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Departments of 1 Epidemiology and 2 Nutrition, 3 Program in Molecular and Genetic Epidemiology, Harvard School of Public Health; Divisions of 4 Preventive Medicine and 5 Aging, 6 Channing Laboratory, Brigham and Women's Hospital, Department of Medicine, Harvard Medical School; 7 Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts; 8 Department of Epidemiology and Surveillance Research, American Cancer Society, National Home Office, Atlanta, Georgia; 9 Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California; 10 Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland; 11 Core Genotyping Facility, National Cancer Institute, Gaithersburg, Maryland; 12 Department of Oncology, University of Cambridge, Cambridge, United Kingdom; 13 Hormones and Cancer Group, 14 Unit of Nutrition and Cancer, International Agency for Research on Cancer, Lyon, France; 15 Epidemiology Unit, Cancer Research United Kingdom, University of Oxford, Oxford, United Kingdom; 16 Cancer Research Center, University of Hawaii, Honolulu, Hawaii; 17 Fondation Jean Dausset, Centre d'Etude du Polymorphisme Humain, Paris, France; 18 Cancer Prevention Unit, National Public Health Institute, Helsinki, Finland; 19 Division of Urology, Washington University School of Medicine, St. Louis, Missouri; and 20 Division of Hematology and Oncology, Milstein Hospital, College of Physicians and Surgeons, Columbia University, New York, New York
Requests for reprints: David J. Hunter, Channing Laboratory, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA 02115. Phone: 617-525-2755; E-mail: dhunter{at}hsph.harvard.edu.
| Abstract |
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| Introduction |
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| Materials and Methods |
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The rs1447295 marker was genotyped using a TaqMan assay and the ABI PRISM 7900 for sequence detection (TaqMan; Applied Biosystems, Foster City, CA) in four laboratories for the prostate samples and in two laboratories for the breast samples. All of the cohorts were represented in the prostate cancer genotyping and the breast cancer genotyping included four cohorts: the ACS-CPSII, the MEC, the Nurses' Health Study, and the Women's Health Study. The genotyping centers were blinded to the inclusion of duplicate or triplicate quality control samples (510%). Each genotyping center reported >99% concordance with the blinded samples and a genotyping completion rate >95%.
We restricted the majority of our prostate cancer analyses to Caucasians because ethnicity-specific results have been reported elsewhere by Freedman et al. (8) for the MEC samples. African Americans were included only in the analyses assessing effect modification by age. Assuming an additive genetic model, we used conditional logistic regression to estimate the ORs for disease associated with carrying one copy of the minor allele (A) relative to carrying no copies, and with carrying two copies relative to carrying no copies. All of the models were adjusted for age in 5-year intervals, cohort, and country where applicable. Ninety-nine percent confidence intervals (CI) are provided and the two-sided P values for association are from a 2 df likelihood ratio test (LRT) comparing the full model with the rs1447295 genotypes versus the intercept-only model. We used in-house SAS v.9.1 (SAS Institute, Cary, NC) macros to perform our analyses, and SAS default options were modified to obtain very small P values in scientific notation.
We tested for heterogeneity in OR estimates across age at diagnosis, body mass index (BMI), height, and family history. The cut-points for the stratifying variables were defined prior to the analyses. We used WHO recommendations to categorize BMI (<25,
25 and <30, and
30 kg/m2), whereas the ethnicity and cohort specific tertile cut-points from controls were used for height. BMI was calculated from self-reported height and weight. Because the average age at diagnosis for prostate cancer was
65 years old before PSA screening, we used this as one of the age cut-points. This age at diagnosis cut-point has been commonly used in the literature to define early and late prostate cancer diagnoses (19, 20). The effects of age at diagnosis were explored further by using the ages of 60 and 70 as cut-points. We defined a positive family history as having at least one first-degree relative diagnosed with prostate cancer. When performing a stratified analysis, a LRT for heterogeneity was used to compare models with and without the cross-product terms. The stratified results according to cohort did not show statistically significant heterogeneity; thereafter, we did a pooled analysis across cohorts. Statistical tests for heterogeneity were assessed at the 0.05 level to minimize the chance of both false-positive and false-negative results.
We used multinomial logistic regression to assess the marker association with prostate cancer aggressiveness. In multinomial logistic regression, a referent group (e.g., controls) was compared with two or more groups (e.g., nonaggressive and aggressive cases) allowing the logits to be calculated simultaneously for each comparison. The aggressive and nonaggressive logits were then compared using a LRT to assess for the presence of heterogeneous effects across aggressiveness. In the multinomial logistic regression, the P values for the marker genotypes were calculated from a Wald
2 test.
Prostate cancer tumor aggressiveness was defined using three different clinical measures: (a) Gleason score at diagnosis, (b) the Whitmore-Jewett staging system, and (c) prostate cancer metastasis or death. Gleason score was categorized by those who had a combined score of
8 at diagnosis and those with a combined Gleason score of <8. When using tumor stage, we grouped cases diagnosed with stage A (T1 in the tumor-node-metastasis staging system) or B (T2) prostate cancer and had not died from prostate cancer or developed metastases during follow-up. The other staging group included cases with stage C (T3) or stage D (metastases) at diagnosis, developed metastases during follow-up, and died from prostate cancer. For the final classification, cases with metastases at diagnosis, or who developed metastases during follow-up or died from prostate cancer, were grouped and compared with those who had not died or developed metastases during follow-up. Cases with missing Gleason score, staging, or follow-up information were excluded from their respective analyses.
| Results |
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As shown in Table 1 , the overall prostate cancer risk in Caucasians, including the MEC Caucasian samples, was 1.34 (99% CI, 1.191.50) in men with one copy of the minor allele (A) and 1.86 (99% CI, 1.302.67) in men with two copies of the minor allele compared with wild-type homozygotes (P = 1.23 x 1013). The overall results were nearly equivalent (ORAC =1.34; 99% CI, 1.191.51; ORAA = 1.82; 99% CI, 1.262.64; P = 8.64 x 1013) when the MEC Caucasians were excluded. The magnitude of the ORs did not vary across cohort with or without the MEC samples, as indicated by the LRT of heterogeneity by cohort (P for heterogeneity by cohort = 0.410 with MEC and P for heterogeneity by cohort = 0.295 without MEC).
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65) was stratified by ethnicity, the effect modification remained statistically significant only in African Americans (P for heterogeneity by age = 0.037; Table 2). Age did not modify the risk in Caucasians excluding or including the MEC samples (P for heterogeneity by age = 0.164 with MEC and P for heterogeneity by age = 0.144 without MEC). The genotype association for the rs1447295 marker was statistically significant in African American men diagnosed at an early age (P = 0.011) and was nonsignificant for those diagnosed at a later age (P = 0.924). Conversely, Caucasian carriers of the minor allele were at greater risk regardless of the age stratum (Table 2). We further explored the effect of age using two additional cut-points (
60 and
70). Heterogeneity by age was not statistically significant among Caucasians, however, at the age cut-point of
60, effect modification remained statistically significant for African Americans (P for heterogeneity by age
60 = 0.027; Supplementary Table S1).
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8) at diagnosis. As shown in Table 3
, the heterozygote and variant homozygote point estimates among Caucasian cases with a Gleason score of <8 (ORAC = 1.29; ORAA = 1.68) and a Gleason score of
8 (ORAC = 1.31; ORAA = 2.12) at diagnosis were similar. The main effects did not differ significantly (P for heterogeneity by staging = 0.153) in high stage prostate cancers (ORAC = 1.33; 99% CI, 0.941.87; ORAA = 2.38; 99% CI, 1.294.40) versus low stage cancers (ORAC = 1.36; 99% CI, 1.111.66; ORAA = 1.70; 99% CI, 1.132.56) compared with controls (Table 3). Likewise, the main effects for diagnosis or development of metastases or death due to prostate cancer were not statistically different (P for heterogeneity by metastases/death = 0.373; ORAC = 1.09; 99% CI, 0.611.95; ORAA = 2.87; 99% CI, 1.226.74) contrasted to localized and nonfatal prostate cancer cases (ORAC = 1.38; 99% CI, 0.852.24; ORAA = 2.08; 99% CI, 0.513.53).
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6, 7, and
8 (Supplementary Table S2). We also examined several additional definitions of prostate cancer aggressiveness: Gleason score and tumor stage combinations (Supplementary Table S3), age at diagnosis stratified by Gleason score or tumor stage (Supplementary Table S4), and tumor stage C only versus controls (Supplementary Table S5). The rs1447295 marker remained statistically significant in nearly every stratum and the risk estimates were similar regardless of tumor classification. A substantial portion of the aggressiveness information was missing (see the legend in Table 3 for a list of the number of cases missing information according to cohort). However, the genotype distribution for individuals missing either tumor stage (CC, 73.2%; AC, 24.6%; AA, 2.2%), Gleason score (CC, 73.9%; AC, 23.7%; AA, 2.2%), or mortality (CC, 73.9%; AC, 24.1%; AA, 2.0%) was nearly identical to the genotype distribution among those with complete information (CC, 73.9%; AC, 23.8%; AA, 2.3%). This provides confidence in the validity of our findings for prostate cancer aggressiveness.
Finally, we assessed the presence of effect modification by several prostate cancer risk factors in Caucasians. The LRT for heterogeneity was not statistically significant for family history (P = 0.471), BMI (P = 0.534), or height (P = 0.353). The rs1447295 marker remained statistically significant across all strata (results not shown).
In the breast cancer analysis, we found no association between rs1447295 and breast cancer risk in any of the four cohorts (Supplementary Table S6). The EPIC breast cancer samples were not genotyped due to the null results observed in the cohorts reported here. As there was no heterogeneity in the risk estimates between cohorts (P for heterogeneity = 0.619), we pooled the data, and still found no association between this SNP and breast cancer risk (ORAC = 0.99; 95% CI, 0.871.14; ORAA = 0.77; 95% CI, 0.471.27; P = 0.590), compared with the CC homozygotes were the reference group. We also saw no evidence of association when the tumors were classified as in situ, localized, or metastatic. We did not observe any significant effect modification after stratification by estrogen or progesterone receptor status, age, or menopausal status (results not shown).
| Discussion |
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The population-attributable risk for this locus, using the minor allele frequencies in controls (Caucasian = 0.11; African Americans = 0.31) and risk estimates from a multiplicative model (ORCaucasian = 1.34; ORAfrican American = 1.17), was
6.6% and 8.2% in Caucasians and African Americans, respectively. Because the rs1447295 marker is not the causative locus, this is the minimum population-attributable risk. Within the BPC3 study, men with a positive family history of prostate cancer were more likely to be diagnosed with prostate cancer compared with men without a positive family history (OR = 1.73; 99% CI, 1.472.00). The association between family history and prostate cancer was only slightly attenuated (OR = 1.70; 99% CI, 1.461.99) when adjusted for the rs1447295 marker. Again, the causative locus may have a greater effect on the association between prostate cancer and family history.
The absence of any association between this marker and breast cancer suggests that the 8q24 locus may not be harboring a gene that is a general cause of hormone-related cancers. The lack of a significant difference between several definitions of early versus late prostate cancers suggests that the unknown gene is associated with prostate cancer at all stages. Our large sample size leaves little room for the possibility of a false-positive result between this locus and prostate cancer risk.
| Acknowledgments |
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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 accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
| Footnotes |
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Received 9/27/06. Revised 12/18/06. Accepted 2/ 7/07.
| References |
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