RESUMO
To examine the expression of vasohibin-1, metastasis-associated in colon cancer-1 (MACC1) and KAI1 proteins in serous ovarian cancer and their clinical significance. Methods: In 124 specimens of serous ovarian cancer (serous ovarian cancer group) and 30 specimens of ovarian serous cystadenoma (ovarian serous cystadenoma group), the expression of vasohibin-1, MACC1 and KAI1 protiens were detected by immunohistochemistry ElivisionTM method. Results: In the serous ovarian cancer group, the positive rates of vasohibin-1 and MACC1 proteins were 48.4% and 58.1%, respectively, which were both higher than those in the ovarian serous cystadenoma group (10.0% and 13.3%, respectively); while the positive rate of KAI1 protein in the serous ovarian cancer group was 33.9%, which was lower than that in the ovarian serous cystadenoma group (86.7%), there were significant differences between the 2 groups (all P<0.05). In the serous ovarian cancer group, the expression of the 3 proteins were closely related to the pathological grade, Federation International of Gynecology and Obstetrics (FIGO) stage and pelvic lymph node metastasis (all P<0.05). The KAI1 protein was negatively correlated with the levels of vasohibin-1 and MACC1 (r=-0.500, -0.600, respectively, both P<0.01); while there was a positive correlation between the vasohibin-1 and the MACC1 (r=0.518, P<0.01). Kaplan-Meier survival analysis showed that the over-expression of vasohibin-1, MACC1 and the low-expression of KAI1 protein were related to the survival rates (all P<0.05). Multi-factor analysis showed that the expression of vasohibin-1, KAI1 protein and the FIGO stage were independent prognosis factors for radical operation of serous ovarian cancer (RR=2.185, 3.893, 0.413; 95% CI=1.263-3.779, 2.190-6.921, 0.251-0.681; all P<0.05). Conclusion: The up-regulation of vasohibin-1, MACC1 and down-regulation of KAI1 in serous ovarian cancer are related to the tumor differentiation, clinical stage, metastasis and prognosis. Combined detection of these indexes is useful in predicting the progression and prognosis of serous ovarian cancer.