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Integration of Bioinformatics Approaches and Experimental Validations to Understand the Role of Notch Signaling in Ovarian Cancer
Published on: January 12, 2020
[Correlation of hK6 expression with clinicopathological features and prognosis in epithelial ovarian cancer]
Cheng-Jin Hu1, Fang Zhang, Ying-Jian Chen
1Department of Laboratory Medicine, General Hospital of Jinan Military Region, Jinan 250031, China. hcj90@263.net
Objective:
To approach the relationship between the expression of hK6 in ovarian neoplasm and clinicopathological variables and prognosis in ovarian cancer patients for finding a new tumor marker of the ovarian cancer.
Methods:
The expression of hK6 was detected by immunohistochemistry in 19 cases of benign, 11 cases of borderline and 45 cases of malignant ovarian neoplasms and statistically analyzed whether its expression correlate with clinicopathological variables and prognosis in patients with ovarian cancer.
Results:
The expression of hK6 in ovarian cancer tissues (60.0%) was significantly higher than that in the benign (15.8%) and borderline (27.3%) ovarian neoplasm tissues (P < 0.01). The expression of hK6 in higher-grade ovarian cancer tissues (68.4% ) was higher than that in low-grade ones (14.3%, P < 0.05). The expression of hK6 in late-stage (stage III, 76.7%) was significantly higher than that in early-stage (stage I or II, 26.7%, P < 0.01). The expression of hK6 was significantly higher in patients with lymph node metastasis (77.8%) than that in patients without (33.3%, P < 0.01). The expression of hK6 in the cancer tissues in the patients died, or with reccurence or metastasis within 3 years after surgery was higher (75.0%) than that in the patients with stable disease (42.9%, P < 0.05).
Conclusion:
The expression of hK6 in ovarian cancer was higher than that in benign and borderline ovarian neoplasms. The expression of hK6 is higher in the ovarian cancer of late stage, higher-grade, with lymph node metastasis and is associated with a poorer prognosis. hK6 may become a new markers in prediction of prognosis of the patients with ovarian tumors.
