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Sequence Variants of Toll-Like Receptor 4 and Susceptibility
to Prostate Cancer
Yen-Ching Chen,1Edward Giovannucci,
2Ross Lazarus,
1Peter Kraft,
3
Shamika Ketkar,3and David J. Hunter
1,2,3
1Channing Laboratory, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School; 2Department of Nutrition and3Program in Molecular and Genetic Epidemiology, Department of Epidemiology, Harvard School of Public Health,Boston, Massachusetts
Abstract
Chronic inflammation has been hypothesized to be a riskfactor for prostate cancer. The Toll-like receptor 4 (TLR4)presents the bacterial lipopolysaccharide (LPS), which inter-acts with ligand-binding protein and CD14 (LPS receptor)and activates expression of inflammatory genes throughnuclear factor-KB and mitogen-activated protein kinasesignaling. A previous case-control study found a modestassociation of a polymorphism in the TLR4 gene [11381G/C,GG versus GC/CC: odds ratio (OR), 1.26] with risk of pro-state cancer. We assessed if sequence variants of TLR4 wereassociated with the risk of prostate cancer. In a nested case-control design within the Health Professionals Follow-upStudy, we identified 700 participants with prostate cancerdiagnosed after they had provided a blood specimen in 1993and before January 2000. Controls were 700 age-matched menwithout prostate cancer who had had a prostate-specificantigen test after providing a blood specimen. We genotyped16 common (>5%) single nucleotide polymorphisms (SNP)discovered in a resequencing study spanning TLR4 to test forassociation between sequence variation in TLR4 and prostatecancer. Homozygosity for the variant alleles of eight SNPswas associated with a statistically significantly lower riskof prostate cancer (TLR4_1893, TLR4_2032, TLR4_2437,TLR4_7764, TLR4_11912, TLR4_16649, TLR4_17050, andTLR4_17923), but the TLR4_15844 polymorphism cor-responding to 11381G/C was not associated with prostatecancer (GG versus CG/CC: OR, 1.01; 95% confidence interval,0.79-1.29). Six common haplotypes (cumulative frequency,81%) were observed; the global test for association betweenhaplotypes and prostate cancer was statistically significant(C2 = 14.8 on 6 degrees of freedom; P = 0.02). Two commonhaplotypes were statistically significantly associated withaltered risk of prostate cancer. Inherited polymorphismsof the innate immune gene TLR4 are associated with risk ofprostate cancer. (Cancer Res 2005; 65(24): 11771-8)
Introduction
Human Toll-like receptor (TLR) is a type I transmembraneprotein with an extracellular domain consisting of a leucine-richrepeat region and an intracellular domain homologous to that ofthe human interleukin (IL)-1 receptor (1). Lipopolysaccharide (LPS)
interacts with ligand-binding protein and CD14, a LPS receptor,to present LPS to TLR4, which then activates the expression ofinflammatory genes (e.g., IL-1, IL-6 , and IL-8) through eithernuclear factor-nB or mitogen-activated protein kinase signaling(2, 3). Human TLR4 is located on chromosome 9q32-q33, has fourexons, and is highly expressed in lymphocytes, spleen, and theheart (4). Exposure to bacterial products or proinflammatorycytokines increases TLR4 expression in monocytes and polymor-phonuclear leukocytes (2, 5). TLR4-deficient or TLR4-mutant miceshowed lower response to viral and bacterial infection than didwild-type mice (6–8), which was related to a subsequent reductionin the innate immune response. Previous work has reported thatgenetic variation in TLR4 is related to the risk of atherosclerosis(9, 10), septic shock, smallpox, Chlamydia trachomatis, Chlamydiapneumoniae , and Mycobacterium tuberculosis and related to thepathogen recognition of Gram-negative bacteria and respiratorysyncytial virus (11–13).An association study (14) in a Swedish population explored
the relationship between TLR4 sequence variations and risk ofprostate cancer. In that study, among eight single nucleotidepolymorphisms (SNP) studied, a sequence variant (11381G/C) inthe 3V untranslated region (UTR) of TLR4 was associated withprostate cancer risk [GG versus CG/CC: odds ratio (OR), 1.26; 95%confidence interval (95% CI), 1.01-1.57]. The same investigatorsalso found that other SNPs in other genes in the TLR family, whichformed TLR6-TLR1-TLR10 gene cluster, were associated with therisk of prostate cancer (15). Chronic inflammation has beenassociated with some cancers (e.g., cervix, breast, primary liver,and bladder cancers; ref. 16). An emerging body of evidence,including studies on sexually transmitted infections, clinicalprostatitis, and genetic and circulating markers of inflammationand response to infection, supports a possible link between chronicintraprostatic inflammation and risk of prostate cancer (17).Therefore, we hypothesized that genetic polymorphisms of TLR4are associated with the risk of prostate cancer. We did both SNPand haplotype analyses to test this hypothesis.
Materials and Methods
Study population. In this nested case-control study, incident prostatecancer cases were identified from the ongoing Health Professionals Follow-
up Study (HPFS) with follow-up from 1986 to 2000. A total of 51,529 U.S.
men ages 40 to 75 years were enrolled in 1986. Every participant completed
a mailed questionnaire on demographics, lifestyle, and medical history anda semiquantitative food frequency questionnaire at baseline. Information on
exposures and diseases was updated every other year, and diet information
was updated every 4 years. Deaths were identified through reports by familymembers, the follow-up questionnaires, or a search of the National Death
Index (18). This study was approved by the institutional review board at the
Harvard School of Public Health.
Requests for reprints: Yen-Ching Chen, Channing Laboratory, 181 LongwoodAvenue, Boston, MA 02115. Fax: 617-525-2008; E-mail: [email protected].
I2005 American Association for Cancer Research.doi:10.1158/0008-5472.CAN-05-2078
www.aacrjournals.org 11771 Cancer Res 2005; 65: (24). December 15, 2005
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Blood samples were obtained from 18,018 of the participants between
1993 and 1995 and collected in tubes containing sodium EDTA. Samples
were shipped by overnight courier and centrifuged; the aliquots, includingplasma, erythrocytes, and buffy coat, were stored in liquid nitrogen freezers.
We used a QIAamp blood extraction kit (Qiagen, Inc., Valencia, CA) for DNA
extraction. All DNA samples were whole genome amplified, and the quality-control samples had 100% genotype concordance rates. Among the men
who gave a blood specimen, 95% responded to the 2000 questionnaire and
18 died of prostate cancer before the end of follow-up and were included in
the case series.We identified 700 incident prostate cancer cases and 700 controls (97%
were Caucasians). Each case was matched with one control who was alive,
had not been diagnosed with cancer by the date of the case’s diagnosis, and
had a prostate-specific antigen (PSA) test after the date of blood draw. Thelatter criterion ensured that controls had the opportunity to have an occult
prostate cancer diagnosed. All controls had a PSA test within 2.5 years of the
date of diagnosis of their matched case. Cases and controls were matched onyear of birth (F1 year), PSA test before blood draw (yes/no), time (midnight
to before 9 a.m., 9 a.m. to before noon, noon to before 4 p.m., and 4 p.m. to
before midnight), season (winter, spring, summer, and fall), and exact year of
blood draw, because plasma analyses were being done on the same case-
control set.Laboratory assays. We selected all common SNPs (n = 20) in TLR4 with
frequencies greater than 5% from the Innate Immunity in Heart, Lung, and
Blood Disease-Programs for Genomic Applications (IIPGA). These SNPswere identified by resequencing the TLR4 gene of 23 unrelated Europeans
from Centre du Etude Polymorphisme Humain (CEPH) families. Resequenc-
ing of TLR4 included 2.5 kb 5Vof the gene, exons, and 1.5 kb 3Vof the gene.We included a less common nonsynonymous SNP (TLR4_13015) because itcauses a change in an amino acid. Laboratory personnel were blind to case-
control status. All case-control matched pairs were analyzed together using
the Sequenom system. Multiplex PCR were carried out to generate short
PCR products (>100 bp) containing one SNP. The details of PCR and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry are
available on request. Six control DNA samples were used for optimization.
Three SNPs failed the Sequenom assay design due to either high dimerpotential for the forward extended primer or other SNPs that might
interfere with primer annealing or extension. After genotyping, two other
Table 1. Characteristics of TLR4 SNPs
IIPGA name SNP name Nucleotide change Location rs no. Minor allele frequency, (controls) HWE P (controls)
TLR4_851 SNP1 A!G 5V UTR rs2770150 26.3 0.32
TLR4_1859 SNP2 G!A 5V UTR rs11536858 38.5 0.25
TLR4_1893 SNP3 A!G 5V UTR rs6478317 35.3 0.18
TLR4_2032 SNP4 T!C 5V UTR rs10116253 28.5 0.29TLR4_2437 SNP5 A!G 5V UTR rs1927914 35.1 0.15
TLR4_2856 SNP6 T!C 5V UTR rs10759932 16.2 0.10
TLR4_7764 SNP7 G!A Intron rs1927911 29.0 0.44TLR4_9263 SNP8 C!A Intron rs11536878 12.3 0.0001
TLR4_11547 SNP9 A!G Intron rs5030717 12.8 0.09
TLR4_11912 SNP10 G!T Intron rs2149356 34.1 0.02
TLR4_13015* SNP11 A!G Exon rs4986790 5.2 0.02TLR4_15844* SNP12 G!C 3V UTR rs11536889 13.8 0.53
TLR4_16649 SNP13 G!C 3V UTR rs7873784 17.9 0.02
TLR4_17050 SNP14 T!C 3V UTR rs11536891 18.0 0.06
TLR4_17723 SNP15 G!A 3V UTR rs11536897 5.4 0.03TLR4_17923 SNP16 C!A 3V UTR rs1536898 14.8 0.26
NOTE: TLR4_13015 (SNP11) corresponds to the nonsynonymous SNP, 8552A/G, in the report of Zheng et al. (14). This nonsynonymous amino acidsubstitution, D299G, is in strong linkage disequilibrium with the nonsynonymous change, T399I, which was not selected in this study. TLR4_15844
(SNP12) corresponds to the prostate cancer risk SNP, 11381 G/C, in the report of Zheng et al. (14).
Figure 1. TLR4 gene structure and SNPs.TLR4 has four transcript isoforms (A-D ).Information from SNPper-SequenceViewer at IIPGA Web site(http://snpper.chip.org/bio/show-gene/TLR4) was used to draw this figure. Boxes,exons; gray area, UTR; black area, codingsequence.
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SNPs were removed because of low genotyping success rates (<90%). Finally,a total of 16 SNPs (Fig. 1; Table 1) were genotyped in three plexes at the
Harvard Partners Center for Genetics and Genomics (Boston, MA). For each
SNP, genotyping data were missing in <5% of the study participants. Sixty-
eight quality-control samples were obtained from 18 external participantsand each of them had two to six duplicates. These quality-control samples
were genotyped together with all other samples in this study. All quality-
control samples passed the quality-control test (discordance rate = 0).
Ascertainment of prostate cancer. Investigators reviewed the medicaland pathology records for men with prostate cancer reported from the
follow-up questionnaire or death certificate to confirm adenocarcinoma of
the prostate and to document clinical presentation, stage, and Gleason sum
of the tumor. Because the reporting of a prostate cancer diagnosis by thesehealth professionals tends to be accurate, self-reported cases for which we
were unable to acquire medical records (7% of this case series) were
included. The clinical presentation was categorized into elevated serumPSA concentration only, abnormal digital rectal examination with or
without an elevated serum PSA concentration, or other/unknown. The
cases were categorized into regionally invasive or metastatic (stagezT3b, N1, or M1), organ-confined or minimal extraprostatic extension
(T1b-T3a and N0M0), higher grade (Gleason sum z7), and lower grade
(Gleason sum <7). Incidental microscopic focal tumors (stage T1a) were
excluded because they are generally indolent and susceptible to detectionbias due to differential rates of surgery for benign prostatic hyperplasia.
In addition, men with a previous cancer, except nonmelanoma skin cancer,
before the date of blood draw were excluded. Confirmed non-T1a tumors
between blood draw and January 31, 2000 were included. In the bloodsubcohort, 92% of cases were confirmed by medical record and 5% by other
corroborating information; only 3% were based on self-report (19). We
included the self-reported cases in the analyses because the concordance
between self-report and medical record confirmed cases was high (>90%)in this cohort.
Statistical analysis. The Hardy-Weinberg equilibrium (HWE) test was
done for each SNP among controls. Haplotype block structure (Fig. 2)was determined by using Haploview (http://www.broad.mit.edu/mpg/
haploview/index.php) and Locusview (http://www.broad.mit.edu/mpg/
Figure 2. TLR4 linkage disequilibrium plot. This plot was generated by Haploview and Locusview programs. Using the Gabriel et al. approach, the 15 SNPsformed one block. The rs number (top , from left to right ) corresponded to the SNP name (e.g., SNP1, SNP2, etc). The level of pair-wise DV, which indicates the degreeof linkage disequilibrium between two SNPs, was shown in the linkage disequilibrium structure in red . Six common haplotypes (frequency > 0.05) were identified.
TLR4 and Prostate Cancer
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locusview/). The partition-ligation-expectation-maximization algorithmwas applied to estimate haplotype frequencies in each block by using
the tagSNP program (20). We calculated haplotype frequencies by using
both progressive-ligation (as implemented in SAS PROC HAPLOTYPE)
and partition-ligation-expectation-maximization algorithms (21, 22). Wearbitrarily broke the 16 SNPs into partitions of three to four SNPs each
(e.g., SNP1-4, SNP5-8, etc.). In regions of high linkage disequilibrium and
limited haplotype diversity, these algorithms yield quite similar results
to each other and to other algorithms (e.g., PHASE; ref. 23). Inparticular, choice of partition does not noticeably change estimates of
haplotype frequency (22). Haplotype frequency estimates in TLR4 using
partition-ligation and progressive-ligation differed by V0.001. Conditionallogistic regression models were used to estimate ORs for disease inparticipants carrying either 1 or 2 versus 0 copies of the minor allele of
each SNP and each multilocus haplotype; haplotype trend regression
(24) was used to test global association between TLR4 haplotypes andprostate cancer. The type I error rate is controlled by the single
multiple-degree-of-freedom test of association between TLR4 haplotypes
and prostate cancer. Given a significant global test, haplotype- and
SNP-specific tests can provide some guidance as to which variant(s)contributes to the significant global test, although the nominal Ps we
present do not control the family-wise error rate for these post hoc
comparisons.
Age and family history are known risk factors for prostate cancer(25, 26); body mass index (BMI) is related to risk of prostate cancer
although not consistently (27). We evaluated how these factors modified
the association between TLR4 SNPs or haplotypes and the risk ofprostate cancer by comparing a model with terms for main effects and
interaction terms to the model with terms for main effects only using
the likelihood ratio test. Because of the role of TLR4 in the innate
immune response, aggressiveness of prostate cancer may relate togenetic variations of TLR4 . We tested the association between TLR4
haplotypes and aggressiveness of prostate cancer among patients with
prostate cancer by using two definitions for tumor aggressiveness
(aggressiveness 1: stage T3b or T4 or N1 or M1 or death due to prostatecancer; aggressiveness 2: stage T3b or T4 or N1 or M1 or death due to
prostate cancer or Gleason sum z7). Aggressiveness 1 is useful for
participants lacking information for Gleason sum and indicates howfar a cancer has progressed independent of grade. Aggressiveness 2 may
indicate the potential of the tumor to progress by considering grade
information. All analyses were conducted with SAS release 9.0 (SAS
Institute, Cary, NC). All statistical tests were two sided.
Results
Sixteen SNPs in TLR4 were genotyped. In the IIPGA data set,the minor allele frequency of SNP11, a nonsynonymous SNP, wasslightly less than 5% in the resequencing data of 23 unrelatedEuropeans from CEPH families but was slightly greater than5% in our study population. SNP8 was out of HWE amongcontrols (P = 0.0001) and was therefore dropped from all theanalyses (Table 1). SNP10, SNP11, SNP13, and SNP15 were out ofHWE (P = 0.02-0.03), but we retained them in the analyses as thesePs were marginal and may be chance findings and the internalblinded quality-control specimens did not show evidence of geno-typing error.Only self-reported Caucasians (97% of participants) were
included in our analyses, minimizing the likelihood of false-positivefindings due to population stratification (28, 29). However,inclusion of non-Caucasians does not change the HWE resultsamong controls.The study population included 700 incident prostate cancer
cases and 700 matched controls. Age and BMI distributions weresimilar for cases and controls (Table 2). Family history ofprostate cancer was significantly different between cases and
controls (P = 0.009). The mean age started smoking, lifetimeaverage number of cigarettes per day, and alcohol consumptionwere similar for cases and controls. Among cases, 80% were intumor stage T1b to T3a, 73% had Gleason grade 5 to 7, 8% hadaggressive prostate cancer (based on aggressiveness 1 definition),and 37% had aggressive prostate cancer (based on aggressiveness2 definition). Eighteen cases died of prostate cancer beforeJanuary 31, 2000.Men carrying one copy of the minor allele of SNP1 had an
increased risk of prostate cancer (OR, 1.38; 95% CI, 1.10-1.73;Table 3). Men carrying one copy of the minor allele of SNP6 andSNP9, on the contrary, had lower risk of prostate cancer (OR, 0.73;95% CI, 0.57-0.93; OR, 0.66; 95% CI, 0.51-0.86). Men carrying twocopies of the minor alleles of eight SNPs were at statisticallysignificantly lower risk of prostate cancer (SNP3: OR, 0.66; 95% CI,0.46-0.94; SNP4: OR, 0.59; 95% CI, 0.39-0.90; SNP5: OR, 0.64; 95% CI,0.45-0.93; SNP7: OR, 0.63; 95% CI, 0.41-0.95; SNP10: OR, 0.64; 95%CI, 0.45-0.91; SNP13: OR, 0.51; 95% CI, 0.28-0.96; SNP14: OR, 0.50;95% CI, 0.27-0.95; SNP16: OR, 0.38; 95% CI, 0.16-0.92).
Table 2. Characteristics of study participants in the HPFS
Variable Cases(n = 700), n (%)
Controls(n = 700), n (%)
AgeV65 313 (45) 318 (45)
>65 387 (55) 382 (55)
BMIV25 434 (62) 417 (60)
25-30 231 (33) 234 (33)
>30 35 (5) 49 (7)
Family history of prostate cancerNo 559 (80) 596 (85)
Yes 141 (20) 104 (15)
Age started smoking 23.1 F 5.2 22.9 F 5.3
Lifetime averagecigarettes per day
10.1 F 6.3 10.9 F 6.7
Alcohol (g/d) 11.3 F 14.8 10.4 F 14.7
PSA (ng/mL) 11.4 F 20.9 (n = 498) NA
StageT1b-T3a 562 (80) NA
T3b or T4 or N1 or M1
or death due toprostate cancer
56 (8)
Missing 82 (11)
Gleason sum
2-4 47 (7) NA5-7 512 (73)
8-10 59 (8)
Missing 82 (12)
Aggressiveness 1No 557 (80) NA
Yes 56 (8)
Missing 87 (12)Aggressiveness 2
No 442 (63) NA
Yes 258 (37)
Missing 0Death due to
prostate cancer
No 682 (97) NA
Yes 18 (2)
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Fifteen SNPs spanning TLR4 form one ‘‘block’’ using a modified
version of the Gabriel et al. (30) algorithm, where blocks identified
with the default settings in Haploview are merged if they havemultiallelic DV greater than 0.8 and the cumulative frequency of
common (>5% frequency) haplotypes in the merged block is >80%
(31). Six common haplotypes ( frequency >5%) were found with anaccumulated frequency of 81% in controls (Table 4). The P for the
global test of the six common haplotypes was 0.02. Men carrying
one copy of the minor Hap1 had a 1.40-fold increased risk of
prostate cancer (95% CI, 1.12-1.75). Hap5, on the other hand, wasassociated with a lower risk of prostate cancer (OR, 0.59; 95% CI,
0.41-0.86).The associations between TLR4 genotypes and the risk of
prostate cancer varied by age (Table 5). SNP4, SNP7, SNP13, andSNP16 variant carriers ages <65 years had a statisticallysignificantly lower risk of prostate cancer than did noncarriers(CC and CT versus TT: OR, 0.64; 95% CI, 0.47-0.86; AA and AG
versus GG: OR, 0.63; 95% CI, 0.46-0.85; CC and CG versus GG: OR,0.66; 95% CI, 0.47-0.94; CC and CA versus AA: OR, 0.59; 95% CI,0.41-0.86, respectively). BMI and family history were not effectmodifiers for the association between TLR4 SNPs and prostatecancer. In addition, the association between TLR4 haplotypes andprostate cancer was not modified by age, BMI, or family history.Case-only analysis (aggressive versus nonaggressive) was done
among prostate cancer patients. None of the SNPs or haplotypes(Table 6) showed a statistically significant association with tumoraggressiveness.
Discussion
TLR4 is located on the surface of the macrophage and playsan important role in signaling the innate immune response inresponse to bacterial or viral infection. TLR4 is the pathogenrecognition receptor for most Gram-negative bacteria (LPS), manyGram-positive bacteria, mycobacteria (2), spirochetes, viruses, and
Table 3. TLR4 SNP analysis by genotype
SNP 0 copies 1 copy 2 copies P*
Case/control OR Case/control OR (95% CI) Case/control OR (95% CI)
SNP1 319/374 1.00 299/254 1.38 (1.10-1.73) 55/52 1.25 (0.83-1.88) 0.02
SNP2 273/270 1.00 323/315 1.02 (0.81-1.28) 100/110 0.90 (0.65-1.23) 0.73
SNP3 308/295 1.00 317/297 1.02 (0.82-1.28) 64/93 0.66 (0.46-0.94) 0.04
SNP4 393/360 1.00 262/272 0.88 (0.71-1.10) 40/62 0.59 (0.39-0.90) 0.04SNP5 297/290 1.00 301/288 1.02 (0.81-1.28) 60/91 0.64 (0.45-0.93) 0.04
SNP6 511/472 1.00 155/197 0.73 (0.57-0.93) 11/12 0.84 (0.37-1.92) 0.04
SNP7 386/352 1.00 263/275 0.87 (0.70-1.08) 43/62 0.63 (0.41-0.95) 0.06SNP9 547/511 1.00 115/162 0.66 (0.51-0.86) 6/6 0.92 (0.30-2.89) 0.01
SNP10 320/305 1.00 286/275 0.99 (0.79-1.24) 61/91 0.64 (0.45-0.91) 0.04
SNP11 588/605 1.00 66/59 1.15 (0.80-1.66) 3/5 0.61 (0.15-2.58) 0.60
SNP12 515/513 1.00 167/159 1.04 (0.81-1.34) 10/15 0.66 (0.29-1.48) 0.54SNP13 475/459 1.00 178/180 0.96 (0.75-1.22) 16/30 0.51 (0.28-0.96) 0.10
SNP14 480/466 1.00 174/186 0.91 (0.71-1.16) 15/29 0.50 (0.27-0.95) 0.08
SNP15 596/606 1.00 57/62 0.93 (0.64-1.36) 1/5 0.20 (0.02-1.75) 0.23
SNP16 487/478 1.00 144/158 0.90 (0.69-1.16) 7/18 0.38 (0.16-0.92) 0.06
*P tested the null hypothesis: OR1 copy = OR2 copies = 1.
Table 4. ORs between TLR4 haplotypes and the risk of prostate cancer
Haplotype Prevalence among
controls, % (95% CI)
Global test P = 0.02 P*
0 copies 1 copy 2 copies
Case/control OR Case/control OR (95% CI) Case/control OR (95% CI)
Hap1: GGATATGAGAGGTGC 25.2 (22.9-27.5) 340/393 1.00 309/257 1.40 (1.12-1.75) 51/47 1.25 (0.82-1.90) 0.01
Hap2: AAATATGAGAGGTGC 25.0 (23.1-27.7) 403/387 1.00 250/270 0.89 (0.71-1.11) 47/39 1.15 (0.74-1.80) 0.41
Hap3: AAATATGAGACGTGC 13.1 (11.3-14.8) 526/528 1.00 164/155 1.07 (0.83-1.37) 9/14 0.64 (0.28-1.50) 0.50Hap4: AGGCGCAGTAGGTGC 7.3 (6.0-8.7) 618/597 1.00 79/98 0.78 (0.56-1.07) 3/2 1.46 (0.24-8.77) 0.27
Hap5: AGGCGCAGTAGCCGA 5.6 (4.5-6.9) 651/619 1.00 49/79 0.59 (0.41-0.86) 0/0 — 0.01
Hap6: AGGCGTAATAGCCAA 5.2 (4.0-6.3) 638/630 1.00 61/62 0.95 (0.65-1.39) 1/5 0.22 (0.03-1.73) 0.26
*P tested the null hypothesis: OR1 copy = OR2 copies = 1.
TLR4 and Prostate Cancer
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other ligands (4). Chronic intraprostatic inflammation mayincrease risk of prostate cancer. Variation in TLR4 may reduce oreven block the signaling of the immune response and thereforelower the risk of prostate cancer.Animal studies showed that TLR4-deficient mice exposed to
respiratory syncytial virus had higher levels of infectious virus intheir lungs and either were unable to clear the virus or cleared itseveral days later than wild-type mice (6). For C3H/HeJ mice, thecodominant lpsd allele corresponded to a missense mutation in the
third exon of the TLR4 gene, resulting in substitution of proline withhistidine at codon 712. For C57B/10ScCr mice, a null mutation ofTLR4 was observed among mice homozygous for the second lpsmutation. These mutations rendered the C3H/HeJ and C57B/10ScCrmice refractory to the toxic effects of lps from Gram-negativebacteria (7, 8). Experimental studies revealed that mutations in TLR4were related to hyporesponsiveness to viral and bacterial infectionand therefore to a reduction in the innate immune response andinflammation.
Table 5. Effect modification by age
SNP Noncarriers Carriers P*
Case/control OR Case/control OR (95% CI)
SNP1Age V65 132/171 1.00 169/139 1.47 (1.09-2.00) 0.22
Age >65 187/203 1.00 185/167 1.20 (0.91-1.58)
SNP2
Age V65 127/121 1.00 184/194 0.92 (0.68-1.24) 0.48Age >65 146/149 1.00 239/231 1.04 (0.79-1.37)
SNP3
Age V65 146/132 1.00 163/180 0.84 (0.63-1.14) 0.27
Age >65 162/163 1.00 218/210 1.04 (0.79-1.37)SNP4
Age V65 193/157 1.00 118/157 0.64 (0.47-0.86) 0.01
Age >65 200/203 1.00 184/177 1.02 (0.78-1.35)SNP5
Age V65 146/132 1.00 151/173 0.79 (0.59-1.07) 0.18
Age >65 151/158 1.00 210/206 1.00 (0.76-1.31)
SNP6Age V65 227/210 1.00 73/100 0.67 (0.47-0.94) 0.53
Age >65 284/262 1.00 93/109 0.79 (0.57-1.09)
SNP7
Age V65 190/152 1.00 120/161 0.63 (0.46-0.85) 0.01Age >65 198/200 1.00 186/176 1.05 (0.80-1.39)
SNP9
Age V65 250/230 1.00 51/79 0.59 (0.40-0.87) 0.41
Age >65 299/281 1.00 70/89 0.72 (0.51-1.03)SNP10
Age V65 153/138 1.00 144/170 0.76 (0.56-1.02) 0.17
Age >65 167/167 1.00 203/196 1.03 (0.78-1.35)SNP11
Age V65 258/281 1.00 37/24 1.61 (0.94-2.74) 0.04
Age >65 330/324 1.00 32/40 0.78 (0.48-1.27)
SNP12Age V65 236/233 1.00 73/80 0.91 (0.63-1.29) 0.40
Age V65 279/280 1.00 104/94 1.12 (0.81-1.54)
SNP13
Age V65 222/205 1.00 73/101 0.66 (0.47-0.94) 0.03Age >65 253/254 1.00 121/109 1.13 (0.83-1.53)
SNP14
Age V65 227/208 1.00 73/101 0.66 (0.46-0.93) 0.06Age >65 253/258 1.00 116/114 1.00 (0.73-1.35)
SNP15
Age V65 278/273 1.00 21/34 0.60 (0.34-1.06) 0.09
Age >65 318/333 1.00 37/33 1.12 (0.69-1.82)SNP16
Age V65 232/211 1.00 56/86 0.59 (0.41-0.86) 0.02
Age >65 255/267 1.00 95/90 1.05 (0.76-1.45)
*P is testing the significance of the interaction.
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A previous study (14) in a Swedish population explored theassociation between genetic variation of TLR4 and the risk ofprostate cancer. The authors found that one SNP (11381G/C,equivalent to our SNP12) was associated with the risk of prostatecancer (CC and CG versus GG: OR, 1.26; 95% CI, 1.01-1.57); thisSNP was not associated with risk in our study. In addition, theauthors did not observe any association between TLR4 haplotypesbased on eight SNPs and prostate cancer. The disparity betweenthe Zheng et al. study and our study might be due to differences inthe study populations, differences in case detection by PSA, orextent of genotyping. We genotyped more SNPs in TLR4 , whichprovided a more comprehensive assessment of TLR4 geneticvariation than the previous study, which was based on genotypingeight common SNPs.Age modified the association between TLR4 SNPs and prostate
cancer, but we observed no effect modification by BMI and familyhistory. Among men ages <65 years, carriers of SNP4, SNP7, SNP13,or SNP16 had a statistically significantly lower risk of prostate can-cer. This indicated that TLR4 genetic polymorphisms had a greaterinfluence among younger than older men and is consistent with agreater influence of inherited genetic risk among younger men.TLR4 haplotypes and risk of aggressive prostate cancer among
cases (Table 6) did not differ using either of the two aggressivenessdefinitions used in this study or the definition of aggressivenessused by Zheng et al. (14).Men carrying one copy of variant Hap1 had a 1.40-fold increased
risk of prostate cancer. In Hap1, SNP1 is the only SNP carrying thevariant allele. Men carrying one copy of the minor allele of SNP1had a 1.38-fold increased risk of prostate cancer, although the ORfor homozygous variant was not significantly elevated. Hap5 wasassociated with a lower risk of prostate cancer, which aftercomparison with hap4 and hap6 was found to be mainlyattributable to variants of SNP13, SNP14, and SNP16. These SNPslocated in the 3VUTR may be associated with lower risk of prostatecancer because they may influence mRNA stability and therebyreduce the innate immune response, inflammation, and subse-
quent carcinogenesis. SNP1, located in the 5V UTR, where thepromoter or transcription factor binding sites are located, maypotentially exert regulator effects and therefore increase cancerrisk. Functional assays are needed to elucidate the molecularmechanisms underlying these associations.Four of the SNPs genotyped were significantly out of HWE in the
controls but not in the cases. Because of the large number of locitested, a conservative significance threshold (a = 0.001) is conven-tionally used when testing HWE to detect genotyping errors (32).None of these four loci are significant at the Bonferroni-correctedsignificance level of 0.003 (0.05/15). Even with the less conservativeBenjamini-Hochberg step-up procedure to control the falsediscovery rate (<5%), the null hypothesis of HWE is rejected onlyfor SNP8. Considering none of the SNPs that showed marginalevidence for deviation from HWE in controls (P < 0.05) showed anyevidence of deviation in cases (P > 0.10), we do not believe that themarginal HWE tests in controls suggest systematic genotypingerrors for these SNPs.Furthermore, haplotype trend regression conditions on observed
genotypes and hence is relatively robust to moderate departuresfrom HWE in haplotype frequencies. We have shown (33)4 that thehaplotype trend regression is closely related to the prospectivelikelihood (34, 35); the latter approach has been shown to yieldaccurate tests and parameter estimates when HWE does not hold(specifically when there is an excess of homozygotes, as is the casefor these five SNPs; ref. 36). We also did haplotype analysesexcluding the four SNPs showing marginal evidence of departuresfrom HWE. Haplotype frequency and OR estimates for the 11-SNPhaplotypes corresponding to the previous 15-SNP haplotypes(e.g., GGATATGA**G*T*G and GGATATGAGAGGTGC) were quitesimilar (differing by at most 0.005 and 0.03, respectively). The twohaplotypes corresponding to the significant haplotypes in theprevious analysis were also significant at the 0.05 level.
4 P. Kraft, unpublished simulation studies.
Table 6. TLR4 haplotypes and risk of aggressive prostate cancer among cases
Haplotype Noncarriers Carriers P*
Aggressive/nonaggressive OR Aggressive/nonaggressive OR (95% CI)
Aggressiveness 1 (Global test P = 0.86)
Hap1: GGATATGAGAGGTGC 28/274 1.00 28/283 1.17 (0.81-1.69) 0.41
Hap2: AAATATGAGAGGTGC 35/334 1.00 21/243 0.96 (0.66-1.39) 0.83
Hap3: AAATATGAGACGTGC 38/426 1.00 18/131 0.98 (0.64-1.50) 0.91Hap4: AGGCGCAGTAGGTGC 48/495 1.00 8/62 1.03 (0.58-1.84) 0.92
Hap5: AGGCGCAGTAGCCGA 53/520 1.00 3/37 1.58 (0.79-3.18) 0.20
Hap6: AGGCGTAATAGCCAA 54/501 1.00 2/56 0.83 (0.43-1.62) 0.58Aggressiveness 2 (Global test P = 0.70)
Hap1: GGATATGAGAGGTGC 128/213 1.00 130/229 1.06 (0.78-1.44) 0.73
Hap2: AAATATGAGAGGTGC 145/258 1.00 113/184 0.92 (0.68-1.26) 0.61
Hap3: AAATATGAGACGTGC 185/341 1.00 73/101 0.75 (0.52-1.06) 0.11Hap4: AGGCGCAGTAGGTGC 226/392 1.00 32/50 0.91 (0.56-1.47) 0.69
Hap5: AGGCGCAGTAGCCGA 239/412 1.00 19/30 0.91 (0.50-1.65) 0.75
Hap6: AGGCGTAATAGCCAA 236/402 1.00 22/40 1.05 (0.60-1.84) 0.85
*P tested the null hypothesis: ORcarriers = 1.
TLR4 and Prostate Cancer
www.aacrjournals.org 11777 Cancer Res 2005; 65: (24). December 15, 2005
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In recent years, chronic inflammation due to the innate immune
response to infection has been suspected to be a risk factor for
cancer at many sites (37, 38). However, research on inflammationand prostate cancer is limited. Our findings suggest that
inflammation may be associated with risk of prostate cancer, and
future investigation of genetic variation in innate immune genesmay cast light on the etiology of this enigmatic disease.
AcknowledgmentsReceived 6/15/2005; revised 8/31/2005; accepted 9/28/2005.
Grant support: NIH grants UO1 CA98233 and CA55075.The costs of publication of this article were defrayed in part by the payment of page
charges. This article must therefore be hereby marked advertisement in accordancewith 18 U.S.C. Section 1734 solely to indicate this fact.
We thank Pati Soule and Ana-Tereza Andrade for DNA sample extraction and thePartners High-Throughput Genotyping Center (Dr. David Kwiatkowski, Alison Brown,and Maura Regan) for genotyping.
References1. Medzhitov R, Preston-Hurlburt P, Janeway CA, Jr. Ahuman homologue of the Drosophila Toll protein signalsactivation of adaptive immunity. Nature 1997;388:394–7.
2. Aderem A, Ulevitch RJ. Toll-like receptors in theinduction of the innate immune response. Nature 2000;406:782–7.
3. Chaudhary PM, Ferguson C, Nguyen V, et al. Cloningand characterization of two Toll/interleukin-1 receptor-like genes TIL3 and TIL4: evidence for a multi-genereceptor family in humans. Blood 1998;91:4020–7.
4. Opal SM, Esmon CT. Bench-to-bedside review: func-tional relationships between coagulation and the innateimmune response and their respective roles in thepathogenesis of sepsis. Crit Care 2003;7:23–38.
5. Muzio M, Bosisio D, Polentarutti N, et al. Differentialexpression and regulation of toll-like receptors (TLR) inhuman leukocytes: selective expression of TLR3 indendritic cells. J Immunol 2000;164:5998–6004.
6. Kurt-Jones EA, Popova L, Kwinn L, et al. Patternrecognition receptors TLR4 and CD14 mediate re-sponse to respiratory syncytial virus. Nat Immunol2000;1:398–401.
7. Poltorak A, He X, Smirnova I, et al. Defective LPSsignaling in C3H/HeJ and C57BL/10ScCr mice: muta-tions in Tlr4 gene. Science 1998;282:2085–8.
8. Qureshi ST, Lariviere L, Leveque G, et al. Endotoxin-tolerant mice have mutations in Toll-like receptor 4(Tlr4). J Exp Med 1999;189:615–25.
9. Vink A, de Kleijn DP, Pasterkamp G. Functional rolefor toll-like receptors in atherosclerosis and arterialremodeling. Curr Opin Lipidol 2004;15:515–21.
10. Michelsen KS, Doherty TM, Shah PK, Arditi M. TLRsignaling: an emerging bridge from innate immunity toatherogenesis. J Immunol 2004;173:5901–7.
11. Abreu MT, Arditi M. Innate immunity and toll-likereceptors: clinical implications of basic science research.J Pediatr 2004;144:421–9.
12. Mogensen TH, Paludan SR. Reading the viralsignature by Toll-like receptors and other patternrecognition receptors. J Mol Med 2005;83:180–92.
13. Imahara SD, O’Keefe GE. Genetic determinants of theinflammatory response. Curr Opin Crit Care 2004;10:318–24.
14. Zheng SL, Augustsson-Balter K, Chang B, et al.
Sequence variants of Toll-like receptor 4 are associ-ated with prostate cancer risk: results from theCancer Prostate in Sweden Study. Cancer Res 2004;64:2918–22.
15. Sun J, Wiklund F, Zheng SL, et al. Sequence variantsin Toll-like receptor gene cluster (TLR6-TLR1-TLR10)and prostate cancer risk. J Natl Cancer Inst 2005;97:525–32.
16. Kinlen L. Infections and immune factors in cancer:the role of epidemiology. Oncogene 2004;23:6341–8.
17. Platz EA, De Marzo AM. Epidemiology of inflamma-tion and prostate cancer. J Urol 2004;171:S36–40.
18. Stampfer MJ, Willett WC, Speizer FE, et al. Testof the National Death Index. Am J Epidemiol 1984;119:837–9.
19. Platz EA, Leitzmann MF, Rifai N, et al. Sex steroidhormones and the androgen receptor gene CAG repeatand subsequent risk of prostate cancer in the prostate-specific antigen era. Cancer Epidemiol Biomarkers Prev2005;14:1262–9.
20. Stram DO, Leigh Pearce C, Bretsky P, et al. Modelingand E-M estimation of haplotype-specific relative risksfrom genotype data for a case-control study of unrelatedindividuals. Hum Hered 2003;55:179–90.
21. Clayton D. SNPHAP: a program for estimatingfrequencies of large haplotypes of SNPs; Genet Epide-miol 2002.
22. Qin Z, Niu T, Liu J. Partition-ligation-expectation-maximization algorithm for haplotype inference withsingle-nucleotide polymorphisms. Am J Hum Genet2002;70:157.
23. Niu T. Algorithms for inferring haplotypes. GenetEpidemiol 2004;27:334–47.
24. Zaykin DV, Westfall PH, Young SS, Karnoub MA,Wagner MJ, Ehm MG. Testing association of statisticallyinferred haplotypes with discrete and continuous traitsin samples of unrelated individuals. Hum Hered2002;53:79–91.
25. Kalish LA, McDougal WS, McKinlay JB. Familyhistory and the risk of prostate cancer. Urology2000;56:803–6.
26. Cerhan JR, Parker AS, Putnam SD, et al. Familyhistory and prostate cancer risk in a population-basedcohort of Iowa men. Cancer Epidemiol Biomarkers Prev1999;8:53–60.
27. Giovannucci E, Rimm EB, Liu Y, et al. Body massindex and risk of prostate cancer in U.S. healthprofessionals. J Natl Cancer Inst 2003;95:1240–4.
28. Wacholder S, Rothman N, Caporaso N. Populationstratification in epidemiologic studies of commongenetic variants and cancer: quantification of bias.J Natl Cancer Inst 2000;92:1151–8.
29. Wacholder S, Rothman N, Caporaso N. Counterpoint:bias from population stratification is not a major threatto the validity of conclusions from epidemiologicalstudies of common polymorphisms and cancer. CancerEpidemiol Biomarkers Prev 2002;11:513–20.
30. Gabriel SB, Schaffner SF, Nguyen H, et al. Thestructure of haplotype blocks in the human genome.Science 2002;296:2225–9.
31. Florez JC, Burtt N, de Bakker PI, et al. Haplotypestructure and genotype-phenotype correlations of thesulfonylurea receptor and the islet ATP-sensitivepotassium channel gene region. Diabetes 2004;53:1360–8.
32. Weir BS, Hill WG, Cardon LR. Allelic associationpatterns for a dense SNP map. Genet Epidemiol 2004;27:442–50.
33. Kraft P, Cox DG, Paynter RA, Hunter D, De Vivo I.Accounting for haplotype uncertainty in matchedassociation studies: a comparison of simple and flexibletechniques. Genet Epidemiol 2005;28:261–72.
34. Lake S, Lyon H, Tantisira K, et al. Estimation andtests of haplotype-environment interaction when link-age phase is ambiguous. Hum Hered 2003;55:56–65.
35. Zhao L, Li S, Khalid N. A method for the assessmentof disease associations with single-nucleotide polymor-phism haplotypes and environmental variables in case-control studies. Am J Hum Genet 2003;72:1231–50.
36. Satten GA, Epstein MP. Comparison of prospectiveand retrospective methods for haplotype inferencein case-control studies. Genet Epidemiol 2004;27:192–201.
37. Konig JE, Senge T, Allhoff EP, Konig W. Analysis ofthe inflammatory network in benign prostate hyperpla-sia and prostate cancer. Prostate 2004;58:121–9.
38. Kinoshita I, Dosaka-Akita H, Shindoh M, et al.Human papillomavirus type 18 DNA and E6-E7 mRNAare detected in squamous cell carcinoma and adeno-carcinoma of the lung. Br J Cancer 1995;71:344–9.
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2005;65:11771-11778. Cancer Res Yen-Ching Chen, Edward Giovannucci, Ross Lazarus, et al. to Prostate CancerSequence Variants of Toll-Like Receptor 4 and Susceptibility
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