Steroidogenic Germline Polymorphism Predictors of Prostate Cancer Progression in the Estradiol Pathway

Purpose: Reliable biomarkers that predict prostate cancer outcomes are urgently needed to improve and personalize treatment approaches. With this goal in mind, we individually and collectively appraised common genetic polymorphisms related to estradiol metabolic pathways to find prostate cancer prognostic markers. Methods: The genetic profiles of 526 men with organ-confined prostate cancer were examined to find common genetic polymorphisms related to estradiol metabolic pathways and these findings were replicated in a cohort of 213 men with more advanced disease (follow-up time for both cohorts, >7.4 years). Specifically, we examined 71 single-nucleotide polymorphisms (SNP) in SULT2A1, SULT2B1, CYP1B1, COMT, CYP3A4, CYP3A5, CYP3A43, NQO1, and NQO2 and assessed the impact of the SNPs alone and in combination on prostate cancer progression and on circulating hormone levels. Results: According to a multivariate analysis, CYP1B1 (rs1800440), COMT (rs16982844), and SULT2B1 (rs12460535, rs2665582, rs10426628) were significantly associated with prostate cancer progression and hormone levels. Remarkably, by combining the SNP information with previously identified HSD17B2 markers, the patients could be stratified into four distinct prognostic subgroups. The most prominent association was observed for the eight-marker combination [CYP1B1 (rs1800440), SULT2B1 (rs12460535, rs2665582, and rs10426628), and HSD17B2 (rs4243229, rs1364287, rs2955162, and rs1119933)]. Conclusion: This study identified specific germline variations in estradiol metabolism–related pathways, namely CYP1B1, SULT2B1, and HSD17B2, as novel prognostic markers that are cumulatively associated with increased risk of prostate cancer progression. This panel of markers warrants additional investigation and validation to help stratify patients according to their risk of progression. Clin Cancer Res; 20(11); 2971–83. ©2014 AACR.