| 1. |
- Canzian, Federico, et al.
(author)
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Genetic polymorphisms of the GNRH1 and GNRHR genes and risk of breast cancer in the National Cancer Institute Breast and Prostate Cancer Cohort Consortium (BPC3).
- 2009
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In: BMC cancer. - : Springer Science and Business Media LLC. - 1471-2407. ; 9, s. 257-
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Journal article (peer-reviewed)abstract
- BACKGROUND: Gonadotropin releasing hormone (GNRH1) triggers the release of follicle stimulating hormone and luteinizing hormone from the pituitary. Genetic variants in the gene encoding GNRH1 or its receptor may influence breast cancer risk by modulating production of ovarian steroid hormones. We studied the association between breast cancer risk and polymorphisms in genes that code for GNRH1 and its receptor (GNRHR) in the large National Cancer Institute Breast and Prostate Cancer Cohort Consortium (NCI-BPC3). METHODS: We sequenced exons of GNRH1 and GNRHR in 95 invasive breast cancer cases. Resulting single nucleotide polymorphisms (SNPs) were genotyped and used to identify haplotype-tagging SNPs (htSNPS) in a panel of 349 healthy women. The htSNPs were genotyped in 5,603 invasive breast cancer cases and 7,480 controls from the Cancer Prevention Study-II (CPS-II), European Prospective Investigation on Cancer and Nutrition (EPIC), Multiethnic Cohort (MEC), Nurses' Health Study (NHS), and Women's Health Study (WHS). Circulating levels of sex steroids (androstenedione, estradiol, estrone and testosterone) were also measured in 4713 study subjects. RESULTS: Breast cancer risk was not associated with any polymorphism or haplotype in the GNRH1 and GNRHR genes, nor were there any statistically significant interactions with known breast cancer risk factors. Polymorphisms in these two genes were not strongly associated with circulating hormone levels. CONCLUSION: Common variants of the GNRH1 and GNRHR genes are not associated with risk of invasive breast cancer in Caucasians.
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| 2. |
- 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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| 3. |
- Canzian, Federico, et al.
(author)
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Comprehensive analysis of common genetic variation in 61 genes related to steroid hormone and insulin-like growth factor-I metabolism and breast cancer risk in the NCI breast and prostate cancer cohort consortium.
- 2010
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In: Human Molecular Genetics. - : Oxford University Press (OUP). - 0964-6906 .- 1460-2083. ; 19:19, s. 3873-84
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Journal article (peer-reviewed)abstract
- There is extensive evidence that increases in blood and tissue concentrations of steroid hormones and of insulin-like growth factor I (IGF-I) are associated with breast cancer risk. However, studies of common variation in genes involved in steroid hormone and IGF-I metabolism have yet to provide convincing evidence that such variants predict breast cancer risk. The Breast and Prostate Cancer Cohort Consortium (BPC3) is a collaboration of large US and European cohorts. We genotyped 1416 tagging single nucleotide polymorphisms (SNPs) in 37 steroid hormone metabolism genes and 24 IGF-I pathway genes in 6292 cases of breast cancer and 8135 controls, mostly Caucasian, postmenopausal women from the BPC3. We also imputed 3921 additional SNPs in the regions of interest. None of the SNPs tested was significantly associated with breast cancer risk, after correction for multiple comparisons. The results remained null when cases and controls were stratified by age at diagnosis/recruitment, advanced or nonadvanced disease, body mass index, with or without in situ cases; or restricted to Caucasians. Among 770 estrogen receptor-negative cases, an SNP located 3' of growth hormone receptor (GHR) was marginally associated with increased risk after correction for multiple testing (P(trend) = 1.5 × 10(-4)). We found no significant overall associations between breast cancer and common germline variation in 61 genes involved in steroid hormone and IGF-I metabolism in this large, comprehensive study. Although previous studies have shown that variations in these genes can influence endogenous hormone levels, the magnitude of the effect of single SNPs does not appear to be sufficient to alter breast cancer risk.
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| 4. |
- Cox, David G., et al.
(author)
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A comprehensive analysis of the androgen receptor gene and risk of breast cancer: results from the National Cancer Institute Breast and Prostate Cancer Cohort Consortium (BPC3)
- 2006
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In: Breast Cancer Research. - : Springer Science and Business Media LLC. - 1465-5411 .- 1465-542X. ; 8:5
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Journal article (peer-reviewed)abstract
- Introduction Androgens have been hypothesised to influence risk of breast cancer through several possible mechanisms, including their conversion to estradiol or their binding to the oestrogen receptor and/ or androgen receptor ( AR) in the breast. Here, we report on the results of a large and comprehensive study of the association between genetic variation in the AR gene and risk of breast cancer in the National Cancer Institute Breast and Prostate Cancer Cohort Consortium ( BPC3). Methods The underlying genetic variation was determined by first sequencing the coding regions of the AR gene in a panel of 95 advanced breast cancer cases. Second, a dense set of markers from the public database was genotyped in a panel of 349 healthy women. The linkage disequilibrium relationships ( blocks) across the gene were then identified, and haplotypetagging single nucleotide polymorphisms ( htSNPs) were selected to capture the common genetic variation across the locus. The htSNPs were then genotyped in the nested breast cancer cases and controls from the Cancer Prevention Study II, European Prospective Investigation into Cancer and Nutrition, Multiethnic Cohort, Nurses' Health Study, and Women's Health Study cohorts ( 5,603 breast cancer cases and 7,480 controls). Results We found no association between any genetic variation ( SNP, haplotype, or the exon 1 CAG repeat) in the AR gene and risk of breast cancer, nor were any statistical interactions with known breast cancer risk factors observed. Conclusion Among postmenopausal Caucasian women, common variants of the AR gene are not associated with risk of breast cancer.
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| 5. |
- Cox, David G, et al.
(author)
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Haplotypes of the estrogen receptor beta gene and breast cancer risk
- 2008
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In: International Journal of Cancer. - : Wiley. - 0020-7136. ; 122:2, s. 387-392
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Journal article (peer-reviewed)abstract
- Exposure to exogenous (oral contraceptives, postmenopausal hormone therapy) and endogenous (number of ovulatory cycles, adiposity) steroid hormones is associated with breast cancer risk. Breast cancer risk associated with these exposures could hypothetically be modified by genes in the steroid hormone synthesis, metabolism and signaling pathways. Estrogen receptors are the first step along the path of signaling cell growth and development upon stimulation with estrogens. The National Cancer Institute Breast and Prostate Cancer Cohort Consortium has systematically selected haplotype tagging SNPs in genes along the steroid hormone synthesis, metabolism and binding pathways, including the estrogen receptor beta (ESR2) gene. Four htSNPs tag the 6 major (>5% frequency) haplotypes of the ESR2 gene. These polymorphisms have been genotyped in 5,789 breast cancer cases and 7,761 controls nested within the American Cancer Society Cancer Prevention Study II, European Prospective Investigation into Cancer and Nutrition, Multiethnic Cohort, Nurses' Health Study and Women's Health Study cohorts. None of the SNPs were independently associated with breast cancer risk. One haplotype of the ESR2 gene was associated with breast cancer risk before correction for multiple testing (OR 1.17, 95% CI 1.07-1.28, p = 0.0007). This haplotype remained associated with breast cancer risk after adjustment for multiple testing using a permutation procedure. There was no statistically significant heterogeneity in SNP or haplotype odds ratios across cohorts. These data suggest that inherited variants in ESR2 (while possibly conferring a small increased risk of breast cancer) are not associated with appreciable (OR > 1.2) changes in breast cancer risk among Caucasian women.
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| 6. |
- Dossus, Laure, et al.
(author)
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PTGS2 and IL6 genetic variation and risk of breast and prostate cancer : results from the Breast and Prostate Cancer Cohort Consortium (BPC3)
- 2010
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In: Carcinogenesis. - : Oxford University Press (OUP). - 0143-3334 .- 1460-2180. ; 31:3, s. 455-461
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Journal article (peer-reviewed)abstract
- Genes involved in the inflammation pathway have been associated with cancer risk. Genetic variants in the interleukin-6 (IL6) and prostaglandin-endoperoxide synthase-2 (PTGS2, encoding for the COX-2 enzyme) genes, in particular, have been related to several cancer types, including breast and prostate cancers. We conducted a study within the Breast and Prostate Cancer Cohort Consortium to examine the association between IL6 and PTGS2 polymorphisms and breast and prostate cancer risk. Twenty-seven polymorphisms, selected by pairwise tagging, were genotyped on 6292 breast cancer cases and 8135 matched controls and 8008 prostate cancer cases and 8604 matched controls. The large sample sizes and comprehensive single nucleotide polymorphism tagging in this study gave us excellent power to detect modest effects for common variants. After adjustment for multiple testing, none of the associations examined remained statistically significant at P = 0.01. In analyses not adjusted for multiple testing, one IL6 polymorphism (rs6949149) was marginally associated with breast cancer risk (TT versus GG, odds ratios (OR): 1.32; 99% confidence intervals (CI): 1.00-1.74, P(trend) = 0.003) and two were marginally associated with prostate cancer risk (rs6969502-AA versus rs6969502-GG, OR: 0.87, 99% CI: 0.75-1.02; P(trend) = 0.002 and rs7805828-AA versus rs7805828-GG, OR: 1.11, 99% CI: 0.99-1.26; P(trend) = 0.007). An increase in breast cancer risk was observed for the PTGS2 polymorphism rs7550380 (TT versus GG, OR: 1.38, 99% CI: 1.04-1.83). No association was observed between PTGS2 polymorphisms and prostate cancer risk. In conclusion, common genetic variation in these two genes might play at best a limited role in breast and prostate cancers.
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| 7. |
- Gu, Fangyi, et al.
(author)
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Eighteen insulin-like growth factor pathway genes, circulating levels of IGF-I and its binding protein, and risk of prostate and breast cancer
- 2010
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In: Cancer Epidemiology, Biomarkers and Prevention. - : American Association for Cancer Research. - 1055-9965 .- 1538-7755. ; 19:11, s. 2877-2887
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Journal article (peer-reviewed)abstract
- Background: Circulating levels of insulin-like growth factor I (IGF-I) and its main binding protein, IGF binding protein 3 (IGFBP-3), have been associated with risk of several types of cancer. Heritable factors explain up to 60% of the variation in IGF-I and IGFBP-3 in studies of adult twins.Methods: We systematically examined common genetic variation in 18 genes in the IGF signaling pathway for associations with circulating levels of IGF-I and IGFBP-3. A total of 302 single nucleotide polymorphisms (SNP) were genotyped in >5,500 Caucasian men and 5,500 Caucasian women from the Breast and Prostate Cancer Cohort Consortium.Results: After adjusting for multiple testing, SNPs in the IGF1 and SSTR5 genes were significantly associated with circulating IGF-I (P < 2.1 × 10−4); SNPs in the IGFBP3 and IGFALS genes were significantly associated with circulating IGFBP-3. Multi-SNP models explained R2 = 0.62% of the variation in circulating IGF-I and 3.9% of the variation in circulating IGFBP-3. We saw no significant association between these multi-SNP predictors of circulating IGF-I or IGFBP-3 and risk of prostate or breast cancers.Conclusion: Common genetic variation in the IGF1 and SSTR5 genes seems to influence circulating IGF-I levels, and variation in IGFBP3 and IGFALS seems to influence circulating IGFBP-3. However, these variants explain only a small percentage of the variation in circulating IGF-I and IGFBP-3 in Caucasian men and women.Impact: Further studies are needed to explore contributions from other genetic factors such as rare variants in these genes and variation outside of these genes.
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| 8. |
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| 9. |
- Hendrickson, Sara J., et al.
(author)
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Plasma Carotenoid- and Retinol-Weighted Multi-SNP Scores and Risk of Breast Cancer in the National Cancer Institute Breast and Prostate Cancer Cohort Consortium
- 2013
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In: Cancer Epidemiology, Biomarkers and Prevention. - Philadelphia, PA, USA : American Association for Cancer Research. - 1055-9965 .- 1538-7755. ; 22:5, s. 927-936
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Journal article (peer-reviewed)abstract
- Background: Dietary and circulating carotenoids have been inversely associated with breast cancer risk, but observed associations may be due to confounding. Single-nucleotide polymorphisms (SNPs) in beta-carotene 15,15'-monooxygenase 1 (BCMO1), a gene encoding the enzyme involved in the first step of synthesizing vitamin A from dietary carotenoids, have been associated with circulating carotenoid concentrations and may serve as unconfounded surrogates for those biomarkers. We determined associations between variants in BCMO1 and breast cancer risk in a large cohort consortium. Methods: We used unconditional logistic regression to test four SNPs in BCMO1 for associations with breast cancer risk in 9,226 cases and 10,420 controls from the National Cancer Institute Breast and Prostate Cancer Cohort Consortium (BPC3). We also tested weighted multi-SNP scores composed of the two SNPs with strong, confirmed associations with circulating carotenoid concentrations. Results: Neither the individual SNPs nor the weighted multi-SNP scores were associated with breast cancer risk [OR (95% confidence interval) comparing extreme quintiles of weighted multi-SNP scores = 1.04 (0.94-1.16) for beta-carotene, 1.08 (0.98-1.20) for alpha-carotene, 1.04 (0.94-1.16) for beta-cryptoxanthin, 0.95 (0.87-1.05) for lutein/zeaxanthin, and 0.92 (0.83-1.02) for retinol]. Furthermore, no associations were observed when stratifying by estrogen receptor status, but power was limited. Conclusions: Our results do not support an association between SNPs associated with circulating carotenoid concentrations and breast cancer risk. Impact: Future studies will need additional genetic surrogates and/or sample sizes at least three times larger to contribute evidence of a causal link between carotenoids and breast cancer. (C) 2013 AACR.
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| 10. |
- Huesing, Anika, et al.
(author)
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Prediction of breast cancer risk by genetic risk factors, overall and by hormone receptor status
- 2012
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In: Journal of Medical Genetics. - : BMJ. - 0022-2593 .- 1468-6244. ; 49:9, s. 601-608
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Journal article (peer-reviewed)abstract
- Objective There is increasing interest in adding common genetic variants identified through genome wide association studies (GWAS) to breast cancer risk prediction models. First results from such models showed modest benefits in terms of risk discrimination. Heterogeneity of breast cancer as defined by hormone-receptor status has not been considered in this context. In this study we investigated the predictive capacity of 32 GWAS-detected common variants for breast cancer risk, alone and in combination with classical risk factors, and for tumours with different hormone receptor status. Material and methods Within the Breast and Prostate Cancer Cohort Consortium, we analysed 6009 invasive breast cancer cases and 7827 matched controls of European ancestry, with data on classical breast cancer risk factors and 32 common gene variants identified through GWAS. Discriminatory ability with respect to breast cancer of specific hormone receptor-status was assessed with the age adjusted and cohort-adjusted concordance statistic (AUROC(a)). Absolute risk scores were calculated with external reference data. Integrated discrimination improvement was used to measure improvements in risk prediction. Results We found a small but steady increase in discriminatory ability with increasing numbers of genetic variants included in the model (difference in AUROC(a) going from 2.7% to 4%). Discriminatory ability for all models varied strongly by hormone receptor status. Discussion and conclusions Adding information on common polymorphisms provides small but statistically significant improvements in the quality of breast cancer risk prediction models. We consistently observed better performance for receptor-positive cases, but the gain in discriminatory quality is not sufficient for clinical application.
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