Dataset Information

Common genetic variants in prostate cancer risk prediction--results from the NCI Breast and Prostate Cancer Cohort Consortium (BPC3).

ABSTRACT: 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.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.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).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.Although adding genetic risk markers improves model performance, the clinical utility of these genetic risk models is limited.

SUBMITTER: Lindstrom S

PROVIDER: S-EPMC3318963 | biostudies-literature | 2012 Mar

REPOSITORIES: biostudies-literature

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Common genetic variants in prostate cancer risk prediction--results from the NCI Breast and Prostate Cancer Cohort Consortium (BPC3).

Lindström Sara S Schumacher Fredrick R FR Cox David D Travis Ruth C RC Albanes Demetrius D Allen Naomi E NE Andriole Gerald G Berndt Sonja I SI Boeing Heiner H Bueno-de-Mesquita H Bas HB Crawford E David ED Diver W Ryan WR Gaziano J Michael JM Giles Graham G GG Giovannucci Edward E Gonzalez Carlos A CA Henderson Brian B Hunter David J DJ Johansson Mattias M Kolonel Laurence N LN Ma Jing J Le Marchand Loïc L Pala Valeria V Stampfer Meir M Stram Daniel O DO Thun Michael J MJ Tjonneland Anne A Trichopoulos Dimitrios D Virtamo Jarmo J Weinstein Stephanie J SJ Willett Walter C WC Yeager Meredith M Hayes Richard B RB Severi Gianluca G Haiman Christopher A CA Chanock Stephen J SJ Kraft Peter P

Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology 20120111 3

<h4>Background</h4>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, fa ...[more]

PMID: 22237985

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Project description:BackgroundScreening 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).ObjectiveTo examine the association of 47 established PCa risk single-nucleotide polymorphisms (SNPs) with PCSM.Design, setting, and participantsWe 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 analysisThe 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 limitationsAmong 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.ConclusionsEight 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 summaryIn 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.

Dataset Information

Common genetic variants in prostate cancer risk prediction--results from the NCI Breast and Prostate Cancer Cohort Consortium (BPC3).

Publications

Common genetic variants in prostate cancer risk prediction--results from the NCI Breast and Prostate Cancer Cohort Consortium (BPC3).

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