Evaluation of the cyclin-dependent kinase inhibitor p21Cip1 in epithelial ovarian tumors of low malignant potential and adenocarcinomas

Abstract

Objective: In view of the controversial information on the significance of the cyclin-dependent kinase inhibitor p21Cip1 in ovarian cancer, we conducted a retrospective investigation to clarify the relationships of this protein to proliferation rate, clinicopathological variables and prognosis of epithelial ovarian tumors. Methods: Paraffin-embedded tissue from 43 ovarian tumors of low malignant potential (LMP) and 82 primary ovarian adenocarcinomas were stained immunohistochemically for p21Cip1, p53 protein and Ki- 67 antigen (a marker of cell proliferation). Results: p21Cip1 levels were significantly higher in LMP tumors (p<0.001) as well as in early stage adenocarcinomas (p=0.021) and those associated with minimal residual disease (p=0.008). However, no relationship existed between p21Cip1 expression and the proliferation rate of adenocarcinomas or LMP tumors. In the vast majority of LMP tumors p21Cip1 expression was not accompanied by p53 accumulation. This p21Cip1-positive/p53-negative phenotype prevailed in the early stage (p=0.026), lower grade (p=0.018) adenocarcinomas as well as in those left with minimal residual disease (p=0.059). In patients with lower grade adenocarcinomas, decreased p21Cip1 expression was adversely related to poor overall survival on its own (p=0.0500) and when combined with p53 protein overexpression (p=0.0323). In multivariate analysis, only the stage remained as the independent predictor of survival. Conclusions: Decreased p21Cip1 expression is related to several indicators of aggressiveness in ovarian adenocarcinomas and seems to be differentially regulated in LMP tumors and adenocarcinomas. On the contrary, deregulation of p21Cip1 expression does not seem to participate in the pathogenesis of LMP tumors. Furthermore, although p21Cip1 alone or combined with p53 is of prognostic significance in lower grade adenocarcinomas, it does not appear to add to the information gained from traditional prognosticators.