The V109G polymorphism of the p27 gene CDKN1B indicates a worse outcome in node-negative breast cancer patients.

Although p27 plays a central role in cell cycle regulation, its role in breast cancer prognosis is controversial. Furthermore, the p27 gene CDKN1B carries a polymorphism with unknown functional relevance. This study was designed to evaluate p27 expression and p27 genotyping with respect to early breast cancer prognosis. 279 patients with infiltrating metastasis-free breast cancer were included in this study. p27 expression was determined in tumor tissue specimens from 261 patients by immunohistochemistry. From 108 patients, the CDKN1B genotype was examined by PCR and subsequent direct sequencing. 55.2% of the tumors were considered p27 positive. p27 expression did not correlate with any of the established parameters except for nodal involvement but significantly correlated to prolonged disease-free survival. In 35% of the tumors analyzed, the CDKN1B gene showed a polymorphism at codon 109 (V109G). The V109G polymorphism correlated with greater nodal involvement. In the node-negative subgroup, V109G correlated significantly with a shortened disease-free survival. In conclusion, the determination of the CDKN1B genotype might be a powerful tool for the prognosis of patients with early breast cancer.

High apoptotic index correlates to p21 and p27 expression indicating a favorable outcome of primary breast cancer patients, but lacking prognostic significance in multivariate analysis.

This study was performed in order to investigate the role of the apoptotic index (AI) as a prediction parameter for the prognosis of patients with primary breast cancer. AI was determined by DNA fragmentation on 298 primary breast cancer samples and compared to clinically established breast cancer parameters. Additionally, we determined the expression of functional parameters including proliferating cell nuclear antigen, p21waf and p27kip by immunohistochemistry. The mean AI was found to be 11.9% (range, 0-90%). 189 tumors (63.4%) were negative for apoptosis, while 109 tissue samples (36.6%) were apoptotic with >5% positive cells. Using univariate analysis (chi2 test), the AI did not show any significant correlation to one of the established prognostic parameters of primary breast cancer (p > 0.05). In contrast, we found a significant positive correlation to the expression of the cell cycle inhibitors p21waf (p = 0.04) and p27kip (p = 0.024). During the clinical follow-up (median observation time for disease-free survival 87 months), several clinically established prognostic parameters including menopausal status, nodal status, tumor size, tumor grade, and hormone receptor expression could be confirmed and were analyzed with respect to the AI in the tumor. Furthermore, AI displayed a significant positive correlation to disease-free survival using Kaplan-Meier survival analysis (log-rank test, p = 0.04). However, AI lost its prognostic significance in multivariate analysis based on the Cox proportional hazard model (relative risk 0.8, confidence interval 0.52-1.33, p = 0.44). Our data indicate that high apoptotic rates in cancer tissues are indicative of a favorable patient outcome. However, the AI was not an independent factor. The study provides indirect evidence that this process may involve cell cycle inhibitors physiologically.