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Diagnostic and Prognostic Significance of Ki-67 Immunohistochemical Expression in Surface Epithelial Ovarian
Asha Mahadevappa1, Shruthi Mysore Krishna2, Manjunath Gubbanna Vimala3
1Associate Professor, Department of Pathology, JSS Medical College, JSS University , Mysuru, Karnataka, India .
Introduction:
The Surface Epithelial Ovarian Carcinoma (SEOC) at the moment of diagnosis, the disease is extended beyond the structures of the pelvis. Ki-67 is one of the prognostic marker which determines the growth fraction of a tumour and its over expression is associated with malignancy, tumour aggression, reserved prognosis and metastasis.
Aim:
To evaluate the proliferative activity using Ki-67 immuno-staining in SEOC and to correlate with histological subtype, grade, Federation of Gynecology and Obstetrics (FIGO) stage, CA125 levels for diagnostic and prognostic purpose.
Materials And Methods:
The study was conducted in JSS Medical College and Hospital, JSS University, Mysuru. It was a descriptive cross-sectional study involving 40 cases of SEOC over a period of two years. The proliferation expression related to Ki-67 antigen was evaluated by immunohistochemical monoclonal MIB-1 antibody. In each case, the Ki-67 labeling index (Ki-67 LI) was articulated as percentage of positively stained cells using high power objective of the microscope (x400).
Results:
Among the 40 carcinomas, 26 were serous, five mucinous, four each of clear cell and undifferentiated and one transitional cell carcinoma. A total of 75% were high grade tumours. High Ki-67 LI was associated with high grade tumours (69.9%), high grade serous tumours (65.34%) and advanced FIGO staging (70.6%) with the p-value of <0.001. CA 125 levels did not have a significant correlation with Ki-67 LI.
Conclusion:
Ki-67 is an exceptionally a cost effective marker to determine the growth fraction of a tumour cell population. In SEOC histological grade and FIGO stage when combined with Ki-67 LI in histopathology report would help in diagnostic differentiation of subtypes, prognostication, deciding the need for adjuvant chemotherapy and in predicting survival analysis.