Randomized trial finds that prostate cancer genetic risk score feedback targets prostate-specific antigen screening among at-risk men.

BACKGROUND: Prostate-specific antigen (PSA) screening may reduce death due to prostate cancer but leads to the overdiagnosis of many cases of indolent cancer. Targeted use of PSA screening may reduce overdiagnosis. Multimarker genomic testing shows promise for risk assessment and could be used to target PSA screening. METHODS: To test whether counseling based on the family history (FH) and counseling based on a genetic risk score (GRS) plus FH would differentially affect subsequent PSA screening at 3 months (primary outcome), a randomized trial of FH versus GRS plus FH was conducted with 700 whites aged 40 to 49 years without prior PSA screening. Secondary outcomes included anxiety, recall, physician discussion at 3 months, and PSA screening at 3 years. Pictographs versus numeric presentations of genetic risk were also evaluated. RESULTS: At 3 months, no significant differences were observed in the rates of PSA screening between the FH arm (2.1%) and the GRS-FH arm (4.5% with GRS-FH vs. 2.1% with FH: χ2 = 3.13, P = .077); however, PSA screening rates at 3 months significantly increased with given risk in the GRS-FH arm (P = .013). Similar results were observed for discussions with physicians at 3 months and PSA screening at 3 years. Average anxiety levels decreased after the individual cancer risk was provided (P = .0007), with no differences between groups. Visual presentation by pictographs did not significantly alter comprehension or anxiety. CONCLUSIONS: This is likely the first randomized trial of multimarker genomic testing to report genomic targeting of cancer screening. This study found little evidence of concern about excess anxiety or overuse/underuse of PSA screening when multimarker genetic risks were provided to patients. Cancer 2016;122:3564-3575. © 2016 American Cancer Society.

A novel germline mutation in HOXB13 is associated with prostate cancer risk in Chinese men.

BACKGROUND: A rare mutation G84E in HOXB13 was recently identified to be associated with prostate cancer (PCa) in Caucasians. The goal of this study is to test association between HOXB13 genetic variants and PCa risk in Chinese men. METHODS: All study subjects were part of the Chinese Consortium for Prostate Cancer Genetics (ChinaPCa). In the first stage, we screened for mutations by sequencing the HOXB13 coding region in 96 unrelated PCa patients. In stage 2, G84E and novel mutations found in stage 1 were genotyped in 671 PCa patients and 1,536 controls. In stage 3, mutation status in 751 additional PCa patients was imputed via haplotype. RESULTS: The G84E mutation was not detected in this study. However, a novel mutation, G135E, was identified among 96 patients in stage 1. It was also observed twice in 575 additional PCa patients but not in 1,536 control subjects of stage 2. The frequency of G135E was significantly different between cases and controls, with a P-value of 0.027, based on Fisher's exact test. Haplotype estimation showed that G135E mutation carriers shared a unique haplotype that was not observed in other subjects. In stage 3, two more PCa patients were predicted to carry the G135E mutation. CONCLUSIONS: We identified a novel rare mutation in the HOXB13 gene, G135E, which appears to be a founder mutation. This mutation is associated with increased PCa risk in Chinese men. Consistent with a previous report, our findings provide further evidence that rare mutations in HOXB13 contribute to PCa risk.

Fine mapping association study and functional analysis implicate a SNP in MSMB at 10q11 as a causal variant for prostate cancer risk.

A single nucleotide polymorphism (SNP) at 10q11 (rs10993994) in the 5' region of the MSMB gene was recently implicated in prostate cancer risk in two genome-wide association studies. To identify possible causal variants in the region, we genotyped 16 tagging SNPs and imputed 29 additional SNPs in approximately 65 kb genomic region at 10q11 in a Swedish population-based case-control study (CAncer of the Prostate in Sweden), including 2899 cases and 1722 controls. We found evidence for two independent loci, separated by a recombination hotspot, associated with prostate cancer risk. Among multiple significant SNPs at locus 1, the initial SNP rs10993994 was most significant. Importantly, using an MSMB promoter reporter assay, we showed that the risk allele of this SNP had only 13% of the promoter activity of the wild-type allele in a prostate cancer model, LNCaP cells. Curiously, the second, novel locus (locus 2) was within NCOA4 (also known as ARA70), which is known to enhance androgen receptor transcriptional activity in prostate cancer cells. However, its association was only weakly confirmed in one of the three additional study populations. The observations that rs10993994 is the strongest associated variant in the region and its risk allele has a major effect on the transcriptional activity of MSMB, a gene with previously described prostate cancer suppressor function, together suggest the T allele of rs10993994 as a potential causal variant at 10q11 that confers increased risk of prostate cancer.

Inherited genetic markers discovered to date are able to identify a significant number of men at considerably elevated risk for prostate cancer.

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 twofold (0.24) or threefold (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.

Cumulative association of five genetic variants with prostate cancer.

BACKGROUND: Single-nucleotide polymorphisms (SNPs) in five chromosomal regions--three at 8q24 and one each at 17q12 and 17q24.3--have been associated with prostate cancer. Each SNP has only a moderate association, but when SNPs are combined, the association may be stronger. METHODS: We evaluated 16 SNPs from five chromosomal regions in a Swedish population (2893 subjects with prostate cancer and 1781 control subjects) and assessed the individual and combined association of the SNPs with prostate cancer. RESULTS: Multiple SNPs in each of the five regions were associated with prostate cancer in single SNP analysis. When the most significant SNP from each of the five regions was selected and included in a multivariate analysis, each SNP remained significant after adjustment for other SNPs and family history. Together, the five SNPs and family history were estimated to account for 46% of the cases of prostate cancer in the Swedish men we studied. The five SNPs plus family history had a cumulative association with prostate cancer (P for trend, 3.93x10(-28)). In men who had any five or more of these factors associated with prostate cancer, the odds ratio for prostate cancer was 9.46 (P=1.29x10(-8)), as compared with men without any of the factors. The cumulative effect of these variants and family history was independent of serum levels of prostate-specific antigen at diagnosis. CONCLUSIONS: SNPs in five chromosomal regions plus a family history of prostate cancer have a cumulative and significant association with prostate cancer.

Genetic variants and family history predict prostate cancer similar to prostate-specific antigen.

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.

Association of prostate cancer risk variants with clinicopathologic characteristics of the disease.

PURPOSE: Fifteen independent genetic variants have been implicated in prostate cancer risk by recent genome-wide association studies. However, their association with clinicopathologic features of prostate cancer is uncertain. EXPERIMENTAL DESIGN: We systematically evaluated these 15 variants in 1,563 prostate cancer patients undergoing radical prostatectomy, taking advantage of the uniform tumor stage and grade information available for each of these cases. Associations of these variants with aggressiveness, pathologic Gleason scores, pathologic stage, age at diagnosis, or serum prostate-specific antigen (PSA) levels were tested. RESULTS: After adjusting for multiple testing, none of the single nucleotide polymorphisms was individually or cumulatively associated with aggressiveness or individual clinicopathologic variables of prostate cancer such as Gleason scores, pathologic stage, or age at diagnosis of prostate cancer. The reported risk allele (G) for single nucleotide polymorphism rs2735839 in the KLK3 gene at 19q13 was more frequent in less aggressive prostate cancer patients (0.89) than in more aggressive prostate cancer patients (0.86; nominal P = 0.03) or in controls (0.86; nominal P = 0.04). Considering that this allele was also significantly associated with higher serum PSA levels among controls (nominal P = 0.003), the observed trend of higher frequency of this risk allele between less and more aggressive prostate cancer, or between less aggressive and controls may be due to detection bias of PSA screening. CONCLUSIONS: Prostate cancer risk variants recently discovered from genome-wide case-control association studies are not associated with clinicopathologic variables in this population. Case-case studies are urgently needed to discover genetic variants that predict tumor aggressiveness.

Integration of somatic deletion analysis of prostate cancers and germline linkage analysis of prostate cancer families reveals two small consensus regions for prostate cancer genes at 8p.

The evidence for tumor suppressor genes at 8p is well supported by many somatic deletion studies and genetic linkage studies. However, it remains a challenge to pinpoint the tumor suppressor genes at 8p primarily because the implicated regions are broad. In this study, we attempted to narrow down the implicated regions by incorporating evidence from both somatic and germline studies. Using high-resolution Affymetrix arrays, we identified two small common deleted regions among 55 prostate tumors at 8p23.1 (9.8-11.5 Mb) and 8p21.3 (20.6-23.7 Mb). Interestingly, our fine mapping linkage analysis at 8p among 206 hereditary prostate cancer families also provided evidence for linkage at these two regions at 8p23.1 (5.8-11.2 Mb) and at 8p21.3 (19.6-23.9 Mb). More importantly, by combining the results from the somatic deletion analysis and genetic linkage analysis, we were able to further narrow the regions to approximately 1.4 Mb at 8p23.1 and approximately 3.1 Mb at 8p21.3. These smaller consensus regions may facilitate a more effective search for prostate cancer genes at 8p.

Deletion of a small consensus region at 6q15, including the MAP3K7 gene, is significantly associated with high-grade prostate cancers.

PURPOSE: Chromosome 6q14-21 is commonly deleted in prostate cancers, occurring in approximately 22% of all tumors and approximately 40% of metastatic tumors. However, candidate prostate tumor suppressor genes in this region have not been identified, in part due to the large and broad nature of the deleted region implicated in previous studies. EXPERIMENTAL DESIGN: We first used high-resolution Affymetrix single nucleotide polymorphism arrays to examine DNA from malignant and matched nonmalignant cells from 55 prostate cancer patients. We identified a small consensus region on 6q14-21 and evaluated the deletion status within the region among additional 40 tumors and normal pairs using quantitative PCR and fluorescence in situ hybridization. We finally tested the association between the deletion and Gleason score using the Fisher's exact test. RESULTS: Tumors with small, interstitial deletions at 6q14-21 defined an 817-kb consensus region that is affected in 20 of 21 tumors. The MAP3K7 gene is one of five genes located in this region. In total, MAP3K7 was deleted in 32% of 95 tumors. Importantly, deletion of MAP3K7 was highly associated with higher-grade disease, occurring in 61% of tumors with Gleason score >or=8 compared with only 22% of tumors with Gleason score

Interactions of sequence variants in interleukin-1 receptor-associated kinase4 and the toll-like receptor 6-1-10 gene cluster increase prostate cancer risk.

Chronic or recurrent inflammation has been suggested as a causal factor in several human malignancies, including prostate cancer. Genetic predisposition is also a strong risk factor in the development of prostate cancer. In particular, Toll-like receptors (TLR), especially the TLR6-1-10 gene cluster, are involved in prostate cancer development. Interleukin-1 receptor-associated kinases (IRAK) 1 and 4 are critical components in the TLR signaling pathway. In this large case-control study, we tested two hypotheses: (a) sequence variants in IRAK1 and IRAK4 are associated with prostate cancer risk and (b) sequence variants in IRAK1/4 and TLR1-6-10 interacts and confers a stronger risk to prostate cancer. We analyzed 11 single nucleotide polymorphisms (four in IRAK1 and seven in IRAK4) among 1,383 newly diagnosed prostate cancer patients and 780 population controls in Sweden. Although the single-nucleotide polymorphisms in IRAK1 and IRAK4 alone were not significantly associated with prostate cancer risk, one single-nucleotide polymorphism in IRAK4, when combined with the high-risk genotype at TLR6-1-10, conferred a significant excess risk of prostate cancer. In particular, men with the risk genotype at TLR6-1-10 and IRAK4-7987 CG/CC had an odds ratio of 9.68 (P = 0.03) when compared with men who had wild-type genotypes. Our findings suggest synergistic effects between sequence variants in IRAK4 and the TLR 6-1-10 gene cluster. Although this study was based on a priori hypothesis and was designed to address many common issues facing this type of study, our results need confirmation in even larger studies.

Sequence variants of toll-like receptor 4 are associated with prostate cancer risk: results from the CAncer Prostate in Sweden Study.

Inflammation has been implicated as an etiological factor in several human cancers. Growing evidence suggests that chronic inflammation may also play a role in the etiology of prostate cancer. Considering that genetic susceptibility is a major risk factor for this disease, we hypothesize that sequence variants in genes that regulate inflammation may modify individual susceptibility to prostate cancer. The lipopolysaccharide receptor Toll-like receptor 4 (TLR4) is a central player in the signaling pathways of the innate immune response to infection by Gram-negative bacteria and is an important candidate inflammatory gene. We performed a systematic genetic analysis of TLR4 sequence variants by evaluating eight single-nucleotide polymorphisms that span the entire gene among 1383 newly diagnosed prostate cancer patients and 780 age- and residence-matched controls in Sweden. We found an association between a sequence variant (11381G/C) in the 3'-untranslated region of the TLR4 gene and prostate cancer risk. The frequency of the variant genotypes (CG or CC) was significantly higher in the patients (24.1%) than in the controls (19.7%; P = 0.02). The frequency of risk genotypes among patients diagnosed before the age of 65 years was even higher (26.3%). Compared with men who had the wild-type genotype of this single-nucleotide polymorphism (GG), those with GC or CC genotypes had a 26% increased risk for prostate cancer (odds ratio, 1.26; 95% confidence interval, 1.01-1.57) and 39% increased risk increased risk for early onset prostate cancer (before age 65 years; odds ratio, 1.39; 95% confidence interval, 1.02-1.91). The risk attributable to this variant for prostate cancer in Sweden was estimated to be 4.9%. Although the biological mechanism of the observed association remains to be elucidated, our finding supports a role for a bacteria-associated response pathway, possibly acting via inflammation, in the development of prostate cancer.

The interaction of four genes in the inflammation pathway significantly predicts prostate cancer risk.

It is widely hypothesized that the interactions of multiple genes influence individual risk to prostate cancer. However, current efforts at identifying prostate cancer risk genes primarily rely on single-gene approaches. In an attempt to fill this gap, we carried out a study to explore the joint effect of multiple genes in the inflammation pathway on prostate cancer risk. We studied 20 genes in the Toll-like receptor signaling pathway as well as several cytokines. For each of these genes, we selected and genotyped haplotype-tagging single nucleotide polymorphisms (SNP) among 1,383 cases and 780 controls from the CAPS (CAncer Prostate in Sweden) study population. A total of 57 SNPs were included in the final analysis. A data mining method, multifactor dimensionality reduction, was used to explore the interaction effects of SNPs on prostate cancer risk. Interaction effects were assessed for all possible n SNP combinations, where n = 2, 3, or 4. For each n SNP combination, the model providing lowest prediction error among 100 cross-validations was chosen. The statistical significance levels of the best models in each n SNP combination were determined using permutation tests. A four-SNP interaction (one SNP each from IL-10, IL-1RN, TIRAP, and TLR5) had the lowest prediction error (43.28%, P = 0.019). Our ability to analyze a large number of SNPs in a large sample size is one of the first efforts in exploring the effect of high-order gene-gene interactions on prostate cancer risk, and this is an important contribution to this new and quickly evolving field.

Evidence for a general cancer susceptibility locus at 3p24 in families with hereditary prostate cancer.

To identify genes that generally increase the risk of cancer, we performed a systematic search throughout the genome in 188 families primarily ascertained for prostate cancer but which also included individuals with other cancers. We observed significant evidence for linkage between susceptibility to all cancers and markers at 3p24, with a peak HLOD of 3.08 (P=0.0002). Compared to families with less than three other cancers and prostate cancer only, evidence for linkage at this region was stronger among families with at least three other cancers. This is the first reported example of a genome-wide search for general cancer susceptibility genes among hereditary prostate cancer families.

African American prostate cancer survivors' treatment decision-making and quality of life.

OBJECTIVE: To examine African-American prostate cancer (PCa) survivors' involvement in treatment decision-making (TDM), and examine the association between TDM and quality of life (QOL), using secondary data. METHODS: African-American PCa survivors (181) were recruited from the North Carolina Central Cancer Registry. Participants completed a cross-sectional survey that asked about their chosen cancer treatment, TDM factors, and PCa-specific QOL (using the Expanded Prostate Cancer Index Composite--EPIC). Multivariate analysis of covariance was conducted to determine the association between TDM and QOL, controlling for confounders. RESULTS: Most men reported being active (44.2%) or collaborative (38.1%) in TDM, while 14.4% preferred a passive role. Adjusting for marital status, education and treatment, passive patients reported somewhat better QOL compared to active patients in the following QOL domains: urinary summary (p=0.04), urinary function (p=0.01), and urinary incontinence (p=0.03). CONCLUSION: Most African-American PCa survivors preferred to be, and were, actively or collaboratively involved in TDM. However, those who preferred a passive role reported better PCa-specific QOL for the urinary domain compared to others. PRACTICE IMPLICATIONS: It is important to assess patients' TDM preference. Patients' QOL may differ by their TDM role, such that active patients may be more bothered by treatment side effects than other patients.

Identification of new differentially methylated genes that have potential functional consequences in prostate cancer.

Many differentially methylated genes have been identified in prostate cancer (PCa), primarily using candidate gene-based assays. Recently, several global DNA methylation profiles have been reported in PCa, however, each of these has weaknesses in terms of ability to observe global DNA methylation alterations in PCa. We hypothesize that there remains unidentified aberrant DNA methylation in PCa, which may be identified using higher resolution assay methods. We used the newly developed Illumina HumanMethylation450 BeadChip in PCa (n = 19) and adjacent normal tissues (n = 4) and combined these with gene expression data for identifying new DNA methylation that may have functional consequences in PCa development and progression. We also confirmed our methylation results in an independent data set. Two aberrant DNA methylation genes were validated among an additional 56 PCa samples and 55 adjacent normal tissues. A total 28,735 CpG sites showed significant differences in DNA methylation (FDR adjusted P<0.05), defined as a mean methylation difference of at least 20% between PCa and normal samples. Furthermore, a total of 122 genes had more than one differentially methylated CpG site in their promoter region and a gene expression pattern that was inverse to the direction of change in DNA methylation (e.g. decreased expression with increased methylation, and vice-versa). Aberrant DNA methylation of two genes, AOX1 and SPON2, were confirmed via bisulfate sequencing, with most of the respective CpG sites showing significant differences between tumor samples and normal tissues. The AOX1 promoter region showed hypermethylation in 92.6% of 54 tested PCa samples in contrast to only three out of 53 tested normal tissues. This study used a new BeadChip combined with gene expression data in PCa to identify novel differentially methylated CpG sites located within genes. The newly identified differentially methylated genes may be used as biomarkers for PCa diagnosis.

Potential impact of adding genetic markers to clinical parameters in predicting prostate biopsy outcomes in men following an initial negative biopsy: findings from the REDUCE trial.

BACKGROUND: Several germline single nucleotide polymorphisms (SNPs) have been consistently associated with prostate cancer (PCa) risk. OBJECTIVE: To determine whether there is an improvement in PCa risk prediction by adding these SNPs to existing predictors of PCa. DESIGN, SETTING, AND PARTICIPANTS: Subjects included men in the placebo arm of the randomized Reduction by Dutasteride of Prostate Cancer Events (REDUCE) trial in whom germline DNA was available. All men had an initial negative prostate biopsy and underwent study-mandated biopsies at 2 yr and 4 yr. Predictive performance of baseline clinical parameters and/or a genetic score based on 33 established PCa risk-associated SNPs was evaluated. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Area under the receiver operating characteristic curves (AUC) were used to compare different models with different predictors. Net reclassification improvement (NRI) and decision curve analysis (DCA) were used to assess changes in risk prediction by adding genetic markers. RESULTS AND LIMITATIONS: Among 1654 men, genetic score was a significant predictor of positive biopsy, even after adjusting for known clinical variables and family history (p = 3.41 × 10(-8)). The AUC for the genetic score exceeded that of any other PCa predictor at 0.59. Adding the genetic score to the best clinical model improved the AUC from 0.62 to 0.66 (p<0.001), reclassified PCa risk in 33% of men (NRI: 0.10; p=0.002), resulted in higher net benefit from DCA, and decreased the number of biopsies needed to detect the same number of PCa instances. The benefit of adding the genetic score was greatest among men at intermediate risk (25th percentile to 75th percentile). Similar results were found for high-grade (Gleason score ≥ 7) PCa. A major limitation of this study was its focus on white patients only. CONCLUSIONS: Adding genetic markers to current clinical parameters may improve PCa risk prediction. The improvement is modest but may be helpful for better determining the need for repeat prostate biopsy. The clinical impact of these results requires further study.

Sequence variants at 22q13 are associated with prostate cancer risk.

To search for genetic variants that are associated with prostate cancer risk in the genome, we combined the data from our genome-wide association study (GWAS) in a population-based case-control study in Sweden with publicly available GWAS data from the Cancer Genetic Markers of Susceptibility (CGEMS) study. We limited the cases to those with aggressive disease in an attempt to identify risk variants that are associated with this most clinically relevant form of the disease. Among the most likely candidate single nucleotide polymorphisms (SNP) identified from the two GWAS, we sequentially confirmed one SNP at 22q13 in two independent study populations: the remaining subjects in Cancer of the Prostate in Sweden and a hospital-based case-control study at Johns Hopkins Hospital. Association of aggressive prostate cancer with the SNP at 22q13 was also observed in the publicly available data of four additional study populations from the second stage of the CGEMS study. In all seven study populations examined, the frequency of allele "C" of rs9623117 at 22q13 was consistently higher in aggressive cases than in controls. The combined allelic test was highly significant, with P = 5.0 x 10(-7). The odds ratio (OR) of allele C for aggressive prostate cancer was estimated to be 1.18 [95% confidence interval (95% CI), 1.11-1.26]. However, the SNP was also associated with nonaggressive prostate cancer, with an estimated OR of 1.11 (95% CI, 1.04-1.19; P = 0.004). The risk-associated variants are located within the genomic region of TNRC6B, a gene involved in miRNA-mediated mRNA degradation. Additional studies are warranted to further confirm the association.

Prostate cancer risk associated loci in African Americans.

Four genome-wide association studies, all in populations of European descent, have identified 20 independent single nucleotide polymorphisms (SNP) in 20 regions that are associated with prostate cancer risk. We evaluated these 20 SNPs in a combined African American (AA) study, with 868 prostate cancer patients and 878 control subjects. For 17 of these 20 SNPs, implicated risk-associated alleles were found to be more common in these AA cases than controls, significantly more than expected under the null hypothesis (P = 0.03). Two of these 17 SNPs, located at 3p12, and region 2 at 8q24, were significantly associated with prostate cancer risk (P < 0.05), and only SNP rs16901979 at region 2 of 8q24 remained significant after accounting for 20 tests. A multivariate analysis of additional SNPs across the broader 8q24 region revealed three independent prostate cancer risk-associated SNPs, including rs16901979, rs13254738, and rs10086908. The first two SNPs were approximately 20 kb apart and the last SNP, a novel finding from this study, was approximately 100 kb centromeric to the first two SNPs. These results suggest that a systematic evaluation of regions harboring known prostate cancer risk SNPs implicated in other races is an efficient approach to identify risk alleles for AA. However, studies with larger numbers of AA subjects are needed, and this will likely require a major collaborative effort to combine multiple AA study populations.

Two independent prostate cancer risk-associated Loci at 11q13.

Single nucleotide polymorphisms (SNP) at 11q13 were recently implicated in prostate cancer risk by two genome-wide association studies and were consistently replicated in multiple study populations. To explore prostate cancer association in the regions flanking these SNPs, we genotyped 31 tagging SNPs in a approximately 110 kb region at 11q13 in a Swedish case-control study (Cancer of the Prostate in Sweden), including 2,899 cases and 1,722 controls. We found evidence of prostate cancer association for the previously implicated SNPs including rs10896449, which we termed locus 1. In addition, multiple SNPs on the centromeric side of the region, including rs12418451, were also significantly associated with prostate cancer risk (termed locus 2). The two groups of SNPs were separated by a recombination hotspot. We then evaluated these two representative SNPs in an additional approximately 4,000 cases and approximately 3,000 controls from three study populations and confirmed both loci at 11q13. In the combined allelic test of all four populations, P = 4.0 x 10(-11) for rs10896449 at locus 1 and P = 1.2 x 10(-6) for rs12418451 at locus 2, and both remained significant after adjusting for the other locus and study population. The prostate cancer association at these two 11q13 loci was unlikely confounded by prostate-specific antigen (PSA) detection bias because neither SNP was associated with PSA levels in controls. Unlike locus 1, in which no known gene is located, several putative mRNAs are in close proximity to locus 2. Additional confirmation studies at locus 2 and functional studies for both loci are needed to advance our knowledge on the etiology of prostate cancer.

A support vector machine approach for detecting gene-gene interaction.

Although genetic factors play an important role in most human diseases, multiple genes or genes and environmental factors may influence individual risk. In order to understand the underlying biological mechanisms of complex diseases, it is important to understand the complex relationships that control the process. In this paper, we consider different perspectives, from each optimization, complexity analysis, and algorithmic design, which allows us to describe a reasonable and applicable computational framework for detecting gene-gene interactions. Accordingly, support vector machine and combinatorial optimization techniques (local search and genetic algorithm) were tailored to fit within this framework. Although the proposed approach is computationally expensive, our results indicate this is a promising tool for the identification and characterization of high order gene-gene and gene-environment interactions. We have demonstrated several advantages of this method, including the strong power for classification, less concern for overfitting, and the ability to handle unbalanced data and achieve more stable models. We would like to make the support vector machine and combinatorial optimization techniques more accessible to genetic epidemiologists, and to promote the use and extension of these powerful approaches.