Prostate cancer gene 3 (PCA3): development and internal validation of a novel biopsy nomogram

Liquid Biomarkers in Prostate Cancer Diagnosis: Current Status and Emerging Prospects

Prostate cancer (PCa) is a major health concern that necessitates appropriate diagnostic approaches for timely intervention. This review critically evaluates the role of liquid biopsy techniques, focusing on blood- and urine-based biomarkers, in overcoming the limitations of conventional diagnostic methods. The 4Kscore test and Prostate Health Index have demonstrated efficacy in distinguishing PCa from benign conditions. Urinary biomarker tests such as PCa antigen 3, MyProstateScore, SelectMDx, and ExoDx Prostate IntelliScore test have revolutionized risk stratification and minimized unnecessary biopsies. Emerging biomarkers, including non-coding RNAs, circulating tumor DNA, and prostate-specific antigen (PSA) glycosylation, offer valuable insights into PCa biology, enabling personalized treatment strategies. Advancements in non-invasive liquid biomarkers for PCa diagnosis may facilitate the stratification of patients and avoid unnecessary biopsies, particularly when PSA is in the gray area of 4 to 10 ng/mL.

Long noncoding RNA as a potential diagnostic tool for prostate cancer: a systematic review and meta-analysis

PURPOSE

To identify consistently expressed lncRNAs and suitable lncRNAs with high sensitivity and specificity from multiple independent studies as potential biomarkers for PCa diagnostics.

METHODS

We searched multiple electronic databases including PubMed, Web of Science, EMBASE, Cochrane Library, CNKI, CQVIP, Wanfang, and CBMdisc for studies published up to July 2022. The quality of the included studies was assessed by two independent reviewers based on the QUADAS-2 tool using Review Manager 5.3. A vote-counting method was used based on the ranking of potential molecular biomarkers. The top-ranked lncRNAs were further assessed for diagnostic value using Meta-disc version 1.4 software.

RESULTS

Among the 26 included studies, 2 circulating lncRNAs (PCA3 and MALAT-1) were reported 3 or more times in PCa patients versus non-PCa patients. In further analysis, the areas under the curve of the summary receiver operating characteristic curves for PCA3 and MALAT-1 distinguishing PCa patients were 0.775 and 0.771, respectively.

CONCLUSIONS

Based on the current evidence, PCA3 and MALAT-1 are reliable lncRNAs for the diagnosis of PCa.

Evaluation and multi-institutional validation of a novel urine biomarker lncRNA546 to improve the diagnostic specificity of prostate cancer in PSA gray-zone

Background and objectives

Prostate specific antigen (PSA) is currently the most commonly used biomarker for prostate cancer diagnosis. However, when PSA is in the gray area of 4-10 ng/ml, the diagnostic specificity of prostate cancer is extremely low, leading to overdiagnosis in many clinically false-positive patients. This study was trying to discover and evaluate a novel urine biomarker long non-coding RNA (lncRNA546) to improve the diagnostic accuracy of prostate cancer in PSA gray-zone.

Methods

A cohort study including consecutive 440 participants with suspected prostate cancer was retrospectively conducted in multi-urology centers. LncRNA546 scores were calculated with quantitative real-time polymerase chain reaction. The area under the receiver operating characteristic curve (AUROC), decision curve analysis (DCA) and a biopsy-specific nomogram were utilized to evaluate the potential for clinical application. Logistic regression model was constructed to confirm the predictive power of lncRNA546.

Results

LncRNA546 scores were sufficient to discriminate positive and negative biopsies. ROC analysis showed a higher AUC for lncRNA546 scores than prostate cancer antigen 3 (PCA3) scores (0.78 vs. 0.66, p<0.01) in the overall cohort. More importantly, the AUC of lncRNA546 (0.80) was significantly higher than the AUCs of total PSA (0.57, p=0.02), percentage of free PSA (%fPSA) (0.64, p=0.04) and PCA3 (0.63, p<0.01) in the PSA 4-10 ng/ml cohort. A base model constructed by multiple logistic regression analysis plus lncRNA546 scores improved the predictive accuracy (PA) from 79.8% to 86.3% and improved AUC results from 0.862 to 0.915. DCA showed that the base model plus lncRNA546 displayed greater net benefit at threshold probabilities beyond 15% in the PSA 4-10 ng/ml cohort.

Conclusion

LncRNA546 is a promising novel biomarker for the early detection of prostate cancer, especially in the PSA 4-10 ng/ml cohort.

Construction and Comparison of Different Models in Detecting Prostate Cancer and Clinically Significant Prostate Cancer

Background

With the widespread adoption of prostatic-specific antigen (PSA) screening, the detection rates of prostate cancer (PCa) have increased. Due to the low specificity and high false-positive rate of serum PSA levels, it was difficult to diagnose PCa accurately. To improve the diagnosis of PCa and clinically significant prostate cancer (CSPCa), we established novel models on the basis of the prostate health index (PHI) and multiparametric magnetic resonance imaging (mpMRI) in the Asian population.

Methods

We retrospectively collected the clinical indicators of patients with TPSA at 4–20 ng/ml. Furthermore, mpMRI was performed using a 3.0-T scanner and reported in the Prostate Imaging Reporting and Data System version 2.1 (PI-RADS). Univariable and multivariable logistic analyses were performed to construct the models. The performance of different models based on PSA derivatives, PHI derivatives, PI-RADS, and a combination of PHI derivatives and PI-RADS was evaluated.

Results

Among the 128 patients, 47 (36.72%) patients were diagnosed with CSPCa and 81 (63.28%) patients were diagnosed with non-CSPCa. Of the 81 (63.28%) patients, 8 (6.25%) patients were diagnosed with Gleason Grade 1 PCa and 73 (57.03%) patients were diagnosed with non-PCa. In the analysis of the receiver operator characteristic (ROC) curves in TPSA 4–20 ng/ml, the multivariable model for PCa was significantly larger than that for the model based on the PI-RADS (p = 0.004) and that for the model based on the PHI derivatives (p = 0.031) in diagnostic accuracy. The multivariable model for CSPCa was significantly larger than that for the model based on the PI-RADS (p = 0.003) and was non-significantly larger than that for the model based on the PHI derivatives (p = 0.061) in diagnostic accuracy. For PCa in TPSA 4–20 ng/ml, a multivariable model achieved the optimal diagnostic value at four levels of predictive variables. For CSPCa in TPSA 4–20 ng/ml, the multivariable model achieved the optimal diagnostic value at a sensitivity close to 90% and 80%.

Conclusions

The models combining PHI derivatives and PI-RADS performed better in detecting PCa and CSPCa than the models based on either PHI or PI-RADS.

LncRNA DGCR5 Isoform-1 Silencing Suppresses the Malignant Phenotype of Clear Cell Renal Cell Carcinoma via miR-211-5p/Snail Signal Axis

Long non-coding RNAs (lncRNAs) play important roles during the initiation and progression of cancer. We identified DiGeorge Syndrome Critical Region Gene 5 (DGCR5) as a clear cell renal cell carcinoma (ccRCC) cancer- and lineage-specific lncRNA. Agarose gel electrophoresis analysis and sanger sequencing verified two main isoforms of DGCR5 in ccRCC patient tissues and cell lines. Quantitative polymerase chain reaction further demonstrated that the expression level of DGCR5 major isoform (isoform-1) was higher in ccRCC tissues than that in papillary/chromophobe RCC and other multiple solid malignant tumors. We investigate the biological functions of DGCR5 isoform-1 in ccRCC and show that DGCR5 isoform-1 exerts a tumor-promoting effect in ccRCC. DGCR5 isoform-1 is localized in cytoplasm and shares the same binding sequence to the tumor-suppressive miR-211-5p with the epithelial-to-mesenchymal transition key component SNAI. Furthermore, cellular and molecular experiments demonstrate that DGCR5 isoform-1 could sequester miR-211-5p, leading to the elevation of Snail protein and downregulation of its downstream targets and further promoting ccRCC cell proliferation and migration. Thus, our study indicates that DGCR5 isoform-1 could contribute to ccRCC progression by sponging miR-211-5p through regulating the expression of Snail protein and could serve as a reliable diagnostic biomarker in ccRCC.

Personalized strategies in population screening for prostate cancer

This review discusses evidence for population-based screening with contemporary screening tools. In Europe, prostate-specific antigen (PSA)-based screening led to a relative reduction of prostate cancer (PCa) mortality, but also to a substantial amount of overdiagnosis and unnecessarily biopsies. Risk stratification based on a single variable (a clinical variable or based on the presence of a lesion on prostate imaging) or based on multivariable approaches can aid in reducing unnecessary prostate biopsies and overdiagnosis by selecting men who can benefit from further clinical assessment. Multivariable approaches include clinical variables, and biomarkers, often combined in risk calculators or nomograms. These risk calculators can also incorporate the result of MRI imaging. In general, as compared to a purely PSA based approach, the combination of relevant prebiopsy information results in superior selection of men at higher risk of harboring clinically significant prostate cancer. Currently, it is not possible to draw any conclusions on the superiority of these multivariable risk-based approaches since head-to-head comparisons are virtually lacking. Recently initiated large population-based screening studies in Finland, Germany and Sweden, incorporating various multivariable risk stratification approaches will hopefully give more insight in whether the harm-benefit ratio can be improved, that is, maintain (or improving) the ability to reduce metastatic disease and prostate cancer mortality while reducing harm caused by unnecessary testing and overdiagnosis including related overtreatment.

Merging new-age biomarkers and nanodiagnostics for precision prostate cancer management

The accurate identification and stratified treatment of clinically significant early-stage prostate cancer have been ongoing concerns since the outcomes of large international prostate cancer screening trials were reported. The controversy surrounding clinical and cost benefits of prostate cancer screening has highlighted the lack of strategies for discriminating high-risk disease (that requires early treatment) from low-risk disease (that could be managed using watchful waiting or active surveillance). Advances in molecular subtyping and multiomics nanotechnology-based prostate cancer risk delineation can enable refinement of prostate cancer molecular taxonomy into clinically meaningful and treatable subtypes. Furthermore, the presence of intertumoural and intratumoural heterogeneity in prostate cancer warrants the development of novel nanodiagnostic technologies to identify clinically significant prostate cancer in a rapid, cost-effective and accurate manner. Circulating and urinary next-generation prostate cancer biomarkers for disease molecular subtyping and the newest complementary nanodiagnostic platforms for enhanced biomarker detection are promising tools for precision prostate cancer management. However, challenges in merging both aspects and clinical translation still need to be overcome.

The Genomic and Molecular Pathology of Prostate Cancer: Clinical Implications for Diagnosis, Prognosis, and Therapy

Prostate cancer (PCa) is the most common noncutaneous malignancy affecting American men and the second most common cause of cancer death. The traditional risk classification schemes for PCa are limited due to the vast clinical and molecular heterogeneity of the disease. Fortunately, recent advancements in sequencing technologies have provided us with valuable insight into the genomics of PCa. To date, a wide array of recurrent genomic alterations in PCa have been identified. Incorporating these distinct molecular subtypes of PCa into prediction models provides opportunities for improved risk stratification and ultimately better patient outcomes. In this review, we summarize the key molecular subtypes of PCa and focus on those genomic alterations that have clinical implications for diagnosis, prognosis, and therapeutic response.

A novel nomogram combined PIRADS v2 and neutrophil-to-lymphocyte ratio to predict the risk of clinically significant prostate cancer in men with PSA < 10 ng/ml at first biopsy

OBJECTIVE

To determine whether Prostate Imaging-Reporting and Data System version 2 (PIRADS v2) and neutrophil-to-lymphocyte ratio(NLR) improve the detection of clinically significant prostate cancer(csCaP) in men with prostate-specific antigen (PSA) <10 ng/ml at first biopsy.

METHODS

Univariable and multivariable binary logistic regression analysis were used to screen for independent risk factors of csCaP. The multivariable model based on the risk factors was to build the nomogram predicting csCaP and assessed by receiver operator characteristic curve analysis, calibration plot, and decision curve analysis.

RESULTS

This retrospective study included 335 men with PSA < 10 ng/ml who underwent initial biopsy. A total of 78 (23.3%) men had csCaP. The nomogram was built based on the multivariable model including age, digital rectal examination, free prostate-specific antigen, PIRADS v2, and NLR. It had high area under the curve of 0.876 and was well calibrated in internal validation. Decision curve analysis also demonstrated that it would improve the prediction of csCaP.

CONCLUSION

PIRADS v2 and NLR improve the detection of csCaP in men with PSA < 10 ng/ml at first biopsy. Due to lack of external validation, relatively small cohort and homogenous population, the study has several limitations. Despite of this, the nomogram based on our study is a promising tool for patients to understand their risk of csCaP and for urologists to make clinical decisions.

The long non-coding RNA PCA3: an update of its functions and clinical applications as a biomarker in prostate cancer

Prostate cancer antigen 3 (PCA3) is an overexpressed prostate long non-coding RNA (lncRNA), transcribed from an intronic region at the long arm of human chromosome 9q21–22. It has been described that PCA3 modulates prostate cancer (PCa) cell survival through modulating androgen receptor (AR) signaling, besides controlling the expression of several androgen responsive and cancer-related genes, including epithelial–mesenchymal transition (EMT) markers and those regulating gene expression and cell signaling. Also, PCA3 urine levels have been successfully used as a PCa diagnostic biomarker. In this review, we have highlighted recent findings regarding PCA3, addressing its gene structure, putative applications as a biomarker, a proposed origin of this lncRNA, roles in PCa biology and expression patterns. We also updated data regarding PCA3 interactions with cancer-related miRNAs and expression in other tissues and diseases beyond the prostate. Altogether, literature data indicate aberrant expression and dysregulated activity of PCA3, suggesting PCA3 as a promising relevant target that should be even further evaluated on its applicability for PCa detection and management.

Novel Diagnostic Biomarkers of Prostate Cancer: An Update

OBJECTIVE

In recent years, several biomarkers alternative to standard prostate specific antigen (PSA) for prostate cancer (PCa) diagnosis have become available. The aim of this systematic review is to assess the current knowledge about alternative serum and urinary biomarkers for the diagnosis of PCa.

MATERIAL AND METHODS

A research was conducted in Medline, restricted to English language articles published between December 2014 and June 2018 with the aim to update previously published series on PCa biomarkers. The preferred reporting items for systematic reviews and meta-analyses (PRISMA) criteria were used for selecting studies with the lowest risk of bias.

RESULTS

Emerging role and actual controversies on serum and urine alternative biomarkers to standard PSA for PCa diagnosis, staging and prognosis assessment, such as prostate health index (PHI), PCA3, ConfirmMDx, Aberrant PSA glycosylation, MiPS, miRNAs are critically presented in the current review.

CONCLUSION

Although the use of several biomarkers has been recommended or questioned by different international guidelines, larger prospective randomized studies are still necessary to validate their efficacy in PCa detection, discrimination, prognosis and treatment effectiveness. To date, only PHI and 4Kscore have shown clinical relevance for discriminating more aggressive PCa. Furthermore, a new grading classification based on molecular features relevant for PCa risk-stratification and tailoring treatment is still needed.

Application of Urinary Volatile Organic Compounds (VOCs) for the Diagnosis of Prostate Cancer

BACKGROUND

Prostate cancer (PCa) screening using serum prostate-specific antigen (PSA) testing has caused unnecessary biopsies and overdiagnosis owing to its low accuracy and reliability. Therefore, there is an increased interest in identifying better PCa biomarkers. Studies showed that trained dogs can discriminate patients with PCa from unaffected men by sniffing urine. We hypothesized that urinary volatile organic compounds (VOCs) may be the source of that odor and could be used to develop urinary VOC PCa diagnosis models.

PATIENTS AND METHODS

Urine samples from 55 and 53 biopsy proven PCa-positive and -negative patients respectively were initially obtained for diagnostic model development. Urinary metabolites were analyzed by gas chromatography-mass spectrometry. A PCa diagnosis model was developed and validated using innovative statistical machine-learning techniques. A second set of samples (53 PCa-positive and 22 PCa-negative patients) were used to evaluate the previously developed PCa diagnosis model.

RESULTS

The analysis resulted in 254 and 282 VOCs for their significant association (P < .05) with either PCa-positive or -negative samples respectively. Regularized logistic regression analysis and the Firth method were then applied to predict PCa prevalence, resulting in a final model that contains 11 VOCs. Under cross-validation, the area under the receiver operating characteristic curve (AUC) for the final model was 0.92 (sensitivity, 0.96; specificity, 0.80). Further evaluation of the developed model using a testing cohort yielded an AUC of 0.86. As a comparison, the PSA-based diagnosis model only rendered an AUC of 0.54.

CONCLUSION

The study describes the development of a urinary VOC-based model for PCa detection.

Prediction Medicine: Biomarkers, Risk Calculators and Magnetic Resonance Imaging as Risk Stratification Tools in Prostate Cancer Diagnosis

This review discusses the most recent evidence for currently available risk stratification tools in the detection of clinically significant prostate cancer (csPCa), and evaluates diagnostic strategies that combine these tools. Novel blood biomarkers, such as the Prostate Health Index (PHI) and 4Kscore, show similar ability to predict csPCa. Prostate cancer antigen 3 (PCA3) is a urinary biomarker that has inferior prediction of csPCa compared to PHI, but may be combined with other markers like TMPRSS2-ERG to improve its performance. Original risk calculators (RCs) have the advantage of incorporating easy to retrieve clinical variables and being freely accessible as a web tool/mobile application. RCs perform similarly well as most novel biomarkers. New promising risk models including novel (genetic) markers are the SelectMDx and Stockholm-3 model (S3M). Prostate magnetic resonance imaging (MRI) has evolved as an appealing tool in the diagnostic arsenal with even stratifying abilities, including in the initial biopsy setting. Merging biomarkers, RCs and MRI results in higher performances than their use as standalone tests. In the current era of prostate MRI, the way forward seems to be multivariable risk assessment based on blood and clinical parameters, potentially extended with information from urine samples, as a triaging test for the selection of candidates for MRI and biopsy.

Molecular Biomarkers in the Clinical Management of Prostate Cancer

Prostate cancer, one of the most common noncutaneous malignancies in men, is a heterogeneous disease with variable clinical outcome. Although the majority of patients harbor indolent tumors that are essentially cured by local therapy, subsets of patients present with aggressive disease or recur/progress after primary treatment. With this in mind, modern clinical approaches to prostate cancer emphasize the need to reduce overdiagnosis and overtreatment via personalized medicine. Advances in our understanding of prostate cancer pathogenesis, coupled with recent technologic innovations, have facilitated the development and validation of numerous molecular biomarkers, representing a range of macromolecules assayed from a variety of patient sample types, to help guide the clinical management of prostate cancer, including early detection, diagnosis, prognostication, and targeted therapeutic selection. Herein, we review the current state of the art regarding prostate cancer molecular biomarkers, emphasizing those with demonstrated utility in clinical practice.

Development and Internal Validation of Novel Nomograms Based on Benign Prostatic Obstruction-Related Parameters to Predict the Risk of Prostate Cancer at First Prostate Biopsy

The present study aimed to determine the ability of novel nomograms based onto readily-available clinical parameters, like those related to benign prostatic obstruction (BPO), in predicting the outcome of first prostate biopsy (PBx). To do so, we analyzed our Internal Review Board-approved prospectively-maintained PBx database. Patients with PSA>20 ng/ml were excluded because of their high risk of harboring prostate cancer (PCa). A total of 2577 were found to be eligible for study analyses. The ability of age, PSA, digital rectal examination (DRE), prostate volume (PVol), post-void residual urinary volume (PVR), and peak flow rate (PFR) in predicting PCa and clinically-significant PCa (CSPCa)was tested by univariable and multivariable logistic regression analysis. The predictive accuracy of the multivariate models was assessed using receiver operator characteristic curves analysis, calibration plot, and decision-curve analyses (DCA). Nomograms predicting PCa and CSPCa were built using the coefficients of the logit function. Multivariable logistic regression analysis showed that all variables but PFR significantly predicted PCA and CSPCa. The addition of the BPO-related variables PVol and PVR to a model based on age, PSA and DRE findings increased the model predictive accuracy from 0.664 to 0.768 for PCa and from 0.7365 to 0.8002 for CSPCa. Calibration plot demonstrated excellent models' concordance. DCA demonstrated that the model predicting PCa is of value between ~15 and ~80% threshold probabilities, whereas the one predicting CSPCa is of value between ~10 and ~60% threshold probabilities. In conclusion, our novel nomograms including PVR and PVol significantly increased the accuracy of the model based on age, PSA and DRE in predicting PCa and CSPCa at first PBx. Being based onto parameters commonly assessed in the initial evaluation of men “prostate health,” these novel nomograms could represent a valuable and easy-to-use tool for physicians to help patients to understand their risk of harboring PCa and CSPCa.

Analysis of competing endogenous RNA network to identify the key RNAs associated with prostate adenocarcinoma

OBJECTIVES

Prostate adenocarcinoma (PRAD) is the most common cancer in men. The aim of this study was to reveal the critical long non-coding RNA (lncRNAs), microRNA (miRNAs) and mRNAs involved in the pathogenesis of PRAD.

METHODS

The level 3 mRNA and miRNA sequencing data of PRAD were downloaded from The Cancer Genome Atlas database. Using the edgeR package of R, the differentially expressed mRNAs (DEGs), lncRNAs (DE-lncRNAs) and miRNAs (DE-miRNAs) between PRAD and normal tissues were screened. The Cox proportional hazards regression method in the survival package was used to select the lncRNAs significantly related to clinical characteristics. After the miRNA-lncRNA and miRNA-mRNA pairs were predicted, a regulatory network was constructed by the Cytoscape software. For the DEGs involved in the network, enrichment analysis was conducted by the Fisher algorithm.

RESULTS

Compared to the normal samples, 25 DE-lncRNAs, 1421 DEGs and 68 DE-miRNAs were identified in the PRAD samples. The down-regulated MESTIT1 had a significantly negative correlation with overall survival. A total of 44 DE-miRNA-DE-lncRNA pairs were predicted, including the PCA3-miR-96 and UCA1-miR-96. Meanwhile, 33 DEGs targeted by miRNAs (for example, miR-96-CYP19A1) were found to correlate with cancers.

CONCLUSION

Functional enrichment analysis showed that the reproductive development process (which involved TDRD1) was enriched for the DEGs implicated in the lncRNA-miRNA-mRNA regulatory network. The lncRNAs MESTIT1, PCA3, and UCA1; mRNAs CYP19A1 and TDRD1; as well as miR-96 might affect the pathogenesis of PRAD.

The role of prostate cancer antigen 3 (PCA3) in prostate cancer detection

INTRODUCTION

The prostate cancer antigen 3 (PCA3) score has been the first urine assay to obtain the Food and Drug Administration approval for guiding decisions regarding additional biopsies. Different aspects of this urinary assay (diagnostic performance, prognostic value, cost/benefit balance, integration with other molecular and imaging modalities) have now been well evaluated. Areas covered: This expert review will summarize current achievements and future perspectives provided by this urine biomarker. Expert commentary: The clinical benefit of the PCA3 score, in addition to the other established factors has been demonstrated before regarding biopsy decision making in men with persistent risk of prostate cancer. Its potential prognostic value also suggests its usefulness in selecting low risk patients for active surveillance protocols, however future daily-practice changing studies are needed. Economics assessment and additional value compared with other biomolecular and imaging modalities are still under investigation.

Spectrophotometric photodynamic diagnosis of prostate cancer cells excreted in voided urine using 5-aminolevulinic acid

To evaluate the feasibility of photodynamic diagnosis using 5-aminolevulinic acid (PDD-ALA) for detection of prostate cancer (PCa) cells in urine samples after prostate massage in patients who were suspected to have PCa. One hundred and eighty-nine patients with abnormal digital rectal examination and/or an elevated prostate-specific antigen (PSA) level who underwent initial prostate biopsy were recruited. After prostate massage, the first 60 mL of voided urine was collected. For PDD-ALA, 50 mL was used. The rest of collected urine was used for polymerase chain reaction (PCR) of PSA and glyceraldehyde 3-phosphate dehydrogenase (GAPDH). After incubation for 2 h, the intensity was measured at 635 nm under a 405-nm wavelength excitation. The results of PDD-ALA were compared with those of an initial transrectal ultrasound (TRUS)-guided prostate biopsy. Overall, 126/189 (67%) samples that showed bands of both PSA and GAPDH on PCR in urine samples were analyzed. The area under the curve, sensitivity, and specificity of PDD-ALA were 0.74, 77, and 67%, respectively. The value of PDD-ALA was significantly higher in patients with Gleason scores of 6 (p = 0.03), 7 (p = 0.005), and 8-10 (p = 0.0002) than in those with negative biopsy results. In the multivariate analysis, high PSA density, abnormal findings on TRUS, and a high value of PDD-ALA were significant markers for prediction of positive biopsy results. PDD-ALA was useful to predict positive biopsy results in patients who underwent initial prostate biopsy with suspected PCa. This PCa-detection method has potential for clinical use.

In-Silico Integration Approach to Identify a Key miRNA Regulating a Gene Network in Aggressive Prostate Cancer

Like other cancer diseases, prostate cancer (PC) is caused by the accumulation of genetic alterations in the cells that drives malignant growth. These alterations are revealed by gene profiling and copy number alteration (CNA) analysis. Moreover, recent evidence suggests that also microRNAs have an important role in PC development. Despite efforts to profile PC, the alterations (gene, CNA, and miRNA) and biological processes that correlate with disease development and progression remain partially elusive. Many gene signatures proposed as diagnostic or prognostic tools in cancer poorly overlap. The identification of co-expressed genes, that are functionally related, can identify a core network of genes associated with PC with a better reproducibility. By combining different approaches, including the integration of mRNA expression profiles, CNAs, and miRNA expression levels, we identified a gene signature of four genes overlapping with other published gene signatures and able to distinguish, in silico, high Gleason-scored PC from normal human tissue, which was further enriched to 19 genes by gene co-expression analysis. From the analysis of miRNAs possibly regulating this network, we found that hsa-miR-153 was highly connected to the genes in the network. Our results identify a four-gene signature with diagnostic and prognostic value in PC and suggest an interesting gene network that could play a key regulatory role in PC development and progression. Furthermore, hsa-miR-153, controlling this network, could be a potential biomarker for theranostics in high Gleason-scored PC.

PCA3 as a second-line biomarker in a prospective controlled randomized opportunistic prostate cancer screening programme

OBJECTIVES

PCA3 performance as a single second line biomarker is compared to the European Randomised Study of Screening for Prostate Cancer risk calculator model 3 (ERSPC RC-3) in an opportunistic screening in prostate cancer (PCa).

MATERIAL AND METHODS

5,199 men, aged 40-75y, underwent prostate-specific antigen (PSA) screening and digital rectal examination (DRE). Men with a normal DRE and PSA ≥3ng/ml had a PCA3 test done. All men with PCA3 ≥35 underwent an initial biopsy (IBx) -12 cores-. Men with PCA3 <35 were randomized 1:1 to either IBx or observation. We compared them to those obtained with ERSPC RC-3.

RESULTS

PCA3 test was performed on 838 men (16.1%). In PCA3(+) and PCA3(-) groups, global PCa detection rates were 40.9% and 14.7% with a median follow-up (FU) of 21.7 months (P<.001). In the PCA3(+) arm (n=301, 35.9%), PCa was identified in 115 men at IBx (38.2%). In the randomized arm, 256 underwent IBx and PCa was found in 46 (18.0%) (P<.001). The biopsy-sparing potential would have been 64.1% as opposed to 76.6% if we had used ERSPC RC-3. However, the estimated false negative cases for HGPCa would have been reduced by 37.1% (89 to 56 patients). Moreover, if we had applied PCA3-35 to avoid IBx, 14.7% PCa and 9.1% of clinical significant PCa patients would not have been diagnosed during this FU.

CONCLUSIONS

When PCA3-35 is used as a second-line biomarker when PSA ≥3ng/ml and DRE is normal, IBx could be avoided in 12.5% less than if ERSPC RC-3 is used and would reduce the false negative cases by 36.2%. At a FU of 21.7 months, this dual protocol would miss 9.1% of clinically significant PCa, so strict FU is mandatory with established biopsy criteria based on PSA and DRE in cases with PCA3 <35.

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.

Prostate cancer screening in Europe and Asia

Prostate cancer (PCa) is the second most common cancer among men worldwide and even ranks first in Europe. Although Asia is known as the region with the lowest PCa incidence, it has been rising rapidly over the last 20 years mostly due to the introduction of prostate-specific antigen (PSA) testing. Randomized PCa screening studies in Europe show a mortality reduction in favor of PSA-based screening but coincide with high proportions of unnecessary biopsies, overdiagnosis and subsequent overtreatment. Conclusive data on the value of PSA-based screening and hence the balance between harms and benefits in Asia is still lacking. Because of known racial variations, Asian countries should not directly apply the European screening models. Like in the western world also in Asia, new predictive markers, tools and risk stratification strategies hold great potential to improve the early detection of PCa and to reduce the worldwide existing negative aspects of PSA-based PCa screening.

Long noncoding RNAs in prostate cancer: overview and clinical implications

Prostate cancer is the second most common cause of cancer mortality among men in the United States. While many prostate cancers are indolent, an important subset of patients experiences disease recurrence after conventional therapy and progresses to castration-resistant prostate cancer (CRPC), which is currently incurable. Thus, there is a critical need to identify biomarkers that will distinguish indolent from aggressive disease, as well as novel therapeutic targets for the prevention or treatment of CRPC. In recent years, long noncoding RNAs (lncRNAs) have emerged as an important class of biological molecules. LncRNAs are polyadenylated RNA species that share many similarities with protein-coding genes despite the fact that they are noncoding (not translated into proteins). They are usually transcribed by RNA polymerase II and exhibit the same epigenetic signatures as protein-coding genes. LncRNAs have also been implicated in the development and progression of variety of cancers, including prostate cancer. While a large number of lncRNAs exhibit tissue- and cancer-specific expression, their utility as diagnostic and prognostic biomarkers is just starting to be explored. In this review, we highlight recent findings on the functional role and molecular mechanisms of lncRNAs in the progression of prostate cancer and evaluate their use as potential biomarkers and therapeutic targets.

Risk Stratification by Urinary Prostate Cancer Gene 3 Testing Before Magnetic Resonance Imaging-Ultrasound Fusion-targeted Prostate Biopsy Among Men With No History of Biopsy

OBJECTIVE

To determine whether a combination of prostate cancer gene 3 (PCA3) and magnetic resonance imaging (MRI) suspicion score (mSS) could further optimize detection of prostate cancer on MRI fusion-targeted biopsy (MRF-TB) among men with no history of biopsy.

MATERIALS AND METHODS

We included in this study 187 men presenting to our institution between June 2012 and August 2014 who underwent multiparametric MRI (mpMRI) and PCA3 before MRF-TB. Biopsy results, stratified by biopsy indication and PCA3 score, were recorded. Receiver operating characteristics curves and multivariable logistic regressions were used to model the association of PCA3 and mSS with cancer detection on MRF-TB.

RESULTS

PCA3 is associated with cancer detection on MRF-TB for men with no prior biopsies (area under the curve: 0.67, 95% confidence interval: 0.59-0.76). Using a cutoff of ≥35, PCA3 was associated with cancer risk among men with mSS 2-3 (P = .004), but not among those with mSS 4-5 (P = .340). The interaction of PCA3 and mSS demonstrated significantly higher discrimination for cancer than mSS alone (area under the curve: 0.83 vs 0.79, P = .0434).

CONCLUSION

Urinary PCA3 is associated with mSS and the detection of cancer on MRF-TB for men with no prior biopsies. PCA3 notably demonstrates a high negative predictive value among mSS 2-3. However, in the case of high-suspicion mpMRI, PCA3 is not associated with cancer detection on MRF-TB, adding little to cancer diagnosis. Further studies are needed to evaluate the utility of PCA3 in predicting cancer among men with normal mpMRI.

External validation of a PCA-3-based nomogram for predicting prostate cancer and high-grade cancer on initial prostate biopsy

INTRODUCTION

The aim of this study was to externally validate a previously developed PCA3-based nomogram for the prediction of prostate cancer (PCa) and high-grade (intermediate and/or high-grade) prostate cancer (HGPCa) at the time of initial prostate biopsy.

METHODS

A retrospective review was performed on a cohort of 336 men from a large urban academic medical center. All men had serum PSA <20 ng/ml and underwent initial transrectal ultrasound-guided prostate biopsy with at least 10 cores sampling for suspicious exam and/or elevated PSA. Covariates were collected for the nomogram and included age, ethnicity, family history (FH) of PCa, PSA at diagnosis, PCA3, total prostate volume (TPV), and abnormal finding on digital rectal exam (DRE). These variables were used to test the accuracy (concordance index) and calibration of a previously published PCA3 nomogram.

RESULTS

Biopsy confirms PCa and HGPCa in 51.0% and 30.4% of validation patients, respectively. This differed from the original cohort in that it had significantly more PCa and HGPCA (51% vs. 44%, P = 0.019; and 30.4% vs. 19.1%, P < 0.001). Despite the differences in PCa detection the concordance index was 75% and 77% for overall PCa and HGPCa, respectively. Calibration for overall PCa was good.

CONCLUSIONS

This represents the first external validation of a PCA3-based prostate cancer predictive nomogram in a North American population. Prostate 76:1019-1023, 2016. © 2016 Wiley Periodicals, Inc.

The clinical effectiveness and cost-effectiveness of the PROGENSA® prostate cancer antigen 3 assay and the Prostate Health Index in the diagnosis of prostate cancer: a systematic review and economic evaluation

BACKGROUND

There is no single definitive test to identify prostate cancer in men. Biopsies are commonly used to obtain samples of prostate tissue for histopathological examination. However, this approach frequently misses cases of cancer, meaning that repeat biopsies may be necessary to obtain a diagnosis. The PROGENSA(®) prostate cancer antigen 3 (PCA3) assay (Hologic Gen-Probe, Marlborough, MA, USA) and the Prostate Health Index (phi; Beckman Coulter Inc., Brea, CA, USA) are two new tests (a urine test and a blood test, respectively) that are designed to be used to help clinicians decide whether or not to recommend a repeat biopsy.

OBJECTIVE

To evaluate the clinical effectiveness and cost-effectiveness of the PCA3 assay and the phi in the diagnosis of prostate cancer.

DATA SOURCES

Multiple publication databases and trial registers were searched in May 2014 (from 2000 to May 2014), including MEDLINE, EMBASE, The Cochrane Library, ISI Web of Science, Medion, Aggressive Research Intelligence Facility database, ClinicalTrials.gov, International Standard Randomised Controlled Trial Number Register and World Health Organization International Clinical Trials Registry Platform.

REVIEW METHODS

The assessment of clinical effectiveness involved three separate systematic reviews, namely reviews of the analytical validity, the clinical validity of these tests and the clinical utility of these tests. The assessment of cost-effectiveness comprised a systematic review of full economic evaluations and the development of a de novo economic model.

SETTING

The perspective of the evaluation was the NHS in England and Wales.

PARTICIPANTS

Men suspected of having prostate cancer for whom the results of an initial prostate biopsy were negative or equivocal.

INTERVENTIONS

The use of the PCA3 score or phi in combination with existing tests (including histopathology results, prostate-specific antigen level and digital rectal examination), multiparametric magnetic resonance imaging and clinical judgement.

RESULTS

In addition to documents published by the manufacturers, six studies were identified for inclusion in the analytical validity review. The review identified issues concerning the precision of the PCA3 assay measurements. It also highlighted issues relating to the storage requirements and stability of samples intended for analysis using the phi assay. Fifteen studies met the inclusion criteria for the clinical validity review. These studies reported results for 10 different clinical comparisons. There was insufficient evidence to enable the identification of appropriate test threshold values for use in a clinical setting. In addition, the implications of adding either the PCA3 assay or the phi to clinical assessment were not clear. Furthermore, the addition of the PCA3 assay or the phi to clinical assessment plus magnetic resonance imaging was not found to improve discrimination. No published papers met the inclusion criteria for either the clinical utility review or the cost-effectiveness review. The results from the cost-effectiveness analyses indicated that using either the PCA3 assay or the phi in the NHS was not cost-effective.

LIMITATIONS

The main limitations of the systematic review of clinical validity are that the review conclusions are over-reliant on findings from one study, the descriptions of clinical assessment vary widely within reviewed studies and many of the reported results for the clinical validity outcomes do not include either standard errors or confidence intervals.

CONCLUSIONS

The clinical benefit of using the PCA3 assay or the phi in combination with existing tests, scans and clinical judgement has not yet been confirmed. The results from the cost-effectiveness analyses indicate that the use of these tests in the NHS would not be cost-effective.

STUDY REGISTRATION

This study is registered as PROSPERO CRD42014009595.

FUNDING

The National Institute for Health Research Health Technology Assessment programme.

PCA3-based nomogram for predicting prostate cancer and high grade cancer on initial transrectal guided biopsy

BACKGROUND

To develop a validated prostate cancer antigen 3 (PCA3) based nomogram that predicts likelihood of overall prostate cancer (PCa) and intermediate/high grade prostate cancer (HGPCa) in men pursuing initial transrectal prostate biopsy (TRUS-PBx).

METHODS

Data were collected on 3,675 men with serum prostate specific antigen level (PSA) ≤ 20 ng/ml who underwent initial prostate biopsy with at least 10 cores sampling at time of the biopsy. Two logistic regression models were constructed to predict overall PCa and HGPCa incorporating age, race, family history (FH) of PCa, PSA at diagnosis, PCA3, total prostate volume (TPV), and digital rectal exam (DRE).

RESULTS

One thousand six hundred twenty (44%) patients had biopsy confirmed PCa with 701 men (19.1%) showing HGPCa. Statistically significant predictors of overall PCa were age (P < 0.0001, OR. 1.51), PSA at diagnosis (P < 0.0001, OR.1.95), PCA3 (P < 0.0001, OR.3.06), TPV (P < 0.0001, OR.0.47), FH (P = 0.003, OR.1.32), and abnormal DRE (P = 0.001, OR. 1.32). While for HGPCa, predictors were age (P < 0.0001, OR.1.77), PSA (P < 0.0001, OR.2.73), PCA3 (P < 0.0001, OR.2.26), TPV (P < 0.0001, OR.0.4), and DRE (P < 0.0001, OR.1.53). Two nomograms were reconstructed for predicted overall PCa probability at time of initial biopsy with a concordance index of 0.742 (Fig. 1), and HGPCa with a concordance index of 0.768 (Fig. 2).

CONCLUSIONS

Our internally validated initial biopsy PCA3 based nomogram is reconstructed based on a large dataset. The c-index indicates high predictive accuracy, especially for high grade PCa and improves the ability to predict biopsy outcomes.

Clinical evaluation of prostate cancer gene 3 score in diagnosis among Chinese men with prostate cancer and benign prostatic hyperplasia

BACKGROUND

Prostate cancer is the second most common diagnosed cancer in men. Due to the low specificity of current diagnosis methods for detecting prostate cancer, identification of new biomarkers is highly desirable. The study was conducted to determine the clinical utility of the prostate cancer gene 3 (PCA3) assay to predict biopsy-detected cancers in Chinese men.

METHODS

The study included men who had a biopsy at The Affiliated Sixth People's Hospital of Shanghai Jiao Tong University from January 2013 to December 2013. Formalin-fixed, paraffin-embedded tissue blocks were used to test PCA3 and prostate-specific antigen (PSA) mRNA. The diagnostic accuracy of the PCA3 score for predicting a positive biopsy outcome was studied using sensitivity and specificity, and it was compared with PSA.

RESULTS

The probability of a positive biopsy increased with increasing PCA3 scores. The mean PCA3 score was significantly higher in men with prostate cancer (198.03, 95 % confidence interval [CI] 74.79-321.27) vs benign prostatic hyperplasia (BPH) (84.31, 95 % CI 6.47-162.15, P < 0.01). The PCA3 score (cutoff 35) had a sensitivity of 85.7 % and specificity of 62.5 %. Receiver operating characteristic analysis showed higher areas under the ROC curve for the PCA3 score vs PSA, but without statistical significance.

CONCLUSIONS

Increased PCA3 in biopsy tissue correlated with prostate cancer and the PCA3 assay may improve the diagnosis efficacy as the PCA3 score being independent of PSA level. The diagnostic significance of urinary PCA3 testing should be explored in future study to determine the prediction value in guiding biopsy decision as the clinical relevance of current study was limited for PCA3 testing based on biopsy tissue in a limited number of Chinese men.

Current biomarkers for diagnosing of prostate cancer

Prostate cancer (PCa) is mostly detected by prostate-specific antigen (PSA) as one of the most widely used tumor markers. But PSA is limited with its low specificity. The prostate health index (phi) can improve specificity over percent free and total PSA and correlates with aggressive cancer. The urinary PCA3 also shows its utility to detect PCa but its correlation with aggressiveness and the low sensitivity at high values are limitations. While the detection of alterations of the androgen-regulated TMPRSS2 and ETS transcription factor genes in tissue of ˜50% of all PCa patients was one research milestone, the urinary assay should only be used in combination with PCA3. Both US FDA-approved markers phi and PCA3 perform equally.

Optimizing the clinical utility of PCA3 to diagnose prostate cancer in initial prostate biopsy

Background

PCA3 has been included in a nomogram outperforming previous clinical models for the prediction of any prostate cancer (PCa) and high grade PCa (HGPCa) at the initial prostate biopsy (IBx). Our objective is to validate such IBx-specific PCA3-based nomogram. We also aim to optimize the use of this nomogram in clinical practice through the definition of risk groups.

Methods

Independent external validation. Clinical and biopsy data from a contemporary cohort of 401 men with the same inclusion criteria to those used to build up the reference’s nomogram in IBx. The predictive value of the nomogram was assessed by means of calibration curves and discrimination ability through the area under the curve (AUC). Clinical utility of the nomogram was analyzed by choosing thresholds points that minimize the overlapping between probability density functions (PDF) in PCa and no PCa and HGPCa and no HGPCa groups, and net benefit was assessed by decision curves.

Results

We detect 28 % of PCa and 11 % of HGPCa in IBx, contrasting to the 46 and 20 % at the reference series. Due to this, there is an overestimation of the nomogram probabilities shown in the calibration curve for PCa. The AUC values are 0.736 for PCa (C.I.95 %:0.68–0.79) and 0.786 for HGPCa (C.I.95 %:0.71–0.87) showing an adequate discrimination ability. PDF show differences in the distributions of nomogram probabilities in PCa and not PCa patient groups. A minimization of the overlapping between these curves confirms the threshold probability of harboring PCa >30 % proposed by Hansen is useful to indicate a IBx, but a cut-off > 40 % could be better in series of opportunistic screening like ours. Similar results appear in HGPCa analysis. The decision curve also shows a net benefit of 6.31 % for the threshold probability of 40 %.

Conclusions

PCA3 is an useful tool to select patients for IBx. Patients with a calculated probability of having PCa over 40 % should be counseled to undergo an IBx if opportunistic screening is required.

Role of PCA3 test in clinical decision making for prostate cancer diagnosis

AIM: To assess the role of PCA3 urine test in the management of patients with suspected prostate cancer after repeat negative prostate biopsies.

METHODS: Patients with suspected prostate cancer either due to high or rising prostate specific antigen (PSA) levels and with a history of prostate biopsy who were candidates for repeat procedure were prospectively recruited to undergo PCA3 urine test. The recommendations on further management including the decision whether to proceed or not to the biopsy were made based on the PCA3 score. Patients’ adherence with the recommendations and influence of the PCA3 test on clinical decision making were assessed. The contribution of the multivariate model was measured with a decision curve analysis.

RESULTS: Three hundred and fifty-six patients were recruited to the study and underwent the PCA3 test. Twenty-six percent of 263 patients underwent prostate biopsy despite the low risk designation by PCA3 and 30% of 93 men did not proceed to biopsy despite a high risk result, rendering overall adherence of 73%. The variables that significantly correlated with adherence were positive family history of prostate cancer and PSA more than 10 ng/mL. Pre-test clinical stage, the number and the results of previous biopsies were not associated with the adherence. The decision curve analysis gave identical results for cut-off points of 25 and 35. On multivariate analysis the model that included PCA3 score, serum PSA, family history and result of the previous biopsy best performed with Area Under the Curve of 0.77.

CONCLUSION: PCA3 urine test markedly outperforms PSA in a repeat biopsy setting. Urologists and patients demonstrate substantial confidence in this analysis and tend to follow its recommendations.

3-Tesla magnetic resonance imaging improves the prostate cancer detection rate in transrectral ultrasound-guided biopsy

The detection rate of prostate cancer (PCa) using traditional biopsy guided by transrectal ultrasound (TRUS) is not satisfactory. The aim of this study was to determine the utility of 3-Tesla (3-T) magnetic resonance imaging (MRI) prior to TRUS-guided prostate biopsy and to investigate which subgroup of patients had the most evident improvement in PCa detection rate. A total of 420 patients underwent 3-T MRI examination prior to the first prostate biopsy and the positions of suspicious areas were recorded respectively. TRUS-guided biopsy regimes included systematic 12-core biopsy and targeted biopsy identified by MRI. Patients were divided into subgroups according to their serum prostate-specific antigen (PSA) levels, PSA density (PSAD), prostate volume, TRUS findings and digital rectal examination (DRE) findings. The ability of MRI to improve the cancer detection rate was evaluated. The biopsy positive rate of PCa was 41.2% (173/420), and 41 of the 173 (23.7%) patients were detected only by targeted biopsy in the MRI-suspicious area. Compared with the systematic biopsy, the positive rate was significantly improved by the additional targeted biopsy (P=0.0033). The highest improvement of detection rate was observed in patients with a PSA level of 4–10 ng/ml, PSAD of 0.12–0.20 ng/ml², prostate volume >50 ml, negative TRUS findings and negative DRE findings (P<0.05). Therefore, it is considered that 3-T MRI examination could improve the PCa detection rate on first biopsy, particularly in patients with a PSA level of 4–10 ng/ml, PSAD of 0.12–0.20 ng/ml², prostate volume of >50 ml, negative TRUS findings and negative DRE findings.

Prostate cancer nomograms: a review of their use in cancer detection and treatment

As prostate cancer treatment discussions have grown more complex, increasing numbers of nomograms to guide decision-making have been found in the literature. Such nomograms can influence every step in the prostate cancer therapeutic process, from determining the need for biopsy to the need for adjuvant therapy. With a properly counseled patient who is aware of the limitations of nomograms, such tools assist in the shared decision-making that characterizes modern informed consent.

Imaging and intervention in prostate cancer: Current perspectives and future trends

Prostate cancer is the commonest malignancy in men that causes significant morbidity and mortality worldwide. Screening by digital rectal examination (DRE) and serum prostate-specific antigen (PSA) is used despite its limitations. Gray-scale transrectal ultrasound (TRUS), used to guide multiple random prostatic biopsies, misses up to 20% cancers and frequently underestimates the grade of malignancy. Increasing the number of biopsy cores marginally increases the yield. Evolving techniques of real-time ultrasound elastography (RTE) and contrast-enhanced ultrasound (CEUS) are being investigated to better detect and improve the yield by allowing “targeted” biopsies. Last decade has witnessed rapid developments in magnetic resonance imaging (MRI) for improved management of prostate cancer. In addition to the anatomical information, it is capable of providing functional information through diffusion-weighted imaging (DWI), magnetic resonance spectroscopy (MRS), and dynamic contrast-enhanced (DCE) MRI. Multi-parametric MRI has the potential to exclude a significant cancer in majority of cases. Inclusion of MRI before prostatic biopsy can reduce the invasiveness of the procedure by limiting the number of cores needed to make a diagnosis and support watchful waiting in others. It is made possible by targeted biopsies as opposed to random. With the availability of minimally invasive therapeutic modalities like high-intensity focused ultrasound (HIFU) and interstitial laser therapy, detecting early cancer is even more relevant today. [18F]--fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸FDG PET/CT) has no role in the initial evaluation of prostate cancer. Choline PET has been recently found to be more useful. Fluoride-PET has a higher sensitivity and resolution than a conventional radionuclide bone scan in detecting skeletal metastases.

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.

New concepts concerning prostate cancer screening

Prostate Cancer (CaP) is rapidly becoming a worldwide health issue. While CaP mortality has decreased in recent years, coincident with the widespread use of Prostate-Specific Antigen (PSA) screening, it remains the most common solid tumor in men and is the second leading cause of cancer death in the United States. The frequency of CaP is growing not only in western cultures, but also its incidence is dramatically increasing in eastern nations. Recently, examination of data from long-term trials and follow up has cast a shadow on the effectiveness of employing PSA as a primary screening tool for CaP. In this review, we not only summarize opinions from this examination and synthesize recommendations from several groups that suggest strategies for utilizing PSA as a tool, but also call for research into biomarkers for CaP diagnosis and disease progression. We also describe our recent work that identified a smooth muscle contractile protein in prostate epithelia, namely smooth muscle gamma actin, and indicate the potential for this molecule as a new unique footprint and as a CaP marker.

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.