouracil, 36 Gy). For gene-expression analysis quantitative TaqMan low-density arrays were applied. Expression levels in pretreatment biopsies of 41 patients (cT2-4, Nx, M0) were compared with the degree of histopathologic regression in resected specimens applying univariate, multivariate and artificial neuronal network analyses. Dihydropyrimidine dehydrogenase was identified as an independent predictor associated with major response (p < 0.002). Multivariate analysis of the marker combination provided response prediction with 75.0% sensitivity, 81.0% specificity and 78.1% accuracy. Artificial neuronal network analysis was the best predictive model for major histopathologic response (80% sensitivity, 90.5% specificity and 85.4% accuracy), representing a clinically practical system. Low-density-array RT-PCR analyzed by artificial neuronal network predicts histopathologic response to neoadjuvant chemoradiation in our patient collective, and could be used to further individualize treatment strategies in esophageal cancer.