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Sökning: WFRF:(Henderson Brian E.) > Thun Michael J

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1.
  • Canzian, Federico, et al. (författare)
  • 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
  • Ingår i: BMC cancer. - : Springer Science and Business Media LLC. - 1471-2407. ; 9, s. 257-
  • Tidskriftsartikel (refereegranskat)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.
  • Gu, Fangyi, et al. (författare)
  • Eighteen insulin-like growth factor pathway genes, circulating levels of IGF-I and its binding protein, and risk of prostate and breast cancer
  • 2010
  • Ingår i: Cancer Epidemiology, Biomarkers and Prevention. - : American Association for Cancer Research. - 1055-9965 .- 1538-7755. ; 19:11, s. 2877-2887
  • Tidskriftsartikel (refereegranskat)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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3.
  • Schumacher, Fredrick R., et al. (författare)
  • A comprehensive analysis of common IGF1, IGFBP1 and IGFBP3 genetic variation with prospective IGF-I and IGFBP-3 blood levels and prostate cancer risk among
  • 2010
  • Ingår i: Human Molecular Genetics. - : Oxford University Press (OUP). - 0964-6906 .- 1460-2083. ; 19:15, s. 3089-3101
  • Tidskriftsartikel (refereegranskat)abstract
    • The insulin-like growth factor (IGF) pathway has been implicated in prostate development and carcinogenesis. We conducted a comprehensive analysis, utilizing a resequencing and tagging single-nucleotide polymorphism (SNP) approach, between common genetic variation in the IGF1, IGF binding protein (BP) 1, and IGFBP3 genes with IGF-I and IGFBP-3 blood levels, and prostate cancer (PCa) risk, among Caucasians in the NCI Breast and Prostate Cancer Cohort Consortium. We genotyped 14 IGF1 SNPs and 16 IGFBP1/IGFBP3 SNPs to capture common [minor allele frequency (MAF) >= 5%] variation among Caucasians. For each SNP, we assessed the geometric mean difference in IGF blood levels (N = 5684) across genotypes and the association with PCa risk (6012 PCa cases/6641 controls). We present two-sided statistical tests and correct for multiple comparisons. A non-synonymous IGFBP3 SNP in exon 1, rs2854746 (Gly32Ala), was associated with IGFBP-3 blood levels (P-adj = 8.8 x 10(-43)) after adjusting for the previously established IGFBP3 promoter polymorphism A-202C (rs2854744); IGFBP-3 blood levels were 6.3% higher for each minor allele. For IGF1 SNP rs4764695, the risk estimates among heterozygotes was 1.01 (99% CI: 0.90-1.14) and 1.20 (99% CI: 1.06-1.37) for variant homozygotes with overall PCa risk. The corrected allelic P-value was 8.7 x 10(-3). IGF-I levels were significantly associated with PCa risk (P-trend = 0.02) with a 21% increase of PCa risk when compared with the highest quartile to the lowest quartile. We have identified SNPs significantly associated with IGFBP-3 blood levels, but none of these alter PCa risk; however, a novel IGF1 SNP, not associated with IGF-I blood levels, shows preliminary evidence for association with PCa risk among Caucasians.
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4.
  • Schumacher, Fredrick R., et al. (författare)
  • Genome-wide association study identifies new prostate cancer susceptibility loci
  • 2011
  • Ingår i: Human Molecular Genetics. - London : IRL Press. - 0964-6906 .- 1460-2083. ; 20:19, s. 3867-3875
  • Tidskriftsartikel (refereegranskat)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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5.
  • Campa, Daniele, et al. (författare)
  • Interactions Between Genetic Variants and Breast Cancer Risk Factors in the Breast and Prostate Cancer Cohort Consortium
  • 2011
  • Ingår i: Journal of the National Cancer Institute. - : Oxford University Press (OUP). - 0027-8874 .- 1460-2105. ; 103:16, s. 1252-1263
  • Tidskriftsartikel (refereegranskat)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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6.
  • Canzian, Federico, et al. (författare)
  • 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
  • Ingår i: Human Molecular Genetics. - : Oxford University Press (OUP). - 0964-6906 .- 1460-2083. ; 19:19, s. 3873-84
  • Tidskriftsartikel (refereegranskat)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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8.
  • Huesing, Anika, et al. (författare)
  • Prediction of breast cancer risk by genetic risk factors, overall and by hormone receptor status
  • 2012
  • Ingår i: Journal of Medical Genetics. - : BMJ. - 0022-2593 .- 1468-6244. ; 49:9, s. 601-608
  • Tidskriftsartikel (refereegranskat)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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9.
  • Joshi, Amit D., et al. (författare)
  • 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
  • Ingår i: American Journal of Epidemiology. - : Oxford University Press. - 0002-9262 .- 1476-6256. ; 180:10, s. 1018-1027
  • Tidskriftsartikel (refereegranskat)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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