Abstract. Huang C-N, Huang S-P, Pao J-B, Hour T-C, Chang T-Y, Lan Y-H, Lu T-L, Lee H-Z, Juang S-H, Wu P-P, Huang C-Y, Hsieh C-J, Bao B-Y (Kaohsiung Medical University Hospital, Kaohsiung; Kaohsiung Medical University, Kaohsiung; Taipei City Hospital, Taipei; Kaohsiung Medical University, Kaohsiung; China Medical University, Taichung; National Taiwan University Hospital; Oriental Institute of Technology; National Taiwan University, Taipei; China Medical University Hospital, Taichung, Taiwan). Genetic polymorphisms in oestrogen receptor-binding sites affect clinical outcomes in patients with prostate cancer receiving androgen-deprivation therapy. J Intern Med 2012; 271: 499–509.
Background. Accumulating evidence indicates that oestrogens have significant direct effects on normal prostate development and carcinogenesis. The majority of the biological activities of oestrogens are mediated through the oestrogen receptor (ER), which functions as a hormone-inducible transcription factor to regulate target gene expression by binding to oestrogen response elements (EREs) in the regulatory regions of target genes. Sequence variants in EREs might affect the ER–ERE interaction and subsequent physiological activities. Therefore, we tested whether common single-nucleotide polymorphisms (SNPs) inside EREs are related to the clinical outcomes of androgen-deprivation therapy (ADT) in men with prostate cancer.
Methods. We systematically evaluated 49 ERE SNPs predicted using a genome-wide database in a cohort of 601 men with advanced prostate cancer treated with ADT. The prognostic significance of these SNPs on disease progression, prostate cancer-specific mortality (PCSM) and all-cause mortality (ACM) after ADT was assessed using Kaplan–Meier analysis and a Cox regression model.
Results. Based on multiple hypothesis testing, BNC2 rs16934641 was found to be associated with disease progression; in addition, TACC2 rs3763763 was associated with PCSM, and ALPK1 rs2051778 and TACC2 rs3763763 were associated with ACM. These SNPs remained significant in multivariate analyses that included known clinicopathological predictors. Moreover, a combined genotype effect on ACM was observed when ALPK1 rs2051778 and TACC2 rs3763763 were analysed in combination. Patients with a greater number of unfavourable genotypes had a shorter time to ACM during ADT (P for trend <0.001).
Conclusion. The incorporation of ERE SNPs into models with known predictors might improve outcome prediction in patients with prostate cancer receiving ADT.