A Molecular Prognostic Model Predicts Esophageal Squamous Cell Carcinoma Prognosis

BACKGROUND: Esophageal squamous cell carcinoma (ESCC) has the highest mortality rates in China. The 5-year survival rate of ESCC remains dismal despite improvements in treatments such as surgical resection and adjuvant chemoradiation, and current clinical staging approaches are limited in their ability to effectively stratify patients for treatment options. The aim of the present study, therefore, was to develop an immunohistochemistry-based prognostic model to improve clinical risk assessment for patients with ESCC. METHODS: We developed a molecular prognostic model based on the combined expression of axis of epidermal growth factor receptor (EGFR), phosphorylated Specificity protein 1 (p-Sp1), and Fascin proteins. The presence of this prognostic model and associated clinical outcomes were analyzed for 130 formalin-fixed, paraffin-embedded esophageal curative resection specimens (generation dataset) and validated using an independent cohort of 185 specimens (validation dataset). RESULTS: The expression of these three genes at the protein level was used to build a molecular prognostic model that was highly predictive of ESCC survival in both generation and validation datasets (P = 0.001). Regression analysis showed that this molecular prognostic model was strongly and independently predictive of overall survival (hazard ratio = 2.358 [95% CI, 1.391–3.996], P = 0.001 in generation dataset; hazard ratio = 1.990 [95% CI, 1.256–3.154], P = 0.003 in validation dataset). Furthermore, the predictive ability of these 3 biomarkers in combination was more robust than that of each individual biomarker. CONCLUSIONS: This technically simple immunohistochemistry-based molecular model accurately predicts ESCC patient survival and thus could serve as a complement to current clinical risk stratification approaches.