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Sökning: WFRF:(Willett Walter) > (2010-2014) > Stram Daniel O

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1.
  • Cao, Yin, et al. (författare)
  • Insulin-like growth factor pathway genetic polymorphisms, circulating IGF1 and IGFBP3, and prostate cancer survival
  • 2014
  • Ingår i: Journal of the National Cancer Institute. - : Oxford University Press. - 0027-8874 .- 1460-2105. ; 106:5
  • Tidskriftsartikel (refereegranskat)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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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.
  • 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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4.
  • Lindstroem, Sara, et al. (författare)
  • Common genetic variants in prostate cancer risk prediction-results from the NCI breast and prostate cancer cohort consortium (BPC3)
  • 2012
  • Ingår i: Cancer Epidemiology, Biomarkers and Prevention. - 1055-9965 .- 1538-7755. ; 21:3, s. 437-444
  • Tidskriftsartikel (refereegranskat)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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5.
  • 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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