Variation in KLK genes, prostate-specific antigen and risk of prostate cancer

Towards Understanding the Key Signature Pathways Associated from Differentially Expressed Gene Analysis in an Indian Prostate Cancer Cohort

Prostate cancer (PCa) is one of the most prevalent cancers among men in India. Although studies on PCa have dealt with genetics, genomics, and the environmental influence in the causality of PCa, not many studies employing the Next Generation Sequencing (NGS) approaches of PCa have been carried out. In our previous study, we identified some causal genes and mutations specific to Indian PCa using Whole Exome Sequencing (WES). In the recent past, with the help of different cancer consortiums such as The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC), along with differentially expressed genes (DEGs), many cancer-associated novel non-coding RNAs have been identified as biomarkers. In this work, we attempt to identify differentially expressed genes (DEGs) including long non-coding RNAs (lncRNAs) associated with signature pathways from an Indian PCa cohort using the RNA-sequencing (RNA-seq) approach. From a cohort of 60, we screened six patients who underwent prostatectomy; we performed whole transcriptome shotgun sequencing (WTSS)/RNA-sequencing to decipher the DEGs. We further normalized the read counts using fragments per kilobase of transcript per million mapped reads (FPKM) and analyzed the DEGs using a cohort of downstream regulatory tools, viz., GeneMANIA, Stringdb, Cytoscape-Cytohubba, and cbioportal, to map the inherent signatures associated with PCa. By comparing the RNA-seq data obtained from the pairs of normal and PCa tissue samples using our benchmarked in-house cuffdiff pipeline, we observed some important genes specific to PCa, such as STEAP2, APP, PMEPA1, PABPC1, NFE2L2, and HN1L, and some other important genes known to be involved in different cancer pathways, such as COL6A1, DOK5, STX6, BCAS1, BACE1, BACE2, LMOD1, SNX9, CTNND1, etc. We also identified a few novel lncRNAs such as LINC01440, SOX2OT, ENSG00000232855, ENSG00000287903, and ENST00000647843.1 that need to be characterized further. In comparison with publicly available datasets, we have identified characteristic DEGs and novel lncRNAs implicated in signature PCa pathways in an Indian PCa cohort which perhaps have not been reported. This has set a precedent for us to validate candidates further experimentally, and we firmly believe this will pave a way toward the discovery of biomarkers and the development of novel therapies.

Cumulative Effect Assessment of Common Genetic Variants on Prostate Cancer: Preliminary Studies

Single nucleotide polymorphisms (SNPs) are the most common type of genetic variation among people. Genome Wide Association studies (GWASs) have generated multiple genetic variants associated with prostate cancer (PC) risk. Taking into account previously identified genetic susceptibility variants, the purpose of our study was to determine the cumulative association between four common SNPs and the overall PC risk. A total of 78 specimens from both PC and benign prostate hyperplasia (BPH) patients were included in the study. Genotyping of all selected SNPs was performed using the TaqMan assay. The association between each SNP and the PC risk was assessed individually and collectively. Analysis of the association between individual SNPs and PC risk revealed that only the rs4054823 polymorphism was significantly associated with PC, and not with BPH (p < 0.001). Statistical analysis also showed that the heterozygous genotype of the rs2735839 polymorphism is more common within the BPH group than in the PC group (p = 0.042). The cumulative effect of high-risk alleles on PC was analyzed using a logistic regression model. As a result, the carriers of at least one risk allele copy in each particular region had a cumulative odd ratio (OR) of 1.42 times, compared to subjects who did not have any of these factors. In addition, the combination of these four genetic variants increased the overall risk of PC by 52%. Our study provides further evidence of the cumulative effects of genetic risk factors on overall PC risk. These results should encourage future research to explain the interactions between known susceptibility variants and their contribution to the development and progression of PC disease.

Inherited risk assessment and its clinical utility for predicting prostate cancer from diagnostic prostate biopsies

BACKGROUND

Many studies on prostate cancer (PCa) germline variants have been published in the last 15 years. This review critically assesses their clinical validity and explores their utility in prediction of PCa detection rates from prostate biopsy.

METHODS

An integrative review was performed to (1) critically synthesize findings on PCa germline studies from published papers since 2016, including risk-associated single nucleotide polymorphisms (SNPs), polygenic risk score methods such as genetic risk score (GRS), and rare pathogenic mutations (RPMs); (2) exemplify the findings in a large population-based cohort from the UK Biobank (UKB); (3) identify gaps for implementing inherited risk assessment in clinic based on experience from a healthcare system; (4) evaluate available GRS data on their clinical utility in predicting PCa detection rates from prostate biopsies; and (5) describe a prospective germline-based biopsy trial to address existing gaps.

RESULTS

SNP-based GRS and RPMs in four genes (HOXB13, BRCA2, ATM, and CHEK2) were significantly and consistently associated with PCa risk in large well-designed studies. In the UKB, positive family history, RPMs in the four implicated genes, and a high GRS (>1.5) identified 8.12%, 1.61%, and 17.38% of men to be at elevated PCa risk, respectively, with hazard ratios of 1.84, 2.74, and 2.39, respectively. Additionally, the performance of GRS for predicting PCa detection rate on prostate biopsy was consistently supported in several retrospective analyses of transrectal ultrasound (TRUS)-biopsy cohorts. Prospective studies evaluating the performance of all three inherited measures in predicting PCa detection rate from contemporary multiparametric MRI (mpMRI)-based biopsy are lacking. A multicenter germline-based biopsy trial to address these gaps is warranted.

CONCLUSIONS

The complementary performance of three inherited risk measures in PCa risk stratification is consistently supported. Their clinical utility in predicting PCa detection rate, if confirmed in prospective clinical trials, may improve current decision-making for prostate biopsy.

KLK3 germline mutation I179T complements DNA repair genes for predicting prostate cancer progression

BACKGROUND

Germline mutations in DNA repair genes and KLK3 have been associated with adverse prostate cancer (PCa) outcomes in separate studies but never jointly. The objective of this study is to simultaneously assess these two types of germline mutations.

METHODS

Germline rare pathogenic mutations (RPMs) in 9 commonly tested DNA repair genes and KLK3 variants were tested for their associations with PCa progression in two PCa cohorts: (1) hospital-based PCa patients treated with radical surgery at the Johns Hopkins Hospital (JHH, N = 1943), and (2) population-based PCa patients in the UK Biobank (UKB, N = 10,224). Progression was defined as metastasis and/or PCa-specific death (JHH) and PCa-specific death (UKB). RPMs of DNA repair genes were annotated using the American College of Medical Genetics recommendations. Known KLK3 variants were genotyped. Associations were tested using a logistic regression model adjusting for genetic background (top ten principal components).

RESULTS

In the JHH, 3.2% (59/1,843) of patients had RPMs in 9 DNA repair genes; odds ratio (OR, 95% confidence interval) for progression was 2.99 (1.6-5.34), P < 0.001. In comparison, KLK3 I179T mutation was more common; 9.7% (189/1,943) carried the mutation, OR = 1.6 (1.05-2.37), P = 0.02. Similar results were found in the UKB. Both types of mutations remained statistically significant in multivariable analyses. In the combined cohort, compared to patients without any mutations (RPMs-/KLK3-), RPMs-/KLK3+ patients had modestly increased risk for progression [OR = 1.54 (1.15-2.02), P = 0.003], and RPMs+/KLK3+ patients had greatly increased risk for progression [OR = 5.41 (2.04-12.99), P < 0.001]. Importantly, associations of mutations with PCa progression were found in patients with clinically defined low- or intermediate risk for disease progression.

CONCLUSIONS

Two different cohorts consistently demonstrate that KLK3 I179T and RPMs of nine commonly tested DNA repair genes are complementary for predicting PCa progression. These results are highly relevant to PCa germline testing and provide critical information for KLK3 I179T to be considered in guidelines.

Expanding cancer predisposition genes with ultra-rare cancer-exclusive human variations

It is estimated that up to 10% of cancer incidents are attributed to inherited genetic alterations. Despite extensive research, there are still gaps in our understanding of genetic predisposition to cancer. It was theorized that ultra-rare variants partially account for the missing heritable component. We harness the UK BioBank dataset of ~ 500,000 individuals, 14% of which were diagnosed with cancer, to detect ultra-rare, possibly high-penetrance cancer predisposition variants. We report on 115 cancer-exclusive ultra-rare variations and nominate 26 variants with additional independent evidence as cancer predisposition variants. We conclude that population cohorts are valuable source for expanding the collection of novel cancer predisposition genes.

Aggressive prostate cancer phenotype and genome-wide association studies: where are we now?

The majority of prostate cancer (PCa) is indolent, however, a percentage of patients are initially diagnosed with metastatic disease, for which there is a worse prognosis. There is a lack of biomarkers to identify men at greater risk for developing aggressive PCa. Genome-wide association studies (GWAS) scan the genome to search associations of SNPs with specific traits, like cancer. To date, eight GWAS have resulted in the reporting of 16 SNPs associated with aggressive PCa (p < 5.00 × 10^-2). Still, validation studies need to be conducted to confirm the obtained results as GWAS can generate false-positive results. Furthermore, post-GWAS studies provide a better understanding of the functional consequences.

Multi-omics Biomarker Pipeline Reveals Elevated Levels of Protein-glutamine Gamma-glutamyltransferase 4 in Seminal Plasma of Prostate Cancer Patients

Seminal plasma, because of its proximity to prostate, is a promising fluid for biomarker discovery and noninvasive diagnostics. In this study, we investigated if seminal plasma proteins could increase diagnostic specificity of detecting primary prostate cancer and discriminate between high- and low-grade cancers. To select 147 most promising biomarker candidates, we combined proteins identified through five independent experimental or data mining approaches: tissue transcriptomics, seminal plasma proteomics, cell line secretomics, tissue specificity, and androgen regulation. A rigorous biomarker development pipeline based on selected reaction monitoring assays was designed to evaluate the most promising candidates. As a result, we qualified 76, and verified 19 proteins in seminal plasma of 67 negative biopsy and 152 prostate cancer patients. Verification revealed a prostate-specific, secreted and androgen-regulated protein-glutamine gamma-glutamyltransferase 4 (TGM4), which predicted prostate cancer on biopsy and outperformed age and serum Prostate-Specific Antigen (PSA). A machine-learning approach for data analysis provided improved multi-marker combinations for diagnosis and prognosis. In the independent verification set measured by an in-house immunoassay, TGM4 protein was upregulated 3.7-fold (p = 0.006) and revealed AUC = 0.66 for detecting prostate cancer on biopsy for patients with serum PSA ≥4 ng/ml and age ≥50. Very low levels of TGM4 (120 pg/ml) were detected in blood serum. Collectively, our study demonstrated rigorous evaluation of one of the remaining and not well-explored prostate-specific proteins within the medium-abundance proteome of seminal plasma. Performance of TGM4 warrants its further investigation within the distinct genomic subtypes and evaluation for the inclusion into emerging multi-biomarker panels.

Kallikarein-related peptidase 3 common genetic variant and the risk of prostate cancer

Kallikarein-related peptidase 3 (KLK3) gene polymorphisms seem to play a role in susceptibility to prostate cancer (PC). The purpose of this study was to investigate the association between rs2735839 polymorphism of KLK3 gene and risk of PC in an Iranian population. In this case-control study, rs2735839 was genotyped in 532 patients with PC and 602 controls with benign prostate hyperplasia (BPH) using polymerase chain reaction-restriction fragment length polymorphism assay. The frequency of GG, AG, and AA genotypes of KLK3 polymorphism was 24.6% and 76.2%, 46.6% and 21.7%, and 28.8% and 2.1%, in patients with BPH and PC, respectively (P < 0.001). The frequency of G allele in patients with BPH and PC was 47.9% and 87%, respectively (odds ratio: 7.31; confidence interval: 5.88-9.10; P < 0.001). Patients with AG and GG genotypes had a higher total serum level of prostate-specific antigen (PSA) compared to those with AA genotype (P < 0.001). Patients with this polymorphism had higher risk of tumor with higher grade (P = 0.23), advanced stage (P = 0.11), perineural invasion (P = 0.07), and vascular invasion (P = 0.07) compared to those without it but this difference was not statistically significant. Based on our results, KLK3 gene polymorphism was associated with the risk of PC. Higher levels of PSA in the presence of KLK3 polymorphism in patients with PC indicated that rs2735839 polymorphism could be a risk factor for increased levels of PSA.

Systematic identification of functionally relevant risk alleles to stratify aggressive versus indolent prostate cancer

Novel approaches for classification, including molecular features, are needed to direct therapy for men with low-grade prostate cancer (PCa), especially men on active surveillance. Risk alleles identified from genome-wide association studies (GWAS) could improve prognostication. Those risk alleles that coincided with genes and somatic copy number aberrations associated with progression of PCa were selected as the most relevant for prognostication.

In a systematic literature review, a total of 698 studies were collated. Fifty-three unique SNPs residing in 29 genomic regions, including 8q24, 10q11 and 19q13, were associated with PCa progression. Functional studies implicated 21 of these single nucleotide polymorphisms (SNPs) as modulating the expression of genes in the androgen receptor pathway and several other oncogenes. In particular, 8q24, encompassing MYC, harbours a high density of SNPs conferring unfavourable pathological characteristics in low-grade PCa, while a copy number gain of MYC in low-grade PCa was associated with prostate-specific antigen recurrence after radical prostatectomy.

By combining GWAS data with gene expression and structural rearrangements, risk alleles were identified that could provide a new basis for developing a prognostication tool to guide therapy for men with early prostate cancer.

Incorporating Known Genetic Variants Does Not Improve the Accuracy of PSA Testing to Identify High Risk Prostate Cancer on Biopsy

INTRODUCTION

Prostate-specific antigen (PSA) testing is a widely accepted screening method for prostate cancer, but with low specificity at thresholds giving good sensitivity. Previous research identified four single nucleotide polymorphisms (SNPs) principally associated with circulating PSA levels rather than with prostate cancer risk (TERT rs2736098, FGFR2 rs10788160, TBX3 rs11067228, KLK3 rs17632542). Removing the genetic contribution to PSA levels may improve the ability of the remaining biologically-determined variation in PSA to discriminate between high and low risk of progression within men with identified prostate cancer. We investigate whether incorporating information on the PSA-SNPs improves the discrimination achieved by a single PSA threshold in men with raised PSA levels.

MATERIALS AND METHODS

Men with PSA between 3-10 ng/mL and histologically-confirmed prostate cancer were categorised as high or low risk of progression (Low risk: Gleason score≤6 and stage T1-T2a; High risk: Gleason score 7-10 or stage T2C). We used the combined genetic effect of the four PSA-SNPs to calculate a genetically corrected PSA risk score. We calculated the Area under the Curve (AUC) to determine how well genetically corrected PSA risk scores distinguished men at high risk of progression from low risk men.

RESULTS

The analysis includes 868 men with prostate cancer (Low risk: 684 (78.8%); High risk: 184 (21.2%)). Receiver operating characteristic (ROC) curves indicate that including the 4 PSA-SNPs does not improve the performance of measured PSA as a screening tool for high/low risk prostate cancer (measured PSA level AUC = 59.5% (95% CI: 54.7,64.2) vs additionally including information from the 4 PSA-SNPs AUC = 59.8% (95% CI: 55.2,64.5) (p-value = 0.40)).

CONCLUSION

We demonstrate that genetically correcting PSA for the combined genetic effect of four PSA-SNPs, did not improve discrimination between high and low risk prostate cancer in men with raised PSA levels (3-10 ng/mL). Replication and gaining more accurate estimates of the effects of the 4 PSA-SNPs and additional variants associated with PSA levels and not prostate cancer could be obtained from subsequent GWAS from larger prospective studies.

Variation in genes involved in the immune response and prostate cancer risk in the placebo arm of the Prostate Cancer Prevention Trial

BACKGROUND

We previously found that inflammation in benign prostate tissue is associated with an increased odds of prostate cancer, especially higher-grade disease. Since part of this link may be due to genetics, we evaluated the association between single nucleotide polymorphisms (SNPs) in immune response genes and prostate cancer in the placebo arm of the Prostate Cancer Prevention Trial.

METHODS

We genotyped 16 candidate SNPs in IL1β, IL2, IL4, IL6, IL8, IL10, IL12(p40), IFNG, MSR1, RNASEL, TLR4, and TNFA and seven tagSNPs in IL10 in 881 prostate cancer cases and 848 controls negative for cancer on an end-of-study biopsy. Cases and controls were non-Hispanic white and frequency matched on age and family history. We classified cases as lower (Gleason sum <7; N = 674) and higher (7-10; N = 172) grade, and used logistic regression to estimate odds ratios (OR) and 95% confidence intervals (CI) adjusting for age and family history.

RESULTS

The minor allele (C) of rs3212227 in IL12(p40) was associated with an increased risk of total (log additive: OR = 1.30, 95%CI 1.10-1.53; P-trend = 0.0017) and lower-grade (OR = 1.36, 95%CI 1.15-1.62; P-trend = 0.0004) prostate cancer. The minor allele (A) of rs4073 in IL8 was possibly associated with a decreased risk of higher-grade (OR = 0.81, 95%CI 0.64-1.02; P-trend = 0.07), but not total disease. None of the other candidates was associated with risk. The minor alleles of IL10 tagSNPs rs1800890 (A; OR = 0.87, 95%CI: 0.75-0.99; P-trend = 0.04) and rs3021094 (C; OR = 1.31, 95%CI 1.03-1.66, P-trend = 0.03) were associated with risk; the latter also with lower- (P-trend = 0.04) and possibly higher- (P-trend = 0.06) grade disease. These patterns were similar among men with PSA <2 ng/ml at biopsy.

CONCLUSION

Variation in some immune response genes may be associated with prostate cancer risk. These associations were not fully explained by PSA-associated detection bias. Our findings generally support the role of inflammation in the etiology of prostate cancer.

A large multiethnic genome-wide association study of prostate cancer identifies novel risk variants and substantial ethnic differences

A genome-wide association study (GWAS) of prostate cancer in Kaiser Permanente health plan members (7,783 cases, 38,595 controls; 80.3% non-Hispanic white, 4.9% African-American, 7.0% East Asian, and 7.8% Latino) revealed a new independent risk indel rs4646284 at the previously identified locus 6q25.3 that replicated in PEGASUS (N = 7,539) and the Multiethnic Cohort (N = 4,679) with an overall P = 1.0 × 10(-19) (OR, 1.18). Across the 6q25.3 locus, rs4646284 exhibited the strongest association with expression of SLC22A1 (P = 1.3 × 10(-23)) and SLC22A3 (P = 3.2 × 10(-52)). At the known 19q13.33 locus, rs2659124 (P = 1.3 × 10(-13); OR, 1.18) nominally replicated in PEGASUS. A risk score of 105 known risk SNPs was strongly associated with prostate cancer (P < 1.0 × 10(-8)). Comparing the highest to lowest risk score deciles, the OR was 6.22 for non-Hispanic whites, 5.82 for Latinos, 3.77 for African-Americans, and 3.38 for East Asians. In non-Hispanic whites, the 105 risk SNPs explained approximately 7.6% of disease heritability. The entire GWAS array explained approximately 33.4% of heritability, with a 4.3-fold enrichment within DNaseI hypersensitivity sites (P = 0.004).

SIGNIFICANCE

Taken together, our findings of independent risk variants, ethnic variation in existing SNP replication, and remaining unexplained heritability have important implications for further clarifying the genetic risk of prostate cancer. Our findings also suggest that there may be much promise in evaluating understudied variation, such as indels and ethnically diverse populations.

Mining for single nucleotide variants (SNVs) at the kallikrein locus with predicted functional consequences

Kallikreins (KLKs) are a group of 15 serine proteases encoded by the KLK locus on chromosome 19. Certain single nucleotide variants (SNVs) within the KLK locus have been linked to human disease. Next-generation sequencing of large human cohorts enables reexamination of genomic variation at the KLK locus. We aimed to identify all KLK-related SNVs and examine their impact on gene regulation and function. To this end, we mined KLK SNVs across Ensembl and Exome Variant Server, with exome-sequencing data from 6503 individuals. PolyPhen-2-based prediction of damaging SNVs and population frequencies of these SNVs were examined. Damaging SNVs were plotted on protein sequence and structure. We identified 4866 SNVs, the largest number of KLK-related SNVs reported. Fourteen percent of noncoding SNVs overlapped with transcription factor binding sites. We identified 602 missense coding SNVs, among which 148 were predicted to be damaging. Nine missense SNVs were common (>1% frequency) and displayed significantly different frequencies between European-American and African-American populations. SNVs predicted to be damaging appeared to alter tertiary structure of KLK1 and KLK6. Similarly, these missense SNVs may affect KLK function, resulting in disease phenotypes. Our study represents a mine of information for those studying KLK-related SNVs and their associations with diseases.

eQTL mapping identifies insertion- and deletion-specific eQTLs in multiple tissues

Genome-wide gene expression quantitative trait loci (eQTL) mapping have been focused on single-nucleotide polymorphisms and have helped interpret findings from diseases mapping studies. The functional effect of structure variants, especially short insertions and deletions (indel) has not been well investigated. Here we impute 1,380,133 indels based on the latest 1,000 Genomes Project panel into three eQTL data sets from multiple tissues. Imputation of indels increased 9.9% power and identifies indel-specific eQTLs for 325 genes. We find introns and vicinities of UTRs are more enriched of indel eQTLs and 3.6 (single-tissue)-9.2%(multi-tissue) of previous identified eSNPs were taggers of eindels. Functional analyses identifies epigenetics marks, gene ontology categories and disease GWAS loci affected by SNPs and indels eQTLs showing tissue-consistent or tissue-specific effects. This study provides new insights into the underlying genetic architecture of gene expression across tissues and new resource to interpret function of diseases and traits associated structure variants.

Polymorphisms influencing prostate-specific antigen concentration may bias genome-wide association studies on prostate cancer

BACKGROUND

Genome-wide association studies (GWAS) have produced weak (OR = 1.1-1.5) but significant associations between single nucleotide polymorphisms (SNPs) and prostate cancer. However, these associations may be explained by detection bias caused by SNPs influencing PSA concentration. Thus, in a simulation study, we quantified the extent of bias in the association between a SNP and prostate cancer when the SNP influences PSA concentration.

METHODS

We generated 2,000 replicate cohorts of 20,000 men using real-world estimates of prostate cancer risk, prevalence of carrying ≥1 minor allele, PSA concentration, and the influence of a SNP on PSA concentration. We modeled risk ratios (RR) of 1.00, 1.25, and 1.50 for the association between carrying ≥1 minor allele and prostate cancer. We calculated mean betas from the replicate cohorts and quantified bias under each scenario.

RESULTS

Assuming no association between a SNP and prostate cancer, the estimated mean bias in betas ranged from 0.02 to 0.10 for ln PSA being 0.05 to 0.20 ng/mL higher in minor allele carriers; the mean biased RRs ranged from 1.03 to 1.11. Assuming true RRs = 1.25 and 1.50, the biased RRs were as large as 1.39 and 1.67, respectively.

CONCLUSION

Estimates of the association between SNPs and prostate cancer can be biased to the magnitude observed in published GWAS, possibly resulting in type I error. However, large associations (RR > 1.10) may not fully be explained by this bias.

IMPACT

The influence of SNPs on PSA concentration should be considered when interpreting results from GWAS on prostate cancer.

Do environmental factors modify the genetic risk of prostate cancer?

BACKGROUND

Many SNPs influence prostate cancer risk. To what extent genetic risk can be reduced by environmental factors is unknown.

METHODS

We evaluated effect modification by environmental factors of the association between susceptibility SNPs and prostate cancer in 1,230 incident prostate cancer cases and 1,361 controls, all white and similar ages, nested in the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Trial. Genetic risk scores were calculated as number of risk alleles for 20 validated SNPs. We estimated the association between higher genetic risk (≥12 SNPs) and prostate cancer within environmental factor strata and tested for interaction.

RESULTS

Men with ≥12 risk alleles had 1.98, 2.04, and 1.91 times the odds of total, advanced, and nonadvanced prostate cancer, respectively. These associations were attenuated with the use of selenium supplements, aspirin, ibuprofen, and higher vegetable intake. For selenium, the attenuation was most striking for advanced prostate cancer: compared with <12 alleles and no selenium, the OR for ≥12 alleles was 2.06 [95% confidence interval (CI), 1.67-2.55] in nonusers and 0.99 (0.38-2.58) in users (Pinteraction = 0.031). Aspirin had the most marked attenuation for nonadvanced prostate cancer: compared with <12 alleles and nonusers, the OR for ≥12 alleles was 2.25 (1.69-3.00) in nonusers and 1.70 (1.25-2.32) in users (Pinteraction = 0.009). This pattern was similar for ibuprofen (Pinteraction = 0.023) and vegetables (Pinteraction = 0.010).

CONCLUSIONS

This study suggests that selenium supplements may reduce genetic risk of advanced prostate cancer, whereas aspirin, ibuprofen, and vegetables may reduce genetic risk of nonadvanced prostate cancer.

IMPACT

The effect of genetic factors on prostate cancer risk may vary by lifestyle interventions.

A genome-wide association study of serum levels of prostate-specific antigen in the Japanese population

BACKGROUND

Prostate-specific antigen (PSA) is a useful marker for prostate cancer (PCa) and is widely used for screening of PCa. Previous studies have shown that genetic components influence the levels of PSA, and some of these genetic components would lead to better diagnostic sensitivity and specificity to PCa. However, genetic studies for PSA from Asian countries are limited. Our aim was to identify genetic components influencing PSA levels in the Japanese population using genome-wide association study (GWAS) and to analyse whether genetic components would lead to better screening abilities of PCa.

METHODS

We performed a GWAS comprising 1086 male subjects using 303 283 single nucleotide proteins, followed by a replication study of 1302 subjects. PSA levels were quantified by chemiluminescence immunoassay method. Quantitative linear regression analysis was performed to assess genetic components of PSA levels. A total of 413 subjects with prostate biopsies were analysed to examine whether genetic determinants would improve diagnostic ability.

RESULTS

Rs16856139 in SLC45A3, the same region as the previous Chinese study, showed an overall significant association with PSA levels (p=2.4×10(-11)) along with rs1058205 in KLK3. In silico analysis revealed significant association between rs16856139 and expression of SLC45A3. Genetic scores of PSA showed a dose-dependent decrease of area under curve (AUC) of PCa and successfully subgrouped the individuals with significantly different AUC (p≤0.0097).

CONCLUSIONS

Rs16856139, associated with the expression of SLC45A3, is significantly associated with the levels of PSA in the Japanese population. Classification of subjects based on PSA genetic determinants would improve screening ability of PSA to detect PCa.

Prostate cancer (PCa) risk variants and risk of fatal PCa in the National Cancer Institute Breast and Prostate Cancer Cohort Consortium

BACKGROUND

Screening and diagnosis of prostate cancer (PCa) is hampered by an inability to predict who has the potential to develop fatal disease and who has indolent cancer. Studies have identified multiple genetic risk loci for PCa incidence, but it is unknown whether they could be used as biomarkers for PCa-specific mortality (PCSM).

OBJECTIVE

To examine the association of 47 established PCa risk single-nucleotide polymorphisms (SNPs) with PCSM.

DESIGN, SETTING, AND PARTICIPANTS

We included 10 487 men who had PCa and 11 024 controls, with a median follow-up of 8.3 yr, during which 1053 PCa deaths occurred.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

The main outcome was PCSM. The risk allele was defined as the allele associated with an increased risk for PCa in the literature. We used Cox proportional hazards regression to calculate the hazard ratios of each SNP with time to progression to PCSM after diagnosis. We also used logistic regression to calculate odds ratios for each risk SNP, comparing fatal PCa cases to controls.

RESULTS AND LIMITATIONS

Among the cases, we found that 8 of the 47 SNPs were significantly associated (p<0.05) with time to PCSM. The risk allele of rs11672691 (intergenic) was associated with an increased risk for PCSM, while 7 SNPs had risk alleles inversely associated (rs13385191 [C2orf43], rs17021918 [PDLIM5], rs10486567 [JAZF1], rs6465657 [LMTK2], rs7127900 (intergenic), rs2735839 [KLK3], rs10993994 [MSMB], rs13385191 [C2orf43]). In the case-control analysis, 22 SNPs were associated (p<0.05) with the risk of fatal PCa, but most did not differentiate between fatal and nonfatal PCa. Rs11672691 and rs10993994 were associated with both fatal and nonfatal PCa, while rs6465657, rs7127900, rs2735839, and rs13385191 were associated with nonfatal PCa only.

CONCLUSIONS

Eight established risk loci were associated with progression to PCSM after diagnosis. Twenty-two SNPs were associated with fatal PCa incidence, but most did not differentiate between fatal and nonfatal PCa. The relatively small magnitudes of the associations do not translate well into risk prediction, but these findings merit further follow-up, because they may yield important clues about the complex biology of fatal PCa.

PATIENT SUMMARY

In this report, we assessed whether established PCa risk variants could predict PCSM. We found eight risk variants associated with PCSM: One predicted an increased risk of PCSM, while seven were associated with decreased risk. Larger studies that focus on fatal PCa are needed to identify more markers that could aid prediction.

Analysis of candidate genes has proposed the role of y chromosome in human prostate cancer

BACKGROUND

Prostate cancer, a serious genetic disease, has known as the first widespread cancer in men, but the molecular changes required for the cancer progression has not fully understood. Availability of high-throughput gene expression data has led to the development of various computational methods, for identification of the critical genes, have involved in the cancer.

METHODS

In this paper, we have shown the construction of co-expression networks, which have been using Y-chromosome genes, provided an alternative strategy for detecting of new candidate, might involve in prostate cancer. In our approach, we have constructed independent co-expression networks from normal and cancerous stages have been using a reverse engineering approach. Then we have highlighted crucial Y chromosome genes involved in the prostate cancer, by analyzing networks, based on party and date hubs.

RESULTS

Our results have led to the detection of 19 critical genes, related to prostate cancer, which 12 of them have previously shown to be involved in this cancer. Also, essential Y chromosome genes have searched based on reconstruction of sub-networks which have led to the identification of 4 experimentally established as well as 4 new Y chromosome genes might be linked putatively to prostate cancer.

CONCLUSION

Correct inference of master genes, which mediate molecular, has changed during cancer progression would be one of the major challenges in cancer genomics. In this paper, we have shown the role of Y chromosome genes in finding of the prostate cancer susceptibility genes. Application of our approach to the prostate cancer has led to the establishment of the previous knowledge about this cancer as well as prediction of other new genes.

Genetic variation in KLK2 and KLK3 is associated with concentrations of hK2 and PSA in serum and seminal plasma in young men

BACKGROUND

Genetic variants in KLK2 and KLK3 have been associated with increased serum concentrations of their encoded proteins, human kallikrein-related peptidase 2 (hK2) and prostate-specific antigen (PSA), and with prostate cancer in older men. Low PSA concentrations in seminal plasma (SP) have been associated with low sperm motility. To evaluate whether KLK2 and KLK3 genetic variants affect physiological prostatic secretion, we studied the association of SNPs with hK2 and PSA concentrations in SP and serum of young, healthy men.

METHODS

Leukocyte DNA was extracted from 303 male military conscripts (median age 18.1 years). Nine SNPs across KLK2-KLK3 were genotyped. We measured PSA and hK2 in SP and serum using immunofluorometric assays. The association of genotype frequencies with hK2 and PSA concentrations was tested with the Kruskal-Wallis test.

RESULTS

Four KLK2 SNPs (rs198972, rs198977, rs198978, and rs80050017) were strongly associated with hK2 concentrations in SP and serum, with individuals homozygous for the major alleles having 3- to 7-fold higher concentrations than the intermediate concentrations found in other homozygotes and heterozygotes (all P < 0.001). Three of these SNPs were significantly associated with percentage of free PSA (%fPSA) in serum (all P < 0.007). Three KLK3 SNPs showed associations with PSA in SP, and the rs1058205 SNP was associated with total PSA in serum (P = 0.001) and %fPSA (P = 0.015).

CONCLUSIONS

Associations observed in young, healthy men between the SP and serum concentrations of hK2 and PSA and several genetic variants in KLK2 and KLK3 could be useful to refine models of PSA cutoff values in prostate cancer testing.

Genome-wide association studies on prostate cancer: the end or the beginning?

Prostate cancer (PCa) is the second most frequently diagnosed malignancy in men. Genome-wide association studies (GWAS) has been highly successful in discovering susceptibility loci for prostate cancer. Currently, more than twenty GWAS have identified more than fifty common variants associated with susceptibility with PCa. Yet with the increase in loci, voices from the scientific society are calling for more. In this review, we summarize current findings, discuss the common problems troubling current studies and shed light upon possible breakthroughs in the future. GWAS is the beginning of something wonderful. Although we are quite near the end of the beginning, post-GWAS studies are just taking off and future studies are needed extensively. It is believed that in the future GWAS information will be helpful to build a comprehensive system intergraded with PCa prevention, diagnosis, molecular classification, personalized therapy.

Association of Polymorphism rs198977 in Human Kallikrein-2 Gene (KLK2) with Susceptibility of Prostate Cancer: A Meta-Analysis

OBJECTIVES

To assess the association of polymorphism rs198977 in the human kallikrein-2 gene (KLK2) and risk of prostate cancer (PCa).

METHODS

Two investigators independently searched the PubMed, Elsevier, EMBASE, Web of Science, Wiley Online Library and Chinese National Knowledge Infrastructure (CNKI). Pooled odds ratios (ORs) and 95% confidence intervals (95% CIs) for rs198977 and PCa were calculated in a fixed-effects model (the Mantel-Haenszel method) and a random-effects model (the DerSimonian and Laird method) when appropriate.

RESULTS

Six studies met the inclusion criteria in this meta-analysis, which included 5859 PCa cases and 4867 controls. Overall, rs198977 was associated with the PCa risk (TT+CT vs. CC, pooled OR = 1.163, 95% CI = 1.076-1.258, P-value <0.0001). When stratified by ethnicity, significant association was observed in Caucasian samples under both allele comparison (T vs. C, pooled OR = 1.152, 95% CI = 1.079-1.229, P-value <0.0001) and dominant model (TT+CT vs. CC, pooled OR = 1.197, 95% CI = 1.104-1.297, P-value <0.0001). In the overall analysis, a comparably significant increase in the frequency of allele T for rs198977 was detected between cases and controls in Caucasian.

CONCLUSION

This meta-analysis suggests that rs198977 of KLK2 was associated with susceptibility of PCa in Caucasian and the allele T might increase the risk of PCa in Caucasian.

Common variation in Kallikrein genes KLK5, KLK6, KLK12, and KLK13 and risk of prostate cancer and tumor aggressiveness

The human tissue Kallikrein family consists of 15 genes with the majority shown to be differentially expressed in cancers and/or indicators of cancer prognosis. We sought to elucidate the role of common genetic variation in four of the Kallikrein genes, KLK5, KLK6, KLK12, and KLK13, in prostate cancer risk and tumor aggressiveness. Genotyping of all 22 tagging single nucleotide polymorphisms (tagSNPs) in the KLK5, KLK6, KLK12, and KLK13 genes was performed in approximately 1,000 prostate cancer cases and 1,300 male controls from Australia. Data from any positive results were also accessed for 1,844 cases and 1,886 controls from a previously published prostate cancer genome-wide association study set from the United Kingdom. For one SNP in KLK12, rs3865443, there was evidence for association with prostate cancer risk of similar direction and magnitude in the replication set to that seen in the Australian cohort. We conducted genotyping of a further 309 prostate cancer cases, and combined analyses revealed an increased risk of prostate cancer for carriers of the rare homozygous genotype for rs3865443 (OR 1.28, 95% CI 1.04-1.57; P = 0.018). No other tagSNPs in the KLK5, KLK6, and KLK13 genes were consistently associated with prostate cancer risk or tumor aggressiveness. Analysis of a combined sample of 3,153 cases and 3,199 controls revealed the KLK12 tagSNP rs3865443 to be marginally statistically significantly associated with risk of prostate cancer. Considering the total number of SNPs investigated in this study, this finding should be interpreted cautiously and requires additional validation from very large datasets such as those of the Prostate Cancer Association group to investigate cancer associated alterations (PRACTICAL) Consortium.

Very low PSA concentrations and deletions of the KLK3 gene

BACKGROUND

Prostate-specific antigen (PSA), a widely used biomarker for prostate cancer (PCa), is encoded by a kallikrein gene (KLK3, kallikrein-related peptidase 3). Serum PSA concentrations vary in the population, with PCa patients generally showing higher PSA concentrations than control individuals, although a small proportion of individuals in the population display very low PSA concentrations. We hypothesized that very low PSA concentrations might reflect gene-inactivating mutations in KLK3 that lead to abnormally reduced gene expression.

METHODS

We have sequenced all KLK3 exons and the promoter and searched for gross deletions or duplications in KLK3 in the 30 individuals with the lowest observed PSA concentrations in a sample of approximately 85 000 men from the Prostate Testing for Cancer and Treatment (ProtecT) study. The ProtecT study examines a community-based population of men from across the UK with little prior PSA testing.

RESULTS

We observed no stop codons or frameshift mutations, but we did find 30 single-base genetic variants, including 3 variants not described previously. These variants included missense variants that could be functionally inactivating and splicing variants. At this stage, however, we cannot confidently conclude whether these variants markedly lower PSA concentration or activity. More importantly, we identified 3 individuals with different large heterozygous deletions that encompass all KLK3 exons. The absence of a functional copy of KLK3 in these individuals is consistent with their reduced serum PSA concentrations.

CONCLUSIONS

The clinical interpretation of the PSA test for individuals with KLK3 gene inactivation could lead to false-negative PSA findings used for screening, diagnosis, or monitoring of PCa.

Design and analysis issues in gene and environment studies

Both nurture (environmental) and nature (genetic factors) play an important role in human disease etiology. Traditionally, these effects have been thought of as independent. This perspective is ill informed for non-mendelian complex disorders which result as an interaction between genetics and environment. To understand health and disease we must study how nature and nurture interact. Recent advances in human genomics and high-throughput biotechnology make it possible to study large numbers of genetic markers and gene products simultaneously to explore their interactions with environment. The purpose of this review is to discuss design and analytic issues for gene-environment interaction studies in the "-omics" era, with a focus on environmental and genetic epidemiological studies. We present an expanded environmental genomic disease paradigm. We discuss several study design issues for gene-environmental interaction studies, including confounding and selection bias, measurement of exposures and genotypes. We discuss statistical issues in studying gene-environment interactions in different study designs, such as choices of statistical models, assumptions regarding biological factors, and power and sample size considerations, especially in genome-wide gene-environment studies. Future research directions are also discussed.

Genetic association of the KLK4 locus with risk of prostate cancer

The Kallikrein-related peptidase, KLK4, has been shown to be significantly overexpressed in prostate tumours in numerous studies and is suggested to be a potential biomarker for prostate cancer. KLK4 may also play a role in prostate cancer progression through its involvement in epithelial-mesenchymal transition, a more aggressive phenotype, and metastases to bone. It is well known that genetic variation has the potential to affect gene expression and/or various protein characteristics and hence we sought to investigate the possible role of single nucleotide polymorphisms (SNPs) in the KLK4 gene in prostate cancer. Assessment of 61 SNPs in the KLK4 locus (± 10 kb) in approximately 1300 prostate cancer cases and 1300 male controls for associations with prostate cancer risk and/or prostate tumour aggressiveness (Gleason score <7 versus ≥ 7) revealed 7 SNPs to be associated with a decreased risk of prostate cancer at the P(trend)<0.05 significance level. Three of these SNPs, rs268923, rs56112930 and the HapMap tagSNP rs7248321, are located several kb upstream of KLK4; rs1654551 encodes a non-synonymous serine to alanine substitution at position 22 of the long isoform of the KLK4 protein, and the remaining 3 risk-associated SNPs, rs1701927, rs1090649 and rs806019, are located downstream of KLK4 and are in high linkage disequilibrium with each other (r(2) ≥ 0.98). Our findings provide suggestive evidence of a role for genetic variation in the KLK4 locus in prostate cancer predisposition.

Androgen metabolism and JAK/STAT pathway genes and prostate cancer risk

BACKGROUND

Prostate cancer (PC) is the most frequently diagnosed solid tumor in U.S. men. Genome-wide association studies (GWAS) have identified over 40 risk-associated single nucleotide polymorphisms (SNPs), including variants in androgen pathway genes (e.g., KLK3 and AR). Androgens are important in PC and genes involved in this pathway are therefore candidates for conferring susceptibility to PC.

METHODS

In this hypothesis-testing study, we evaluated PC risk in association with SNPs in 22 candidate genes involved in androgen metabolism or interactions with the androgen receptor (AR). A total of 187 SNPs were genotyped in 1458 cases and 1351 age-matched controls from a population-based study. PC risk was estimated using adjusted unconditional logistic regression and multinomial regression models.

RESULTS

Single SNP analyses showed evidence (p < 0.05) for associations with 14 SNPs in 9 genes: NKX3.1, HSD17B3, AKR1C3, SULT2A1, CYP17A1, KLK3, JAK2, NCOA4 and STAT3. The most significant result was observed for rs2253502 in HSD17B3 (odds ratio, OR = 0.57, 95% CI: 0.39-0.84). In addition, five SNPs in four genes (CYP17A1, HSD17B4, NCOA4, and SULT2A1) were associated with more aggressive disease (p < 0.01).

CONCLUSIONS

Our results replicate previously reported associations for SNPs in CYP17A1, HSD17B3, ARK1C3, NKX3.1, NCOA4 and KLK3. In addition, novel associations were observed for SNPs in JAK2, HSD17B4, and SULT2A1. These results will require replication in larger studies.

Utility of genome-wide association study findings: prostate cancer as a translational research paradigm

Genome-wide association studies have identified thousands of consistently replicated associations between genetic markers and complex disease risk, including cancers. Alone, these markers have limited utility in risk prediction; however, when several of these markers are used in combination, the predictive performance appears to be similar to that of many currently available clinical predictors. Despite this, there are divergent views regarding the clinical validity and utility of these genetic markers in risk prediction. There are valid concerns, thus providing a direction for new lines of research. Herein, we outline the debate and use the example of prostate cancer to highlight emerging evidence from studies that aim to address potential concerns. We also describe a translational framework that could be used to guide the development of a new generation of comprehensive research studies aimed at capitalizing on these exciting new discoveries.

Risk-based prostate cancer screening

CONTEXT

Widespread mass screening of prostate cancer (PCa) is not recommended because the balance between benefits and harms is still not well established. The achieved mortality reduction comes with considerable harm such as unnecessary biopsies, overdiagnoses, and overtreatment. Therefore, patient stratification with regard to PCa risk and aggressiveness is necessary to identify those men who are at risk and may actually benefit from early detection.

OBJECTIVE

This review critically examines the current evidence regarding risk-based PCa screening.

EVIDENCE ACQUISITION

A search of the literature was performed using the Medline database. Further studies were selected based on manual searches of reference lists and review articles.

EVIDENCE SYNTHESIS

Prostate-specific antigen (PSA) has been shown to be the single most significant predictive factor for identifying men at increased risk of developing PCa. Especially in men with no additional risk factors, PSA alone provides an appropriate marker up to 30 yr into the future. After assessment of an early PSA test, the screening frequency may be determined based on individualized risk. A limited list of additional factors such as age, comorbidity, prostate volume, family history, ethnicity, and previous biopsy status have been identified to modify risk and are important for consideration in routine practice. In men with a known PSA, risk calculators may hold the promise of identifying those who are at increased risk of having PCa and are therefore candidates for biopsy.

CONCLUSIONS

PSA testing may serve as the foundation for a more risk-based assessment. However, the decision to undergo early PSA testing should be a shared one between the patient and his physician based on information balancing its advantages and disadvantages.

Association between Prostinogen (KLK15) genetic variants and prostate cancer risk and aggressiveness in Australia and a meta-analysis of GWAS data

BACKGROUND

Kallikrein 15 (KLK15)/Prostinogen is a plausible candidate for prostate cancer susceptibility. Elevated KLK15 expression has been reported in prostate cancer and it has been described as an unfavorable prognostic marker for the disease.

OBJECTIVES

We performed a comprehensive analysis of association of variants in the KLK15 gene with prostate cancer risk and aggressiveness by genotyping tagSNPs, as well as putative functional SNPs identified by extensive bioinformatics analysis. METHODS AND DATA SOURCES: Twelve out of 22 SNPs, selected on the basis of linkage disequilibrium pattern, were analyzed in an Australian sample of 1,011 histologically verified prostate cancer cases and 1,405 ethnically matched controls. Replication was sought from two existing genome wide association studies (GWAS): the Cancer Genetic Markers of Susceptibility (CGEMS) project and a UK GWAS study.

RESULTS

Two KLK15 SNPs, rs2659053 and rs3745522, showed evidence of association (p<0.05) but were not present on the GWAS platforms. KLK15 SNP rs2659056 was found to be associated with prostate cancer aggressiveness and showed evidence of association in a replication cohort of 5,051 patients from the UK, Australia, and the CGEMS dataset of US samples. A highly significant association with Gleason score was observed when the data was combined from these three studies with an Odds Ratio (OR) of 0.85 (95% CI = 0.77-0.93; p = 2.7×10(-4)). The rs2659056 SNP is predicted to alter binding of the RORalpha transcription factor, which has a role in the control of cell growth and differentiation and has been suggested to control the metastatic behavior of prostate cancer cells.

CONCLUSIONS

Our findings suggest a role for KLK15 genetic variation in the etiology of prostate cancer among men of European ancestry, although further studies in very large sample sets are necessary to confirm effect sizes.

Genome-wide association study identifies new prostate cancer susceptibility loci

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

Genetics of prostate cancer risk

For decades, physicians and researchers have recognized that family history is a significant risk factor for prostate cancer. The identification of the genes responsible for inherited risk, however, proved difficult. With the sequencing of the human genome and the completion of the initial phases of the International HapMap Project, the tools are available to scan the entire genome and find genetic markers for disease. Since 2006, more than 30 inherited variants strongly associated with prostate cancer have been reported. As the inherited component of the disease is revealed, efforts are ongoing to translate genetic findings into the clinic.

Early detection of prostate cancer with emphasis on genetic markers

BACKGROUND

The recent advances in genomic research have made it possible to identify several new genomic-based biomarkers for prostate cancer. In this review we evaluate these new markers and speculate about future scenarios.

RESULTS

Today 35 single nucleotide polymorphisms (SNPs) have been identified and independently validated to associate with prostate cancer. These SNPs are common in the population (>5%) but the effect of these SNPs in these regions on prostate cancer risk is modest with odds ratios typically ranging between 1.1 and 1.3. It is estimated that these markers explain 25% of the familial risk of prostate cancer. However, it is anticipated that additional 50-75 prostate cancer SNPs will be identified in the near future. The SNPs associated with prostate cancer so far are not associated with disease stage or outcome. There are several efforts to identify germline genetic markers that can be used as prognostic markers. There are also tumor-based methods that are promising in identifying new genetic markers that can be easily measured in plasma or urine.

CONCLUSION

There are several new "genetic" markers that in the near future might be used in clinical routine. These markers are easy to measure and stable over time. However the challenge is not only to identify new biomarkers but the real test is to validate new biomarkers in several large well-characterized patient populations. This validation must be done together will all other known biomarkers at the same time as it not likely that one single marker is enough, but a panel of different markers. Today 2010 there are over 19 000 publications in the area of biomarkers and prostate cancer, but only one biomarker, PSA, is used in the clinic today!

Identification of a novel prostate cancer susceptibility variant in the KLK3 gene transcript

Genome-wide association studies (GWAS) have identified more than 30 prostate cancer (PrCa) susceptibility loci. One of these (rs2735839) is located close to a plausible candidate susceptibility gene, KLK3, which encodes prostate-specific antigen (PSA). PSA is widely used as a biomarker for PrCa detection and disease monitoring. To refine the association between PrCa and variants in this region, we used genotyping data from a two-stage GWAS using samples from the UK and Australia, and the Cancer Genetic Markers of Susceptibility (CGEMS) study. Genotypes were imputed for 197 and 312 single nucleotide polymorphisms (SNPs) from HapMap2 and the 1000 Genome Project, respectively. The most significant association with PrCa was with a previously unidentified SNP, rs17632542 (combined P = 3.9 × 10⁻²²). This association was confirmed by direct genotyping in three stages of the UK/Australian GWAS, involving 10,405 cases and 10,681 controls (combined P = 1.9 × 10⁻³⁴). rs17632542 is also shown to be associated with PSA levels and it is a non-synonymous coding SNP (Ile179Thr) in KLK3. Using molecular dynamic simulation, we showed evidence that this variant has the potential to introduce alterations in the protein or affect RNA splicing. We propose that rs17632542 may directly influence PrCa risk.

Genetic correction of PSA values using sequence variants associated with PSA levels

Measuring serum levels of the prostate-specific antigen (PSA) is the most common screening method for prostate cancer. However, PSA levels are affected by a number of factors apart from neoplasia. Notably, around 40% of the variability of PSA levels in the general population is accounted for by inherited factors, suggesting that it may be possible to improve both sensitivity and specificity by adjusting test results for genetic effects. To search for sequence variants that associate with PSA levels, we performed a genome-wide association study and follow-up analysis using PSA information from 15,757 Icelandic and 454 British men not diagnosed with prostate cancer. Overall, we detected a genome-wide significant association between PSA levels and single-nucleotide polymorphisms (SNPs) at six loci: 5p15.33 (rs2736098), 10q11 (rs10993994), 10q26 (rs10788160), 12q24 (rs11067228), 17q12 (rs4430796), and 19q13.33 [rs17632542 (KLK3: I179T)], each with P(combined) <3 × 10(-10). Among 3834 men who underwent a biopsy of the prostate, the 10q26, 12q24, and 19q13.33 alleles that associate with high PSA levels are associated with higher probability of a negative biopsy (odds ratio between 1.15 and 1.27). Assessment of association between the six loci and prostate cancer risk in 5325 cases and 41,417 controls from Iceland, the Netherlands, Spain, Romania, and the United States showed that the SNPs at 10q26 and 12q24 were exclusively associated with PSA levels, whereas the other four loci also were associated with prostate cancer risk. We propose that a personalized PSA cutoff value, based on genotype, should be used when deciding to perform a prostate biopsy.

Personalized prostate cancer screening: improving PSA tests with genomic information

The use of a prostate-specific antigen (PSA) test to screen for prostate cancer is controversial because of its modest predictive value and the potential overdiagnosis and over-treatment of the disease. A research article in this issue of Science Translational Medicine describes single-nucleotide polymorphisms (SNPs) in or near six genes that are independently associated with serum PSA concentrations and that help to explain interindividual PSA variation. Three of these SNPs are also associated with prostate biopsy outcomes. These findings are an important step toward incorporating genetic markers into PSA screening, with the ultimate goal of devising personalized PSA tests for use in the clinic.

Association of KLK3 (PSA) genetic variants with prostate cancer risk and PSA levels

Genome-wide association studies have identified genetic markers in kallikrein-related peptidase 3 (KLK3) associated with prostate cancer. However, some of these markers are also associated with prostate-specific antigen (PSA) levels, so it is unclear whether the polymorphisms are causal or if the association with risk is solely due to detection bias through PSA screening. PSA is a biologically active serine protease, cleaving insulin-like growth factor-binding protein. We examined the association of single-nucleotide polymorphisms (SNPs) in KLK3 with prostate cancer risk, disease-specific survival and pre-diagnostic PSA levels in a case-control study nested within the Physicians' Health Study, which began in 1982, with over 27 years of follow-up. We genotyped SNPs spanning the entire KLK3 locus to capture common variation at high resolution. Six polymorphisms were significantly associated with prostate cancer incidence (P < 0.05); the odds ratios per minor allele ranged from 0.88 to 0.73. For four of these, the odds ratios were lower when restricting to cases diagnosed in the pre-PSA screening era (before 1989). The four alleles significantly associated with lower PSA levels were also associated with lower prostate cancer risk. KLK3 variants were not significantly associated with stage at diagnosis, risk of lethal cancer or survival. Our results suggest that detection bias due to the association of KLK3 variants with PSA levels cannot completely explain the association with prostate cancer risk. Understanding the mechanism by which genetic variation in KLK3 affects prostate cancer risk has important implications for study of the biological role of PSA in prostate tumorigenesis.

Association of prostate cancer risk Loci with disease aggressiveness and prostate cancer-specific mortality

Genome-wide association studies have detected more than 30 inherited prostate cancer risk variants. While clearly associated with risk, their relationship with clinical outcome, particularly prostate cancer-specific mortality, is less well known. We investigated whether the risk variants are associated with various measures of disease aggressiveness and prostate cancer-specific mortality. In a cohort of 3,945 men of European ancestry with prostate cancer, we genotyped 36 single nucleotide polymorphisms (SNP): 35 known prostate cancer risk variants and one SNP (rs4054823) that was recently reported to be associated with prostate cancer aggressiveness. The majority of subjects had a diagnosis of prostate cancer between 1995 and 2004, and the cohort included a total of 580 prostate cancer-specific deaths. We evaluated associations between the 36 polymorphisms and prostate cancer survival, as well as other clinical parameters including age at diagnosis, prostate-specific antigen (PSA) at diagnosis, and Gleason score. Two SNPs, rs2735839 at chromosome 19q13 and rs7679673 at 4q24, were associated with prostate cancer-specific survival (P = 7 × 10(-4) and 0.014, respectively). A total of 12 SNPs were associated with other variables (P < 0.05): age at diagnosis, PSA at diagnosis, Gleason score, and/or disease aggressiveness based on D'Amico criteria. Genotype status at rs4054823 was not associated with aggressiveness or outcome. Our results identify two common polymorphisms associated with prostate cancer-specific mortality.

Characterizing associations and SNP-environment interactions for GWAS-identified prostate cancer risk markers--results from BPC3

Genome-wide association studies (GWAS) have identified multiple single nucleotide polymorphisms (SNPs) associated with prostate cancer risk. However, whether these associations can be consistently replicated, vary with disease aggressiveness (tumor stage and grade) and/or interact with non-genetic potential risk factors or other SNPs is unknown. We therefore genotyped 39 SNPs from regions identified by several prostate cancer GWAS in 10,501 prostate cancer cases and 10,831 controls from the NCI Breast and Prostate Cancer Cohort Consortium (BPC3). We replicated 36 out of 39 SNPs (P-values ranging from 0.01 to 10⁻²⁸). Two SNPs located near KLK3 associated with PSA levels showed differential association with Gleason grade (rs2735839, P = 0.0001 and rs266849, P = 0.0004; case-only test), where the alleles associated with decreasing PSA levels were inversely associated with low-grade (as defined by Gleason grade < 8) tumors but positively associated with high-grade tumors. No other SNP showed differential associations according to disease stage or grade. We observed no effect modification by SNP for association with age at diagnosis, family history of prostate cancer, diabetes, BMI, height, smoking or alcohol intake. Moreover, we found no evidence of pair-wise SNP-SNP interactions. While these SNPs represent new independent risk factors for prostate cancer, we saw little evidence for effect modification by other SNPs or by the environmental factors examined.

Prostate cancer predisposition loci and risk of metastatic disease and prostate cancer recurrence

PURPOSE

Genome-wide association studies (GWAS) have identified multiple novel prostate cancer predisposition loci. Whether these common genetic variants are associated with incident metastatic prostate cancer or with recurrence after surgical treatment for clinically localized prostate cancer is uncertain.

EXPERIMENTAL DESIGN

Twelve single nucleotide polymorphisms (SNPs) were selected for study in relation to prostate metastatic cancer and recurrence, based on their genome-wide association with prostate cancer in the Cancer Genetic Markers of Susceptibility (CGEMS). To assess risk for metastatic disease, we compared genotypes for the 12 SNPs by logistic regression of 470 incident metastatic prostate cancer cases and 1,945 controls in 3 case-control studies. To assess the relationship of these SNPs to risk for prostate cancer recurrence, we used Cox regression in a cohort of 1,412 men treated for localized prostate cancer, including 328 recurrences, and used logistic regression in a case-case study, comparing 450 recurrent versus 450 nonrecurrent prostate cancer cases. Study-specific relative risks (RRs) for risk of metastatic disease and recurrence were summarized using meta-analysis, with inverse variance weights.

RESULTS

MSMB rs10993994 (per variant allele summary RR = 1.24, 95% CI = 1.05-1.48), 8q24 rs4242382 (RR = 1.40, 95% CI = 1.13-1.75), and 8q24 rs6983267 (RR = 0.67, 95% CI = 0.50-0.89) were associated with risk for metastatic prostate cancer. None of the 12 SNPs was associated with prostate cancer recurrence.

CONCLUSIONS

SNPs in MSMB and 8q24 which predispose to prostate cancer overall are associated with risk for metastatic prostate cancer, the most lethal form of this disease. SNPs predictive of prostate cancer recurrence were not identified, among the predisposition SNPs. GWAS specific to these 2 phenotypes may identify additional phenotype-specific genetic determinants.

Fine mapping the KLK3 locus on chromosome 19q13.33 associated with prostate cancer susceptibility and PSA levels

Measurements of serum prostate-specific antigen (PSA) protein levels form the basis for a widely used test to screen men for prostate cancer. Germline variants in the gene that encodes the PSA protein (KLK3) have been shown to be associated with both serum PSA levels and prostate cancer. Based on a resequencing analysis of a 56 kb region on chromosome 19q13.33, centered on the KLK3 gene, we fine mapped this locus by genotyping tag SNPs in 3,522 prostate cancer cases and 3,338 controls from five case–control studies. We did not observe a strong association with the KLK3 variant, reported in previous studies to confer risk for prostate cancer (rs2735839; P = 0.20) but did observe three highly correlated SNPs (rs17632542, rs62113212 and rs62113214) associated with prostate cancer [P = 3.41 × 10⁻⁴, per-allele trend odds ratio (OR) = 0.77, 95% CI = 0.67–0.89]. The signal was apparent only for nonaggressive prostate cancer cases with Gleason score <7 and disease stage <III (P = 4.72 × 10⁻⁵, per-allele trend OR = 0.68, 95% CI = 0.57–0.82) and not for advanced cases with Gleason score >8 or stage ≥III (P = 0.31, per-allele trend OR = 1.12, 95% CI = 0.90–1.40). One of the three highly correlated SNPs, rs17632542, introduces a non-synonymous amino acid change in the KLK3 protein with a predicted benign or neutral functional impact. Baseline PSA levels were 43.7% higher in control subjects with no minor alleles (1.61 ng/ml, 95% CI = 1.49–1.72) than in those with one or more minor alleles at any one of the three SNPs (1.12 ng/ml, 95% CI = 0.96–1.28) (P = 9.70 × 10⁻⁵). Together our results suggest that germline KLK3 variants could influence the diagnosis of nonaggressive prostate cancer by influencing the likelihood of biopsy.

Meta-analysis of genome-wide and replication association studies on prostate cancer

BACKGROUND

Genome-wide and replication association studies (GWAs) have identified multiple loci at which common variants modestly influence the risk of developing prostate cancer (PCa). To enhance the power to identify loci associated with PCa, we constructed a meta-analysis of GWAs on PCa.

METHODS

Articles evaluating the effects of genome-wide SNPs on PCa were identified by searching the PubMed database. After extraction of relevant data, main and subgroup meta-analyses were performed to assess the effects of relevant SNPs on PCa.

RESULTS

21 eligible articles containing 71 subgroups were included in this meta-analysis. Significant associations were found between 31 SNPs and PCa. They were rs445114, rs620861, rs983085, rs1016343, rs1447295, rs1859962, rs2660753, rs2710646, rs2735839, rs3760511, rs4242382, rs4430796, rs4962416, rs5945572, rs5945619, rs6470494, rs6501455, rs6983267, rs6983561, rs7000448, rs7214479, rs7501939, rs7920517, rs7931342, rs9364554, rs9623117, rs10090154, rs10486567, rs10896449, rs10993994, and rs16901979. The weighted odds ratios for above SNPs ranged between 0.64 and 1.88 (all P < 0.05). Subgroup analysis further indicated that the significant associations of some SNPs existed only in specific ancestry population (P < 10⁻⁵).

CONCLUSIONS

The current meta-analysis demonstrated the moderate effects of above 31 SNPs on PCa and 14 independent PCa risk loci were identified.

Prediction of significant prostate cancer diagnosed 20 to 30 years later with a single measure of prostate-specific antigen at or before age 50

BACKGROUND

We previously reported that a single prostate-specific antigen (PSA) measured at ages 44-50 was highly predictive of subsequent prostate cancer diagnosis in an unscreened population. Here we report an additional 7 years of follow-up. This provides replication using an independent data set and allows estimates of the association between early PSA and subsequent advanced cancer (clinical stage ≥T3 or metastases at diagnosis).

METHODS

Blood was collected from 21,277 men in a Swedish city (74% participation rate) during 1974-1986 at ages 33-50. Through 2006, prostate cancer was diagnosed in 1408 participants; we measured PSA in archived plasma for 1312 of these cases (93%) and for 3728 controls.

RESULTS

At a median follow-up of 23 years, baseline PSA was strongly associated with subsequent prostate cancer (area under the curve, 0.72; 95% CI, 0.70-0.74; for advanced cancer, 0.75; 95% CI, 0.72-0.78). Associations between PSA and prostate cancer were virtually identical for the initial and replication data sets, with 81% of advanced cases (95% CI, 77%-86%) found in men with PSA above the median (0.63 ng/mL at ages 44-50).

CONCLUSIONS

A single PSA at or before age 50 predicts advanced prostate cancer diagnosed up to 30 years later. Use of early PSA to stratify risk would allow a large group of low-risk men to be screened less often but increase frequency of testing on a more limited number of high-risk men. This is likely to improve the ratio of benefit to harm for screening.

A common prostate cancer risk variant 5' of microseminoprotein-beta (MSMB) is a strong predictor of circulating beta-microseminoprotein (MSP) levels in multiple populations

BACKGROUND

β-Microseminoprotein (MSP) is one of the three most abundantly secreted proteins of the prostate and has been suggested as a biomarker for prostate cancer risk. A common variant, rs10993994, in the 5' region of the gene that encodes MSP (MSMB) has recently been identified as a risk factor for prostate cancer.

METHODS

We examined the association between rs10993994 genotype and MSP levels in a sample of 500 prostate cancer-free men from four racial/ethnic populations in the Multiethnic Cohort (European Americans, African Americans, Latinos, and Japanese Americans). Generalized linear models were used to estimate the association between rs10993994 genotype and MSP levels.

RESULTS

We observed robust associations between rs10994994 genotype and MSP levels in each racial/ethnic population (all P < 10(-8)), with carriers of the C allele having lower geometric mean MSP levels (ng/mL; CC/CT/TT genotypes: European Americans, 28.8/20.9/10.0; African Americans, 29.0/21.9/10.9; Latinos, 29.2/17.1/8.3; and Japanese Americans, 25.8/16.4/6.7). We estimated the variant accounts for 30% to 50% of the variation in MSP levels in each population. We also observed significant differences in MSP levels between populations (P = 3.5 × 10(-6)), with MSP levels observed to be highest in African Americans and lowest in Japanese Americans.

CONCLUSIONS

Rs10993994 genotype is strongly associated with plasma MSP levels in multiple racial/ethnic populations.

IMPACT

This supports the hypothesis that rs10993994 may be the biologically functional allele.

Kallikreins on steroids: structure, function, and hormonal regulation of prostate-specific antigen and the extended kallikrein locus

The 15 members of the kallikrein-related serine peptidase (KLK) family have diverse tissue-specific expression profiles and putative proteolytic functions. The kallikrein family is also emerging as a rich source of disease biomarkers with KLK3, commonly known as prostate-specific antigen, being the current serum biomarker for prostate cancer. The kallikrein locus is also notable because it is extraordinarily responsive to steroids and other hormones. Indeed, at least 14 functional hormone response elements have been identified in the kallikrein locus. A more comprehensive understanding of the transcriptional regulation of kallikreins may help the field make more informed hypotheses about the physiological functions of kallikreins and their effectiveness as biomarkers. In this review, we describe the organization of the kallikrein locus and the structure of kallikrein genes and proteins. We also focus on the transcriptional regulation of kallikreins by androgens, progestins, glucocorticoids, mineralocorticoids, estrogens, and other hormones in animal models and human prostate, breast, and reproductive tract tissues. The interaction of the androgen receptor with androgen response elements in the promoter and enhancer of KLK2 and KLK3 is also summarized in detail. There is evidence that all kallikreins are regulated by multiple nuclear receptors. Yet, apart from KLK2 and KLK3, it is not clear whether all kallikreins are direct transcriptional targets. Therefore, we argue that gaining more detailed information about the mechanisms that regulate kallikrein expression should be a priority of future studies and that the kallikrein locus will continue to be an important model in the era of genome-wide analyses.

Prostate cancer genomics: can we distinguish between indolent and fatal disease using genetic markers?

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

Susceptibility loci associated with prostate cancer progression and mortality

PURPOSE

Prostate cancer is a heterogeneous disease with a variable natural history that is not accurately predicted by currently used prognostic tools.

EXPERIMENTAL DESIGN

We genotyped 798 prostate cancer cases of Ashkenazi Jewish ancestry treated for localized prostate cancer between June 1988 and December 2007. Blood samples were prospectively collected and de-identified before being genotyped and matched to clinical data. The survival analysis was adjusted for Gleason score and prostate-specific antigen. We investigated associations between 29 single nucleotide polymorphisms (SNP) and biochemical recurrence, castration-resistant metastasis, and prostate cancer-specific survival. Subsequently, we did an independent analysis using a high-resolution panel of 13 SNPs.

RESULTS

On univariate analysis, two SNPs were associated (P<0.05) with biochemical recurrence, three SNPs were associated with clinical metastases, and one SNP was associated with prostate cancer-specific mortality. Applying a Bonferroni correction (P<0.0017), one association with biochemical recurrence (P=0.0007) was significant. Three SNPs showed associations on multivariable analysis, although not after correcting for multiple testing. The secondary analysis identified an additional association with prostate cancer-specific mortality in KLK3 (P<0.0005 by both univariate and multivariable analysis).

CONCLUSIONS

We identified associations between prostate cancer susceptibility SNPs and clinical end points. The rs61752561 in KLK3 and rs2735839 in the KLK2-KLK3 intergenic region were strongly associated with prostate cancer-specific survival, and rs10486567 in the 7JAZF1 gene were associated with biochemical recurrence. A larger study will be required to independently validate these findings and determine the role of these SNPs in prognostic models.