| 1. |
- Lindstroem, Sara, et al.
(författare)
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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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Ingår i: Cancer Epidemiology, Biomarkers and Prevention. - 1055-9965 .- 1538-7755. ; 21:3, s. 437-444
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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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| 2. |
- Lindstrom, Sara, et al.
(författare)
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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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Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 6:2
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Tidskriftsartikel (refereegranskat)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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| 3. |
- Schmit, Stephanie L, et al.
(författare)
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Novel Common Genetic Susceptibility Loci for Colorectal Cancer.
- 2019
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Ingår i: Journal of the National Cancer Institute. - : Oxford University Press (OUP). - 0027-8874 .- 1460-2105. ; 111:2, s. 146-157
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Tidskriftsartikel (refereegranskat)abstract
- Background: Previous genome-wide association studies (GWAS) have identified 42 loci (P < 5 × 10-8) associated with risk of colorectal cancer (CRC). Expanded consortium efforts facilitating the discovery of additional susceptibility loci may capture unexplained familial risk.Methods: We conducted a GWAS in European descent CRC cases and control subjects using a discovery-replication design, followed by examination of novel findings in a multiethnic sample (cumulative n = 163 315). In the discovery stage (36 948 case subjects/30 864 control subjects), we identified genetic variants with a minor allele frequency of 1% or greater associated with risk of CRC using logistic regression followed by a fixed-effects inverse variance weighted meta-analysis. All novel independent variants reaching genome-wide statistical significance (two-sided P < 5 × 10-8) were tested for replication in separate European ancestry samples (12 952 case subjects/48 383 control subjects). Next, we examined the generalizability of discovered variants in East Asians, African Americans, and Hispanics (12 085 case subjects/22 083 control subjects). Finally, we examined the contributions of novel risk variants to familial relative risk and examined the prediction capabilities of a polygenic risk score. All statistical tests were two-sided.Results: The discovery GWAS identified 11 variants associated with CRC at P < 5 × 10-8, of which nine (at 4q22.2/5p15.33/5p13.1/6p21.31/6p12.1/10q11.23/12q24.21/16q24.1/20q13.13) independently replicated at a P value of less than .05. Multiethnic follow-up supported the generalizability of discovery findings. These results demonstrated a 14.7% increase in familial relative risk explained by common risk alleles from 10.3% (95% confidence interval [CI] = 7.9% to 13.7%; known variants) to 11.9% (95% CI = 9.2% to 15.5%; known and novel variants). A polygenic risk score identified 4.3% of the population at an odds ratio for developing CRC of at least 2.0.Conclusions: This study provides insight into the architecture of common genetic variation contributing to CRC etiology and improves risk prediction for individualized screening.
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| 4. |
- Shui, Irene M., et al.
(författare)
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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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Ingår i: European Urology. - : Elsevier BV. - 0302-2838 .- 1873-7560. ; 65:6, s. 1069-1075
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Tidskriftsartikel (refereegranskat)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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| 5. |
- Tsilidis, Konstantinos K., et al.
(författare)
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Interactions Between Genome-wide Significant Genetic Variants and Circulating Concentrations of Insulin-like Growth Factor 1, Sex Hormones, and Binding Proteins in Relation to Prostate Cancer Risk in the National Cancer Institute Breast and Prostate Cancer Cohort Consortium
- 2012
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Ingår i: American Journal of Epidemiology. - : Oxford University Press (OUP). - 0002-9262 .- 1476-6256. ; 175:9, s. 926-935
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Tidskriftsartikel (refereegranskat)abstract
- Genome-wide association studies (GWAS) have identified many single nucleotide polymorphisms (SNPs) associated with prostate cancer risk. There is limited information on the mechanistic basis of these associations, particularly about whether they interact with circulating concentrations of growth factors and sex hormones, which may be important in prostate cancer etiology. Using conditional logistic regression, the authors compared per-allele odds ratios for prostate cancer for 39 GWAS-identified SNPs across thirds (tertile groups) of circulating concentrations of insulin-like growth factor 1 (IGF-1), insulin-like growth factor binding protein 3 (IGFBP-3), testosterone, androstenedione, androstanediol glucuronide, estradiol, and sex hormone-binding globulin (SHBG) for 3,043 cases and 3,478 controls in the Breast and Prostate Cancer Cohort Consortium. After allowing for multiple testing, none of the SNPs examined were significantly associated with growth factor or hormone concentrations, and the SNP-prostate cancer associations did not differ by these concentrations, although 4 interactions were marginally significant (MSMB-rs10993994 with androstenedione (uncorrected P = 0.008); CTBP2-rs4962416 with IGFBP-3 (uncorrected P = 0.003); 11q13.2-rs12418451 with IGF-1 (uncorrected P = 0.006); and 11q13.2-rs10896449 with SHBG (uncorrected P = 0.005)). The authors found no strong evidence that associations between GWAS-identified SNPs and prostate cancer are modified by circulating concentrations of IGF-1, sex hormones, or their major binding proteins.
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| 6. |
- Wang, Zhaoming, et al.
(författare)
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Imputation and subset-based association analysis across different cancer types identifies multiple independent risk loci in the TERT-CLPTM1L region on chromosome 5p15.33
- 2014
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Ingår i: Human Molecular Genetics. - : Oxford University Press (OUP). - 0964-6906 .- 1460-2083. ; 23:24, s. 6616-6633
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Tidskriftsartikel (refereegranskat)abstract
- Genome-wide association studies (GWAS) have mapped risk alleles for at least 10 distinct cancers to a small region of 63 000 bp on chromosome 5p15.33. This region harbors the TERT and CLPTM1L genes; the former encodes the catalytic subunit of telomerase reverse transcriptase and the latter may play a role in apoptosis. To investigate further the genetic architecture of common susceptibility alleles in this region, we conducted an agnostic subset-based meta-analysis (association analysis based on subsets) across six distinct cancers in 34 248 cases and 45 036 controls. Based on sequential conditional analysis, we identified as many as six independent risk loci marked by common single-nucleotide polymorphisms: five in the TERT gene (Region 1: rs7726159, P = 2.10 × 10(-39); Region 3: rs2853677, P = 3.30 × 10(-36) and PConditional = 2.36 × 10(-8); Region 4: rs2736098, P = 3.87 × 10(-12) and PConditional = 5.19 × 10(-6), Region 5: rs13172201, P = 0.041 and PConditional = 2.04 × 10(-6); and Region 6: rs10069690, P = 7.49 × 10(-15) and PConditional = 5.35 × 10(-7)) and one in the neighboring CLPTM1L gene (Region 2: rs451360; P = 1.90 × 10(-18) and PConditional = 7.06 × 10(-16)). Between three and five cancers mapped to each independent locus with both risk-enhancing and protective effects. Allele-specific effects on DNA methylation were seen for a subset of risk loci, indicating that methylation and subsequent effects on gene expression may contribute to the biology of risk variants on 5p15.33. Our results provide strong support for extensive pleiotropy across this region of 5p15.33, to an extent not previously observed in other cancer susceptibility loci.
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