| 1. |
- Sun, Jielin, et al.
(author)
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Evidence for two independent prostate cancer risk-associated loci in the HNF1B gene at 17q12
- 2008
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In: Nature Genetics. - London : Nature Publishing Group. - 1061-4036 .- 1546-1718. ; 40:10, s. 1153-1155
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Journal article (other academic/artistic)abstract
- We carried out a fine-mapping study in the HNF1B gene at 17q12 in two study populations and identified a second locus associated with prostate cancer risk, 26 kb centromeric to the first known locus (rs4430796); these loci are separated by a recombination hot spot. We confirmed the association with a SNP in the second locus (rs11649743) in five additional populations, with P = 1.7 10-9 for an allelic test of the seven studies combined. The association at each SNP remained significant after adjustment for the other SNP.
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| 2. |
- Wiklund, Fredrik, et al.
(author)
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Association of Reported Prostate Cancer Risk Alleles With PSA Levels Among Men Without a Diagnosis of Prostate Cancer
- 2009
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In: The Prostate. - : Wiley. - 0270-4137 .- 1097-0045. ; 69:4, s. 419-427
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Journal article (peer-reviewed)abstract
- BACKGROUND. Prostate specific antigen (PSA) is widely used for prostate cancer screening but its levels are influenced by many non cancer-related factors. The goal of the study is to estimate the effect of genetic variants on PSA levels. METHODS. We evaluated the association of SNPs that were reported to be associated with prostate cancer risk in recent genome-wide association studies with plasma PSA levels in a Swedish study population, including 1,722 control subjects without a diagnosis of prostate cancer. RESULTS. Of the 16 SNPs analyzed in control subjects, significant associations with PSA levels (P <= 0.05) were found for six SNPs. These six SNP's had a cumulative effect on PSA levels; the mean PSA levels in men were almost twofold increased across increasing quintile of number of PSA associated alleles, P-trend = 3.4 x 10(-14). In this Swedish study population risk allele frequencies were similar among T1c case patients (cancer detected by elevated PSA levels alone) as compared to T2 and above prostate cancer case patients. CONCLUSIONS. Results from this study may have two important clinical implications. The cumulative effect of six SNPs on PSA levels suggests genetic-specific PSA cutoff values may be used to improve the discriminatory performance of this test for prostate cancer; and the dual associations of these SNPs with PSA levels and prostate cancer risk raise a concern that some of reported prostate cancer risk-associated SNPs may be confounded by the prevalent use of PSA screening. Prostate 69: 419-427, 2009. (C) 2008 Wiley-Liss, Inc.
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| 3. |
- Zheng, S. Lilly, et al.
(author)
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Genetic variants and family history predict prostate cancer similar to prostate-specific antigen
- 2009
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In: Clinical Cancer Research. - 1078-0432 .- 1557-3265. ; 15:3, s. 1105-1111
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Journal article (peer-reviewed)abstract
- PURPOSE: Although prostate-specific antigen (PSA) is the best biomarker for predicting prostate cancer, its predictive performance needs to be improved. Results from the Prostate Cancer Prevention Trial revealed the overall performance measured by the areas under curve of the receiver operating characteristic at 0.68. The goal of the present study is to assess the ability of genetic variants as a PSA-independent method to predict prostate cancer risk. EXPERIMENTAL DESIGN: We systematically evaluated all prostate cancer risk variants that were identified from genome-wide association studies during the past year in a large population-based prostate cancer case-control study population in Sweden, including 2,893 prostate cancer patients and 1,781 men without prostate cancer. RESULTS: Twelve single nucleotide polymorphisms were independently associated with prostate cancer risk in this Swedish study population. Using a cutoff of any 11 risk alleles or family history, the sensitivity and specificity for predicting prostate cancer were 0.25 and 0.86, respectively. The overall predictive performance of prostate cancer using genetic variants, family history, and age, measured by areas under curve was 0.65 (95% confidence interval, 0.63-0.66), significantly improved over that of family history and age (0.61%; 95% confidence interval, 0.59-0.62; P = 2.3 x 10(-10)). CONCLUSION: The predictive performance for prostate cancer using genetic variants and family history is similar to that of PSA. The utility of genetic testing, alone and in combination with PSA levels, should be evaluated in large studies such as the European Randomized Study for Prostate Cancer trial and Prostate Cancer Prevention Trial.
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| 4. |
- Zheng, S. Lilly, et al.
(author)
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A comprehensive association study for genes in inflammation pathway provides support for their roles in prostate cancer risk in the CAPS study
- 2006
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In: The Prostate. - Wake Forest Univ, Bowman Gray Sch Med, Ctr Human Genom, Winston Salem, NC USA. Karolinska Inst, Dept Med Epidemiol & Biotat, Stockholm, Sweden. Orebro Univ Hosp, Dept Urol & Clin Med, Orebro, Sweden. Translat Genom Res Inst, Phoenix, AZ USA. Johns Hopkins Med Inst, Dept Urol, Baltimore, MD 21205 USA. : WILEY-LISS. - 0270-4137 .- 1097-0045. ; 66:14, s. 1556-1564
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Journal article (peer-reviewed)abstract
- BACKGROUND. Recently identified associations of prostate cancer risk with several genes involved in innate immunity support a role of inflammation in the etiology of prostate cancer. Considering inflammation is regulated by a complex system of gene products, we hypothesize sequence variants in many other genes of this pathway are associated with prostate cancer. METHODS. We evaluated 9,275 SNPs; in 1,086 genes of the inflammation pathway using a MegAlleleTM genotyping system among 200 familial cases and 200 unaffected controls selected from a large Swedish case-control population (CAPS). RESULTS. We found that significantly more than the expected numbers of SNPs were significant at a nominal P-value of 0.01, 0.05, and 0.1, providing overall support for our hypothesis. The excess was largest when using a more liberal nominal P-value (0.1); we observed 992 significant SNPs compared with the 854 significant SNPs expected by chance, and this difference was significant based on a permutation test (P = 0.0025). We also began the effort of differentiating true associated SNPs by selecting a small subset of significant SNPs (N = 26) and genotyped these in an independent sample of similar to 1,900 CAPS1 subjects. We were able to confirm 3 of these 26 SNPs. It is expected that many more true associated SNPs will be confirmed among the 992 significant SNPs identified in our pathway screen. CONCLUSIONS. Our study provides the first objective support for an association between prostate cancer and multiple modest-effect genes in inflammatory pathways.
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