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Carcinogenesis Advance Access originally published online on November 13, 2007
Carcinogenesis 2008 29(3):568-572; doi:10.1093/carcin/bgm253
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© The Author 2007. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Polymorphic variants in PTGS2 and prostate cancer risk: results from two large nested case–control studies

Kim N. Danforth1,*, Richard B. Hayes1, Carmen Rodriguez2, Kai Yu1, Lori C. Sakoda3, Wen-Yi Huang1, Bingshu E. Chen4, Jinbo Chen5, Gerald L. Andriole6, Eugenia E. Calle2, Eric J. Jacobs2, Lisa W. Chu7, Jonine D. Figueroa1,7, Meredith Yeager8, Elizabeth A. Platz9, Dominique S. Michaud10, Stephen J. Chanock1,8,11, Michael J. Thun2 and Ann W. Hsing1

1 Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, MD 20852
2 Department of Epidemiology and Surveillance Research, American Cancer Society, Atlanta, GA 30303
3 Department of Epidemiology, School of Public Health and Community Medicine, University of Washington, Seattle, WA 98195
4 Department of Mathematics and Statistics, Concordia University, Montreal, Quebec H3G 1M8, Canada
5 Department of Biostatistics and Epidemiology, University of Pennsylvania School of Medicine, Philadelphia, PA 19104
6 Division of Urologic Surgery, Washington University School of Medicine, St Louis, MO 63110
7 Cancer Prevention Fellowship Program, Office of Preventive Oncology, Division of Cancer Prevention, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, MD 20852
8 Core Genotyping Facility, Division of Cancer Epidemiology and Genetics, Advanced Technology Program, SAIC Frederick, Inc., NCI-Frederick, Frederick, MD 20877
9 Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205
10 Department of Epidemiology, Harvard School of Public Health, Boston, MA 02115
11 Center for Cancer Research, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, MD 20892

* To whom correspondence should be addressed. Tel: +1 301 594 5631; Fax: +1 301 402 0916; Email: danfortk{at}mail.nih.gov


   Abstract
Top
 Abstract
Introduction
 Materials and methods
 Results
 Discussion
 Funding
 References
 
Chronic inflammation has been hypothesized to increase prostate cancer risk. Prostaglandin-endoperoxide synthase 2 (PTGS2) encodes the proinflammatory cyclooxygenase 2 enzyme believed to be the rate-limiting step in the synthesis of prostaglandins, important mediators of inflammation. We investigated associations between PTGS2 polymorphisms and prostate cancer risk among 2321 prostate cancer cases and 2560 controls in two large case–control studies nested within the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial and the Cancer Prevention Study II Nutrition Cohort. Five single nucleotide polymorphisms (SNPs) (rs5277, rs20432, rs4648276, rs5275 and rs689470) were examined in SNP and haplotype analyses (five SNPs in PLCO and four SNPs in the Nutrition Cohort). In PLCO, the Ex10 +837 T>C marker (rs5275) was initially associated with prostate cancer risk (P-trend = 0.02) but became non-significant after adjustment for multiple comparisons (P = 0.08); this SNP showed no association with prostate cancer risk in the Nutrition Cohort (P-trend = 0.54) or in an analysis pooling the two cohorts (P-trend = 0.20). No other SNP was associated with prostate cancer risk in PLCO or the Nutrition Cohort individually or combined. Haplotype analyses suggested an association between PTGS2 variants in PLCO alone (global P = 0.007), but not in the Nutrition Cohort (global P = 0.78) or pooled analysis (global P = 0.18). In conclusion, despite the potential importance of inflammation in prostate carcinogenesis, results from our large study of five PTGS2 SNPs does not support a strong association between PTGS2 variants and prostate cancer risk in non-Hispanic white men.

Abbreviations: CGEMS, Cancer Genetic Markers of Susceptibility; CPS-II, Cancer Prevention Study II; CI, confidence interval; NCI, National Cancer Institute; NSAID, non-steroidal anti-inflammatory drug; OR, odds ratio; PTGS2, prostaglandin-endoperoxide synthase 2; PLCO, Prostate, Lung, Colorectal and Ovarian; SNP, single nucleotide polymorphism


   Introduction
Top
 Abstract
 Introduction
Materials and methods
 Results
 Discussion
 Funding
 References
 
The prostaglandin-endoperoxide synthase 2 (PTGS2) gene encodes the proinflammatory cyclooxygenase 2 enzyme believed to be the rate-limiting step in the synthesis of prostaglandins, important mediators of inflammation (1). Chronic inflammation has been implicated in the development of several cancers, including prostate cancer (2,3), and proliferative inflammatory atrophy, an inflammatory condition in the prostate, has been hypothesized to be a precursor lesion for prostate cancer (4). Recently, a large Swedish study examined 9275 single nucleotide polymorphisms (SNPs) in 1086 inflammatory genes and reported significant ({alpha} = 0.01) associations between 106 SNPs and prostate cancer (5), suggesting that variation in inflammation genes may play a role in prostate cancer risk. Research on non-genetic factors, including non-steroidal anti-inflammatory drug (NSAID) use, obesity and prostatitis, also supports a possible etiologic role for inflammation in prostate cancer risk (6–9).

Three previous studies have examined the relationships between various PTGS2 polymorphisms and prostate cancer risk (10–12) with mixed results. To further clarify the role of PTGS2 variants in prostate cancer development, we investigated associations between five PTGS2 polymorphisms and prostate cancer risk among 2321 prostate cancer cases and 2560 controls in two large case–control studies nested within the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial and the Cancer Prevention Study II (CPS-II) Nutrition Cohort.


   Materials and methods
Top
 Abstract
 Introduction
 Materials and methods
Results
 Discussion
 Funding
 References
 
Study participants
PLCO Cancer Screening Trial.
The PLCO Cancer Screening Trial (hereafter referred to as PLCO) is an ongoing, randomized controlled trial designed to evaluate the impact of screening tests on cancer-specific mortality. Details on the trial have been published previously (13,14). From 1993–2001, 154 000 men and women, aged 55–74 years, were enrolled at 10 screening centers throughout the country (Washington, DC; Detroit, MI; Salt Lake City, UT; Denver, CO; Honolulu, HI; Minneapolis, MN; Marshfield, WI; Pittsburgh, PA; St Louis, MO; Birmingham, AL) and randomized to the trial's screening arm or usual care. During screening visits, blood samples were collected. This analysis uses non-Hispanic white men from the screening arm of the trial. Institutional review boards at the National Cancer Institute (NCI) and each of the participating institutions approved the PLCO protocol, and each participant provided written informed consent.

Prostate tumors were identified by screening exams (prostate-specific antigen test, digital rectal exam), reports from participants, physicians or relatives, linkage with the National Death Index or linkage with state cancer registries. All cases were pathologically confirmed. Cases were classified as ‘advanced’ if there was extraprostatic extension (stage III), metastasis (stage IV) or a Gleason score of ≥7 (using the highest available Gleason score and the best available information from pathology and/or clinical data for staging). Controls (n = 1399) were matched to cases (n = 1162) identified between October 1993 and September 2001 on age, time since initial screening and year of blood draw using incidence density sampling.

CPS-II Nutrition Cohort.
The CPS-II Nutrition Cohort (hereafter referred to as the Nutrition Cohort) is a prospective cohort study designed to examine associations between a wide range of exposures and cancer incidence, as described previously (15). It was established by the American Cancer Society in 1992 and 1993 among 86 000 men and 97 000 women in 21 USA states (California, Connecticut, Florida, Georgia, Illinois, Iowa, Louisiana, Maryland, Massachusetts, Michigan, Minnesota, Missouri, New Jersey, New Mexico, New York, North Carolina, Pennsylvania, Utah, Virginia, Washington, Wisconsin). Blood samples were collected from a subset of Nutrition Cohort participants between June 1998 and June 2001 (17 411 men and 21 965 women). This analysis uses non-Hispanic white men who provided a blood sample. The Emory University Institutional Review Board approved the study, and participants provided written consent.

Prostate cancers diagnosed between enrollment in the Nutrition Cohort and August 2001 were identified through self-report or National Death Index linkage and were subsequently confirmed by medical record review or registry linkage, except for two prostate cancer deaths for which information was available only from death certificates. Prostate cancer was classified as advanced if the Gleason score was ≥7, the tumor was classified as stage III or IV, or it was a fatal case of unknown stage at diagnosis. Cases (n = 1159) and controls (n = 1161) were matched on age and date of blood collection using incidence density sampling.

Genotyping
SNPs were selected based on putative function, reported minor allele frequency (≥5%) and the availability of a validated assay at the NCI's Core Genotyping Facility (http://snp500cancer.nci.nih.gov). Five SNPs were genotyped in PLCO and four in the Nutrition Cohort (all also in PLCO) using the TaqMan assay. The genotyping completion rate was ≥98% in PLCO and >92% in the Nutrition Cohort. The interassay concordance from blinded quality control samples was >99% in both studies.

Many participants (~75%) in our original PLCO analysis had one of their SNPs (rs5275) genotyped again, using an Illumina assay, when they were later included in a genome-wide scan as part of the Cancer Genetic Markers of Susceptibility (CGEMS) Study (16,17). The CGEMS study, which oversampled advanced cancers, also genotyped several hundred additional PLCO participants who were identified during further follow-up and were not included in our original sample. For men assayed by both platforms (n = 1817), genotype concordance was >99.9% after excluding missing data (<1.5% for each method).

Statistical analysis
For SNP analyses, odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using unconditional logistic regression models. In each study (PLCO and Nutrition Cohort), results from unadjusted and adjusted (for matching factors) models were similar; therefore, only unadjusted results are presented. (The matching factors considered as covariates in adjusted models were age, time since initial screening and year of blood draw in PLCO and age and date of blood collection in the Nutrition Cohort.)

Associations were calculated for each genotype (heterozygote and homozygote for the variant allele) separately and combined, compared with the referent genotype (homozygote for the most common allele). Tests for trend were based on the number of copies of the minor allele. For pooled analyses (PLCO and Nutrition Cohort), heterogeneity was assessed using a two degrees of freedom Wald test for gene-by-study interaction terms. Pooled analyses for rs5275 included PLCO participants with and without data from CGEMS and Nutrition Cohort participants.

Haplotype frequencies and ORs were estimated using the expectation–maximization algorithm in haplo.stats (R) (18) based on the four SNPs in both studies. Haplotype frequencies among controls were compared for PLCO and the Nutrition Cohort before pooling data; in the pooled analysis, heterogeneity by study was assessed using a global Wald test (19).

SNP analyses were adjusted for multiple testing using the Simes test, which is based on the test for linear trend using the number of copies of the minor allele (0, 1 and 2) (20). A global score test by Schaid et al. (21) was used to test for overall differences in the frequency of the haplotypes between cases and controls.


   Results
Top
 Abstract
 Introduction
 Materials and methods
 Results
Discussion
 Funding
 References
 
In each study, ~65% of study participants were between 60 and 70 years old (Table I). Men in both studies were highly educated, with >40% receiving at least a college degree. A little over half of participants reported use of NSAIDs. Men in the Nutrition Cohort were less likely to report a history of diabetes, but more likely to report a family history of prostate cancer, than men in PLCO.


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  		Table I. Characteristicsa of non-Hispanic white prostate cancer cases and controls in the PLCO Cancer Screening Trial and the CPS-II Nutrition Cohort

 
Among controls, all polymorphisms were in Hardy–Weinberg equilibrium (P > 0.05). In PLCO, PTGS2 variants were not associated overall with prostate cancer risk (Table II). Although the CC genotype of the Ex10 +837T>C marker (rs5275) was initially associated with a 37% increased risk compared with the TT genotype, this association was not significant after adjustment for multiple testing (P = 0.08). Results for this SNP also became borderline significant (P-trend = 0.05) when >350 men genotyped through CGEMS were included (CC versus TT genotype, OR = 1.26, 95% CI: 0.98–1.60). No other SNP was significantly associated with prostate cancer risk in PLCO, although point estimates for three other SNPs (rs5277, rs20432 and rs4648276) were similar to those observed for rs5275.


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  		Table II. ORs and 95% CIs for prostate cancer risk and PTGS2 polymorphisms among non-Hispanic white men in the PLCO Cancer Screening Trial and the CPS-II Nutrition Cohort

 
Among Nutrition Cohort participants, no SNP was associated with prostate cancer risk, with all point estimates close to one. The Ex10 +837T>C marker (rs5275) that appeared suggestive in PLCO showed no relationship to prostate cancer risk in the Nutrition Cohort (TC versus TT genotype, OR = 0.95, 95% CI: 0.80–1.13; CC versus TT genotype, OR = 0.94, 95% CI: 0.70–1.25).

There was no statistical evidence of heterogeneity between results of these two cohorts (P-heterogeneity > 0.10); thus, data from the two studies were pooled. In the pooled analyses, no SNP was associated with prostate cancer risk (including rs5275, P-trend = 0.20).

Haplotype frequency was significantly different between cases and controls in PLCO (global P = 0.007), but not in the Nutrition Cohort (global P = 0.78) (Table II). Using the four SNPs in both PLCO and the Nutrition Cohort, haplotype frequencies were similar among controls (P = 0.32). As was done for the SNP analyses, data were pooled from the two studies in a combined haplotype analysis (P-heterogeneity = 0.05). In the pooled analysis, PTGS2 haplotypes were not associated with prostate cancer risk (global P = 0.18).

In PLCO, risk patterns were generally similar among non-NSAID and NSAID users (data not shown). However, in the Nutrition Cohort, risk estimates varied by NSAID use, although no PTGS2 SNP was significantly associated with prostate cancer risk among either non-NSAID or NSAID users. For example, for the Ex10 +837T>C marker (rs5275), among non-NSAID users point estimates suggested an increased risk of prostate cancer (CC versus TT genotype, OR = 1.32, 95% CI: 0.84–2.08; n = 50 cases and 42 controls), whereas among NSAID users point estimates suggested a decreased risk of prostate cancer (CC versus TT genotype, OR = 0.75, 95% CI: 0.51–1.09; n = 62 cases and 74 controls) with the variant allele. When non-advanced/advanced tumor status was accounted for in this analysis, results remained non-significant but point estimates were slightly stronger for the advanced tumors compared with non-advanced tumors in both non-NSAID and NSAID users. In analyses stratified only by non-advanced/advanced tumor status, results were similar for advanced and non-advanced cases (data not shown).


   Discussion
Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
Funding
 References
 
In this nested case–control study of >2300 prostate cancer cases, we did not observe significant associations between PTGS2 variants and prostate cancer risk overall. Although SNP and haplotype findings were suggestive in PLCO, they did not persist after adjustment for multiple comparisons or the inclusion of additional PLCO participants available through CGEMS. SNP and haplotype results for four SNPs were null in the Nutrition Cohort and pooled data set, and they did not support an association between PTGS2 variants and prostate cancer risk.

Overall, we did not find a strong association between prostate cancer risk and the Ex10 +837T>C marker (rs5275), although SNP and haplotype results were somewhat suggestive in PLCO. The role of rs5275 has been investigated in two previous studies, one in Sweden (n = 2160) (11) and one in the USA (n = 834 whites) (12), and in both studies, this SNP was not associated with prostate cancer risk.

Other SNPs (rs689470, rs5277, rs4648276 and rs20432) in our analysis were also examined by previous studies. The Ex10 –90C>T marker (rs689470) showed no association in two USA studies (12), including ours, but the variant (T) allele of this marker was associated with a decreased risk of prostate cancer in a Swedish case–control study (11). In addition, consistent with our results, null associations were observed for the Ex3 –8G>C (rs5277) marker in a USA study (12) and the IVS7 +111T>C marker (rs4648276) in a Swedish study (11). However, in contrast to our results, the Swedish study found an association for the IVS5 –275T>G marker (rs20432) with prostate cancer risk, although point estimates did not suggest a dose–response trend across copies of the variant allele (11).

A SNP not included in our study, rs2745557, was included in two other studies (11,12). This polymorphism had the strongest association among SNPs examined in a USA case–control study of advanced prostate cancer (12), but no dose–response trend was observed across copies of the variant allele, and no association was found in the Swedish case–control study for this SNP with prostate cancer risk (11). One other epidemiologic study reported associations for variants in the PTGS2 promoter and prostate cancer risk, but risk could not be reliably evaluated among whites due to their small sample size (n = 92 cases and 92 controls) and low minor allele frequencies (most ≤1%) (10).

No consistent association emerged for various PTGS2 SNPs across multiple study populations. Thus, despite some suggestive findings in each of three studies [our study, the USA case–control study (12) and the Swedish case–control study (11)], associations between PTGS2 variants and prostate cancer risk do not appear robust. It is unclear why associations vary across studies. Within our own study, differences were observed across study populations (PLCO and Nutrition Cohort) despite relatively large sample sizes, similar allele frequencies and similar demographic characteristics (e.g. both highly educated, white, older men from multiple states in the USA). It is possible that the varying associations resulted from chance alone, as supported by the attenuation of results within PLCO when additional PLCO participants were added to our original analysis (who had genotyping data available through CGEMS for rs5275, the SNP whose association was initially significant). However, it is also possible that the varied findings reflect differences in unidentified characteristics (genes or lifestyle factors) that interact with PTGS2 in affecting prostate cancer risk.

There was some suggestion that associations between the PTGS2 SNPs and prostate cancer risk were different among non-NSAID and NSAID users in the Nutrition Cohort, although no SNP was significantly associated with prostate cancer risk. Similarly, another USA case–control study of advanced prostate cancer (12) suggested possible differences in associations between PTGS2 variants and prostate cancer risk by NSAID use. Although the interaction between rs2745557 and NSAID use was not statistically significant, point estimates for NSAID use were stronger (more inverse) among men with the homozygote genotype for the most common allele than among men with the variant allele (OR=0.62 and 0.86, respectively) (12). Thus, interactions between PTGS2 variants and NSAID use might be further examined in studies large enough to detect these gene–environment interactions.

A notable strength of our study is its relatively large size with >2300 cases, providing sufficient power to detect modest main effects. Genotyping error in the study is low, as evidenced by the high genotyping success rates and high interassay concordance. However, one major weakness of our study is that, with five candidate SNPs, we had limited gene coverage of PTGS2. Our analysis included two (rs 5277 and rs5275) of the four (rs5277, rs5275, rs2066826 and rs2206593) PTGS2 SNPs needed to capture common genetic variation (minor allele frequency > 0.05) according to HapMap data, based on Caucasian Utah residents of northern and western Europe ancestry (22). Furthermore, results from a recent genome-wide scan (CGEMS) in one of our study populations (PLCO) provided information on four additional PTGS2 SNPs (rs2206593, rs10911905, rs2143417 and rs2383529) not included in our original PLCO analysis, one of which was identified in HapMap (rs2206593) as a tagging SNP. No significant associations with prostate cancer risk were observed for any of these PTGS2 SNPs (all P-values ≥ 0.36) (17), indicating that PTGS2 is not associated with prostate cancer.

Another limitation is that we did not examine other types of genetic variation, such as deletions, insertions or tandem repeats, and it is possible that these types of genetic variation in the PTGS2 gene are important. Furthermore, variations in other genes in the inflammation pathway may interact with variants in PTGS2 to affect the risk of prostate cancer. Thus, future studies should seek to examine the combined effects of multiple genes in the inflammation pathway on prostate cancer risk.

In conclusion, despite the potential importance of inflammation in prostate carcinogenesis, results from our large study of five PTGS2 SNPs does not support a strong association between PTGS2 variants and prostate cancer risk in non-Hispanic white men. However, it is possible that PTGS2 may interact with other genes or lifestyle factors, such as NSAID use, to influence prostate cancer risk. Larger studies will be needed to evaluate such interactions.


   Funding
Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 Funding
References
 
Intramural Research Program of the National Cancer Institute, National Institutes of Health, Department of Health and Human Services; this project funded in part with federal funds from the National Cancer Institute, National Institutes of Health (under contract N01-CO-12400); the Sallie Rosen Kaplan Fellowship for Women Scientists in Cancer Research (to K.N.D.), National Cancer Institute, National Institutes of Health, Department of Health and Human Services.


   Acknowledgments
 
We thank Drs Christine Berg and Philip Prorok (Division of Cancer Prevention, NCI); the Screening Center investigators and staff of the PLCO Cancer Screening Trial; Tom Riley and staff (Information Management Services, Silver Spring, MD); Barbara O'Brien, Shelley Niwa and staff (Westat, Rockville, MD); Drs Bill Kopp, Wen Shao and staff (Science Applications International Corporation-Frederick) and Kimberly Walker–Thurmond and Cari Lichtman (American Cancer Society) for their contributions to making this study possible. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products or organizations imply endorsement by the USA Government.

Conflict of Interest Statement: None declared.


   References
Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 Funding
 References
 

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Received September 7, 2007; revised November 2, 2007; accepted November 4, 2007.


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