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Dis Esophagus ; 29(6): 621-6, 2016 Aug.
Article in English | MEDLINE | ID: mdl-25951709

ABSTRACT

In the present study, we aimed to evaluate the expression of special AT-rich sequence-binding protein 1 (SATB1) in esophageal squamous cell carcinoma (ESCC) and assess the correlation between its expression and the clinicopathological features and prognosis of the disease. SATB1 expression in ESCC tissue was determined by using immunohistochemical analysis, quantitative real-time polymerase chain reaction, and western blot analysis. The relationship between SATB1 expression and clinicopathological features was examined by using the chi-squared test, and the survival rate was calculated by using the Kaplan-Meier survival curve. The correlation between the indicators and patient survival was estimated by using a Cox regression analysis. High SATB1 expression in was detected in 48.3% and 7.8% of ESCC and normal esophagus tissues (P < 0.05), respectively. SATB1 expression did not significantly correlate with clinicopathological features. The Kaplan-Meier curve indicated that patients with high SATB1 expression had significantly shorter survival than those with low SATB1 expression. In a multivariate Cox regression model, high SATB1 expression was identified as an independent prognostic factor for patients with ESCC. In conclusion, these results suggest that high SATB1 expression is predictive of poor prognosis in ESCC and may be a promising new candidate for targeted therapies for ESCC.


Subject(s)
Carcinoma, Squamous Cell/genetics , Esophageal Neoplasms/genetics , Matrix Attachment Region Binding Proteins/genetics , RNA, Messenger/metabolism , Adult , Aged , Blotting, Western , Carcinoma, Squamous Cell/metabolism , Carcinoma, Squamous Cell/mortality , Esophageal Neoplasms/metabolism , Esophageal Neoplasms/mortality , Esophageal Squamous Cell Carcinoma , Female , Humans , Immunohistochemistry , Kaplan-Meier Estimate , Male , Matrix Attachment Region Binding Proteins/metabolism , Middle Aged , Multivariate Analysis , Pilot Projects , Prognosis , Proportional Hazards Models , Real-Time Polymerase Chain Reaction , Retrospective Studies
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