Overexpression of Nuclear Protein Kinase CK2 [beta] Subunit and Prognosis in Human Gastric Carcinoma

• Published in: Annals of surgical oncology Vol. 17; no. 6; p. 1695
• Main Authors: Lin, Kai-yuan, Fang, Chia-lang, Chen, Yi, Li, Chien-feng, Chen, Sheng-hsuan, Kuo, Chen-yi, Tai, Chein, Uen, Yih-huei
• Format: Journal Article
• Language: English
• Published: New York Springer Nature B.V 01.06.2010
• ISSN: 1068-9265; 1534-4681
• DOI: 10.1245/s10434-010-0911-9

Gastric carcinoma is one of the most common malignancies in the world, yet little is known about the molecular process of its development and progression. The aims of this study are to correlate the expression of nuclear protein kinase CK2 β subunit (CK2β) with clinicopathologic parameters and patient survival. Expression levels of nuclear CK2β were analyzed in 104 gastric tissues from patients with gastric carcinoma by immunohistochemistry. A paired t test was used to analyze the differences in nuclear CK2β expression between tumor and nontumor tissues in the same patient. A two-tailed χ ^sup 2^ test was performed to determine the significance of the difference between nuclear CK2β expression and clinicopathologic parameters. All time-to-event endpoints according to various clinicopathologic parameters were plotted by Kaplan-Meier method, and significance was then determined by univariate log-rank test. Cox proportional-hazards model was used for multivariate analysis to determine the independence of prognostic impact of nuclear CK2β expression. Overexpression of nuclear CK2β was significantly correlated with depth of invasion (P = 0.042). Patients with high expression levels of nuclear CK2β had a significantly poorer overall survival rate compared with patients with low expression levels of nuclear CK2β (P = 0.0006). On multivariate Cox regression analysis, overexpression of nuclear CK2β and stage were proven to be independent prognostic markers for gastric carcinoma (P = 0.0036 and 0.0005, respectively). Overexpression of nuclear CK2β can be a useful marker for predicting the outcome of patients with gastric carcinoma.[PUBLICATION ABSTRACT]