Clinical utility of the PCA3 urine assay in European men scheduled for repeat biopsy

The development of nomograms for stratification of men at risk of prostate cancer prior to prostate biopsy

A main limitation of early prostate cancer (PCa) detection due to elevated PSA levels is caused by the low specificity of PSA, which is associated with a high proportion of men detected with nonmalignant findings at first or subsequent prostate biopsy (PBX). Multivariate prediction models, such as nomograms, have been developed, providing a more accurate method to prospectively determine the risk of a positive PBX. Combining established clinical risk factors with novel diagnostic markers of PCa appears promising to further improve predictive accuracy estimates. Ideally, these nomograms should be capable of identifying PCa at PBX without missing men with high-grade PCa, and preventing a significant proportion of men without, or with insignificant, PCa from undergoing PBX. The intention is to reduce disease morbidity and mortality by detecting significant PCa at an early stage, and at the same time to avoid overdiagnosis as well as overintervention.

Nucleic acid-based biomarkers in body fluids of patients with urologic malignancies

This review focuses on the promising potential of nucleic acids in body fluids such as blood and urine as diagnostic, prognostic, predictive and monitoring biomarkers in urologic malignancies. The tremendous progress in the basic knowledge of molecular processes in cancer, as shown in the companion review on nucleic acid-based biomarkers in tissue of urologic tumors, provides a strong rationale for using these molecular changes as non-invasive markers in body fluids. The changes observed in body fluids are an integrative result, reflecting both tissue changes and processes occurring in the body fluids. The availability of sensitive methods has only recently made possible detailed studies of DNA- and RNA-based markers in body fluids. In addition to these biological aspects, methodological aspects of the determination of nucleic acids in body fluids, i.e. pre-analytical, analytical and post-analytical issues, are particularly emphasized. The characteristic changes of RNA (differential mRNA and miRNA expression) and DNA (concentrations, integrity index, mutations, microsatellite and methylation alterations) in serum/plasma and urine samples of patients suffering from the essential urologic cancers of the prostate, bladder, kidney and testis are summarized and critically discussed below. To translate the promising results into clinical practice, laboratory scientists and clinicians have to collaborate to resolve the challenges of harmonized and feasible pre-analytical and analytical conditions for the selected markers and to validate these markers in well-designed and sufficiently powered multi-center studies.

Diagnostic value of urine prostate cancer antigen 3 test using a cutoff value of 35 μg/L in patients with prostate cancer

The aim of this study is to explore the diagnostic role of urine prostate cancer antigen 3 (PCA3) in detecting prostate cancer (PCa) through a systematic review and meta-analysis. Relevant research studies aiming at the application of urine PCA3 level in PCa diagnosis were searched in PubMed, Embase, Chinese Biomedical Database (CBM), Chinese National Knowledge Infrastructure (CNKI), VIP, and Wan Fang databases independently, which were published up to May 8, 2014. The pooled sensitivity, specificity, positive diagnostic likelihood ratio (DLR+), negative diagnostic likelihood ratio (DLR-), diagnostic odds ratio, and the area under the summary receiver operating characteristic were used to evaluate the value of urine PCA3 in diagnosis of PCa by using the Meta-DiSc and STATA 12.0 statistical software. Sixteen research studies with a total 2,457 PCa patients and 4,236 control individuals were included in this meta-analysis. Overall, the results showed sensitivity and specificity of urine PCA3 in the diagnosis of PCa was 0.57 (95 % CI = 0.55-0.59), and 0.71 (95 % CI = 0.70-0.73), respectively. The DLR + and PLR - in the diagnosis of PCa were 2.12 (95 % CI = 1.89-2.38), and 0.55 (95 % CI = 0. 50-0.61), respectively. The pooled diagnostic odds ratio was 3.93 (95 % CI = 3.28-4.72). The area under the curve (AUCs) and *Q index estimate were 0.7118 and 0.6623, respectively. Urine PCA3 is a potential biomarker for the diagnosis of PCa. However, further well-designed studies with large samples will be needed to confirm the results got from present meta-analysis.

The role of biomarkers in the assessment of prostate cancer risk prior to prostate biopsy: which markers matter and how should they be used?

Prostate cancer (PCa) screening has been substantially influenced by the clinical implementation of serum prostate-specific antigen (PSA). In this context, improvement of early PCa detection and stage migration as well as reduced PCa mortality were achieved, and up-to-date PSA represents the gold standard biomarker of PCa diagnosis together with clinical findings. Nonetheless, PSA shows weakness in discriminating between malign and benign prostatic disease or indolent and aggressive cancers. As a result, the expansion of PSA screening is extensively debated with regard to overdetection and ultimately overtreatment, keeping in mind that PCa is still the third leading cause of cancer-specific mortality in the Western male population. Consequently, today's task is to increase the accuracy of PCa detection and furthermore to allow stratification for indolent PCa that might permit active surveillance and to filter out aggressive cancers necessitating treatment. Thus, novel biomarkers, especially in combination with approved clinical risk factors (e.g., age or family history of PCa), within multivariable prediction models carry the potential to improve many aspects of PCa diagnosis and to enable risk classification in clinical practice. Multivariable models lead to superior accuracy for PCa prediction instead of the use of a single risk factor. The aim of this article was to present an overview of known risk factors for PCa together with new promising blood- and urine-based biomarkers and their application within risk models that may allow risk stratification for PCa prior to prostate biopsy. Risk models may optimize PCa detection and classification with regard to improved PCa risk assessment and avoidance of unnecessary prostate biopsies.

Long noncoding RNAs and prostate carcinogenesis: the missing 'linc'?

Long noncoding RNAs (lncRNAs) are rapidly becoming essential pieces in the cancer puzzle. Our understanding of their functional capabilities is in its infancy. One certain fact, however, is that their molecular interactions extend beyond chromatin complexes into diverse biological processes. In prostate cancer, aberrant expression of lncRNAs is associated with disease progression. Overexpression of oncogenic lncRNAs promotes tumor-cell proliferation and metastasis through chromatin looping and distal engagement with the androgen receptor, antisense gene regulation, alternative splicing, and impeding DNA repair. Several lncRNAs, such as prostate cancer antigen 3 (PCA3), prostate cancer gene expression marker 1 (PCGEM1), and prostate cancer associated ncRNA transcript 1 (PCAT1), are highly prostate-specific, posing as attractive biomarkers. Herein we review the mechanisms of action of lncRNAs in prostate carcinogenesis and their potential clinical utility for disease.

Optimizing prostate cancer screening; prospective randomized controlled study of the role of PSA and PCA3 testing in a sequential manner in an opportunistic screening program

OBJECTIVES

To reduce unnecessary biopsies (Bx) in an opportunistic screening programme of prostate cancer.

MATERIAL AND METHODS

We perform a prospective evaluation of PCA3 as a second line biomarker in an opportunistic screening for prostate cancer (PCa). From September-2010 until September-2012, 2,366 men, aged 40-74 years and with >10 years life expectancy, were initially screened with PSA/digital rectal examination (DRE). Men with previous Bx or with recent urine infections were excluded. Men with abnormal DRE and/or PSA >3 ng/ml were submitted for PCA3. All men with PCA3 ≥ 35 underwent an initial biopsy (IBx) -12cores-. Men with PCA3 < 35 were randomized 1:1 to either IBx or observation. Re-biopsy(16-18 cores) criteria were PSA increase >.5 ng/ml at 4-6 months or PSAv > .75 ng/ml/year.

RESULTS

With median follow-up (FU) of 10.1 months, PCA3 was performed in 321/2366 men (13.57%), 289 at first visit and 32 during FU. All 110 PCA3+ men (34.3%) were biopsied and PCa was identified in 43 men in IBx (39.1%). In the randomized arm, 110 were observed and 101 underwent biopsy, finding 12 PCa (11.9%), showing a statistically significant reduction of PCa detection rate in this cohort (P<.001). Global PCa detection rates were 40.9% and 9.5% for the PCA3+ and PCA3- branches, respectively (P<.001). Area under the curve for PSA and PCA3 were .601 and .74, respectively. This is an ongoing prospective study limited by its short follow-up period and still limited enrolment.

CONCLUSIONS

PCA3 as a second line biomarker within an opportunistic dual screening protocol, can potentially avoid 65.7% and 50.1% biopsies at first round and at median FU of 10.1 months, respectively, just missing around 3.2% of high grade PCa.

Prostate-specific antigen and other serum and urine markers in prostate cancer

Prostate-specific antigen (PSA) is one of the most widely used tumor markers, and strongly correlates with the risk of harboring from prostate cancer (PCa). This risk is visible already several years in advance but PSA has severe limitations for PCa detection with its low specificity and low negative predictive value. There is an urgent need for new biomarkers especially to detect clinically significant and aggressive PCa. From all PSA-based markers, the FDA-approved Prostate Health Index (phi) shows improved specificity over percent free and total PSA. Other serum kallikreins or sarcosine in serum or urine show more diverging data. In urine, the FDA-approved prostate cancer gene 3 (PCA3) has also proven its utility in the detection and management of early PCa. However, some aspects on its correlation with aggressiveness and the low sensitivity at very high values have to be re-examined. The detection of a fusion of the androgen regulated TMPRSS2 gene with the ERG oncogene (from the ETS family), which acts as transcription factor gene, in tissue of ~50% of all PCa patients was one milestone in PCa research. When combining the urinary assays for TMPRSS2:ERG and PCA3, an improved accuracy for PCa detection is visible. PCA3 and phi as the best available PCa biomarkers show an equal performance in direct comparisons.

Diagnostic and predictive value of urine PCA3 gene expression for the clinical management of patients with altered prostatic specific antigen

OBJECTIVE

Analyze the impact of the introduction of the study of PCA3 gene in post-prostatic massage urine in the clinical management of patients with PSA altered, evaluating its diagnostic ability and predictive value of tumor aggressiveness.

METHODS

Observational, prospective, multicenter study of patients with suspected prostate cancer (PC) candidates for biopsy. We present a series of 670 consecutive samples of urine collected post-prostatic massage for three years in which we determined the "PCA3 score" (s-PCA3). Biopsy was only indicated in cases with s-positive PCA3.

RESULTS

The s-PCA3 was positive in 43.7% of samples. In the 124 biopsies performed, the incidence of PC or atypical small acinar proliferation was 54%, reaching 68,6% in s-PCA3≥100. Statistically significant relationship between the s-PCA3 and tumor grade was demonstrated. In cases with s-PCA3 between 35 and 50 only 23% of PC were high grade (Gleason≥7), compared to 76.7% in cases with s-PCA3 over 50. There was a statistically significant correlation between s-PCA3 and cylinders affected. Both relationships were confirmed by applying a log-linear model.

CONCLUSIONS

The incorporation of PCA3 can avoid the need for biopsies in 54% of patients. s-PCA3 positivity increases the likelihood of a positive biopsy, especially in higher s-PCA3 100 (68.6%). s-PCA3 is also an indicator of tumor aggressiveness and provides essential information in making treatment decisions.

A Quest to Identify Prostate Cancer Circulating Biomarkers with a Bench-to-Bedside Potential

Prostate cancer (PCA) is a major health concern in current times. Ever since prostate specific antigen (PSA) was introduced in clinical practice almost three decades ago, the diagnosis and management of PCA have been revolutionized. With time, concerns arose as to the inherent shortcomings of this biomarker and alternatives were actively sought. Over the past decade new PCA biomarkers have been identified in tissue, blood, urine, and other body fluids that offer improved specificity and supplement our knowledge of disease progression. This review focuses on superiority of circulating biomarkers over tissue biomarkers due to the advantages of being more readily accessible, minimally invasive (blood) or noninvasive (urine), accessible for sampling on regular intervals, and easily utilized for follow-up after surgery or other treatment modalities. Some of the circulating biomarkers like PCA3, IL-6, and TMPRSS2-ERG are now detectable by commercially available kits while others like microRNAs (miR-21, -221, -141) and exosomes hold potential to become available as multiplexed assays. In this paper, we will review some of these potential candidate circulating biomarkers that either individually or in combination, once validated with large-scale trials, may eventually get utilized clinically for improved diagnosis, risk stratification, and treatment.

Recent Advances in Metabolic Profiling And Imaging of Prostate Cancer

Cancer is a metabolic disease. Cancer cells, being highly proliferative, show significant alterations in metabolic pathways such as glycolysis, respiration, the tricarboxylic acid (TCA) cycle, oxidative phosphorylation, lipid metabolism, and amino acid metabolism. Metabolites like peptides, nucleotides, products of glycolysis, the TCA cycle, fatty acids, and steroids can be an important read out of disease when characterized in biological samples such as tissues and body fluids like urine, serum, etc. The cancer metabolome has been studied since the 1960s by analytical techniques such as mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy. Current research is focused on the identification and validation of biomarkers in the cancer metabolome that can stratify high-risk patients and distinguish between benign and advanced metastatic forms of the disease. In this review, we discuss the current state of prostate cancer metabolomics, the biomarkers that show promise in distinguishing indolent from aggressive forms of the disease, the strengths and limitations of the analytical techniques being employed, and future applications of metabolomics in diagnostic imaging and personalized medicine of prostate cancer.

Role of PSA-related variables in improving positive ratio of biopsy of prostate cancer within serum PSA gray zone

OBJECTIVE

The aim of this study was to assess the validity of predictors of prostate biopsy outcome in order to improve their positive predictive value (PPV). The related variables of PSA such as free/total PSA ratio (F/T), complexed/total PSA ratio (C/T), density of PSA (PSAD) were studied to improve early diagnosis for early PCa within serum PSA gray zone.

METHODS

Samples of venous blood were collected early in the morning from 459 patients, aged 50 to 88 years (average 70.5 years old), whose serum T-PSA was between 4 to 10 ng/mL (153 cases of Pca, 306 cases of BPH). Serum T-PSA, F-PSA and C-PSA were determined by ELISA method; prostate volume was measured by transrectal ultrasound, then prostate biopsy was taken for all patients.

RESULTS

Out of f 459 patients, 153 cases of Pca and 306 of BPH were diagnosed by prostate biopsy, whose mean values of T-PSA were 7.2 ± 1.25 ng/mL and 6.8 ± 0.96 ng/mL, respectively (P<0.05), of F/T were 0.117 ± 0.018 and 0.196 ± 0.021 (P<0.01), and of C/T they were 0.890 ± 0.023 and 0.754 ± 0.015 (P<0.01), of PSAD were 0.197 ± 0.023 and 0.106 ± 0.019 (P<0.01). The threshold of F/T>0.16 diagnosed 91 cases of cancer (59.5%), of C/T>0.84 88 cases (57.5%), of PSAD>0.15 94 cases (61.4%), and especially, of F/T>0.16 combined PSAD>0.15 80 cases whose sensitivity, specificity, accuracy, positive predictive values were 52.3%, 76.1%, 68.2%, 52.3%, respectively (P<0.05).

CONCLUSION

There are some defects only in taking T-PSA as a biomarker for the diagnosis of PCa within serum PSA gray zone, and the threshold of F/T>0.16 combined PSAD>0.15 may be a new and significant indicator to provide a better basis for the diagnosis of early PCa.

Prostate cancer biomarkers: an update

Many aspects of prostate cancer diagnosis and treatment could be greatly advanced with new, effective biomarkers. Prostate-specific antigen (PSA) has multiple weaknesses as a biomarker, such as not distinguishing well between cancer and benign prostatic hyperplasia or between indolent and aggressive cancers, thus leading to overtreatment, especially unnecessary biopsies. PSA also often fails to indicate accurately which patients are responding to a given treatment. Yet PSA is the only prostate cancer biomarker routinely used by urologists. Here, we provide updated information on the most relevant of the other biomarkers currently in use or in development for prostate cancer. Recent research shows improvement over using PSA alone by comparing total PSA (tPSA) or free PSA (fPSA) with new, related markers, such as prostate cancer antigen (PCA) 3, the individual molecular forms of PSA (proPSA, benign PSA, and intact PSA), and kallikreins other than PSA. Promising results have also been seen with the use of the fusion gene TMPRSS2:ERG and with various forms of the urokinase plasminogen activation receptor. Initially, there were high hopes for early PCA, but those data were not reproducible and thus research on early PCA has been abandoned. Much work remains to be done before any of these biomarkers are fully validated and accepted. Currently, the only markers discussed in this paper with Food and Drug Administration-approved tests are PCA 3 and an isoform of proPSA, [-2]proPSA. Assays are in development for most of the other biomarkers described in this paper. While the biomarker validation process can be long and filled with obstacles, the rewards will be great-in terms of both patient care and costs to the health care system.

Translating genetic risk factors for prostate cancer to the clinic: 2013 and beyond

Prostate cancer (PrCa) is the most commonly diagnosed cancer in the male UK population, with over 40,000 new cases per year. PrCa has a complex, polygenic predisposition, due to rare variants such as BRCA and common variants such as single nucleotide polymorphisms (SNPs). With the introduction of genome-wide association studies, 78 susceptibility loci (SNPs) associated with PrCa risk have been identified. Genetic profiling could risk-stratify a population, leading to the discovery of a higher proportion of clinically significant disease and a reduction in the morbidity related to age-based prostate-specific antigen screening. Based on the combined risk of the 78 SNPs identified so far, the top 1% of the risk distribution has a 4.7-times higher risk of developing PrCa compared with the average of the general population.

Imaging and Markers as Novel Diagnostic Tools in Detecting Insignificant Prostate Cancer: A Critical Overview

Recent therapeutic advances for managing low-risk prostate cancer include the active surveillance and focal treatment. However, locating a tumor and detecting its volume by adequate sampling is still problematic. Development of predictive biomarkers guiding individual therapeutic choices remains an ongoing challenge. At the same time, prostate cancer magnetic resonance imaging is gaining increasing importance for prostate diagnostics. The high morphological resolution of T2-weighted imaging and functional MRI methods may increase the specificity and sensitivity of diagnostics. Also, recent studies founded an ability of novel biomarkers to identify clinically insignificant prostate cancer, risk of progression, and association with poor differentiation and, therefore, with clinical significance. Probably, the above mentioned methods would improve tumor characterization in terms of its volume, aggressiveness, and focality. In this review, we attempted to evaluate the applications of novel imaging techniques and biomarkers in assessing the significance of the prostate cancer.

Urinary PCA3 as a predictor of prostate cancer in a cohort of 3,073 men undergoing initial prostate biopsy

PURPOSE

PCA3 is a urinary marker that has shown promise in predicting the presence of prostate cancer in men undergoing repeat prostate biopsy. We studied PCA3 before initial prostate biopsy.

MATERIALS AND METHODS

Records from a single organization were retrospectively reviewed. The predictive value of PCA3 was explored using nonparametric receiver operating characteristic curve analysis (ROC) and multivariable logistic regression analysis.

RESULTS

A total of 3,073 men underwent PCA3 analysis before initial prostate biopsy sampling of 12 to 14 areas. Mean PCA3 was 27.2 and 52.5 for patients without and with cancer, respectively. Prostate cancer was identified in 1,341 (43.6%) men. Overall 54.5% had Gleason 6 disease and 45.5% had Gleason 7 or greater (high grade prostate cancer). Mean PCA3 was 47.5 and 58.5 for the patients with Gleason 6 and 7 or greater disease, respectively. On multivariable logistic analysis PCA3 was statistically significantly associated with prostate cancer and high grade prostate cancer after adjusting for prostate specific antigen (p<0.001 for both), free prostate specific antigen (p=0.04 and p=0.01, respectively), age (p<0.001 for both), family history (p<0.001 and p=0.59, respectively), abnormal digital rectal examination (p=0.31 and p<0.001, respectively), prostate volume (p<0.001 for both) and body mass index (p<0.001 for both). Using ROC analysis PCA3 outperformed prostate specific antigen in the prediction of prostate cancer (AUC 0.697 vs 0.599, p<0.01) but not for high grade prostate cancer (AUC 0.682 vs 0.679, p=0.702).

CONCLUSIONS

PCA3 proved a useful tool in identifying patients at risk for prostate cancer before initial prostate biopsy. To our knowledge this is the largest PCA3 study in the initial biopsy population. These results suggest that further exploration of the value of PCA3 is warranted.

Biomarkers in prostate cancer surveillance and screening: past, present, and future

The use of biomarkers for prostate cancer (PCa) screening, detection, and prognostication have revolutionized the diagnosis and management of the disease. Current clinical practice has been driven largely by the utilization of prostate-specific antigen (PSA). The lack of specificity of PSA for PCa has led to both unnecessary biopsies and overdiagnosis of indolent cancers. The recent controversial recommendation by the United States Preventive Services Task Force against PCa screening has highlighted the need for novel clinically useful biomarkers. We review the literature on PCa biomarkers in serum, urine, and tissue. While these markers show promise, none seems poised to replace PSA, but rather may augment it. Further validation and consideration of how these novel markers improve clinical outcome is necessary. The discovery of new genetic markers shows promise in stratifying men with aggressive PCa.

Prostate cancer biomarker profiles in urinary sediments and exosomes

PURPOSE

Urinary biomarker tests for diagnosing prostate cancer have gained considerable interest. Urine is a complex mixture that can be subfractionated. We evaluated 2 urinary fractions that contain nucleic acids, ie cell pellets and exosomes. The influence of digital rectal examination before urine collection was also studied and the prostate cancer specific biomarkers PCA3 and TMPRSS2-ERG were assayed.

MATERIALS AND METHODS

Urine samples were prospectively obtained before and after digital rectal examination from 30 men scheduled for prostate biopsy. Cell pellet and exosomes were isolated and used for biomarker analysis. Analytical and diagnostic performance was tested using the Student t-test and ROC curves.

RESULTS

Unlike the exosome fraction, urinary sediment gene expression analysis was compromised by amorphous precipitation in 10% of all specimens. Digital rectal examination resulted in increased mRNA levels in each fraction. This was particularly relevant for the exosomal fraction since after digital rectal examination the number of samples decreased in which cancer specific markers were below the analytical detection limit. Biomarker diagnostic performance was comparable to that in large clinical studies. In exosomes the biomarkers had to be normalized for prostate specific antigen mRNA while cell pellet absolute PCA3 levels had diagnostic value.

CONCLUSIONS

Exosomes have characteristics that enable them to serve as a stable substrate for biomarker analysis. Thus, digital rectal examination enhances the analytical performance of biomarker analysis in exosomes and cell pellets. The diagnostic performance of biomarkers in exosomes differs from that of cell pellets. Clinical usefulness must be prospectively assessed in larger clinical cohorts.

Clinical use of novel urine and blood based prostate cancer biomarkers: a review

In the era of upcoming techniques for molecular profiling, breakthroughs led to new discoveries in the field of prostate cancer (PCa) biomarkers. Since the early 1990s a tremendous increase in PCa incidence is seen, dedicated to the introduction of prostate specific antigen (PSA) testing. However, due to its lack of specificity many men undergo unnecessary biopsies, resulting in a rising incidence of clinically insignificant PCa. To overcome this drawback, cancer specific biomarkers are needed to identify patients who are at high risk of harbouring PCa and to distinguish patients with aggressive disease from patients with insignificant cancer. The most non-invasive, easy to obtain substrate for biomarker measurement is urine. The most promising markers to date are PCA3 and TMPRSS2-ERG. Both markers demonstrate to have a higher specificity and diagnostic accuracy for PCa outcome compared to serum PSA. This might better predict the presence of PCa and therefore reduce the number of unnecessary biopsies. Combining both markers in a panel might result in an even higher diagnostic accuracy, given the heterogeneity of the disease. In PCa management, circulating tumour cells (CTCs) detected in the blood seem a promising tool to predict treatment response and survival benefit. Although results appear to be encouraging, the biggest challenge about new markers in PCa is to validate them in large clinical trials and subsequently implement these markers into clinical practice. In this review we discuss the clinical usefulness of novel, non-invasive tests in PCa management.

Molecular diagnosis of prostate cancer: are we up to age?

Prostate cancer (PCa), a highly heterogeneous disease, is the one of the leading cause of morbidity and mortality in the developed countries. Historically used biomarkers such as prostatic acid phosphatase (PAP), serum prostate-specific antigen (PSA), and its precursor have not stood the challenge of sensitivity and specificity. At present, there is need to re-evaluate the approach to diagnose and monitor PCa. To this end, molecular markers that can accurately identify men with PCa at an early stage, and those who would benefit from early therapeutic intervention, are the need of the hour. There has been unprecedented progress in the development of new PCa biomarkers through advancements in proteomics, tissue DNA and protein/RNA microarray, identification of microRNA, isolation of circulating tumor cells, and tumor immunohistochemistry. This review will examine the current status of prostate cancer biomarkers with emphasis on emerging biomarkers by evaluating their diagnostic and prognostic potentials.

PCA3 and PCA3-based nomograms improve diagnostic accuracy in patients undergoing first prostate biopsy

While now recognized as an aid to predict repeat prostate biopsy outcome, the urinary PCA3 (prostate cancer gene 3) test has also been recently advocated to predict initial biopsy results. The objective is to evaluate the performance of the PCA3 test in predicting results of initial prostate biopsies and to determine whether its incorporation into specific nomograms reinforces its diagnostic value. A prospective study included 601 consecutive patients addressed for initial prostate biopsy. The PCA3 test was performed before ≥12-core initial prostate biopsy, along with standard risk factor assessment. Diagnostic performance of the PCA3 test was evaluated. The three available nomograms (Hansen's and Chun's nomograms, as well as the updated Prostate Cancer Prevention Trial risk calculator; PCPT) were applied to the cohort, and their predictive accuracies were assessed in terms of biopsy outcome: the presence of any prostate cancer (PCa) and high-grade prostate cancer (HGPCa). The PCA3 score provided significant predictive accuracy. While the PCPT risk calculator appeared less accurate; both Chun's and Hansen's nomograms provided good calibration and high net benefit on decision curve analyses. When applying nomogram-derived PCa probability thresholds ≤30%, ≤6% of HGPCa would have been missed, while avoiding up to 48% of unnecessary biopsies. The urinary PCA3 test and PCA3-incorporating nomograms can be considered as reliable tools to aid in the initial biopsy decision.

Assays for prostate cancer : changing the screening paradigm?

Prostate cancer (PCa) screening and detection have changed dramatically since the introduction of serum prostate-specific antigen (PSA) testing. Despite the resulting improvement in early PCa detection and stage migration, in clinical practice the use of PSA testing may cause overdetection and ultimately overtreatment. As a consequence, novel biomarkers are needed to increase the specificity of PCa detection. The aim of this article is to present an overview of novel blood- and urine-based biomarkers that may optimize PCa detection, with improved identification of patients with significant PCa and avoidance of unnecessary prostate biopsies. A systematic and comprehensive PubMed search was performed using the MeSH search terms 'prostate cancer', 'biomarker', 'marker', and 'detection'. Results were restricted to the English language. Several blood- and urine-based biomarkers have the potential to improve prediction of the presence and/or significance of PCa. Ideally, biomarkers should be used in combination within multivariate models, leading to superior accuracy for prediction of any PCa or clinically significant PCa, compared with the use of a single marker.

Comparison of prostate cancer diagnosis in patients receiving unrelated urological and non-urological cancer care

OBJECTIVE

To evaluate prostate cancer diagnosis rates and survival outcomes in patients receiving unrelated (non-prostate) urological care with those in patients receiving non-urological care.

MATERIALS AND METHODS

We conducted a population-based study using the Surveillance Epidemiology and End Results (SEER) database to identify men who underwent surgical treatment of renal cell carcinoma (RCC; n = 18,188) and colorectal carcinoma (CRC; n = 45,093) between 1992 and 2008. Using SEER*stat software to estimate standardized incidence ratios (SIRs), we investigated rates of prostate cancer diagnosis in patients with RCC and patients with CRC. Adjusting for patient age, race and year of diagnosis on multivariate analysis, we used Cox and Fine and Gray proportional hazards regressions to evaluate overall and disease-specific survival endpoints.

RESULTS

The observed incidence of prostate cancer was higher in both the patients with RCC and those with CRC: SIR = 1.36 (95% confidence interval [CI] 1.27-1.46) vs 1.06 (95% CI 1.02-1.11). Adjusted prostate cancer SIRs were 30% higher (P < 0.001) in patients with RCC. Overall (hazard ratio = 1.13, P < 0.001) and primary cancer-adjusted mortalities (sub-distribution Hazard Ratio (sHR) = 1.17, P < 0.001) were higher in patients with RCC with no significant difference in prostate cancer-specific mortality (sHR = 0.827, P = 0.391).

CONCLUSION

Rates of prostate cancer diagnosis were higher in patients with RCC (a cohort with unrelated urological cancer care) than in those with CRC. Despite higher overall mortality in patients with RCC, prostate cancer-specific survival was similar in both groups. Opportunities may exist to better target prostate cancer screening in patients who receive non-prostate-related urological care. Furthermore, urologists should not feel obligated to perform prostate-specific antigen screening for all patients receiving non-prostate-related urological care.

Value of PCA3 to predict biopsy outcome and its potential role in selecting patients for multiparametric MRI

PCA3 (prostate cancer gene 3) and multiparametric 3 tesla MRI are new promising diagnostic tools in the detection of PCa. Our aim was to study the clinical value of the Progensa PCA3-test: its predictive value for biopsy outcome, Gleason score and MRI outcome. We evaluated, retrospectively, 591 patients who underwent a Progensa PCA3-test at the Radboud University Nijmegen Medical Centre between May 2006 and December 2009. Prostate biopsies were performed in 290 patients; a multiparametric 3 tesla MRI of the prostate was performed in 163/591 patients. The PCA3-score was correlated to biopsy results and MRI outcome. The results show that PCA3 was highly predictive for biopsy outcome (p < 0.001); there was no correlation with the Gleason score upon biopsy (p = 0.194). The PCA3-score of patients with a suspicious region for PCa on MRI was significantly higher (p < 0.001) than in patients with no suspicious region on MRI (52 vs. 21). In conclusion, PCA3 is a valuable diagnostic biomarker for PCa; it did not correlate with the Gleason score. Furthermore, multiparametric MRI outcome was significantly correlated with the PCA3-score. Thus, PCA3 could be used to select patients that require MRI. However, in patients with a negative PCA3 and high clinical suspicion of PCa, a multiparametric MRI should also be done.

PCA3 score and prostate cancer diagnosis at repeated saturation biopsy. Which cut-off: 20 or 35?

PURPOSE

To compare PCA3 score cut-off of 35 vs 20 in PCa diagnosis in patients undergoing repeated saturation prostate biopsy (SPBx).

MATERIAL AND METHODS

From January 2010 to May 2011, 118 patients (median 62.5 years) with primary negative extended biopsy underwent a transperineal SPBx (median 30 cores) for persistent suspicion of PCa. The indications for repeated biopsy were: persistently high or increasing PSA values; PSA > 10 ng/mL, PSA values between 4.1-10 or 2.6-4 ng/mL with free/total PSA ≤ 25% and ≤ 20 %, respectively; moreover, before performing SPBx urinary PCA3 score was evaluated.

RESULTS

All patients had negative DRE and median PSA was 8.5 ng/mL (range: 3.7-24 ng/mL). A T1c PCa was found in 32 patients (27.1 %): PCA3 score was 59 (median; range: 7-201) in the presence of PCa and 35 (median; range: 3-253) in the absence of cancer (p < 0.05). In the presence of ASAP and HGPIN median PCA3 score was 109 (range: 42-253) and 40 (range: 30-140), respectively. Diagnostic accuracy, sensitivity, specificity, PPV and NPV of PCA3 score cut-off of 20 vs 35 in PCa diagnosis were 44.9 vs 50 %, 90.6 vs 71.9 %, 27.9 vs 41.8 %, 31.9 vs 31.5 % and 88.9 vs 80 %, respectively. ROC analysis demonstrated an AUC for PCA3 ≥ 20 vs ≥ 35 of 0.678 and 0.634, respectively.

CONCLUSIONS

Our data suggest that PCA3 is more useful as an exclusion tool; moreover, setting a PCA3 cut-off at 20 vs 35, would have avoided 22.9 vs 38.1 % of biopsies while missing 9.4 % and 28 % diagnosis of PCa.

Clinical applications of recent molecular advances in urologic malignancies: no longer chasing a "mirage"?

As our understanding of the molecular events leading to the development and progression of genitourologic malignancies, new markers of detection, prognostication, and therapy prediction can be exploited in the management of these prevalent tumors. The current review discusses the recent advances in prostate, bladder, renal, and testicular neoplasms that are pertinent to the anatomic pathologist.

PCA3 in the detection and management of early prostate cancer

Although widely used, the value of prostate-specific antigen (PSA) in the detection of prostate cancer is controversial. The percentage of free PSA increases the specificity of PSA, but results are not enough. Prostate cancer gene 3 (PCA3) has been proposed as an option that may complement these markers in the detection and management of early prostate cancer. Our aim has been to review the value of PCA3 as tumor marker. The available results suggest that PCA3 is particularly useful to select in which patients the biopsy should be repeated when the first biopsy was negative. However, some points should be specified with further studies, including the most appropriate PCA3 cutoff level and the significance of a high PCA3 score in patients with negative biopsy. False-negative results are also a conflictive point in the use of PCA3, because prostate cancer, including aggressive tumors, may be present in patients with a low PCA3 score. Probably, a proper interpretation of this test requires its management together with other tests, through multivariate models for the detection of prostate cancer. On the other hand, several studies showed the relation between PCA3 score and Gleason score, and also the utility of PCA3 to select patients for active surveillance. To summarize, the available studies show the utility of PCA3 in the detection and management of early prostate cancer, although some aspects referred to its use need to be retested after further studies to confirm the actual value and the limitations of this test.

Urine TMPRSS2:ERG fusion transcript integrated with PCA3 score, genotyping, and biological features are correlated to the results of prostatic biopsies in men at risk of prostate cancer

BACKGROUND

Detection of fusion gene TMPRSS2:ERG transcripts in urine have been recently described in order to refine urine-based detection of prostate cancer (PCa), but data its clinical impact remain scarce. We aimed at investigating the correlation of TMPRSS2:ERG, prostate cancer antigen 3 (PCA3), prostate specific antigen (PSA) density, genetic variants, and androgenic status with outcome and pathological findings at prostatic biopsy.

METHODS

Between 2007 and 2011, 291 patients at risk of PCa because of PSA > 3.0 ng/ml (55%) or candidate to active surveillance protocol justifying restaging biopsy management (45%) were recruited. TMPRSS2:ERG was detected by urine assay (Progensa™). PCA3-score, PSA level, bioavailable testosterone level, prostate volume, rs1447295 and rs6983267 genotypes were prospectively assessed. Univariate and multivariate analysis by logistic regression model (logit) were conducted to study the correlation of TMPRSS2:ERG status, PCA3, and PSA density with biopsy results, and Gleason score.

RESULTS

Of 291 patients, 173 had PCa and 118 had negative biopsy. PCA3 score, PSA density and TMPRSS2:ERG-score were correlated with presence of PCa (P < 0.0001, P = 0.046, and P < 0.0001, respectively). This correlation remained strong on multivariable analysis model (area under curve 0.743). PCA3 score and PSA density were significantly associated with presence of Grade 4 through multivariable analysis. PCA3 score was also correlated to the percentage of positive cores at biopsy (P = 0.008).

CONCLUSIONS

Integration of levels TMPRSS2:ERG transcripts in urine, with PCA3-score, androgenic status, genetic status and traditional clinical variables could significantly increase detection of high risk localized PCa.

Prostate health index (phi) and prostate cancer antigen 3 (PCA3) significantly improve diagnostic accuracy in patients undergoing prostate biopsy

BACKGROUND

Prostate health index (phi) and prostate cancer antigen 3 (PCA3) have been recently proposed as novel biomarkers for prostate cancer (PCa). We assessed the diagnostic performance of these biomarkers, alone or in combination, in men undergoing first prostate biopsy for suspicion of PCa.

METHODS

One hundred sixty male subjects were enrolled in this prospective observational study. PSA molecular forms, phi index (Beckman coulter immunoassay), PCA3 score (Progensa PCA3 assay), and other established biomarkers (tPSA, fPSA, and %fPSA) were assessed before patients underwent a 18-core first prostate biopsy. The discriminating ability between PCa-negative and PCa-positive biopsies of Beckman coulter phi and PCA3 score and other used biomarkers were determined.

RESULTS

One hundred sixty patients met inclusion criteria. %p2PSA (p2PSA/fPSA × 100), phi and PCA3 were significantly higher in patients with PCa compared to PCa-negative group (median values: 1.92 vs. 1.55, 49.97 vs. 36.84, and 50 vs. 32, respectively, P ≤ 0.001). ROC curve analysis showed that %p2PSA, phi, and PCA3 are good indicator of malignancy (AUCs = 0.68, 0.71, and 0.66, respectively). A multivariable logistic regression model consisting of both the phi index and PCA3 score allowed to reach an overall diagnostic accuracy of 0.77. Decision curve analysis revealed that this "combined" marker achieved the highest net benefit over the examined range of the threshold probability.

CONCLUSIONS

phi and PCA3 showed no significant difference in the ability to predict PCa diagnosis in men undergoing first prostate biopsy. However, diagnostic performance is significantly improved by combining phi and PCA3.

Artificial neural networks and prostate cancer--tools for diagnosis and management

Artificial neural networks (ANNs) are mathematical models that are based on biological neural networks and are composed of interconnected groups of artificial neurons. ANNs are used to map and predict outcomes in complex relationships between given 'inputs' and sought-after 'outputs' and can also be used find patterns in datasets. In medicine, ANN applications have been used in cancer diagnosis, staging and recurrence prediction since the mid-1990s, when an enormous effort was initiated, especially in prostate cancer detection. Modern ANNs can incorporate new biomarkers and imaging data to improve their predictive power and can offer a number of advantages as clinical decision making tools, such as easy handling of distribution-free input parameters. Most importantly, ANNs consider nonlinear relationships among input data that cannot always be recognized by conventional analyses. In the future, complex medical diagnostic and treatment decisions will be increasingly based on ANNs and other multivariate models.

Clinical utility of the prostate cancer gene 3 (PCA3) urine assay in Japanese men undergoing prostate biopsy

WHAT'S KNOWN ON THE SUBJECT? AND WHAT DOES THE STUDY ADD?: It is known that a prostate cancer gene 3 (PCA3) urine assay is superior to serum PSA level or PSA-related indices for predicting a positive biopsy result in European and US men. This is the first report on PCA3 in a large cohort of Japanese men. The diagnostic value of the PCA3 score in Japanese men was similar to those reported in European and US men. The study concludes that a combination of PSA density and PCA3 score may be useful for selecting patients who could avoid an unnecessary biopsy.

OBJECTIVE

To examine the diagnostic performance of the prostate cancer gene 3 (PCA3) score for prostate cancer in Japanese men undergoing prostate biopsy.

PATIENTS AND METHODS

This Japanese, multicentre study included 647 Asian men who underwent extended prostate biopsy with elevated prostate-specific antigen (PSA) and/or abnormal digital rectal examination (DRE). Urine samples were collected after DRE. The PCA3 score was determined using a PROGENSA PCA3 assay and correlated with biopsy outcome. Its diagnostic accuracy was compared with that of serum PSA level, prostate volume (PV), PSA density (PSAD), and free/total PSA ratio (f/t PSA).

RESULTS

A total of 633 urine samples were successfully analysed (the informative rate was 98%). Median PSA was 7.6 ng/mL. Biopsy revealed cancer in 264 men (41.7%). The PCA3 score for men with prostate cancer was significantly higher than that for men with negative biopsies (median PCA3 score: 49 vs. 18; P < 0.001). The rate of positive biopsy was 16.0% in men with a PCA3 score of <20 and 60.6% in those with a PCA3 score of ≥50. Using a PCA3 score threshold of 35, sensitivity and specificity were 66.5 and 71.6%, respectively. The area under the curve of the PCA3 score was significantly higher than that of the f/t PSA in men with PSA 4-10 ng/mL (0.742 vs 0.647; P < 0.05). In men with PSAD < 0.15 and PCA3 < 20, only three (4.2%) out of 72 men had prostate cancer.

CONCLUSIONS

The PCA3 score was significantly superior to f/t PSA in predicting a positive biopsy result for prostate cancer in Japanese men with PSA 4-10 ng/mL. The combination of PSAD and PCA3 score may be useful for selecting patients who could avoid an unnecessary biopsy.

Relationship between prostate cancer gene 3 (PCA3) and characteristics of tumor aggressiveness

BACKGROUND

Data supporting prostate cancer gene 3 (PCA3) as prognostic marker are still inconsistent. With special emphasis to Gleason pattern specific tumor volumes (TVs) the relationships between PCA3 score and different characteristics of tumor aggressiveness were meticulously analyzed.

METHODS

In 127 patients treated with radical prostatectomy for clinically localized prostate cancer, urinary PCA3 score was quantified using Progensa™ PCA3 assay. Total TV and Gleason patterns' specific tumor volumes (GPTV) were assessed by computer-assisted planimetry. Spearman's rank correlations coefficients (r) were calculated to assess relationships between PCA3 and TV as well as GPTV. Regression analyses were performed to estimate the relationship between PCA3 and TV as well as non-organ confined disease.

RESULTS

Mean patients' age was 60.8 years. Patients showed a mean PSA level of 8.1 ng/ml and a mean PCA3 score of 68.5. PCA3 was not significantly correlated with TV (r = 0.131, P = 0.142). Stratified by Gleason score groups ≤ 6, 7, and ≥ 8, PCA3 showed no significant correlations with TV. In a subgroup analysis of 50 patients with different primary and secondary Gleason patterns there was neither a correlation with the primary GPTV (r = 0.071, P = 0.626) nor with the secondary GPTV (r = 0.052, P = 0.722). The PCA3 score was neither an independent predictor for TV nor for non-organ confined disease.

CONCLUSIONS

The PCA3 score did not show any significant correlation with TV, primary or secondary GPTV. Moreover, the PCA3 score was not an independent predictor for TV or for non-organ confined disease. Thus, the PCA3 score had no impact for the prediction of aggressive prostate cancers.

Use of PCA3 in detecting prostate cancer in initial and repeat prostate biopsy patients

BACKGROUND

The PCA3 urinary assay has shown promise in predicting the presence of prostate cancer. We evaluated the value of this test in patients undergoing initial and repeat prostate biopsy.

METHODS

PCA3 and PSA levels were obtained from 456 men with no known personal history of prostate cancer prior to prostate biopsy. Two hundred eighty-nine men underwent an initial prostate biopsy and 167 underwent a repeat prostate biopsy. PCA3 and PSA levels were compared to the prostate biopsy results.

RESULTS

PCA3 score was shown to be independent of prostate volume (P = 0.162) and PSA level (P = 0.959). PCA3 scores were significantly higher in patients with cancer on prostate biopsy compared to patients with negative biopsy results (P < 0.0001). In logistic regression, PCA3 showed a significantly higher AUC than PSA (0.726 vs. 0.512, P = 0.0001). This difference persisted when examining the initial biopsy subgroup, with PCA3 out-performing PSA (AUC 0.772 vs. AUC = 0.552, P < 0.0001), but not in the repeat biopsy subgroup (AUC = 0.605 vs. AUC = 0.500, P = 0.2488).

CONCLUSIONS

PCA3 was found to be a better predictor of prostate cancer than PSA in the total population as well as the initial biopsy population, but was not superior to PSA in the repeat biopsy population. Prostate 73: 48-53, 2013. © 2012 Wiley Periodicals, Inc.

Rational basis for the combination of PCA3 and TMPRSS2:ERG gene fusion for prostate cancer diagnosis

BACKGROUND

The prostate cancer gene 3 (PCA3) and TMPRSS2:ERG gene fusion are promising prostate cancer (PCa) specific biomarkers. Our aim was to simultaneously quantify the expression levels of PCA3 and TMPRSS2:ERG in a panel of benign prostatic hyperplasia (BPH), normal prostate adjacent to PCa (NP) and PCa tissue samples, to provide a rational basis for the understanding of the false-positive and false-negative results of the urine assays.

METHODS

The tissue samples were carefully histopathologically characterized to obtain homogeneous groups. The mRNA was isolated, transcribed into cDNA and the relative expressions of PCA3 and TMPRSS2:ERG were measured using a quantitative real-time polymerase chain reaction. The expression levels of PCA3 and TMPRSS2:ERG were compared between the different groups.

RESULTS

We included 48 BPH, 32 NP, and 48 PCa. The PCA3 expression levels progressively increased from BPH to NP (3 times) and finally to PCa (30 times). There were one false-positive sample and seven false-negative samples. The TMPRSS2:ERG gene fusion was found in 8.3% of the BPH, 15.6% of the NP, and 50% of the PCa samples. The use of TMPRSS2:ERG in the PCA3 negative cases allowed diagnosis of four of the seven false-negative samples and added one false-positive, but we had to define a cut-off value to avoid eight false-positive results.

CONCLUSIONS

Considering tissue expression of the markers, most of the false-negative results of the PCA3 test were corrected by TMPRSS2:ERG (57%) and the combination of both had a higher sensitivity for PCa diagnosis. Some of the control samples did express TMPRSS2:ERG and a cut-off value had to be defined to avoid false-positive results.

Impact of adoption of a decision algorithm including PCA3 for repeat biopsy on the costs for prostate cancer diagnosis in France

OBJECTIVE

A recent expert study (RAND Appropriateness Method (RAM)) including a panel of 12 European urologists reported that the PCA3 score may be instrumental in taking appropriate prostate biopsy (PBx) decisions, mainly for repeat PBx. This study determined the cost/benefit balance of introducing PCA3 in the decision-making for PBx in France.

METHODS

Two RAM models, without and with PCA3, were retrospectively applied to a sample of 808 French men who had PBx in 2010 (78% first, 22% repeat). Outcome measures included the proportion of PBx that could have been avoided (i.e., judged inappropriate) in the French sample according to both RAM models, and the estimated impact of application of these models on the annual number of PBx and associated costs for France (based on most recent published data).

RESULTS

Complete profiles were available for 698 men. In the model without PCA3, 2% of PBx were deemed inappropriate. Knowledge of PCA3 would have avoided another 7% of PBx. Repeat PBx would have been avoided in 5% of cases without PCA3 and in 37% with PCA3. For France, application of the RAM model including PCA3 would result in 18,345 fewer repeat PBx. It would be budget-neutral in the unlikely hypothesis of no complications or no costs incurred by complications and would save €1.7 million for a mean cost for complications of €100/procedure or €5 million for a mean cost for complications of €280/procedure, calculated based on US and Canadian data.

LIMITATIONS

Limitations of the study are the theoretical nature of the analysis and the fact that PCA3 distributions had to be derived from other sources.

CONCLUSIONS

Adoption of RAM expert recommendations including PCA3 for repeat PBx decisions in clinical practice in France would reduce the number of repeat PBx and control costs.

Personalized management in low-risk prostate cancer: the role of biomarkers

Current criteria to predict low-risk prostate cancer (PCa) are still subject to discussion as a substantial number of PCa patients who progress to a more aggressive disease seem to be missed, using these criteria. The main challenge in PCa diagnosis, therefore, is to distinguish patients with low-risk PCa who will show slow progression of disease from patients at risk for progression to a more aggressive cancer. The current discovered biomarkers could potentially guide in this management and improve detection, staging, and prognosis. This paper provides an overview of the current available serum-, urine-, and tissue-based biomarkers in PCa and evaluates the clinical usefulness of these biomarkers in the detection and management of low-risk PCa.

Comparative assessment of urinary prostate cancer antigen 3 and TMPRSS2:ERG gene fusion with the serum [-2]proprostate-specific antigen-based prostate health index for detection of prostate cancer

BACKGROUND

We compared urinary prostate cancer antigen 3 (PCA3), transmembrane protease, serine 2 (TMPRSS2):v-ets erythroblastosis virus E26 oncogene homolog (avian) (ERG) gene fusion (T2:ERG), and the serum [-2]proprostate-specific antigen ([-2]proPSA)-based prostate health index (Phi) for predicting biopsy outcome.

METHODS

Serum samples and first-catch urine samples were collected after digital rectal examination (DRE) from consented outpatients with PSA 0.5-20 μg/L who were scheduled for prostate biopsy. The PCA3 score (PROGENSA PCA3, Hologic Gen-Probe) and T2:ERG score (Hologic Gen-Probe) were determined. Measurements of serum PSA, free PSA, and [-2]proPSA (Beckman Coulter) were performed, and the percentages of free PSA (%fPSA) and Phi ([-2]proPSA/fPSA × √PSA) were determined.

RESULTS

Of 246 enrolled men, prostate cancer (PCa) was diagnosed in 110 (45%) and there was no evidence of malignancy (NEM) in 136 (55%). A first set of biopsies was performed in 136 (55%) of all men, and 110 (45%) had ≥1 repeat biopsies. PCA3, Phi, and T2:ERG differed significantly between men with PCa and NEM, and these markers showed the largest areas under the ROC curve (AUCs) (0.74, 0.68, and 0.63, respectively). PCA3 had the largest AUC of all parameters, albeit not statistically different from Phi. Phi showed somewhat lower specificities than PCA3 at 90% sensitivity. Combination of both markers enhanced diagnostic power with modest AUC gains of 0.01-0.04. Although PCA3 had the highest AUC in the repeat-biopsy cohort, the highest AUC for Phi was observed in DRE-negative patients with PSA in the 2-10 μg/L range.

CONCLUSIONS

PCA3 and Phi were superior to the other evaluated parameters but their combination gave only moderate enhancements in diagnostic accuracy for PCa at first or repeat prostate biopsy.