Research Article

Significance of Ebp1 and p53 protein expression in cervical cancer

Published: October 02, 2015
Genet. Mol. Res. 14 (4) : 11860-11866 DOI: 10.4238/2015.October.2.19

Abstract

In this study, the ErbB3-binding protein (Ebp1) and p53 protein expression in cervical cancer tissues, and its significance in the prognosis of the disease was investigated. Ebp1 and p53 protein expression was detected by immunohistochemical analysis in cervical cancer tissues (N = 60) and normal tissues adjacent to the cancer tissues (N = 60). The rates of positive Ebp1 and p53 protein expression were 35.0 and 60.0%, respectively. Ebp1 and p53 were overexpressed in cervical cancer tissues, compared to normal tissues (P 0.05). Ebp1 and p53 protein expression was not correlated with age, tumor size, or family tumor history (P > 0.05). However, high levels of expression of Ebp1 and p53 were positively correlated with the TNM stage and lymphatic metastasis in cervical cancer patients (P 0.05). The combined determination of Ebp1 and p53 expression levels in cervical cancer patients could support the effective prediction of metastatic potential and patient prognosis.

In this study, the ErbB3-binding protein (Ebp1) and p53 protein expression in cervical cancer tissues, and its significance in the prognosis of the disease was investigated. Ebp1 and p53 protein expression was detected by immunohistochemical analysis in cervical cancer tissues (N = 60) and normal tissues adjacent to the cancer tissues (N = 60). The rates of positive Ebp1 and p53 protein expression were 35.0 and 60.0%, respectively. Ebp1 and p53 were overexpressed in cervical cancer tissues, compared to normal tissues (P < 0.05). Ebp1 and p53 protein expression was not correlated with age, tumor size, or family tumor history (P > 0.05). However, high levels of expression of Ebp1 and p53 were positively correlated with the TNM stage and lymphatic metastasis in cervical cancer patients (P < 0.05). The combined determination of Ebp1 and p53 expression levels in cervical cancer patients could support the effective prediction of metastatic potential and patient prognosis.