Gene 546 (2014) 156–161
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Common variants of xeroderma pigmentosum genes and prostate cancer risk Aneta Mirecka a,⁎,1, Katarzyna Paszkowska-Szczur a,1, Rodney J. Scott b, Bohdan Górski a, Thierry van de Wetering a, Dominika Wokołorczyk a, Tomasz Gromowski a, Pablo Serrano-Fernandez a, Cezary Cybulski a, Aniruddh Kashyap a, Satish Gupta a,c, Adam Gołąb d, Marcin Słojewski d, Andrzej Sikorski d, Jan Lubiński a, Tadeusz Dębniak a a
Department of Genetics and Pathology, Pomeranian Medical University, Poland School of Biomedical Sciences, University of Newcastle, Australia c Postgraduate School of Molecular Medicine, Warsaw Medical University, Poland d Department of Urology, Pomeranian Medical University, Poland b
a r t i c l e
i n f o
Article history: Received 9 January 2014 Received in revised form 10 June 2014 Accepted 12 June 2014 Available online 13 June 2014 Keywords: Xeroderma pigmentosum Prostate Cancer SNP Polymorphism
a b s t r a c t The genetic basis of prostate cancer (PC) is complex and appears to involve multiple susceptibility genes. A number of studies have evaluated a possible correlation between several NER gene polymorphisms and PC risk, but most of them evaluated only single SNPs among XP genes and the results remain inconsistent. Out of 94 SNPs located in seven XP genes (XPA–XPG) a total of 15 SNPs were assayed in 720 unselected patients with PC and compared to 1121 healthy adults. An increased risk of disease was associated with the XPD SNP, rs1799793 (Asp312Asn) AG genotype (OR = 2.60; p b 0.001) and with the AA genotype (OR = 531; p b 0.0001) compared to the control population. Haplotype analysis of XPD revealed one protective haplotype and four associated with an increased disease risk, which showed that the A allele (XPD rs1799793) appeared to drive the main effect on promoting prostate cancer risk. Polymorphism in XPD gene appears to be associated with the risk of prostate cancer. © 2014 Published by Elsevier B.V.
1. Introduction Prostate cancer (PC) is the most prevalent malignancy among men in North America and Europe. In Poland there were 9273 new cases of PC diagnosed in 2010 and its incidence has increased by 83% over the last 10 years (http://epid.coi.waw.pl/krn/). PC represents one of the leading causes of morbidity and mortality in men, which is considered to be due to a combination of environmental and genetic factors. A Scandinavian twin study suggested that the heritability of prostate cancer could be as high as 42% (Lichtenstein et al., 2000). The genetic basis of prostate cancer is complex and appears to involve multiple susceptibility genes. A number of genome wide association studies (GWAS) have identified over 70 SNPs, associate with disease, each of which is associated with an increased risk of prostate
Abbreviations: PC, prostate cancer; XP genes, xeroderma pigmentosum; GWAS, genome wide association studies; SNP, single nucleotide polymorphism; OR, odds ratio; CI, confidence interval; HWE, Hardy–Weinberg equilibrium; DRE, digital rectal examination. ⁎ Corresponding authors at: International Hereditary Cancer Center, Department of Genetics and Pathology, Pomeranian Medical University, ul. Połabska 4, Szczecin 70-115, Poland. E-mail address: [email protected] (A. Mirecka). 1 These authors contributed equally to this study.
http://dx.doi.org/10.1016/j.gene.2014.06.026 0378-1119/© 2014 Published by Elsevier B.V.
cancer, but the effect sizes are small, with odds ratios ranging from 1.1 to 1.6 (Eeles et al., 2013). To date the number of genes identified for which mutations clearly predispose to prostate cancer is small, and include BRCA2, BRCA1, CHEK2, NBS1 and HOXB13 (Cybulski et al., 2004; Dong et al., 2003; Edwards et al., 2003; Ewing et al., 2012; Kirchhoff et al., 2004; Kote-Jarai et al., 2011; Leongamornlert et al., 2012; Seppala et al., 2003; Struewing et al., 1997; Thorlacius et al., 1997). Four of these, BRCA2, BRCA1, CHEK2, and NBS1 (also known as Nibrin; NBN) are involved in the DNA damage response pathway (Futaki and Liu, 2001). Thus DNA damage signaling pathways play a crucial role in the maintenance of genomic integrity in response to DNA damage and are implicated in the pathogenesis of prostate cancer (Dong et al., 2003; Easton et al., 1999; Edwards et al., 2003; Fan et al., 2000; Gayther et al., 2000; Koivisto and Rantala, 1999; Voelkel-Johnson et al., 2000). Nucleotide excision repair (NER) genes play a crucial role in the maintenance of genomic integrity by removing UV-light-induced DNA lesions (Cleaver, 2002, http://xpmutations.org/genes.html) as well as lesions that are a result of UV-mimetic agents. Numerous polymorphisms of the NER genes have been identified and may, individually or in combination, modify NER capacity, thereby contributing to the development of PC. A number of studies have evaluated a possible correlation between a few NER gene polymorphisms and PC risk, but most have
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evaluated only single SNPs among genes involved in NER that were initially identified in patients with xeroderma pigmentosum that are now referred to as XP genes. The results of these studies remain controversial, as there has not been a large systematic study that has specifically focused on these genes. Genome wide association studies have also not revealed any association between XP genes and PC risk, most likely due to the stringent and highly conservative nature that requires the application of stringent correction for multiple testing in the analysis used to identify genetic risk markers. The aim of this study was to evaluate the role of NER polymorphisms in PC risk and establish whether specific haplotypes of one or more NER genes could be used as a marker of disease risk. Out of 94 SNPs located in seven XP genes a total of 15 SNPs were assayed in 720 unselected patients with PC and compared to 1121 healthy adults. Logistic regression and haplotype analysis were undertaken to assess the impact of these polymorphisms on PC susceptibility. 2. Materials and methods 2.1. Patients We studied a group of 720 unselected PC patients (age range: 41–96, mean age: 68.3) who were diagnosed with disease in two hospitals (Clinic of Urology, Pomeranian Medical University and Division of Urology from Maria Skłodowska-Curie Hospital) between the years 2003 and 2012 in Szczecin, Poland. All men with prostate cancer were invited to participate. Study subjects were asked to participate at the time of diagnosis or during an outpatient visit to an oncology clinic and were unselected for age or family history. The participation rate was 86%. All patients provided a blood sample within six months of diagnosis. A family history was taken either by the construction of a family tree or the completion of a standardized questionnaire. All first- and second-degree relatives diagnosed with prostate cancer and the ages of diagnosis were recorded. Of the 720 men with prostate cancer, 83 had at least one first- or second-degree relative with prostate cancer (familial cases). In addition, information was recorded on PSA level at time of diagnosis and grade (Gleason score). 2.2. Control participants The control group consisted of 1121 healthy men (age range: 35–92, mean age: 64.6) collected between the years 2005 and 2010. These healthy adults had a negative cancer family history for first- and second-degree relatives as assessed by completing a questionnaire about their family's medical history. This was part of a populationbased study of 1.5 million residents of West Pomerania aimed at identifying familial aggregations of malignancies performed recently by our center. During the interview, the goals of the study were explained, informed consent was obtained, genetic counseling was given and a blood sample was taken for DNA analysis. Individuals affected with any malignancy or with cancers diagnosed among first- or second-degree relatives were excluded from our study control group. A blood sample was taken from all men for PSA level and DNA analyses, and digital rectal examination (DRE) was performed. Individuals with abnormal DRE findings or PSA N 4 were excluded from further analyses. All participants signed an informed consent document prior to entering the study. The study was approved by the institutional review board of the Pomeranian Medical University. 2.3. SNP selection All non-synonymous or exon/intron boundary SNPs or those located in UTR sequences (total number: 94) of the 7 DNA repair genes (XPA: 8 SNPs, XPB: 10 SNPs, XPC: 16 SNPs, XPD: 11 SNPs, XPE: 5 SNPs, XPF: 16 SNPs, XPG: 28 SNPs) were selected from http://snpper.chip.org/ and genotyped in our previous study (see Paszkowska-Szczur et al., 2013)
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using the MassARRAY MALDI-TOF MS platform for genotyping (Sequenom Inc., San Diego, CA, USA). This analysis allowed the identification of all XP polymorphic SNPs present in Polish population. Monomorphic SNPs were excluded from further analysis. Out of 94 SNPs, 27 were polymorphic and these were selected for further analyses. 23 SNPs were genotyped among 720 prostate cancer cases and 1121 healthy males using the MassARRAY MALDI-TOF MS platform for genotyping, using 4 TaqMan probes. The minimum threshold for minor allele genotype frequency was set at 5%. Out of 27 polymorphic SNPs, 15 were used in final analyses (Table 1). 2.4. Genotyping Genotyping was performed on DNA isolated from peripheral blood samples taken from PC patients and healthy controls according to the method described previously (Miller et al., 1988). Molecular analysis was performed using a combination of real-time PCR (LightCycler 480, Roche, Penzberg, Germany) and MassARRAY MALDI-TOF MS analysis (Sequenom Inc., San Diego, CA, USA). For real-time PCR TaqMan probes were used (Applied Biosystems, Foster City, CA). MALDI-TOF analysis was based on a primer extension reaction to detect and determine the SNP allele. Reactions were performed according to the manufacturer's instructions. 2.5. Sequencing Random DNA samples were sequenced to verify the results of the MassARRAY genotyping and real-time PCR analysis (data not shown). Sequencing was conducted using universal primers in combination with the ABI PRISM BigDye Terminator Cycle kit (Applied Biosystems, Foster City, CA). 2.6. Statistics Genotype frequency differences, the odds ratio (OR) and 95% confidence intervals (95%CI) were estimated using regression analysis for an additive model of inheritance. Logistic regression analysis was performed using the R software environment (version 2.15.0). Possible deviation of the allele frequencies from those expected under Hardy–Weinberg equilibrium (HWE) was also assessed using the Chi-square probability test (Ott, 1988, http://www.hgmp.mrc.ac. uk/Registered/Help/linkutil/). For statistical evaluation of mean age a t-test was used. Median PSA level was calculated using the Mann–Whitney test. Haplotype frequencies and their potential association with disease risk were estimated using the haplo.stats CRAN package (version 1.5.5) by Sinnwell and Schaid for the R environment. Statistical power was calculated using the pwr package of R (version 2.15.0). Linkage disequilibrium between SNPs for a given haplotype was calculated using the software JLIN by Carter et al. (2006). Bonferroni correction for multiple testing was applied to all results that demonstrated a significant difference between the cases and controls. 3. Results There was no evidence that the genotype frequencies of the examined variants deviated from those expected under HWE for the control and patient groups (Table 1). From the 15 SNPs analyzed, logistic regression analysis revealed that one SNP in XPD was associated with PC risk. An increased risk of disease was associated with rs1799793 (Asp312Asn) AG genotype (OR = 2.60; p b 0.001) and a further increase in risk with the AA genotype (OR = 5.31; p b 0.0001) compared to the control population.
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Table 1 Association of common variants of XP genes with prostate risk. Gene
SNP
Ga
Cases
Controls
p-Value
OR
95%CI
HWE
PTb
XPB
rs9282675
G1475A
507 (97.31%) 10 (1.92%) 4 (0.77%) 532 (93.66%) 30 (5.28%) 6 (1.06%) 214 (35.55%) 290 (48.17%) 98 (16.28%) 310 (62.38%) 167 (33.60%) 20 (4.02%) 290 (58.94%) 163 (33.13%) 39 (7.93%) 632 (95.90%) 27 (4.10%) 0 (0%) 113 (22.07%) 300 (58.59%) 99 (19.34%) 231 (35.27%) 302 (46.11%) 122 (18.62%) 199 (34.79%) 249 (43.53%) 124 (21.68%) 565 (88.84%) 65 (10.22%) 6 (0.94%) 315 (59.32%) 173 (32.58%) 43 (8.10%) 221 (35.59%) 272 (43.80%) 128 (20.61%) 577 (93.82%) 37 (6.02%) 1 (0.16%) 485 (84.94%) 83 (14.54%) 3 (0.52%) 396 (62.26%) 208 (32.71%) 32 (5.03%)
651 (97.17%) 15 (2.23%) 4 (0.6%) 691 (91.04%) 68 (8.96%) 0 (0%) 265 (34.37%) 384 (49.81%) 122 (15.82%) 440 (54.52%) 312 (38.66%) 55 (6.81%) 454 (51.82%) 347 (42.64%) 52 (5.54%) 809 (92.88%) 61 (7.00%) 1 (0.12%) 141 (20.80%) 411 (60.62%) 126 (18.58%) 319 (34.49%) 444 (48.00%) 162 (17.51%) 377 (60.13%) 218 (34.76%) 32 (5.13%) 688 (88.20%) 90 (11.54%) 2 (0.26%) 433 (56.09%) 288 (37.30%) 51 (6.61%) 259 (33.16%) 368 (47.12%) 154 (19.72%) 732 (93.49%) 49 (6.26%) 2 (0.25%) 682 (87.21%) 99 (12.66%) 1 (0.13%) 523 (67.22%) 224 (28.79%) 31 (3.99%)
– 0.6784 0.8669 – 0.0140 (0.21*) NA – 0.5779 0.9742 – 0.0234 (0.351*) 0.0148 (0.222*) – 0.024 (0.36*) 0.3155 – 0.0166 (0.249*) NA – 0.5260 0.9145 – 0.5832 0.7908 – p b 0.0001 (0.0015*) p b 0.0001 (0.0015*) – 0.4562 0.1134 – 0.1147 0.5022 – 0.2375 0.8616 – 0.8484 0.7104 – 0.3043 0.2131 – 0.0814 0.2345
– 0.7951 1.0121 – 0.5730 NA – 0.9352 0.9947 – 0.7661 0.5250 – 0.6832 1.2590 – 0.5666 NA – 0.9108 0.9804 – 0.9393 1.0400 – 2.5952 5.3100 – 0.8794 3.6531 – 0.8257 1.1590 – 0.8662 0.9741 – 0.9579 0.6343 – 1.1789 4.2186 – 1.2264 1.3633
– 0.4318–1.4547 0.5445–1.1841 – 0.3675–0.8935 NA – 0.7386–1.1841 0.7215–1.3714 – 0.7510–1.2173 0.2250–0.6249 – 0.5390–0.8659 0.8030–1.9739 – 0.3559–0.9019 NA – 0.6823–1.2157 0.6831–1.4071 – 0.7510–1.1748 0.7785–1.3893 – 2.0117–3.3479 3.6352–7.7566 – 0.6273–1.2330 0.7345–18.1700 – 0.6509–1.0475 0.7532–1.7834 – 0.6826–1.0993 0.7251–1.3086 – 0.6166–1.4883 0.0574–7.0130 – 0.8612–1.6139 0.4375–40.6784 – 0.9749–1.5427 0.8179–2.2724
0.35
XPC
CC CT TT GG AG AA AA AC CC CC CT TT GG AG AA CC CT TT CC AC AA AA AC CC CC CT TT CC CT TT GG AG AA CC CT TT AA AG GG GG CG CC GG CG CC
– 0.97 0.15 – 0.36 NA – 0.009 0.004 – 0.13 0.22 – 0.43 0.04 – 0.32 NA – 0.01 0.005 – 0.02 0.009 – 0.56 1 – 0.01 0.12 – 0.12 0.03 – 0.05 0.006 – 0.004 0.006 – 0.03 0.05 – 0.09 0.03
rs2228001
rs2228000
G2061A
rs3731062
XPD
rs238406
rs13181
rs1799793
XPE
rs1050244
XPF
rs762521
XPG
rs1047768
rs1047769
rs2227869
rs17655
a b
0.19
0.38
0.13
0.18
0.89
0.24
0.72
0.94
0.59
0.74
0.26
0.23
0.18
0.26
Genotype. Statistical power test.
These results all remained significant after Bonferroni correction (see Table 1). We found a non-significant tendency towards a decreased PC risk for the XPC rs2228000 (Ala499Val) TT genotype (OR = 0.29; p = 0.222) compared to the reference genotype (CC) and the CT genotype (OR = 0.76; p = 0.351). None of the other SNPs were found to be associated with PC risk. 3.1. Age and PC risk For XPD, the rs1799793 polymorphism in patients over 65 years of age who were heterozygous carriers of the rs1799793 SNP appeared to have a slightly greater increased risk of PC compared to the control population (OR = 2.92, p b 0.0015corrected) than those under 65 years of age (OR = 2.28, p b 0.0015corrected). Interestingly, patients under 65 years of age who are homozygous carriers of this SNP had a similar risk of PC (OR = 5.89, p b 0.0015corrected) than those patients over 65 (OR = 5.44, p b 0.0015corrected) (Supplementary Tables 1, 2). Age stratification analysis revealed non-significant differences between the associations of the XPC rs2228000_TT genotype in patients under and over 65. The protective effect of rs2228000_TT genotype was stronger among patients under 65 years of age (OR =
0.31, p = 0.0685) than those over 65 years (OR = 0.48, p = 0.093) (Supplementary Tables 1, 2). The mean age at diagnosis was 67 years for carriers of the XPD rs1799793 mutation versus 68 years for non-carriers (p = 0.9).
3.2. Gleason score and PSA level We found no significant differences of the allele distribution of the examined SNPs among less-aggressive (Gleason 2–6) compared to more aggressive prostate cancers (Gleason N 6). There were also nonsignificant differences in the prevalence of the SNPs among high-PSA scores (N10) compared to lower PSA levels (b10) (Supplementary Table 3). Carriers and non-carriers of rs1799793 were similar with respect to PSA level at diagnosis (median PSA level was 12.0 in carriers vs 11.5 in non-carriers; p = 0.8). Aggressive cancers (Gleason 7–10) were seen in 48% carriers versus 49.2% non-carriers (p = 1.0).
3.3. Haplotype analysis Using the haplo.stats CRAN package (version 1.5.5) we undertook haplotype analysis for XPC. Differences in the haplotype structure
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revealed no significant differences in disease risk between cases and controls (see Supplementary Table 4). Haplotype analysis of XPD revealed one protective haplotype and four that were associated with an increase in disease risk (see Table 2). Differences in the XPG haplotype structure revealed no significant differences in disease risk between cases and controls (see Supplementary Table 5). 3.3.1. Linkage disequilibrium The linkage disequilibrium (LD) plot was calculated on the basis of the genotype frequencies in our control population. The whole fragment between the six analyzed SNPs in XPC is in linkage disequilibrium and most of them with D′ values approaching 1.0. Only G1475A ↔ rs3731062 (D′ value ranges 0.2–0.4) and A2815C ↔ rs222800 and rs2228001 ↔ rs2228000 (D′ values range 0.6–0.8) were considered not to be in high LD. 3.3.2. Gene–gene interaction Multivariate logistic regression was applied to identify possible dual interactions between the 15 SNPs (120 interactions: 105 possible SNP pairs with several genotype combinations, each). No significant interaction could be identified (p-values ranging from 0.9976167 to 0.9999999) (see Supplementary Table 6). 4. Discussion In the current study that included 720 patients with prostate cancer and 1121 healthy men, we found overall that the XPD rs1799793 (Asp312Asn) polymorphism was significantly associated with prostate cancer risk. Logistic regression analysis of XPD genotypes in our study revealed an association with XPD rs1799793 (Asp312Asn) AG and AA genotypes with an increased PC risk. These results were further supported by haplotype analysis, which showed that the A allele (XPD rs1799793) appeared to drive the main effect on promoting prostate cancer risk. The XPD Asp312Asn polymorphism (rs1799793) at position 312 in exon 10 is characterized by a G to A substitution resulting in aspartic amino acid to asparagine amino acid exchange (Butkiewicz et al. 2001). This non-conservative amino acid exchange is found in an evolutionary highly conserved region (Shen et al. 1998). Asp312Asn amino acid substitution is not found in functional domains of XPD, but 312 Asp is located in the seven-motif helicase domain of the RecQ family of DNA helicases (Butkiewicz et al. 2001). RecQ enzymes are a subfamily of helicases that play an essential role in the maintenance of genome stability by acting at the interface between DNA replication, recombination, and repair (Bachrati and Hickson, 2008). Conservation of 312 Asp residue suggests that it is important for normal protein structure and integrity (Butkiewicz et al. 2001, Shen et al. 1998). The 312 variant (Asn) has the acidic moiety of the aspartic acid removed (Benhamou and Sarasin, 2002). The amino acid substitution could result in a protein malfunction in either repair capacity or fidelity (Butkiewicz et al. 2001, Shen et al. 1998). Asp312Asn substitution may modify protein folding and thus affect the protein function (Affatato et al. 2004).
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Previous reports assessing the association of XPD polymorphisms with the risk of PC have been inconclusive. Three meta-analyses (Ma et al., 2013; Mi et al., 2012; Zhu et al., 2012), which included respectively, 8 studies (2641 cases and 3259 controls), 8 studies (2620 cases and 3225 controls) and 9 studies (2555 cases and 3182 controls) for the XPD Asp312Asn polymorphism, showed a significant association between prostate cancer risk and SNP, which is consistent with our results. In contrast the results reported by Zhu et al. (2012) in their metaanalysis examining 5765 cases and 6270 controls (derived from 15 studies) revealed no evidence of a modifying effect of the XPD Asp312Asn polymorphism. Similarly, Agalliu et al. (2010) examined 1457 cases and 1351 controls and demonstrated no association between XPD Asp312Asn and Lys751Gln with disease risk. Additionally Lavender et al. (2010) investigated 208 PC patients and 605 controls and failed to detect any correlation of the XPD Asp312Asn polymorphisms and PC. The results of the present study revealed a lack of association between XPD Lys751Gln and PC risk, which confirmed those reports described above (Agalliu et al., 2010; Ma et al., 2013; Zhu et al., 2012; Zhu et al., 2013). Moreover, a few studies showed nonsignificant associations between XPD Lys751Gln polymorphisms and PC risk (Mi et al., 2012; Ritchey et al., 2005; Sobti et al., 2012). Taken together, our results support previous published findings about the absence of any association of XPD Lys751Gln with prostate cancer. Logistic regression showed a tendency of the XPC rs2228000_TT genotype towards an association with a decreased PC risk. We found no association between the remaining variants of XPC and PC risk. As far as we can ascertain, only a few studies have investigated the role of XPC in PC development but most of them were performed in Asian populations and we cannot rule out the possibility of population stratification. None of these studies examined the association of the rs2228000 polymorphism with PC risk. Hirata et al. (2007) examined 165 cases of prostate cancer and 165 controls and suggested a correlation between the XPC 939Gln variant and decreased PC risk in the Japanese population. In contrast, Liu et al. (2012) examined 202 PC patients and 221 healthy controls in a Chinese population and reported that the XPC Lys939Gln polymorphism is not associated with disease risk. They also assessed the correlation between XPC-PAT polymorphisms and PC cancer development and revealed that the PAT+/+ genotype was associated with a 2.11-fold increase in PC risk. Similar findings were observed by Mandal et al. (2012) in an Indian case–control study of 192 cases and 224 controls. In that study the XPC PAT +/+ genotype increased PC risk by 2.55-fold, but they also found that the CC genotype in XPC Lys939Gln was significantly associated with disease risk. These results were corroborated by Mittal and Mandal (2012) in their study that examined 195 prostate cancer cases and 250 controls. Analysis showed that XPC Lys939Gln and XPC-PAT polymorphisms were associated with PC development. The different results obtained by Agalliu et al. (2010) in their 2 population-based studies that included 1457 cases and 1352 controls from the USA suggested no association between SNPs in XPC and PC development. Recent results of two meta-analyses of common variants of XPC and prostate cancer risk have been published. In the first study the prevalence of rs2228001 (Lys939Gln) was evaluated among 1966 prostate cancer patients and no association of this variant with disease risk was found (He et al., 2013). The subject
Table 2 Haplotype frequency of examined XPD variants between cases (n = 706) and controls (n = 928). rs238406
rs13181
rs1799793
p-Value
OR
95%CI
Control haplotype frequency [%]
Case haplotype frequency [%]
A C C A C A A C
A C A C C C A A
G G G G A A A A
Ref b0.001 0.002 0.41 b0.001 b0.001 b0.001 b0.001
1.00 0.37 0.92 2.20 1.37 12.62 24.02 3.96
Ref 0.24–0.56 0.63–1.33 1.45–3.35 1.10–1.71 2.85–55.92 3.12–184.91 2.63–5.98
43 16 12 5 20 0.2 0.1 3
34 5 9 9 25 3 3 13
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of the second study was the PAT polymorphism, reported by authors to be associated with cancer risk, especially the urinary system cancer. It consists of an insertion of 83 bases of A and T (Dai et al., 2013) and a 5 base deletion within intron 9. Since we genotyped single nucleotide polymorphisms/point mutations only, in this study we did not analyze XPC-PAT polymorphisms but we did assess the XPC Lys939Gln polymorphism and did not found any association with PC risk. Together, the evidence suggests that XPC acts differentially on disease risk between Asian and European prostate cancer patients, which is most likely due to population stratification. None of the SNPs in XPE, XPF, and XPG were associated with disease risk in the Polish population. XPB, XPE and XPF genes have not previously been examined with respect to its role in PC susceptibility. A small study of an Indian population examining the XPG Asp1104His (rs17655) SNP conducted on 150 PC cases and 150 controls revealed that the synonymous SNP genotype increased PC risk (Berhane et al., 2012). Our findings do not support this finding, which may be due to population stratification, or more likely since it was performed on a small population that it lacks sufficient power to detect any real difference between the two groups. Evaluation of XP gene–gene interactions revealed no significant results, however it seems that for such analysis the sample size studied herein was too small and type 2 statistical errors cannot be excluded. In summary, this study reveals that polymorphisms in some of the nucleotide excision repair genes appear to be related to the risk of prostate cancer. There was no association with Gleason score suggesting that these genes or their variants are not associated with disease progression but only the risk of acquiring disease. The failure of these SNPs to be detected in larger GWAS of PC is not surprising given the highly stringent statistical cut-offs used to define associations in these studies. Understanding the role of nucleotide excision repair in PC is an important step in identifying predisposing factors to be used in a strategy to reduce disease risk. Conflict of interest None declared. Acknowledgment The study was partially funded by Polish Ministry of Science and Higher Education (MNiSW), project number MB-158-79/13. Appendix A. Supplementary data Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.gene.2014.06.026. References Affatato, A.A., Wolfe, K.J., Lopez, M.S., Hallberg, C., Ammenheuser, M.M., Abdel-Rahman, S.Z., 2004. Effect of XPD/ERCC2 polymorphisms on chromosome aberration frequencies in smokers and on sensitivity to the mutagenic tobacco-specific nitrosamine NNK. Environ. Mol. Mutagen. 44, 65–73. Agalliu, I., Kwon, E.M., Salinas, C.A., Koopmeiners, J.S., Ostrander, E.A., Stanford, J.L., 2010. Genetic variation in DNA repair genes and prostate cancer risk: results from a population-based study. Cancer Causes Control 21, 289–300. Bachrati, C.Z., Hickson, I.D., 2008. RecQ helicases: guardian angels of the DNA replication fork. Chromosoma 117, 219–233. Benhamou, S., Sarasin, A., 2002. ERCC2/XPD gene polymorphisms and cancer risk. Mutagenesis 17, 463–469. Berhane, N., Sobti, R.C., Mahdi, S.A., 2012. DNA repair genes polymorphism (XPG and XRCC1) and association of prostate cancer in a north Indian population. Mol. Biol. Rep. 39, 2471–2479. Butkiewicz, D., Rusin, M., Enewold, L., Shields, P.G., Chorazy, M., Harris, C.C., 2001. Genetic polymorphisms in DNA repair genes and risk of lung cancer. Carcinogenesis 22, 593–597. Carter, K.W., McCaskie, P.A., Palmer, L.J., 2006. JLIN: a java based linkage disequilibrium plotter. BMC Bioinforma. 7, 60.
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No association between variant DNA repair genes and prostate cancer risk among men of African descent. Prostate 70, 113–119. Leongamornlert, D., Mahmud, N., Tymrakiewicz, M., Saunders, E., Dadaev, T., Castro, E., Goh, C., Govindasami, K., Guy, M., O'Brien, L., Sawyer, E., Hall, A., Wilkinson, R., Easton, D., Goldgar, D., Eeles, R., Kote-Jarai, Z., 2012. Germline BRCA1 mutations increase prostate cancer risk. Br. J. Cancer 106, 1697–1701. Lichtenstein, P., Holm, N.V., Verkasalo, P.K., Iliadou, A., Kaprio, J., Koskenvuo, M., Pukkala, E., Skytthe, A., Hemminki, K., 2000. Environmental and heritable factors in the
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Common variants of xeroderma pigmentosum genes and prostate cancer risk Aneta Mirecka a,⁎,1, Katarzyna Paszkowska-Szczur a,1, Rodney J. Scott b, Bohdan Górski a, Thierry van de Wetering a, Dominika Wokołorczyk a, Tomasz Gromowski a, Pablo Serrano-Fernandez a, Cezary Cybulski a, Aniruddh Kashyap a, Satish Gupta a,c, Adam Gołąb d, Marcin Słojewski d, Andrzej Sikorski d, Jan Lubiński a, Tadeusz Dębniak a a
Department of Genetics and Pathology, Pomeranian Medical University, Poland School of Biomedical Sciences, University of Newcastle, Australia c Postgraduate School of Molecular Medicine, Warsaw Medical University, Poland d Department of Urology, Pomeranian Medical University, Poland b
a r t i c l e
i n f o
Article history: Received 9 January 2014 Received in revised form 10 June 2014 Accepted 12 June 2014 Available online 13 June 2014 Keywords: Xeroderma pigmentosum Prostate Cancer SNP Polymorphism
a b s t r a c t The genetic basis of prostate cancer (PC) is complex and appears to involve multiple susceptibility genes. A number of studies have evaluated a possible correlation between several NER gene polymorphisms and PC risk, but most of them evaluated only single SNPs among XP genes and the results remain inconsistent. Out of 94 SNPs located in seven XP genes (XPA–XPG) a total of 15 SNPs were assayed in 720 unselected patients with PC and compared to 1121 healthy adults. An increased risk of disease was associated with the XPD SNP, rs1799793 (Asp312Asn) AG genotype (OR = 2.60; p b 0.001) and with the AA genotype (OR = 531; p b 0.0001) compared to the control population. Haplotype analysis of XPD revealed one protective haplotype and four associated with an increased disease risk, which showed that the A allele (XPD rs1799793) appeared to drive the main effect on promoting prostate cancer risk. Polymorphism in XPD gene appears to be associated with the risk of prostate cancer. © 2014 Published by Elsevier B.V.
1. Introduction Prostate cancer (PC) is the most prevalent malignancy among men in North America and Europe. In Poland there were 9273 new cases of PC diagnosed in 2010 and its incidence has increased by 83% over the last 10 years (http://epid.coi.waw.pl/krn/). PC represents one of the leading causes of morbidity and mortality in men, which is considered to be due to a combination of environmental and genetic factors. A Scandinavian twin study suggested that the heritability of prostate cancer could be as high as 42% (Lichtenstein et al., 2000). The genetic basis of prostate cancer is complex and appears to involve multiple susceptibility genes. A number of genome wide association studies (GWAS) have identified over 70 SNPs, associate with disease, each of which is associated with an increased risk of prostate
Abbreviations: PC, prostate cancer; XP genes, xeroderma pigmentosum; GWAS, genome wide association studies; SNP, single nucleotide polymorphism; OR, odds ratio; CI, confidence interval; HWE, Hardy–Weinberg equilibrium; DRE, digital rectal examination. ⁎ Corresponding authors at: International Hereditary Cancer Center, Department of Genetics and Pathology, Pomeranian Medical University, ul. Połabska 4, Szczecin 70-115, Poland. E-mail address: [email protected] (A. Mirecka). 1 These authors contributed equally to this study.
http://dx.doi.org/10.1016/j.gene.2014.06.026 0378-1119/© 2014 Published by Elsevier B.V.
cancer, but the effect sizes are small, with odds ratios ranging from 1.1 to 1.6 (Eeles et al., 2013). To date the number of genes identified for which mutations clearly predispose to prostate cancer is small, and include BRCA2, BRCA1, CHEK2, NBS1 and HOXB13 (Cybulski et al., 2004; Dong et al., 2003; Edwards et al., 2003; Ewing et al., 2012; Kirchhoff et al., 2004; Kote-Jarai et al., 2011; Leongamornlert et al., 2012; Seppala et al., 2003; Struewing et al., 1997; Thorlacius et al., 1997). Four of these, BRCA2, BRCA1, CHEK2, and NBS1 (also known as Nibrin; NBN) are involved in the DNA damage response pathway (Futaki and Liu, 2001). Thus DNA damage signaling pathways play a crucial role in the maintenance of genomic integrity in response to DNA damage and are implicated in the pathogenesis of prostate cancer (Dong et al., 2003; Easton et al., 1999; Edwards et al., 2003; Fan et al., 2000; Gayther et al., 2000; Koivisto and Rantala, 1999; Voelkel-Johnson et al., 2000). Nucleotide excision repair (NER) genes play a crucial role in the maintenance of genomic integrity by removing UV-light-induced DNA lesions (Cleaver, 2002, http://xpmutations.org/genes.html) as well as lesions that are a result of UV-mimetic agents. Numerous polymorphisms of the NER genes have been identified and may, individually or in combination, modify NER capacity, thereby contributing to the development of PC. A number of studies have evaluated a possible correlation between a few NER gene polymorphisms and PC risk, but most have
A. Mirecka et al. / Gene 546 (2014) 156–161
evaluated only single SNPs among genes involved in NER that were initially identified in patients with xeroderma pigmentosum that are now referred to as XP genes. The results of these studies remain controversial, as there has not been a large systematic study that has specifically focused on these genes. Genome wide association studies have also not revealed any association between XP genes and PC risk, most likely due to the stringent and highly conservative nature that requires the application of stringent correction for multiple testing in the analysis used to identify genetic risk markers. The aim of this study was to evaluate the role of NER polymorphisms in PC risk and establish whether specific haplotypes of one or more NER genes could be used as a marker of disease risk. Out of 94 SNPs located in seven XP genes a total of 15 SNPs were assayed in 720 unselected patients with PC and compared to 1121 healthy adults. Logistic regression and haplotype analysis were undertaken to assess the impact of these polymorphisms on PC susceptibility. 2. Materials and methods 2.1. Patients We studied a group of 720 unselected PC patients (age range: 41–96, mean age: 68.3) who were diagnosed with disease in two hospitals (Clinic of Urology, Pomeranian Medical University and Division of Urology from Maria Skłodowska-Curie Hospital) between the years 2003 and 2012 in Szczecin, Poland. All men with prostate cancer were invited to participate. Study subjects were asked to participate at the time of diagnosis or during an outpatient visit to an oncology clinic and were unselected for age or family history. The participation rate was 86%. All patients provided a blood sample within six months of diagnosis. A family history was taken either by the construction of a family tree or the completion of a standardized questionnaire. All first- and second-degree relatives diagnosed with prostate cancer and the ages of diagnosis were recorded. Of the 720 men with prostate cancer, 83 had at least one first- or second-degree relative with prostate cancer (familial cases). In addition, information was recorded on PSA level at time of diagnosis and grade (Gleason score). 2.2. Control participants The control group consisted of 1121 healthy men (age range: 35–92, mean age: 64.6) collected between the years 2005 and 2010. These healthy adults had a negative cancer family history for first- and second-degree relatives as assessed by completing a questionnaire about their family's medical history. This was part of a populationbased study of 1.5 million residents of West Pomerania aimed at identifying familial aggregations of malignancies performed recently by our center. During the interview, the goals of the study were explained, informed consent was obtained, genetic counseling was given and a blood sample was taken for DNA analysis. Individuals affected with any malignancy or with cancers diagnosed among first- or second-degree relatives were excluded from our study control group. A blood sample was taken from all men for PSA level and DNA analyses, and digital rectal examination (DRE) was performed. Individuals with abnormal DRE findings or PSA N 4 were excluded from further analyses. All participants signed an informed consent document prior to entering the study. The study was approved by the institutional review board of the Pomeranian Medical University. 2.3. SNP selection All non-synonymous or exon/intron boundary SNPs or those located in UTR sequences (total number: 94) of the 7 DNA repair genes (XPA: 8 SNPs, XPB: 10 SNPs, XPC: 16 SNPs, XPD: 11 SNPs, XPE: 5 SNPs, XPF: 16 SNPs, XPG: 28 SNPs) were selected from http://snpper.chip.org/ and genotyped in our previous study (see Paszkowska-Szczur et al., 2013)
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using the MassARRAY MALDI-TOF MS platform for genotyping (Sequenom Inc., San Diego, CA, USA). This analysis allowed the identification of all XP polymorphic SNPs present in Polish population. Monomorphic SNPs were excluded from further analysis. Out of 94 SNPs, 27 were polymorphic and these were selected for further analyses. 23 SNPs were genotyped among 720 prostate cancer cases and 1121 healthy males using the MassARRAY MALDI-TOF MS platform for genotyping, using 4 TaqMan probes. The minimum threshold for minor allele genotype frequency was set at 5%. Out of 27 polymorphic SNPs, 15 were used in final analyses (Table 1). 2.4. Genotyping Genotyping was performed on DNA isolated from peripheral blood samples taken from PC patients and healthy controls according to the method described previously (Miller et al., 1988). Molecular analysis was performed using a combination of real-time PCR (LightCycler 480, Roche, Penzberg, Germany) and MassARRAY MALDI-TOF MS analysis (Sequenom Inc., San Diego, CA, USA). For real-time PCR TaqMan probes were used (Applied Biosystems, Foster City, CA). MALDI-TOF analysis was based on a primer extension reaction to detect and determine the SNP allele. Reactions were performed according to the manufacturer's instructions. 2.5. Sequencing Random DNA samples were sequenced to verify the results of the MassARRAY genotyping and real-time PCR analysis (data not shown). Sequencing was conducted using universal primers in combination with the ABI PRISM BigDye Terminator Cycle kit (Applied Biosystems, Foster City, CA). 2.6. Statistics Genotype frequency differences, the odds ratio (OR) and 95% confidence intervals (95%CI) were estimated using regression analysis for an additive model of inheritance. Logistic regression analysis was performed using the R software environment (version 2.15.0). Possible deviation of the allele frequencies from those expected under Hardy–Weinberg equilibrium (HWE) was also assessed using the Chi-square probability test (Ott, 1988, http://www.hgmp.mrc.ac. uk/Registered/Help/linkutil/). For statistical evaluation of mean age a t-test was used. Median PSA level was calculated using the Mann–Whitney test. Haplotype frequencies and their potential association with disease risk were estimated using the haplo.stats CRAN package (version 1.5.5) by Sinnwell and Schaid for the R environment. Statistical power was calculated using the pwr package of R (version 2.15.0). Linkage disequilibrium between SNPs for a given haplotype was calculated using the software JLIN by Carter et al. (2006). Bonferroni correction for multiple testing was applied to all results that demonstrated a significant difference between the cases and controls. 3. Results There was no evidence that the genotype frequencies of the examined variants deviated from those expected under HWE for the control and patient groups (Table 1). From the 15 SNPs analyzed, logistic regression analysis revealed that one SNP in XPD was associated with PC risk. An increased risk of disease was associated with rs1799793 (Asp312Asn) AG genotype (OR = 2.60; p b 0.001) and a further increase in risk with the AA genotype (OR = 5.31; p b 0.0001) compared to the control population.
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Table 1 Association of common variants of XP genes with prostate risk. Gene
SNP
Ga
Cases
Controls
p-Value
OR
95%CI
HWE
PTb
XPB
rs9282675
G1475A
507 (97.31%) 10 (1.92%) 4 (0.77%) 532 (93.66%) 30 (5.28%) 6 (1.06%) 214 (35.55%) 290 (48.17%) 98 (16.28%) 310 (62.38%) 167 (33.60%) 20 (4.02%) 290 (58.94%) 163 (33.13%) 39 (7.93%) 632 (95.90%) 27 (4.10%) 0 (0%) 113 (22.07%) 300 (58.59%) 99 (19.34%) 231 (35.27%) 302 (46.11%) 122 (18.62%) 199 (34.79%) 249 (43.53%) 124 (21.68%) 565 (88.84%) 65 (10.22%) 6 (0.94%) 315 (59.32%) 173 (32.58%) 43 (8.10%) 221 (35.59%) 272 (43.80%) 128 (20.61%) 577 (93.82%) 37 (6.02%) 1 (0.16%) 485 (84.94%) 83 (14.54%) 3 (0.52%) 396 (62.26%) 208 (32.71%) 32 (5.03%)
651 (97.17%) 15 (2.23%) 4 (0.6%) 691 (91.04%) 68 (8.96%) 0 (0%) 265 (34.37%) 384 (49.81%) 122 (15.82%) 440 (54.52%) 312 (38.66%) 55 (6.81%) 454 (51.82%) 347 (42.64%) 52 (5.54%) 809 (92.88%) 61 (7.00%) 1 (0.12%) 141 (20.80%) 411 (60.62%) 126 (18.58%) 319 (34.49%) 444 (48.00%) 162 (17.51%) 377 (60.13%) 218 (34.76%) 32 (5.13%) 688 (88.20%) 90 (11.54%) 2 (0.26%) 433 (56.09%) 288 (37.30%) 51 (6.61%) 259 (33.16%) 368 (47.12%) 154 (19.72%) 732 (93.49%) 49 (6.26%) 2 (0.25%) 682 (87.21%) 99 (12.66%) 1 (0.13%) 523 (67.22%) 224 (28.79%) 31 (3.99%)
– 0.6784 0.8669 – 0.0140 (0.21*) NA – 0.5779 0.9742 – 0.0234 (0.351*) 0.0148 (0.222*) – 0.024 (0.36*) 0.3155 – 0.0166 (0.249*) NA – 0.5260 0.9145 – 0.5832 0.7908 – p b 0.0001 (0.0015*) p b 0.0001 (0.0015*) – 0.4562 0.1134 – 0.1147 0.5022 – 0.2375 0.8616 – 0.8484 0.7104 – 0.3043 0.2131 – 0.0814 0.2345
– 0.7951 1.0121 – 0.5730 NA – 0.9352 0.9947 – 0.7661 0.5250 – 0.6832 1.2590 – 0.5666 NA – 0.9108 0.9804 – 0.9393 1.0400 – 2.5952 5.3100 – 0.8794 3.6531 – 0.8257 1.1590 – 0.8662 0.9741 – 0.9579 0.6343 – 1.1789 4.2186 – 1.2264 1.3633
– 0.4318–1.4547 0.5445–1.1841 – 0.3675–0.8935 NA – 0.7386–1.1841 0.7215–1.3714 – 0.7510–1.2173 0.2250–0.6249 – 0.5390–0.8659 0.8030–1.9739 – 0.3559–0.9019 NA – 0.6823–1.2157 0.6831–1.4071 – 0.7510–1.1748 0.7785–1.3893 – 2.0117–3.3479 3.6352–7.7566 – 0.6273–1.2330 0.7345–18.1700 – 0.6509–1.0475 0.7532–1.7834 – 0.6826–1.0993 0.7251–1.3086 – 0.6166–1.4883 0.0574–7.0130 – 0.8612–1.6139 0.4375–40.6784 – 0.9749–1.5427 0.8179–2.2724
0.35
XPC
CC CT TT GG AG AA AA AC CC CC CT TT GG AG AA CC CT TT CC AC AA AA AC CC CC CT TT CC CT TT GG AG AA CC CT TT AA AG GG GG CG CC GG CG CC
– 0.97 0.15 – 0.36 NA – 0.009 0.004 – 0.13 0.22 – 0.43 0.04 – 0.32 NA – 0.01 0.005 – 0.02 0.009 – 0.56 1 – 0.01 0.12 – 0.12 0.03 – 0.05 0.006 – 0.004 0.006 – 0.03 0.05 – 0.09 0.03
rs2228001
rs2228000
G2061A
rs3731062
XPD
rs238406
rs13181
rs1799793
XPE
rs1050244
XPF
rs762521
XPG
rs1047768
rs1047769
rs2227869
rs17655
a b
0.19
0.38
0.13
0.18
0.89
0.24
0.72
0.94
0.59
0.74
0.26
0.23
0.18
0.26
Genotype. Statistical power test.
These results all remained significant after Bonferroni correction (see Table 1). We found a non-significant tendency towards a decreased PC risk for the XPC rs2228000 (Ala499Val) TT genotype (OR = 0.29; p = 0.222) compared to the reference genotype (CC) and the CT genotype (OR = 0.76; p = 0.351). None of the other SNPs were found to be associated with PC risk. 3.1. Age and PC risk For XPD, the rs1799793 polymorphism in patients over 65 years of age who were heterozygous carriers of the rs1799793 SNP appeared to have a slightly greater increased risk of PC compared to the control population (OR = 2.92, p b 0.0015corrected) than those under 65 years of age (OR = 2.28, p b 0.0015corrected). Interestingly, patients under 65 years of age who are homozygous carriers of this SNP had a similar risk of PC (OR = 5.89, p b 0.0015corrected) than those patients over 65 (OR = 5.44, p b 0.0015corrected) (Supplementary Tables 1, 2). Age stratification analysis revealed non-significant differences between the associations of the XPC rs2228000_TT genotype in patients under and over 65. The protective effect of rs2228000_TT genotype was stronger among patients under 65 years of age (OR =
0.31, p = 0.0685) than those over 65 years (OR = 0.48, p = 0.093) (Supplementary Tables 1, 2). The mean age at diagnosis was 67 years for carriers of the XPD rs1799793 mutation versus 68 years for non-carriers (p = 0.9).
3.2. Gleason score and PSA level We found no significant differences of the allele distribution of the examined SNPs among less-aggressive (Gleason 2–6) compared to more aggressive prostate cancers (Gleason N 6). There were also nonsignificant differences in the prevalence of the SNPs among high-PSA scores (N10) compared to lower PSA levels (b10) (Supplementary Table 3). Carriers and non-carriers of rs1799793 were similar with respect to PSA level at diagnosis (median PSA level was 12.0 in carriers vs 11.5 in non-carriers; p = 0.8). Aggressive cancers (Gleason 7–10) were seen in 48% carriers versus 49.2% non-carriers (p = 1.0).
3.3. Haplotype analysis Using the haplo.stats CRAN package (version 1.5.5) we undertook haplotype analysis for XPC. Differences in the haplotype structure
A. Mirecka et al. / Gene 546 (2014) 156–161
revealed no significant differences in disease risk between cases and controls (see Supplementary Table 4). Haplotype analysis of XPD revealed one protective haplotype and four that were associated with an increase in disease risk (see Table 2). Differences in the XPG haplotype structure revealed no significant differences in disease risk between cases and controls (see Supplementary Table 5). 3.3.1. Linkage disequilibrium The linkage disequilibrium (LD) plot was calculated on the basis of the genotype frequencies in our control population. The whole fragment between the six analyzed SNPs in XPC is in linkage disequilibrium and most of them with D′ values approaching 1.0. Only G1475A ↔ rs3731062 (D′ value ranges 0.2–0.4) and A2815C ↔ rs222800 and rs2228001 ↔ rs2228000 (D′ values range 0.6–0.8) were considered not to be in high LD. 3.3.2. Gene–gene interaction Multivariate logistic regression was applied to identify possible dual interactions between the 15 SNPs (120 interactions: 105 possible SNP pairs with several genotype combinations, each). No significant interaction could be identified (p-values ranging from 0.9976167 to 0.9999999) (see Supplementary Table 6). 4. Discussion In the current study that included 720 patients with prostate cancer and 1121 healthy men, we found overall that the XPD rs1799793 (Asp312Asn) polymorphism was significantly associated with prostate cancer risk. Logistic regression analysis of XPD genotypes in our study revealed an association with XPD rs1799793 (Asp312Asn) AG and AA genotypes with an increased PC risk. These results were further supported by haplotype analysis, which showed that the A allele (XPD rs1799793) appeared to drive the main effect on promoting prostate cancer risk. The XPD Asp312Asn polymorphism (rs1799793) at position 312 in exon 10 is characterized by a G to A substitution resulting in aspartic amino acid to asparagine amino acid exchange (Butkiewicz et al. 2001). This non-conservative amino acid exchange is found in an evolutionary highly conserved region (Shen et al. 1998). Asp312Asn amino acid substitution is not found in functional domains of XPD, but 312 Asp is located in the seven-motif helicase domain of the RecQ family of DNA helicases (Butkiewicz et al. 2001). RecQ enzymes are a subfamily of helicases that play an essential role in the maintenance of genome stability by acting at the interface between DNA replication, recombination, and repair (Bachrati and Hickson, 2008). Conservation of 312 Asp residue suggests that it is important for normal protein structure and integrity (Butkiewicz et al. 2001, Shen et al. 1998). The 312 variant (Asn) has the acidic moiety of the aspartic acid removed (Benhamou and Sarasin, 2002). The amino acid substitution could result in a protein malfunction in either repair capacity or fidelity (Butkiewicz et al. 2001, Shen et al. 1998). Asp312Asn substitution may modify protein folding and thus affect the protein function (Affatato et al. 2004).
159
Previous reports assessing the association of XPD polymorphisms with the risk of PC have been inconclusive. Three meta-analyses (Ma et al., 2013; Mi et al., 2012; Zhu et al., 2012), which included respectively, 8 studies (2641 cases and 3259 controls), 8 studies (2620 cases and 3225 controls) and 9 studies (2555 cases and 3182 controls) for the XPD Asp312Asn polymorphism, showed a significant association between prostate cancer risk and SNP, which is consistent with our results. In contrast the results reported by Zhu et al. (2012) in their metaanalysis examining 5765 cases and 6270 controls (derived from 15 studies) revealed no evidence of a modifying effect of the XPD Asp312Asn polymorphism. Similarly, Agalliu et al. (2010) examined 1457 cases and 1351 controls and demonstrated no association between XPD Asp312Asn and Lys751Gln with disease risk. Additionally Lavender et al. (2010) investigated 208 PC patients and 605 controls and failed to detect any correlation of the XPD Asp312Asn polymorphisms and PC. The results of the present study revealed a lack of association between XPD Lys751Gln and PC risk, which confirmed those reports described above (Agalliu et al., 2010; Ma et al., 2013; Zhu et al., 2012; Zhu et al., 2013). Moreover, a few studies showed nonsignificant associations between XPD Lys751Gln polymorphisms and PC risk (Mi et al., 2012; Ritchey et al., 2005; Sobti et al., 2012). Taken together, our results support previous published findings about the absence of any association of XPD Lys751Gln with prostate cancer. Logistic regression showed a tendency of the XPC rs2228000_TT genotype towards an association with a decreased PC risk. We found no association between the remaining variants of XPC and PC risk. As far as we can ascertain, only a few studies have investigated the role of XPC in PC development but most of them were performed in Asian populations and we cannot rule out the possibility of population stratification. None of these studies examined the association of the rs2228000 polymorphism with PC risk. Hirata et al. (2007) examined 165 cases of prostate cancer and 165 controls and suggested a correlation between the XPC 939Gln variant and decreased PC risk in the Japanese population. In contrast, Liu et al. (2012) examined 202 PC patients and 221 healthy controls in a Chinese population and reported that the XPC Lys939Gln polymorphism is not associated with disease risk. They also assessed the correlation between XPC-PAT polymorphisms and PC cancer development and revealed that the PAT+/+ genotype was associated with a 2.11-fold increase in PC risk. Similar findings were observed by Mandal et al. (2012) in an Indian case–control study of 192 cases and 224 controls. In that study the XPC PAT +/+ genotype increased PC risk by 2.55-fold, but they also found that the CC genotype in XPC Lys939Gln was significantly associated with disease risk. These results were corroborated by Mittal and Mandal (2012) in their study that examined 195 prostate cancer cases and 250 controls. Analysis showed that XPC Lys939Gln and XPC-PAT polymorphisms were associated with PC development. The different results obtained by Agalliu et al. (2010) in their 2 population-based studies that included 1457 cases and 1352 controls from the USA suggested no association between SNPs in XPC and PC development. Recent results of two meta-analyses of common variants of XPC and prostate cancer risk have been published. In the first study the prevalence of rs2228001 (Lys939Gln) was evaluated among 1966 prostate cancer patients and no association of this variant with disease risk was found (He et al., 2013). The subject
Table 2 Haplotype frequency of examined XPD variants between cases (n = 706) and controls (n = 928). rs238406
rs13181
rs1799793
p-Value
OR
95%CI
Control haplotype frequency [%]
Case haplotype frequency [%]
A C C A C A A C
A C A C C C A A
G G G G A A A A
Ref b0.001 0.002 0.41 b0.001 b0.001 b0.001 b0.001
1.00 0.37 0.92 2.20 1.37 12.62 24.02 3.96
Ref 0.24–0.56 0.63–1.33 1.45–3.35 1.10–1.71 2.85–55.92 3.12–184.91 2.63–5.98
43 16 12 5 20 0.2 0.1 3
34 5 9 9 25 3 3 13
160
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of the second study was the PAT polymorphism, reported by authors to be associated with cancer risk, especially the urinary system cancer. It consists of an insertion of 83 bases of A and T (Dai et al., 2013) and a 5 base deletion within intron 9. Since we genotyped single nucleotide polymorphisms/point mutations only, in this study we did not analyze XPC-PAT polymorphisms but we did assess the XPC Lys939Gln polymorphism and did not found any association with PC risk. Together, the evidence suggests that XPC acts differentially on disease risk between Asian and European prostate cancer patients, which is most likely due to population stratification. None of the SNPs in XPE, XPF, and XPG were associated with disease risk in the Polish population. XPB, XPE and XPF genes have not previously been examined with respect to its role in PC susceptibility. A small study of an Indian population examining the XPG Asp1104His (rs17655) SNP conducted on 150 PC cases and 150 controls revealed that the synonymous SNP genotype increased PC risk (Berhane et al., 2012). Our findings do not support this finding, which may be due to population stratification, or more likely since it was performed on a small population that it lacks sufficient power to detect any real difference between the two groups. Evaluation of XP gene–gene interactions revealed no significant results, however it seems that for such analysis the sample size studied herein was too small and type 2 statistical errors cannot be excluded. In summary, this study reveals that polymorphisms in some of the nucleotide excision repair genes appear to be related to the risk of prostate cancer. There was no association with Gleason score suggesting that these genes or their variants are not associated with disease progression but only the risk of acquiring disease. The failure of these SNPs to be detected in larger GWAS of PC is not surprising given the highly stringent statistical cut-offs used to define associations in these studies. Understanding the role of nucleotide excision repair in PC is an important step in identifying predisposing factors to be used in a strategy to reduce disease risk. Conflict of interest None declared. Acknowledgment The study was partially funded by Polish Ministry of Science and Higher Education (MNiSW), project number MB-158-79/13. Appendix A. Supplementary data Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.gene.2014.06.026. References Affatato, A.A., Wolfe, K.J., Lopez, M.S., Hallberg, C., Ammenheuser, M.M., Abdel-Rahman, S.Z., 2004. Effect of XPD/ERCC2 polymorphisms on chromosome aberration frequencies in smokers and on sensitivity to the mutagenic tobacco-specific nitrosamine NNK. Environ. Mol. Mutagen. 44, 65–73. Agalliu, I., Kwon, E.M., Salinas, C.A., Koopmeiners, J.S., Ostrander, E.A., Stanford, J.L., 2010. Genetic variation in DNA repair genes and prostate cancer risk: results from a population-based study. Cancer Causes Control 21, 289–300. Bachrati, C.Z., Hickson, I.D., 2008. RecQ helicases: guardian angels of the DNA replication fork. Chromosoma 117, 219–233. Benhamou, S., Sarasin, A., 2002. ERCC2/XPD gene polymorphisms and cancer risk. Mutagenesis 17, 463–469. Berhane, N., Sobti, R.C., Mahdi, S.A., 2012. DNA repair genes polymorphism (XPG and XRCC1) and association of prostate cancer in a north Indian population. Mol. Biol. Rep. 39, 2471–2479. Butkiewicz, D., Rusin, M., Enewold, L., Shields, P.G., Chorazy, M., Harris, C.C., 2001. Genetic polymorphisms in DNA repair genes and risk of lung cancer. Carcinogenesis 22, 593–597. Carter, K.W., McCaskie, P.A., Palmer, L.J., 2006. JLIN: a java based linkage disequilibrium plotter. BMC Bioinforma. 7, 60.
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