Abstract

BACKGROUND: Nectin-4 is overexpressed in several human malignant tumors. This study aimed to investigate the expression of Nectin-4 in esophageal cancer tissues compared with adjacent normal esophageal tissue and its association with clinicopathological parameters and prognosis.

MATERIAL AND METHODS: Nectin-4 expression in esophageal cancer tissues was compared with adjacent normal esophageal tissue from 94 patients using immunohistochemistry, Western blot, and quantitative reverse transcription-polymerase chain reaction (RT-qPCR). The chi-squared (χ²) test and Fisher’s exact test compared categorical variables. The log-rank test and Kaplan-Meier survival analysis assessed the relationship between Nectin-4 expression and overall survival (OS). Univariate and multivariate Cox proportional risk models compared Nectin-4 expression, patient prognosis, and clinicopathological parameters.

RESULTS: Nectin-4 expression was significantly increased in esophageal cancer tissue compared with normal tissue (P<0.001), tumor size ≥4.5 cm, and tumor invasion in T3/T4 compared with T1/T2 stage. Kaplan-Meier survival analysis showed that the OS of patients with increased Nectin-4 expression was significantly reduced compared with patients with low levels of Nectin-4 expression. Patient prognosis in men was less than women, tumor diameter ≥4.5 cm, lymph node involvement, and depth of invasion were associated with poor prognosis. Independent prognostic factors were Nectin-4 expression, lymph node involvement, and depth of invasion.

CONCLUSIONS: In patients with esophageal cancer, the expression levels of Nectin-4, lymph node involvement, and depth of tumor invasion were independent prognostic factors. Further studies should be performed to evaluate the diagnostic and prognostic roles of Nectin-4 and its potential role as a therapeutic target.

Keywords: Carcinoma, Esophageal Neoplasms, Tumor Markers, Biological, Cell Adhesion Molecules, Esophagus, Gene Expression Regulation, Neoplastic, Middle Aged, Prognosis, Proportional Hazards Models, Survival Analysis