A preoperative model evaluating the tissue effects of chemopreventive agents in low-volume prostate cancer

Abstract

1007 Background: To identify and assess biomarkers modulated by prostate cancer chemopreventive agents, we created a model that, by exploiting the time between histologic diagnosis of prostate cancer and definitive therapy (prostatectomy), expedites tissue cross comparison and confronts the multifocality and multizonal heterogeneity of prostate cancer. Methods: Between February 2001 and April 2002, 48 presurgical patients were enrolled in a single-institution, randomized, double-blind trial of vitamin E (VE) and L-selenomethionine (SeMET) based on the framework of the ongoing Selenium and Vitamin E Cancer Prevention Trial. Patients were treated with 400 IU VE, 200 μg SeMET, a combination of VE and SeMET, or placebo for 3 to 6 weeks before prostatectomy. All patients also received a multivitamin and vitamin C 250 mg each day. Ex vivo simulated sextant biopsies on the radical prostatectomy specimen (RPS) were performed, and 36 of 39 evaluable patients had RPS sections that were suitable for pathologic evaluation. Blood components were collected at baseline and prior to prostatectomy. We derived an apoptotic index (AI) morphologically and a proliferation index (PI) by using immunohistochemistry and counting Ki-67-positive nuclei. Cells were counted and identified by cell type (normal and cancerous) and by zone (peripheral [PZ], transition [TZ], and central [CZ]). Results: In normal epithelial cells when the Wilcoxon rank sum test was used to compare AI and PI changes between groups, the AI was higher in the TZ than in the CZ, a difference independent of treatment effects (p = .01). Between the largest PZ and TZ tumor foci, a statistically significant difference in PI was observed (p = .006). Using a multiple linear regression model fitted for AI from the largest RPS PZ tumor focus, we found a statistically significant difference between the SeMET group and the placebo group (p = .02). Conclusions: Besides introducing new findings, the clinicopathologic model proved itself a platform for biomarker discovery by leveraging molecular technologies to full advantage, including serum protein profiling (Kim et al., CEBP 2005) and gene expression profiling of different cell types. Supported by NIH grant CA88761. No significant financial relationships to disclose.