Evaluation of multiple risk-associated single nucleotide polymorphisms versus prostate-specific antigen at baseline to predict prostate cancer in unscreened men

Genetically adjusted PSA levels for prostate cancer screening

Prostate-specific antigen (PSA) screening for prostate cancer remains controversial because it increases overdiagnosis and overtreatment of clinically insignificant tumors. Accounting for genetic determinants of constitutive, non-cancer-related PSA variation has potential to improve screening utility. In this study, we discovered 128 genome-wide significant associations (P < 5 × 10-8) in a multi-ancestry meta-analysis of 95,768 men and developed a PSA polygenic score (PGSPSA) that explains 9.61% of constitutive PSA variation. We found that, in men of European ancestry, using PGS-adjusted PSA would avoid up to 31% of negative prostate biopsies but also result in 12% fewer biopsies in patients with prostate cancer, mostly with Gleason score <7 tumors. Genetically adjusted PSA was more predictive of aggressive prostate cancer (odds ratio (OR) = 3.44, P = 6.2 × 10-14, area under the curve (AUC) = 0.755) than unadjusted PSA (OR = 3.31, P = 1.1 × 10-12, AUC = 0.738) in 106 cases and 23,667 controls. Compared to a prostate cancer PGS alone (AUC = 0.712), including genetically adjusted PSA improved detection of aggressive disease (AUC = 0.786, P = 7.2 × 10-4). Our findings highlight the potential utility of incorporating PGS for personalized biomarkers in prostate cancer screening.

Biochemical activity induced by a germline variation in KLK3 (PSA) associates with cellular function and clinical outcome in prostate cancer

Genetic variation at the 19q13.3 KLK locus is linked with prostate cancer susceptibility. The non-synonymous KLK3 SNP, rs17632542 (c.536T>C; Ile163Thr-substitution in PSA) is associated with reduced prostate cancer risk, however, the functional relevance is unknown. Here, we identify that the SNP variant-induced change in PSA biochemical activity as a previously undescribed function mediating prostate cancer pathogenesis. The 'Thr' PSA variant led to small subcutaneous tumours, supporting reduced prostate cancer risk. However, 'Thr' PSA also displayed higher metastatic potential with pronounced osteolytic activity in an experimental metastasis in-vivo model. Biochemical characterization of this PSA variant demonstrated markedly reduced proteolytic activity that correlated with differences in in-vivo tumour burden. The SNP is associated with increased risk for aggressive disease and prostate cancer-specific mortality in three independent cohorts, highlighting its critical function in mediating metastasis. Carriers of this SNP allele had reduced serum total PSA and a higher free/total PSA ratio that could contribute to late biopsy decisions and delay in diagnosis. Our results provide a molecular explanation for the prominent 19q13.3 KLK locus, rs17632542 SNP, association with a spectrum of prostate cancer clinical outcomes.

Genetic polymorphisms at 19q13.33 are associated with [-2]proPSA (p2PSA) levels and provide additional predictive value to prostate health index for prostate cancer

BACKGROUND

Prostate health index (phi), a derivative of [-2]proPSA (p2PSA), has shown better accuracy than prostate-specific antigen (PSA) in prostate cancer (PCa) detection. The present study was to investigate whether previously identified PSA-associated single nucleotide polymorphisms (SNPs) influence p2PSA or phi levels and lead to potential clinical utility.

METHODS

We conducted an observational prospective study with 2268 consecutive patients who underwent prostate biopsy in three tertiary medical centers from August 2013 to March 2019. Genotyping data of the 46 candidate genes with a ± 100 kb window were tested for association with p2PSA and phi levels using linear regression. Multivariable logistic regression models were performed and internally validated using repeated tenfold cross-validation. We further calculated personalized phi cutoff values based on the significant genotypes. Discriminative performance was assessed using decision curve analysis and net reclassification improvement (NRI) index.

RESULTS

We detected 11 significant variants at 19q13.33 which were p2PSA-associated independent of PCa. The most significant SNP, rs198978 in KLK2 (P_combined  = 5.73 × 10^-9 ), was also associated with phi values (P_combined  = 3.20 × 10^-6 ). Compared to the two commonly used phi cutoffs of 27.0 and 36.0, the personalized phi cutoffs had a significant NRI for PCa ranged from 5.23% to 9.70% among men carrying variant types (all p < .01).

CONCLUSION

Rs198978, is independently associated with p2PSA values, and can improve the diagnostic ability of phi for PCa using personalized cutoff values.

Comprehensive Analysis of Multiple Cohort Datasets Deciphers the Utility of Germline Single-Nucleotide Polymorphisms in Prostate Cancer Diagnosis

Prostate cancer susceptibility is a polygenic trait. We aimed to examine the controversial diagnostic utility of single-nucleotide polymorphisms (SNP) for prostate cancer. We analyzed two datasets collected from Europeans and one from Africans. These datasets were generated by the genome-wide association studies, that is, CGEMS, BPC3, and MEC-Africans, respectively. About 540,000 SNPs, including 61 risk markers that constitute a panel termed MK-61, were commonly genotyped. For each dataset, we augmented the MK-61 panel to generate an MK-61⁺ one by adding several thousands of SNPs that were moderately associated with prostate cancer occurrence in external dataset(s). We assessed the diagnostic utility of both panels by measuring their predictive strength for prostate cancer occurrence with AUC statistics. We calculated the theoretical AUCs using quantitative genetics model-based formulae and obtained the empirical estimates via 10-fold cross-validation using statistical and machine learning techniques. For the MK-61 panel, the 95% confidence intervals of the theoretical AUCs (AUC-CI.95) were 0.578-0.655, 0.596-0.656, and 0.539-0.596 in the CGEMS, BPC3, and MEC-Africans cohorts, respectively. For the MK-61⁺ panels, the corresponding AUC-CI.95 were 0.617-0.663, 0.527-0.736, and 0.547-0.565. The empirical AUCs largely fell within the theoretical interval. A promising result (AUC = 0.703, FNR = 0.354, FPR = 0.353) was obtained in the BPC3 cohort when the MK-61⁺ panel was used. In the CGEMS cohort, the MK-61⁺ panel complemented PSA in predicting the disease status of PSA ≥ 2.0 ng/mL samples. This study demonstrates that augmented risk SNP panels can enhance prostate cancer prediction for males of European ancestry, especially those with [Formula: see text]ng/mL. PREVENTION RELEVANCE: This study demonstrates that augmented risk SNP panels can enhance prostate cancer prediction for males of European ancestry, especially those with PSA ≥ 2 ng/mL.

Single nucleotide polymorphisms (SNPs) in prostate cancer: its implications in diagnostics and therapeutics

Prostate cancer is one of the most frequently diagnosed malignancies in developed countries and approximately 248,530 new cases of prostate cancer are likely to be diagnosed in the United States in 2021. During the late 1990s and 2000s, the prostate cancer-related death rate has decreased by 4% per year on average because of advancements in prostate-specific antigen (PSA) testing. However, the non-specificity of PSA to distinguish between benign and malignant forms of cancer is a major concern in the management of prostate cancer. Despite other risk factors in the pathogenesis of prostate cancer, recent advancement in molecular genetics suggests that genetic heredity plays a crucial role in prostate carcinogenesis. Approximately, 60% of heritability and more than 100 well-recognized single-nucleotide-polymorphisms (SNPs) have been found to be associated with prostate cancer and constitute a major risk factor in the development of prostate cancer. Recent findings revealed that a low to moderate effect on the progression of prostate cancer of individual SNPs was observed compared to a strong progressive effect when SNPs were in combination. Here, in this review, we made an attempt to critically analyze the role of SNPs and associated genes in the development of prostate cancer and their implications in diagnostics and therapeutics. A better understanding of the role of SNPs in prostate cancer susceptibility may improve risk prediction, enhance fine-mapping, and furnish new insights into the underlying pathophysiology of prostate cancer.

Functional roles of antisense enhancer RNA for promoting prostate cancer progression

Rationale: Enhancer RNA (eRNA) bi-directionally expresses from enhancer region and sense eRNA regulates adjacent mRNA in cis and in trans. However, it has remained unclear whether antisense eRNAs in different direction are functional or merely a reflection of enhancer activation. Methods: Strand-specific, ribosome-minus RNA sequencing (RNA-seq) were performed in AR positive prostate cancer cells. RNA-seq, GRO-seq, ChIP-seq, 4C-seq and DNA-methylation-seq that published in our and other labs were re-analyzed to define bi-directional enhancer RNA and DNA methylation regions. Molecular mechanisms were demonstrated by 3C, ChIP, ChIRP, CLIP, RT-PCR and western blot assays. The biological functions of antisense-eRNA were assessed using mice xenograft model and RT-PCR analysis in human tissues. Results: In this study, we identified that antisense eRNA was regulated by androgen receptor (AR) activity in prostate cancer cells. Antisense eRNA negatively regulated antisense ncRNA in AR-related target genes' loci, through recruiting DNMT1 on the antisense enhancer in the gene-ending regions and elevating DNA methylation. Importantly, the chromatin exhibited a double looping manner that facilitated sense-eRNA to promoter and antisense-eRNA to gene-ending region in cis. Depletion of antisense eRNA impaired its neighbor mRNA expression, cancer growth and invasion. The expressions of antisense eRNA were correlated with biochemical recurrence and clinical marker PSA's levels in patients' tissues. Conclusions: The findings indicated that antisense eRNA was a functional RNA and may be a novel target that when suppressed improved prostate cancer therapy and diagnosis. New chromatin interaction among enhancer, promoter and gene-ending region might provide new insight into the spatiotemporal mechanism of the gene transcription and acting of bi-directional eRNAs.

Genome-wide association study identifies novel single nucleotide polymorphisms having age-specific effect on prostate-specific antigen levels

BACKGROUND

Testing for prostate-specific antigen (PSA) levels in blood are widely used and associated with prostate cancer risk and outcome. After puberty, PSA levels increase by age and multiple single nucleotide polymorphisms (SNPs) have been found to be associated with PSA levels. However, the relationship between the effects of SNPs and age on PSA remains unknown.

METHODS

To test for SNP × age interaction, we conducted a genome-wide association study using 2394 men without prostate cancer diagnosis from Malmö, Sweden as a discovery set and 2137 men from the eMERGE study (USA) for validation. Linear regression was used to identify significant interactions between SNP and age (p < 1 × 10-4 for discovery, p < .05 for validation).

RESULTS

The 15 SNPs from three different loci (8p11.22, 8p12, 3q25.31) are found to have age-specific effect on PSA levels. Expression quantitative trait loci (eQTLs) analysis shows that 12 SNPs from 3q25.31 locus affect the expression level of three genes: KCNAB1, SLC33A1, PLCH1.

CONCLUSIONS

Our results suggest that SNPs may have age-specific effect on PSA levels, which provides new direction to study genetic markers for PSA.

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.

Prostate Cancer Risk-Associated Single-Nucleotide Polymorphism Affects Prostate-Specific Antigen Glycosylation and Its Function

BACKGROUND

Genetic association studies have reported single-nucleotide polymorphisms (SNPs) at chromosome 19q13.3 to be associated with prostate cancer (PCa) risk. Recently, the rs61752561 SNP (Asp84Asn substitution) in exon 3 of the kallikrein-related peptidase 3 (KLK3) gene encoding prostate-specific antigen (PSA) was reported to be strongly associated with PCa risk (P = 2.3 × 10^-8). However, the biological contribution of the rs61752561 SNP to PCa risk has not been elucidated.

METHODS

Recombinant PSA protein variants were generated to assess the SNP-mediated biochemical changes by stability and substrate activity assays. PC3 cell-PSA overexpression models were established to evaluate the effect of the SNP on PCa pathogenesis. Genotype-specific correlation of the SNP with total PSA (tPSA) concentrations and free/total (F/T) PSA ratio were determined from serum samples.

RESULTS

Functional analysis showed that the rs61752561 SNP affects PSA stability and structural conformation and creates an extra glycosylation site. This PSA variant had reduced enzymatic activity and the ability to stimulate proliferation and migration of PCa cells. Interestingly, the minor allele is associated with lower tPSA concentrations and high F/T PSA ratio in serum samples, indicating that the amino acid substitution may affect PSA immunoreactivity to the antibodies used in the clinical immunoassays.

CONCLUSIONS

The rs61752561 SNP appears to have a potential role in PCa pathogenesis by changing the glycosylation, protein stability, and PSA activity and may also affect the clinically measured F/T PSA ratio. Accounting for these effects on tPSA concentration and F/T PSA ratio may help to improve the accuracy of the current PSA test.

Genome-wide Scan Identifies Role for AOX1 in Prostate Cancer Survival

BACKGROUND

Most men diagnosed with prostate cancer have low-risk cancers. How to predict prostate cancer progression at the time of diagnosis remains challenging.

OBJECTIVE

To identify single nucleotide polymorphisms (SNPs) associated with death from prostate cancer.

DESIGN, SETTING, AND PARTICIPANTS

Blood samples from 11 506 men in Sweden were collected during 1991-1996. Of these, 1053 men were diagnosed with prostate cancer and 245 died from the disease. Stage and grade at diagnosis and outcome information were obtained, and DNA from all cases was genotyped.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

A total of 6 126 633 SNPs were tested for association with prostate-cancer-specific survival time using a Cox proportional hazard model, adjusted for age, stage, and grade at diagnosis. A value of 1×10^-6 was used as suggestive significance threshold. Positive candidate SNPs were tested for association with gene expression using expression quantitative trait locus analysis.

RESULTS AND LIMITATIONS

We found 12 SNPs at seven independent loci associated with prostate-cancer-specific survival time. One of 6 126 633 SNPs tested reached genome-wide significance (p<5×10^-8) and replicated in an independent cohort: rs73055188 (p=5.27×10^-9, per-allele hazard ratio [HR]=2.27, 95% confidence interval [CI] 1.72-2.98) in the AOX1 gene. A second SNP reached a suggestive level of significance (p<1×10^-6) and replicated in an independent cohort: rs2702185 (p=7.1×10^-7, per-allele HR=2.55, 95% CI=1.76-3.69) in the SMG7 gene. The SNP rs73055188 is correlated with AOX1 expression levels, which is associated with biochemical recurrence of prostate cancer in independent cohorts. This association is yet to be validated in other ethnic groups.

CONCLUSIONS

The SNP rs73055188 at the AOX1 locus is associated with prostate-cancer-specific survival time, and AOX1 gene expression level is correlated with biochemical recurrence of prostate cancer.

PATIENT SUMMARY

We identify two genetic markers that are associated with prostate-cancer-specific survival time.

Genomic Markers in Prostate Cancer Decision Making

CONTEXT

Although the widespread use of prostate-specific antigen (PSA) has led to an early detection of prostate cancer (PCa) and a reduction of metastatic disease at diagnosis, PSA remains one of the most controversial biomarkers due to its limited specificity. As part of emerging efforts to improve both detection and management decision making, a number of new genomic tools have recently been developed.

OBJECTIVE

This review summarizes the ability of genomic biomarkers to recognize men at high risk of developing PCa, discriminate clinically insignificant and aggressive tumors, and facilitate the selection of therapies in patients with advanced disease.

EVIDENCE ACQUISITION

A PubMed-based literature search was conducted up to May 2017. We selected the most recent and relevant original articles and clinical trials that have provided indispensable information to guide treatment decisions.

EVIDENCE SYNTHESIS

Genome-wide association studies have identified several genetic polymorphisms and inherited variants associated with PCa susceptibility. Moreover, the urine-based assays SelectMDx, Mi-Prostate Score, and ExoDx have provided new insights into the identification of patients who may benefit from prostate biopsy. In men with previous negative pathological findings, Prostate Cancer Antigen 3 and ConfirmMDx predicted the outcome of subsequent biopsy. Commercially available tools (Decipher, Oncotype DX, and Prolaris) improved PCa risk stratification, identifying men at the highest risk of adverse outcome. Furthermore, other biomarkers could assist in treatment selection in castration-resistant PCa. AR-V7 expression predicts resistance to abiraterone/enzalutamide, while poly(ADP-ribose) polymerase-1 inhibitor and platinum-based chemotherapy could be indicated in metastatic patients who are carriers of mutations in DNA mismatch repair genes.

CONCLUSIONS

Introduction of genomic biomarkers has dramatically improved the detection, prognosis, and risk evaluation of PCa. Despite the progress made in discovering suitable biomarker candidates, few have been used in a clinical setting. Large-scale and multi-institutional studies are required to validate the efficacy and cost utility of these new technologies.

PATIENT SUMMARY

Prostate cancer is a heterogeneous disease with a wide variability. Genomic biomarkers in combination with clinical and pathological variables are useful tools to reduce the number of unnecessary biopsies, stratify low-risk from high-risk tumors, and guide personalized treatment decisions.

Plasma enterolactone and risk of prostate cancer in middle-aged Swedish men

Purpose

Enterolactone (ENL) is formed in the human gut after consumption of lignans, has estrogenic properties, and has been associated with risk of prostate cancer. We examined the association between plasma ENL levels and prostate cancer in a nested case–control study within the population-based Malmö Diet and Cancer cohort. We also examined the association between plasma ENL and dietary and lifestyle factors.

Methods

The study population consisted of 1010 cases occurring during a mean follow-up of 14.6 years, and 1817 controls matched on age and study entry date. We used national registers (95%) and hospital records (5%) to ascertain cases. Diet was estimated by a modified diet history method. Plasma ENL concentrations were determined by a time-resolved fluoroimmunoassay. Odds ratios were calculated by unconditional logistic regression.

Results

There were no significant associations between plasma ENL and incidence of all prostate cancer (odds ratio 0.99 [95% confidence interval 0.77–1.280] for the highest ENL quintile versus lowest, p for trend 0.66). However, in certain subgroups of men, including men with abdominal obesity (p for interaction = 0.012), we observed associations between high ENL levels and lower odds of high-risk prostate cancer. Plasma ENL was positively associated with consumption of high-fibre bread, fruit, tea, and coffee; with age, and with height, while it was negatively associated with smoking and waist circumference; however, although significant, all associations were rather weak (r ≤ |0.14|).

Conclusion

ENL concentration was not consistently associated with lower prostate cancer risk, although it was weakly associated with a healthy lifestyle.

Electronic supplementary material

The online version of this article (doi:10.1007/s00394-017-1530-z) contains supplementary material, which is available to authorized users.

Population-standardized genetic risk score: the SNP-based method of choice for inherited risk assessment of prostate cancer

Several different approaches are available to clinicians for determining prostate cancer (PCa) risk. The clinical validity of various PCa risk assessment methods utilizing single nucleotide polymorphisms (SNPs) has been established; however, these SNP-based methods have not been compared. The objective of this study was to compare the three most commonly used SNP-based methods for PCa risk assessment. Participants were men (n = 1654) enrolled in a prospective study of PCa development. Genotypes of 59 PCa risk-associated SNPs were available in this cohort. Three methods of calculating SNP-based genetic risk scores (GRSs) were used for the evaluation of individual disease risk such as risk allele count (GRS-RAC), weighted risk allele count (GRS-wRAC), and population-standardized genetic risk score (GRS-PS). Mean GRSs were calculated, and performances were compared using area under the receiver operating characteristic curve (AUC) and positive predictive value (PPV). All SNP-based methods were found to be independently associated with PCa (all P < 0.05; hence their clinical validity). The mean GRSs in men with or without PCa using GRS-RAC were 55.15 and 53.46, respectively, using GRS-wRAC were 7.42 and 6.97, respectively, and using GRS-PS were 1.12 and 0.84, respectively (all P < 0.05 for differences between patients with or without PCa). All three SNP-based methods performed similarly in discriminating PCa from non-PCa based on AUC and in predicting PCa risk based on PPV (all P > 0.05 for comparisons between the three methods), and all three SNP-based methods had a significantly higher AUC than family history (all P < 0.05). Results from this study suggest that while the three most commonly used SNP-based methods performed similarly in discriminating PCa from non-PCa at the population level, GRS-PS is the method of choice for risk assessment at the individual level because its value (where 1.0 represents average population risk) can be easily interpreted regardless of the number of risk-associated SNPs used in the calculation.

Genome-wide association study of prostate-specific antigen levels identifies novel loci independent of prostate cancer

Prostate-specific antigen (PSA) levels have been used for detection and surveillance of prostate cancer (PCa). However, factors other than PCa—such as genetics—can impact PSA. Here we present findings from a genome-wide association study (GWAS) of PSA in 28,503 Kaiser Permanente whites and 17,428 men from replication cohorts. We detect 40 genome-wide significant (P<5 × 10⁻⁸) single-nucleotide polymorphisms (SNPs): 19 novel, 15 previously identified for PSA (14 of which were also PCa-associated), and 6 previously identified for PCa only. Further analysis incorporating PCa cases suggests that at least half of the 40 SNPs are PSA-associated independent of PCa. The 40 SNPs explain 9.5% of PSA variation in non-Hispanic whites, and the remaining GWAS SNPs explain an additional 31.7%; this percentage is higher in younger men, supporting the genetic basis of PSA levels. These findings provide important information about genetic markers for PSA that may improve PCa screening, thereby reducing over-diagnosis and over-treatment.

Prostate-specific antigen is used as a biomarker of prostate cancer, but levels can be affected by other factors not related to cancer. Here, the authors find genes associated with prostate specific antigen levels in healthy men, which could be used to reduce over-diagnosis and over-treatment.

Beyond prostate-specific antigen: utilizing novel strategies to screen men for prostate cancer

PURPOSE OF REVIEW

The purpose of this article is to review blood and urine tests that are currently available and under investigation for a role in prostate cancer screening and detection.

RECENT FINDINGS

Compared with total prostate-specific antigen (PSA) alone, its combination with percentage free-to-total PSA contributes greater specificity for prostate cancer, and is a component of two newer blood tests called the 4kScore and Prostate Health Index. All three tests improve the prediction of high-grade disease and are commercially available options to aid in initial or repeat prostate biopsy decisions. PCA3 is a urinary marker that is currently available for repeat prostate biopsy decisions. Although PCA3 alone has inferior prediction of clinically significant disease and requires collection of urine after digital rectal examination, it may be combined with other clinical variables or other urine markers like TMPRSS2:ERG to improve performance. Little data are available to support a role for single nucleotide polymorphisms or other investigational markers in early detection.

SUMMARY

Several commercially available blood and urine tests have been shown to improve specificity of PSA for high-grade prostate cancer. Use of such tests would decrease unnecessary biopsy and overdiagnosis of indolent disease. Biopsy of men with moderately elevated PSA without use of such a reflex test should be discouraged.

Influence of age on predictiveness of genetic risk score for prostate cancer in a Chinese hospital-based biopsy cohort

Background

We investigated whether age influences the predictiveness of genetic risk score (GRS) for prostate cancer (PCa) in a Chinese hospital-based biopsy cohort.

Methods

We included consecutive patients who underwent prostate biopsies in two tertiary centers between 2012 and 2014. GRS was calculated using 24 PCa-associated genetic variants and its predictiveness was assessed by area under curve (AUC).

Results

Of 1120 men tested, 724 with prostate-specific antigen (PSA) < 20 ng/ml were selected for further analysis. Patients were divided into 3 groups by age cutoffs at 60 and 70 years. GRS significantly predicted PCa for all patients (AUC: 0.561; 95% CI: 0.514–0.609) and was an independent predictor in multivariate analysis for the 60–70 year-olds (AUC: 0.612, 95% CI: 0.541–0.684), but not for patients aged < 60 years or ≥70 years. For PCa with Gleason score ≥7, GRS discriminative ability was 0.582 (95% CI=0.527–0.637) for all patients, and 0.647 (95% CI: 0.541–0.684) for the 60–70 year-old group.

Conclusion

GRS significantly increased clinical prediction of PCa and high-grade disease in Chinese men aged 60–70 years, which implies that men in this age group would benefit most from genetic testing.

Association between 17q25.3-rs6465657 polymorphism and prostate cancer susceptibility: a meta-analysis based on 19 studies

Background

Genome-wide association studies have identified rs6465657 polymorphism at chromosome 17q25.3 as a new prostate cancer (PCa) susceptibility locus in people of European descent. However, subsequent replication studies have yielded inconsistent results among different ethnicities. In this study, a comprehensive meta-analysis was conducted to systematically evaluate the relationship between rs6465657 polymorphism and PCa risk.

Methods

All the articles involved were identified from PubMed, EMBASE, Web of Science, EBSCO databases, and Google Scholar before December 2015. The odds ratios (ORs) with corresponding 95% confidence internals (95% CIs) were pooled under the allele model. Fourteen eligible articles with 19 studies were finally included.

Results

In the overall population, the 17q25.3-rs6465657C allele was found to be significantly associated with increased risk of PCa compared to the T allele (OR =1.097; 95% CI: 1.061–1.134; P<0.001). In the subgroup analysis stratified by ethnicity, significantly increased risk was found in the Caucasian population (OR =1.120; 95% CI: 1.078–1.162; P<0.001), while the difference of OR did not reach the statistical significance in the Asian or African-American population. The analyses of sensitivity indicated the robust stability of the results, and the Begg’s and Egger’s test indicated that no publication bias existed.

Conclusion

The current meta-analysis suggested that the 17q25.3-rs6465657 polymorphism could be associated with PCa susceptibility, especially in the Caucasians, while this association might be different in other ethnicities.

The PROFILE Feasibility Study: Targeted Screening of Men With a Family History of Prostate Cancer

BACKGROUND

A better assessment of individualized prostate cancer (PrCa) risk is needed to improve screening. The use of the prostate-specific antigen (PSA) level for screening in the general population has limitations and is not currently advocated. Approximately 100 common single nucleotide polymorphisms (SNPs) have been identified that are associated with the risk of developing PrCa. The PROFILE pilot study explored the feasibility of using SNP profiling in men with a family history (FH) of PrCa to investigate the probability of detecting PrCa at prostate biopsy (PB). The primary aim of this pilot study was to determine the safety and feasibility of PrCa screening using transrectal ultrasound-guided PB with or without diffusion-weighted magnetic resonance imaging (DW-MRI) in men with a FH. A secondary aim was to evaluate the potential use of SNP profiling as a screening tool in this population.

PATIENTS AND METHODS

A total of 100 men aged 40-69 years with a FH of PrCa underwent PB, regardless of their baseline PSA level. Polygenic risk scores (PRSs) were calculated for each participant using 71 common PrCa susceptibility alleles. We treated the disease outcome at PB as the outcome variable and evaluated its associations with the PRS, PSA level, and DW-MRI findings using univariate logistic regression.

RESULTS

Of the 100 men, 25 were diagnosed with PrCa, of whom 12 (48%) had clinically significant disease. Four adverse events occurred and no deaths. The PSA level and age at study entry were associated with PrCa at PB (p = .00037 and p = .00004, respectively).

CONCLUSION

The results of the present pilot study have demonstrated that PB is a feasible and safe method of PrCa screening in men with a FH, with a high proportion of PrCa identified requiring radical treatment. It is feasible to collect data on PrCa-risk SNPs to evaluate their combined effect as a potential screening tool. A larger prospective study powered to detect statistical associations is in progress.

IMPLICATIONS FOR PRACTICE

Prostate biopsy is a feasible and safe approach to prostate cancer screening in men with a family history and detects a high proportion of prostate cancer that needs radical treatment. Calculating a polygenic risk score using prostate cancer risk single nucleotide polymorphisms could be a potential future screening tool for prostate cancer.

Microseminoprotein-Beta Expression in Different Stages of Prostate Cancer

Microseminoprotein-beta (MSMB, MSMB) is an abundant secretory protein contributed by the prostate, and is implicated as a prostate cancer (PC) biomarker based on observations of its lower expression in cancerous cells compared with benign prostate epithelium. However, as the current literature on MSMB is inconsistent, we assessed the expression of MSMB at the protein and mRNA levels in a comprehensive set of different clinical stages of PC. Immunohistochemistry using monoclonal and polyclonal antibodies against MSMB was used to study protein expression in tissue specimens representing prostatectomies (n = 261) and in diagnostic needle biopsies from patients treated with androgen deprivation therapy (ADT) (n = 100), and in locally recurrent castration-resistant PC (CRPC) (n = 105) and CRPC metastases (n = 113). The transcript levels of MSMB, nuclear receptor co-activator 4 (NCOA4) and MSMB-NCOA4 fusion were examined by qRT-PCR in prostatectomy samples and by RNA-sequencing in benign prostatic hyperplasia, PC, and CRPC samples. We also measured serum MSMB levels and genotyped the single nucleotide polymorphism rs10993994 using DNA from the blood of 369 PC patients and 903 controls. MSMB expression in PC (29% of prostatectomies and 21% of needle biopsies) was more frequent than in CRPC (9% of locally recurrent CRPCs and 9% of CRPC metastases) (p<0.0001). Detection of MSMB protein was inversely correlated with the Gleason score in prostatectomy specimens (p = 0.024). The read-through MSMB-NCOA4 transcript was detected at very low levels in PC. MSMB levels in serum were similar in cases of PC and controls but were significantly associated with PC risk when adjusted for age at diagnosis and levels of free or total PSA (p<0.001). Serum levels of MSMB in both PC patients and controls were significantly associated with the rs10993994 genotype (p<0.0001). In conclusion, decreased expression of MSMB parallels the clinical progression of PC and adjusted serum MSMB levels are associated with PC risk.

Improved prediction of complex diseases by common genetic markers: state of the art and further perspectives

Reliable risk assessment of frequent, but treatable diseases and disorders has considerable clinical and socio-economic relevance. However, as these conditions usually originate from a complex interplay between genetic and environmental factors, precise prediction remains a considerable challenge. The current progress in genotyping technology has resulted in a substantial increase of knowledge regarding the genetic basis of such diseases and disorders. Consequently, common genetic risk variants are increasingly being included in epidemiological models to improve risk prediction. This work reviews recent high-quality publications targeting the prediction of common complex diseases. To be included in this review, articles had to report both, numerical measures of prediction performance based on traditional (non-genetic) risk factors, as well as measures of prediction performance when adding common genetic variants to the model. Systematic PubMed-based search finally identified 55 eligible studies. These studies were compared with respect to the chosen approach and methodology as well as results and clinical impact. Phenotypes analysed included tumours, diabetes mellitus, and cardiovascular diseases. All studies applied one or more statistical measures reporting on calibration, discrimination, or reclassification to quantify the benefit of including SNPs, but differed substantially regarding the methodological details that were reported. Several examples for improved risk assessments by considering disease-related SNPs were identified. Although the add-on benefit of including SNP genotyping data was mostly moderate, the strategy can be of clinical relevance and may, when being paralleled by an even deeper understanding of disease-related genetics, further explain the development of enhanced predictive and diagnostic strategies for complex diseases.

Replication study of 34 common SNPs associated with prostate cancer in the Romanian population

Prostate cancer is the third‐most common form of cancer in men in Romania. The Romanian unscreened population represents a good sample to study common genetic risk variants. However, a comprehensive analysis has not been conducted yet. Here, we report our replication efforts in a Romanian population of 979 cases and 1027 controls, for potential association of 34 literature‐reported single nucleotide polymorphisms (SNPs) with prostate cancer. We also examined whether any SNP was differentially associated with tumour grade or stage at diagnosis, with disease aggressiveness, and with the levels of PSA (prostate specific antigen). In the allelic analysis, we replicated the previously reported risk for 19 loci on 4q24, 6q25.3, 7p15.2, 8q24.21, 10q11.23, 10q26.13, 11p15.5, 11q13.2, 11q13.3. Statistically significant associations were replicated for other six SNPs only with a particular disease phenotype: low‐grade tumour and low PSA levels (rs1512268), high PSA levels (rs401681 and rs11649743), less aggressive cancers (rs1465618, rs721048, rs17021918). The strongest association of our tested SNP's with PSA in controls was for rs2735839, with 29% increase for each copy of the major allele G, consistent with previous results. Our results suggest that rs4962416, previously associated only with prostate cancer, is also associated with PSA levels, with 12% increase for each copy of the minor allele C. The study enabled the replication of the effect for the majority of previously reported genetic variants in a set of clinically relevant prostate cancers. This is the first replication study on these loci, known to associate with prostate cancer, in a Romanian population.

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.

Prostate genetic score (PGS-33) is independently associated with risk of prostate cancer in the PLCO trial

BACKGROUND

To investigate the ability of the prostate genetic score (PGS-33), a germ-line biomarker of prostate cancer (PCa) risk, to categorize men participating in the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial.

METHODS

We obtained the genetic data from the Cancer Genetic Markers of Susceptibility (CGEMS), a nested case control study examining germ-line DNA in the screened arm of the PLCO trial. A PGS-33 was calculated based on their genotype at 33 PCa associated single nucleotide polymorphisms (SNPs). The primary outcome was the diagnosis of PCa and primary predictor was PGS-33.

RESULTS

We identified 2,244 subjects (no cancer, N = 1017) and cases (N = 1227). The PGS-33 (P<0.001), prostate specific antigen (PSA; P < 0.001), family history of PCa (< 0.001), abnormal digital rectal exam (DRE, P < 0.001), and history of ever smoking (P = 0.037) were associated with a PCa diagnosis. In multivariable analysis, the log (PGS-33) was associated with PCa diagnosis with an odds ratio of 1.68 (95% CI 1.36-2.08, P < 0.001), log (PSA) (OR 8.2; 95% CI 6.75-10.04, P < 0.001), and family history of PCa (OR 2.01; 95% CI 1.26-3.20, P = 0.003). PGS-33 quartiles noted an increasing rate of PCa detection in addition to PSA: 43.2% (Q1), 47.8% (Q2), 58.8% (Q3), and 69.4 (Q4) (P < 0.001) and improvement in PSA performance (P < 0.001).

CONCLUSIONS

Germ-line DNA in the form of the PGS-33 is able to risk stratify men regarding their risk of PCa. The PGS-33 may have implications regarding who may benefit most from PCa screening and possibly add to PSA performance.

Association between EHBP1 rs721048(A>G) polymorphism and prostate cancer susceptibility: a meta-analysis of 17 studies involving 150,678 subjects

Background

EHBP1 rs721048(A) was first identified as a prostate cancer (PCa) risk in Caucasians by genome-wide association study, but subsequent replication studies involving Caucasian and other ethnicities did not produce consistent results. The aim of this study was to obtain a more definite association between rs721048(A) and PCa risk.

Methods

We comprehensively searched several databases updated to September 2014, including PubMed, Web of Science, EBSCO, and Google Scholar. Two authors independently screened and reviewed the eligibility of each study. The quality of the included studies was assessed by the Newcastle–Ottawa scale. The association of rs721048(A) and PCa risk was assessed by pooling odds ratios (ORs) with 95% confidence intervals (CIs).

Results

A total of 17 studies, including 48,135 cases and 102,543 controls, published between 2008 and 2014 were included in the meta-analysis. Overall, the pooled analysis demonstrated that rs721048(A) was significantly associated with the risk of PCa under the allele model (OR=1.14, 95% CI=1.11–1.17, P=0.000). Subgroup analysis based on ethnicity revealed a significant association between rs721048(A) and PCa in Caucasian (OR=1.14, 95% CI=1.11–1.16, P=0.000), African descent (OR=1.11, 95% CI=1.01–1.23, P=0.025), and Asian (OR=1.35, 95% CI=1.12–1.64, P=0.002).

Conclusion

Our results provided strong evidence that rs721048(A) could be a risk factor for PCa.

An analysis of the association between prostate cancer risk loci, PSA levels, disease aggressiveness and disease-specific mortality

BACKGROUND

Genome-wide association studies have identified multiple single-nucleotide polymorphsims (SNPs) associated with prostate cancer (PCa). Although these SNPs have been clearly associated with disease risk, their relationship with clinical outcomes is less clear. Our aim was to assess the frequency of known PCa susceptibility alleles within a single institution ascertainment and to correlate risk alleles with disease-specific outcomes.

METHODS

We genotyped 1354 individuals treated for localised PCa between June 1988 and December 2007. Blood samples were prospectively collected and de-identified before being genotyped and matched to phenotypic data. We investigated associations between 61 SNPs and disease-specific end points using multivariable analysis and also determined if SNPs were associated with PSA at diagnosis.

RESULTS

Seven SNPs showed associations on multivariable analysis (P<0.05), rs13385191 with both biochemical recurrence (BR) and castrate metastasis (CM), rs339331 (BR), rs1894292, rs17178655 and rs11067228 (CM), and rs11902236 and rs4857841 PCa-specific mortality. After applying a Bonferroni correction for number of SNPs (P<0.0008), the only persistent significant association was between rs17632542 (KLK3) and PSA levels at diagnosis (P=1.4 × 10(-5)).

CONCLUSIONS

We confirmed that rs17632542 in KLK3 is associated with PSA at diagnosis. No significant association was seen between loci and disease-specific end points when accounting for multiple testing. This provides further evidence that known PCa risk SNPs do not predict likelihood of disease progression.

Impact of prostate-specific antigen on a baseline prostate cancer risk assessment including genetic risk

OBJECTIVE

To determine to what extent prostate cancer (PCa) risk prediction is improved by adding prostate-specific antigen (PSA) to a baseline model including genetic risk.

METHODS

Peripheral blood deoxyribonucleic acid was obtained from Caucasian men undergoing prostate biopsy at the University of Toronto (September 1, 2008 to January 31, 2010). Thirty-three PCa risk-associated single nucleotide polymorphisms were genotyped to generate the prostate cancer genetic score 33 (PGS-33). Primary outcome is PCa on study prostate biopsy. Logistic regression, area under the receiver-operating characteristic curves (AUC), and net reclassification improvement were used to compare models.

RESULTS

Among 670 patients, 323 (48.2%) were diagnosed with PCa. The PGS-33 was highly associated with biopsy-detectable PCa (odds ratio, 1.66; P = 5.86E-05; AUC, 0.59) compared with PSA (odds ratio, 1.33; P = .01; AUC, 0.55). PSA did not improve risk prediction when added to a baseline model (age, family history, digital rectal examination, and PGS-33) for overall risk (AUC, 0.66 vs 0.66; P = .86) or Gleason score ≥7 PCa (AUC, 0.71 vs 0.73; P = .15). Net reclassification improvement analyses demonstrated no appropriate reclassifications with the addition of PSA to the baseline model for overall PCa but did show some benefit for reclassification of men thought to be at higher baseline risk in the high-grade PCa analysis.

CONCLUSION

In a baseline model of PCa risk including the PGS-33, PSA does not add to risk prediction for overall PCa for men presenting for "for-cause" biopsy. These findings suggest that PSA screening may be minimized in men at low baseline risk.

Prostate cancer in young men: an important clinical entity

Prostate cancer is considered a disease of older men (aged >65 years), but today over 10% of new diagnoses in the USA occur in young men aged ≤55 years. Early-onset prostate cancer, that is prostate cancer diagnosed at age ≤55 years, differs from prostate cancer diagnosed at an older age in several ways. Firstly, among men with high-grade and advanced-stage prostate cancer, those diagnosed at a young age have a higher cause-specific mortality than men diagnosed at an older age, except those over age 80 years. This finding suggests that important biological differences exist between early-onset prostate cancer and late-onset disease. Secondly, early-onset prostate cancer has a strong genetic component, which indicates that young men with prostate cancer could benefit from evaluation of genetic risk. Furthermore, although the majority of men with early-onset prostate cancer are diagnosed with low-risk disease, the extended life expectancy of these patients exposes them to long-term effects of treatment-related morbidities and to long-term risk of disease progression leading to death from prostate cancer. For these reasons, patients with early-onset prostate cancer pose unique challenges, as well as opportunities, for both research and clinical communities. Current data suggest that early-onset prostate cancer is a distinct phenotype-from both an aetiological and clinical perspective-that deserves further attention.

Cumulative effect of genome-wide association study-identified genetic variants for bladder cancer

Recent genome-wide association studies have identified 14 genetic variants associated with bladder cancer in Caucasians. The effects of these risk variants and their cumulative effects in Asian populations are unknown. We genotyped these newly identified variants in a case-control study of 1,050 patients diagnosed with bladder cancer and 1,404 controls in the Chinese population. Odds rations (ORs) and 95% confidence intervals (CIs) were computed by logistic regression, and cumulative effect of risk alleles were evaluated. Overall, seven of the 14 variants were significantly associated with bladder cancer risk (p = 9.763 × 10(-3) for rs9642880 at 8q24.21, p = 3.004 × 10(-3) for rs2294008 at 8q24.3, p = 0.012 for rs798766 at 4p16.3, p = 0.034 for rs1495741 at 8p22, p = 2.306 × 10(-4) for GSTM1, p = 8.507 × 10(-8) for rs17674580 at 18q12.3, p = 7.179 × 10(-4) for rs10936599 at 3q26.2) and the odds ratios (ORs) ranged from 1.13 to 1.65. Moreover, there were a significant increased risk for bladder cancer positively correlated numbers of risk alleles and smoking status (Ptrend  = 7.060 × 10(-16) ). However, no allelic interaction effects on bladder cancer risk were observed between cumulative effects of variants and clinical characteristics. These findings suggest that seven bladder cancer risk-associated variants (rs9642880, rs2294008, rs798766, rs1495741, GSTM1 null, rs17674580 and rs10936599) may be used, collectively, to effectively measure inherited risk for bladder cancer.

Does genotyping of risk-associated single nucleotide polymorphisms improve patient selection for prostate biopsy when combined with a prostate cancer risk calculator?

BACKGROUND

Genome-wide association studies have identified single nucleotide polymorphisms (SNPs) associated with higher risk of prostate cancer (PCa). This study aimed to evaluate whether published SNPs improve the performance of a clinical risk-calculator in predicting prostate biopsy result.

METHODS

Three hundred forty-six patients with a previous prostate biopsy (191 positive, 155 negative) were enrolled. After literature search, nine SNPs were selected for their statistically significant association with increased PCa risk. Allelic odds ratios were computed and a new logistic regression model was built integrating the clinical risk score (i.e., prior biopsy results, PSA level, prostate volume, transrectal ultrasound, and digital rectal examination) and a multilocus genetic risk score (MGRS). Areas under the receiver operating characteristic (ROC) curves (AUC) of the clinical score alone versus the integrated clinic-genetic model were compared. The added value of the MGRS was assessed using the Integrated Discrimination Improvement (IDI) and Net Reclassification Improvement (NRI) statistics.

RESULTS

Predictive performance of the integrated clinico-genetic model (AUC = 0.781) was slightly higher than predictive performance of the clinical score alone (AUC = 0.770). The prediction of PCa was significantly improved with an IDI of 0.015 (P-value = 0.035) and a continuous NRI of 0.403 (P-value < 0.001).

CONCLUSIONS

The predictive performance of the clinical model was only slightly improved by adding MGRS questioning the real clinical added value with regards to the cost of genetic testing and performance of current inexpensive clinical risk-calculators.

The role of single nucleotide polymorphisms in predicting prostate cancer risk and therapeutic decision making

Prostate cancer (PCa) is a major health care problem because of its high prevalence, health-related costs, and mortality. Epidemiological studies have suggested an important role of genetics in PCa development. Because of this, an increasing number of single nucleotide polymorphisms (SNPs) had been suggested to be implicated in the development and progression of PCa. While individual SNPs are only moderately associated with PCa risk, in combination, they have a stronger, dose-dependent association, currently explaining 30% of PCa familial risk. This review aims to give a brief overview of studies in which the possible role of genetic variants was investigated in clinical settings. We will highlight the major research questions in the translation of SNP identification into clinical practice.

Plateau effect of prostate cancer risk-associated SNPs in discriminating prostate biopsy outcomes

BACKGROUND

Additional prostate cancer (PCa) risk-associated single nucleotide polymorphisms (SNPs) continue to be identified. It is unclear whether addition of newly identified SNPs improves the discriminative performance of biopsy outcomes over previously established SNPs.

METHODS

A total of 667 consecutive patients that underwent prostate biopsy for detection of PCa at Huashan Hospital and Changhai Hospital, Shanghai, China were recruited. Genetic scores were calculated for each patient using various combinations of 29 PCa risk-associated SNPs. Performance of these genetic scores for discriminating prostate biopsy outcomes were compared using the area under a receiver operating characteristic curve (AUC).

RESULTS

The discriminative performance of genetic score derived from a panel of all 29 SNPs (24 previous and 5 new) was similar to that derived from the 24 previously established SNPs, the AUC of which were 0.60 and 0.61, respectively (P = 0.72). When SNPs with the strongest effect on PCa risk (ranked based on contribution to the total genetic variance from an external study) were sequentially added to the models for calculating genetic score, the AUC gradually increased and peaked at 0.62 with the top 13 strongest SNPs. Under the 13-SNP model, the PCa detection rate was 21.52%, 36.74%, and 51.98%, respectively for men with low (<0.5), intermediate (0.5-1.5), and high (>1.5) genetic score, P-trend = 9.91 × 10(-6).

CONCLUSION

Genetic score based on PCa risk-associated SNPs implicated to date is a significant predictor of biopsy outcome. Additional small-effect PCa risk-associated SNPs to be discovered in the future are unlikely to further improve predictive performance.

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.

The presence of prostate cancer at biopsy is predicted by a number of genetic variants

Several single nucleotide polymorphisms (SNPs) have been associated with an elevated risk of prostate cancer risk. It is not established if they are useful in predicting the presence of prostate cancer at biopsy or if they can be used to define a low-risk group of men. In this study, 4,548 men underwent a prostate biopsy because of an elevated prostate specific antigen (PSA; ≥4 ng/mL) or an abnormal digital rectal examination (DRE). All men were genotyped for 11 selected SNPs. The effect of each SNP, alone and in combination, on prostate cancer prevalence was studied. Of 4,548 men: 1,834 (40.3%) were found to have cancer. A positive association with prostate cancer was seen for 5 of 11 SNPs studied (rs1800629, rs1859962, rs1447295, rs4430796, rs11228565). The cancer detection rate rose with the number of SNP risk alleles from 29% for men with no variant to 63% for men who carried seven or more risk alleles (OR = 4.2; p = 0.002). The SNP data did not improve the predictive power of clinical factors (age, PSA and DRE) for detecting prostate cancer (AUC: 0.726 vs. 0.735; p = 0.4). We were unable to define a group of men with a sufficiently low prevalence of prostate cancer that a biopsy might have been avoided. In conclusion, our data do not support the routine use of SNP polymorphisms as an adjunct test to be used on the context of prostate biopsy for Polish men with an abnormal screening test.

A genetic score can identify men at high risk for prostate cancer among men with prostate-specific antigen of 1-3 ng/ml

BACKGROUND

The diagnostic performance of a genetic score based on single nucleotide polymorphisms (SNPs) is unknown in the prostate-specific antigen (PSA) range of 1-3 ng/ml. A substantial proportion of men in this PSA span have prostate cancer (PCa), but biomarkers to determine who should undergo a prostate biopsy are lacking.

OBJECTIVE

To evaluate whether a genetic risk score identifies men in the PSA range of 1-3 ng/ml who are at higher risk for PCa.

DESIGN, SETTING, AND PARTICIPANTS

Men aged 50-69 yr with PSA 1-3 ng/ml and without a previous prostate biopsy were selected from the STHLM2 cohort. Of 2696 men, 49 SNPs were genotyped, and a polygenic risk score was calculated. Of these men, 860 were invited according to risk score, and 172 underwent biopsy.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

The risk of PCa was assessed using univariate and multivariate logistic regression analysis.

RESULTS AND LIMITATIONS

PCa was diagnosed in 47 of 172 participants (27%), with Gleason sum 6 in 36 of 47 men (77%) and Gleason sum ≥7 in 10 of 47 men (21%); one man had intraductal cancer. The genetic score was a significant predictor of a positive biopsy (p=0.028), even after adjusting for PSA, ratio of free to total PSA, prostate volume, age, and family history. There was an increase in the odds ratio of 1.60 (95% confidence interval, 1.05-2.45) with increasing genetic risk score. The absolute risk difference of positive biopsy was 19 percentage points, comparing the high and low genetic risk group (37% vs 18%).

CONCLUSIONS

A risk score based on SNPs predicts biopsy outcome in previously unbiopsied men with PSA 1-3 ng/ml. Introducing a genetic-based risk stratification tool can increase the proportion of men being classified in line with their true risk of PCa.

A personalised approach to prostate cancer screening based on genotyping of risk founder alleles

Background:

To evaluate whether genotyping for 18 prostate cancer founder variants is helpful in identifying high-risk individuals and for determining optimal screening regimens.

Methods:

A serum PSA level was measured and a digital rectal examination (DRE) was performed on 2907 unaffected men aged 40–90. Three hundred and twenty-three men with an elevated PSA (⩾4 ng ml⁻¹) or an abnormal DRE underwent a prostate biopsy. All men were genotyped for three founder alleles in BRCA1 (5382insC, 4153delA and C61G), for four alleles in CHEK2 (1100delC, IVS2+1G>A, del5395 and I157T), for one allele in NBS1 (657del5), for one allele in HOXB13 (G84E), and for nine low-risk single-nucleotide polymorphisms (SNPs).

Results:

On the basis of an elevated PSA or an abnormal DRE, prostate cancer was diagnosed in 135 of 2907 men (4.6%). In men with a CHEK2 missense mutation I157T, the cancer detection rate among men with an elevated PSA or an abnormal DRE was much higher (10.2%, P=0.0008). The cancer detection rate rose with the number of SNP risk genotypes observed from 1.2% for men with no variant to 8.6% for men who carried six or more variants (P=0.04). No single variant was helpful on its own in predicting the presence of prostate cancer, however, the combination of all rare mutations and SNPs improved predictive power (area under the curve=0.59; P=0.03).

Conclusion:

These results suggest that testing for germline CHEK2 mutations improves the ability to predict the presence of prostate cancer in screened men, however, the clinical utility of incorporating DNA variants in the screening process is marginal.

Prostate cancer risk-associated genetic markers and their potential clinical utility

Prostate cancer (PCa) is one of the most common cancers among men in Western developed countries and its incidence has increased considerably in many other parts of the world, including China. The etiology of PCa is largely unknown but is thought to be multifactorial, where inherited genetics plays an important role. In this article, we first briefly review results from studies of familial aggregation and genetic susceptibility to PCa. We then recap key findings of rare and high-penetrance PCa susceptibility genes from linkage studies in PCa families. We devote a significant portion of this article to summarizing discoveries of common and low-penetrance PCa risk-associated single-nucleotide polymorphisms (SNPs) from genetic association studies in PCa cases and controls, especially those from genome-wide association studies (GWASs). A strong focus of this article is to review the literature on the potential clinical utility of these implicated genetic markers. Most of these published studies described PCa risk estimation using a genetic score derived from multiple risk-associated SNPs and its utility in determining the need for prostate biopsy. Finally, we comment on the newly proposed concept of genetic score; the notion is to treat it as a marker for genetic predisposition, similar to family history, rather than a diagnostic marker to discriminate PCa patients from non-cancer patients. Available evidence to date suggests that genetic score is an objective and better measurement of inherited risk of PCa than family history. Another unique feature of this article is the inclusion of genetic association studies of PCa in Chinese and Japanese populations.

Poor reproducibility of allergic rhinitis SNP associations

Replication of reported associations is crucial to the investigation of complex disease. More than 100 SNPs have previously been reported as associated with allergic rhinitis (AR), but few of these have been replicated successfully. To investigate the general reproducibility of reported AR-associations in candidate gene studies, one Swedish (352 AR-cases, 709 controls) and one Singapore Chinese population (948 AR-cases, 580 controls) were analyzed using 49 AR-associated SNPs. The overall pattern of P-values indicated that very few of the investigated SNPs were associated with AR. Given published odds ratios (ORs) most SNPs showed high power to detect an association, but no correlations were found between the ORs of the two study populations or with published ORs. None of the association signals were in common to the two genome-wide association studies published in AR, indicating that the associations represent false positives or have much lower effect-sizes than reported.

TERT-CLPTM1L polymorphism rs401681 contributes to cancers risk: evidence from a meta-analysis based on 29 publications

Background

Some common genetic variants of TERT-CLPTM1L gene, which encode key protein subunits of telomerase, have been suggested to play a crucial role in tumorigenesis. The TERT-CLPTM1L polymorphism rs401681 was of special interest for cancers risk but with inconclusive results.

Methodology/Principal Findings

We performed a comprehensive meta-analysis of 29 publications with a total of 91263 cases and 735952 controls. We assessed the strength of the association between rs401681 and overall cancers risk and performed subgroup analyses by cancer type, ethnicity, source of control, sample size and expected power. Rs401681 C allele was found to be associated with marginally increased cancers risk, with per allele OR of 1.04 (95%CI = 1.00–1.08, P_{heterogeneity}<0.001) and an expected power of 1.000. Following further stratified analyses, the increased cancers risk were discovered in subgroups of lung, bladder, prostate, basal cell carcinomas and Asians, while a declined risk of pancreatic cancer and melanoma were detected.

Conclusions/Significance

These findings suggested that rs401681 C allele was a low-penetrance risk allele for the development of cancers of lung, bladder, prostate and basal cell carcinoma, but a potential protective allele for melanoma and pancreatic cancer.

Reproducibility, performance, and clinical utility of a genetic risk prediction model for prostate cancer in Japanese

Prostate specific antigen (PSA) is widely used as a diagnostic biomarker for prostate cancer (PC). However, due to its low predictive performance, many patients without PC suffer from the harms of unnecessary prostate needle biopsies. The present study aims to evaluate the reproducibility and performance of a genetic risk prediction model in Japanese and estimate its utility as a diagnostic biomarker in a clinical scenario. We created a logistic regression model incorporating 16 SNPs that were significantly associated with PC in a genome-wide association study of Japanese population using 689 cases and 749 male controls. The model was validated by two independent sets of Japanese samples comprising 3,294 cases and 6,281 male controls. The areas under curve (AUC) of the model were 0.679, 0.655, and 0.661 for the samples used to create the model and those used for validation. The AUCs were not significantly altered in samples with PSA 1-10 ng/ml. 24.2% and 9.7% of the patients had odds ratio <0.5 (low risk) or >2 (high risk) in the model. Assuming the overall positive rate of prostate needle biopsies to be 20%, the positive biopsy rates were 10.7% and 42.4% for the low and high genetic risk groups respectively. Our genetic risk prediction model for PC was highly reproducible, and its predictive performance was not influenced by PSA. The model could have a potential to affect clinical decision when it is applied to patients with gray-zone PSA, which should be confirmed in future clinical studies.

Beyond prostate-specific antigen - future biomarkers for the early detection and management of prostate cancer

Prostate-specific antigen is currently commonly used as a screening biomarker for prostate cancer, but it has limitations in both sensitivity and specificity. The development of novel biomarkers for early cancer detection has the potential to improve survival, reduce unnecessary investigations and benefit the health economy. Here we review the use and limitations of prostate-specific antigen and its subtypes, urinary biomarkers including PCA3, alpha-methylacyl-CoA racemase, the TMPRSS2-ERG fusion gene and microseminoprotein-beta, and other novel markers in both serum and urine. Many of these biomarkers are at early stages of development and require evaluation in prospective trials to determine their potential usefulness in clinical practice. Genetic profiling may allow for the targeting of high-risk populations for screening and may offer the opportunity to combine biomarker results with genotype to aid risk assessment.

A population-based assessment of germline HOXB13 G84E mutation and prostate cancer risk

BACKGROUND

A rare but recurrent missense mutation (G84E, rs138213197) in the gene homeobox B13 (HOXB13) was recently reported to be associated with hereditary prostate cancer.

OBJECTIVE

To explore the prevalence and penetrance of HOXB13 G84E in a general population.

DESIGN, SETTING, AND PARTICIPANTS

G84E and 14 additional HOXB13 polymorphisms were genotyped in two population-based, Swedish, case-control samples (Cancer of the Prostate in Sweden [CAPS] and Stockholm-1) comprising 4693 controls and 5003 prostate cancer cases. CAPS collected data on patients and population controls nationally between 2001 and 2003. Stockholm-1 collected data on biopsy-positive patients and biopsy-negative controls in the Stockholm area between 2005 and 2007.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

The outcome was pathologically verified prostate cancer. Relative and absolute risks among HOXB13 G84E mutation carriers were explored, as was the combined impact on disease risk of G84E and a polygenic score based on 33 established, common, low-risk variants.

RESULTS AND LIMITATIONS

HOXB13 G84E was observed in 1.3% of population controls and was strongly associated with prostate cancer risk (CAPS: odds ratio [OR]: 3.4; 95% confidence interval [CI], 2.2-5.4; Stockholm-1: OR: 3.5; 95% CI, 2.4-5.2). The strongest association was observed for young-onset (OR: 8.6; 95% CI, 5.1-14.0) and hereditary (OR: 6.6; 95% CI, 3.3-12.0) prostate cancer. Haplotype analyses supported that G84E is a founder mutation. G84E carriers have an estimated 33% (95% CI, 23-46) cumulative risk to age 80 yr of prostate cancer, compared to 12% (95% CI, 11-13) among noncarriers. For G84E carriers within the top quartile of a polygenic score of established susceptibility variants, the cumulative risk was estimated at 48% (95% CI, 36-64).

CONCLUSIONS

HOXB13 G84E is prevalent in >1% of the Swedish population and is associated with a 3.5-fold increased risk of prostate cancer. One-third of G84E carriers will be diagnosed with prostate cancer, which has implications for surveillance in mutation carriers.