Single and Multigenic Analysis of the Association between Variants in 12 Steroid Hormone Metabolism Genes and Risk of Prostate Cancer

Department of Cellular and Structural Biology, The University of Texas Health Science Center, San Antonio, Texas 78229-3900, USA.
Cancer Epidemiology Biomarkers & Prevention (Impact Factor: 4.32). 06/2009; 18(6):1869-80. DOI: 10.1158/1055-9965.EPI-09-0076
Source: PubMed

ABSTRACT To estimate the prostate cancer risk conferred by individual single nucleotide polymorphisms (SNPs), SNP-SNP interactions, and/or cumulative SNP effects, we evaluated the association between prostate cancer risk and the genetic variants of 12 key genes within the steroid hormone pathway (CYP17, HSD17B3, ESR1, SRD5A2, HSD3B1, HSD3B2, CYP19, CYP1A1, CYP1B1, CYP3A4, CYP27B1, and CYP24A1). A total of 116 tagged SNPs covering the group of genes were analyzed in 2,452 samples (886 cases and 1,566 controls) in three ethnic/racial groups. Several SNPs within CYP19 were significantly associated with prostate cancer in all three ethnicities (P = 0.001-0.009). Genetic variants within HSD3B2 and CYP24A1 conferred increased risk of prostate cancer in non-Hispanic or Hispanic Caucasians. A significant gene-dosage effect for increasing numbers of potential high-risk genotypes was found in non-Hispanic and Hispanic Caucasians. Higher-order interactions showed a seven-SNP interaction involving HSD17B3, CYP19, and CYP24A1 in Hispanic Caucasians (P = 0.001). In African Americans, a 10-locus model, with SNPs located within SRD5A2, HSD17B3, CYP17, CYP27B1, CYP19, and CYP24A1, showed a significant interaction (P = 0.014). In non-Hispanic Caucasians, an interaction of four SNPs in HSD3B2, HSD17B3, and CYP19 was found (P < 0.001). These data are consistent with a polygenic model of prostate cancer, indicating that multiple interacting genes of the steroid hormone pathway confer increased risk of prostate cancer.

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Available from: Jonathan Gelfond, Jul 28, 2015
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    • "Mixed A119S , L432V Sobti et al . 2006 India 100 100 Asian L432V Cussenot et al . 2007 French 1053 837 Caucasian L432V Berndt et al . 2007 USA 488 617 Mixed R48G , L432V , N453S Beuten et al . 2008 USA 153 240 Hispanic Caucasian 213C / T . R48G , L432V , N453S Beuten et al . 2008 USA 496 498 Non - Hispanic Caucasian 213C / T . R48G , L432V , N453S Beuten et al . 2009 USA 67 133 African American R48G Rodrigues et al . 2011 Brazil 154 154 Caucasian A119S Catsburg et al . 2012 USA 1419 756 Mixed L432V Holt et al . 2013 USA 1304 1266 Caucasian L432V doi : 10 . 1371 / journal . pone . 0068634 . t001"
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    ABSTRACT: Studies investigating the association between single-nucleotide polymorphisms (SNPs) of the cytochrome P450 1B1 (CYP1B1) and prostate cancer (PCa) risk report conflicting results. To derive a more precise estimation of the relationship between CYP1B1 polymorphisms and PCa risk, a meta-analysis was performed. A comprehensive literature search was conducted to identify all eligible studies of CYP1B1 polymorphisms and PCa risk. A total of 14 independent studies, including 6380 cases and 5807 controls, were identified. We investigated by meta-analysis the effects of 5 polymorphisms in CYP1B1 L432V (12 studies, 5999 cases, 5438 controls), R48G (6 studies, 1647 cases, 1846 controls), N453S (4 studies, 1407 cases, 1499 controls), -13C/T (4 studies, 1116 cases, 1114 controls), and A119S (4 studies, 1057 cases, 1018 controls). There was no evidence that L432V had significant association with PCa in overall population. After subgroup analyses by ethnicity, we found that L432V was significantly associated with PCa risk in Asians (additive: OR = 2.38, 95%CI = 1.31-4.33, P = 0.004; recessive: OR = 2.11, 95%CI = 1.17-3.79, P = 0.01; dominant: OR = 1.52, 95%CI = 1.14-2.01, P = 0.004; allelic: OR = 1.52, 95%CI = 1.20-1.92, P = 0.0006). When stratified by source of controls, significantly elevated PCa risk was found in all genetic models in population based studies (additive: OR = 1.34, 95%CI = 1.14-1.57, P = 0.0003; recessive: OR = 1.25, 95%CI = 1.09-1.43, P = 0.002; dominant: OR = 1.25, 95%CI = 1.11-1.41, P = 0.0002; allelic: OR = 1.18, 95%CI = 1.09-1.28, P<0.0001). For N453S, there was a significant association between N453S polymorphism and PCa risk in both overall population (dominant: OR = 1.18, 95%CI = 1.00-1.38, P = 0.04) and mixed population (domiant: OR = 1.31, 95%CI = 1.06-1.63, P = 0.01; allelic: OR = 1.27, 95%CI = 1.05-1.54, P = 0.01). For A119S, our analysis suggested that A119S was associated with PCa risk under recessive model in overall population (OR = 1.37, 95%CI = 1.04-1.80, P = 0.03). The results suggest that L432V, N453S, and A119S polymorphisms of CYP1B1 might be associated with the susceptibility of PCa. Further larger and well-designed multicenter studies are warranted to validate these findings.
    PLoS ONE 07/2013; 8(7):e68634. DOI:10.1371/journal.pone.0068634 · 3.53 Impact Factor
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    • "CYP3A4*1B has a higher frequency in men from African descent than Caucasian and is absent in Asian men [121] [122] [123] [124] [125], but case-control studies didn't find an association between CYP3A4*1B and PCa risk in men of African descent who had a high frequency of the variant [78] [111] [124] [126]. In addition, reports in Caucasian men were contradictory [111] [124] [127]. Studies for the association between CYP3A4*1B and the progression of PCa were also inconclusive, some studies reported CYP3A4*1B is associated with aggressive PCa in Caucasian and African American men [122] [123] [125] [127] [128], however others studies disagreed [129] [130] [131]. "
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    ABSTRACT: Prostate cancer (PCa) is the most commonly diagnosed male malignancy and the second biggest cause of cancer death in men of the Western world. Higher incidences of PCa occur in men from North America, Oceania and Western countries, whereas men from Asia and North Africa have a much lower PCa incidence rate. Investigations into this population disparity of PCa incidence, in order to identify potential preventive factors or targets for the therapeutic intervention of PCa, have found differences in both environmental and genetic variations between these populations. Environmental variations include both diet and lifestyle, which vary widely between populations. Evidence that diet comes into play has been shown by men who immigrate from Eastern to Western countries. PCa incidence in these men is higher than men in their native countries. However the number of immigrants developing PCa still doesn't match native black/white men, therefore genetic factors also contribute to PCa risk, which are supported by familial studies. There are a number of genetic polymorphisms that are differentially presented between Western and Eastern men, which are potentially associated with PCa incidence. Androgen and its receptor (AR) play a major role in PCa development and progression. In this study, we focus on genes involved in androgen biosynthesis and metabolism, as well as those associated with AR pathway, whose polymorphisms affect androgen level and biological or physiological functions of androgen. While many of the genetic polymorphisms in this androgen/AR system showed different frequencies between populations, contradictory evidences exist for most of these genes investigated individually as to the true contribution to PCa risk. More accurate measurements of androgen activity within the prostate are required and further studies need to include more African and Asian subjects. As many of these genetic polymorphisms may contribute to different steps in the same biological/physiological function of androgen and AR pathway, an integrated analysis considering the combined effect of all the genetic polymorphisms may be necessary to assess their contribution to PCa initiation and progression.
    American Journal of Cancer Research 01/2013; 3(2):127-151. · 3.97 Impact Factor
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    • "Both genes are related to the balance of androgen and estrogen in the prostate gland, which play a significant role for maintaining prostate health (Carruba, 2007, Ellem & Risbridger, 2010). Previous studies have been shown that CYP19A1 (Beuten et al., 2009) and ESR1 (Nicolaiew et al., 2009, McIntyre et al., 2007) may be associated with prostate cancer risk. Furthermore, the SNP-SNP interactions between CYP19A1 and ESR1 genes are observed to be associated with premature ovarian failure (Kim et al., 2011). "
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    ABSTRACT: Studies have shown that interactions of single nucleotide polymorphisms (SNPs) may play an important role in understanding the causes of complex disease. We have proposed an integrated machine learning method that combines two machine-learning methods-Random Forests (RF) and Multivariate Adaptive Regression Splines (MARS)-to identify a subset of important SNPs and detect interaction patterns more effectively and efficiently. In this two-stage RF-MARS (TRM) approach, RF is first applied to detect a predictive subset of SNPs, and then MARS is used to identify the interaction patterns. We evaluated the TRM performances in four models. RF variable selection was based on out-of-bag classification error rate (OOB) and variable important spectrum (IS). Our results support that RF(OOB) had better performance than MARS and RF(IS) in detecting important variables. This study demonstrates that TRM(OOB) , which is RF(OOB) plus MARS, has combined the strengths of RF and MARS in identifying SNP-SNP interactions in a scenario of 100 candidate SNPs. TRM(OOB) had greater true positive rate and lower false positive rate compared with MARS, particularly for searching interactions with a strong association with the outcome. Therefore, the use of TRM(OOB) is favored for exploring SNP-SNP interactions in a large-scale genetic variation study.
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