We conducted a genome-wide SNP association study on prostate cancer on over 23,000 Icelanders, followed by a replication study including over 15,500 individuals from Europe and the United States. Two newly identified variants were shown to be associated with prostate cancer: rs5945572 on Xp11.22 and rs721048 on 2p15 (odds ratios (OR) = 1.23 and 1.15; P = 3.9 × 10−13 and 7.7 × 10−9, respectively). The 2p15 variant shows a significantly stronger association with more aggressive, rather than less aggressive, forms of the disease.

Background

In spite of intensive efforts, understanding of the genetic aspects of familial prostate cancer remains largely incomplete. In a previous microsatellite-based linkage scan of 1233 prostate cancer (PC) families, we identified suggestive evidence for linkage (i.e. LOD≥1.86) at 5q12, 15q11, 17q21, 22q12, and two loci on 8p, with additional regions implicated in subsets of families defined by age at diagnosis, disease aggressiveness, or number of affected members.

Methods

In an attempt to replicate these findings and increase linkage resolution, we used the Illumina 6000 SNP linkage panel to perform a genome-wide linkage scan of an independent set of 762 multiplex PC families, collected by 11 ICPCG groups.

Results

Of the regions identified previously, modest evidence of replication was observed only on the short arm of chromosome 8, where HLOD scores of 1.63 and 3.60 were observed in the complete set of families and families with young average age at diagnosis, respectively. The most significant linkage signals found in the complete set of families were observed across a broad, 37 cM interval on 4q13-25, with LOD scores ranging from 2.02 to 2.62, increasing to 4.50 in families with older average age at diagnosis. In families with multiple cases presenting with more aggressive disease, LOD scores over 3.0 were observed at 8q24 in the vicinity of previously identified common PC risk variants, as well as MYC, an important gene in PC biology.

Conclusions

These results will be useful in prioritizing future susceptibility gene discovery efforts in this common cancer.

Purpose

High serum levels of macrophage inhibitory cytokine 1 (MIC-1) are strongly associated with metastatic prostate cancer, suggesting MIC-1 is a biomarker for prostate cancer prognosis.

Experimental Design

We conducted a prospective cohort study of 1,442 Swedish men with a pathologically verified diagnosis of prostate cancer between 2001 and 2003. Blood was drawn either pretreatment (n = 431) or posttreatment (n = 1,011) and cases were followed for a mean time of 4.9 years (range, 0.1–6.8 years).

Results

MIC-1 serum levels independently predicted poor cancer-specific survival with an almost 3-fold higher cancer death rate in patients with serum levels in the highest quartile compared with men with serum levels in the lowest quartile (adjusted hazard ratio, 2.98; 95% confidence interval, 1.82–4.68). Pretreatment MIC-1 levels revealed an even stronger association with disease outcome with an 8-fold higher death rate in the highest compared with the lowest category (adjusted hazard ratio, 7.98; 95% confidence interval, 1.73–36.86). Among patients considered to have localized disease, MIC-1 significantly increased the discriminative capacity between indolent and lethal prostate cancer compared with the established prognostic markers clinical stage, pathologic grade, and prostate-specific antigen level (P = 0.016). A sequence variant in the MIC-1 gene was associated with decreased MIC-1 serum levels (P = 0.002) and decreased prostate cancer mortality (P = 0.003), suggesting a causative role of MIC-1 in prostate cancer prognosis.

Conclusions

Serum MIC-1 concentration is a novel biomarker capable of predicting prostate cancer prognosis.

Multiple prostate cancer (PCa) risk-related loci have been discovered by genome-wide association studies (GWAS) based on case–control designs. However, GWAS findings may be confounded by population stratification if cases and controls are inadvertently drawn from different genetic backgrounds. In addition, since these loci were identified in cases with predominantly sporadic disease, little is known about their relationships with hereditary prostate cancer (HPC). The association between seventeen reported PCa susceptibility loci was evaluated with a family-based association test using 1,979 hereditary PCa families of European descent collected by members of the International Consortium for Prostate Cancer Genetics, with a total of 5,730 affected men. The risk alleles for 8 of the 17 loci were significantly over-transmitted from parents to affected offspring, including SNPs residing in 8q24 (regions 1, 2 and 3), 10q11, 11q13, 17q12 (region 1), 17q24 and Xp11. In subgroup analyses, three loci, at 8q24 (regions 1 and 2) plus 17q12, were significantly over-transmitted in hereditary PCa families with five or more affected members, while loci at 3p12, 8q24 (region 2), 11q13, 17q12 (region 1), 17q24 and Xp11 were significantly over-transmitted in HPC families with an average age of diagnosis at 65 years or less. Our results indicate that at least a subset of PCa risk-related loci identified by case–control GWAS are also associated with disease risk in HPC families.

Background

Percentage of free-to-total prostate-specific antigen (%fPSA) is an independent predictor of risk for prostate cancer among men with modestly elevated level of total PSA (tPSA) in blood. Physiological and pathological factors have been shown to influence the %fPSA value and diagnostic accuracy.

Materials/Methods

To evaluate genetic determinants of %fPSA, we conducted a genome-wide association study of serum %fPSA by genotyping 642,584 single nucleotide polymorphisms (SNPs) in 3192 men of European ancestry, each with a tPSA level of 2.5 to 10 ng/ml, that were recruited in the REduction by DUtasteride of Prostate Cancer Events study. Single nucleotide polymorphisms (SNPs) with P < 10-5 were further evaluated among the controls of a population-based case-control study in Sweden (2899 prostate cancer cases and 1722 male controls), including 464 controls having tPSA levels of 2.5 to 10 ng/ml.

Results

We identified two loci that were associated with %fPSA at a genome-wide significance level (P <5 x 10-8). The first associated SNP was rs3213764 (P = 6.45 x 10-10), a nonsynonymous variant (K530R) in the ATF7IP gene at 12p13. This variant was also nominally associated with tPSA (P = .015). The second locus was rs1354774 (P = 1.25 x 10-12), near KLK2 at 19q13, which was not associated with tPSA levels, and is separate from the rs17632542 locus at KLK3 that was previously associated with tPSA levels and prostate cancer risk. Neither rs3213764 nor rs1354774 was associated with prostate cancer risk or aggressiveness.

Conclusions

These findings demonstrate that genetic variants at ATF7IP and KLK2 contribute to the variance of %fPSA.

Prostate cancer has a strong familial component but uncovering the molecular basis for inherited susceptibility for this disease has been challenging. Recently, a rare, recurrent mutation (G84E) in HOXB13 was reported to be associated with prostate cancer risk. Confirmation and characterization of this finding is necessary to potentially translate this information to the clinic. To examine this finding in a large international sample of prostate cancer families, we genotyped this mutation and 14 other SNPs in or flanking HOXB13 in 2,443 prostate cancer families recruited by the International Consortium for Prostate Cancer Genetics (ICPCG). At least one mutation carrier was found in 112 prostate cancer families (4.6 %), all of European descent. Within carrier families, the G84E mutation was more common in men with a diagnosis of prostate cancer (194 of 382, 51 %) than those without (42 of 137, 30 %), P = 9.9 × 10−8 [odds ratio 4.42 (95 % confidence interval 2.56–7.64)]. A family-based association test found G84E to be significantly over-transmitted from parents to affected offspring (P = 6.5 × 10−6). Analysis of markers flanking the G84E mutation indicates that it resides in the same haplotype in 95 % of carriers, consistent with a founder effect. Clinical characteristics of cancers in mutation carriers included features of high-risk disease. These findings demonstrate that the HOXB13 G84E mutation is present in ~5 % of prostate cancer families, predominantly of European descent, and confirm its association with prostate cancer risk. While future studies are needed to more fully define the clinical utility of this observation, this allele and others like it could form the basis for early, targeted screening of men at elevated risk for this common, clinically heterogeneous cancer.

Electronic supplementary material

The online version of this article (doi:10.1007/s00439-012-1229-4) contains supplementary material, which is available to authorized users.

Prostate cancer (PrCa) is the most common non-skin cancer diagnosed among males in developed countries and the second leading cause of cancer mortality, yet little is known regarding its etiology and factors that influence clinical outcome. Genome-wide association studies (GWAS) of PrCa have identified at least 30 distinct loci associated with small differences in risk. We conducted a GWAS in 2782 advanced PrCa cases (Gleason grade ≥ 8 or tumor stage C/D) and 4458 controls with 571 243 single nucleotide polymorphisms (SNPs). Based on in silico replication of 4679 SNPs (Stage 1, P < 0.02) in two published GWAS with 7358 PrCa cases and 6732 controls, we identified a new susceptibility locus associated with overall PrCa risk at 2q37.3 (rs2292884, P= 4.3 × 10−8). We also confirmed a locus suggested by an earlier GWAS at 12q13 (rs902774, P= 8.6 × 10−9). The estimated per-allele odds ratios for these loci (1.14 for rs2292884 and 1.17 for rs902774) did not differ between advanced and non-advanced PrCa (case-only test for heterogeneity P= 0.72 and P= 0.61, respectively). Further studies will be needed to assess whether these or other loci are differentially associated with PrCa subtypes.

Background

Prostate cancer is the second leading cause of cancer-related deaths in men, accounting for over 30,000 deaths annually. The purpose of this study was to test whether variation in selected candidate genes in biological pathways of interest for prostate cancer progression could help distinguish patients at higher risk for fatal prostate cancer.

Methods

In this hypothesis-driven study, we genotyped 937 single nucleotide polymorphisms (SNPs) in 156 candidate genes in a population-based cohort of 1,309 prostate cancer patients. We identified 22 top-ranking SNPs (P ≤0.01, FDR ≤0.70) associated with prostate cancer-specific mortality (PCSM). A subsequent validation study was completed in an independent population-based cohort of 2,875 prostate cancer patients.

Results

Five SNPs were validated (P ≤0.05) as being significantly associated with PCSM, one each in the LEPR, CRY1, RNASEL, IL4, and ARVCF genes. Compared to patients with 0–2 of the at-risk genotypes those with 4–5 at-risk genotypes had a 50% (95% CI, 1.2–1.9) higher risk of PCSM and risk increased with the number of at-risk genotypes carried (Ptrend = 0.001), adjusting for clinicopathological factors known to influence prognosis.

Conclusion

Five genetic markers were validated to be associated with lethal prostate cancer.

Impact

This is the first population-based study to demonstrate that germline genetic variants provide prognostic information for prostate cancer-specific survival. The clinical utility of this five-SNP panel to stratify patients at higher risk for adverse outcomes should be evaluated.

We report a genome-wide association study in 10,286 cases and 9,135 controls of European ancestry, in the Cancer Genetic Markers of Susceptibility (CGEMS) initiative, identifying a new association with prostate cancer risk on chromosome 8q24 (rs620861, p=1.3×10-10, heterozygote OR = 1.17, 95% CI 1.10 – 1.24; homozygote OR = 1.33; 95% CI 1.21 – 1.45). This defines a new prostate locus on 8q24, Region 4, previously associated with breast cancer.

Previous genome-wide association studies have identified two independent variants in HNF1B as susceptibility loci for prostate cancer risk. To fine-map common genetic variation in this region, we genotyped 79 single nucleotide polymorphisms (SNPs) in the 17q12 region harboring HNF1B in 10 272 prostate cancer cases and 9123 controls of European ancestry from 10 case–control studies as part of the Cancer Genetic Markers of Susceptibility (CGEMS) initiative. Ten SNPs were significantly related to prostate cancer risk at a genome-wide significance level of P < 5 × 10−8 with the most significant association with rs4430796 (P = 1.62 × 10−24). However, risk within this first locus was not entirely explained by rs4430796. Although modestly correlated (r2= 0.64), rs7405696 was also associated with risk (P = 9.35 × 10−23) even after adjustment for rs4430769 (P = 0.007). As expected, rs11649743 was related to prostate cancer risk (P = 3.54 × 10−8); however, the association within this second locus was stronger for rs4794758 (P = 4.95 × 10−10), which explained all of the risk observed with rs11649743 when both SNPs were included in the same model (P = 0.32 for rs11649743; P = 0.002 for rs4794758). Sequential conditional analyses indicated that five SNPs (rs4430796, rs7405696, rs4794758, rs1016990 and rs3094509) together comprise the best model for risk in this region. This study demonstrates a complex relationship between variants in the HNF1B region and prostate cancer risk. Further studies are needed to investigate the biological basis of the association of variants in 17q12 with prostate cancer.

Genome-wide association studies have identified prostate cancer susceptibility alleles on chromosome 11q13. As part of the Cancer Genetic Markers of Susceptibility (CGEMS) Initiative, the region flanking the most significant marker, rs10896449, was fine mapped in 10 272 cases and 9123 controls of European origin (10 studies) using 120 common single nucleotide polymorphisms (SNPs) selected by a two-staged tagging strategy using HapMap SNPs. Single-locus analysis identified 18 SNPs below genome-wide significance (P< 10−8) with rs10896449 the most significant (P= 7.94 × 10−19). Multi-locus models that included significant SNPs sequentially identified a second association at rs12793759 [odds ratio (OR) = 1.14, P= 4.76 × 10−5, adjusted P= 0.004] that is independent of rs10896449 and remained significant after adjustment for multiple testing within the region. rs10896438, a proxy of previously reported rs12418451 (r2= 0.96), independent of both rs10896449 and rs12793759 was detected (OR = 1.07, P= 5.92 × 10−3, adjusted P= 0.054). Our observation of a recombination hotspot that separates rs10896438 from rs10896449 and rs12793759, and low linkage disequilibrium (rs10896449–rs12793759, r2= 0.17; rs10896449–rs10896438, r2= 0.10; rs12793759–rs10896438, r2= 0.12) corroborate our finding of three independent signals. By analysis of tagged SNPs across ∼123 kb using next generation sequencing of 63 controls of European origin, 1000 Genome and HapMap data, we observed multiple surrogates for the three independent signals marked by rs10896449 (n= 31), rs10896438 (n= 24) and rs12793759 (n= 8). Our results indicate that a complex architecture underlying the common variants contributing to prostate cancer risk at 11q13. We estimate that at least 63 common variants should be considered in future studies designed to investigate the biological basis of the multiple association signals.

The genetic determinants for aggressiveness of prostate cancer (PCa) are poorly understood. Copy-number variations (CNVs) are one of the major sources for genetic diversity and critically modulate cellular biology and human diseases. We hypothesized that CNVs may be associated with PCa aggressiveness. To test this hypothesis, we conducted a genome-wide common CNVs analysis in 448 aggressive and 500 nonaggressive PCa cases recruited from Johns Hopkins Hospital (JHH1) using Affymetrix 6.0 arrays. Suggestive associations were further confirmed using single-nucleotide polymorphisms (SNPs) that tagged the CNVs of interest in an additional 2895 aggressive and 3094 nonaggressive cases, including those from the remaining case subjects of the JHH study (JHH2), the NCI Cancer Genetic Markers of Susceptibility (CGEMS) Study, and the CAncer of the Prostate in Sweden (CAPS) Study. We found that CNP2454, a 32.3 kb deletion polymorphism at 20p13, was significantly associated with aggressiveness of PCa in JHH1 [odds ratio (OR) = 1.30, 95% confidence interval (CI): 1.01–1.68; P = 0.045]. The best-tagging SNP for CNP2454, rs2209313, was used to confirm this finding in both JHH1 (P = 0.045) and all confirmation study populations combined (P = 1.77 × 10−3). Pooled analysis using all 3353 aggressive and 3584 nonaggressive cases showed the T allele of rs2209313 was significantly associated with an increased risk of aggressive PCa (OR = 1.17, 95% CI: 1.07–1.27; P = 2.75 × 10−4). Our results indicate that genetic variations at 20p13 may be responsible for the progression of PCa.

Recent genome-wide association studies have been successful in identifying common sequence variants associated with prostate cancer risk; however, their importance in prostate cancer prognosis remains unknown. To assess confirmed prostate cancer susceptibility variants with prostate cancer prognosis, we genotyped 16 established susceptibility variants in a Swedish cohort of 2,875 prostate cancer cases, ascertained between 2001 and 2003, with complete follow-up regarding vital status through January 2008. Cox regression models, adjusted for age, clinical stage, pathologic grade, nodal or distant metastases, and diagnostic serum levels of prostate-specific antigen level, were used to assess association between risk variants and prostate cancer–specific survival. During follow-up, 626 men died, and of those, 440 had prostate cancer classified as their underlying cause of death. We found no association between any of the explored sequence variants and prostate cancer–specific mortality, either in exploring individual variants or in assessing the cumulative effect of all variants. We conclude that hitherto established prostate cancer susceptibility variants are not associated with the lethal potential of prostate cancer.

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 SNPs 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=3.4×10−14. 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.

BACKGROUND

Prostate cancer (PCa) risk-associated single nucleotide polymorphisms (SNPs) are continuously being discovered. Their ability to identify men at high risk and the impact of increasing numbers of SNPs on predictive performance are not well understood.

METHODS

Absolute risk for PCa was estimated in a population-based case-control study in Sweden (2,899 cases and 1,722 controls) using family history and three sets of sequentially discovered PCa risk-associated SNPs. Their performance in predicting PCa was assessed by positive predictive values (PPV) and sensitivity.

RESULTS

SNPs and family history were able to differentiate individual risk for PCa and identify men at higher risk; ~18% and ~8% of men in the study had 20-year (55–74 years) absolute risks that were two-fold (0.24) or three-fold (0.36) greater than the population median risk (0.12), respectively. When predictive performances were compared at absolute risk cutoffs of 0.12, 0.24 or 0.36, PPV increased considerably (~20%, ~30% and ~37%, respectively) while sensitivity decreased considerably (~55%, ~20% and ~10%, respectively). In contrast, when increasing numbers of SNPs (5, 11 and 28 SNPs) were used in risk prediction, PPV approached a constant value while sensitivity increased steadily.

CONCLUSIONS

SNPs discovered to date are suitable for risk prediction while additional SNPs discovered in the future may identify more subjects at higher risk. Men identified as high-risk by SNP-based testing may be targeted for PCa screening or chemoprevention. The clinical impact on improving the effectiveness of these interventions can be and should be assessed.

In genome-wide association studies, inherited risk of glioma has been demonstrated for rare familial syndromes and with common variants from 3–5 chromosomal regions. To assess the degree of familial aggregation of glioma, the authors performed a pooled analysis of data from 2 large glioma case-control studies in the United States (MD Anderson Cancer Center, Houston, Texas (1994–2006) and University of California, San Francisco (1991–2004)) and from the Swedish Cancer Registry (1958–2006) to measure excess cases of cancer among first-degree relatives of glioma probands. This analysis included 20,377 probands with glioma and 52,714 first-degree relatives. No overall increase was found in the expected number of cancers among family members; however, there were 77% more gliomas than expected. There were also significantly more sarcoma and melanoma cases than expected, which is supported by evidence in the literature, whereas there were significantly fewer-than-expected cases of leukemia, non-Hodgkin lymphoma, and bladder, lung, pancreatic, prostate, and uterine cancers. This large pooled analysis provided sufficient numbers of related family members to examine the genetic mechanisms involved in the aggregation of glioma with other cancers in these families. However, misclassification due to unvalidated cancers among family members could account for the differences seen by study site.

A fine mapping study in the HNF1B gene at 17q12 among two study populations revealed a second prostate cancer locus, ~26 kb centromeric to the first known locus (rs4430796); these are separated by a recombination hotspot. A SNP in the second locus (rs11649743) was confirmed in five additional populations, and P=1.7×10−9 for an allelic test in the seven combined studies. The association at each SNP remains significant after adjusting for the other SNP.

Purpose

While PSA is the best biomarker for predicting prostate cancer, its predictive performance needs to be improved. Results from the Prostate Cancer Prevention Trial (PCPT) revealed the overall performance measured by the areas under curve (AUC) of the receiver operating characteristic (ROC) 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 SNPs 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 AUC was 0.65 (95% CI: 0.63–0.66), significantly improved over that of family history and age (0.61%, 95% CI: 0.59–0.62), P = 2.3 × 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 PCPT.

Prostate cancer is one of the most heritable cancers in men, and recent genome-wide association studies have revealed numerous genetic variants associated with disease. The risk variants identified using case-control designs that compared unaffected individuals with all types of patients with prostate cancer show little or no ability to discriminate between indolent and fatal forms of this disease. This suggests different genetic components are involved in the initiation as compared with the prognosis of prostate cancer. Future studies contrasting patients with more and less aggressive disease, and exploring association with disease progression and prognosis, should be more effective in detecting genetic risk factors for prostate cancer outcome.

We conducted dense linkage disequilibrium (LD) mapping of a series of 25 genes putatively involved in lipid metabolism in 1567 dementia cases [including 1270 with Alzheimer disease (AD)] and 2203 Swedish controls. Across a total of 448 tested genetic markers, the strongest evidence of association was as anticipated for APOE (rs429358 at P ∼ 10−72) followed by a previously reported association of ABCA1 (rs2230805 at P ∼ 10−8). In the present study, we report two additional markers near the SREBF1 locus on chromosome 17p that were also significant after multiple testing correction (best P = 3.1 × 10−6 for marker rs3183702). There was no convincing evidence of association for remaining genes, including candidates highlighted from recent genome-wide association studies of plasma lipids (CELSR2/PSRC1/SORT1, MLXIPL, PCSK9, GALNT2 and GCKR). The associated markers near SREBF1 reside in a large LD block, extending more than 400 kb across seven candidate genes. Secondary analyses of gene expression levels of candidates spanning the LD region together with an investigation of gene network context highlighted two possible susceptibility genes including ATPAF2 and TOM1L2. Several markers in strong LD (r2 > 0.7) with rs3183702 were found to be significantly associated with AD risk in recent genome-wide association studies with similar effect sizes, providing independent support of the current findings.

Polymorphisms associated with prostate cancer include those in three genes encoding major secretory products of the prostate: KLK2 (encoding kallikrein-related peptidase 2; hK2), KLK3 (encoding prostate-specific antigen; PSA), and MSMB (encoding beta-microseminoprotein). PSA and hK2, members of the kallikrein family, are elevated in serum of men with prostate cancer. In a comprehensive analysis which included sequencing of all coding, flanking, and 2kb of putative promoter regions of all 15 kallikrein (KLK) genes spanning ≈280 Kb on chromosome 19q, we identified novel SNPs and genotyped 104 SNPs in 1419 cancer cases and 736 controls in CAPS1, with independent replication in 1267 cases and 901 controls in CAPS2. This verified prior associations of SNPs in KLK2 and in MSMB (but not in KLK3) with prostate cancer. Twelve SNPs in KLK2 and KLK3 were associated with levels of PSA forms or hK2 in plasma of control subjects. Based on our comprehensive approach, this is likely to represent all common KLK variants associated with these phenotypes. A T allele at rs198977 in KLK2 associated with increased cancer risk and a striking decrease of hK2 levels in blood. We also found a strong interaction between rs198977 genotype and hK2 levels in blood in predicting cancer risk. Based on this strong association, we developed a model for predicting prostate cancer risk from standard biomarkers, rs198977 genotype, and rs198977 x hK2 interaction; this model had greater accuracy than did biomarkers alone (AUC 0.874 vs 0.866), providing proof in principle to clinical application for our findings.

Background

Genome-wide association studies (GWAS) have identified multiple genetic variants associated with susceptibility to prostate cancer (PrCa). In the two-stage Cancer Genetic Markers of Susceptibility (CGEMS) prostate cancer scan, a single-nucleotide polymorphism (SNP) rs10486567 located within intron 2 of JAZF1 gene on chromosome 7p15.2 showed a promising association with PrCa overall (p = 2.14×10−6) with a suggestion of stronger association with aggressive disease (p = 1.2×10−7).

Methods

In the third stage of GWAS, we genotyped 106 JAZF1 SNPs in 10,286 PrCa cases and 9,135 controls of European ancestry.

Results

The strongest association was observed with the initial marker, rs10486567, which now achieves genome-wide significance (p = 7.79×10−11, ORHET 1.19; 95%CI = 1.12 – 1.27 and ORHOM 1.37; 95%CI = 1.20 – 1.56). We did not confirm a previous suggestion of a stronger association of rs10486567 with aggressive disease (p = 1.60×10−4 for aggressive cancer, n=4,597; p = 3.25×10−8 for non-aggressive cancer, n=4,514). Based on a multi-locus model with adjustment for rs10486567, no additional independent signals were observed at chromosome 7p15.2. There was no association between PrCa risk and SNPs in JAZF1 previously associated with height (rs849140, p = 0.587), body stature (rs849141, tagged by rs849136, p = 0.171), risk of type 2 diabetes and systemic lupus erythematosus (rs864745, tagged by rs849142, p = 0.657).

Conclusions

rs10486567 remains the most significant marker for PrCa risk within JAZF1 in individuals of European ancestry.

Impact

Future studies should identify all variants in high LD with rs10486567 and evaluate their functional significance for PrCa.

Disease risk-associated single nucleotide polymorphisms (SNPs) identified from genome-wide association studies have the potential to be used for disease risk prediction. An important feature of these risk-associated SNPs is their weak individual effect but stronger cumulative effect on disease risk. Several approaches are commonly used to model the combined effect in risk prediction but their performance is unclear. We compared two methods to model the combined effect of 14 prostate cancer (PCa) risk-associated SNPs and family history for the estimation of absolute risk for PCa in a population-based case-control study in Sweden (2,899 cases and 1,722 controls). Method 1 weighs each risk allele equally using a simple method of counting the number of risk alleles while Method 2 weighs each risk SNP differently based on their respective Odds Ratios. We found considerable differences between the two methods. Absolute risk estimates from Method 1 were generally higher than that of Method 2, especially among men at higher risk. The difference in the overall discriminative performance, measured by area under the curve (AUC) of the receiver operating characteristic was small between Method 1 (0.614) and Method 2 (0.618), P = 0.20. However, the performance of these two methods in identifying high-risk individuals (two-fold or three-fold higher than average risk), measured by positive predictive values (PPV), was higher for Method 2 than Method 1. In conclusion, these results suggest that Method 2 is superior to Method 1 in estimating absolute risk if the purpose of risk prediction is to identify high-risk individuals.

Background

Genetic variation in two members of the Toll-like receptors family, TLR4 and the gene cluster TLR6-1-10, has been implicated in prostate cancer in several studies, but the associated alleles have not been consistent across reports.

Methods

We performed a pooled analysis combining genotype data from three case-control studies, CAPS, HPFS and PLCO, with data from 3,101 prostate cancer cases and 2,523 controls. We performed imputation to obtain dense coverage of the genes and comparable genotype data for all cohorts. In total, 58 SNPs in TLR4 and 96 SNPs in TLR6-1-10 were genotyped or imputed and analyzed in the entire dataset. We performed cohort-specific analysis as well as meta-analysis and pooled analysis. We also evaluated whether the analyses differed by age or disease severity.

Results

We observed no overall association between genetic variation at the TLR4 and TLR6-1-10 loci and risk of prostate cancer.

Conclusions

Common germline genetic variation in TLR4 and TLR6-1-10 does not appear to have a strong association with risk of prostate cancer.