| 1. |
- Barrdahl, Myrto, et al.
(author)
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Post-G WAS gene-environment interplay in breast cancer : results from the Breast and Prostate Cancer Cohort Consortium and a meta-analysis on 79 000 women
- 2014
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In: Human Molecular Genetics. - : Oxford University Press (OUP). - 0964-6906 .- 1460-2083. ; 23:19, s. 5260-5270
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Journal article (peer-reviewed)abstract
- We studied the interplay between 39 breast cancer (BC) risk SNPs and established BC risk (body mass index, height, age at menarche, parity, age at menopause, smoking, alcohol and family history of BC) and prognostic factors (TNM stage, tumor grade, tumor size, age at diagnosis, estrogen receptor status and progesterone receptor status) as joint determinants of BC risk. We used a nested case-control design within the National Cancer Institute's Breast and Prostate Cancer Cohort Consortium (BPC3), with 16 285 BC cases and 19 376 controls. We performed stratified analyses for both the risk and prognostic factors, testing for heterogeneity for the risk factors, and case-case comparisons for differential associations of polymorphisms by subgroups of the prognostic factors. We analyzed multiplicative interactions between the SNPs and the risk factors. Finally, we also performed a meta-analysis of the interaction ORs from BPC3 and the Breast Cancer Association Consortium. After correction for multiple testing, no significant interaction between the SNPs and the established risk factors in the BPC3 study was found. The meta-analysis showed a suggestive interaction between smoking status and SLC4A7-rs4973768 (P-interaction = 8.84 x 10(-4)) which, although not significant after considering multiple comparison, has a plausible biological explanation. In conclusion, in this study of up to almost 79 000 women we can conclusively exclude any novel major interactions between genome-wide association studies hits and the epidemiologic risk factors taken into consideration, but we propose a suggestive interaction between smoking status and SLC4A7-rs4973768 that if further replicated could help our understanding in the etiology of BC.
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| 2. |
- Berndt, Sonja I, et al.
(author)
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Large-scale fine mapping of the HNF1B locus and prostate cancer risk
- 2011
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In: Human Molecular Genetics. - : Oxford University Press (OUP). - 0964-6906 .- 1460-2083. ; 20:16, s. 3322-3329
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Journal article (peer-reviewed)abstract
- Previous genome-wide association studies have identified two independent variants in HNF1B as susceptibility loci for prostate cancer risk. To fine-map common genetic variation in this region, we genotyped 79 single nucleotide polymorphisms (SNPs) in the 17q12 region harboring HNF1B in 10 272 prostate cancer cases and 9123 controls of European ancestry from 10 case-control studies as part of the Cancer Genetic Markers of Susceptibility (CGEMS) initiative. Ten SNPs were significantly related to prostate cancer risk at a genome-wide significance level of P < 5 × 10(-8) with the most significant association with rs4430796 (P = 1.62 × 10(-24)). However, risk within this first locus was not entirely explained by rs4430796. Although modestly correlated (r(2)= 0.64), rs7405696 was also associated with risk (P = 9.35 × 10(-23)) even after adjustment for rs4430769 (P = 0.007). As expected, rs11649743 was related to prostate cancer risk (P = 3.54 × 10(-8)); however, the association within this second locus was stronger for rs4794758 (P = 4.95 × 10(-10)), which explained all of the risk observed with rs11649743 when both SNPs were included in the same model (P = 0.32 for rs11649743; P = 0.002 for rs4794758). Sequential conditional analyses indicated that five SNPs (rs4430796, rs7405696, rs4794758, rs1016990 and rs3094509) together comprise the best model for risk in this region. This study demonstrates a complex relationship between variants in the HNF1B region and prostate cancer risk. Further studies are needed to investigate the biological basis of the association of variants in 17q12 with prostate cancer.
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| 3. |
- Campa, Daniele, et al.
(author)
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Interactions Between Genetic Variants and Breast Cancer Risk Factors in the Breast and Prostate Cancer Cohort Consortium
- 2011
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In: Journal of the National Cancer Institute. - : Oxford University Press (OUP). - 0027-8874 .- 1460-2105. ; 103:16, s. 1252-1263
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Journal article (peer-reviewed)abstract
- Background Recently, several genome-wide association studies have identified various genetic susceptibility loci for breast cancer. Relatively little is known about the possible interactions between these loci and the established risk factors for breast cancer. Methods To assess interactions between single-nucleotide polymorphisms (SNPs) and established risk factors, we prospectively collected DNA samples and questionnaire data from 8576 breast cancer case subjects and 11 892 control subjects nested within the National Cancer Institute's Breast and Prostate Cancer Cohort Consortium (BPC3). We genotyped 17 germline SNPs (FGFR2-rs2981582, FGFR2-rs3750817, TNRC9-rs3803662, 2q35-rs13387042, MAP3K1-rs889312, 8q24-rs13281615, CASP8-rs1045485, LSP1-rs3817198, COL1A1-rs2075555, COX11-rs6504950, RNF146-rs2180341, 6q25-rs2046210, SLC4A7-rs4973768, NOTCH2-rs11249433, 5p12-rs4415084, 5p12-rs10941679, RAD51L1-rs999737), and odds ratios were estimated by logistic regression to confirm previously reported associations with breast cancer risk. We performed likelihood ratio test to assess interactions between 17 SNPs and nine established risk factors (age at menarche, parity, age at menopause, use of hormone replacement therapy, family history, height, body mass index, smoking status, and alcohol consumption), and a correction for multiple testing of 153 tests (adjusted P value threshold = .05/153 = 3 x 10(-4)) was done. Casecase comparisons were performed for possible differential associations of polymorphisms by subgroups of tumor stage, estrogen and progesterone receptor status, and age at diagnosis. All statistical tests were two-sided. Results We confirmed the association of 14 SNPs with breast cancer risk (P(trend) = 2.57 x 10(-3) -3.96 x 10(-19)). Three SNPs (LSP1-rs3817198, COL1A1-rs2075555, and RNF146-rs2180341) did not show association with breast cancer risk. After accounting for multiple testing, no statistically significant interactions were detected between the 17 SNPs and the nine risk factors. We also confirmed that SNPs in FGFR2 and TNRC9 were associated with greater risk of estrogen receptor-positive than estrogen receptor-negative breast cancer (P(heterogeneity) = .0016 for FGFR2-rs2981582 and P(heterogeneity) = .0053 for TNRC9-rs3803662). SNP 5p12-rs10941679 was statistically significantly associated with greater risk of progesterone receptor-positive than progesterone receptor-negative breast cancer (P(heterogeneity) = .0028). Conclusion This study does not support the hypothesis that known common breast cancer susceptibility loci strongly modify the associations between established risk factors and breast cancer.
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| 4. |
- Cao, Yin, et al.
(author)
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Insulin-like growth factor pathway genetic polymorphisms, circulating IGF1 and IGFBP3, and prostate cancer survival
- 2014
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In: Journal of the National Cancer Institute. - : Oxford University Press. - 0027-8874 .- 1460-2105. ; 106:5
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Journal article (peer-reviewed)abstract
- BACKGROUND: The insulin-like growth factor (IGF) signaling pathway has been implicated in prostate cancer (PCa) initiation, but its role in progression remains unknown.METHODS: Among 5887 PCa patients (704 PCa deaths) of European ancestry from seven cohorts in the National Cancer Institute Breast and Prostate Cancer Cohort Consortium, we conducted Cox kernel machine pathway analysis to evaluate whether 530 tagging single nucleotide polymorphisms (SNPs) in 26 IGF pathway-related genes were collectively associated with PCa mortality. We also conducted SNP-specific analysis using stratified Cox models adjusting for multiple testing. In 2424 patients (313 PCa deaths), we evaluated the association of prediagnostic circulating IGF1 and IGFBP3 levels and PCa mortality. All statistical tests were two-sided.RESULTS: The IGF signaling pathway was associated with PCa mortality (P = .03), and IGF2-AS and SSTR2 were the main contributors (both P = .04). In SNP-specific analysis, 36 SNPs were associated with PCa mortality with P-trend less than .05, but only three SNPs in the IGF2-AS remained statistically significant after gene-based corrections. Two were in linkage disequilibrium (r(2) = 1 for rs1004446 and rs3741211), whereas the third, rs4366464, was independent (r(2) = 0.03). The hazard ratios (HRs) per each additional risk allele were 1.19 (95% confidence interval [CI] = 1.06 to 1.34; P-trend = .003) for rs3741211 and 1.44 (95% CI = 1.20 to 1.73; P-trend < .001) for rs4366464. rs4366464 remained statistically significant after correction for all SNPs (P-trend.corr = .04). Prediagnostic IGF1 (HRhighest (vs lowest quartile) = 0.71; 95% CI = 0.48 to 1.04) and IGFBP3 (HR = 0.93; 95% Cl = 0.65 to 1.34) levels were not associated with PCa mortality.CONCLUSIONS: The IGF signaling pathway, primarily IGF2-AS and SSTR2 genes, may be important in PCa survival.
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| 5. |
- Joshi, Amit D., et al.
(author)
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Additive interactions between susceptibility single-nucleotide polymorphisms identified in genome-wide association studies and breast cancer risk factors in the Breast and Prostate Cancer Cohort Consortium
- 2014
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In: American Journal of Epidemiology. - : Oxford University Press. - 0002-9262 .- 1476-6256. ; 180:10, s. 1018-1027
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Journal article (peer-reviewed)abstract
- Additive interactions can have public health and etiological implications but are infrequently reported. We assessed departures from additivity on the absolute risk scale between 9 established breast cancer risk factors and 23 susceptibility single-nucleotide polymorphisms (SNPs) identified from genome-wide association studies among 10,146 non-Hispanic white breast cancer cases and 12,760 controls within the National Cancer Institute's Breast and Prostate Cancer Cohort Consortium. We estimated the relative excess risk due to interaction and its 95% confidence interval for each pairwise combination of SNPs and nongenetic risk factors using age- and cohort-adjusted logistic regression models. After correction for multiple comparisons, we identified a statistically significant relative excess risk due to interaction (uncorrected P = 4.51 x 10(-5)) between a SNP in the DNA repair protein RAD51 homolog 2 gene (RAD51L1; rs10483813) and body mass index (weight (kg)/height (m)(2)). We also compared additive and multiplicative polygenic risk prediction models using per-allele odds ratio estimates from previous studies for breast-cancer susceptibility SNPs and observed that the multiplicative model had a substantially better goodness of fit than the additive model.
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| 6. |
- Lindstroem, Sara, et al.
(author)
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Common genetic variants in prostate cancer risk prediction-results from the NCI breast and prostate cancer cohort consortium (BPC3)
- 2012
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In: Cancer Epidemiology, Biomarkers and Prevention. - 1055-9965 .- 1538-7755. ; 21:3, s. 437-444
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Journal article (peer-reviewed)abstract
- Background: One of the goals of personalized medicine is to generate individual risk profiles that could identify individuals in the population that exhibit high risk. The discovery of more than two-dozen independent single-nucleotide polymorphism markers in prostate cancer has raised the possibility for such risk stratification. In this study, we evaluated the discriminative and predictive ability for prostate cancer risk models incorporating 25 common prostate cancer genetic markers, family history of prostate cancer, and age.Methods: We fit a series of risk models and estimated their performance in 7,509 prostate cancer cases and 7,652 controls within the National Cancer Institute Breast and Prostate Cancer Cohort Consortium (BPC3). We also calculated absolute risks based on SEER incidence data.Results: The best risk model (C-statistic = 0.642) included individual genetic markers and family history of prostate cancer. We observed a decreasing trend in discriminative ability with advancing age (P = 0.009), with highest accuracy in men younger than 60 years (C-statistic = 0.679). The absolute ten-year risk for 50-year-old men with a family history ranged from 1.6% (10th percentile of genetic risk) to 6.7% (90th percentile of genetic risk). For men without family history, the risk ranged from 0.8% (10th percentile) to 3.4% (90th percentile).Conclusions: Our results indicate that incorporating genetic information and family history in prostate cancer risk models can be particularly useful for identifying younger men that might benefit from prostate-specific antigen screening.Impact: Although adding genetic risk markers improves model performance, the clinical utility of these genetic risk models is limited.
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| 7. |
- Lindstrom, Sara, et al.
(author)
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Characterizing Associations and SNP-Environment Interactions for GWAS-Identified Prostate Cancer Risk Markers-Results from BPC3
- 2011
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In: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 6:2
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Journal article (peer-reviewed)abstract
- Genome-wide association studies (GWAS) have identified multiple single nucleotide polymorphisms (SNPs) associated with prostate cancer risk. However, whether these associations can be consistently replicated, vary with disease aggressiveness (tumor stage and grade) and/or interact with non-genetic potential risk factors or other SNPs is unknown. We therefore genotyped 39 SNPs from regions identified by several prostate cancer GWAS in 10,501 prostate cancer cases and 10,831 controls from the NCI Breast and Prostate Cancer Cohort Consortium (BPC3). We replicated 36 out of 39 SNPs (P-values ranging from 0.01 to 10(-28)). Two SNPs located near KLK3 associated with PSA levels showed differential association with Gleason grade (rs2735839, P = 0.0001 and rs266849, P = 0.0004; case-only test), where the alleles associated with decreasing PSA levels were inversely associated with low-grade (as defined by Gleason grade,8) tumors but positively associated with high-grade tumors. No other SNP showed differential associations according to disease stage or grade. We observed no effect modification by SNP for association with age at diagnosis, family history of prostate cancer, diabetes, BMI, height, smoking or alcohol intake. Moreover, we found no evidence of pair-wise SNP-SNP interactions. While these SNPs represent new independent risk factors for prostate cancer, we saw little evidence for effect modification by other SNPs or by the environmental factors examined.
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| 8. |
- Schumacher, Fredrick R., et al.
(author)
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Genome-wide association study identifies new prostate cancer susceptibility loci
- 2011
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In: Human Molecular Genetics. - London : IRL Press. - 0964-6906 .- 1460-2083. ; 20:19, s. 3867-3875
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Journal article (peer-reviewed)abstract
- Prostate cancer (PrCa) is the most common non-skin cancer diagnosed among males in developed countries and the second leading cause of cancer mortality, yet little is known regarding its etiology and factors that influence clinical outcome. Genome-wide association studies (GWAS) of PrCa have identified at least 30 distinct loci associated with small differences in risk. We conducted a GWAS in 2782 advanced PrCa cases (Gleason grade >= 8 or tumor stage C/D) and 4458 controls with 571 243 single nucleotide polymorphisms (SNPs). Based on in silico replication of 4679 SNPs (Stage 1, P < 0.02) in two published GWAS with 7358 PrCa cases and 6732 controls, we identified a new susceptibility locus associated with overall PrCa risk at 2q37.3 (rs2292884, P = 4.3 x 10(-8)). We also confirmed a locus suggested by an earlier GWAS at 12q13 (rs902774, P = 8.6 x 10(-9)). The estimated per-allele odds ratios for these loci (1.14 for rs2292884 and 1.17 for rs902774) did not differ between advanced and non-advanced PrCa (case-only test for heterogeneity P = 0.72 and P = 0.61, respectively). Further studies will be needed to assess whether these or other loci are differentially associated with PrCa subtypes.
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| 9. |
- Shui, Irene M., et al.
(author)
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Prostate Cancer (PCa) Risk Variants and Risk of Fatal PCa in the National Cancer Institute Breast and Prostate Cancer Cohort Consortium
- 2014
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In: European Urology. - : Elsevier BV. - 0302-2838 .- 1873-7560. ; 65:6, s. 1069-1075
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Journal article (peer-reviewed)abstract
- Background: Screening and diagnosis of prostate cancer (PCa) is hampered by an inability to predict who has the potential to develop fatal disease and who has indolent cancer. Studies have identified multiple genetic risk loci for PCa incidence, but it is unknown whether they could be used as biomarkers for PCa-specific mortality (PCSM). Objective: To examine the association of 47 established PCa risk single-nucleotide polymorphisms (SNPs) with PCSM. Design, setting, and participants: We included 10 487 men who had PCa and 11 024 controls, with a median follow-up of 8.3 yr, during which 1053 PCa deaths occurred. Outcome measurements and statistical analysis: The main outcome was PCSM. The risk allele was defined as the allele associated with an increased risk for PCa in the literature. We used Cox proportional hazards regression to calculate the hazard ratios of each SNP with time to progression to PCSM after diagnosis. We also used logistic regression to calculate odds ratios for each risk SNP, comparing fatal PCa cases to controls. Results and limitations: Among the cases, we found that 8 of the 47 SNPs were significantly associated (p < 0.05) with time to PCSM. The risk allele of rs11672691 (intergenic) was associated with an increased risk for PCSM, while 7 SNPs had risk alleles inversely associated (rs13385191 [C2orf43], rs17021918 [PDLIM5], rs10486567 [JAZF1], rs6465657 [LMTK2], rs7127900 (intergenic), rs2735839 [KLK3], rs10993994 [MSMB], rs13385191 [C2orf43]). In the case-control analysis, 22 SNPs were associated (p < 0.05) with the risk of fatal PCa, but most did not differentiate between fatal and nonfatal PCa. Rs11672691 and rs10993994 were associated with both fatal and nonfatal PCa, while rs6465657, rs7127900, rs2735839, and rs13385191 were associated with nonfatal PCa only. Conclusions: Eight established risk loci were associated with progression to PCSM after diagnosis. Twenty-two SNPs were associated with fatal PCa incidence, but most did not differentiate between fatal and nonfatal PCa. The relatively small magnitudes of the associations do not translate well into risk prediction, but these findings merit further follow-up, because they may yield important clues about the complex biology of fatal PCa. Patient summary: In this report, we assessed whether established PCa risk variants could predict PCSM. We found eight risk variants associated with PCSM: One predicted an increased risk of PCSM, while seven were associated with decreased risk. Larger studies that focus on fatal PCa are needed to identify more markers that could aid prediction. (C) 2013 European Association of Urology. Published by Elsevier B.V. All rights reserved.
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| 10. |
- Tsilidis, Konstantinos K., et al.
(author)
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Insulin-like growth factor pathway genes and blood concentrations, dietary protein and risk of prostate cancer in the NCI Breast and Prostate Cancer Cohort Consortium (BPC3)
- 2013
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In: International Journal of Cancer. - Hoboken, NJ, USA : Wiley-Blackwell. - 0020-7136 .- 1097-0215. ; 133:2, s. 495-504
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Journal article (peer-reviewed)abstract
- It has been hypothesized that a high intake of dairy protein may increase prostate cancer risk by increasing the production of insulin-like growth factor 1 (IGF-1). Several single nucleotide polymorphisms (SNPs) have been weakly associated with circulating concentrations of IGF-1 and IGF binding protein 3 (IGFBP-3), but none of these SNPs was associated with risk of prostate cancer. We examined whether an association between 16 SNPs associated with circulating IGF-1 or IGFBP-3 concentrations and prostate cancer exists within subgroups defined by dietary protein intake in 5,253 cases and 4,963 controls of European ancestry within the NCI Breast and Prostate Cancer Cohort Consortium (BPC3). The BPC3 includes nested casecontrol studies within large North-American and European cohorts. Per-allele odds ratios for prostate cancer for the SNPs were compared across tertiles of protein intake, which was expressed as the percentage of energy derived from total, animal, dairy or plant protein sources, using conditional logistic regression models. Total, animal, dairy and plant protein intakes were significantly positively associated with blood IGF-1 (p<0.01), but not with IGFBP-3 concentrations (p>0.10) or with risk of prostate cancer (p>0.20). After adjusting for multiple testing, the SNP-prostate cancer associations did not differ by intakes of protein, although two interactions by intake of plant protein were of marginal statistical significance [SSTR5 (somatostatin receptor 5)-rs197056 (uncorrected p for interaction, 0.001); SSTR5-rs197057 (uncorrected p for interaction, 0.002)]. We found no strong evidence that the associations between 16 IGF pathway SNPs and prostate cancer differed by intakes of dietary protein.
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