Prostate Cancer and Prostatic Disease (2014) 17, 149–156 & 2014 Macmillan Publishers Limited All rights reserved 1365-7852/14 www.nature.com/pcan
ORIGINAL ARTICLE
Genetic variants in the CYP24A1 gene are associated with prostate cancer risk and aggressiveness in a Korean study population JJ Oh1,2, S-S Byun3, SE Lee3, SK Hong3, CW Jeong3, WS Choi4, D Kim5, HJ Kim6,7 and SC Myung6,7,8 BACKGROUND: Vitamin D-deactivating enzyme CYP24A1 had controversial effects on prostate cancer risk; the genetic study also showed the controversial results. Therefore, we identified the relationships between polymorphisms in CYP24A1 and prostate cancer in a Korean cohort. METHODS: We evaluated the association between 21 single-nucleotide polymorphisms (SNPs) in the CYP24A1 and prostate cancer in Korean men (272 prostate cancers and 173 controls). BPH patients with high PSA or abnormal digital rectal examination who underwent negative prostate biopsy were enrolled in the control group. Twenty-one SNPs in the CYP24A1 were selected from the International HapMap database and the NCBI database with calculation of minor allele frequency and linkage disequilibrium, preferably including the SNPs that were nonsynonymous and located within exons. We also investigated the association between 21 SNPs in the CYP24A1 gene and known clinical characteristics, such as the PSA level, clinical stage, pathological stage and Gleason score. RESULTS: The statistical analysis suggested that five CYP24A1 sequence variants (rs2248461—odds ratio (OR): 0.63, rs2248359—OR: 0.65, rs6022999—OR: 0.65, rs2585428—OR: 0.46, rs4809959—OR: 0.52) had a significant association with prostate cancer risk after multiple comparisons by a method of false discovery rate. Logistic analyses of the CYP24A1 polymorphisms with several prostate cancer-related factors showed that several SNPs were significant: four SNPs to PSA level, three to clinical stage, two to pathological stage and two SNPs to the Gleason score. CONCLUSIONS: The results of this study suggest that some CYP24A1 gene polymorphisms might be associated with the risk of prostate cancer in Korean men. Five CYP24A1 sequence variants showed the significance to predict prostate cancer, and several SNPs of CYP24A1 gene had an important finding to predict prostate cancer-related factors. However, these results should be validated in future large-scale studies. Prostate Cancer and Prostatic Disease (2014) 17, 149–156; doi:10.1038/pcan.2014.1; published online 4 February 2014 Keywords: prostate; CYP24A1; polymorphism; cancer risk
INTRODUCTION Prostate cancer is one of the most common malignancies described among men in western countries.1 Similarly, the incidence rate of prostate cancer in Korea has increased rapidly during the past decade.2 The etiology of prostate cancer is largely unknown, although several risk factors such as ethnicity, family history and age have been strongly associated with an increased risk.3 Recently, genome-wide association studies analyses have provided novel insights into the etiology of prostate cancer.4–6 A large-scale multicenter genome-wide association study showed that the loci at 2q37.3 (rs2292884) and 12q13 (rs902774) were significant predictors of prostate cancer among 2782 cancer patients and 4458 control group individuals.5 Another study to identify common prostate cancer susceptibility alleles genotyped 211 155 single-nucleotide polymorphisms (SNPs) by using blood samples from 25 074 prostate cancer and 24 272 control group individuals, and 23 new prostate cancer susceptibility loci were identified at genome-wide significance.6 Biological and epidemiological data suggest that vitamin D levels may influence cancer development. However, there is
controversial evidence of an association between vitamin D and prostate cancer risk, as positive effects,7,8 null effects9 and inverse effects have all been reported.10 The 25-hydroxyvitamin D, the prohormonal major circulating form of vitamin D, is metabolically activated to 1,25-dihydroxyvitamin D by cytochrome P450, family 27, subfamily B, polypeptide 1 (CYP27B1) and is deactivated by cytochrome P450, family 24, subfamily A, polypeptide 1 (CYP24A1) in the kidney.11 Recent analyses of genetic polymorphisms associated with prostate cancer have revealed that CYP24A1 increases the risk of prostate cancer in Hispanic Caucasians.12 They showed that the three CYP24A1 genetic variants of rs2245153, rs13038432 and rs3787554 were significantly associated with prostate cancer, and rs3787754 maintained the significance after multiple comparison test (odds ratio (OR) ¼ 2.14, P ¼ 0.005). However, these SNPs had no significance with prostate cancer in non-Hispanic or African–American population in their report. Another report that analyzed vitamin D pathway genes in prostate cancer showed that CYP24A1 and CYP27B1 were not associated with prostate cancer risk.13 Although results were controversial, no study has shown an association between the aforementioned
1 CHA Bundang Medical Center, Department of Urology, CHA University, Seongnam, Korea; 2CHA Cancer Research Center, CHA University, Seoul, Korea; 3Department of Urology, Seoul National University Bundang Hospital, Seongnam-si, Korea; 4Choi Won Suk Urology Clinic, Youngin, Korea; 5Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, PA, USA; 6Advanced Urogenital Disease Research Center, Chung-Ang University College of Medicine, Seoul, Korea; 7Research Institute for Translational System Biomics, Chung-Ang University College of Medicine, Seoul, Korea and 8Department of Urology, Chung-Ang University College of Medicine, Seoul, Korea. Correspondence: Dr S-S Byun, Department of Urology, Seoul National University Bundang Hospital, 300, Gumi-dong, Bundang-gu, Seongnam-si, Kyunggi-do 463-707, Korea or Dr SC Myung, Department of Urology, Chung-Ang University College of Medicine, 221 Heukseok-dong, Dongjak-ku, Seoul 156-756, Korea. E-mail: [email protected] or [email protected] Received 16 September 2013; revised 21 November 2013; accepted 19 December 2013; published online 4 February 2014
Genetic variations in CYP24A1 and prostate cancer JJ Oh et al
150 SNPs and well-established factors related to prostate cancer, such as PSA, Gleason score and pathological stage in the Asian population. Because there are significant racial/ethnic differences in serum vitamin D status,14–16 we examined the contribution of CYP24A1 gene variants to prostate cancer risk, and their correlation with PSA levels, Gleason score and clinical and pathological stages in Korean men. MATERIALS AND METHODS Study population This study was approved by the institutional review board of Chung-Ang University Hospital and Seoul National University Bundang Hospital (IRB nos. C2008035 and B-0905/075-011, respectively). Both the prostate cancer and BPH groups comprised a population of older men treated for urological problems at the Seoul National University Bundang Hospital (Gyeonggi, Seoul, Korea) and Chung-Ang University Hospital (Seoul, Korea). We excluded patients who had undergone prior biopsies or the surgical treatment of prostate disease before receiving a biopsy. Peripheral blood leukocyte samples were obtained before the prostate biopsy for genotyping from 445 men (prostate cancer ¼ 272; BPH ¼ 173) and stored at 80 1C. All 445 men underwent multi (X12)-core transrectal ultrasound-guided biopsy for the evaluation of elevated PSA levels (X3 ngml 1), abnormal digital rectal exams or hypoechoic lesions, as detected using prostate ultrasound. In all men, the prostate was routinely biopsied bilaterally near the base, mid-gland region and apex, with at least six biopsies per side. If necessary, additional biopsies were obtained to evaluate suspicious lesions. Among 173 patients enrolled in the BPH group, which was negative for malignancy in prostate biopsy, 135 patients underwent TURP owing to lower urinary tract symptoms. After TURP, all specimens were shown to be benign by a pathological examination. BPH samples obtained from patients and confirmed to be pathologically negative were used as the control group for reducing selection bias. Most of the 272 prostate cancer patients underwent radical prostatectomy, and eight patients who had metastatic lesions in a preoperative radiologic evaluation underwent hormonal therapy plus external radiotherapy. Five patients with prostate cancer were enrolled in a watchful waiting protocol owing to their poor medical condition. Written informed consent was obtained from all study participants. Blood samples were collected in tubes containing sodium EDTA. The QIAamp Blood Extraction kit (Qiagen, Seoul, Korea) was used for DNA extraction. The PSA level was classified as low (PSAo4 ngml 1), intermediate (4pPSAo10 ngml 1) and high (10 ngml 1pPSA). The Gleason score was classified as low (2–6), intermediate (4 þ 3, 3 þ 4) or high (8–10). The clinical and pathological stages were categorized as localized (T1 or T2N0M0), locally advanced (T3 or T4N0M0) and metastatic (TxN þ or M þ ) on the basis of pathological and/ or radiological reports. The clinical characteristics of the cases were similar to a previous Korean study.17
SNP selection and genotyping In this study, we selected 21 SNPs from two international databases (International HapMap and NCBI dbSNPs). SNP selection from the International HapMap database (Han Chinese and Japanese) was carried out as follows: (1) extraction of all genotypes from the CHB and JPN population in the CYP24A1 gene region using HapMart of the International HapMap database (version: release #27; http://www.hapmap.org); (2) the calculation of minor allele frequency and linkage disequilibrium (LD) using the Haploview software (Cambridge, MA, USA; http://www.broad.mit.edu/ mpg/haploview); and (3) selection of SNPs with a minor allele frequency40.05 and tagging SNPs if several SNPs showed high LD40.98. Furthermore, we added the SNPs from NCBI dbSNPs in the CYP24A1 gene region. The selection criteria included location (SNPs in exons were preferred) and amino acid changes (nonsynonymous SNPs were preferred). Accordingly, rs2296241, rs6068816, rs76747058, rs2296239 and rs2762934 were included as nonsynonymous SNPs. Genotyping was performed at the multiplex level using the Illumina Golden Gate genotyping system.18 Briefly, approximately 250 ng of genomic DNA extracted from the blood of each individual was used to genotype each sample that underwent DNA activation, binding to paramagnetic particles, hybridization to oligonucleotides, washing, extension, ligation, amplification by PCR and hybridization to the beadplate in an appropriate hybridization buffer. Image intensities were scanned by a beadxpress reader and genotyped using the GenomeStudio software (Illumina, San Diego, CA, USA). The Prostate Cancer and Prostatic Disease (2014), 149 – 156
genotype quality score for retaining data was set to 0.25. A total of 21 SNPs were successfully genotyped in the 445 DNA samples. All SNPs showed a call rate higher than 98% in cases or controls. Ten samples were randomly selected for genotyping in duplicate. Concordance among duplicate samples was 100%. The overall call rate for all SNPs was 99.8%.
Statistics SNP genotype frequencies were examined for Hardy–Weinberg equilibrium using the w2-statistic, and all were found to be consistent (P40.05) with Hardy–Weinberg equilibrium among Korean controls. Data were analyzed using an unconditional logistic regression to calculate an OR as an estimate of the relative risk of prostate cancer associated with SNP genotypes.19 To determine the association between the genotype and haplotype distributions of patients and controls, a logistic analysis was performed controlling for age (continuous value) as a covariate to eliminate or reduce any confounding factors that might influence the findings. The significant associations are shown in boldface (Pp0.05). In analyzing a model in which a codominant (additive) effect of the variant (V) allele was assumed, the genotypes wild (W)/W, W/V and V/V were coded as 0, 1 and 2, respectively. When a dominant effect was assumed, genotype W/W was coded as 0, and W/V and V/V were coded as 1, whereas W/V and V/V were scored as 0 and V/V was scored as 1 in a model that assumed a recessive effect.20 Lewontin’s D0 (|D0 |) and the LD coefficient r2 were examined to measure LD between all pairs of biallelic loci.21 The haplotypes were inferred from the successfully genotyped SNPs using PHASE algorithm ver. 2.0,22 using SAS version 9.1 (SAS, Cary, NC, USA). The effective number of independent marker loci was calculated to correct multiple testing, using the software SNPSpD (http://www.genepi. qimr.edu.au/general/daleN/SNPSpD/), which is based on the spectral decomposition of matrices of pairwise LD between SNPs.23 The resulting number of independent marker loci (23.1) was applied to correct for multiple testing. All P-values from the results were corrected for multiple testing by controlling for the false discovery rate.24
RESULTS Twenty-one sequence variants in the CYP24A1 gene were examined in this study; 2 were located in the promoter, 14 in introns, 18 in exons and 1 in the 30 -untranslated region (Figure 1a). The measured LD among 21 SNPs was determined by calculating Lewontin’s D0 and r2 values; the results showed that these SNPs were divided into haplotype blocks (Figures 1b and c). The clinical characteristics of the prostate cancer cases and controls are shown in Table 1. The genotype frequencies for each polymorphism in both the prostate cancer and control groups were analyzed using a logistic regression model (Table 2). Among the 21 polymorphisms examined, 11 polymorphisms (rs2248461, rs2248359, rs6022999, rs2585428, rs2296241, rs4809959, rs2181874, rs4809958, rs6068816, rs6127119 and rs2209314) were significantly correlated with having prostate cancer. The rs2248461 (OR: 0.63), rs2248359 (OR: 0.65), rs6022999 (OR: 0.65), rs2585428 (OR: 0.71), rs2296241 (OR: 0.74), rs4809959 (OR: 0.75), rs2181874 (OR: 0.67) and rs2209314 (OR: 0.71) had negative correlation with prostate cancer compared with the control group. Moreover, rs4809958 (1.34), rs6068816 (OR: 1.50) and rs6127119 (OR: 1.41) were in positive correlation with prostate cancer compared with the control group. No significant association was found between the presence of prostate cancer and the other 10 SNPs. In addition, a haplotype association test was performed on 13 common haplotypes (freq.40.05) within four haplotype blocks (Figure 1b). Six haplotypes (CYP24A1_B1_ht1, CYP24A1_B1_ht2, CYP24A1_B2_ht1, CYP24A1_B2_ht2, CYP24A1_B3_ht1 and CYP24A1_B3_ht3) showed a significant association with prostate cancer risk. After correction for multiple testing, estimating a false discovery rate o50% for Po0.01, five SNPs rs2248461, rs2248359, rs6022999, rs2585428, rs4809959) remained as a significant predictor of prostate cancer among aforementioned 11 SNPs (Table 3). Furthermore, among aforementioned six haplotypes, five haplotypes & 2014 Macmillan Publishers Limited
Genetic variations in CYP24A1 and prostate cancer JJ Oh et al
151
Figure 1. Gene map, haplotypes and LD coefficients for the CYP24A1 polymorphisms. (a) Coding exons are marked by black blocks, and 50 and 30 UTRs by white blocks. (b) Haplotypes of CYP24A1. Only those with frequencies 40.02 are shown. The ‘others’ category contains rare haplotypes. (c) Linkage disequilibrium coefficients (|D0 | and r2) among CYP24A1 polymorphisms.
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Prostate Cancer and Prostatic Disease (2014), 149 – 156
Genetic variations in CYP24A1 and prostate cancer JJ Oh et al
152 Table 1.
Study characteristics of prostate cancer cases and controls Cases (prostate cancer)
N Age (year)±s.d. Body mass index in kgm 2 (%) Prostate volume (cm3)±s.d. PSA, ngml 1 (mean±s.d.)
Controls (BPH)
P-value
272 68.2±6.8 24.1±3.3
173 67.3±8.8 24.0±3.0
0.85 0.41
37.2±18.6
48.4±26.2
0.02
48.2±192.8
5.2±6.7
Gleason score, n (%) p6 7 X8
29 (11) 202 (75) 39 (14)
Clinical stage, n (%) Localized Locally advanced Metastatic
252 (92.6) 12 (3.7) 8 (2.9)
Pathologic stage, n (%) Localized (T2) Advanced (XT3)
152 (60.3) 100 (39.7)
o0.01
(CYP24A1_B1_ht1, CYP24A1_B1_ht2, CYP24A1_B2_ht1, CYP24A1_ B2_ht2 and CYP24A1_B3_ht3) also remained as significant predictors after multiple comparison. Among the 272 prostate cancer patients, associations between target SNPs and several clinical factors, including PSA, clinical stage, pathological stage and Gleason grade, were investigated using a logistic regression model (Table 4). In the analysis of logistic regression model of CYP24A1 polymorphisms according to PSA levels, three SNPs (rs2585428, rs2296241 and rs4809959) were inversely associated with PSA levels both in the codominant model (OR: 0.66, P ¼ 0.02; OR: 0.69, P ¼ 0.04 and OR: 0.67, P ¼ 0.02, respectively) and in the dominant model (OR: 0.56, P ¼ 0.02, OR: 0.62, P ¼ 0.05 and OR: 0.58, P ¼ 0.03). The rs972650 and one haplotype (CYP24A1_B4_ht2) had a significant effect on elevated PSA level in the recessive model (OR: 2.23, P ¼ 0.03 and OR: 2.23, P ¼ 0.03, respectively). In the analysis based on clinical stage criteria (metastatic vs locally advanced vs localized), three SNPs (rs2585428, rs2296241 and rs2762941) had significantly negative association with clinical stage (rs2585428; OR: 0.36 in dominant model, rs2296241; OR: 0.34 in dominant model and rs2762941; OR: 0.38 in codominant model). In the analysis that focused on pathological stage criteria (which was divided into locally advanced and localized), rs2244719 and one haplotype (CYP24A1_B3_ht4) were significantly associated with advanced pathological stage in the codominant model (OR: 1.68 and OR: 2.50, respectively). However, rs2209314 was in negative association with pathological stage (OR: 0.31 in recessive model). When we stratified the patients according to Gleason score, we observed the positive associations between prostate cancer risk and rs2209314 SNPs in the recessive model (OR: 2.65); however, rs6127119 showed negative association with pathologic Gleason score (OR: 0.67) in the co-dominant model.
DISCUSSION The present case–control study was conducted to investigate the potential association between CYP24A1 gene polymorphisms and the risk for prostate cancer in a Korean population. Logistic regression analyses suggested that some CYP24A1 gene polymorphisms were inversely associated with a risk for prostate cancer when compared with those of BPH controls. These results Prostate Cancer and Prostatic Disease (2014), 149 – 156
suggest that CYP24A1 gene polymorphisms may alter the susceptibility to prostate cancer and may be useful as biomarkers for the disease. The growth and differentiation of normal prostatic tissue is also promoted by interactions between the vitamin D and dihydrotestosterone pathways.25 Levels of the bioactive form of vitamin D are controlled by both the activating enzyme 1-A-hydroxylase (coded by CYP27B1) and the deactivating enzyme 24-hydroxylase (coded by CYP24A1), which regulate cell growth and may reduce the risk of malignant transformation. Functional variants in the genes of these pathways are likely to influence prostate carcinogenesis. Significant associations between variants in one or more of the above genes and risk for prostate cancer have been reported but with inconsistent findings. In a branch study of a large randomized controlled trial in the USA (PLCO; prostate, lung, colorectal and ovarian cancer screening trial), Ahn et al.11 investigated the association between prostate cancer and 22 SNPs of CYP24A1 among 749 prostate cancer patients and 781 control patients. Their study demonstrated that there was no significant association between tag SNPs in CYP24A1 and prostate cancer risk. Similarly, Holick et al.13 investigated the associations between 14 SNPs and prostate cancer risk among 630 patients through the Seattle-Puget Sound Surveillance, epidemiology and end results cancer registry, and concluded that CYP24A1 genotypes were not associated with prostate cancer risk. In contrast to the aforementioned studies, our results showed that several CYP24A1 SNPs were significantly associated with prostate cancer risk. Although rs6068816, rs2181874, rs2296241 and rs6022999 had no significant association in the study by Holick et al.,13 only rs6022999 was significantly associated in our study. The rs4809959 and rs2248359 were also significant in our logistic regression model, although they were not in the PLCO study. This disparity may have resulted from two different study conditions, the first being racial differences. The aforementioned negative study for the association between prostate cancer risk and CYP24A1 SNPs was conducted in a western population. The study population of the PLCO trial included non-Hispanic white males in the United States,11 and the study by Holick et al.13 was also conducted in the United States. However, no Asian study has evaluated the association between prostate cancer risk and CYP24A1, and racial differences may affect the results, causing differences between our study and studies from western countries. Indeed, there are significant racial/ ethnic differences in serum vitamin D status. Previous studies have reported that individuals of African ancestry have approximately twofold lower levels of vitamin D than those with European ancestry.14–16 In particular, Asian men had a relatively low vitamin D level compared with Hispanic men.15 This disparity of vitamin D status in each race might lead to the difference of result in the association between prostate cancer and CYP24A1 genetic variants. The second possible influencing factor is different characteristics of the control group. Our study included a control group with a negative prostate biopsy; however, the aforementioned negative study included a control population through the social cohort. Because there were some cases of prostate cancer with a low PSA level and negative digital rectal examination, our study setting was better for reducing selection bias. CYP27B1, which encodes the vitamin D-activating enzyme 1alpha-hydroxylase, and CYP24A1, which encodes for the vitamin D-deactivating enzyme 24-hydroxylase, are both expressed in prostate epithelial cells.26 Our previous study regarding CYP271B SNPs demonstrated no association with prostate cancer risk and any associated factors, such as PSA level, clinical stage, pathological stage and Gleason score (data were not shown). However, 11 SNPs were significantly associated with prostate cancer risk, four SNPs with PSA level, three SNPs with clinical stage, two SNPs with pathological stage and two SNPs with Gleason score. One genome-wide scan for prostate cancer in a USA cohort found no significant association with prostate cancer & 2014 Macmillan Publishers Limited
& 2014 Macmillan Publishers Limited
20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20
rs2248461 rs2248359 rs6022999 rs2585428 rs2245153 rs2296241 rs4809960 rs4809959 rs2181874 rs2762941 rs3787557 rs2244719 rs4809958 rs6068816 rs76747058 rs6127119 rs2209314 rs912505 rs2296239 rs927650 rs2762934 CYP24A1_B1_ht1 CYP24A1_B1_ht2 CYP24A1_B2_ht1 CYP24A1_B2_ht2 CYP24A1_B2_ht3 CYP24A1_B2_ht4 CYP24A1_B3_ht1 CYP24A1_B3_ht2 CYP24A1_B3_ht3 CYP24A1_B3_ht4 CYP24A1_B4_ht1 CYP24A1_B4_ht2 CYP24A1_B4_ht3
Promoter Promoter Intron Intron Intron CDS Intron Intron Intron Intron Intron Intron Intron CDS CDS Intron Intron Intron CDS Intron 3’UTR — — — — — — — — — — — — —
Position
— — — — — A184A — — — — — — — T248T C303S — — — P375P — — — — — — — — — — — — — — —
AA Change
G4A C4T A4G G4A T4C G4A T4C A4G G4A A4G T4C T4C T4G C4T C4G C4T T4C G4A T4C C4T G4A — — — — — — — — — — — — —
Alleles
0.319 0.336 0.199 0.346 0.176 0.360 0.202 0.426 0.207 0.367 0.262 0.149 0.412 0.410 0.015 0.469 0.344 0.441 0.441 0.342 0.100 0.335 0.318 0.441 0.164 0.165 0.063 0.399 0.204 0.156 0.064 0.441 0.342 0.099
PCa (n ¼ 272) 0.419 0.428 0.272 0.434 0.208 0.442 0.214 0.503 0.275 0.358 0.254 0.145 0.350 0.350 0.023 0.393 0.413 0.416 0.416 0.312 0.104 0.428 0.419 0.520 0.240 0.182 0.064 0.332 0.197 0.237 0.061 0.416 0.312 0.104
BPH (n ¼ 173)
Minor allele frequency
0.63 0.65 0.65 0.71 0.85 0.74 0.97 0.75 0.67 1.07 1.04 1.04 1.34 1.33 0.46 1.41 0.71 1.16 1.16 1.20 0.96 0.65 0.63 0.74 0.60 0.92 0.91 1.37 1.09 0.60 1.10 1.16 1.20 0.95
(0.47–0.84) (0.49–0.87) (0.47–0.91) (0.54–0.94) (0.60–1.21) (0.56–0.98) (0.69–1.36) (0.57–0.98) (0.49–0.94) (0.79–1.44) (0.75–1.45) (0.70–1.53) (1.00–1.80) (0.99–1.78) (0.17–1.29) (1.06–1.88) (0.53–0.95) (0.87–1.55) (0.87–1.55) (0.89–1.63) (0.60–1.52) (0.49–0.87) (0.47–0.84) (0.56–0.97) (0.42–0.86) (0.64–1.33) (0.51–1.60) (1.02–1.84) (0.76–1.57) (0.42–0.85) (0.62–1.96) (0.87–1.55) (0.89–1.63) (0.60–1.51)
OR (95% CI)
Codominant
0.002 0.004 0.01 0.02 0.36 0.03 0.87 0.04 0.02 0.68 0.80 0.86 0.05 0.06 0.14 0.02 0.02 0.32 0.32 0.24 0.84 0.004 0.002 0.03 0.005 0.67 0.73 0.04 0.64 0.005 0.74 0.32 0.24 0.83
P-value 0.63 0.66 0.62 0.77 0.86 0.75 1.00 0.84 0.62 1.14 0.95 1.05 1.52 1.50 0.46 1.66 0.68 1.12 1.11 1.21 0.93 0.66 0.63 0.90 0.53 0.90 0.85 1.49 1.06 0.57 1.15 1.12 1.21 0.93
(0.42–0.95) (0.44–1.00) (0.42–0.93) (0.51–1.15) (0.57–1.29) (0.50–1.13) (0.67–1.51) (0.55–1.30) (0.42–0.92) (0.76–1.71) (0.64–1.42) (0.68–1.64) (1.01–2.29) (1.00–2.25) (0.17–1.29) (1.09–2.53) (0.45–1.03) (0.73–1.71) (0.73–1.70) (0.81–1.80) (0.57–1.52) (0.44–0.99) (0.42–0.94) (0.58–1.40) (0.35–0.80) (0.59–1.37) (0.47–1.54) (0.99–2.22) (0.70–1.58) (0.38–0.87) (0.63–2.11) (0.73–1.71) (0.81–1.80) (0.57–1.52)
OR (95% CI)
Dominant
0.03 0.05 0.02 0.20 0.46 0.17 0.99 0.44 0.02 0.52 0.81 0.82 0.04 0.05 0.14 0.02 0.07 0.61 0.62 0.35 0.78 0.05 0.02 0.64 0.003 0.62 0.59 0.05 0.79 0.008 0.65 0.61 0.35 0.76
P-value
Recessive
1.52 1.72 0.40 0.47 1.38 1.42 1.58
1.46 0.57 1.38 1.38 1.42 1.58 0.43 0.40 0.47 0.74 0.99
(0.23–0.71) (0.25–0.76) (0.20–1.25) (0.27–0.77) (0.25–1.79) (0.33–0.92) (0.33–2.01) (0.33–0.83) (0.26–1.43) (0.52–1.77) (0.69–4.26) (0.25–3.50) (0.74–2.37) (0.74–2.37) — (0.87–2.44) (0.32–1.02) (0.81–2.34) (0.81–2.35) (0.73–2.76) (0.14–18.34) (0.25–0.76) (0.23–0.71) (0.30–0.75) (0.25–2.14) (0.32–3.07) — (0.83–2.78) (0.44–6.76) (0.14–1.14) (0.03–7.72) (0.81–2.34) (0.73–2.76) (0.14–18.32)
OR (95% CI) 0.40 0.44 0.50 0.46 0.66 0.55 0.81 0.52 0.61 0.96 1.71 0.94 1.33 1.33
Abbreviations: CI, confidence interval; OR, odds ratio; PCa, prostate cancer. Minor allele frequencies and P-values for logistic analyses of three alternative models (codominant, dominant and recessive models) controlling for age as covariate are shown. Signiciant associations are shown in boldface (P-valuep0.05).
Chr
Logistic regression analysis of CYP24A1 single-nucleotide polymorphisms with the risk of prostate cancer in Korean population
SNP ID
Table 2.
0.002 0.004 0.14 0.004 0.42 0.02 0.65 0.007 0.26 0.89 0.25 0.92 0.34 0.34 — 0.15 0.06 0.24 0.24 0.31 0.72 0.004 0.002 0.001 0.57 0.99 — 0.18 0.44 0.09 0.60 0.24 0.31 0.72
P-value
Genetic variations in CYP24A1 and prostate cancer JJ Oh et al
153
Prostate Cancer and Prostatic Disease (2014), 149 – 156
Genetic variations in CYP24A1 and prostate cancer JJ Oh et al
154 Table 3. Outcome of multiple testing for logistic regression analysis of CYP24A1 single-nucleotide polymorphisms with the risk of prostate cancer in Korean population SNP ID
rs2248461 rs2248359 rs6022999 rs2585428 rs2245153 rs2296241 rs4809960 rs4809959 rs2181874 rs2762941 rs3787557 rs2244719 rs4809958 rs6068816 rs76747058 rs6127119 rs2209314 rs912505 rs2296239 rs927650 rs2762934 CYP24A1_B1_ht1 CYP24A1_B1_ht2 CYP24A1_B2_ht1 CYP24A1_B2_ht2 CYP24A1_B2_ht3 CYP24A1_B2_ht4 CYP24A1_B3_ht1 CYP24A1_B3_ht2 CYP24A1_B3_ht3 CYP24A1_B3_ht4 CYP24A1_B4_ht1 CYP24A1_B4_ht2 CYP24A1_B4_ht3
Chr
20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20
Minor allele frequency
Adjusted P-value after multiple test correction (false discovery rate)
PCa (n ¼ 272)
BPH (n ¼ 173)
Codominant
Dominant
Recessive
0.319 0.336 0.199 0.346 0.176 0.360 0.202 0.426 0.207 0.367 0.262 0.149 0.412 0.410 0.015 0.469 0.344 0.441 0.441 0.342 0.100 0.335 0.318 0.441 0.164 0.165 0.063 0.399 0.204 0.156 0.064 0.441 0.342 0.099
0.419 0.428 0.272 0.434 0.208 0.442 0.214 0.503 0.275 0.358 0.254 0.145 0.350 0.350 0.023 0.393 0.413 0.416 0.416 0.312 0.104 0.428 0.419 0.520 0.240 0.182 0.064 0.332 0.197 0.237 0.061 0.416 0.312 0.104
0.028 0.028 0.049 0.062 0.510 0.078 0.870 0.091 0.062 0.856 0.870 0.870 0.106 0.120 0.264 0.062 0.062 0.473 0.473 0.408 0.870 0.028 0.028 0.078 0.028 0.856 0.868 0.091 0.856 0.028 0.868 0.473 0.408 0.870
0.142 0.142 0.113 0.425 0.782 0.385 0.990 0.782 0.113 0.789 0.845 0.845 0.142 0.142 0.340 0.113 0.183 0.789 0.789 0.661 0.845 0.142 0.113 0.789 0.102 0.789 0.789 0.142 0.845 0.113 0.789 0.789 0.661 0.845
0.021 0.021 0.400 0.021 0.584 0.080 0.770 0.032 0.462 0.949 0.462 0.950 0.495 0.495 — 0.400 0.213 0.462 0.462 0.495 0.794 0.021 0.021 0.021 0.730 0.990 — 0.443 0.587 0.288 0.738 0.462 0.495
Abbreviation: PCa, prostate cancer. Significant associations are shown in boldface (P-value p0.05).
risk for CYP27B1 or CYP24A1.27 Although almost all studies have reported no association between CYP24A1 and prostate cancer risk, recent analysis from prostate cancer cohort consortium showed that the allele in rs6013897 near CYP24A1 decreased aggressive prostate cancer risk.28 However, in their results, aforementioned SNP had a trend for increasing the risk of nonaggressive prostate cancer. Likewise our study had shown the several significant SNPs which supplies ambivalent effect of prostate cancer even included in CYP24A1 gene. And some SNPs had different significance according to logistic model. The rs2209314 had an unfavorable effect on Gleason score, but a favorable effect on pathologic stage. Only rs2585428 had uniform effect on prostate cancer risk, clinical stage and PSA level in trend to decreasing prostate cancer; however, its significance was different according to models; rs2585428 was significantly associated with prostate cancer in the co-dominant model and recessive model, but not in the dominant model. However, it was significantly associated with PSA level in the co-dominant model and dominant model, but not in the recessive model. Although there were limitations, we believe this is the first study to report a significant association between CYP24A1 and prostate cancer risk in an Asian population among patients with histologically proven cancers. Prostate cancer occurs more frequently among African Americans, and this characteristic is consistent with a role for vitamin D deficiency in the etiology of this disease.29 In addition, different Prostate Cancer and Prostatic Disease (2014), 149 – 156
genotype distributions for Caucasians and African Americans have been observed.30 Thus, genetic polymorphisms in vitamin D-related genes may partly explain variations in prostate cancer risk among ethnic groups. Prostate cancer risk likely differs with race and ethnicity, and vitamin D status also differs by country, which may explain the disparity in disease incidence. Our study also investigated the associations between prostate cancer-related factors and CYP24A1 SNPs; several SNPs and haplotypes were significantly associated with PSA level, clinical stage, pathological stage and Gleason score. Our study had several limitations. Our analysis was based on a comparison of samples from patients with prostate cancer and samples from patients with non-malignant BPH as controls. Although our control group was proven as benign via a previous prostate biopsy, all the men in the BPH group were potentially at risk for the development of prostate cancer and may have had latent prostate cancer at the time of their designation as controls, leading to disease misclassification. In this study, we had limitation of only adjusting the age as covariate in logistic analysis, it should be necessary for controlling other health related factors. In addition, we could not adjust for other factors that could alter vitamin D levels, such as sun exposure, calcium intake and vitamin D intake, which could modify the risk estimates, as reported previously.7,8 It is well known that dietary factors, such as calcium and vitamin D, and lifestyle factors, such as body mass index and & 2014 Macmillan Publishers Limited
PSAX10 (n ¼ 112)
4pPSAo10 (n ¼ 98)
Minor allele frequency
& 2014 Macmillan Publishers Limited
Metastatic (n ¼ 8)
Locally advanced (n ¼ 12)
Minor allele frequency
Locally advanced (n ¼ 100)
Localized (n ¼ 152)
Minor allele frequency
High grade (GSX8) (n ¼ 39)
Intermediate (GS 7) (n ¼ 202)
Minor allele frequency Low grade (GSp6) (n ¼ 29)
1.68 (0.99–2.84) 0.72 (0.48–1.08) 2.50 (1.17–5.36)
OR (95% CI)
OR (95% CI)
Dominant
0.05 0.27
P-value
0.09 0.54 0.03
0.59 (0.32–1.08) 1.01 (0.58–1.75)
OR (95% CI)
0.09 0.98
Recessive
(0.30–1.40) (0.30–1.27) (0.32–1.17) (1.10–4.54) (0.29–1.08) (1.10–4.54)
OR (95% CI)
Recessive
1.57 (0.44–5.61) 1.36 (0.38–4.83)
OR (95% CI)
0.65 0.62 0.61 2.23 0.56 2.23
OR (95% CI)
Recessive
0.60 (0.30–1.18) 2.65 (1.15–6.13)
OR (95% CI)
Recessive
4.80 (0.49–46.96) 0.31 (0.11–0.85)
P-value
0.05 0.04 0.06
Dominant
0.36 (0.13–0.99) 0.34 (0.12–0.95) 0.39 (0.14–1.03)
P-value
0.02 0.05 0.03 0.06 0.08 0.06
P-value
P-value
Dominant
(0.35–0.91) (0.38–0.99) (0.35–0.95) (0.40–1.02) (0.39–1.06) (0.40–1.02)
OR (95% CI)
0.56 0.62 0.58 0.64 0.64 0.64
OR (95% CI)
1.65 (0.93–2.94) 0.85 (0.50–1.43) 2.47 (1.12–5.45) Codominant
0.05 0.11 0.02
P-value
0.23 0.19 0.03
P-value
0.02 0.04 0.02 0.80 0.03 0.80
P-value
0.67 (0.45–1.00) 1.26 (0.83–1.91)
Codominant
0.63 (0.29–1.36) 0.60 (0.28–1.29) 0.38 (0.16–0.92)
OR (95% CI)
0.466 0.345
Codominant
(0.46–0.95) (0.49–0.98) (0.47–0.95) (0.67–1.36) (0.48–0.97) (0.67–1.36)
OR (95% CI)
0.66 0.69 0.67 0.95 0.68 0.95
OR (95% CI)
Dominant
0.14 0.02
P-value
0.18 0.02
P-value
0.49 0.64
P-value
0.27 0.19 0.14 0.03 0.08 0.03
P-value
Abbreviations: CI, confidence interval; OR, odds ratio. Minor allele frequencies and P-values for logistic analyses of three alternative models (codominant, dominant and recessive models) controlling for age as covariate are shown. Referents of logistic analysis of CYP24A1 polymorphisms according to PSA criteria was PSAo4 ngml 1. Referents of logistic analysis of CYP24A1 polymorphisms according to clinical stage were localized. Referents of logistic analysis of CYP24A1 polymorphisms according to pathological stage were localized. Referents of logistic analysis of CYP24A1 polymorphisms according to Gleason score (GS) were low grade. Significant associations are shown in boldface (P-valuep0.05).
Logistic analysis of CYP24A1 polymorphisms according to Gleason score criteria rs6127119 0.480 0.517 rs2209314 0.345 0.293
SNP ID
Logistic analysis of CYP24A1 polymorphisms according to pathological stage criteria rs2244719 0.175 0.117 rs2209314 0.314 0.375 CYP24A1_B3_ht4 0.093 0.040
SNP ID
0.353 0.369 0.378
Localized (n ¼ 252)
Logistic analysis of CYP24A1 polymorphisms according to clinical stage criteria rs2585428 0.563 0.000 rs2296241 0.563 0.000 rs2762941 0.313 0.100
SNP ID
0.346 0.360 0.426 0.342 0.472 0.340
PSAo4 (n ¼ 62)
Codominant
Significant CYP24A1 polymorphism after logistic analysis according to variable factors among prostate cancer patients
Logistic analysis of CYP24A1 polymorphisms according to PSA criteria rs2585428 0.321 0.381 rs2296241 0.340 0.393 rs4809959 0.425 0.462 rs927650 0.396 0.340 CYP24A1_B2_ht1 0.350 0.453 CYP24A1_B4_ht2 0.300 0.396
SNP ID
Table 4.
Genetic variations in CYP24A1 and prostate cancer JJ Oh et al
155
Prostate Cancer and Prostatic Disease (2014), 149 – 156
Genetic variations in CYP24A1 and prostate cancer JJ Oh et al
156 physical activity, may influence expression levels.31 Thus, an assessment of the association between the vitamin D metabolism-related gene variants and diet and lifestyle factors is needed to clearly determine the impact of the CYP24A1 gene on cancer etiology. There were limitations, that is, we could not measure the vitamin D level in enrolled patients and could not investigate functional outcomes of CYP24A1 variants to realistic vitamin D mechanistic pathway; nonsynonymous SNPs included in this study did not have significance after multiple comparisons. As heterogeneous prostate cancer patients including metastatic, locally advanced and localized were enrolled in this study, mean PSA level among prostate cancer patients was higher with a large standard deviation, and it should be adjusted in future study. Another limitation was the relatively small cohort included in this analysis. However, this study included a unique racial population, and the control group also had little selection bias owing to their exclusion by biopsy. To confirm the association between aforementioned SNPs and prostate cancerrelated factors, further prospective large cohort study should be necessary to validate our results. CONCLUSIONS The results suggest that some CYP24A1 gene polymorphisms in Korean men might be associated with the risk of developing prostate cancer. As racial/ethnic differences may exist, our study demonstrating an association between prostate cancer and CYP24A1 gene polymorphisms is one of the first efforts in an Asian population. Outside validation of these findings should be performed, especially to find the relationships between several SNPs and prostate cancer-related factors that correlated with prognostic outcomes. CONFLICT OF INTEREST The authors declare no conflict of interest.
ACKNOWLEDGEMENTS This work was supported by grant no. 03-2010-012 from the SNUBH Research Fund, grant of the Korea Healthcare Technology R&D Project, Ministry of Health, Welfare & Family Affairs the Republic of Korea (A085138) and supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2012R1A12006392).
REFERENCES 1 Jemal A, Siegel R, Xu J, Ward E. Cancer statistics, 2010. CA Cancer J Clin 2010; 60: 277–300. 2 Park SK, Sakoda LC, Kang D, Chokkalingam AP, Lee E, Shin HR et al. Rising prostate cancer rates in South Korea. Prostate 2006; 66: 1285–1291. 3 Chan JM, Holick CN, Leitzmann MF, Rimm EB, Willett WC, Stampfer MJ et al. Diet after diagnosis and the risk of prostate cancer progression, recurrence, and death (United States). Cancer Causes Control 2006; 17: 199–208. 4 Chen L, Davey Smith G, Evans DM, Cox A, Lawlor DA, Donovan J et al. Genetic variants in the vitamin D receptor are associated with advanced prostate cancer at diagnosis: findings from the prostate testing for cancer and treatment study and a systematic review. Cancer Epidemiol Biomarkers Prev 2009; 18: 2874–2881. 5 Schumacher FR, Berndt SI, Siddiq A, Jacobs KB, Wang Z, Lindstrom S et al. Genome-wide association study identifies new prostate cancer susceptibility loci. Hum Mol Genet 2011; 20: 3867–3875. 6 Eeles RA, Olama AA, Benlloch S, Saunders EJ, Leongamornlert DA, Tymrakiewicz M et al. Identification of 23 new prostate cancer susceptibility loci using the iCOGS custom genotyping array. Nat Genet 2013; 45: 385–391. 7 Mikhak B, Hunter DJ, Spiegelman D, Platz EA, Hollis BW, Giovannucci E. Plasma 1,25-dihydroxy- and 25-hydroxyvitamin D and subsequent risk of prostate cancer. Cancer Causes Control 2004; 15: 255–265.
Prostate Cancer and Prostatic Disease (2014), 149 – 156
8 Li H, Stampfer MJ, Hollis JB, Mucci LA, Gaziano JM, Hunter D et al. A prospective study of plasma vitamin D metabolites, vitamin D receptor polymorphisms, and prostate cancer. PLoS Med 2007; 4: e103. 9 Mikhak B, Hunter DJ, Spiegelman D, Platz EA, Hollis BW, Giovannucci E. Vitamin D receptor (VDR) gene polymorphisms and haplotypes, interactions with plasma 25hydroxyvitamin D and 1,25-dihydroxyvitamin D, and prostate cancer risk. Prostate 2007; 67: 911–923. 10 Ahonen MH, Zhuang YH, Aine R, Ylikomi T, Tuohimaa P. Androgen receptor and vitamin D receptor in human ovarian cancer: growth stimulation and inhibition by ligands. Int J Cancer 2000; 86: 40–46. 11 Ahn J, Albanes D, Berndt SI, Peters U, Chatterjee N, Freedman ND et al. Vitamin D-related genes, serum vitamin D concentrations and prostate cancer risk. Carcinogenesis 2009; 30: 769–776. 12 Beuten J, Gelfond JA, Franke JL, Weldon KS, Crandall AC, Johnson-Pais TL et al. Single and multigenic analysis of the association between variants in 12 steroid hormone metabolism genes and risk of prostate cancer. Cancer Epidemiol Biomarkers Prev 2009; 18: 1869–1880. 13 Holick CN, Stanford JL, Kwon EM, Ostrander EA, Nejentsev S, Peters U. Comprehensive association analysis of the vitamin D pathway genes, VDR, CYP27B1, and CYP24A1, in prostate cancer. Cancer Epidemiol Biomarkers Prev 2007; 16: 1990–1999. 14 Harris SS, Dawson-Hughes B. Seasonal changes in plasma 25-hydroxyvitamin D concentrations of young American black and white women. Am J Clin Nutr 1998; 67: 1232–1236. 15 Harris SS, Soteriades E, Coolidge JA, Mudgal S, Dawson-Hughes B. Vitamin D insufficiency and hyperparathyroidism in a low income, multiracial, elderly population. J Clin Endocrinol Metab 2000; 85: 4125–4130. 16 Zadshir A, Tareen N, Pan D, Norris K, Martins D. The prevalence of hypovitaminosis D among US adults: data from the NHANES III. Ethn Dis 2005; 15: S5–97-101. 17 Song SY, Kim SR, Ahn G, Choi HY. Pathologic characteristics of prostatic adenocarcinomas: a mapping analysis of Korean patients. Prostate Cancer Prostatic Dis 2003; 6: 143–147. 18 Oliphant A, Barker DL, Stuelpnagel JR, Chee MS. BeadArray technology: enabling an accurate, cost-effective approach to high-throughput genotyping. Biotechniques 2002; Suppl: 56-8: 60–61. 19 Morris JA, Gardner MJ. Calculating confidence intervals for relative risks (odds ratios) and standardised ratios and rates. Br Med J (Clin Res Ed) 1988; 296: 1313–1316. 20 Lewis CM. Genetic association studies: design, analysis and interpretation. Brief Bioinform. 2002; 3: 146–153. 21 Hedrick PW. Gametic disequilibrium measures: proceed with caution. Genetics 1987; 117: 331–341. 22 Stephens M, Smith NJ, Donnelly P. A new statistical method for haplotype reconstruction from population data. Am J Hum Genet 2001; 68: 978–989. 23 Nyholt DR. A simple correction for multiple testing for single-nucleotide polymorphisms in linkage disequilibrium with each other. Am J Hum Genet 2004; 74: 765–769. 24 Benjamini Y, Drai D, Elmer G, Kafkafi N, Golani I. Controlling the false discovery rate in behavior genetics research. Behav Brain Res 2001; 125: 279–284. 25 Leman ES, DeMiguel F, Gao AC, Getzenberg RH. Regulation of androgen and vitamin D receptors by 1,25-dihydroxyvitamin D3 in human prostate epithelial and stromal cells. J Urol 2003; 170: 235–240. 26 Omdahl JL, Morris HA, May BK. Hydroxylase enzymes of the vitamin D pathway: expression, function, and regulation. Annu Rev Nutr. 2002; 22: 139–166. 27 Nomura AM, Stemmermann GN, Lee J, Kolonel LN, Chen TC, Turner A et al. Serum vitamin D metabolite levels and the subsequent development of prostate cancer (Hawaii, United States). Cancer Causes Control 1998; 9: 425–432. 28 Mondul AM, Shui IM, Yu K, Travis RC, Stevens VL, Campa D et al. Genetic variation in the vitamin D pathway in relation to risk of prostate cancer—results from the breast and prostate cancer cohort consortium. Cancer Epidemiol Biomarkers Prev 2013; 22: 688–696. 29 Schwartz GG, Hulka BS. Is vitamin D deficiency a risk factor for prostate cancer? (Hypothesis). Anticancer Res 1990; 10: 1307–1311. 30 Nejentsev S, Godfrey L, Snook H, Rance H, Nutland S, Walker NM et al. Comparative high-resolution analysis of linkage disequilibrium and tag single nucleotide polymorphisms between populations in the vitamin D receptor gene. Hum Mol Genet 2004; 13: 1633–1639. 31 Feskanich D, Hunter DJ, Willett WC, Hankinson SE, Hollis BW, Hough HL et al. Vitamin D receptor genotype and the risk of bone fractures in women. Epidemiology 1998; 9: 535–539.
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ORIGINAL ARTICLE
Genetic variants in the CYP24A1 gene are associated with prostate cancer risk and aggressiveness in a Korean study population JJ Oh1,2, S-S Byun3, SE Lee3, SK Hong3, CW Jeong3, WS Choi4, D Kim5, HJ Kim6,7 and SC Myung6,7,8 BACKGROUND: Vitamin D-deactivating enzyme CYP24A1 had controversial effects on prostate cancer risk; the genetic study also showed the controversial results. Therefore, we identified the relationships between polymorphisms in CYP24A1 and prostate cancer in a Korean cohort. METHODS: We evaluated the association between 21 single-nucleotide polymorphisms (SNPs) in the CYP24A1 and prostate cancer in Korean men (272 prostate cancers and 173 controls). BPH patients with high PSA or abnormal digital rectal examination who underwent negative prostate biopsy were enrolled in the control group. Twenty-one SNPs in the CYP24A1 were selected from the International HapMap database and the NCBI database with calculation of minor allele frequency and linkage disequilibrium, preferably including the SNPs that were nonsynonymous and located within exons. We also investigated the association between 21 SNPs in the CYP24A1 gene and known clinical characteristics, such as the PSA level, clinical stage, pathological stage and Gleason score. RESULTS: The statistical analysis suggested that five CYP24A1 sequence variants (rs2248461—odds ratio (OR): 0.63, rs2248359—OR: 0.65, rs6022999—OR: 0.65, rs2585428—OR: 0.46, rs4809959—OR: 0.52) had a significant association with prostate cancer risk after multiple comparisons by a method of false discovery rate. Logistic analyses of the CYP24A1 polymorphisms with several prostate cancer-related factors showed that several SNPs were significant: four SNPs to PSA level, three to clinical stage, two to pathological stage and two SNPs to the Gleason score. CONCLUSIONS: The results of this study suggest that some CYP24A1 gene polymorphisms might be associated with the risk of prostate cancer in Korean men. Five CYP24A1 sequence variants showed the significance to predict prostate cancer, and several SNPs of CYP24A1 gene had an important finding to predict prostate cancer-related factors. However, these results should be validated in future large-scale studies. Prostate Cancer and Prostatic Disease (2014) 17, 149–156; doi:10.1038/pcan.2014.1; published online 4 February 2014 Keywords: prostate; CYP24A1; polymorphism; cancer risk
INTRODUCTION Prostate cancer is one of the most common malignancies described among men in western countries.1 Similarly, the incidence rate of prostate cancer in Korea has increased rapidly during the past decade.2 The etiology of prostate cancer is largely unknown, although several risk factors such as ethnicity, family history and age have been strongly associated with an increased risk.3 Recently, genome-wide association studies analyses have provided novel insights into the etiology of prostate cancer.4–6 A large-scale multicenter genome-wide association study showed that the loci at 2q37.3 (rs2292884) and 12q13 (rs902774) were significant predictors of prostate cancer among 2782 cancer patients and 4458 control group individuals.5 Another study to identify common prostate cancer susceptibility alleles genotyped 211 155 single-nucleotide polymorphisms (SNPs) by using blood samples from 25 074 prostate cancer and 24 272 control group individuals, and 23 new prostate cancer susceptibility loci were identified at genome-wide significance.6 Biological and epidemiological data suggest that vitamin D levels may influence cancer development. However, there is
controversial evidence of an association between vitamin D and prostate cancer risk, as positive effects,7,8 null effects9 and inverse effects have all been reported.10 The 25-hydroxyvitamin D, the prohormonal major circulating form of vitamin D, is metabolically activated to 1,25-dihydroxyvitamin D by cytochrome P450, family 27, subfamily B, polypeptide 1 (CYP27B1) and is deactivated by cytochrome P450, family 24, subfamily A, polypeptide 1 (CYP24A1) in the kidney.11 Recent analyses of genetic polymorphisms associated with prostate cancer have revealed that CYP24A1 increases the risk of prostate cancer in Hispanic Caucasians.12 They showed that the three CYP24A1 genetic variants of rs2245153, rs13038432 and rs3787554 were significantly associated with prostate cancer, and rs3787754 maintained the significance after multiple comparison test (odds ratio (OR) ¼ 2.14, P ¼ 0.005). However, these SNPs had no significance with prostate cancer in non-Hispanic or African–American population in their report. Another report that analyzed vitamin D pathway genes in prostate cancer showed that CYP24A1 and CYP27B1 were not associated with prostate cancer risk.13 Although results were controversial, no study has shown an association between the aforementioned
1 CHA Bundang Medical Center, Department of Urology, CHA University, Seongnam, Korea; 2CHA Cancer Research Center, CHA University, Seoul, Korea; 3Department of Urology, Seoul National University Bundang Hospital, Seongnam-si, Korea; 4Choi Won Suk Urology Clinic, Youngin, Korea; 5Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, PA, USA; 6Advanced Urogenital Disease Research Center, Chung-Ang University College of Medicine, Seoul, Korea; 7Research Institute for Translational System Biomics, Chung-Ang University College of Medicine, Seoul, Korea and 8Department of Urology, Chung-Ang University College of Medicine, Seoul, Korea. Correspondence: Dr S-S Byun, Department of Urology, Seoul National University Bundang Hospital, 300, Gumi-dong, Bundang-gu, Seongnam-si, Kyunggi-do 463-707, Korea or Dr SC Myung, Department of Urology, Chung-Ang University College of Medicine, 221 Heukseok-dong, Dongjak-ku, Seoul 156-756, Korea. E-mail: [email protected] or [email protected] Received 16 September 2013; revised 21 November 2013; accepted 19 December 2013; published online 4 February 2014
Genetic variations in CYP24A1 and prostate cancer JJ Oh et al
150 SNPs and well-established factors related to prostate cancer, such as PSA, Gleason score and pathological stage in the Asian population. Because there are significant racial/ethnic differences in serum vitamin D status,14–16 we examined the contribution of CYP24A1 gene variants to prostate cancer risk, and their correlation with PSA levels, Gleason score and clinical and pathological stages in Korean men. MATERIALS AND METHODS Study population This study was approved by the institutional review board of Chung-Ang University Hospital and Seoul National University Bundang Hospital (IRB nos. C2008035 and B-0905/075-011, respectively). Both the prostate cancer and BPH groups comprised a population of older men treated for urological problems at the Seoul National University Bundang Hospital (Gyeonggi, Seoul, Korea) and Chung-Ang University Hospital (Seoul, Korea). We excluded patients who had undergone prior biopsies or the surgical treatment of prostate disease before receiving a biopsy. Peripheral blood leukocyte samples were obtained before the prostate biopsy for genotyping from 445 men (prostate cancer ¼ 272; BPH ¼ 173) and stored at 80 1C. All 445 men underwent multi (X12)-core transrectal ultrasound-guided biopsy for the evaluation of elevated PSA levels (X3 ngml 1), abnormal digital rectal exams or hypoechoic lesions, as detected using prostate ultrasound. In all men, the prostate was routinely biopsied bilaterally near the base, mid-gland region and apex, with at least six biopsies per side. If necessary, additional biopsies were obtained to evaluate suspicious lesions. Among 173 patients enrolled in the BPH group, which was negative for malignancy in prostate biopsy, 135 patients underwent TURP owing to lower urinary tract symptoms. After TURP, all specimens were shown to be benign by a pathological examination. BPH samples obtained from patients and confirmed to be pathologically negative were used as the control group for reducing selection bias. Most of the 272 prostate cancer patients underwent radical prostatectomy, and eight patients who had metastatic lesions in a preoperative radiologic evaluation underwent hormonal therapy plus external radiotherapy. Five patients with prostate cancer were enrolled in a watchful waiting protocol owing to their poor medical condition. Written informed consent was obtained from all study participants. Blood samples were collected in tubes containing sodium EDTA. The QIAamp Blood Extraction kit (Qiagen, Seoul, Korea) was used for DNA extraction. The PSA level was classified as low (PSAo4 ngml 1), intermediate (4pPSAo10 ngml 1) and high (10 ngml 1pPSA). The Gleason score was classified as low (2–6), intermediate (4 þ 3, 3 þ 4) or high (8–10). The clinical and pathological stages were categorized as localized (T1 or T2N0M0), locally advanced (T3 or T4N0M0) and metastatic (TxN þ or M þ ) on the basis of pathological and/ or radiological reports. The clinical characteristics of the cases were similar to a previous Korean study.17
SNP selection and genotyping In this study, we selected 21 SNPs from two international databases (International HapMap and NCBI dbSNPs). SNP selection from the International HapMap database (Han Chinese and Japanese) was carried out as follows: (1) extraction of all genotypes from the CHB and JPN population in the CYP24A1 gene region using HapMart of the International HapMap database (version: release #27; http://www.hapmap.org); (2) the calculation of minor allele frequency and linkage disequilibrium (LD) using the Haploview software (Cambridge, MA, USA; http://www.broad.mit.edu/ mpg/haploview); and (3) selection of SNPs with a minor allele frequency40.05 and tagging SNPs if several SNPs showed high LD40.98. Furthermore, we added the SNPs from NCBI dbSNPs in the CYP24A1 gene region. The selection criteria included location (SNPs in exons were preferred) and amino acid changes (nonsynonymous SNPs were preferred). Accordingly, rs2296241, rs6068816, rs76747058, rs2296239 and rs2762934 were included as nonsynonymous SNPs. Genotyping was performed at the multiplex level using the Illumina Golden Gate genotyping system.18 Briefly, approximately 250 ng of genomic DNA extracted from the blood of each individual was used to genotype each sample that underwent DNA activation, binding to paramagnetic particles, hybridization to oligonucleotides, washing, extension, ligation, amplification by PCR and hybridization to the beadplate in an appropriate hybridization buffer. Image intensities were scanned by a beadxpress reader and genotyped using the GenomeStudio software (Illumina, San Diego, CA, USA). The Prostate Cancer and Prostatic Disease (2014), 149 – 156
genotype quality score for retaining data was set to 0.25. A total of 21 SNPs were successfully genotyped in the 445 DNA samples. All SNPs showed a call rate higher than 98% in cases or controls. Ten samples were randomly selected for genotyping in duplicate. Concordance among duplicate samples was 100%. The overall call rate for all SNPs was 99.8%.
Statistics SNP genotype frequencies were examined for Hardy–Weinberg equilibrium using the w2-statistic, and all were found to be consistent (P40.05) with Hardy–Weinberg equilibrium among Korean controls. Data were analyzed using an unconditional logistic regression to calculate an OR as an estimate of the relative risk of prostate cancer associated with SNP genotypes.19 To determine the association between the genotype and haplotype distributions of patients and controls, a logistic analysis was performed controlling for age (continuous value) as a covariate to eliminate or reduce any confounding factors that might influence the findings. The significant associations are shown in boldface (Pp0.05). In analyzing a model in which a codominant (additive) effect of the variant (V) allele was assumed, the genotypes wild (W)/W, W/V and V/V were coded as 0, 1 and 2, respectively. When a dominant effect was assumed, genotype W/W was coded as 0, and W/V and V/V were coded as 1, whereas W/V and V/V were scored as 0 and V/V was scored as 1 in a model that assumed a recessive effect.20 Lewontin’s D0 (|D0 |) and the LD coefficient r2 were examined to measure LD between all pairs of biallelic loci.21 The haplotypes were inferred from the successfully genotyped SNPs using PHASE algorithm ver. 2.0,22 using SAS version 9.1 (SAS, Cary, NC, USA). The effective number of independent marker loci was calculated to correct multiple testing, using the software SNPSpD (http://www.genepi. qimr.edu.au/general/daleN/SNPSpD/), which is based on the spectral decomposition of matrices of pairwise LD between SNPs.23 The resulting number of independent marker loci (23.1) was applied to correct for multiple testing. All P-values from the results were corrected for multiple testing by controlling for the false discovery rate.24
RESULTS Twenty-one sequence variants in the CYP24A1 gene were examined in this study; 2 were located in the promoter, 14 in introns, 18 in exons and 1 in the 30 -untranslated region (Figure 1a). The measured LD among 21 SNPs was determined by calculating Lewontin’s D0 and r2 values; the results showed that these SNPs were divided into haplotype blocks (Figures 1b and c). The clinical characteristics of the prostate cancer cases and controls are shown in Table 1. The genotype frequencies for each polymorphism in both the prostate cancer and control groups were analyzed using a logistic regression model (Table 2). Among the 21 polymorphisms examined, 11 polymorphisms (rs2248461, rs2248359, rs6022999, rs2585428, rs2296241, rs4809959, rs2181874, rs4809958, rs6068816, rs6127119 and rs2209314) were significantly correlated with having prostate cancer. The rs2248461 (OR: 0.63), rs2248359 (OR: 0.65), rs6022999 (OR: 0.65), rs2585428 (OR: 0.71), rs2296241 (OR: 0.74), rs4809959 (OR: 0.75), rs2181874 (OR: 0.67) and rs2209314 (OR: 0.71) had negative correlation with prostate cancer compared with the control group. Moreover, rs4809958 (1.34), rs6068816 (OR: 1.50) and rs6127119 (OR: 1.41) were in positive correlation with prostate cancer compared with the control group. No significant association was found between the presence of prostate cancer and the other 10 SNPs. In addition, a haplotype association test was performed on 13 common haplotypes (freq.40.05) within four haplotype blocks (Figure 1b). Six haplotypes (CYP24A1_B1_ht1, CYP24A1_B1_ht2, CYP24A1_B2_ht1, CYP24A1_B2_ht2, CYP24A1_B3_ht1 and CYP24A1_B3_ht3) showed a significant association with prostate cancer risk. After correction for multiple testing, estimating a false discovery rate o50% for Po0.01, five SNPs rs2248461, rs2248359, rs6022999, rs2585428, rs4809959) remained as a significant predictor of prostate cancer among aforementioned 11 SNPs (Table 3). Furthermore, among aforementioned six haplotypes, five haplotypes & 2014 Macmillan Publishers Limited
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151
Figure 1. Gene map, haplotypes and LD coefficients for the CYP24A1 polymorphisms. (a) Coding exons are marked by black blocks, and 50 and 30 UTRs by white blocks. (b) Haplotypes of CYP24A1. Only those with frequencies 40.02 are shown. The ‘others’ category contains rare haplotypes. (c) Linkage disequilibrium coefficients (|D0 | and r2) among CYP24A1 polymorphisms.
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Prostate Cancer and Prostatic Disease (2014), 149 – 156
Genetic variations in CYP24A1 and prostate cancer JJ Oh et al
152 Table 1.
Study characteristics of prostate cancer cases and controls Cases (prostate cancer)
N Age (year)±s.d. Body mass index in kgm 2 (%) Prostate volume (cm3)±s.d. PSA, ngml 1 (mean±s.d.)
Controls (BPH)
P-value
272 68.2±6.8 24.1±3.3
173 67.3±8.8 24.0±3.0
0.85 0.41
37.2±18.6
48.4±26.2
0.02
48.2±192.8
5.2±6.7
Gleason score, n (%) p6 7 X8
29 (11) 202 (75) 39 (14)
Clinical stage, n (%) Localized Locally advanced Metastatic
252 (92.6) 12 (3.7) 8 (2.9)
Pathologic stage, n (%) Localized (T2) Advanced (XT3)
152 (60.3) 100 (39.7)
o0.01
(CYP24A1_B1_ht1, CYP24A1_B1_ht2, CYP24A1_B2_ht1, CYP24A1_ B2_ht2 and CYP24A1_B3_ht3) also remained as significant predictors after multiple comparison. Among the 272 prostate cancer patients, associations between target SNPs and several clinical factors, including PSA, clinical stage, pathological stage and Gleason grade, were investigated using a logistic regression model (Table 4). In the analysis of logistic regression model of CYP24A1 polymorphisms according to PSA levels, three SNPs (rs2585428, rs2296241 and rs4809959) were inversely associated with PSA levels both in the codominant model (OR: 0.66, P ¼ 0.02; OR: 0.69, P ¼ 0.04 and OR: 0.67, P ¼ 0.02, respectively) and in the dominant model (OR: 0.56, P ¼ 0.02, OR: 0.62, P ¼ 0.05 and OR: 0.58, P ¼ 0.03). The rs972650 and one haplotype (CYP24A1_B4_ht2) had a significant effect on elevated PSA level in the recessive model (OR: 2.23, P ¼ 0.03 and OR: 2.23, P ¼ 0.03, respectively). In the analysis based on clinical stage criteria (metastatic vs locally advanced vs localized), three SNPs (rs2585428, rs2296241 and rs2762941) had significantly negative association with clinical stage (rs2585428; OR: 0.36 in dominant model, rs2296241; OR: 0.34 in dominant model and rs2762941; OR: 0.38 in codominant model). In the analysis that focused on pathological stage criteria (which was divided into locally advanced and localized), rs2244719 and one haplotype (CYP24A1_B3_ht4) were significantly associated with advanced pathological stage in the codominant model (OR: 1.68 and OR: 2.50, respectively). However, rs2209314 was in negative association with pathological stage (OR: 0.31 in recessive model). When we stratified the patients according to Gleason score, we observed the positive associations between prostate cancer risk and rs2209314 SNPs in the recessive model (OR: 2.65); however, rs6127119 showed negative association with pathologic Gleason score (OR: 0.67) in the co-dominant model.
DISCUSSION The present case–control study was conducted to investigate the potential association between CYP24A1 gene polymorphisms and the risk for prostate cancer in a Korean population. Logistic regression analyses suggested that some CYP24A1 gene polymorphisms were inversely associated with a risk for prostate cancer when compared with those of BPH controls. These results Prostate Cancer and Prostatic Disease (2014), 149 – 156
suggest that CYP24A1 gene polymorphisms may alter the susceptibility to prostate cancer and may be useful as biomarkers for the disease. The growth and differentiation of normal prostatic tissue is also promoted by interactions between the vitamin D and dihydrotestosterone pathways.25 Levels of the bioactive form of vitamin D are controlled by both the activating enzyme 1-A-hydroxylase (coded by CYP27B1) and the deactivating enzyme 24-hydroxylase (coded by CYP24A1), which regulate cell growth and may reduce the risk of malignant transformation. Functional variants in the genes of these pathways are likely to influence prostate carcinogenesis. Significant associations between variants in one or more of the above genes and risk for prostate cancer have been reported but with inconsistent findings. In a branch study of a large randomized controlled trial in the USA (PLCO; prostate, lung, colorectal and ovarian cancer screening trial), Ahn et al.11 investigated the association between prostate cancer and 22 SNPs of CYP24A1 among 749 prostate cancer patients and 781 control patients. Their study demonstrated that there was no significant association between tag SNPs in CYP24A1 and prostate cancer risk. Similarly, Holick et al.13 investigated the associations between 14 SNPs and prostate cancer risk among 630 patients through the Seattle-Puget Sound Surveillance, epidemiology and end results cancer registry, and concluded that CYP24A1 genotypes were not associated with prostate cancer risk. In contrast to the aforementioned studies, our results showed that several CYP24A1 SNPs were significantly associated with prostate cancer risk. Although rs6068816, rs2181874, rs2296241 and rs6022999 had no significant association in the study by Holick et al.,13 only rs6022999 was significantly associated in our study. The rs4809959 and rs2248359 were also significant in our logistic regression model, although they were not in the PLCO study. This disparity may have resulted from two different study conditions, the first being racial differences. The aforementioned negative study for the association between prostate cancer risk and CYP24A1 SNPs was conducted in a western population. The study population of the PLCO trial included non-Hispanic white males in the United States,11 and the study by Holick et al.13 was also conducted in the United States. However, no Asian study has evaluated the association between prostate cancer risk and CYP24A1, and racial differences may affect the results, causing differences between our study and studies from western countries. Indeed, there are significant racial/ ethnic differences in serum vitamin D status. Previous studies have reported that individuals of African ancestry have approximately twofold lower levels of vitamin D than those with European ancestry.14–16 In particular, Asian men had a relatively low vitamin D level compared with Hispanic men.15 This disparity of vitamin D status in each race might lead to the difference of result in the association between prostate cancer and CYP24A1 genetic variants. The second possible influencing factor is different characteristics of the control group. Our study included a control group with a negative prostate biopsy; however, the aforementioned negative study included a control population through the social cohort. Because there were some cases of prostate cancer with a low PSA level and negative digital rectal examination, our study setting was better for reducing selection bias. CYP27B1, which encodes the vitamin D-activating enzyme 1alpha-hydroxylase, and CYP24A1, which encodes for the vitamin D-deactivating enzyme 24-hydroxylase, are both expressed in prostate epithelial cells.26 Our previous study regarding CYP271B SNPs demonstrated no association with prostate cancer risk and any associated factors, such as PSA level, clinical stage, pathological stage and Gleason score (data were not shown). However, 11 SNPs were significantly associated with prostate cancer risk, four SNPs with PSA level, three SNPs with clinical stage, two SNPs with pathological stage and two SNPs with Gleason score. One genome-wide scan for prostate cancer in a USA cohort found no significant association with prostate cancer & 2014 Macmillan Publishers Limited
& 2014 Macmillan Publishers Limited
20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20
rs2248461 rs2248359 rs6022999 rs2585428 rs2245153 rs2296241 rs4809960 rs4809959 rs2181874 rs2762941 rs3787557 rs2244719 rs4809958 rs6068816 rs76747058 rs6127119 rs2209314 rs912505 rs2296239 rs927650 rs2762934 CYP24A1_B1_ht1 CYP24A1_B1_ht2 CYP24A1_B2_ht1 CYP24A1_B2_ht2 CYP24A1_B2_ht3 CYP24A1_B2_ht4 CYP24A1_B3_ht1 CYP24A1_B3_ht2 CYP24A1_B3_ht3 CYP24A1_B3_ht4 CYP24A1_B4_ht1 CYP24A1_B4_ht2 CYP24A1_B4_ht3
Promoter Promoter Intron Intron Intron CDS Intron Intron Intron Intron Intron Intron Intron CDS CDS Intron Intron Intron CDS Intron 3’UTR — — — — — — — — — — — — —
Position
— — — — — A184A — — — — — — — T248T C303S — — — P375P — — — — — — — — — — — — — — —
AA Change
G4A C4T A4G G4A T4C G4A T4C A4G G4A A4G T4C T4C T4G C4T C4G C4T T4C G4A T4C C4T G4A — — — — — — — — — — — — —
Alleles
0.319 0.336 0.199 0.346 0.176 0.360 0.202 0.426 0.207 0.367 0.262 0.149 0.412 0.410 0.015 0.469 0.344 0.441 0.441 0.342 0.100 0.335 0.318 0.441 0.164 0.165 0.063 0.399 0.204 0.156 0.064 0.441 0.342 0.099
PCa (n ¼ 272) 0.419 0.428 0.272 0.434 0.208 0.442 0.214 0.503 0.275 0.358 0.254 0.145 0.350 0.350 0.023 0.393 0.413 0.416 0.416 0.312 0.104 0.428 0.419 0.520 0.240 0.182 0.064 0.332 0.197 0.237 0.061 0.416 0.312 0.104
BPH (n ¼ 173)
Minor allele frequency
0.63 0.65 0.65 0.71 0.85 0.74 0.97 0.75 0.67 1.07 1.04 1.04 1.34 1.33 0.46 1.41 0.71 1.16 1.16 1.20 0.96 0.65 0.63 0.74 0.60 0.92 0.91 1.37 1.09 0.60 1.10 1.16 1.20 0.95
(0.47–0.84) (0.49–0.87) (0.47–0.91) (0.54–0.94) (0.60–1.21) (0.56–0.98) (0.69–1.36) (0.57–0.98) (0.49–0.94) (0.79–1.44) (0.75–1.45) (0.70–1.53) (1.00–1.80) (0.99–1.78) (0.17–1.29) (1.06–1.88) (0.53–0.95) (0.87–1.55) (0.87–1.55) (0.89–1.63) (0.60–1.52) (0.49–0.87) (0.47–0.84) (0.56–0.97) (0.42–0.86) (0.64–1.33) (0.51–1.60) (1.02–1.84) (0.76–1.57) (0.42–0.85) (0.62–1.96) (0.87–1.55) (0.89–1.63) (0.60–1.51)
OR (95% CI)
Codominant
0.002 0.004 0.01 0.02 0.36 0.03 0.87 0.04 0.02 0.68 0.80 0.86 0.05 0.06 0.14 0.02 0.02 0.32 0.32 0.24 0.84 0.004 0.002 0.03 0.005 0.67 0.73 0.04 0.64 0.005 0.74 0.32 0.24 0.83
P-value 0.63 0.66 0.62 0.77 0.86 0.75 1.00 0.84 0.62 1.14 0.95 1.05 1.52 1.50 0.46 1.66 0.68 1.12 1.11 1.21 0.93 0.66 0.63 0.90 0.53 0.90 0.85 1.49 1.06 0.57 1.15 1.12 1.21 0.93
(0.42–0.95) (0.44–1.00) (0.42–0.93) (0.51–1.15) (0.57–1.29) (0.50–1.13) (0.67–1.51) (0.55–1.30) (0.42–0.92) (0.76–1.71) (0.64–1.42) (0.68–1.64) (1.01–2.29) (1.00–2.25) (0.17–1.29) (1.09–2.53) (0.45–1.03) (0.73–1.71) (0.73–1.70) (0.81–1.80) (0.57–1.52) (0.44–0.99) (0.42–0.94) (0.58–1.40) (0.35–0.80) (0.59–1.37) (0.47–1.54) (0.99–2.22) (0.70–1.58) (0.38–0.87) (0.63–2.11) (0.73–1.71) (0.81–1.80) (0.57–1.52)
OR (95% CI)
Dominant
0.03 0.05 0.02 0.20 0.46 0.17 0.99 0.44 0.02 0.52 0.81 0.82 0.04 0.05 0.14 0.02 0.07 0.61 0.62 0.35 0.78 0.05 0.02 0.64 0.003 0.62 0.59 0.05 0.79 0.008 0.65 0.61 0.35 0.76
P-value
Recessive
1.52 1.72 0.40 0.47 1.38 1.42 1.58
1.46 0.57 1.38 1.38 1.42 1.58 0.43 0.40 0.47 0.74 0.99
(0.23–0.71) (0.25–0.76) (0.20–1.25) (0.27–0.77) (0.25–1.79) (0.33–0.92) (0.33–2.01) (0.33–0.83) (0.26–1.43) (0.52–1.77) (0.69–4.26) (0.25–3.50) (0.74–2.37) (0.74–2.37) — (0.87–2.44) (0.32–1.02) (0.81–2.34) (0.81–2.35) (0.73–2.76) (0.14–18.34) (0.25–0.76) (0.23–0.71) (0.30–0.75) (0.25–2.14) (0.32–3.07) — (0.83–2.78) (0.44–6.76) (0.14–1.14) (0.03–7.72) (0.81–2.34) (0.73–2.76) (0.14–18.32)
OR (95% CI) 0.40 0.44 0.50 0.46 0.66 0.55 0.81 0.52 0.61 0.96 1.71 0.94 1.33 1.33
Abbreviations: CI, confidence interval; OR, odds ratio; PCa, prostate cancer. Minor allele frequencies and P-values for logistic analyses of three alternative models (codominant, dominant and recessive models) controlling for age as covariate are shown. Signiciant associations are shown in boldface (P-valuep0.05).
Chr
Logistic regression analysis of CYP24A1 single-nucleotide polymorphisms with the risk of prostate cancer in Korean population
SNP ID
Table 2.
0.002 0.004 0.14 0.004 0.42 0.02 0.65 0.007 0.26 0.89 0.25 0.92 0.34 0.34 — 0.15 0.06 0.24 0.24 0.31 0.72 0.004 0.002 0.001 0.57 0.99 — 0.18 0.44 0.09 0.60 0.24 0.31 0.72
P-value
Genetic variations in CYP24A1 and prostate cancer JJ Oh et al
153
Prostate Cancer and Prostatic Disease (2014), 149 – 156
Genetic variations in CYP24A1 and prostate cancer JJ Oh et al
154 Table 3. Outcome of multiple testing for logistic regression analysis of CYP24A1 single-nucleotide polymorphisms with the risk of prostate cancer in Korean population SNP ID
rs2248461 rs2248359 rs6022999 rs2585428 rs2245153 rs2296241 rs4809960 rs4809959 rs2181874 rs2762941 rs3787557 rs2244719 rs4809958 rs6068816 rs76747058 rs6127119 rs2209314 rs912505 rs2296239 rs927650 rs2762934 CYP24A1_B1_ht1 CYP24A1_B1_ht2 CYP24A1_B2_ht1 CYP24A1_B2_ht2 CYP24A1_B2_ht3 CYP24A1_B2_ht4 CYP24A1_B3_ht1 CYP24A1_B3_ht2 CYP24A1_B3_ht3 CYP24A1_B3_ht4 CYP24A1_B4_ht1 CYP24A1_B4_ht2 CYP24A1_B4_ht3
Chr
20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20
Minor allele frequency
Adjusted P-value after multiple test correction (false discovery rate)
PCa (n ¼ 272)
BPH (n ¼ 173)
Codominant
Dominant
Recessive
0.319 0.336 0.199 0.346 0.176 0.360 0.202 0.426 0.207 0.367 0.262 0.149 0.412 0.410 0.015 0.469 0.344 0.441 0.441 0.342 0.100 0.335 0.318 0.441 0.164 0.165 0.063 0.399 0.204 0.156 0.064 0.441 0.342 0.099
0.419 0.428 0.272 0.434 0.208 0.442 0.214 0.503 0.275 0.358 0.254 0.145 0.350 0.350 0.023 0.393 0.413 0.416 0.416 0.312 0.104 0.428 0.419 0.520 0.240 0.182 0.064 0.332 0.197 0.237 0.061 0.416 0.312 0.104
0.028 0.028 0.049 0.062 0.510 0.078 0.870 0.091 0.062 0.856 0.870 0.870 0.106 0.120 0.264 0.062 0.062 0.473 0.473 0.408 0.870 0.028 0.028 0.078 0.028 0.856 0.868 0.091 0.856 0.028 0.868 0.473 0.408 0.870
0.142 0.142 0.113 0.425 0.782 0.385 0.990 0.782 0.113 0.789 0.845 0.845 0.142 0.142 0.340 0.113 0.183 0.789 0.789 0.661 0.845 0.142 0.113 0.789 0.102 0.789 0.789 0.142 0.845 0.113 0.789 0.789 0.661 0.845
0.021 0.021 0.400 0.021 0.584 0.080 0.770 0.032 0.462 0.949 0.462 0.950 0.495 0.495 — 0.400 0.213 0.462 0.462 0.495 0.794 0.021 0.021 0.021 0.730 0.990 — 0.443 0.587 0.288 0.738 0.462 0.495
Abbreviation: PCa, prostate cancer. Significant associations are shown in boldface (P-value p0.05).
risk for CYP27B1 or CYP24A1.27 Although almost all studies have reported no association between CYP24A1 and prostate cancer risk, recent analysis from prostate cancer cohort consortium showed that the allele in rs6013897 near CYP24A1 decreased aggressive prostate cancer risk.28 However, in their results, aforementioned SNP had a trend for increasing the risk of nonaggressive prostate cancer. Likewise our study had shown the several significant SNPs which supplies ambivalent effect of prostate cancer even included in CYP24A1 gene. And some SNPs had different significance according to logistic model. The rs2209314 had an unfavorable effect on Gleason score, but a favorable effect on pathologic stage. Only rs2585428 had uniform effect on prostate cancer risk, clinical stage and PSA level in trend to decreasing prostate cancer; however, its significance was different according to models; rs2585428 was significantly associated with prostate cancer in the co-dominant model and recessive model, but not in the dominant model. However, it was significantly associated with PSA level in the co-dominant model and dominant model, but not in the recessive model. Although there were limitations, we believe this is the first study to report a significant association between CYP24A1 and prostate cancer risk in an Asian population among patients with histologically proven cancers. Prostate cancer occurs more frequently among African Americans, and this characteristic is consistent with a role for vitamin D deficiency in the etiology of this disease.29 In addition, different Prostate Cancer and Prostatic Disease (2014), 149 – 156
genotype distributions for Caucasians and African Americans have been observed.30 Thus, genetic polymorphisms in vitamin D-related genes may partly explain variations in prostate cancer risk among ethnic groups. Prostate cancer risk likely differs with race and ethnicity, and vitamin D status also differs by country, which may explain the disparity in disease incidence. Our study also investigated the associations between prostate cancer-related factors and CYP24A1 SNPs; several SNPs and haplotypes were significantly associated with PSA level, clinical stage, pathological stage and Gleason score. Our study had several limitations. Our analysis was based on a comparison of samples from patients with prostate cancer and samples from patients with non-malignant BPH as controls. Although our control group was proven as benign via a previous prostate biopsy, all the men in the BPH group were potentially at risk for the development of prostate cancer and may have had latent prostate cancer at the time of their designation as controls, leading to disease misclassification. In this study, we had limitation of only adjusting the age as covariate in logistic analysis, it should be necessary for controlling other health related factors. In addition, we could not adjust for other factors that could alter vitamin D levels, such as sun exposure, calcium intake and vitamin D intake, which could modify the risk estimates, as reported previously.7,8 It is well known that dietary factors, such as calcium and vitamin D, and lifestyle factors, such as body mass index and & 2014 Macmillan Publishers Limited
PSAX10 (n ¼ 112)
4pPSAo10 (n ¼ 98)
Minor allele frequency
& 2014 Macmillan Publishers Limited
Metastatic (n ¼ 8)
Locally advanced (n ¼ 12)
Minor allele frequency
Locally advanced (n ¼ 100)
Localized (n ¼ 152)
Minor allele frequency
High grade (GSX8) (n ¼ 39)
Intermediate (GS 7) (n ¼ 202)
Minor allele frequency Low grade (GSp6) (n ¼ 29)
1.68 (0.99–2.84) 0.72 (0.48–1.08) 2.50 (1.17–5.36)
OR (95% CI)
OR (95% CI)
Dominant
0.05 0.27
P-value
0.09 0.54 0.03
0.59 (0.32–1.08) 1.01 (0.58–1.75)
OR (95% CI)
0.09 0.98
Recessive
(0.30–1.40) (0.30–1.27) (0.32–1.17) (1.10–4.54) (0.29–1.08) (1.10–4.54)
OR (95% CI)
Recessive
1.57 (0.44–5.61) 1.36 (0.38–4.83)
OR (95% CI)
0.65 0.62 0.61 2.23 0.56 2.23
OR (95% CI)
Recessive
0.60 (0.30–1.18) 2.65 (1.15–6.13)
OR (95% CI)
Recessive
4.80 (0.49–46.96) 0.31 (0.11–0.85)
P-value
0.05 0.04 0.06
Dominant
0.36 (0.13–0.99) 0.34 (0.12–0.95) 0.39 (0.14–1.03)
P-value
0.02 0.05 0.03 0.06 0.08 0.06
P-value
P-value
Dominant
(0.35–0.91) (0.38–0.99) (0.35–0.95) (0.40–1.02) (0.39–1.06) (0.40–1.02)
OR (95% CI)
0.56 0.62 0.58 0.64 0.64 0.64
OR (95% CI)
1.65 (0.93–2.94) 0.85 (0.50–1.43) 2.47 (1.12–5.45) Codominant
0.05 0.11 0.02
P-value
0.23 0.19 0.03
P-value
0.02 0.04 0.02 0.80 0.03 0.80
P-value
0.67 (0.45–1.00) 1.26 (0.83–1.91)
Codominant
0.63 (0.29–1.36) 0.60 (0.28–1.29) 0.38 (0.16–0.92)
OR (95% CI)
0.466 0.345
Codominant
(0.46–0.95) (0.49–0.98) (0.47–0.95) (0.67–1.36) (0.48–0.97) (0.67–1.36)
OR (95% CI)
0.66 0.69 0.67 0.95 0.68 0.95
OR (95% CI)
Dominant
0.14 0.02
P-value
0.18 0.02
P-value
0.49 0.64
P-value
0.27 0.19 0.14 0.03 0.08 0.03
P-value
Abbreviations: CI, confidence interval; OR, odds ratio. Minor allele frequencies and P-values for logistic analyses of three alternative models (codominant, dominant and recessive models) controlling for age as covariate are shown. Referents of logistic analysis of CYP24A1 polymorphisms according to PSA criteria was PSAo4 ngml 1. Referents of logistic analysis of CYP24A1 polymorphisms according to clinical stage were localized. Referents of logistic analysis of CYP24A1 polymorphisms according to pathological stage were localized. Referents of logistic analysis of CYP24A1 polymorphisms according to Gleason score (GS) were low grade. Significant associations are shown in boldface (P-valuep0.05).
Logistic analysis of CYP24A1 polymorphisms according to Gleason score criteria rs6127119 0.480 0.517 rs2209314 0.345 0.293
SNP ID
Logistic analysis of CYP24A1 polymorphisms according to pathological stage criteria rs2244719 0.175 0.117 rs2209314 0.314 0.375 CYP24A1_B3_ht4 0.093 0.040
SNP ID
0.353 0.369 0.378
Localized (n ¼ 252)
Logistic analysis of CYP24A1 polymorphisms according to clinical stage criteria rs2585428 0.563 0.000 rs2296241 0.563 0.000 rs2762941 0.313 0.100
SNP ID
0.346 0.360 0.426 0.342 0.472 0.340
PSAo4 (n ¼ 62)
Codominant
Significant CYP24A1 polymorphism after logistic analysis according to variable factors among prostate cancer patients
Logistic analysis of CYP24A1 polymorphisms according to PSA criteria rs2585428 0.321 0.381 rs2296241 0.340 0.393 rs4809959 0.425 0.462 rs927650 0.396 0.340 CYP24A1_B2_ht1 0.350 0.453 CYP24A1_B4_ht2 0.300 0.396
SNP ID
Table 4.
Genetic variations in CYP24A1 and prostate cancer JJ Oh et al
155
Prostate Cancer and Prostatic Disease (2014), 149 – 156
Genetic variations in CYP24A1 and prostate cancer JJ Oh et al
156 physical activity, may influence expression levels.31 Thus, an assessment of the association between the vitamin D metabolism-related gene variants and diet and lifestyle factors is needed to clearly determine the impact of the CYP24A1 gene on cancer etiology. There were limitations, that is, we could not measure the vitamin D level in enrolled patients and could not investigate functional outcomes of CYP24A1 variants to realistic vitamin D mechanistic pathway; nonsynonymous SNPs included in this study did not have significance after multiple comparisons. As heterogeneous prostate cancer patients including metastatic, locally advanced and localized were enrolled in this study, mean PSA level among prostate cancer patients was higher with a large standard deviation, and it should be adjusted in future study. Another limitation was the relatively small cohort included in this analysis. However, this study included a unique racial population, and the control group also had little selection bias owing to their exclusion by biopsy. To confirm the association between aforementioned SNPs and prostate cancerrelated factors, further prospective large cohort study should be necessary to validate our results. CONCLUSIONS The results suggest that some CYP24A1 gene polymorphisms in Korean men might be associated with the risk of developing prostate cancer. As racial/ethnic differences may exist, our study demonstrating an association between prostate cancer and CYP24A1 gene polymorphisms is one of the first efforts in an Asian population. Outside validation of these findings should be performed, especially to find the relationships between several SNPs and prostate cancer-related factors that correlated with prognostic outcomes. CONFLICT OF INTEREST The authors declare no conflict of interest.
ACKNOWLEDGEMENTS This work was supported by grant no. 03-2010-012 from the SNUBH Research Fund, grant of the Korea Healthcare Technology R&D Project, Ministry of Health, Welfare & Family Affairs the Republic of Korea (A085138) and supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2012R1A12006392).
REFERENCES 1 Jemal A, Siegel R, Xu J, Ward E. Cancer statistics, 2010. CA Cancer J Clin 2010; 60: 277–300. 2 Park SK, Sakoda LC, Kang D, Chokkalingam AP, Lee E, Shin HR et al. Rising prostate cancer rates in South Korea. Prostate 2006; 66: 1285–1291. 3 Chan JM, Holick CN, Leitzmann MF, Rimm EB, Willett WC, Stampfer MJ et al. Diet after diagnosis and the risk of prostate cancer progression, recurrence, and death (United States). Cancer Causes Control 2006; 17: 199–208. 4 Chen L, Davey Smith G, Evans DM, Cox A, Lawlor DA, Donovan J et al. Genetic variants in the vitamin D receptor are associated with advanced prostate cancer at diagnosis: findings from the prostate testing for cancer and treatment study and a systematic review. Cancer Epidemiol Biomarkers Prev 2009; 18: 2874–2881. 5 Schumacher FR, Berndt SI, Siddiq A, Jacobs KB, Wang Z, Lindstrom S et al. Genome-wide association study identifies new prostate cancer susceptibility loci. Hum Mol Genet 2011; 20: 3867–3875. 6 Eeles RA, Olama AA, Benlloch S, Saunders EJ, Leongamornlert DA, Tymrakiewicz M et al. Identification of 23 new prostate cancer susceptibility loci using the iCOGS custom genotyping array. Nat Genet 2013; 45: 385–391. 7 Mikhak B, Hunter DJ, Spiegelman D, Platz EA, Hollis BW, Giovannucci E. Plasma 1,25-dihydroxy- and 25-hydroxyvitamin D and subsequent risk of prostate cancer. Cancer Causes Control 2004; 15: 255–265.
Prostate Cancer and Prostatic Disease (2014), 149 – 156
8 Li H, Stampfer MJ, Hollis JB, Mucci LA, Gaziano JM, Hunter D et al. A prospective study of plasma vitamin D metabolites, vitamin D receptor polymorphisms, and prostate cancer. PLoS Med 2007; 4: e103. 9 Mikhak B, Hunter DJ, Spiegelman D, Platz EA, Hollis BW, Giovannucci E. Vitamin D receptor (VDR) gene polymorphisms and haplotypes, interactions with plasma 25hydroxyvitamin D and 1,25-dihydroxyvitamin D, and prostate cancer risk. Prostate 2007; 67: 911–923. 10 Ahonen MH, Zhuang YH, Aine R, Ylikomi T, Tuohimaa P. Androgen receptor and vitamin D receptor in human ovarian cancer: growth stimulation and inhibition by ligands. Int J Cancer 2000; 86: 40–46. 11 Ahn J, Albanes D, Berndt SI, Peters U, Chatterjee N, Freedman ND et al. Vitamin D-related genes, serum vitamin D concentrations and prostate cancer risk. Carcinogenesis 2009; 30: 769–776. 12 Beuten J, Gelfond JA, Franke JL, Weldon KS, Crandall AC, Johnson-Pais TL et al. Single and multigenic analysis of the association between variants in 12 steroid hormone metabolism genes and risk of prostate cancer. Cancer Epidemiol Biomarkers Prev 2009; 18: 1869–1880. 13 Holick CN, Stanford JL, Kwon EM, Ostrander EA, Nejentsev S, Peters U. Comprehensive association analysis of the vitamin D pathway genes, VDR, CYP27B1, and CYP24A1, in prostate cancer. Cancer Epidemiol Biomarkers Prev 2007; 16: 1990–1999. 14 Harris SS, Dawson-Hughes B. Seasonal changes in plasma 25-hydroxyvitamin D concentrations of young American black and white women. Am J Clin Nutr 1998; 67: 1232–1236. 15 Harris SS, Soteriades E, Coolidge JA, Mudgal S, Dawson-Hughes B. Vitamin D insufficiency and hyperparathyroidism in a low income, multiracial, elderly population. J Clin Endocrinol Metab 2000; 85: 4125–4130. 16 Zadshir A, Tareen N, Pan D, Norris K, Martins D. The prevalence of hypovitaminosis D among US adults: data from the NHANES III. Ethn Dis 2005; 15: S5–97-101. 17 Song SY, Kim SR, Ahn G, Choi HY. Pathologic characteristics of prostatic adenocarcinomas: a mapping analysis of Korean patients. Prostate Cancer Prostatic Dis 2003; 6: 143–147. 18 Oliphant A, Barker DL, Stuelpnagel JR, Chee MS. BeadArray technology: enabling an accurate, cost-effective approach to high-throughput genotyping. Biotechniques 2002; Suppl: 56-8: 60–61. 19 Morris JA, Gardner MJ. Calculating confidence intervals for relative risks (odds ratios) and standardised ratios and rates. Br Med J (Clin Res Ed) 1988; 296: 1313–1316. 20 Lewis CM. Genetic association studies: design, analysis and interpretation. Brief Bioinform. 2002; 3: 146–153. 21 Hedrick PW. Gametic disequilibrium measures: proceed with caution. Genetics 1987; 117: 331–341. 22 Stephens M, Smith NJ, Donnelly P. A new statistical method for haplotype reconstruction from population data. Am J Hum Genet 2001; 68: 978–989. 23 Nyholt DR. A simple correction for multiple testing for single-nucleotide polymorphisms in linkage disequilibrium with each other. Am J Hum Genet 2004; 74: 765–769. 24 Benjamini Y, Drai D, Elmer G, Kafkafi N, Golani I. Controlling the false discovery rate in behavior genetics research. Behav Brain Res 2001; 125: 279–284. 25 Leman ES, DeMiguel F, Gao AC, Getzenberg RH. Regulation of androgen and vitamin D receptors by 1,25-dihydroxyvitamin D3 in human prostate epithelial and stromal cells. J Urol 2003; 170: 235–240. 26 Omdahl JL, Morris HA, May BK. Hydroxylase enzymes of the vitamin D pathway: expression, function, and regulation. Annu Rev Nutr. 2002; 22: 139–166. 27 Nomura AM, Stemmermann GN, Lee J, Kolonel LN, Chen TC, Turner A et al. Serum vitamin D metabolite levels and the subsequent development of prostate cancer (Hawaii, United States). Cancer Causes Control 1998; 9: 425–432. 28 Mondul AM, Shui IM, Yu K, Travis RC, Stevens VL, Campa D et al. Genetic variation in the vitamin D pathway in relation to risk of prostate cancer—results from the breast and prostate cancer cohort consortium. Cancer Epidemiol Biomarkers Prev 2013; 22: 688–696. 29 Schwartz GG, Hulka BS. Is vitamin D deficiency a risk factor for prostate cancer? (Hypothesis). Anticancer Res 1990; 10: 1307–1311. 30 Nejentsev S, Godfrey L, Snook H, Rance H, Nutland S, Walker NM et al. Comparative high-resolution analysis of linkage disequilibrium and tag single nucleotide polymorphisms between populations in the vitamin D receptor gene. Hum Mol Genet 2004; 13: 1633–1639. 31 Feskanich D, Hunter DJ, Willett WC, Hankinson SE, Hollis BW, Hough HL et al. Vitamin D receptor genotype and the risk of bone fractures in women. Epidemiology 1998; 9: 535–539.
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