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Updated: Feb 10, 2026

An Orthotopic Model of Serous Ovarian Cancer in Immunocompetent Mice for in vivo Tumor Imaging and Monitoring of Tumor Immune Responses
Published on: November 28, 2010
Increased Expression of Holliday Junction-Recognizing Protein (HJURP) as an Independent Prognostic Biomarker in
Abstract:
BACKGROUND Advanced-stage serous ovarian carcinoma results in the majority of deaths from ovarian carcinoma. The histone chaperone, Holliday junction-recognizing protein (HJURP), binds with centromere protein-A (CENP-A) and its expression has been shown to be a prognostic biomarker in some cancers. The aim of this study was to investigate the role of HJURP expression in advanced-stage serous ovarian carcinoma. MATERIAL AND METHODS Ninety-eight patients with advanced-stage serous ovarian carcinoma, who had tumor tissue samples available, were studied. Expression levels of HJURP were detected using immunohistochemistry (IHC) and were correlated with HJURP expression and patient clinicopathological factors. Fisher's correlation coefficient, Kaplan-Meier survival curves, the log-rank test, and Cox's regression proportional hazards model were performed to analyze the significance of factors affecting survival rate and independent prognostic factors. RESULTS Increased expression levels of HJURP in advanced-stage serous ovarian carcinoma were found in 33.67% (33/98) of cases; low expression levels of HJURP were found in 66.33% (65/98) of cases. High expression levels of HJURP were significantly associated with lymph node metastases (P=0.018), and lower overall survival (P=0.002). HJURP expression was identified as an independent prognostic biomarker for patients with advanced serous ovarian cancer in this study group of 98 patients (P=0.013). CONCLUSIONS Increased expression of HJURP was identified as an independent negative prognostic biomarker for patients with advanced serous ovarian cancer in this study. Further studies are required to determine whether HJURP expression in serous ovarian carcinoma may have a role in guiding clinical management by stratifying patients according to risk.
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