Urinary Prostate Cancer 3 Test: Toward the Age of Reason?

Urinary PCA3 a Superior Diagnostic Biomarker for Prostate Cancer among Ghanaian Men

Introduction. Prostate cancer is one of the most commonly diagnosed cancers in men. Prostate-specific antigen (PSA) has been the biomarker of choice for screening and diagnosis of prostate cancer. However, inefficiencies exist with its diagnostic capabilities. This study thus evaluated the diagnostic and prognostic potential of urinary PCA3 as an alternative biomarker for prostate cancer in the Ghanaian population. Methods. A hospital-based cross-sectional study was conducted at the Urology Department of the 37 Military Hospital, Accra, Ghana. A total of 237 participants aged 40 years and above with any form of suspected prostate disorder were recruited into the study after written informed consent was obtained. Total serum PSA levels was measured using the electrochemiluminescence method and transrectal ultrasound-guided systematic core needle biopsies were obtained from each study participant. Receiver operating characteristic curve (ROC) analysis was used to evaluate the diagnostic accuracies of serum PSA, DRE, and PCA3 as diagnostic tools for prostate cancer. These three diagnostic tools were also evaluated in various combinations to ascertain the combinations with the best diagnostic accuracy. Results. Prostate cancer was diagnosed in 26.6% of the participants. Benign prostate hyperplasia and prostatitis were diagnosed in 48.5% and 24.9% participants, respectively. DRE had a sensitivity of 93.7% and a specificity of 12.1%. PSA had a sensitivity of 92.1% and a specificity of 16.1%. PCA3 had a sensitivity of 57.1% and a specificity of 85.6% and showed a better accuracy ( $\text{AUC}=83.0$ ) compared to PSA ( $\text{AUC}=60.0$ ) and DRE ( $\text{AUC}=65.0$ ) as individual diagnostic tools. The combination of DRE+PCA3 score had the best diagnostic accuracy ( $\text{AUC}=0.80$ ) with a sensitivity and specificity of 60.3% and 80.5%, respectively. Conclusion. The urinary PCA3 assay showed a better diagnostic performance compared to serum PSA and DRE. PCA3 as a stand-alone and in combination with DRE could be a suitable complimentary marker in diagnosis and management of prostate cancer.

Long Noncoding RNAs as Innovative Urinary Diagnostic Biomarkers

The characterization of circulating tumor cells (CTCs) is now widely studied as a promising source of cancer-derived biomarkers because of their role in tumor formation and progression. However, CTCs analysis presents some limitations and no standardized method for CTCs isolation from urine has been defined so far. In fact, besides blood, urine represents an ideal source of noninvasive biomarkers, especially for the early detection of genitourinary tumors. Besides CTCs, long noncoding RNAs (lncRNAs) have also been proposed as potential noninvasive biomarkers, and the evaluation of the diagnostic accuracy of urinary lncRNAs has dramatically increased over the last years, with many studies being published. Therefore, this review provides an update on the clinical utility of urinary lncRNAs as novel biomarkers for the diagnosis of bladder and prostate cancers.

A novel urinary mRNA signature using the droplet digital polymerase chain reaction platform improves discrimination between prostate cancer and benign prostatic hyperplasia within the prostate-specific antigen gray zone

Purpose

The aim of this study was to identify a noninvasive urinary marker for prostate cancer (PCa) diagnosis and to validate the clinical performance of this novel urinary mRNA signature using the droplet digital polymerase chain reaction (ddPCR) approach.

Materials and Methods

A gene expression microarray (HT-12, Illumina Inc., USA) was used to identify genes differentially expressed between 16 PCa and 8 benign prostatic hyperplasia (BPH) tissues; ddPCR (QX200; Bio-Rad Laboratories, USA) was carried out to quantify the expression of selected genes in urine. The urinary molecular PCa risk score (UMPCaRS) was calculated by using the sum of three upregulated genes as the numerator and the sum of three downregulated genes as the denominator. The diagnostic utility of the UMPCaRS was validated by using a screening set (10 PCa and 10 BPH samples) and a validation set (131 PCa and 105 BPH samples).

Results

Three upregulated genes (PDLIM5, GDF-15, THBS4) and three downregulated genes (UPK1A, SSTR3, NPFFR2) were selected from the microarray and subjected to ddPCR. The UMPCaRS for PCa in the screening and validation sets was significantly higher than that for BPH. For the validation set, the diagnostic accuracy of the UMPCaRS was comparable with that of prostate-specific antigen (PSA). Importantly, in the "PSA gray zone" (3-10 ng/mL), the AUC for the UMPCaRS was 0.843 and that for PSA was 0.628 (p<0.001).

Conclusions

The data demonstrate that the UMPCaRS is useful for discriminating between PCa and BPH in the "PSA gray zone".

Prostate cancer and the role of biomarkers

PURPOSE

To review available prostate cancer biomarkers and their performance in a clinical order, from prostate cancer detection, to treatment of localized and advanced disease.

METHODS

We used an electronic literature search of the PubMed database using the key words "prostate biomarkers," "genomic markers," and "prostate cancer screening," as well as specific biomarkers, until March 2019.

RESULTS

Prostate-specific antigen (PSA) lacks sensitivity for prostate cancer detection, and PSA derivatives have slightly improved its specificity, but have not resolved the limitations of PSA screening. Prostate cancer biomarkers have emerged as an ancillary tool to guide the clinical decision-making in different clinical scenarios. Urine-based tests can identify patients who may benefit from a prostate biopsy, and issue-based markers are helpful in guiding the decision regarding a second biopsy, stratifying patient with newly diagnosed prostate cancer to active surveillance or treatment, and identifying patients who may benefit from adjuvant treatment after surgery.

CONCLUSIONS

New biomarkers have improved risk stratification in diagnosing and treating prostate cancer. Many of these markers are still considered experimental, and their efficacy and cost utility have not been determined.

From biomarkers to therapeutic targets-the promises and perils of long non-coding RNAs in cancer

Biomarker-driven personalized cancer therapy is a field of growing interest, and several molecular tests have been developed to detect biomarkers that predict, e.g., response of cancers to particular therapies. Identification of these molecules and understanding their molecular mechanisms is important for cancer prognosis and the development of therapeutics for late stage diseases. In the past, significant efforts have been placed on the discovery of protein or DNA-based biomarkers while only recently the class of long non-coding RNA (lncRNA) has emerged as a new category of biomarker. The mammalian genome is pervasively transcribed yielding a vast amount of non-protein-coding RNAs including lncRNAs. Hence, these transcripts represent a rich source of information that has the potential to significantly contribute to precision medicine in the future. Importantly, many lncRNAs are differentially expressed in carcinomas and they are emerging as potent regulators of tumor progression and metastasis. Here, we will highlight prime examples of lncRNAs that serve as marker for cancer progression or therapy response and which might represent promising therapeutic targets. Furthermore, we will introduce lncRNA targeting tools and strategies, and we will discuss potential pitfalls in translating these into clinical trials.

Obstacles in prostate cancer screening: Current issues and future solutions

Prostate cancer is the most common cancer in men and is associated with unacceptably high mortality rates, yet an accurate and acceptable screening programme that detects clinically significant prostate cancer remains elusive. Although there is good evidence that prostate-specific antigen (PSA)-based screening lowers prostate cancer-specific mortality, especially when conducted at high intensity, the harm caused by overinvestigation, overdiagnosis and overtreatment of clinically insignificant cases arguably outweighs these benefits. Several attempts have therefore been made to improve screening, enhancing the diagnostic value of PSA and identifying novel modalities for screening. Here, we provide a comprehensive review of the benefits and harms, and analyse which of these novel screening methods show most promise.

Level of evidence: 5, expert opinion

Association between human papillomavirus infection and prostate cancer: A global systematic review and meta-analysis

Although an increasing number of studies have been conducted to evaluate the association between human papillomavirus (HPV) infections and distribution of HPV types worldwide with the risk of prostate cancer (PC), the results remain inadequate. Hence, we investigated the association between HPV infection and PC risk using a meta-analysis. Relevant studies from January 1990 to December 2016 were searched in PubMed, Web of sciences, and Scopus databases. Pooled odds ratio (OR) and their corresponding 95% confidence interval (CI) were calculated to find the association between the prevalence of HPV and prostate cancer risk. To do so, data from 24 studies with 5546 prostate cancer cases were pooled in order to evaluate the heterogeneity of chief parameters including study region, specimen type, HPV DNA source, detection technique, publication calendar period, and Gleason score. All statistical analyses were performed using STATA 11 and MedCalc 13. A significant positive association was found between HPV infection and PC risk (OR = 1.281; P = 0.026). The genotype 16 was more frequently found in patients with PC which significantly increased the cancer risk (OR = 1.60; P < 0.001). Age 65 and older could significantly escalate PC risk (OR = 3.564; P < 0.001). Our results clearly favor the potential pathogenetic link between HPV infection and increased risk of PC affirming that HPV infections could play a part in the risk of PC.

Identification of Multisialylated LacdiNAc Structures as Highly Prostate Cancer Specific Glycan Signatures on PSA

Serum prostate-specific antigen (PSA) test is the current gold standard for screening and diagnosis of prostate cancer (PCa), while overdiagnosis and overtreatment are social problems. In order to improve the specificity and exclude a false positive diagnosis in PSA test, PCa-specific glycosylation subtypes of PSA were explored using in-depth quantitative profiling of PSA glycoforms based on mass spectrometric oxonium ion monitoring technology. As a result of analysis using sera from 15 PCa or 15 benign prostate hyperplasia (BPH) patients whose PSA levels were in the "gray zone" (4.0-10.0 ng/mL), 52 glycan structures on PSA were quantitatively observed. We found that abundance of multisialylated LacdiNAc (GalNAcβ1-4GlcNAc) structures were significantly upregulated in the PCa group compared to the BPH group. A couple of those glycoforms were then extracted and subjected to establish a novel PCa-specific diagnosis model (PSA G-index). When the diagnostic power was assessed using an independent validation sample set (15 PCa and 15 BPH patients in the PSA gray zone), an AUC of PSA G-index was 1.00, while that of total PSA or PSA f/T ratio was 0.50 or 0.60, respectively. Moreover, both PSA glycoforms showed significant correlation with Gleason scores. Lectin histochemical staining analysis also showed that PCa cells overexpressed glycoproteins containing LacdiNAc and sialic acids moieties. Thus, PSA G-index could serve as not only an effective secondary screening method to exclude false positive diagnosis in PSA screening, but also a potential grading biomarker for PCa.

Long non-coding RNAs in prostate cancer: Biological and clinical implications

Prostate cancer (PCa) is a major health issue in the Western world. Current clinical imperatives for this disease include better stratification of indolent versus aggressive disease to enable improved patient management, as well as the identification of more effective therapies for the prevention and treatment of metastatic and therapy-resistant PCa. The advent of next-generation transcriptomics led to the identification of an important class of molecules, long non-coding RNAs (lncRNAs). LncRNAs have critical functions in normal physiology, but their dysregulation has also been implicated in the development and progression of a variety of cancers, including PCa. Importantly, a subset of lncRNAs are highly prostate-specific, suggesting potential for utility as both biomarkers and therapeutic targets. In this review, we summarise the biology of lncRNAs and their mechanisms of action in the development and progression of prostate cancer. Additionally, we cast a critical eye over the potential for this class of molecules to impact on clinical practice.

The Diverse Mechanisms of miRNAs and lncRNAs in the Maintenance of Liver Cancer Stem Cells

Liver cancer is the second leading cause of cancer-related death worldwide. The high frequency of recurrence and metastasis is the main reason for poor prognosis. Liver cancer stem cells (CSCs) have unlimited self-renewal, differentiation, and tumor-regenerating capacities. The maintenance of CSCs may account for the refractory features of liver cancer. Despite extensive investigations, the underlying regulatory mechanisms of liver CSCs remain elusive. miRNA and lncRNA, two major classes of the ncRNA family, can exert important roles in various biological processes, and their diverse regulatory mechanisms in CSC maintenance have acquired increasing attention. However, to the best of our knowledge, there is a lack of reviews summarizing these findings. Therefore, we systematically recapitulated the latest studies on miRNAs and lncRNAs in sustaining liver CSCs. Moreover, we highlighted the potential clinical application of these dysregulated ncRNAs as novel diagnostic and prognostic biomarkers and therapeutic targets. This review not only sheds new light to fully understand liver CSCs but also provides valuable clues on targeting ncRNAs to block or eradicate CSCs in cancer treatment.

Urinary extracellular vesicle biomarkers in urological cancers: From discovery towards clinical implementation

Urine contains cellular elements, biochemicals, and proteins derived from glomerular filtration of plasma, renal tubule excretion, and urogenital tract secretions that reflect an individual's metabolic and pathophysiologic state. Despite intensive research into the discovery of urinary biomarkers to facilitate early diagnosis, accurate prognosis and prediction of therapy response in urological cancers, none of these markers has reached widespread use. Their implementation into daily clinical practice is hampered by a substantial degree of heterogeneity in performance characteristics and uncertainty about reliability, clinical utility and cost-effectiveness, in addition to several technical limitations. Extracellular vesicles (EV) have raised interest as a potential source of biomarker discovery because of their role in intercellular communication and the resemblance of their molecular content to that of the releasing cells. We review currently used urinary biomarkers in the clinic and attempts that have been made to identify EV-derived biomarkers for urological cancers. In addition, we discuss technical and methodological considerations towards their clinical implementation.

Update on Screening for Urological Malignancies

Urological malignancies are a major source of morbidity and mortality in men over 40. Screening for those malignancies has a potential benefit of reducing both. However, even after more than two decades of screening for prostate cancer, the implications of most resulting information are still a matter of debate. Controversy extends over several aspects of prostate cancer screening programs, including age of onset, defining populations at risk, most appropriate intervals, as well as the optimal methods to be used for screening. The medical community is still divided regarding the effectiveness of prostate cancer-related death prevention and its benefits-to-harms ratio, reflecting an inconsistency regarding screening recommendations. Similarly, benefits of screening for urothelial and kidney tumors are yet lacking high-level evidence, although recent evidence supports screening of populations at risk. Clearly, the current era of evolving molecular and genetic biomarkers harbors the potential to change screening practice. In this paper, we review current guidelines as well as giving an update on new developments which might influence screening strategies in common urological malignancies.

Urinary long noncoding RNAs in nonmuscle-invasive bladder cancer: new architects in cancer prognostic biomarkers

Several reports over the last 10 years provided evidence that long noncoding RNAs (lncRNAs) are often altered in bladder cancers. lncRNAs are longer than 200 nucleotides and function as important regulators of gene expression, interacting with the major pathways of cell growth, proliferation, differentiation, and survival. A large number of lncRNAs has oncogenic function and is more expressed in tumor compared with normal tissues. Their overexpression may be associated with tumor formation, progression, and metastasis in a variety of tumors including bladder cancer. Although lncRNAs have been shown to have critical regulatory roles in cancer biology, the biological functions and prognostic values in nonmuscle-invasive bladder cancer remain largely unknown. Nevertheless, a growing body of evidence suggests that several lncRNAs expression profiles in bladder malignancies are associated with poor prognosis, and they can be detected in biological fluids, such as urines. Here, we review current progress in the biology and the implication of lncRNAs associated with bladder cancer, and we discuss their potential use as diagnosis and prognosis biomarkers in bladder malignancies with a focus on their role in high-risk nonmuscle-invasive tumors.

Prostate Cancer Antigen 3 Score Does Not Predict for Adverse Pathologic Features at Radical Prostatectomy or for Progression-free Survival in Clinically Localized, Intermediate- and High-risk Prostate Cancer

OBJECTIVE

To evaluate whether preoperative urinary prostate cancer antigen 3 (PCA3) scores predict for adverse pathologic features (APFs) or progression-free survival (PFS) in men with intermediate- or high-risk prostate cancer (PCa) undergoing radical prostatectomy (RP).

MATERIALS AND METHODS

One hundred nine men with intermediate- (n = 52) or high-risk (n = 57) PCa who underwent RP were retrospectively identified. Logistic regression analysis was performed to evaluate the association of PCA3 score with various APFs (eg, extracapsular extension, seminal vesicle invasion, etc.). Among 78 men with ≥1 year of follow-up, the association between PCA3 score and PFS was assessed using Cox regression analysis.

RESULTS

At RP, 52% of patients had at least 1 APF, and with median follow-up of 2.3 years, overall 3-year PFS was 70%. PCA3 was not a significant predictor of any APF on multivariate analysis (MVA), whereas canonical predictors (eg, biopsy Gleason score and initial prostate-specific antigen) remained predictive of various APFs. No significant predictors for PFS were found on MVA, although certain canonical predictors (eg, National Comprehensive Cancer Network risk group) were significant predictors of PFS on univariate analysis (UVA). PCA3 score was not a significant predictor of PFS on either UVA or MVA.

CONCLUSION

Unlike in lower risk cohorts, increasing PCA3 score was not associated with any APF in this higher risk cohort, despite enrichment for APFs, nor was it associated with PFS. Notably, multiple known preoperative predictors for APFs were significant on MVA, and multiple predictors were associated with PFS on UVA. Therefore, PCA3 may not be a useful adjunct predictive marker in men with intermediate- or high-risk PCa.

Improving the evaluation and diagnosis of clinically significant prostate cancer in 2017

PURPOSE OF REVIEW

To provide an overview of the current state of the evidence and highlight recent advances in the evaluation and diagnosis of clinically significant prostate cancer, focusing on biomarkers, risk calculators and multiparametric MRI (mpMRI).

RECENT FINDINGS

In 2017 there are numerous options to improve early detection as compared to a purely prostate-specific antigen (PSA)-based approach. All have strengths and drawbacks. In addition to repeating the PSA and performing clinical work-up (digital rectal examination and estimation of prostate volume), additional tests investigated in the initial biopsy setting are: %free PSA, Prostate Health Index, 4-kallikrein score, SelectMDx, and Michigan Prostate Score and in the repeat setting: %free PSA, Prostate Health Index, 4-kallikrein score, Prostate Cancer Antigen 3, and ConfirmMDx. Risk calculators are available for both biopsy settings and incorporate clinical data with, or without, biomarkers. mpMRI is an important diagnostic adjunct.

SUMMARY

There are numerous tests available that can help increase the specificity of PSA, in the initial and repeat biopsy setting. All coincide with a small decrease in sensitivity of detecting high-grade cancer. Cost effectiveness is crucial. The way forward is a multivariable risk assessment on the basis of readily available clinical data, potentially with the addition of PSA subforms, preferably at low cost. MRI in the prediagnostic setting is promising, but is not ready for 'prime time'.

Epigenomic Regulation of Androgen Receptor Signaling: Potential Role in Prostate Cancer Therapy

Androgen receptor (AR) signaling remains the major oncogenic pathway in prostate cancer (PCa). Androgen-deprivation therapy (ADT) is the principle treatment for locally advanced and metastatic disease. However, a significant number of patients acquire treatment resistance leading to castration resistant prostate cancer (CRPC). Epigenetics, the study of heritable and reversible changes in gene expression without alterations in DNA sequences, is a crucial regulatory step in AR signaling. We and others, recently described the technological advance Chem-seq, a method to identify the interaction between a drug and the genome. This has permitted better understanding of the underlying regulatory mechanisms of AR during carcinogenesis and revealed the importance of epigenetic modifiers. In screening for new epigenomic modifiying drugs, we identified SD-70, and found that this demethylase inhibitor is effective in CRPC cells in combination with current therapies. The aim of this review is to explore the role of epigenetic modifications as biomarkers for detection, prognosis, and risk evaluation of PCa. Furthermore, we also provide an update of the recent findings on the epigenetic key processes (DNA methylation, chromatin modifications and alterations in noncoding RNA profiles) involved in AR expression and their possible role as therapeutic targets.

Evaluation of expressed prostatic secretion and serum using surface-enhanced Raman spectroscopy for the noninvasive detection of prostate cancer, a preliminary study

Surface-enhanced Raman spectroscopy (SERS) involving expressed prostatic secretion (EPS) and serum was investigated; the objective was to determine if this approach could distinguish prostate cancer from benign prostatic hyperplasia. A total of 120 SERS spectra for EPS and 96 spectra for serum were gathered from patients within a prospective contemporary biopsy cohort. Significant differences in spectra between prostate cancer and benign prostatic hyperplasia were tentatively assigned to component changes in EPS and serum samples. Principal component analysis and linear discriminate analysis were utilized to evaluate the spectral data for EPS and serum, to build diagnostic algorithms. The leave-one-out cross-validation method was used to validate the diagnostic algorithms; it revealed diagnostic sensitivities of 75% and 60%, specificities of 75% and 76.5%, and accuracies of 75% and 68% for EPS and serum, respectively. The results suggest that EPS and serum SERS analysis could be a potential tool for prostate cancer detection.

Recent progress and perspectives on prostate cancer biomarkers

The application of prostate-specific antigen (PSA) in prostate cancer (PC) screening, diagnosis, and prognosis has improved the clinical management of PC patients. However, the PSA assay has been faced with criticism due to its potential association with over-diagnosis and subsequent overtreatment of patients with indolent disease. The United States Preventive Services Task Force incited much debate over PSA-based screening in 2012 by recommending against this approach. However, the PSA assay remains the first-line tool for the early detection of PC. This debate highlights the unmet need for non-invasive PC biomarkers with greater sensitivity and specificity that are capable of distinguishing aggressive disease from indolent disease, predicting treatment response, and guiding treatment decisions. Recent investigations into putative PC biomarkers have focused on PSA isoform assays (prostate health index, 4-kallikurein panel), PC-associated genes in the urine (PCA3 and TMPRSS2-ERG), glycan-associated biomarkers (S2, 3PSA, GCNT1, and tri- and tetra-antennary serum N-glycans), and circulating tumor cells. Although substantial efforts to identify novel PC biomarkers that might replace PSA have been put forth, the majority of the putative PC biomarkers reported in the last few years are still under investigation or validation. This review provides an overview of the current state of PC biomarker research and focuses on a few promising PC biomarkers in development.

The Present and Future of Biomarkers in Prostate Cancer: Proteomics, Genomics, and Immunology Advancements

Prostate cancer (PC) is the second most common form of cancer in men worldwide. Biomarkers have emerged as essential tools for treatment and assessment since the variability of disease behavior, the cost and diversity of treatments, and the related impairment of quality of life have given rise to a need for a personalized approach. High-throughput technology platforms in proteomics and genomics have accelerated the development of biomarkers. Furthermore, recent successes of several new agents in PC, including immunotherapy, have stimulated the search for predictors of response and resistance and have improved the understanding of the biological mechanisms at work. This review provides an overview of currently established biomarkers in PC, as well as a selection of the most promising biomarkers within these particular fields of development.

PSA and beyond: alternative prostate cancer biomarkers

BACKGROUND

The use of biomarkers for prostate cancer screening, diagnosis and prognosis has the potential to improve the clinical management of the patients. Owing to inherent limitations of the biomarker prostate-specific antigen (PSA), intensive efforts are currently directed towards a search for alternative prostate cancer biomarkers, particularly those that can predict disease aggressiveness and drive better treatment decisions.

METHODS

A literature search of Medline articles focused on recent and emerging advances in prostate cancer biomarkers was performed. The most promising biomarkers that have the potential to meet the unmet clinical needs in prostate cancer patient management and/or that are clinically implemented were selected.

CONCLUSIONS

With the advent of advanced genomic and proteomic technologies, we have in recent years seen an enormous spurt in prostate cancer biomarker research with several promising alternative biomarkers being discovered that show an improved sensitivity and specificity over PSA. The new generation of biomarkers can be tested via serum, urine, or tissue-based assays that have either received regulatory approval by the US Food and Drug Administration or are available as Clinical Laboratory Improvement Amendments-based laboratory developed tests. Additional emerging novel biomarkers for prostate cancer, including circulating tumor cells, microRNAs and exosomes, are still in their infancy. Together, these biomarkers provide actionable guidance for prostate cancer risk assessment, and are expected to lead to an era of personalized medicine.

Clinical prospects of long noncoding RNAs as novel biomarkers and therapeutic targets in prostate cancer

BACKGROUND

The lack of sensitive and specific biomarkers for prostate cancer (PCa) has led to over-diagnosis and overtreatment with uncertain benefit. Therefore, biomarkers for early diagnosis that can distinguish aggressive from indolent tumors and that can detect metastatic or recurrent disease are needed. Long noncoding RNAs (lncRNAs) are non-protein-coding RNA species. lncRNAs are dysregulated in many diseases including PCa and are emerging as major players in cancer development. lncRNAs have several features that make then suitable as both biomarkers and therapeutics, and lncRNAs regulate critical cancer hallmarks in prostate epithelial cells including proliferation and survival.

METHODS

The PubMed database was searched using the terms 'long noncoding RNA', 'biomarker' and 'prostate cancer'. Known lncRNAs implicated as biomarkers and potential therapeutic targets in PCa are reviewed.

RESULTS

We comprehensively review several lncRNAs with potential as biomarkers for PCa. lncRNAs including PCA3, PCATs, SChLAP1, SPRY4-IT1 and TRPM2-AS are upregulated in PCa and are cancer specific; they are, therefore, attractive lead candidate biomarkers for clinical application. Several lncRNA therapeutics are currently being investigated by several companies for the treatment of various cancers including PCa. Small interfering RNAs, antisense oligonucleotides, ribozymes, deoxyribozymes and aptemers are few promising technologies for future lncRNA bases therapeutics.

CONCLUSION

lncRNA expression is altered in cancer. Aberrant regulation promotes tumor formation, progression and metastasis. lncRNAs can use as tumor markers for PCa and may be attractive novel therapeutic targets for the diagnosis and treatment of PCa.

Potential Utility of Novel Biomarkers in Active Surveillance of Low-Risk Prostate Cancer

Active surveillance (AS) is now an accepted management strategy for men with low-risk localized prostate cancer (PCa). However, detecting disease progression in a patient selected for AS remains a challenge. It is crucial to know what will serve as the best parameter to correctly identify tumors that progress to a more aggressive phenotype so as not to miss the window of curability. Several biomarkers are now being actively investigated as novel tools to improve PCa risk assessments. To date, several serum, urinary, and tissue biomarkers have shown promising prognostic value. %[-2]proPSA and PHI showed improved predictive value for an unfavorable biopsy conversion at annual surveillance biopsy in the AS program. PCA3 and TMPRSS2:ERG had additional independent predictive value for the prediction of PCa detection and progression, although PCA3 was limited in predicting aggressive cancer. Other tissue biomarkers also showed promising ability to predict disease progression. Although several of these novel biomarkers have an improved predictive accuracy that is better than classical parameters, there is still a need for further well-designed, large, multicenter, prospective trials to avoid common bias and clinical validation.

Risk calculators and updated tools to select and plan a repeat biopsy for prostate cancer detection

Millions of men each year are faced with a clinical suspicion of prostate cancer (PCa) but the prostate biopsy fails to detect the disease. For the urologists, how to select the appropriate candidate for repeat biopsy is a significant clinical dilemma. Traditional risk-stratification tools in this setting such as prostate-specific antigen (PSA) related markers and histopathology findings have met with limited correlation with cancer diagnosis or with significant disease. Thus, an individualized approach using predictive models such as an online risk calculator (RC) or updated biomarkers is more suitable in counseling men about their risk of harboring clinically significant prostate cancer. This review will focus on the available risk-stratification tools in the population of men with prior negative biopsies and persistent suspicion of PCa. The underlying methodology and platforms of the available tools are reviewed to better understand the development and validation of these models. The index patient is then assessed with different RCs to determine the range of heterogeneity among various RCs. This should allow the urologists to better incorporate these various risk-stratification tools into their clinical practice and improve patient counseling.

Biomarkers in prostate cancer: what's new?

PURPOSE OF REVIEW

This review is intended to provide an overview of the current state of biomarkers for prostate cancer (PCa), with a focus on biomarkers approved by the US Food and Drug Administration (FDA) as well as biomarkers available from Clinical Laboratory Improvement Amendment (CLIA)-certified clinical laboratories within the last 1-2 years.

RECENT FINDINGS

During the past 2 years, two biomarkers have been approved by the US FDA. These include proPSA as part of the Prostate Health Index (phi) by Beckman Coulter, Inc and PCA3 as Progensa by Gen Probe, Inc. With the advances in genomic and proteomic technologies, several new CLIA-based laboratory-developed tests have become available. Examples are Oncotype DX from Genomics Health, Inc, and Prolaris from Myriad Genetics, Inc. In most cases, these new tests are based on a combination of multiple genomic or proteomic biomarkers.

SUMMARY

Several new tests, as discussed in this review, have become available during the last 2 years. Although the intended use of most of these tests is to distinguish PCa from benign prostatic conditions with better sensitivity and specificity than prostate-specific antigen, studies have shown that some of them may also be useful in the differentiation of aggressive from nonaggressive forms of PCa.

The emerging role of extracellular vesicles as biomarkers for urogenital cancers

The knowledge gained from comprehensive profiling projects that aim to define the complex genomic alterations present within cancers will undoubtedly improve our ability to detect and treat those diseases, but the influence of these resources on our understanding of basic cancer biology is still to be demonstrated. Extracellular vesicles have gained considerable attention in past years, both as mediators of intercellular signalling and as potential sources for the discovery of novel cancer biomarkers. In general, research on extracellular vesicles investigates either the basic mechanism of vesicle formation and cargo incorporation, or the isolation of vesicles from available body fluids for biomarker discovery. A deeper understanding of the cargo molecules present in extracellular vesicles obtained from patients with urogenital cancers, through high-throughput proteomics or genomics approaches, will aid in the identification of novel diagnostic and prognostic biomarkers, and can potentially lead to the discovery of new therapeutic targets.

Point-of-care diagnostics, a major opportunity for change in traditional diagnostic approaches: potential and limitations

'Point-of-care' (POC) diagnostics are a powerful emerging healthcare approach. They can rapidly provide statistically significant results, are simple to use, do not require specialized equipment and are cost-effective. For these reasons, they have the potential to play a major role in revolutionizing the diagnosis, initiation and monitoring of treatment of major global diseases. This review focuses on antibody-based POC devices that target four major global diseases: cardiovascular diseases, prostate cancer, HIV infection and tuberculosis. The key statistics and pathology of each disease is described in detail, followed by an in-depth discussion on emerging POC devices that target each disease, highlighting their potential and limitations.

The decalog of long non-coding RNA involvement in cancer diagnosis and monitoring

Long non-coding RNAs (lncRNAs) are transcripts without protein-coding capacity; initially regarded as "transcriptional noise", lately they have emerged as essential factors in both cell biology and mechanisms of disease. In this article, we present basic knowledge of lncRNA molecular mechanisms, associated physiological processes and cancer association, as well as their diagnostic and therapeutic value in the form of a decalog: (1) Non-coding RNAs (ncRNAs) are transcripts without protein-coding capacity divided by size (short and long ncRNAs), function (housekeeping RNA and regulatory RNA) and direction of transcription (sense/antisense, bidirectional, intronic and intergenic), containing a broad range of molecules with diverse properties and functions, such as messenger RNA, transfer RNA, microRNA and long non-coding RNAs. (2) Long non-coding RNAs are implicated in many molecular mechanisms, such as transcriptional regulation, post-transcriptional regulation and processing of other short ncRNAs. (3) Long non-coding RNAs play an important role in many physiological processes such as X-chromosome inactivation, cell differentiation, immune response and apoptosis. (4) Long non-coding RNAs have been linked to hallmarks of cancer: (a) sustaining proliferative signaling; (b) evading growth suppressors; (c) enabling replicative immortality; (d) activating invasion and metastasis; (e) inducing angiogenesis; (f) resisting cell death; and (g) reprogramming energy metabolism. (5) Regarding their impact on cancer cells, lncRNAs are divided into two groups: oncogenic and tumor-suppressor lncRNAs. (6) Studies of lncRNA involvement in cancer usually analyze deregulated expression patterns at the RNA level as well as the effects of single nucleotide polymorphisms and copy number variations at the DNA level. (7) Long non-coding RNAs have potential as novel biomarkers due to tissue-specific expression patterns, efficient detection in body fluids and high stability. (8) LncRNAs serve as novel biomarkers for diagnostic, prognostic and monitoring purposes. (9) Tissue specificity of lncRNAs enables the development of selective therapeutic options. (10) Long non-coding RNAs are emerging as commercial biomarkers and therapeutic agents.

Comparative evaluation of urinary PCA3 and TMPRSS2: ERG scores and serum PHI in predicting prostate cancer aggressiveness

It has been suggested that urinary PCA3 and TMPRSS2:ERG fusion tests and serum PHI correlate to cancer aggressiveness-related pathological criteria at prostatectomy. To evaluate and compare their ability in predicting prostate cancer aggressiveness, PHI and urinary PCA3 and TMPRSS2:ERG (T2) scores were assessed in 154 patients who underwent radical prostatectomy for biopsy-proven prostate cancer. Univariate and multivariate analyses using logistic regression and decision curve analyses were performed. All three markers were predictors of a tumor volume≥0.5 mL. Only PHI predicted Gleason score≥7. T2 score and PHI were both independent predictors of extracapsular extension(≥pT3), while multifocality was only predicted by PCA3 score. Moreover, when compared to a base model (age, digital rectal examination, serum PSA, and Gleason sum at biopsy), the addition of both PCA3 score and PHI to the base model induced a significant increase (+12%) when predicting tumor volume>0.5 mL. PHI and urinary PCA3 and T2 scores can be considered as complementary predictors of cancer aggressiveness at prostatectomy.

Microarray-based identification of individual HERV loci expression: application to biomarker discovery in prostate cancer

The prostate-specific antigen (PSA) is the main diagnostic biomarker for prostate cancer in clinical use, but it lacks specificity and sensitivity, particularly in low dosage values¹​​. ‘How to use PSA' remains a current issue, either for diagnosis as a gray zone corresponding to a concentration in serum of 2.5-10 ng/ml which does not allow a clear differentiation to be made between cancer and noncancer² or for patient follow-up as analysis of post-operative PSA kinetic parameters can pose considerable challenges for their practical application^3,4. Alternatively, noncoding RNAs (ncRNAs) are emerging as key molecules in human cancer, with the potential to serve as novel markers of disease, e.g. PCA3 in prostate cancer^5,6 and to reveal uncharacterized aspects of tumor biology. Moreover, data from the ENCODE project published in 2012 showed that different RNA types cover about 62% of the genome. It also appears that the amount of transcriptional regulatory motifs is at least 4.5x higher than the one corresponding to protein-coding exons. Thus, long terminal repeats (LTRs) of human endogenous retroviruses (HERVs) constitute a wide range of putative/candidate transcriptional regulatory sequences, as it is their primary function in infectious retroviruses. HERVs, which are spread throughout the human genome, originate from ancestral and independent infections within the germ line, followed by copy-paste propagation processes and leading to multicopy families occupying 8% of the human genome (note that exons span 2% of our genome). Some HERV loci still express proteins that have been associated with several pathologies including cancer^7-10. We have designed a high-density microarray, in Affymetrix format, aiming to optimally characterize individual HERV loci expression, in order to better understand whether they can be active, if they drive ncRNA transcription or modulate coding gene expression. This tool has been applied in the prostate cancer field (Figure 1).

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.

Differentially expressed androgen-regulated genes in androgen-sensitive tissues reveal potential biomarkers of early prostate cancer

Background

Several data favor androgen receptor implication in prostate cancer initiation through the induction of several gene activation programs. The aim of the study is to identify potential biomarkers for early diagnosis of prostate cancer (PCa) among androgen-regulated genes (ARG) and to evaluate comparative expression of these genes in normal prostate and normal prostate-related androgen-sensitive tissues that do not (or rarely) give rise to cancer.

Methods

ARG were selected in non-neoplastic adult human prostatic epithelial RWPE-1 cells stably expressing an exogenous human androgen receptor, using RNA-microarrays and validation by qRT-PCR. Expression of 48 preselected genes was quantified in tissue samples (seminal vesicles, prostate transitional zones and prostate cancers, benign prostatic hypertrophy obtained from surgical specimens) using TaqMan® low-density arrays. The diagnostic performances of these potential biomarkers were compared to that of genes known to be associated with PCa (i.e. PCA3 and DLX1).

Results and Discussion

By crossing expression studies in 26 matched PCa and normal prostate transitional zone samples, and 35 matched seminal vesicle and PCa samples, 14 genes were identified. Similarly, 9 genes were overexpressed in 15 benign prostatic hypertrophy samples, as compared to PCa samples. Overall, we selected 8 genes of interest to evaluate their diagnostic performances in comparison with that of PCA3 and DLX1. Among them, 3 genes: CRYAB, KCNMA1 and SDPR, were overexpressed in all 3 reference non-cancerous tissues. The areas under ROC curves of these genes reached those of PCA3 (0.91) and DLX1 (0.94).

Conclusions

We identified ARG with reduced expression in PCa and with significant diagnostic values for discriminating between cancerous and non-cancerous prostatic tissues, similar that of PCA3. Given their expression pattern, they could be considered as potentially protective against prostate cancer. Moreover, they could be complementary to known genes overexpressed in PCa and included along with them in multiplex diagnostic tools.

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.

A comparison of Bayesian and frequentist approaches to incorporating external information for the prediction of prostate cancer risk

We present the most comprehensive comparison to date of the predictive benefit of genetics in addition to currently used clinical variables, using genotype data for 33 single-nucleotide polymorphisms (SNPs) in 1,547 Caucasian men from the placebo arm of the REduction by DUtasteride of prostate Cancer Events (REDUCE®) trial. Moreover, we conducted a detailed comparison of three techniques for incorporating genetics into clinical risk prediction. The first method was a standard logistic regression model, which included separate terms for the clinical covariates and for each of the genetic markers. This approach ignores a substantial amount of external information concerning effect sizes for these Genome Wide Association Study (GWAS)-replicated SNPs. The second and third methods investigated two possible approaches to incorporating meta-analysed external SNP effect estimates - one via a weighted PCa 'risk' score based solely on the meta analysis estimates, and the other incorporating both the current and prior data via informative priors in a Bayesian logistic regression model. All methods demonstrated a slight improvement in predictive performance upon incorporation of genetics. The two methods that incorporated external information showed the greatest receiver-operating-characteristic AUCs increase from 0.61 to 0.64. The value of our methods comparison is likely to lie in observations of performance similarities, rather than difference, between three approaches of very different resource requirements. The two methods that included external information performed best, but only marginally despite substantial differences in complexity.

Urinary biomarkers for prostate cancer: a review

Although the routine use of serum prostate-specific antigen (PSA) testing has undoubtedly increased prostate cancer (PCa) detection, one of its main drawbacks is its lack of specificity. As a consequence, many men undergo unnecessary biopsies or treatments for indolent tumours. PCa-specific markers are needed for the early detection of the disease and the prediction of aggressiveness of a prostate tumour. Since PCa is a heterogeneous disease, a panel of tumour markers is fundamental for a more precise diagnosis. Several biomarkers are promising due to their specificity for the disease in tissue. However, tissue is unsuitable as a possible screening tool. Since urine can be easily obtained in a non-invasive manner, it is a promising substrate for biomarker testing. This article reviews the biomarkers for the non-invasive testing of PCa in urine.

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.

Toward the detection of prostate cancer in urine: a critical analysis

PURPOSE

Prostate specific antigen and digital rectal examination have low specificity for detecting prostate cancer and they poorly predict the presence of aggressive disease. Urine is readily available and noninvasive, and it represents a promising source of biomarkers for the early detection and prediction of prostate cancer prognosis. We identified promising biomarkers for urine based prostate cancer, examined trends and outlined potential pitfalls.

MATERIALS AND METHODS

We performed PubMed® and Web of Science® database searches of the peer reviewed literature on urine based testing for prostate cancer. Original studies of this subject as well as a small number of reviews were analyzed, including the strengths and weaknesses. We provide a comprehensive review of urine based testing for prostate cancer that covers the technical aspects, including the methodology of urine collection, as well as recent developments in biomarkers spanning the fields of genomics, epigenetics, transcriptomics, proteomics and metabolomics.

RESULTS

The process of urine collection is subject to variability, which may result in conflicting clinical results. Detecting prostate cancer in urine is technically feasible, as demonstrated by numerous proof of principle studies, but few markers have been validated in multiple large sample sets. Biomarker development using urine has been accelerating in recent years with numerous studies identifying DNA, RNA, protein and metabolite based biomarkers in urine. Advanced clinical studies have identified PCA3 and TMPRSS2:ERG fusion transcripts as promising RNA markers for cancer detection and possibly prognosis. DNA methylation analysis of multiple genes improves specificity and represents a promising platform for developing clinical grade assays.

CONCLUSIONS

Urine based testing is noninvasive and represents a rich source of novel biomarkers for prostate cancer. Although urine shows promise for detecting cancer, the ability to identify aggressive subsets of prostate cancer needs further development.

Prognostic determinants in prostate cancer

Clinical outcomes in prostate cancer are heterogeneous, and given the high prevalence of the disease, there is a pressing need to identify clinically useful markers of prognosis. Many clinical, pathological, molecular, and genetic factors have been investigated in this capacity, although relatively few are routinely used. With a growing understanding of the molecular pathogenesis of prostate cancer, there is the potential that the next generation of makers will prove sufficiently robust to guide the optimal management of men with prostate cancer. Here, we review the various clinical and molecular prognostic determinants in prostate cancer.

PCA3 sensitivity and specificity for prostate cancer detection in patients with abnormal PSA and/or suspicious digital rectal examination. First Latin American experience

INTRODUCTION

Prostate Cancer Gene 3 (PCA3) is a recently described and highly specific urinary marker for prostate cancer (CaP). Its introduction in clinical practice to supplement low specificity of prostate specific antigen (PSA) can improve CaP diagnosis and follow-up. However, before its introduction, it is necessary to validate the method of PCA3 detection in distinct geographic populations.

OBJECTIVES

Our aim was to describe for the first time in Latin America, the application of the PROGENSA PCA3 assay for PCA3 detection in urine in Chilean men and its utility for CaP diagnosis in men with an indication of prostate biopsy.

MATERIALS AND METHODS

Sixty-four Chilean patients (mean age, 64 years) with indication of prostate biopsy because of elevated PSA and/or suspicious digital rectal examination (DRE) were prospectively recruited. PCA3 scores were assessed from urine samples obtained after DRE, before biopsy, and compared with PSA levels and biopsy outcome.

RESULTS

The median PSA value and mean PCA3 score were 5.8 ng/ml and 31.7, respectively. Using a cutoff PCA3 score of 35, the sensitivity and specificity for detecting CaP were 52% and 87%, respectively. The receiver operating characteristic (ROC) curve analysis showed an area under the curve of 0.77 for PCA3 and 0.57 for PSA, for the same group of patients. In patients with previous negative biopsy, PCA3 specificity increased by 2.2%.

CONCLUSIONS

This is the first report in Latin America on the use of PCA3 in diagnosing CaP. Our results are comparable to those reported in other populations in the literature, demonstrating the reproducibility of the test. PCA3 score was highly specific and we specially recommend its use in patients with persistent elevated PSA and prior negative biopsies.

Chronic prostatitis does not influence urinary PCA3 score

BACKGROUND

The influence of chronic prostatitis on serum PSA level is well known. Whether it also influences potential new biomarkers of prostate cancer (PCa) has to be determined. We conducted a prospective study to evaluate the effect of chronic prostatitis on the PCa urinary marker PCA3.

METHODS

Included were 38 patients, mean-aged of 37.5 years, with clinical suspicion of chronic prostatitis. A simplified version of the Meares-Stamey four-glass localization test was performed and urine specimens were collected for cytological analysis and culture. A postprostatic massage urine sample was used for the urinary PCA3 test.

RESULTS

Four patients had an eventual diagnosis of urethritis and all had a PCA3 score less than 5. Among the remaining 34 patients, 7 had bacterial chronic prostatitis (NIH II prostatitis), 11 had abacterial chronic prostatitis (NIH IIIa), and 16 had non inflammatory prostatodynia (NIH IIIb). All these patients had a PCA3 score less than 28, that is, under the cutoff of 35, which is commonly used for prostate cancer diagnosis. Patients with NIH category IIIa prostatitis had significantly higher number of leukocytes and red cells as well as prostate cells in urine samples but their PCA3 scores did not differ from those of other prostatitis patients.

CONCLUSION

In this study, NIH II and III chronic prostatitis did not influence the PCA3 score. Our results suggest that increased PCA3 score is unlikely to be explained by the sole chronic prostatitis and warrants prostate biopsies to eliminate prostate cancer.

Molecular study of the PCA3 gene: genotypic analysis of PCA3 polymorphism -845G>A and metastatic prostate cancer

AIMS

The prostate cancer gene 3 (PCA3) is a prostate-specific, non-protein-coding RNA. It is overexpressed in prostate cancer compared with the normal prostate and has a negative expression in other tissues. This case-control study sought to analyze the frequency of the polymorphism PCA3 -845 G>A in participants without prostate cancer and patients with metastatic prostate cancer.

RESULTS

Carriers of GA and AA genotype had a higher risk for metastatic prostate cancer (odds ratio [OR] for genotype GA, 1.79 [95% confidence interval (CI), 1.14-2.29]; p=0.007; OR for genotype AA, 2.38 [95% CI, 1.22-4.65]; p=0.006). Furthermore, the recessive model showed that A allele carriers have an increased risk for developing metastatic prostate cancer (OR, 1.91 [95% CI, 1.26-2.90]; p=0.001).

CONCLUSIONS

These results suggest a link between PCA3 and metastatic prostate cancer. The evaluation of individual genetic profiles, according to the PCA3 -845 G>A polymorphism, may elucidate the function of this gene and the mechanisms involved in its regulation and role in prostate cancer.