Prostate Cancer Risk Variants Research Articles

Combined Effect of a Polygenic Risk Score and Rare Genetic Variants on Prostate Cancer Risk

Although prostate cancer is known to have a strong genetic basis and is influenced by both common and rare variants, the ability to investigate the combined effect of such genetic risk factors has been limited to date. We conducted an investigation of 81 094 men from the UK Biobank, including 3568 prostate cancer cases, to examine the combined effect of rare pathogenic/likely pathogenic/deleterious (P/LP/D) germline variants and common prostate cancer risk variants, measured using a polygenic risk score (PRS), on prostate cancer risk. The absolute risk of prostate cancer for HOXB13, BRCA2, ATM, and CHEK2 P/LP/D carriers ranged from 9% to 56%, and the absolute risk in noncarriers ranged from 2% to 31%, by age 85 yr, for men in the lowest and highest PRS decile, respectively. The high-penetrant HOXB13 G84E prostate cancer risk variant was most common in cases in the lowest PRS quintile (4.4%) and least common in cases in the highest PRS quintile (0.5%; p = 0.005), whereas there was no statistically significant difference in frequencies by PRS in controls. While rare and common variants strongly and distinctly influence prostate cancer onset, consideration of rare and common variants in conjunction will lead to more precise estimates of a man’s lifetime risk of prostate cancer. Patient summaryWe found that the risk of prostate cancer conveyed by rare variants could vary depending on an individual’s genetic profile of common risk variants. This implies that in order to comprehensively assess genetic risk of prostate cancer, it is important to consider both rare and common variants.

Validation of prostate cancer risk variants rs10993994 and rs7098889 by CRISPR/Cas9 mediated genome editing.

GWAS have identified numerous SNPs associated with prostate cancer risk. One such SNP is rs10993994. It is located in the β-microseminoprotein (MSMB) promoter region, mediates MSMB prostate secretion levels, and is linked to mRNA expression changes in both MSMB and the adjacent gene NCOA4. In addition, our previous work showed a second SNP, rs7098889, is in positive linkage disequilibrium with rs10993994 and associated with MSMB expression independent of rs10993994. Here, we generate a series of clones with single alleles removed by double guide RNA (gRNA) mediated CRISPR/Cas9 deletions, through which we demonstrate that each of these SNPs independently and greatly alters MSMB expression in an allele-specific manner. We further show that these SNPs have no substantial effect on the expression of NCOA4. These data demonstrate that a single SNP can have a large effect on gene expression and illustrate the importance of functional validation studies to deconvolute observed correlations. The method we have developed is generally applicable to test any SNP for which a relevant heterozygous cell line is available. AUTHOR SUMMARY: In pursuing the underlying biological mechanism of prostate cancer pathogenesis, scientists utilized the existence of common single nucleotide polymorphisms (SNPs) in the human genome as genetic markers to perform large scale genome wide association studies (GWAS) and have so far identified more than a hundred prostate cancer risk variants. Such variants provide an unbiased and systematic new venue to study the disease mechanism, and the next big challenge is to translate these genetic associations to the causal role of altered gene function in oncogenesis. The majority of these variants are waiting to be studied and lots of them may act in oncogenesis through gene expression regulation. To prove the concept, we took rs10993994 and its linked rs7098889 as an example and engineered single cell clones by allelic-specific CRISPR/Cas9 deletion to separate the effect of each allele. We observed that a single nucleotide difference would lead to surprisingly high level of MSMB gene expression change in a gene specific and cell-type specific manner. Our study strongly supports the notion that differential level of gene expression caused by risk variants and their associated genetic locus play a major role in oncogenesis and also highlights the importance of studying the function of MSMB encoded β-MSP in prostate cancer pathogenesis.

Evaluation of Polygenic Risk Scores for Prediction of Prostate Cancer in Korean Men.

AimsThe purpose of this study is to evaluate an aggregate influence of prostate cancer (PCa) susceptibility variants on the development of PCa in Korean men by using the polygenic risk score (PRS) approach.MethodsAn analysis of 1,001 cases of PCa and 2,641 controls was performed to: (i) identify potential PCa-related risk loci in Koreans and (ii) validate the cumulative association between these loci and PCa using the PRS. Subgroup analyses based on risk stratification were conducted to better characterize the potential correlation to key PCa-related clinical outcomes (e.g., Gleason score, prostate-specific antigen levels). The results were replicated using 514 cases of PCa and 548 controls from an independent cohort.ResultsGenome-wide association analysis from our discovery cohort revealed 11 candidate single-nucleotide polymorphisms (SNPs) associated with PCa showing statistical significance of p < 5.0 × 10–5. Seven variants were located at 8q24.21 (rs1016343, rs16901979, and rs13252298 in PRNCR1; rs4242384, rs7837688, and rs1447295 in CASC8; and rs1512268 in NKX3). Two variants located within HNF1B (rs7501939 and rs4430796) had a significant negative association with PCa risk [odds ratio (OR) = 0.717 and 0.747, p = 6.42 × 10–7 and 3.67 × 10–6, respectively]. Of the six independent SNPs that remained after linkage disequilibrium (LD) pruning, the top four SNPs best predicted PCa risk with an area under the receiver operating characteristic curve (AUC) of 0.637 (95% CI: 0.582–0.692). Those with top 25% polygenic risk had a 4.2-fold increased risk of developing PCa compared with those with low risk.ConclusionEleven PCa risk variants in Korean men were identified; PRSs of a subset of these variants could help predict PCa susceptibility.

Association study between genetic variants in retinol metabolism pathway genes and prostate cancer risk

BackgroundEvidence suggests that serum retinol level is associated with prostate cancer risk, but the association between genetic variants in the retinol metabolism pathway genes and prostate cancer risk remains unclarified.MethodsSingle‐nucleotide polymorphisms (SNPs) in 31 genes in the retinol metabolism pathway were genotyped to evaluate the association with prostate cancer risk in 4,662 cases and 3,114 controls from the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial. The gene expression analysis was evaluated using data from the Gene Expression Omnibus (GEO) datasets and the Cancer Genome Atlas (TCGA) database. Data from the Genotype‐Tissue Expression (GTEx) project dataset were utilized to perform the expression quantitative trait loci (eQTL) analysis.ResultsTwo SNPs were significantly associated with prostate cancer risk [rs1330286 in ALDH1A1: odds ratio (OR) = 0.88, 95% confidence interval (CI) = 0.83‐0.94, p = 2.45 × 10−4; rs4646653 in ALDH1A3: OR = 1.17, 95% CI =1.07‐1.27, p = 4.33 × 10−4]. Moreover, the mRNA level of ALDH1A3 was significantly higher in prostate cancer tissues than in normal tissues in both TCGA datasets and GEO datasets (p = 1.63 × 10−12 and p = 4.33 × 10−2, respectively). rs1330286 was an eQTL of ALDH1A1 (P = 2.90 × 10−3).ConclusionOur findings highlight that genetic variants in retinol metabolism pathway genes are associated with prostate cancer risk.

Abstract 3513: Genome-wide scan for novel prostate cancer susceptibility loci with clinical consequence utilizing increased genetic drift of the Finnish population

Abstract Background: Prostate cancer (PC) is the second most common cancer in men worldwide with a rising prevalence. However, only limited number of clinically actionable variants are known. The objective of this study is to identify novel PC susceptibility loci with potential clinical relevance utilizing the increased genetic drift and reduced selective pressure of the recently bottlenecked powerful resource of the Finnish population. Methods: We meta-analysed &amp;gt;185.000 germline single nucleotide polymorphisms (SNPs) in 2738 PC cases and 2401 controls of Finnish origin in the Collaborative Oncological Gene-Environment Study (COGS) using Illumina iSelect custom SNP genotyping platform. Results: Altogether 160 variants remain significant on GWAS level (p&amp;lt;5 × 10−8) in 18 different gene regions. Out of the 160 identified PC susceptibility hits 78 (49%) are novel variants not reported earlier in association with PC. PC associated signals are in close proximity to one another forming genetic hot-spots on chromosomes 8, 7, 11, 17 and 19. The strength of association varies for 101 PC risk variants (OR 1.24-1.86) and 59 protective SNPs (OR 0.59-0.80). The strongest risk gene is CASC8 (OR=1.86; p=1.214 × 10−11). The most significant signals were found at the 8p21.2 chromosomal region (p&amp;lt;7.6 × 10−16). Functional annotation identified a missense coding SNP at KLK3 gene to be a candidate causal variant. We showed evidence for association both with early-onset PC (OR 1.73; P=0.02), high serum PSA level at diagnosis (OR 1.36; P=0.024) and with aggressive PC (Gleason score ≥8; OR 1.44; P=0.02) at 17q21. Conclusion: The results facilitate risk stratification for screening, clinical studies, treatment choices and functional research of PC Citation Format: Csilla Sipeky, Teuvo L. Tammela, Anssi Auvinen, Johanna Schleutker. Genome-wide scan for novel prostate cancer susceptibility loci with clinical consequence utilizing increased genetic drift of the Finnish population [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 3513.

A Germline Variant at 8q24 Contributes to Familial Clustering of Prostate Cancer in Men of African Ancestry

Although men of African ancestry have a high risk of prostate cancer (PCa), no genes or mutations have been identified that contribute to familial clustering of PCa in this population. We investigated whether the African ancestry–specific PCa risk variant at 8q24, rs72725854, is enriched in men with a PCa family history in 9052 cases, 143 cases from high-risk families, and 8595 controls of African ancestry. We found the risk allele to be significantly associated with earlier age at diagnosis, more aggressive disease, and enriched in men with a PCa family history (32% of high-risk familial cases carried the variant vs 23% of cases without a family history and 12% of controls). For cases with two or more first-degree relatives with PCa who had at least one family member diagnosed at age <60 yr, the odds ratios for TA heterozygotes and TT homozygotes were 3.92 (95% confidence interval [CI] = 2.13–7.22) and 33.41 (95% CI = 10.86–102.84), respectively. Among men with a PCa family history, the absolute risk by age 60 yr reached 21% (95% CI = 17–25%) for TA heterozygotes and 38% (95% CI = 13–65%) for TT homozygotes. We estimate that in men of African ancestry, rs72725854 accounts for 32% of the total familial risk explained by all known PCa risk variants. Patient summaryWe found that rs72725854, an African ancestry–specific risk variant, is more common in men with a family history of prostate cancer and in those diagnosed with prostate cancer at younger ages. Men of African ancestry may benefit from the knowledge of their carrier status for this genetic risk variant to guide decisions about prostate cancer screening.

Pathogenic Variants in Cancer Predisposition Genes and Prostate Cancer Risk in Men of African Ancestry.

In studies of men of European ancestry, rare pathogenic variants in DNA repair pathway genes have been shown to be associated with risk of aggressive prostate cancer. The contribution of rare coding variation to prostate cancer risk in men of African ancestry has not been established. We sequenced a panel of 19 DNA repair and cancer predisposition genes in 2,453 African American and 1,151 Ugandan prostate cancer cases and controls. Rare variants were classified as pathogenic or putatively functionally disruptive and examined in association with prostate cancer risk and disease aggressiveness in gene and pathway-level association analyses. Pathogenic variants were found in 75 out of 2,098 cases (3.6%) and 31 out of 1,481 controls (2.1%) (OR=1.82, 95% CI=1.19 to 2.79, P=0.0044) with the association being stronger for more aggressive disease phenotypes (OR=3.10, 95% CI=1.54 to 6.23, P=0.0022). The highest risks for aggressive disease were observed with pathogenic variants in the ATM, BRCA2, PALB2 and NBN genes, with odds ratios ranging from ~4 to 15 in the combined study sample of African American and Ugandan men. Rare, non-pathogenic, non-synonymous variants did not have a major impact on risk of overall prostate cancer or disease aggressiveness. Rare pathogenic variants in DNA repair genes have appreciable effects on risk of aggressive prostate cancer in men of African ancestry. These findings have potential implications for panel testing and risk stratification in this high-risk population.

A novel computational OMICS and non-OMICS approach for identifying true pathogenic risk variants for Asian prostate cancer.

47 Background: Large-scale genome-wide association studies have established germline polygenic risk loci that underpin the susceptibility to prostate cancer (PCa). However, most trials conducted are in men of European ancestry with data missing for Asian male PCa. Here, we report on an in-house multidimensional bioinformatics pipeline that integrates OMICS and non-OMICS approaches in identifying true germline risk-variants for PCa in Asian men. Methods: We utilized a prospective cohort study of Asian men who were newly diagnosed with PCa. Whole exome sequencing (Illumina Hiseq, CA) of blood (100X) was performed. The OMICS-based approach entailed a stepwise screen for hallmarks of cancer-specific pathways. A genome-proteome network was then developed to filter for known pathogenic variants; this was followed by comparison against a large artificial database of aggregated germline variants (N = 95,000) with reported linkage to PCa susceptibility. Finally, mutations were filtered through a non-OMICS pipeline that entailed data synchronization with population-level statistics and clinical outcomes (recurrence and survival). Results: Preliminary analyses were based on 277 PCa cases; of which 50 were M1 cases. Screening using a non-combined unbiased approach yielded 36,157 germline variants. This contrast against our OMICS-based approach, which reduced the variant calls to 6,144 significantly associated mutations. Next, by focusing on pathway-specific genes related to hormonal regulation and known cancer hotspot mutations, we could further tighten our variant calls to 3,562 hormone-related variants (rs9269958 on HLA-DRB1) and 2,125 variants in known cancer genes, notably (rs8176320 on BRCA1/2, rs2555691 on LILRA2, rs8036934 on TP53BP1). Conclusions: Here, we show that application of an OMICS approach that combines pathway-driven analyses and an artificial dataset, along with population-level statistics and clinical relevance resulted in more robust annotation of germline variants that were associated with PCa.

Analysis of Over 140,000 European Descendants Identifies Genetically Predicted Blood Protein Biomarkers Associated with Prostate Cancer Risk.

Several blood protein biomarkers have been associated with prostate cancer risk. However, most studies assessed only a small number of biomarkers and/or included a small sample size. To identify novel protein biomarkers of prostate cancer risk, we studied 79,194 cases and 61,112 controls of European ancestry, included in the PRACTICAL/ELLIPSE consortia, using genetic instruments of protein quantitative trait loci for 1,478 plasma proteins. A total of 31 proteins were associated with prostate cancer risk including proteins encoded by GSTP1, whose methylation level was shown previously to be associated with prostate cancer risk, and MSMB, SPINT2, IGF2R, and CTSS, which were previously implicated as potential target genes of prostate cancer risk variants identified in genome-wide association studies. A total of 18 proteins inversely correlated and 13 positively correlated with prostate cancer risk. For 28 of the identified proteins, gene somatic changes of short indels, splice site, nonsense, or missense mutations were detected in patients with prostate cancer in The Cancer Genome Atlas. Pathway enrichment analysis showed that relevant genes were significantly enriched in cancer-related pathways. In conclusion, this study identifies 31 candidates of protein biomarkers for prostate cancer risk and provides new insights into the biology and genetics of prostate tumorigenesis. SIGNIFICANCE: Integration of genomics and proteomics data identifies biomarkers associated with prostate cancer risk.

Identification of Novel Susceptibility Loci and Genes for Prostate Cancer Risk: A Transcriptome-Wide Association Study in Over 140,000 European Descendants.

Genome-wide association study-identified prostate cancer risk variants explain only a relatively small fraction of its familial relative risk, and the genes responsible for many of these identified associations remain unknown. To discover novel prostate cancer genetic loci and possible causal genes at previously identified risk loci, we performed a transcriptome-wide association study in 79,194 cases and 61,112 controls of European ancestry. Using data from the Genotype-Tissue Expression Project, we established genetic models to predict gene expression across the transcriptome for both prostate models and cross-tissue models and evaluated model performance using two independent datasets. We identified significant associations for 137 genes at P < 2.61 × 10-6, a Bonferroni-corrected threshold, including nine genes that remained significant at P < 2.61 × 10-6 after adjusting for all known prostate cancer risk variants in nearby regions. Of the 128 remaining associated genes, 94 have not yet been reported as potential target genes at known loci. We silenced 14 genes and many showed a consistent effect on viability and colony-forming efficiency in three cell lines. Our study provides substantial new information to advance our understanding of prostate cancer genetics and biology. SIGNIFICANCE: This study identifies novel prostate cancer genetic loci and possible causal genes, advancing our understanding of the molecular mechanisms that drive prostate cancer.

Circadian genes and risk of prostate cancer: Findings from the EPICAP study.

Circadian rhythms regulate several physiological functions and genes controlling the circadian rhythm were found to regulate cell proliferation, cell cycle and apoptosis. Few studies have investigated the role of those circadian genes in prostate cancer occurrence. We aim to investigate the relationship between circadian genes polymorphisms and prostate cancer risk based on data from the EPICAP study, a population-based case-control study including 1,515 men (732 cases / 783 controls) with genotyped data. Odds Ratios (ORs) for association between prostate cancer and circadian gene variants were estimated for each of the 872 single nucleotide polymorphisms (SNPs) in 31 circadian clock genes. We also used a gene-based and pathway-based approach with a focus on the pathway including 9 core circadian genes. Separate analyses were conducted by prostate cancer aggressiveness. The core-circadian pathway (p = 0.0006) was significantly associated to prostate cancer, for either low (p = 0.002) or high (p = 0.01) grade tumor. At the gene level, we observed significant associations between all prostate cancer and NPAS2 and PER1 after correcting for multiple testing, while only RORA was significant for aggressive tumors. At the SNP-level, no significant association was observed. Our findings provide additional evidence of a potential link between genetic variants in circadian genes and prostate cancer risk. Further investigation is warranted to confirm these findings and to better understand the biological pathways involved.

F89EXPLOITING POLYGENIC RISK SCORES TO INFER DE NOVO OR RARE DELETERIOUS ALLELES

Although prostate cancer is known to have a strong genetic basis and is influenced by both common and rare variants, the ability to investigate the combined effect of such genetic risk factors has been limited to date. We conducted an investigation of 81 094 men from the UK Biobank, including 3568 prostate cancer cases, to examine the combined effect of rare pathogenic/likely pathogenic/deleterious (P/LP/D) germline variants and common prostate cancer risk variants, measured using a polygenic risk score (PRS), on prostate cancer risk. The absolute risk of prostate cancer for HOXB13, BRCA2, ATM, and CHEK2 P/LP/D carriers ranged from 9% to 56%, and the absolute risk in noncarriers ranged from 2% to 31%, by age 85 yr, for men in the lowest and highest PRS decile, respectively. The high-penetrant HOXB13 G84E prostate cancer risk variant was most common in cases in the lowest PRS quintile (4.4%) and least common in cases in the highest PRS quintile (0.5%; p = 0.005), whereas there was no statistically significant difference in frequencies by PRS in controls. While rare and common variants strongly and distinctly influence prostate cancer onset, consideration of rare and common variants in conjunction will lead to more precise estimates of a man’s lifetime risk of prostate cancer.We found that the risk of prostate cancer conveyed by rare variants could vary depending on an individual’s genetic profile of common risk variants. This implies that in order to comprehensively assess genetic risk of prostate cancer, it is important to consider both rare and common variants.

Genome-wide associations for benign prostatic hyperplasia reveal a genetic correlation with serum levels of PSA

Benign prostatic hyperplasia and associated lower urinary tract symptoms (BPH/LUTS) are common conditions affecting the majority of elderly males. Here we report the results of a genome-wide association study of symptomatic BPH/LUTS in 20,621 patients and 280,541 controls of European ancestry, from Iceland and the UK. We discovered 23 genome-wide significant variants, located at 14 loci. There is little or no overlap between the BPH/LUTS variants and published prostate cancer risk variants. However, 15 of the variants reported here also associate with serum levels of prostate specific antigen (PSA) (at a Bonferroni corrected P < 0.0022). Furthermore, there is a strong genetic correlation, rg = 0.77 (P = 2.6 × 10−11), between PSA and BPH/LUTS, and one standard deviation increase in a polygenic risk score (PRS) for BPH/LUTS increases PSA levels by 12.9% (P = 1.6×10−55). These results shed a light on the genetic background of BPH/LUTS and its substantial influence on PSA levels.

Cumulative Evidence for Relationships Between 8q24 Variants and Prostate Cancer.

Multiple independent cancer susceptibility loci at chromosome 8q24 have been identified by GWAS (Genome-wide association studies). Forty six articles including 60,293 cases and 62,971 controls were collected to conduct a meta-analysis to evaluate the associations between 21 variants in 8q24 and prostate cancer risk. Of the 21 variants located in 8q2\\5 were significantly associated with the risk of prostate cancer. In particular, both homozygous AA and heterozygous CA genotypes of rs16901979, as well as the AA and CA genotypes of rs1447295, were associated with the risk of prostate cancer. Our study showed that variants in the 8q24 region are associated with prostate cancer risk in this large-scale research synopsis and meta-analysis. Further studies are needed to explore the role of the 8q24 variants involved in the etiology of prostate cancer.

Circadian genes and prostate cancer risk: Results from the EPICAP study

Background Night work has been associated with cancer risk, including prostate cancer, in several studies. It has been suggested that disruption of circadian rhythm, induced by night work, may play a role in carcinogenesis. Indeed, circadian rhythms regulate several physiological functions and genes controlling the circadian rhythm were found to regulate cell proliferation, cell cycle and apoptosis. Very few studies have investigated the role of those circadian genes in prostate cancer occurrence. This study aims to analyze the association between circadian genes polymorphisms and prostate cancer risk based on data from the EPICAP study. Methods EPICAP is a French population-based case-control study including 819 incident prostate cancer cases and 879 controls frequency matched for age, among which 777 cases and 823 controls provided blood or saliva sample, allowing the constitution of a DNA bank. Blood and salivary samples were used for DNA extractions and genotyping using the Infinium® Oncoarray-500 K BeadChip (Illumina). This chip contains 276,000 single nucleotide polymorphisms (SNPs) assuring a genome-wide coverage and was completed by 234,000 SNPs selected for their potential relevance to the most common cancers including prostate cancer. Overall, the EPICAP genetic database included 1515 subjects (732 cases/783 controls) and 447,896 SNPs that passed stringent quality controls. For the purpose of this study, 31 circadian clock genes including 872 SNPs with a minor allele frequency (MAF) greater than 0.01 were selected. Genes from the circadian pathway was additionally divided into 2 sub-pathways: the well-established core circadian genes that include 9 genes (CLOCK, NPAS2, ARNTL, CSNKIE, CRY1, CRY2, PER1, PER2, and PER3) and the other 22 genes. Odds ratios (ORs) for association between prostate cancer and each SNP were estimated using unconditional logistic regression assuming a log-additive model. We also used a gene-based and pathway-based approach such as the Adaptive Rank Truncated Product (ARTP) method which combines association signals from the SNPs in a given gene (or from the genes in a pathway) to provide a P-value at the gene (or pathway level). Separate analyses were conducted by prostate cancer aggressiveness according to the Gleason score (low or intermediate score ≤ 7 [including 3 + 4], high score ≥ 7 [including 4 + 3]). Results No SNP was significantly associated to prostate cancer after correction for multiple testing using the false discovery rate (FDR) method. At the gene level, we reported 2 genes significantly associated to prostate cancer risk: NPAS2 (P = 0.046) and PER1 (P = 0.046). The whole circadian pathway was significantly associated to prostate cancer (P = 0.023) and this association was mainly supported by the circadian core-genes sub-pathway (P = 0.0002). Similar results were observed either in aggressive (P = 0.04 for the whole pathway and P = 0.01 for the core-genes sub-pathway) or less aggressive (P = 0.004 for the whole pathway and P = 0.001 for the core-genes sub-pathway) prostate cancer. Conclusion Our results support the hypothesis of a potential link between genetic variants in circadian genes and prostate cancer risk. Further investigation is warranted to confirm these findings and to better understand the biological pathways involved.

Genetic risk of prostate cancer in Ugandan men.

Men of African-ancestry have elevated prostate cancer (PCa) incidence and mortality compared to men of other racial groups. There is support for a genetic contribution to this disparity, with evidence of genetic heterogeneity in the underlying risk alleles between populations. Studies of PCa among African men may inform the contribution of genetic risk factors to the elevated disease burden in this population. We conducted an association study of >100 previously reported PCa risk alleles among 571 incidence cases and 485 controls among Uganda men. Unconditional logistic regression was used to test genetic associations and a polygenic risk score (PRS) was derived to assess the cumulative effect of the known risk alleles in association with PCa risk. In an exploratory analysis, we also tested associations of 17 125 421 genotyped and imputed markers genome-wide in association with PCa risk. Of the 111 known risk loci with a frequency >1%, 75 (68%) had effects that were directionally consistent with the initial discovery population,14 (13%) of which were nominally significantly associated with PCa risk at P < 0.05. Compared to men with average risk (25th -75th percentile in PRS distribution), Ugandan men in the top 10% of the PRS, constructed of alleles outside of 8q24, had a 2.9-fold (95%CI: 1.75, 4.97) risk of developing PCa; risk for the top 10% increased to 4.86 (95%CI: 2.70, 8.76) with the inclusion of risk alleles at 8q24. In genome-wide association testing, the strongest associations were noted with known risk alleles located in the 8q24 region, including rs72725854 (OR = 3.37, P = 2.14 × 10-11 ) that is limited to populations of African ancestry (6% frequency). The ∼100 known PCa risk variants were shown to effectively stratify PCa risk in Ugandan men, with 10% of men having a >4-fold increase in risk. The 8q24 risk region was also found to be a major contributor to PCa risk in Ugandan men, with the African ancestry-specific risk variant rs72725854 estimated to account for 12% of PCa in this population.

The Association Between Three Genetic Variants in MicroRNAs (Rs11614913, Rs2910164, Rs3746444) and Prostate Cancer Risk

Background/Aims: MicroRNAs (miRNAs) are a class of small non-coding RNA molecules which play a significant role in transcriptional and translational regulation. Published data on the association between the miRNA SNPs and prostate cancer (PCa) risk are somewhat inconclusive. Methods: We performed a meta-analysis of all available studies including 2,227 patients and 2,331 control subjects to evaluate the impact of three common genetic variants of microRNAs in prostate cancer risk. Odds ratios (ORs) with 95% confidence intervals (CIs) were utilized to investigate the strength of the association. Results: For miR-499 polymorphism, a significant association was observed between the rs3746444 A>G polymorphism and PCa risk in heterozygote comparison and dominant genetic model, in particular in Asian population subgroup. For miR-146a polymorphism, the rs2910164 CC genotype was associated with decreased PCa risk in Asian population in homozygote comparison. In addition, rs2910164 CC genotype had a weekly higher percentage value in subgroup of Gleason score < 7. Similar results were also indicated in localized prostate cancer in subgroup analysis by tumor stage. For miR-196a2 polymorphism, no association was observed between this variant and PCa risk in the overall group. However, in stratified analysis by ethnicity, we found that rs11614913 T allele was a risk factor for Asian PCa patients. Conclusions: Polymorphisms of miR-196a2 rs11614913, miR-146a rs2910164, and miR-499 rs3746444 may contribute to the risk for developing prostate cancer in Asian descendants. Moreover, miR-146a rs2910164 polymorphism was related to PCa prognosis.

Profile of common prostate cancer risk variants in an unscreened Romanian population.

To find sequence variants affecting prostate cancer (PCA) susceptibility in an unscreened Romanian population we use a genome‐wide association study (GWAS). The study population included 990 unrelated pathologically confirmed PCA cases and 1034 male controls. DNA was genotyped using Illumina SNP arrays, and 24.295.558 variants were imputed using the 1000 Genomes data set. An association test was performed between the imputed markers and PCA. A systematic literature review for variants associated with PCA risk identified 115 unique variants that were tested in the Romanian sample set. Thirty of the previously reported SNPs replicated (P‐value < 0.05), with the strongest associations observed at: 8q24.21, 11q13.3, 6q25.3, 5p15.33, 22q13.2, 17q12 and 3q13.2. The replicated variants showing the most significant association in Romania are rs1016343 at 8q24.21 (P = 2.2 × 10−4), rs7929962 at 11q13.3 (P = 2.7 × 10−4) and rs9364554 at 6q25.2 (P = 4.7 × 10−4). None of the variants tested in the Romanian GWAS reached genome‐wide significance (P‐value <5 × 10−8) but 807 markers had P‐values <1 × 10−4. Here, we report the results of the first GWAS of PCA performed in a Romanian population. Our study provides evidence that a substantial fraction of previously validated PCA variants associate with risk in this unscreened Romanian population.

Network-directed cis-mediator analysis of normal prostate tissue expression profiles reveals downstream regulatory associations of prostate cancer susceptibility loci.

Large-scale genome-wide association studies have identified multiple single-nucleotide polymorphisms associated with risk of prostate cancer. Many of these genetic variants are presumed to be regulatory in nature; however, follow-up expression quantitative trait loci (eQTL) association studies have to-date been restricted largely to cis-acting associations due to study limitations. While trans-eQTL scans suffer from high testing dimensionality, recent evidence indicates most trans-eQTL associations are mediated by cis-regulated genes, such as transcription factors. Leveraging a data-driven gene co-expression network, we conducted a comprehensive cis-mediator analysis using RNA-Seq data from 471 normal prostate tissue samples to identify downstream regulatory associations of previously identified prostate cancer risk variants. We discovered multiple trans-eQTL associations that were significantly mediated by cis-regulated transcripts, four of which involved risk locus 17q12, proximal transcription factor HNF1B, and target trans-genes with known HNF response elements (MIA2, SRC, SEMA6A, KIF12). We additionally identified evidence of cis-acting down-regulation of MSMB via rs10993994 corresponding to reduced co-expression of NDRG1. The majority of these cis-mediator relationships demonstrated trans-eQTL replicability in 87 prostate tissue samples from the Gene-Tissue Expression Project. These findings provide further biological context to known risk loci and outline new hypotheses for investigation into the etiology of prostate cancer.

Abstract 4956: Transcriptome-wide association study identifies new prostate cancer susceptibility genes in the OncoArray data

Abstract Genome-wide association studies (GWAS) have identified over 150 genomic regions harboring risk variants for prostate cancer which explain one third of all familial risk. However, with some notable exceptions, the causal variants and target susceptibility genes at these risk loci have yet to be identified. Recent work has shown a strong overlap between loci associated with gene expression levels (eQTLs) in prostate tissue and GWAS loci, which suggests that the causal mechanism at a significant proportion of risk loci includes causal alleles that regulate expression levels of nearby susceptibility genes. While overlapping eQTLs with GWAS is a powerful method to prioritize susceptibility genes, it is often the case that multiple eQTLs co-localize at the GWAS risk region (due to linkage disequilibrium (LD) and correlations across transcript levels). This prohibits the identification of the true susceptibility gene as opposed to spurious co-localization at the same locus. We recently leveraged gene expression imputation to perform transcriptome-wide association studies (TWAS) as a principled approach to measure the strength of association between gene expression and disease status. Here, we use imputed expression to identify new susceptibility genes for prostate cancer in the OncoArray GWAS data. We integrate gene expression data from more than 44 tissues across ~4,000 individuals with GWAS of prostate cancer from the OncoArray in ~140,000 individuals. Our approach identified 118 susceptibility genes for prostate cancer that reside in 90 independent loci across the genome. Of these, we report 7 genes located more than 0.5 Megabases away from any previously reported GWAS loci for prostate cancer, thus providing new risk loci. Second, we use TWAS to investigate genes previously reported as susceptibility genes for prostate cancer through overlaps of eQTL and GWAS. We find 36 (out of 86 previously reported genes) to be significant in TWAS. Overall, our findings highlight the power of integrating gene expression data with GWAS and provide testable hypotheses for future functional validation of prostate cancer risk. Citation Format: Nicholas Mancuso, Wei Zheng, Kathryn Penney, The PRACTICAL Consortium, Zsofia Kote-Jarai, Christopher Haiman, Simon Gayther, Matthew Freedman, Bogdan Pasaniuc. Transcriptome-wide association study identifies new prostate cancer susceptibility genes in the OncoArray data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4956. doi:10.1158/1538-7445.AM2017-4956