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Mutation Research 661 (2009) 85–92

Contents lists available at ScienceDirect

Mutation Research/Fundamental and MolecularMechanisms of Mutagenesis

journa l homepage: www.e lsev ier .com/ locate /molmutCommuni ty address : www.e lsev ier .com/ locate /mutres

enetic variants in the death receptor 4 gene contributeo susceptibility to bladder cancer

eilin Wanga,b,1, Miaomiao Wanga,1, Gong Chengc,1, Zhizhong Zhangb,uangbo Fud, Zhengdong Zhanga,b,∗

Department of Molecular & Genetic Toxicology, Cancer Center of Nanjing Medical University, Nanjing 210029, ChinaDepartment of Epidemiology & Biostatistics, Cancer Center of Nanjing Medical University, Nanjing, ChinaDepartment of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, ChinaDepartment of Urology, The Huai-An First Affiliated Hospital of Nanjing Medical University, Huai-An, China

r t i c l e i n f o

rticle history:eceived 27 August 2008eceived in revised form2 November 2008ccepted 13 November 2008vailable online 25 November 2008

a b s t r a c t

Death receptor 4 (DR4) is an important mediator of apoptosis, and its dysfunction may be related tocarcinogenesis and cancer development. We hypothesized that common variants in the DR4 gene areassociated with risk of bladder cancer and test this hypothesis in a case–control study of 368 bladdercancer patients and 368 cancer-free controls. We genotyped six tagging single nucleotide polymorphisms(tagSNPs) in these subjects and found a significantly increased risk of bladder cancer associated with theSNP1−397GT/TT genotype (adjusted OR = 1.55; 95% CI = 1.15–2.09) compared with the GG genotype. This

eywords:enetic variationpoptosisrogenital cancerolecular epidemiology

increased risk was more pronounced for superficial bladder cancer. A luciferase assay, performed in vitro,revealed that the −397T allele had a lower transcriptional activity than the −397G allele. Multifactordimensionality reduction (MDR) analysis indicated that the two-factor model including −397G > T andpack-years of smoking was best for predicting bladder cancer risk. Moreover, a significant additive (butnot multiplicative) interaction, was found between the −397G > T polymorphism and smoking on bladdercancer risk. In conclusion, genetic variants of the DR4 gene may be involved in the etiology of bladder

eed f

cancer, and our findings n

. Introduction

Bladder cancer is an important common disease with a com-licated, multifactorial etiology, including interactions betweenenetic makeup and environmental factors. Tobacco smoking andccupational or environmental exposure to chemical carcino-ens are the strongest known risk factors for bladder cancer [1].lthough, many people are exposed to these risk factors, only a

ew develop bladder cancer, suggesting that there is a variation inndividual susceptibility to bladder carcinogenesis in the generalopulation.

Allelic loss of chromosome 8p21-22 is a frequent event in var-

ous human cancers, including bladder cancer [2]. The DR4, alsonown as TNFRSF10A, is located within this chromosomal region.t is involved in the apoptosis upon TNF-related apoptosis-inducingigand (TRAIL) binding. DR4 binding of TRAIL results in trimer-

∗ Corresponding author at: Department of Molecular & Genetic Toxicology, Schoolf Public Health, Nanjing Medical University, 140 Hanzhong Road, Nanjing 210029,hina. Tel.: +86 25 86862937; fax: +86 25 86527613.

E-mail address: zdzhang@njmu.edu.cn (Z. Zhang).1 These authors contributed equally to this work.

027-5107/$ – see front matter © 2008 Elsevier B.V. All rights reserved.oi:10.1016/j.mrfmmm.2008.11.009

urther validation by larger studies.© 2008 Elsevier B.V. All rights reserved.

ization of the receptors and clustering of their intracellular deathdomains. This leads to the formation of death-inducing signalingcomplexes followed by the recruitment of the adaptor molecule,Fas-associated death receptor, and subsequent binding and acti-vation of caspase-8 and caspase-10 [3]. Suppression of cell deathsignaling due to detrimental alterations in DR4 involves deregulatedcell proliferation and predisposes to cancer [4].

Single nucleotide polymorphisms (SNPs) in the DR4 gene havebeen associated with cancer risk, including breast cancers [5,6], col-orectal cancers [7], chronic lymphocytic leukemia [8], mantle celllymphoma [8], prostate cancers [8,9], head and neck cancers [8,10],lung cancers [10] as well as bladder cancers [11]. Most of the epi-demiologic studies focused on the exons of the DR4 (i.e., His141Arg,Thr209Arg, and Glu228Ala); however, the functional effects of thesepolymorphisms are presently unknown. Furthermore, epidemio-logic results remain conflicting rather than conclusive, suggestingthat a comprehensive characterization and functional studies ofpolymorphisms in the DR4 gene should be accomplished. In the

present study, we selected six tagging SNPs (tagSNPs) from the datafor Chinese in the HapMap (http://www.hapmap.org/) to evaluatethe association between common genetic variants in DR4 and riskof bladder cancer in our ongoing hospital-based case–control studyin a Chinese population.

8 n Research 661 (2009) 85–92

2

2

dcamccwvAhft8sswlmrti>wsps

2

ei2adbt0aTrMrsT

cTrsawd

2

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2

icCst

Fig. 1. DR4 gene structure and linkage disequilibrium (LD) plot. This plot was gen-erated by the Haploview and Locusview programs. The rs number (top, from left toright) corresponds to the SNP name (i.e., SNP1, SNP2, etc.). The level of pair-wise D′ ,

6 M. Wang et al. / Mutatio

. Materials and methods

.1. Study subjects

The detailed methods of recruiting study subjects for this study have beenescribed previously [12]. Briefly, 368 cases of histologically confirmed transitionalell carcinoma of bladder and 368 cancer-free control subjects were recruited inn ongoing study starting in January 2003. Those cases who had previous cancer,etastasized cancer from other or unknown origins, and previous radiotherapy or

hemotherapy were excluded. Approximately 95% of the eligible patients contactedhose to participate. The cancer-free control subjects were recruited from those whoere seeking health care. The controls were genetically unrelated cancer-free indi-

iduals living in the same residential areas, and they are all Han Chinese subjects.lthough, the controls did not have a cystoscopy, controls were excluded if theyad symptoms suggestive of bladder cancer, such as haematuria. Controls were

requency-matched to the cases by age (±5 years) and sex. The response rate ofhose control subjects we approached for participation in the study was greater than5%. Before recruitment, informed consent was obtained from each of the eligibleubjects. For each individual, demographic information as well as data on smokingtatus and alcohol use was obtained through face-to-face interviews. Those subjectsho smoked daily for more than 1 year and had smoked >100 cigarettes in their

ifetimes were defined as ever smokers. Ever smokers who had quit smoking forore than 1 year were defined as former smokers, and the other smokers as cur-

ent smokers. Pack-years [(cigarettes per day/20) × years smoked] were calculatedo indicate the cumulative smoking dose and the smokers were further categorizednto two groups: light smokers (pack-years ≤ 20) and heavy smokers (pack-years20) according to the median pack-year value of the ever smokers. Those subjectsho consumed three or more alcohol drinks per week for at least 1 year were con-

idered ever drinkers, and the rest were defined as never drinkers. The researchrotocol was approved by the institutional review board of Nanjing Medical Univer-ity.

.2. SNP selection, tagSNPs identification, and genotyping

The DR4 gene has −33 kb in size, consisting of 10 exons and 9 introns (Fig. 1). Toxamine the gene extensively, we searched this DR4 gene by including its flank-ng regions of 1000-bp both upstream and downstream (i.e., from 23103114 to3139491) and found a total of 53 SNPs including 20 common SNPs [i.e., minorllele frequency (MAF) ≥0.05] among a Chinese population included in the HapMapatabase (HapMap Data Rel 21a/Phase II, Jan07, on NCBI B35 assembly, dbSNP125). For the genotyping, we selected a set of tagSNPs in the DR4 gene withhe following criteria: a minimal set of haplotypes that ensures an R2

hof at least

.8 to cover all possible haplotypes that had a frequency of a least 5% as evalu-ted by the tagSNPs program [13]. The reported coding region SNPs (i.e., rs20577hr33Ile in exon1, rs6557634 His141Arg in exon3, rs20575 Thr209Arg in exon4,s20576 Glu228Ala in exon5) were not chosen in this study, because of their lowAF (<0.05) in Asian populations. As a result, six tagSNPs, which could accu-

ately predict the common (>0.05) haplotypes with a minimum R2h

of 0.817, wereelected. The selected SNP IDs, locations, and allele frequencies are shown inable 2.

The selected SNPs were genotyped for all 736 subjects by the polymerasehain reaction (PCR)-restriction fragment length polymorphism (RFLP) method.he primers and restriction enzymes for the RFLP genotyping are available uponequest. The polymorphism analysis was performed independently by two per-ons in a blind fashion. About 1% of the PCR products were randomly selectednd confirmed by sequencing (data not shown), and more than 10% of the samplesere randomly selected for repeated genotyping. The results were 100% concor-ant.

.3. Construction of reporter plasmids

To examine potential effects of the SNP1−397G > T polymorphism on the DR4ranscription activity, we constructed two reporter plasmids encompassing −419o +44 bp of the DR4 promoter region from two genomic DNA samples withither −397G or −397T allele by using primers with restriction sites. The primersor the RFLP were 5′-ATACACGCGTAAGGCAGGCTGAATCACTCG-3′ (forward) and′-CGTTAAGCTTGCCAGGAACGCACCTAGATG-3′ (reverse), including the MluI andindIII restriction sites (The protective nucleotides are marked in bold and restric-

ion sites are underlined). The PCR products were inserted upstream of the luciferaseene in the pGL3-basic plasmid (Promega, Madison, WI, USA). The correct sequencef all the clones was verified by DNA sequencing.

.4. Transient transfection and luciferase assay

For transfections, HeLa, NIH-3T3, and T24 cells were seeded at 3 × 105 cells/wellsn 24-well plates, and each well was transfected with 2.25 �g of the vector DNAontaining either the −397G or −397T allele by Lipofectamine 2000 (Invitrogen,arlsbad, CA, USA) according to the manufacture’s instructions. As an internaltandard, all plasmids were cotransfected with 10 ng of pRL-SV40, which con-ained the Renilla luciferase gene. The pGL3-basic vector without an insert was

which indicates the degree of LD between two SNPs, is shown in the LD structure inred. Seven common haplotypes (frequencies >0.03) were identified. (For interpreta-tion of the references to color in this figure legend, the reader is referred to the webversion of the article.)

used as a negative control. Cells were collected 48 h after transfection, and celllysates were prepared according to the manufacture’s instructions. Luciferaseactivity was measured with a Dual-Luciferase Reporter Assay System (Promega,Madison, WI, USA) and normalized against the activity of the Renilla luciferasegene. Independent triplicate experiments were performed for each plasmid con-struct.

2.5. Statistical analysis

Chi-square test was used to compare the differences in frequency distribu-tions of selected demographic variables and the known risk factors, such as tobaccosmoking, as well as each allele and genotype of the DR4 polymorphisms betweenthe cases and controls. Hardy-Weinberg equilibrium of the controls’ genotype dis-tributions was tested by a goodness-of-fit �2 test. EM algorithm (SAS 9.1 PROCHAPLOTYPE) was used to infer haplotype frequencies based on the observed DR4genotypes. Unconditional univariate and multivariate logistic regression analyseswere performed to obtain crude and adjusted odds ratios (ORs) for risk of bladdercancer and their 95% confidence intervals (CIs). In the association study, SNPSpD,which could reflect the correction of markers (LD) on the corrected P-values, wasused to control inflation of type I error rate in multiple testing. The method isa simple correction for multiple testing of SNPs in LD with each others, on the

basis of the spectral decomposition (SpD) of matrices of pairwise LD betweenSNPs. This method provides a useful alternative to more computationally intensivepermutation tests. Besides, a user-friendly interface (SNPSpS) for performing thiscorrection is available online (http://gump.qimr.edu.au/general/daleN/SNPSpD/)[14]. The statistical power was calculated by using the PS software (http://biostat.mc.vanderbilt.edu/twiki/bin/view/Main/PowerSampleSize). Our power calculation

M. Wang et al. / Mutation Rese

Table 1Distribution of selected variables between the bladder cancer cases and controlsubjects.

Variables Cases (N = 368) Controls (N = 368) Pa

N % N %

Age (years)<60 112 30.4 123 33.4 0.14860–65 121 32.9 135 36.7>65 135 36.7 110 29.9

SexMale 302 82.1 296 80.4 0.571Female 66 17.9 72 19.6

Smoking statusNever 160 43.5 219 59.5 <0.001Ever 208 56.5 149 40.5

Former 96 26.1 42 11.4Current 112 30.4 107 29.1

Pack-years of smoking0 160 43.5 219 59.5 <0.0011–20 112 30.4 73 19.8>20 96 26.1 76 20.7

Drinking statusNever 191 51.9 231 62.8 0.003Ever 177 48.1 137 37.2

t

sepriodwtwaiatfmmt(oetistSwrSw

were pooled into a mixed group. After adjustment for age, sex,

TP

G

D(8

a Two-sided �2 test for the frequency distributions of selected variables betweenhe cases and controls.

uggested that we had an 80% power for the lowest detectable OR of 1.63 with anxposure frequency of 20% under the current sample size (the inputs of PS softwarearameters was as follows: ˛ = 0.05, P0 = 0.20, n = 368, m = 1.00). The false positiveeport probability (FPRP) test of Wacholder et al. [15] was applied to address thessue of false positive SNP associations. ORs were also calculated for subgroupsf patients with tumor of different TNM stage and World Health Organizationifferentiation grade. The pairwise linkage disequilibrium (LD) among the SNPsas examined using the normalized measure of allelic association D′ and r2, and

he characterization of these patterns were determined by Haploview 4.0 soft-are [16]. Haplotype blocks were generated by the Haploview software using the

pproach given by Gabriel et al. [17]. Potential locus–locus and gene–environmentnteractions were conducted by using the nonparametric multifactor dimension-lity reduction (MDR) software (version 1.1.0) [18] with six tagSNPs and therichotomized cumulative smoking dose, because smoking is an established riskactor for bladder cancer. The fitness of an MDR model was assessed by esti-

ating the testing accuracy, and the cross-validation consistency (CVC) was aeasure of how many times out of 10 divisions of the data that MDR found in

he same best model. Then, interaction dendrogram was employed. The attributesi.e., SNPs) that were strongly interacting appeared close together at the leavesf the tree, while those that do not interact appeared far from one another. Toxplore potential interactions between the SNPs and cigarette smoking, we testedhe null hypotheses of no departure from a multiplicative interaction model byncluding the main-effect variables and their product terms in the logistic regres-ion model [19]. When the test for multiplicative interaction was not rejected,he additive interaction was further assessed by a bootstrapping test by using the

tata software (version 8.2; StataCorp LP, College Station, TX). The Student’s t-testas performed to examine the difference in expression levels of the luciferase

eporter gene between different constructs. All tests were two-sided by using theAS software (version 9.1; SAS Institute, Inc., Cary, NC), unless indicated other-ise.

able 2rimary information of genotyped SNPs of DR4.

ene (accession no.) and locus NCBI rs no. Positiona Location Base

R4NM 003844)p21.3

rs13278062 23138916 Promoter G > Trs1000294 23136080 Intron 1 T > Crs2235126 23114403 Intron 7 T > Crs11780345 23107911 Intron 9 T > Crs11775256 23107430 Intron 9 C > Trs11779484 23107300 Intron 9 T > C

a SNP position in NCBI dbSNP (http://www.ncbi.nlm.nih.gov/SNP).b MAF from the HapMap database (http://www.hapmap.org).c HWE P value in the control group.

arch 661 (2009) 85–92 87

3. Results

3.1. Characteristics of the study subjects

The distributions of selected characteristics between bladdercancer patients and control subjects are shown in Table 1. Over-all, the frequency matching was adequate for age and sex betweenthe cases and controls (P = 0.148 for age and 0.571 for sex). How-ever, there were more ever smokers (56.5%) and ever alcohol users(48.1%) among the cases than among the controls (40.5% and 37.2%,respectively) (P < 0.001 for smoking and 0.003 for alcohol use).Specifically, light smokers (≤20 pack-years) had a 2.10-fold (95%CI = 1.47–3.01) and heavy smokers (>20 pack-years) had a 1.73-fold(95% CI = 1.20–2.49) increased risk, compared with nonsmokers.

3.2. Individual SNP association analysis

The primary information and allele frequencies observed arelisted in Table 2. All genotype distributions of control subjects wereconsistent with those expected from the Hardy-Weinberg equi-librium (all P > 0.05). However, we found that one of six tagSNPswas not common (MAF = 0.026 for rs11779484) in the control sub-jects, which were not consistent with that reported in the HapMapdatabase (MAF = 0.130). This inconsistency may be due to the lim-ited sample size of the Chinese population used in the HapMapdatabase. As shown in Table 3, only the genotype frequencies ofSNP1−397G > T (rs13278062) polymorphism were significantly dif-ferent between the cases and controls (P = 0.013 and 0.005 forgenotype and allele, respectively, P = 0.045 and 0.018 for genotypeand allele, respectively, after the SNPSpd correction). Comparedwith the wild-type genotype GG, the heterozygous GT, but not thehomozygous TT, was associated with a statistically significantlyincreased risk (adjusted OR = 1.64; 95% CI = 1.20–2.24 for GT and1.35, 0.82–2.23 for TT). Because the variant TT genotype was rarein this study population, we combined the variant TT genotypewith the GT genotype (i.e., GT/TT), assuming a dominant geneticmodel (i.e., the T allele is dominant). We found that a significantincreased risk of bladder cancer was associated with the combinedvariant genotypes GT/TT, compared with the GG genotype (adjustedOR = 1.55; 95% CI = 1.15–2.09; Table 3). However, no significant asso-ciation with bladder cancer risk was identified for the other tagSNPsexamined in this study (Table 4).

3.3. Association between haplotypes and risk of bladder cancer

The LD between each pair of SNPs in DR4 is presented inFig. 1. As shown in Table 5, haplotypes with a frequency <0.03

pack-years of smoking, and alcohol use, the TTTTCT haplotypewas associated with a significantly increased bladder cancer risk(adjusted OR = 1.93; 95% CI = 1.10–3.39), compared with the com-mon haplotype GTTTCT. However, the significance for TTTTCT

change MAF P for HWEc Genotyped (%)

HapMapb Case Control

0.256 0.350 0.288 0.077 93.90.341 0.338 0.330 0.119 93.60.150 0.269 0.301 0.446 93.80.156 0.139 0.171 0.372 93.90.089 0.068 0.071 0.144 94.30.130 0.036 0.026 0.610 94.1

88 M. Wang et al. / Mutation Research 661 (2009) 85–92

Table 3Genotype and allele frequencies of six tagSNPs in DR4 among the cases and controls and the associations with risk of bladder cancer.

SNP ID Genotype Cases Controls Pa Adjusted OR (95% CI)b

N % N % Allele Genotype

1 rs13278062 GG 150 41.0 191 52.6 0.013c 0.005c 1.00GT 176 48.1 135 37.2 1.64 (1.20–2.24)TT 40 10.9 37 10.2 1.35 (0.82–2.23)GT/TT 216 59.0 172 47.4 1.55 (1.15–2.09)

2 rs1000294 TT 168 46.2 169 46.7 0.795 0.920 1.00TC 146 40.1 147 40.6 1.02 (0.74–1.40)CC 50 13.7 46 12.7 1.06 (0.67–1.67)

3 rs2235126 TT 196 53.8 181 49.7 0.202 0.413 1.00TC 140 38.5 147 40.4 0.89 (0.65–1.21)CC 28 7.7 36 9.9 0.69 (0.40–1.19)

4 rs11780345 TT 269 73.5 252 69.4 0.113 0.117 1.00TC 92 25.1 98 27.0 0.88 (0.63–1.23)CC 5 1.4 13 3.6 0.34 (0.12–0.99)

5 rs11775256 CC 315 86.3 315 85.8 0.941 0.854 1.00CT 50 13.7 52 14.2 0.95 (0.62–1.45)TT – – –

6 rs11779484 TT 339 92.9 346 94.8 0.364 0.281 1.00TC 26 7.1 19 5.2 1.44 (0.77–2.66)CC – – –

sion mgeno

hHbtt

3p

sb13tslvwwbbt

TA

V

C

C

T

T

a Two-sided �2 test for the distributions of genotype and allele frequencies.b Adjusted for age, sex, pack-years of smoking, and alcohol use in a logistic regresc Corrected P values were calculated by SNPSpd (P = 0.045 and 0.018 for allele and

aplotype did not remain after the Bonferroni correction (P = 0.184).owever, the global haplotype test indicated that the distri-ution pattern of the haplotypes differed significantly betweenhe cases and controls (P = 0.001 after 1000 times of permuta-ion).

.4. Association between the SNP1−397G > T polymorphism androgression of bladder cancer

The association between the −397G > T polymorphism and Ttage and grade of bladder cancer was further examined. Of the 366ladder cancer patients, 304 (83.1%) had a low-grade tumor (grades–2), and the remaining 62 (16.9%) had a high-grade tumor (grade). Furthermore, 232 (63.4%) had a superficial tumor (pTa–pT1), andhe remaining 134 (36.6%) had an invasive tumor (pT2–pT4). Aftertratification for grade, a statistically significant increased risk ofow-grade bladder cancer was found for carries of the −397GT/TTariant genotypes (OR = 1.58; 95% CI = 1.16–2.15), compared with

ild-type GG genotype. Furthermore, in the stratification of stage,e found that an increased risk was only significant in superficialladder cancer (OR = 1.72; 95% CI = 1.23–2.42) but not in invasiveladder cancer (OR = 1.31; 95% CI = 0.87–1.96), which is likely dueo the reduced number of subjects in the stratum.

able 4ssociations between the SNP1 −397G > T polymorphism of DR4 and progression of bladd

ariables −397G > T genotype, n (%)

GG

ontrols (n = 363) 191 (52.6)

ases (n = 366)Total 150 (41.0)

umor gradeLow (grade 1 and grade 2) 124 (40.8)High (grade 3) 26 (42.0)

umor stageSuperficial (pTa–pT1) 90 (38.8)Invasive (pT2–pT4) 60 (44.8)

a Adjusted for age, sex, pack-years of smoking, and alcohol use in logistic regression mo

odel.type after the SNPSpd correction, respectively).

3.5. Locus–locus and gene–environment interactions

We then analyzed potential locus–locus and gene–environmentinteractions on bladder cancer risk by the use of MDR soft-ware. MDR analysis was performed with all six tagSNPs and thetrichotomized cumulative smoking dose. As shown in Fig. 2A, pack-years of smoking was the strongest single factor for predictingbladder cancer risk (testing accuracy = 0.5066, CVC = 99/100). Butthe best interaction model was the two-factor model (i.e., SNP1rs13278062 and pack-years of smoking), with an improved testingaccuracy to 61.82% and a perfect CVC of 100 that was statisticallysignificant (P = 0.001), as also determined empirically by the per-mutation testing. All models including two or more factors had adecrease in the testing accuracy or CVC. Furthermore, we performedthe interaction dendrogram and prepared a graph to determinewhether there was a synergistic relationship in the best model(Fig. 2B). The SNP1 and pack-years of smoking were placed on thesame branch, suggesting the best model might have a synergistic

interaction effect on modulating risk of bladder cancer.

For the variables generated in the best model, we evaluatedthe gene–smoking interaction by the logistic regression analysisbetween the SNP1 and pack-years of smoking (Table 6). As shownin Table 6, the −397GT/TT variant genotype was associated with

er cancer.

Adjusted OR (95% CI)a

GT/TT GT/TT vs. GG

172 (47.4) 1.00 (ref.)

216 (59.0) 1.55 (1.15–2.09)

180 (59.2) 1.58 (1.16–2.15)36 (58.0) 0.99 (0.36–2.75)

142 (61.2) 1.72 (1.23–2.42)74 (55.2) 1.31 (0.87–1.96)

del.

M. Wang et al. / Mutation Research 661 (2009) 85–92 89

Table 5Frequencies of the inferred haplotypes of DR4 among the cases and controls and the associations with risk of bladder cancer.

Haplotypesa Cases Controls Adjusted OR (95% CI)b Pb Global Pc

N % N %

GTTTCT 405 55.5 408 56.2 1.00 0.001TCCTCT 63 8.6 63 8.3 1.04 (0.71–1.53) 0.844TCCCCT 36 5.0 36 5.0 0.90 (0.55–1.47) 0.669TCCCTT 35 4.8 35 3.4 1.37 (0.79–2.35) 0.260TTTTCT 39 5.3 20 2.8 1.93 (1.10–3.39) 0.023d

TCTTCT 27 3.7 22 3.0 1.13 (0.62–2.04) 0.691GCTTCT 30 4.1 19 2.6 1.56 (0.86–2.85) 0.145Otherse 95 13.0 136 18.7 0.72 (0.54–0.98) 0.036d

a The alleles of haplotypes were arranged as the location of the SNPs in DR4 from 5′ to 3′ .b Adjusted for age, sex, pack-years of smoking, and alcohol use.c Generated by permutation test with 1000 times of stimulation.d P values were calculated by Bonferroni correction (P = 0.184 for TTTTCT haplotype and 0.288 for Others, respectively).e Haplotypes with a frequency <0.03 were pooled into one mixed group.

Table 6Interaction analyses of SNP1−397G > T polymorphism and cumulative smoking dose in MDR.

Smoking Genotypes Cases Controls P Adjusted OR (95% CI)a

N % N %

Non-smokers GG 75 20.5 116 32.0 1.00Non-smokers GT/TT 85 23.2 101 27.8 0.206 1.31 (0.86–1.98)Light smokers GG 44 12.0 42 11.6 0.068 1.65 (0.96–2.82)Light smokers GT/TT 68 18.6 30 8.3 <0.001 3.51 (2.04–6.01)Heavy smokers GG 31 8.5 33 9.1 0.321 1.35 (0.75–2.46)Heavy smokers GT/TT 63 17.2 41 11.3 0.002 2.23 (1.33–3.74)PP

i9s2u1wpOe

FIb

for interaction (additive)for interaction (multiplicative)

a Adjusted for age, sex, and alcohol use in logistic regression model.

ncreased risk of bladder cancer among non-smokers (OR = 1.31;5% CI = 0.86–1.98) compared with the GG genotype, whereas heavymokers caring this genotype had a higher risk, with an OR of.23 (95% CI = 1.33–3.74), which is 1.26-fold greater than the prod-ct of the ORs for heavy smokers with the GG genotype (i.e.,

.31 × 1.35 = 1.77). A similar result was also seen for −397GT/TT,ith an OR of 3.51 (2.04–6.01) being 1.63-fold greater than theroduct of the OR for non-smokers with the GG genotype and theR for light smokers with GG genotype (i.e., 1.31 × 1.65 = 2.16). How-ver, no evidence for a multiplicative interaction but for an additive

ig. 2. MDR models and interaction dendrogram of DR4 tagSNPs and pack-years of smonteraction dendrogram. The color indicates the strength of dependence, green is weak,ranch, but SNP2 was on another branch. (For interpretation of the references to color in

0.0380.496

interaction was observed between the genotypes and smokers (Pfor multiplication interaction/additive interaction: 0.496/0.038),which is also likely due to a limited study power of the reducedsample size in the stratum.

3.6. Effect of the DR4−397G > T polymorphism on transcriptionalactivity

The effect of the −397G > T polymorphism on the promoteractivity of DR4 was investigated by use of a luciferase assay. As

king on bladder cancer risk. (A) Information of the MDR interaction models. (B)and red is strong. SNP1, SNP3 and pack-years of smoking are located on the samethis figure legend, the reader is referred to the web version of the article.)

90 M. Wang et al. / Mutation Rese

Fig. 3. Effect of the −397G > T polymorphism on the DR4 luciferase activity. (A)Schematic representation of reporter plasmids containing the −397G or −397Tallele, which was inserted upstream of the luciferase reporter gene in pGL3 basicplasmid. (B) The two constructs were transiently transfected into the NIH-3T3, HeLa,aawc

siwHts

4

tadpnibGttbtafii

m[p[c6ryD

nd T24 cells, respectively. The luciferase activity of each construct was normalizedgainst the internal control of Renilla luciferase. The data indicate the mean valuesith the standard deviation (S.D.) from three independent experiments. *P < 0.05

ompared with the construct counterpart.

hown in Fig. 3, the vectors with the −397G allele had a 20.6–58.1%ncrease in the relative luciferase activities, compared with those

ith the −397T allele in all three types of cell lines (i.e., NIH-3T3,eLa, and T24 cell lines) (P < 0.05 for all). These results suggested

hat the −397G allele in the promoter region may increase tran-criptional activity of the DR4 gene.

. Discussion

In this bladder cancer case–control study in a Chinese popula-ion, we investigated the association of common variants of DR4nd their interaction with cigarette exposure with the risk of blad-er cancer. We found, for the first time, that the SNP1−397G > Tolymorphism (rs13278062) in the DR4 promoter region was sig-ificantly associated with bladder cancer risk. In addition, the

ncreased risk was more pronounced in superficial than in advancedladder cancer. Further functional evaluations indicated that the

to T change of this polymorphism significantly decreased theranscription activity of the DR4 gene. However, there was no statis-ical evidence for an association between the haplotypes and risk ofladder cancer due to a limited study power. The MDR analysis iden-ified a significant two-factor interaction model, including SNP1nd pack-years of smoking, and statistical evidence was observedor an additive interaction between the SNP1 and tobacco smok-ng. The lack of statistical evidence for a multiplicative interactions also likely due to our limited study power.

DR4 is an important mediator of apoptosis, and its dysfunctionay be related to cancer development and distant tumor spread

4]. Several studies have investigated the associations between DR4olymorphisms and human cancer risk, including bladder cancer11], but these focused mostly on only one or two variants in the

oding region. For example, Hazra et al. [11] found that the DR426GG genotype in exon 4 was associated with an overall deceasedisk of bladder cancer in Caucasians, which was more apparent inounger women and light smokers. Frank et al. revealed that theR4 haplotype 626C–683C was associated with an increased risk in

arch 661 (2009) 85–92

breast cancer [5] and colorectal cancer [7]. Recently, Langsenlehneret al. [9] reported that the Glu228Ala polymorphism in DR4 wasassociated with an increased risk for prostate cancer metastases,but not with tumor stage, grade, or age at diagnosis. Since the MAFof these polymorphisms in exons of DR4 was low in Asians, we couldnot perform an adequate analysis for risk of bladder cancer in thisstudy population. However, it is noted that the other genetic vari-ants in DR4 may also be important and that their roles in humancancer susceptibility should be evaluated. Our results showed thatthe SNP1−397G > T polymorphism in the DR4 promoter region wasassociated with bladder cancer risk. Our tagSNPs selection wasbased on the r2 LD statistic, because r2 is directly related to statis-tical power to detect disease associations with untyped loci [20]. Itis believed that this polymorphism may be in LD with other codingregion SNPs in DR4 or other genes nearby

In this study, the most notable finding was the associationbetween the SNP1−397G > T polymorphism and bladder can-cer risk. In the single-locus analysis, the −397TT genotype wasassociated with a significantly increased risk of bladder cancer. Fur-thermore, the −397G > T polymorphism was in the best two-factormodel for predicting bladder cancer risk in MDR analyses. This asso-ciation appears to be consistent across all analyses, suggesting that−397G > T polymorphism may be involved in the development ofbladder cancer in this study population. The luciferase assay, per-formed in vitro, revealed that the −397T allele had a significantlylower transcriptional activity than the −397G allele, suggesting thatthe −397G > T polymorphism in the promoter region may influ-ence DR4 expression and thus contribute to genetic susceptibility tobladder cancer. The mechanism by which the −397T allele leads to ahigher promoter activity is unknown. Accumulating evidence sug-gests that transcriptional regulation factors could be destroyed bypolymorphism in the promoter region, leading to altered transcrip-tion activities [21,22]. An AP-1 binding site in the DR4 promoter hasbeen identified and shown to be important for the promoter activa-tion [23]. An analysis of potential transcription factor-binding sitesusing the Alibaba2 program [24] showed that the G to T changeof the −397G > T polymorphism could destroy the creation of anadditional Sp1-binding site. Sp1 is considered to be a transcrip-tional activator in some cells, but it may negatively regulate genetranscription [25,26]. Therefore, it is possible that the predictedchange in the putative transcription factor-binding site with the−397G > T change may lead to a reduced promoter activity. In addi-tion, because DR4 is known to be expressed at levels of mRNA orprotein in the bladder tissues [2], which could be affected the pres-ence of −397G allele. Hence, additional experiments of bladdertissues with different genotypes are warranted in future studies.

Subgroup analysis according to tumor stage and grade may helpin identifying prognostic factors involved in different bladder can-cer progression pathways [27]. After stratification analysis by tumorgrade and T stage, it appeared that the −397T allele was asso-ciated with an obviously increased risk of developing superficialbladder cancer. It has been postulated that superficial and invasivebladder carcinomas may have a different etiology involving differ-ent genetic and epigenetic defects [28]. However, this finding fromour relatively small study needs validation by larger studies in thefuture.

For complex multifactorial common diseases such as cancer, achallenge is to interpret interactions between genetic and envi-ronmental factors. Accumulating evidence has indicated that theeffect of single genetic variant may be dependent on other geneticvariants and environmental factors [29]. In the present study, we

used both parametric statistical methods and nonparametric MDRapproach to detect and characterize the gene–environment inter-action between the DR4 gene and smoking. As the results show,the two-factor model including SNP1 −397G > T and pack-yearsof smoking is the best model for predicting bladder cancer risk.

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urther interaction dendrogram also showed that they had a jointffect on the risk of bladder cancer. In addition, we tested theene–environment interaction with MDR-selected variables usingarametric statistical methods, and the results revealed an additive

oint effect between the −397G > T polymorphism and smoking indentifying bladder cancer risk. These results suggested that theariants of DR4 may be a biomarker for susceptibility to smoking-nduced bladder cancer or that the genetic variants of DR4 may

odulate the cancer risk associated with smoking. These findings,fter validation by larger studies, may help identify at-risk popula-ion for primary cancer prevention.

There are some limitations in our study. First, since the blad-er cancer cases and control subjects were enrolled from hospitals,

nherent selection bias cannot be excluded. However, by matchingn age, sex, and ethnicity, potential confounding factors have beeninimized. Any inadequacy in matching would have also been con-

rolled in data analysis with further adjustment. Second, the sampleize in this study may not large enough to detect a multiplicativenteraction between smoking and the investigated DR4 genotypes.lthough we did detect an association between the −397G > T poly-orphism and bladder cancer risk, the FPRP value was notable with<20% chance of being a false positive (data not shown). Third, in

ddition to tobacco smoking and alcohol use, we did not obtainnough information on occupational exposure that may interactith the DR4 genotypes. Finally, since the findings from the present

tudy were only from a Han Chinese population, it is uncertainhether these results are relevant to other ethnic groups. However,

he −397G > T polymorphism (rs13278062) showed considerableeterogeneity in all ethnic groups: the frequency of the −397T allele

s 11.9% in sub-Saharan Africans, 49.2% in individuals of Europeanncestry, and 25.6% in Asians, according to the dbSNP database.iven this is a common polymorphism worldwide, it would beppropriate to conduct independent studies in other populationsor comparisons and additional further functional studies to underhe mechanisms by which this polymorphism alters cancer risk.

In conclusion, the present study indicates that genetic vari-nts, particularly the −397G > T polymorphism (rs13278062), inR4 modulate the risk of bladder cancer. In particular, these vari-nts, along with environment factors, could alter bladder cancerisk. To confirm our findings, further functional evaluations in vivond larger molecular epidemiological studies with diverse ethnicopulations are warranted.

onflict of interest statement

There is no conflict of interest.

cknowledgements

We would like to thank Ruiwen Zhang (University of Alabama atirmingham, USA) and Qingyi Wei (Department of Epidemiology,he University of Texas M.D. Anderson Cancer Center) for criticalomments and scientific editing. This study was partly supportedy the National Natural Science Foundation of China (30571583 and0872084), the Ph.D. Programs Foundation of Ministry of Educa-ion of China (20060312002), the Natural Science Foundation ofiangsu Province (BK2006231), the Postdoctoral Science Founda-ion of China (20060390293), the Postdoctoral Science Foundationf Jiangsu Province (0601049) and “Qinglan Project” Foundation forhe Young Academic Leader of Jiangsu Province (2006).

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