Loss of the cell adhesion molecule E-cadherin is suggested to promote tumor invasion and distant metastasis in tumor development. Recently, it has been proposed that E-cadherin function requires its linkage to the cytoskeleton through catenins. We evaluated the expression of E-cadherin and α-, β-, and γ-catenins in tissues of human endometrial carcinoma, analyzed the patterns of cell adhesion molecules' expression in endometrial carcinoma and investigated the relationship between the statuses of cell adhesion molecules and various clinicopathological factors. This study investigated the immunohistochemical expression of E-cadherin and a-, β-, and γ-catenins in 33 paraffin embedded formalin fixed tissues of endometrial carcinomas. Aberrant E-cadherin, and a-, β-, and γ-catenin expression was observed in 33.3 (11 of 33), 27.3 (9 of 33), 18.2 (6 of 33), and 51.5 (17 of 33) % of the specimens, respectively. Statistically significant correlation was found between aberrant expression of E-cadherin and lymph node metastasis and cell types other than endometrioid adenocarcinoma. Aberrant pattern of γ-catenin expression was also correlated with deep myometrial invasion. However, α-, and β-catenin expression was not correlated with any clinico-pathological parameters. Using the Kaplan-Meier method and log-rank comparison test, abnormal expression of E-cadherin was correlated closely with poor survival (p<0.05), but cases with loss of both E-cadherin and catenin expression predicted even poorer survival than cases with only one or no aberrant expression in E-cadherin and catenins. We revealed aberrant expression of these cell adhesion molecules among patients with endometrial carcinoma. Aberrant expression of E-cadherin was correlated with lymph node metastasis and cell types other than endometrioid adenocarcinoma, while aberrant expression of γ-catenin was related with deep myometrial invasion. The expression of E-cadherin might be a possible prognostic factor for endometrial cancer while the expression of catenins may help predict patient's survival.
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