| 1. |
- Haiman, Christopher A, et al.
(författare)
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Levels of Beta-Microseminoprotein in Blood and Risk of Prostate Cancer in Multiple Populations.
- 2012
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Ingår i: Journal of the National Cancer Institute. - : Oxford University Press (OUP). - 1460-2105 .- 0027-8874.
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundA common genetic variant (rs10993994) in the 5' region of the gene encoding β-microseminoprotein (MSP) is associated with circulating levels of MSP and prostate cancer risk. Whether MSP levels are predictive of prostate cancer risk has not been evaluated.MethodsWe investigated the prospective relationship between circulating plasma levels of MSP and prostate cancer risk in a nested case-control study of 1503 case subjects and 1503 control subjects among black, Latino, Japanese, Native Hawaiian, and white men from the Multiethnic Cohort study. We also examined the ability of MSP to serve as a biomarker for discriminating prostate cancer case subjects from control subjects. All statistical tests are two-sided.ResultsIn all racial and ethnic groups, men with lower MSP levels were at greater risk of developing prostate cancer (odds ratio = 1.02 per one unit decrease in MSP, P < .001 in the prostate-specific antigen [PSA]-adjusted analysis). Compared with men in the highest decile of MSP, the multivariable PSA-adjusted odds ratio was 3.64 (95% confidence interval = 2.41 to 5.49) for men in the lowest decile. The positive association with lower MSP levels was observed consistently across racial and ethnic populations, by disease stage and Gleason score, for men with both high and low levels of PSA and across all genotype classes of rs10993994. However, we did not detect strong evidence of MSP levels in improving prostate cancer prediction beyond that of PSA.ConclusionsRegardless of race and ethnicity or rs10993994 genotype, men with low blood levels of MSP have increased risk of prostate cancer.
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| 2. |
- Huesing, Anika, et al.
(författare)
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Prediction of breast cancer risk by genetic risk factors, overall and by hormone receptor status
- 2012
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Ingår i: Journal of Medical Genetics. - : BMJ. - 0022-2593 .- 1468-6244. ; 49:9, s. 601-608
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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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| 3. |
- 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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