Prostate Cancer Risk Single Nucleotide Polymorphisms Research Articles

Identification of Candidate mRNA Isoforms for Prostate Cancer-Risk SNPs Utilizing Iso-eQTL and sQTL Methods.

Single nucleotide polymorphisms (SNPs) impacting the alternative splicing (AS) process (sQTLs) or isoform expression (iso-eQTL) are implicated as important cancer regulatory elements. To find the sQTL and iso-eQTL, we retrieved prostate cancer (PrCa) tissue RNA-seq and genotype data originating from 385 PrCa European patients from The Cancer Genome Atlas. We conducted RNA-seq analysis with isoform-based and splice event-based approaches. The MatrixEQTL was used to identify PrCa-associated sQTLs and iso-eQTLs. The overlap between sQTL and iso-eQTL with GWAS loci and those that are differentially expressed between cancer and normal tissue were identified. The cis-acting associations (FDR < 0.05) for PrCa-risk SNPs identified 42, 123, and 90 PrCa-associated cassette exons, intron retention, and mRNA isoforms belonging to 25, 95, and 83 genes, respectively; while assessment of trans-acting association (FDR < 0.05) yielded 59, 65, and 196 PrCa-associated cassette exons, intron retention and mRNA isoforms belonging to 35, 55, and 181 genes, respectively. The results suggest that functional PrCa-associated SNPs can play a role in PrCa genesis by making an important contribution to the dysregulation of AS and, consequently, impacting the expression of the mRNA isoforms.

The BARCODE1 Pilot: a feasibility study of using germline single nucleotide polymorphisms to target prostate cancer screening.

ObjectivesTo assess the feasibility and uptake of a community‐based prostate cancer (PCa) screening programme selecting men according to their genetic risk of PCa. To assess the uptake of PCa screening investigations by men invited for screening. The uptake of the pilot study would guide the opening of the larger BARCODE1 study recruiting 5000 men.Subjects and MethodsHealthy males aged 55–69 years were invited to participate via their general practitioners (GPs). Saliva samples were collected via mailed collection kits. After DNA extraction, genotyping was conducted using a study specific assay. Genetic risk was based on genotyping 130 germline PCa risk single nucleotide polymorphisms (SNPs). A polygenic risk score (PRS) was calculated for each participant using the sum of weighted alleles for 130 SNPs. Study participants with a PRS lying above the 90th centile value were invited for PCa screening by prostate magnetic resonance imaging (MRI) and biopsy.ResultsInvitation letters were sent to 1434 men. The overall study uptake was 26% (375/1436) and 87% of responders were eligible for study entry. DNA genotyping data were available for 297 men and 25 were invited for screening. After exclusions due to medical comorbidity/invitations declined, 18 of 25 men (72%) underwent MRI and biopsy of the prostate. There were seven diagnoses of PCa (38.9%). All cancers were low‐risk and were managed with active surveillance.ConclusionThe BARCODE1 Pilot has shown this community study in the UK to be feasible, with an overall uptake of 26%. The main BARCODE1 study is now open and will recruit 5000 men. The results of BARCODE1 will be important in defining the role of genetic profiling in targeted PCa population screening. Patient SummaryWhat is the paper about?Very few prostate cancer screening programmes currently exist anywhere in the world. Our pilot study investigated if men in the UK would find it acceptable to have a genetic test based on a saliva sample to examine their risk of prostate cancer development. This test would guide whether men are offered prostate cancer screening tests.What does it mean for patients?We found that the study design was acceptable: 26% of men invited to take part agreed to have the test. The majority of men who were found to have an increased genetic risk of prostate cancer underwent further tests offered (prostate MRI scan and biopsy). We have now expanded the study to enrol 5000 men. The BARCODE1 study will be important in examining whether this approach could be used for large‐scale population prostate cancer screening.

How Cancer Risk SNPs May Contribute to Prostate Cancer Disparities.

Disparities in cancer incidence, prevalence, burden, and outcome exist among specific population groups in the United States. Researchers have identified germline genetic risk single-nucleotide polymorphisms (SNP) that differ by ancestry and may contribute to some of these differences. In this issue of Cancer Research, Han and colleagues found the prostate cancer risk SNP rs4713266 is associated with increased risk of patients with African ancestry. The authors investigated the functional role of the risk SNP, finding that it alters activity of a NEDD9 enhancer and increases NEDD9 expression. The study provides epidemiologic and mechanistic insight into factors that may drive prostate cancer disparities.See related article by Han et al., p. 3766.

Genetics of prostate cancer and its utility in treatment and screening.

Prostate cancer heritability is attributed to a combination of rare, moderate to highly penetrant genetic variants as well as commonly occurring variants conferring modest risks [single nucleotide polymorphisms (SNPs)]. Some of the former type of variants (e.g., BRCA2 mutations) predispose particularly to aggressive prostate cancer and confer poorer prognoses compared to men who do not carry mutations. Molecularly targeted treatments such as PARP inhibitors have improved outcomes in men carrying somatic and/or germline DNA repair gene mutations. Ongoing clinical trials are exploring other molecular targeted approaches based on prostate cancer somatic alterations. Genome wide association studies have identified >250 loci that associate with prostate cancer risk. Multi-ancestry analyses have identified shared as well as population specific risk SNPs. Prostate cancer risk SNPs can be used to estimate a polygenic risk score (PRS) to determine an individual's genetic risk of prostate cancer. The odds ratio of prostate cancer development in men whose PRS lies in the top 1% of the risk profile ranges from 9 to 11. Ongoing studies are investigating the utility of a prostate cancer PRS to target population screening to those at highest risk. With the advent of personalized medicine and development of DNA sequencing technologies, access to clinical genetic testing is increasing, and oncology guidelines from bodies such as NCCN and ESMO have been updated to provide criteria for germline testing of "at risk" healthy men as well as those with prostate cancer. Both germline and somatic prostate cancer research have significantly evolved in the past decade and will lead to further development of precision medicine approaches to prostate cancer treatment as well as potentially developing precision population screening models.

Abstract 54: An miRNA transcriptome-wide association study of prostate cancer risk

Abstract Background: Large genome-wide association studies (GWAS) have identified hundreds of single-nucleotide polymorphisms (SNPs) associated with increased risk of prostate cancer (PRCA). The majority of these risk loci are intergenic and the underlying causal variants are presumed to confer regulatory effects on gene expression. While follow-up eQTL studies have begun to explore putative regulatory targets of PRCA risk SNPs, these have largely focused on protein-coding genes. Recent evidence demonstrates that pri-miRNA transcripts are susceptible to the same cis-acting regulatory effects as other long RNAs, and PRCA risk SNPs may confer systemic impacts on the prostate transcriptome through miRNA expression dysregulation. However, no miRNA transcriptome-wide association studies (TWAS) of PRCA risk have been conducted to date, and the role of miRNA dysregulation in PRCA risk is poorly understood. Methods: We performed a comprehensive miRNA TWAS of PRCA risk using small RNA sequencing and genome-wide genotyping data from N = 441 normal prostate tissue samples from Mayo Clinic along with N = 411 prostate adenocarcinoma (PRAD) tumor samples from the Cancer Genome Atlas (TCGA). Both miRNA expression datasets were uniformly processed separately using the CAP-miRSeq miRNA workflow and trimmed mean of M (TMM) normalization. Expressed mature miRNAs were identified as ≥ 5 reads in &amp;gt;25% of samples. PEER was used to remove known and latent factors on miRNA expression levels, and subsequent analyses were performed on residual values. Genetically regulated expression (GReX) prediction models were trained for all expressed miRNAs with evidence of cis-heritability (P&amp;lt;0.01) in the respective normal and tumor datasets using the FUSION TWAS software. TWAS for PRCA risk was performed with both sets of GReX models using single-SNP summary statistics from the recent PRACTICAL consortium PRCA case-control OncoArray GWAS meta-analysis. Significant TWAS associations were declared at a false discovery rate of 0.05. Results: A total of 615 and 571 distinct expressed miRNAs were identified in the normal and tumor tissue datasets, respectively (overlap: 480). Among these, 98 (16%) normal tissue miRNAs demonstrated significant cis-heritability (median cis-h2 = 0.09, range: 0.04-0.79) for GReX model training. Similar results were obtained from TCGA tumor samples, with 63 (11%) miRNA GReX models successfully trained (median cis-h2 = 0.11, range: 0.05-0.60). Using normal tissue GReX models, we identified three significant TWAS miRNA associations with PRCA risk: over-expression of mir-941 family miRNAs (PTWAS = 3.1E-04) and reduced expression of miR-3617-5p (PTWAS = 1.7E-04) and hsa-miR-16-2-3p (PTWAS = 9.1E-04). The TCGA tumor TWAS also identified a significant association with miR-941 overexpression (PTWAS = 9.7E-04). All associated miRNAs have previously reported oncogenic or tumor-suppressive associations in other cancer types. Conclusions: We identified significant associations with PRCA genetic risk and miRNA expression dysregulation using tumor and normal prostate tissue data. Future work will examine downstream regulatory effects of miRNA dysregulation as well as miRNA-mediated risk mechanisms via competing endogenous RNA relationships. Citation Format: Nicholas B. Larson, Shannon K. McDonnell, Zachary Fogarty, Stephen N. Thibodeau. An miRNA transcriptome-wide association study of prostate cancer risk [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 54.

Abstract 2566: Comprehensive analysis to identify functional basis of prostate cancer risk SNPs

Abstract Introduction: Genome-wide association studies (GWAS) have identified numerous common single nucleotide polymorphisms (SNPs) associated with the risk of developing prostate cancer. Many of these prostate cancer GWAS hits occur in intergenic regions, distant from any annotated gene. Little is yet known about how these SNPs function to alter an individual's risk of prostate cancer. Here we test the hypothesis that many of these SNPs, or SNPs with which they are correlated, alter regulatory regions and thus gene expression in the prostate. Materials and Methods: To test if prostate cancer risk SNPs are correlated with gene expression changes, we conducted expression quantitative trait locus (eQTL) association analysis. Using genome-wide high-density genotypes and gene expression data from 56 tumor and 58 adjacent normal prostate tissues we asked if any of the prostate cancer risk SNPs correlate with expression changes in nearby genes using linear regression, adjusting gene expression levels for principal components of ancestry and different batches. We also asked if individuals who have a higher genetic risk of prostate cancer based on the genotype of all of their risk SNPs show different gene expression patterns in the prostate than those at lower risk of prostate cancer. Results: We have identified several novel cis-eQTLs in prostate tissue for prostate cancer risk SNPs including rs1933488 with RGS17. We have also replicated several previously known cis-eQTLs, including those for IRX4, PPP1R14A, and FOXP4. Individuals at higher genetic risk of developing prostate cancer have altered expression of 37 genes (p&amp;lt;0.001) in their tumor tissue compared to individuals at lower genetic risk. Conclusions: These data demonstrate that several prostate cancer risk SNPs are associated with expression changes in nearby genes in both pathologically malignant and pathologically benign prostate tissue from patients who underwent radical prostatectomy. Additional genes, including HMOX1, CSGALNACT1, and WDR36 show altered expression in patients with different levels of genetic risk of prostate cancer. Citation Format: Mridu Middha, Xing Xu, Riina-Minna Vaananen, James Hayes, Pekka Taimen, Xiaoni Gao, Hans G. Lilja, Kim Pettersson, Robert J. Klein. Comprehensive analysis to identify functional basis of prostate cancer risk SNPs. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2566.

Expressional profiling of prostate cancer risk SNPs at 11q13.5 identifies DGAT2 as a new target gene.

A total of nine non-coding variants on 11q13.5 predispose men to prostate cancer (PrCa). rs200331695 within the EMSY intron is associated with aggressive PrCa and two high linkage disequilibrium (LD) groups of single-nucleotide polymorphisms (SNPs) in the intergenic region are associated with PrCa death. Here, the cis-effect of the SNPs on gene expression using expression quantitative trait loci analysis was investigated. The regulatory potential was screened in prostate tumors (n = 41) and in whole blood (n = 99). The results were validated in a second tumor set (n = 41), in lymphoblastoid cell lines (LCLs) (n = 38), and using the GTEx Portal. The effects of haplotypes were analyzed in the whole blood. The high LD SNPs (rs143975731, rs12277366, rs2155225, and rs2155222) were associated with DGAT2 expression in both tumors sets (screening P = 0.035-0.043; validation P = 0.005-0.018). The PrCa death-associated alleles decreased the expression by two-fold. rs200331695 decreased DGAT2 expression in LCLs (P = 0.006). The findings of SNPs regulating CAPN5 (P = 0.026-0.046) and AP001189.4 (P = 0.03-0.039) in the whole blood were not observed in LCLs, but the association with AP001189.4 expression was validated via the GTEx Portal (P = 8.7 × 10(-5) to 4.3 × 10(-4) ), which suggests that the high LD intergenic SNPs exert a tissue-dependent effect on the expression of two genes. No haplotypes including the risk SNPs at 11q13.5 were associated with gene expression and PrCa. The findings indicate the functionality of the PrCa death-predisposing SNPs rs143975731, rs12277366, rs2155225, and rs2155222 as DGAT2 regulators in prostate tumors. © 2016 Wiley Periodicals, Inc.

Known susceptibility SNPs for sporadic prostate cancer show a similar association with "hereditary" prostate cancer.

BackgroundMore than 70 single nucleotide polymorphisms (SNPs) have been reported to be associated with prostate cancer (PC) risk; these were mainly identified in the general population with predominantly sporadic PC (SPC). Previous studies have suggested similar associations between a selection of these SNPs and hereditary PC (HPC). Our aim was to evaluate the effect of all known PC risk SNPs and their discriminative value for SPC and HPC.MethodsSeventy‐four PC susceptibility SNPs (reported in literature up to June 2014) were genotyped in a population‐based series of 620 SPC patients, 312 HPC patients from the national Dutch registry and 1819 population‐based referents. Association analyses were performed using logistic regression, focusing on directional consistency of the odds ratios (ORs) with those in the original reports, that is, whether the OR was in the same direction as in the original report. Discriminative performance was evaluated by a genetic risk score used in logistic regression and receiver operating characteristic (ROC) curve analyses.ResultsDirectional consistency was seen for 62 SNPs in SPC and 64 SNPs in HPC, 56 of which overlapped. ORs were mostly higher for HPC with 22 ORs >1.25 versus 5 for SPC. Discriminative performance was better for HPC with an area under the ROC curve of 0.73 versus 0.64 for SPC.ConclusionsA large overlap was found for the associations between low‐penetrance susceptibility SNPs and SPC and HPC, suggesting a similarity in genetic etiology. This warrants a reconsideration of “HPC” and a restrictive policy toward prostate‐specific antigen testing in men with a positive family history. Genetic risk scores might be used for PC risk stratification on the population level. Prostate 75: 474–483, 2015 © 2014 The Authors. The Prostate published by Wiley Periodicals, Inc.

A genetic-based approach to personalized prostate cancer screening and treatment.

Recent advances in sequencing technologies have allowed for the identification of genetic variants within germline DNA that can explain a significant portion of the genetic underpinnings of prostate cancer. Despite evidence suggesting that these genetic variants can be used for improved risk stratification, they have not yet been routinely incorporated into routine clinical practice. This review highlights their potential utility in prostate cancer screening. There are now almost 100 genetic variants, called single nucleotide polymorphisms (SNPs) that have been recently found to be associated with the risk of developing prostate cancer. In addition, some of these prostate cancer risk SNPs have also been found to influence prostate specific antigen (PSA) expression levels and potentially aggressive disease. Incorporation of panels of prostate cancer risk SNPs into clinical practice offers potential to provide improvements in patient selection for prostate cancer screening; PSA interpretation (e.g. by correcting for the presence of SNPs that influence PSA expression levels; decision for biopsy (using prostate cancer risk SNPs); and possibly the decision for treatment. A proposed clinical algorithm incorporating these prostate cancer risk SNPs is discussed.

Transcriptional regulation and prostate cancer risk loci.

1554 Background: While genome-wide association studies (GWAS) have identified numerous loci at which common single nucleotide polymorphisms (SNPs) are clearly associated with the risk of developing prostate cancer, the mechanism by which these variants influence disease is not clear. Based on the observation that regions of the genome with marks of transcriptional regulatory elements harbor SNPs that are more likely to be under negative selective pressure, we hypothesized that many prostate cancer associated SNPs, or their correlated proxies in linkage disequilibrium, function by altering regulation of nearby genes through alteration of transcription factor binding sites. Two predictions of this hypothesis are that there will be an enrichment of prostate cancer risk SNPs or their proxies in regulatory elements in prostate tissue and that some of these SNPs will correlate with the expression levels of nearby genes. Methods: To test the first prediction, we compared the number of prostate cancer risk SNPs (or their proxies) that overlap with DNase hypersensitive sites in the LNCaP prostate cancer cell line with randomly selected SNPs matched for allele frequency, distance from nearby genes, and local gene density. To test the second prediction, we asked if any of the known prostate cancer risk SNPs are associated with mRNA expression levels of nearby genes. Results: We found a four-fold enrichment of real prostate cancer risk SNPs overlapping with DNase hypersensitive sites versus the random set (p=0.03) at an r2 threshold of 0.95. In both tumor and benign prostate tissue, we found that a recently identified prostate cancer risk SNP is associated with expression levels of IRX4, a transcription factor previously implicated only in cardiac development. Conclusions: These data support the hypothesis that many GWAS-identified risk SNPs alter transcriptional regulation of nearby genes.

Clinical implications of a prostate cancer risk SNP profile in two treatment cohorts.

e16000 Background: Prostate cancer (PCa) has a heritable risk and genome-wide association studies (GWAS) have so far identified 76 single nucleotide polymorphisms (SNPs) associated with PCa risk. Currently these SNPs have only been evaluated against overall PCa risk and several disease parameters. Their clinical utility remains undefined. We explore the potential prognostic role of the risk SNP profile in 2 PCa cohorts; Active Surveillance (AS) and androgen deprivation therapy (ADT). Methods: PCa patients at the Royal Marsden Hospital who consented for DNA analyses were eligible. 2 separate cohorts were identified; those undergoing AS and those receiving ADT. The risk SNPs were genotyped using Sequenom or Fluidigm platforms. The cumulative SNP risk scores for each patient were calculated by summing risk alleles for each loci using the weighted effect as estimated in previous studies (log-additive model). For the AS group, the risk scores were analysed against defined adverse outcomes in AS, including adverse histology on repeat biopsy and time to treatment, to determine their prognostic value. For the ADT group, the risk scores were assessed against time to relapse, defined by either biochemical relapse or evidence of progression on imaging. Results: In the AS group, 391 patients’ DNA were studied. 31% of those have since undergone treatment and 30% have histological upgrade on repeat biopsies. On univariate analysis, there was no significant relationship between the risk scores and biopsy upgrade or time to treatment (p&gt;0.05). When analysing differences in outcomes between the higher and lower risk groups (top 25% and lowest 25% of the genetic risk distribution), there was again no relationship (p&gt;0.05). In the ADT group, 567 patients’ DNA were studied. The mean duration of response was 30 months. No significant associations were found when risk scores were analysed as a continuous variable against time to relapse on ADT, or when analysing difference between the top and bottom 25% of the risk distribution (p&gt;0.05). Conclusions: PCa SNP risk scores have not been shown to be prognostic factors in either AS or ADT. This is the first study analysing the potential prognostic role of the latest GWAS risk SNPs in PCa treatment cohorts.

Clinical implications of family history of prostate cancer and genetic risk single nucleotide polymorphism (SNP) profiles in an active surveillance cohort

To explore the potential prognostic role of family history (FH) of prostate cancer and prostate cancer risk single nucleotide polymorphisms (SNPs) in patients undergoing active surveillance (AS) for prostate cancer. This is the first study to date, which has investigated the potential prognostic role of SNP profiles in an AS cohort FH data were collected from patients in the Royal Marsden Hospital AS study. In all, 39 prostate cancer-risk SNPs identified from published genome wide association studies (GWAS) were genotyped using the Sequenom Platform and TaqMan™ assays from available DNA. The cumulative genetic-risk scores for each patient were then calculated using the weighted effect estimated from previous GWAS (log-additive model). FH status and the genetic-risk scores were assessed against adverse outcomes in AS, time to treatment and adverse histology on repeat biopsy, using univariable and multivariable Cox regression models to address time to treatment; and binary logistic regression to address biopsy upgrade. Of 471 patients, 55 (13.6%) had adverse histology on repeat biopsies and 145 (30.8%) had deferred treatment. On univariate analysis, there was no significant relationship between FH of prostate cancer in any degree of relation, and adverse histology or time to treatment. For risk score analyses, 386 patients' DNA was studied; and there was also no relationship found between the calculated genetic risk scores and adverse histology or time to treatment (P = 0.573 and P = 0.965, respectively). The retrospective study design and the few events were the main limitation of the study. There is currently insufficient data to support the use of FH status or prostate cancer SNP profile risk scores as prognostic factors in AS and these should not be used to influence management decisions. As more genetic variants are discovered this may change and should be reassessed in multicentre AS cohorts.

A Genome-Wide Survey over the ChIP-On-Chip Identified Androgen Receptor-Binding Genomic Regions Identifies a Novel Prostate Cancer Susceptibility Locus at 12q13.13

The molecular mechanisms for the genome-wide association studies (GWAS)-identified prostate cancer (PCa) risk-associated single-nucleotide polymorphisms (SNP) remain largely unexplained. One recent finding that the PCa risk SNPs are enriched in genomic regions containing androgen receptor (AR)-binding sites has suggested altered AR signaling as a potentially important mechanism. To explore novel associations by leveraging this knowledge, we utilized a meta-analysis previously done over SNPs harbored in ChIP-on-chip identified AR-binding genomic regions using the GWAS data from the Johns Hopkins Hospital (JHH) and the Cancer Genetic Markers of Susceptibility (CGEMS) study, and subsequently evaluated the top associations in a third population from the CAncer of the Prostate in Sweden (CAPS) study. One SNP (rs4919743: G>A), located at the KRT8 locus at 12q13.13 which encodes a keratin protein (K8) long used as a prostate epithelial malignancy marker and implicated in the tumorigenesis of several cancer types, was identified to be associated with PCa risk. The frequency of its minor "A" allele was consistently higher in PCa cases than in controls in all three study populations, with a combined OR of 1.22 (95% CI: 1.13-1.32) and an overall P value of 4.50 × 10(-7) (Bonferroni corrected, P = 0.006). We have identified a novel genetic locus that is associated with PCa risk. This study illustrated the great potential of prior biological knowledge in facilitating the search for novel disease-associated genetic loci. This finding warrants further replication in other studies.

Genetic architecture of prostate cancer in the Ashkenazi Jewish population

Background:Recently, numerous prostate cancer risk loci have been identified, some of which show association in specific populations. No study has yet investigated whether these single nucleotide polymorphisms (SNPs) are associated with prostate cancer in the Ashkenazi Jewish (AJ) population.Methods:A total of 29 known prostate cancer risk SNPs were genotyped in 963 prostate cancer cases and 613 controls of AJ ancestry. These data were combined with data from 1241 additional Ashkenazi controls and tested for association with prostate cancer. Correction for multiple testing was performed using the false discovery rate procedure.Results:Ten of twenty-three SNPs that passed quality control procedures were associated with prostate cancer risk at a false discovery rate of 5%. Of these, nine were originally discovered in studies of individuals of European ancestry. Based on power calculations, the number of significant associations observed is not surprising.Conclusion:We see no convincing evidence that the genetic architecture of prostate cancer in the AJ population is substantively different from that observed in other populations of European ancestry.

In vivo exploration of the functional activity of the non-coding 8q24 prostate cancer risk locus

In vivo exploration of the functional activity of the non-coding 8q24 prostate cancer risk locus

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.