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

Discovery of prognostic lncRNAs in colorectal cancer using spatial transcriptomics

Colorectal cancer (CRC) exhibits significant genetic and epigenetic diversity, evolving into sub-clonal populations with varied metastatic potentials and treatment responses. Predicting metastatic disease in CRC patients remains challenging, underscoring the need for reliable biomarkers. While most research on therapeutic targets and biomarkers has focused on proteins, non-coding RNAs such as long non-coding RNAs (lncRNAs) comprise most of the transcriptome and demonstrate superior tissue- and cancer-specific expression. We utilised spatial transcriptomics to investigate lncRNAs in CRC tumours, offering more precise cell-type-specific expression data compared to bulk RNA sequencing. Our analysis identified 301 lncRNAs linked to malignant CRC regions, which we validated with public data. Further validation using RNA-FISH revealed three lncRNAs (LINC01978, PLAC4, and LINC01303) that are detectable in stage II tumours but not in normal epithelium and are upregulated in metastatic tissues. These lncRNAs hold potential as biomarkers for early risk assessment of metastatic disease.

How to Integrate Prostate Cancer Biomarkers in Urology Clinical Practice: An Update

Nowadays, the management of prostate cancer has become more and more challenging due to the increasing number of available treatment options, therapeutic agents, and our understanding of its carcinogenesis and disease progression. Moreover, currently available risk stratification systems used to facilitate clinical decision-making have limitations, particularly in providing a personalized and patient-centered management strategy. Although prognosis and prostate cancer-specific survival have improved in recent years, the heterogenous behavior of the disease among patients included in the same risk prognostic group negatively impacts not only our clinical decision-making but also oncological outcomes, irrespective of the treatment strategy. Several biomarkers, along with available tests, have been developed to help clinicians in difficult decision-making scenarios and guide management strategies. In this review article, we focus on the scientific evidence that supports the clinical use of several biomarkers considered by professional urological societies (and included in uro-oncological guidelines) in the diagnosis process and specific difficult management strategies for clinically localized or advanced prostate cancer.

PCA3 and TMPRSS2: ERG Urine Level as Diagnostic Biomarker of Prostate Cancer

Background

Prostate cancer is a highly prevalent urological carcinoma with an increasing incidence in Indonesia and all around the world. Early diagnosis can greatly affect treatment outcomes and increase life expectancy. Several biomarkers for detecting prostate cancer have been studied and showed great promise.

Purpose

This study aims to analyze prostate cancer antigen 3 (PCA3) as well as transmembrane serine protease 2:ERG (TMPRSS2:ERG) for diagnosing and serving as urine biomarkers in predicting prostate cancer incidences.

Methods

We conducted an analytical study to assess the utility of PCA3 and TMPRSS2:ERG for detecting prostate cancer. Thirty samples were included in this study to see the utilization of PCA3 and TMPRSS2:ERG as diagnostic biomarkers of prostate cancer. A urine sample was taken and the PCA3 test was performed using the PCA3 PROGENSA test, while the TMPRSS2:ERG was performed using the chemiluminescent DNA probe method with a hybridization protection test.

Results

The average age of the subject was 61.07±8.3 years. Based on calculations using the Mann-Whitney test, there was a significant relationship between prostate-Specific Antigen (PSA) overexpression (p<0.001), TMPRSS2:ERG (p=0.001), and PCA3 (p=0.003) with prostate cancer incidence. The sensitivity of PCA3 and TMPRSS2:ERG in detecting prostate cancer was 76.9% and 92.3%, respectively. Hence, TMPRSS2:ERG and PCA3 can be used as biomarkers for the occurrence of prostate cancer. We also performed a Kruskal-Wallis test; however, there was no significant relationship between PSA (p=0.236), TMPRSS2:ERG (p=0.801), and PCA3 (p=0.091) with the Gleason score.

Conclusion

There is a significant correlation between overexpression of PSA, TMPRSS2:ERG and PCA3 with the incidence of prostate cancer, and TMPRSS2:ERG and PCA3 can be used as biomarkers of prostate cancer.

Systematic review of methods used to improve the efficacy of magnetic resonance in early detection of clinically significant prostate cancer

BACKGROUND AND OBJECTIVE

Prostate cancer (PC) is the malignant neoplasm with the highest incidence after lung cancer worldwide. The objective of this study is to review the literature on the methods that improve the efficacy of the current strategy for the early diagnosis of clinically significant PC (csPC), based on the performance of magnetic resonance imaging (RM) and targeted biopsies when suspicious lesions are detected, in addition to systematic biopsy.

EVIDENCE ACQUISITION

A systematic literature review was performed in PubMed, Web of Science and Cochrane according to the PRISMA criteria (Preferred Reporting Items for Systematic Reviews and Meta-Analyses), using the search terms: multiparametric magnetic resonance imaging, biparametric magnetic resonance imaging, biomarkers in prostate cancer, prostate cancer y early diagnosis. A total of 297 references were identified and, using the PICO selection criteria, 21 publications were finally selected to synthesize the evidence.

EVIDENCE SYNTHESIS

With the consolidation of MRI as the test of choice for the diagnosis of prostate cancer, the role of PSA density (PSAD) becomes relevant as a predictive tool included in prediction nomograms, without added cost. PSAD and diagnostic markers, combined with MRI, offer a high diagnostic power with an area under curve (AUC) above 0.7. Only the SHTLM3 model integrates markers in the creation of a nomogram. Prediction models also offer consistent efficacy with an AUC greater than 0.8 when associating MRI.

CONCLUSIONS

The efficacy of MRI in clinically significant prostate cancer detection can be improved with different parameters in order to generate predictive models that support decision making.

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.

Locus-Specific Bisulfate NGS Sequencing of GSTP1, RNF219, and KIAA1539 Genes in the Total Pool of Cell-Free and Cell-Surface-Bound DNA in Prostate Cancer: A Novel Approach for Prostate Cancer Diagnostics

The locus-specific methylation of three genes (GSTP1, RNF219, and KIAA1539, also known as FAM214B) in the total pool of blood cell-free DNA, including cell-free DNA from plasma and cell-surface-bound DNA, of patients with prostate cancer and healthy donors was studied on the MiSeq platform. Our study found a higher methylation index of loci for total cell-free DNA compared with cell-free DNA. For total cell-free DNA, the methylation of GSTP1 in each of the 11 positions provided a complete separation of cancer patients from healthy donors, whereas for cell-free DNA, there were no positions in the three genes allowing for such separation. Among the prostate cancer patients, the minimum proportion of GSTP1 genes methylated in any of the 17 positions was 12.1% of the total circulated DNA fragments, and the minimum proportion of GSTP1 genes methylated in any of the 11 diagnostically specific positions was 8.4%. Total cell-free DNA was shown to be more convenient and informative as a source of methylated DNA molecules circulating in the blood than cell-free DNA.

LINC01146/F11R facilitates growth and metastasis of prostate cancer under the regulation of TGF-β

The effect of long intergenic non-protein coding RNAs (lncRNAs) was verified in prostate cancer (PCa), but the mechanism of LINC01146 in PCa is unclear. Bioinformatics was applied to analyze LINC01146 expression in PCa and predict target genes of LINC01146, followed by the verification of qRT-PCR, RNA pull-down and co-immunoprecipitation (Co-IP). The correlation between LINC01146 expression and clinicopathological characteristics was investigated. The location of LINC01146 in PCa cells was detected by fluorescence in situ hybridization (FISH). After interference with LINC01146 or/and F11 receptor (F11R) or treated with transforming growth factor beta 1 (TGF-β1), the function of LINC01146 in PCa in vitro or in vivo was determined by CCK-8, colony formation, flow cytometry, scratch test, transwell assay, xenograft experiment and western blot. LINC01146 and F11R were over-expressed in PCa and positively correlated with poor prognosis. LINC01146 located in the cytoplasm and combined with F11R. LINC01146 overexpression impeded apoptosis, facilitated viability, proliferation, migration and invasion in PCa cells in vitro, promoted tumor growth in vivo, downregulated E-cadherin, Bax and Cleaved caspase-3, and upregulated N-cadherin, Vimentin and PCNA, but LINC01146 silencing did the opposite. F11R was positively regulated by LINC01146 and F11R depletion negated the effect of LINC01146 overexpression on malignant phenotypes of PCa cells. The expression of LINC01146 and F11R was regulated by TGF-β1. The promoting role of TGF-β1 in migration, invasion and F11R in PCa cells was reversed by LINC01146 silencing. LINC01146 upregulated F11R to facilitate malignant phenotypes of PCa cells, which was regulated by TGF-β.

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.

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.

The promising role of new molecular biomarkers in prostate cancer: from coding and non-coding genes to artificial intelligence approaches

Background

Risk stratification or progression in prostate cancer is performed with the support of clinical-pathological data such as the sum of the Gleason score and serum levels PSA. For several decades, methods aimed at the early detection of prostate cancer have included the determination of PSA serum levels. The aim of this systematic review is to provide an overview about recent advances in the discovery of new molecular biomarkers through transcriptomics, genomics and artificial intelligence that are expected to improve clinical management of the prostate cancer patient.

Methods

An exhaustive search was conducted by Pubmed, Google Scholar and Connected Papers using keywords relating to the genetics, genomics and artificial intelligence in prostate cancer, it includes “biomarkers”, “non-coding RNAs”, “lncRNAs”, “microRNAs”, “repetitive sequence”, “prognosis”, “prediction”, “whole-genome sequencing”, “RNA-Seq”, “transcriptome”, “machine learning”, and “deep learning”.

Results

New advances, including the search for changes in novel biomarkers such as mRNAs, microRNAs, lncRNAs, and repetitive sequences, are expected to contribute to an earlier and accurate diagnosis for each patient in the context of precision medicine, thus improving the prognosis and quality of life of patients. We analyze several aspects that are relevant for prostate cancer including its new molecular markers associated with diagnosis, prognosis, and prediction to therapy and how bioinformatic approaches such as machine learning and deep learning can contribute to clinic. Furthermore, we also include current techniques that will allow an earlier diagnosis, such as Spatial Transcriptomics, Exome Sequencing, and Whole-Genome Sequencing.

Conclusion

Transcriptomic and genomic analysis have contributed to generate knowledge in the field of prostate carcinogenesis, new information about coding and non-coding genes as biomarkers has emerged. Synergies created by the implementation of artificial intelligence to analyze and understand sequencing data have allowed the development of clinical strategies that facilitate decision-making and improve personalized management in prostate cancer.

Liquid biomarkers for early detection of prostate cancer and summary of available data for their use in African-American men

BACKGROUND

Several liquid biomarker tests have been developed to account for the limitations of prostate specific antigen (PSA) screening prior to prostate biopsy. African ancestry is an established risk factor for prostate cancer (PCa) and must be particularly considered when evaluating patients with liquid biomarkers. While multiple tests have been developed over decades of exploration, recent advances can help patients and physicians incorporate data into a broader clinical context.

METHODS

We sought to review currently available liquid biomarker tests in a practical, clinically directed fashion with particular focus on performance in men with African ancestry. We reviewed discovery and validation studies and highlight important considerations for each test.

RESULTS

We discuss the advantages and limitations of percent free PSA, Prostate Health Index, Progensa® PCA3, ExoDx® Prostate Test, SelectMDx®, 4Kscore® Test, and Mi-Prostate Score and summarize salient studies on their use. A literature review of evidence specifically for men with African ancestry was conducted and available studies were summarized.

CONCLUSIONS

Liquid biomarkers can be useful tools for aiding in risk stratification prior to prostate biopsy. Use of such tests should be individualized based on a thorough knowledge of supporting evidence and the goals of the patient and physician. Further study should prioritize evaluation of such biomarkers in men with African ancestry.

Beyond Prostate Specific Antigen: New Prostate Cancer Screening Options

Prostate specific antigen (PSA) is one of the best-known biomarkers for screening, diagnosis and follow-up of patients for prostate cancer. Owing to several inherent limitations with PSA, various newer blood and urinary based biomarkers have been evaluated in pursuit of better detection and risk stratification of prostate cancer cases. A combination of these different markers, in adjunct with clinical risk factors, and recent advances in imaging promises to offer better diagnostic performance with clearer risk stratification guiding therapeutics. We carried out an extensive literature search for the different biomarkers available for screening and diagnosis of prostate cancer, compared their performance with serum PSA to allow clinicians to draw meaningful conclusions to offer their patients a more personalized medical care.

Biomarkers for prostate cancer detection and risk stratification

Although prostate cancer (PCa) is the most commonly diagnosed cancer in men, most patients do not die from the disease. Prostate specific antigen (PSA), the most widely used oncologic biomarker, has revolutionized screening and early detection, resulting in reduced proportion of patients presenting with advanced disease. However, given the inherent limitations of PSA, additional diagnostic and prognostic tools are needed to facilitate early detection and accurate risk stratification of disease. Serum, urine, and tissue-based biomarkers are increasingly being incorporated into the clinical care paradigm, but there is still a limited understanding of how to use them most effectively. In the current article, we review test characteristics and clinical performance data for both serum [4 K score, prostate health index (phi)] and urine [SelectMDx, ExoDx Prostate Intelliscore, MyProstateScore (MPS), and PCa antigen 3 (PCA3)] biomarkers to aid decisions regarding initial or repeat biopsies as well as tissue-based biomarkers (Confirm MDx, Decipher, Oncotype Dx, and Polaris) aimed at risk stratifying patients and identifying those patients most likely to benefit from treatment versus surveillance or monotherapy versus multi-modal therapy.

Locus-Specific Methylation of GSTP1, RNF219, and KIAA1539 Genes with Single Molecule Resolution in Cell-Free DNA from Healthy Donors and Prostate Tumor Patients: Application in Diagnostics

Simple Summary

Prostate cancer (PCa) is the second most commonly diagnosed cancer in men, which is constantly accompanied by benign prostate hyperplasia (BPH). To reach a 100% 5-year survival rate in PCa, which is characteristic for PCa if it is diagnosed in early stages, efficient PCa diagnostics against the background of BPH are demanded. The article describes a liquid biopsy approach to differential PCa diagnostics based on the data on locus-specific methylation of the three genes (GSTP1, RNF219, and KIAA1539) obtained with NGS of cell-free DNA from blood plasma of PCa, BPH, and healthy individuals. We offered a diagnostic approach including the analysis of simultaneous methylation status of two CpGs in one cell-free DNA molecule, allowing the discrimination of all patients with absolute sensitivity and specificity.

Abstract

The locus-specific methylation of three genes (GSTP1, RNF219, and KIAA1539 (also known as FAM214B)) in the blood plasma cell-free DNA (cfDNA) of 20 patients with prostate cancer (PCa), 18 healthy donors (HDs), and 17 patients with benign prostatic hyperplasia (BPH) was studied via the MiSeq platform. The methylation status of two CpGs within the same loci were used as the diagnostic feature for discriminating the patient groups. Many variables had good diagnostic characteristics, e.g., each of the variables GSTP1.C3.C9, GSTP1.C9, and GSTP1.C9.T17 demonstrated an 80% sensitivity at a 100% specificity for PCa patients vs. the others comparison. The analysis of RNF219 gene loci methylation allowed discriminating BPH patients with absolute sensitivity and specificity. The data on the methylation of the genes GSTP1 and RNF219 allowed discriminating PCa patients, as well as HDs, with absolute sensitivity and specificity. Thus, the data on the locus-specific methylation of cfDNA (with single-molecule resolution) combined with a diagnostic approach considering the simultaneous methylation of several CpGs in one locus enabled the discrimination of HD, BPH, and PCa patients.

Optimization of Apta-Sensing Platform for Detection of Prostate Cancer Marker PCA3

This work is a continuation of our research into the development of simple, reliable, and cost-effective methods for the early diagnosis of prostate cancer (PCa). The proposed method is based on the electrochemical detection of the PCA3 biomarker of PCa (long non-coded RNA transcript expressed in urine) using a specific aptamer labeled with a redox group (methylene blue). The electrochemical measurements (cyclic voltammograms) obtained from electrodes functionalized with the aptamer were complemented in this work by another biosensing technique: total internal reflection ellipsometry (TIRE). In addition to proving the concept of the detection of PCA3 in low concentrations down to 90 pM, this study improved our understanding of the processes by which PCA3 binds to its specific aptamer. The high specificity of the binding of PCA3 to the aptamer was assessed by studying the binding kinetics, which yielded an affinity constant (K_D) of 2.58 × 10⁻⁹ M. Additional XPS measurements confirmed the strong covalent binding of aptamers to gold and showed spectral features associated with PCA3 to aptamer binding.

An origami paper-based peptide nucleic acid device coupled with label-free DNAzyme probe hybridization chain reaction for prostate cancer molecular screening test

Prostate cancer associated 3 (PCA3) assay has been used to improve prostate cancer diagnosis and reduce unnecessary biopsies. In this work, we successfully developed a new PCA3 assay on an origami paper-based peptide nucleic acid device (oPAD). The PCA3 oPAD comprises an acrylic cassette and shutter slides to facilitate the molecular reaction and liquid control occurring on the paper surface. To quantify PCA3, a pyrrolidinyl peptide nucleic acid (acpcPNA) was immobilized onto the aldehyde-modified oPAD surface as a selective capture probe. A G-quadruplex (GQD) DNAzyme reporter probe was designed so that the PCA3 gene target binding triggered the hybridization chain reaction of the reporter probe, resulting in the accumulation of the GQD on the oPAD. The peroxidase activity of the GQD-hemin generated a deep green color of the oxidized ABTS substrate. Image analyses were performed in Adobe Photoshop CS6. The proposed oPAD was successfully applied in PCA3 detection ranges of 1-5 μM (r² = 0.982) with a limit of detection of 0.5 μM. Our proposed oPAD was demonstrated to measure PCA3 samples in both urine matrix and human cancer cell lines. The results reveal the great potential of our origami paper-based platform to be an alternative approach for facile, rapid, and low-cost detection of PCA3 in real samples.

Tumour markers of prostate cancer: The post-PSA era

Although PSA-based prostate cancer (PCa) screening had a positive impact in reducing PCa mortality, it also led to overdiagnosis, overtreatment and to a significant number of unnecessary biopsies. In the post-PSA era, new biomarkers have emerged that can complement the information given by PSA, towards a better cancer diagnostic specificity, and also allow a better estimate of the aggressiveness of the disease and its clinical outcome. That means those markers have the potential to assist the clinician in the decision-making processes, such as whether or not to perform a biopsy, and to make the best treatment choice among the new therapeutic options available, including active surveillance (AS) in lower risk disease. In this article, we will review several of those more recent diagnostic markers (4Kscore®, [-2]proPSA and Prostate Health Index (PHI), SelectMDx®, ConfirmMDx®, Progensa® Prostate Cancer Antigen 3, Mi-Prostate Score, ExoDx™ Prostate Test, the Stockholm-3 test and ERSPC risk calculators) and prognostic markers (OncotypeDX® Genomic Prostate Score, Prolaris®, Decipher® and ProMark®). We will also address some new liquid biopsy approaches - circulating tumour cells and cell-free DNA (cfDNA) - with a potential role in metastatic castration-resistant PCa and will briefly give some future perspectives, mostly outlooking epigenetic markers.

Tissue- and Liquid-Based Biomarkers in Prostate Cancer Precision Medicine

Worldwide, prostate cancer (PC) is the second-most-frequently diagnosed male cancer and the fifth-most-common cause of all cancer-related deaths. Suspicion of PC in a patient is largely based upon clinical signs and the use of prostate-specific antigen (PSA) levels. Although PSA levels have been criticised for a lack of specificity, leading to PC over-diagnosis, it is still the most commonly used biomarker in PC management. Unfortunately, PC is extremely heterogeneous, and it can be difficult to stratify patients whose tumours are unlikely to progress from those that are aggressive and require treatment intensification. Although PC-specific biomarker research has previously focused on disease diagnosis, there is an unmet clinical need for novel prognostic, predictive and treatment response biomarkers that can be used to provide a precision medicine approach to PC management. In particular, the identification of biomarkers at the time of screening/diagnosis that can provide an indication of disease aggressiveness is perhaps the greatest current unmet clinical need in PC management. Largely through advances in genomic and proteomic techniques, exciting pre-clinical and clinical research is continuing to identify potential tissue, blood and urine-based PC-specific biomarkers that may in the future supplement or replace current standard practices. In this review, we describe how PC-specific biomarker research is progressing, including the evolution of PSA-based tests and those novel assays that have gained clinical approval. We also describe alternative diagnostic biomarkers to PSA, in addition to biomarkers that can predict PC aggressiveness and biomarkers that can predict response to certain therapies. We believe that novel biomarker research has the potential to make significant improvements to the clinical management of this disease in the near future.

SelectMDx and Multiparametric Magnetic Resonance Imaging of the Prostate for Men Undergoing Primary Prostate Biopsy: A Prospective Assessment in a Multi-Institutional Study

Prostate-specific antigen (PSA) testing as the sole indication for prostate biopsy lacks specificity, resulting in overdiagnosis of indolent prostate cancer (PCa) and missing clinically significant PCa (csPCa). SelectMDx is a biomarker-based risk score to assess urinary HOXC6 and DLX1 mRNA expression combined with traditional clinical risk factors. The aim of this prospective multi-institutional study was to evaluate the diagnostic accuracy of SelectMDx and its association with multiparametric magnetic resonance (mpMRI) when predicting PCa in prostate biopsies. Overall, 310 consecutive subjects were included. All patients underwent mpMRI and SelectMDx prior to prostate biopsy. SelectMDx and mpMRI showed sensitivity and specificity of 86.5% vs. 51.9%, and 73.8% vs. 88.3%, respectively, in predicting PCa at biopsy, and 87.1% vs. 61.3%, and 63.7% vs. 83.9%, respectively, in predicting csPCa at biopsy. SelectMDx was revealed to be a good predictor of PCa, while with regards to csPCa detection, it was demonstrated to be less effective, showing results similar to mpMRI. With analysis of strategies assessed to define the best diagnostic strategy to avoid unnecessary biopsy, SelectMDx appeared to be a reliable pathway after an initial negative mpMRI. Thus, biopsy could be proposed for all cases of mpMRI PI-RADS 4-5 score, and to those with Prostate Imaging-Reporting and Data System (PI-RADS) 1-3 score followed by a positive SelectMDx.

Biomarkers in Prostate Cancer Diagnosis: From Current Knowledge to the Role of Metabolomics and Exosomes

Early detection of prostate cancer (PC) is largely carried out using assessment of prostate-specific antigen (PSA) level; yet it cannot reliably discriminate between benign pathologies and clinically significant forms of PC. To overcome the current limitations of PSA, new urinary and serum biomarkers have been developed in recent years. Although several biomarkers have been explored in various scenarios and patient settings, to date, specific guidelines with a high level of evidence on the use of these markers are lacking. Recent advances in metabolomic, genomics, and proteomics have made new potential biomarkers available. A number of studies focused on the characterization of the specific PC metabolic phenotype using different experimental approaches has been recently reported; yet, to date, research on metabolomic application for PC has focused on a small group of metabolites that have been known to be related to the prostate gland. Exosomes are extracellular vesicles that are secreted from all mammalian cells and virtually detected in all bio-fluids, thus allowing their use as tumor biomarkers. Thanks to a general improvement of the technical equipment to analyze exosomes, we are able to obtain reliable quantitative and qualitative information useful for clinical application. Although some pilot clinical investigations have proposed potential PC biomarkers, data are still preliminary and non-conclusive.

Noncoding RNAs in Glioblastoma: Emerging Biological Concepts and Potential Therapeutic Implications

Simple Summary

Since the completion of the Human Genome Project, noncoding RNAs (ncRNAs) have emerged as an important class of genetic regulators. Several classes of ncRNAs, which include microRNAs (miRNAs), long noncoding RNAs (lncRNAs), circular RNAs (circRNAs), and piwi-interacting RNAs (piRNAs), have been shown to play important roles in controlling developmental and disease processes. In this article, we discuss the potential roles of ncRNAs in regulating glioblastoma (GBM) formation and progression as well as potential strategies to exploit the diagnostic and therapeutic potential of ncRNAs in GBM.

Abstract

Noncoding RNAs (ncRNAs) have emerged as a novel class of genomic regulators, ushering in a new era in molecular biology. With the advent of advanced genetic sequencing technology, several different classes of ncRNAs have been uncovered, including microRNAs (miRNAs), long noncoding RNAs (lncRNAs), circular RNAs (circRNAs), and piwi-interacting RNAs (piRNAs), which have been linked to many important developmental and disease processes and are being pursued as clinical and therapeutic targets. Molecular phenotyping studies of glioblastoma (GBM), the most common and lethal cancer of the adult brain, revealed that several ncRNAs are frequently dysregulated in its pathogenesis. Additionally, ncRNAs regulate many important aspects of glioma biology including tumour cell proliferation, migration, invasion, apoptosis, angiogenesis, and self-renewal. Here, we present an overview of the biogenesis of the different classes of ncRNAs, discuss their biological roles, as well as their relevance to gliomagenesis. We conclude by discussing potential approaches to therapeutically target the ncRNAs in clinic.

Electrochemical Detection of Prostate Cancer Biomarker PCA3 Using Specific RNA-Based Aptamer Labelled with Ferrocene

This paper reports on a feasibility study of electrochemical in-vitro detection of prostate cancer biomarker PCA3 (prostate cancer antigen 3) in direct assay with specific RNA aptamer labelled with a redox group (ferrocene) and immobilized on a screen-printed gold electrode surface. The cyclic voltammograms and electrochemical impedance spectroscopy methods yield encouraging results on the detection of PCA3 in a range of concentrations from 1 μg/mL down to 0.1 ng/mL in buffer solutions. Both anodic and cathodic current values in cyclic voltammograms measurements and charge transfer resistance values in electrochemical impedance spectroscopy experiments correlate with the PCA3 concentration in the sample. Kinetics studies of the binding of the PCA3 to our aptamer demonstrated high specificity of the reaction with a characteristic affinity constant of approximately 4·10−10 molar. The results of this work provide a background for the future development of novel, highly sensitive and cost-effective diagnostic methodologies for prostate cancer detection.

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.

PCA3 in Prostate Cancer

Prostate cancer antigen 3 (PCA3) is a urinary biomarker for prostate cancer and has demonstrated a good specificity and sensitivity representing a minimally invasive test.PCA3 assay could be useful in combination with PSA to suggest an eventual rebiopsy in men who have had one or more previous negative prostate biopsies.Combination of multiple tumor biomarkers will be the trend in the near future to achieve the goal of evaluate the aggressiveness of cancer and at the same time reducing the number of unnecessary biopsies.

Commercialized Blood-, Urinary- and Tissue-Based Biomarker Tests for Prostate Cancer Diagnosis and Prognosis

In the diagnosis and prognosis of prostate cancer (PCa), the serum prostate-specific antigen test is widely used but is associated with low specificity. Therefore, blood-, urinary- and tissue-based biomarker tests have been developed, intended to be used in the diagnostic and prognostic setting of PCa. This review provides an overview of commercially available biomarker tests developed to be used in several clinical stages of PCa management. In the diagnostic setting, the following tests can help selecting the right patients for initial and/or repeat biopsy: PHI, 4K, MiPS, SelectMDx, ExoDx, Proclarix, ConfirmMDx, PCA3 and PCMT. In the prognostic setting, the Prolaris, OncotypeDx and Decipher test can help in risk-stratification of patients regarding treatment decisions. Following, an overview is provided of the studies available comparing the performance of biomarker tests. However, only a small number of recently published head-to-head comparison studies are available. In contrast, recent research has focused on the use of biomarker tests in relation to the (complementary) use of multiparametric magnetic resonance imaging in PCa diagnosis.

Diagnosis accuracy of PCA3 level in patients with prostate cancer: a systematic review with meta-analysis

BACKGROUND

The diagnostic value and suitability of prostate cancer antigen 3 (PCA3) for the detection of prostate cancer (PCa) have been inconsistent in previous studies. Thus, the aim of the present meta-analysis was performed to systematically evaluate the diagnostic value of PCA3 for PCa.

MATERIALS AND METHODS

A meta-analysis was performed to search relevant studies using online databases EMBASE, PubMed and Web of Science published until February 1st, 2019. Ultimately, 65 studies met the inclusion criteria for this meta-analysis with 8.139 cases and 14.116 controls. The sensitivity, specificity, positive likelihood ratios (LR+), negative likelihood ratios (LR-), and other measures of PCA3 were pooled and determined to evaluate the diagnostic rate of PCa by the random-effect model.

RESULTS

With PCA3, the pooled overall diagnostic sensitivity, specificity, LR+, LR-, and 95% confidence intervals (CIs) for predicting significant PCa were 0.68 (0.64-0.72), 0.72 (0.68-0.75), 2.41 (2.16-2.69), 0.44 (0.40-0.49), respectively. Besides, the summary diagnostic odds ratio (DOR) and 95% CIs for PCA3 was 5.44 (4.53-6.53). In addition, the area under summary receiver operating characteristic (sROC) curves and 95% CIs was 0.76 (0.72-0.79). The major design deficiencies of included studies were differential verification bias, and a lack of clear inclusion and exclusion criteria.

CONCLUSIONS

The results of this meta-analysis suggested that PCA3 was a non-invasive method with the acceptable sensitivity and specificity in the diagnosis of PCa, to distinguish between patients and healthy individuals. To validate the potential applicability of PCA3 in the diagnosis of PCa, more rigorous studies were needed to confirm these conclusions.

LncRNA MAGI2-AS3 inhibits bladder cancer progression by targeting the miR-31-5p/TNS1 axis

In this study, we performed bioinformatics analysis to identify the competing endogenous RNAs (ceRNAs) that regulate bladder cancer (BCa) progression. RNA-sequencing data analysis identified 2451 differentially expressed mRNAs, 174 differentially expressed lncRNAs, and 186 microRNAs (miRNAs) in BCa tissues (n=414) compared to the normal urothelial tissues (n=19) from the TGCA database. CeRNA network analysis of the differentially expressed lncRNAs and mRNAs showed strong positive correlation between lncRNA MAGI2-AS3 and Tensin 1 (TNS1) mRNA in BCa tissues. Bioinformatics analysis also showed that both MAGI2-AS3 and TNS1 mRNA sequences contain miR-31-5p binding sites. Furthermore, we observed significantly lower MAGI2-AS3 and TNS1 mRNA expression and higher miR-31-5p expression in the BCa tissues and cell lines (T24 and J82) compared with their corresponding controls. Functional and biochemical experiments in BCa cell lines including luciferase reporter assays showed that MAGI2-AS3 upregulated TNS1 by sponging miR-31-5p. Transwell assays showed that the MAGI2-AS3/miR-31-5p/TNS1 axis regulated migration and invasion ability of BCa cell lines. Moreover, immunohistochemical staining of paired BCa and normal urothelial tissues showed that low expression of TNS1 correlated with advanced tumor (T) stages and lymph node metastasis in BCa. In conclusion, our study demonstrates that the MAGI2-AS3/miR-31-5p/TNS1 axis regulates BCa progression.

Identification of Clinically Significant Prostate Cancer by Combined PCA3 and AMACR mRNA Detection in Urine Samples

Purpose

Preclinical evaluation of PCA3 and AMACR transcript simultaneous detection in urine to diagnose clinical significant prostate cancer (prostate cancer with Gleason score ≥7) in a Russian cohort.

Patients and Methods

We analyzed urine samples of patients with a total serum PSA ≥2 ng/mL: 31 men with prostate cancer scheduled for radical prostatectomy, 128 men scheduled for first diagnostic biopsy (prebiopsy cohort). PCA3, AMACR, PSA and GPI transcripts were detected by multiplex reverse transcription quantitative polymerase chain reaction, and the results were used for scores for calculation and statistical analysis.

Results

There was no significant difference between clinically significant and nonsignificant prostate cancer PCA3 scores. However, there was a significant difference in the AMACR score (patients scheduled for radical prostatectomy p=0.0088, prebiopsy cohort p=0.029). We estimated AUCs, optimal cutoffs, sensitivities and specificities for PCa and csPCa detection in the prebiopsy cohort by tPSA, PCA3 score, PCPT Risk Calculator and classification models based on tPSA, PCA3 score and AMACR score. In the clinically significant prostate cancer ROC analysis, the PCA3 score AUC was 0.632 (95%CI: 0.511–0.752), the AMACR score AUC was 0.711 (95%CI: 0.617–0.806) and AUC of classification model based on the PCA3 score, the AMACR score and total PSA was 0.72 (95%CI: 0.58–0.83). In addition, the correlation of the AMACR score with the ratio of total RNA and RNA of prostate cells in urine was shown (tau=0.347, p=6.542e–09). Significant amounts of nonprostate RNA in urine may be a limitation for the AMACR score use.

Conclusion

The AMACR score is a good predictor of clinically significant prostate cancer. Significant amounts of nonprostate RNA in urine may be a limitation for the AMACR score use. Evaluation of the AMACR score and classification models based on it for clinically significant prostate cancer detection with larger samples and a follow-up analysis is promising.

Initial experience with SelectMDx® in the diagnosis of prostate cancer in a real-world evidence clinical practice setting

INTRODUCTION

The use of biomarkers in the detection of prostate cancer (PC) can decrease overdiagnosis and overtreatment of non-significant PC. We analyze the usefulness and applicability of the SelectMDx® marker in a routine clinical practice setting.

MATERIAL AND METHODS

Retrospective study of 48 patients evaluated by the SelectMDx® test between July 2017 and April 2019. Patients were stratified into two groups according to the risk estimated by the clinically significant CP test (CS-PC): <2% or 'very low risk', and >2%. Results were expressed based on previous prostate biopsy (PB) and multi-parametric magnetic resonance imaging (mpMRI) outcomes.

RESULTS

Patients with negative PB and normal/doubtful mpMRI had <2% risk in 7/9 cases. Patients without PB and normal/doubtful mpMRI had <2% risk in 12/18 cases, and 2/6 cases with a >2% risk presented CS-PC. Of the 14 patients with no previous PB or mpMRI, 9 had <2% risk, and 2 cases were diagnosed with PC from the group of patients (5) with risk >2%. The number of patients in the remaining subgroups is too small to draw any conclusions. In all cases with pathological digital rectal examination, the test showed a >2% PC risk.

CONCLUSION

SelectMDx® is a promising test for detecting patients with a very low risk of CS-PC, especially in patients with suspected PC, with or without negative PB, with normal/doubtful mpMRI. The presence of a pathological digital rectal examination may condition the result of the test.

Early Diagnosis of Prostate Cancer from the Perspective of Chinese Physicians

Prostate cancer (PCa) is the seventh most diagnosed cancer and the tenth leading cause of cancer mortality in China. Unlike the USA, both incidence and mortality continue to increase. In China, PCa is often diagnosed at a locally advanced or metastatic stage, resulting in a high mortality-to-incidence ratio. Implementing regular screening using a well-validated biomarker may result in the earlier diagnosis of localized disease. Furthermore, it is important to be able to distinguish between low-grade and high-grade disease, to avoid subjecting patients to unnecessary biopsies, undertreatment of significant disease, or overtreatment of indolent disease. While prostate-specific antigen (PSA) is commonly used in PCa screening around the world, its relationship to PCa is still unclear and results vary widely across different studies. New biomarkers, imaging techniques and risk predictive models have been developed in recent years to improve upon the accurate detection of high-grade PCa. Blood- and urine-based biomarkers, such as PSA isoforms, prostate cancer antigen 3, or mRNA transcripts, have been used to improve the detection of high-grade PCa. These markers have also been used to create risk predictive models, which can further improve PCa detection. Furthermore, multiparametric magnetic resonance imaging is becoming increasingly accessible for the detection of PCa. Because of ethnic variations, biomarkers and risk predictive models validated in Western populations cannot be directly applied to Chinese men. Validation of new biomarkers and risk predictive models in the Chinese population may improve PCa screening and reduce mortality of this disease in China.

All change in the prostate cancer diagnostic pathway

Following detection of high levels of serum prostate-specific antigen, many men are advised to have transrectal ultrasound-guided biopsy in an attempt to locate a cancer. This nontargeted approach lacks accuracy and carries a small risk of potentially life-threatening sepsis. Worse still, it can detect clinically insignificant cancer cells, which are unlikely to be the origin of advanced-stage disease. The detection of these indolent cancer cells has led to overdiagnosis, one of the major problems of contemporary medicine, whereby many men with clinically insignificant disease are advised to undergo unnecessary radical surgery or radiotherapy. Advances in imaging and biomarker discovery have led to a revolution in prostate cancer diagnosis, and nontargeted prostate biopsies should become obsolete. In this Perspective article, we describe the current diagnostic pathway for prostate cancer, which relies on nontargeted biopsies, and the problems linked to this pathway. We then discuss the utility of prebiopsy multiparametric MRI and novel tumour markers. Finally, we comment on how the incorporation of these advances into a new diagnostic pathway will affect the current risk-stratification system and explore future challenges.

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.

Long non-coding RNAs in genitourinary malignancies: a whole new world

Long non-coding RNAs (lncRNAs) are regulators of cellular machinery that are commonly dysregulated in genitourinary malignancies. Accordingly, the investigation of lncRNAs is improving our understanding of genitourinary cancers, from development to progression and dissemination. lncRNAs are involved in major oncogenic events in genitourinary malignancies, including androgen receptor (AR) signalling in prostate cancer, hypoxia-inducible factor (HIF) pathway activation in renal cell carcinoma and invasiveness in bladder cancer, as well as multiple other proliferation and survival mechanisms. In line with their putative oncogenic roles, new lncRNA-based classifications are emerging as potent predictors of prognosis. In clinical practice, detection of oncogenic lncRNAs in serum or urine might enable early cancer detection, and lncRNAs might also be promising therapeutic targets for patients with genitourinary cancer. Furthermore, as predictors of sensitivity to anticancer treatments, lncRNAs could be integrated into future precision medicine strategies. Overall, lncRNAs are promising new candidates for molecular studies and for discovery of innovative biomarkers and are putative therapeutic targets in genitourinary oncology.

Detection of the Prostate Cancer Biomarker PCA3 with Electrochemical and Impedance-Based Biosensors

Diagnosis of prostate cancer via PCA3 biomarker detection is promising to be much more efficient than with the prostatic specific antigens currently used. In this study, we present the first electrochemical and impedance-based biosensors that are capable of detecting PCA3 down to 0.128 nmol/L. The biosensors were made with a layer of PCA3-complementary single-stranded DNA (ssDNA) probe, immobilized on a layer-by-layer (LbL) film of chitosan (CHT) and carbon nanotubes (MWCNT). They are highly selective to PCA3, which was confirmed in impedance measurements and with polarization-modulated infrared reflection absorption spectroscopy (PM-IRRAS). Using information visualization methods, we could also distinguish between cell lines expressing the endogenous PCA3 long noncoding RNA (lncRNA) from cells that did not contain detectable levels of this biomarker. Since the methods involved in fabrication the biosensors are potentially low cost, one may hope to deploy PCA3 tests in any laboratory of clinical analyses and even for point-of-care diagnostics.

Extracellular vesicles in urological malignancies: an update

Extracellular vesicles (EVs) have an essential functional role in local tumour progression, metastatic spread and the emergence of drug resistance in bladder, kidney and prostate cancer. Thus, EVs could be diagnostic, prognostic and predictive biomarkers for these malignancies. Virtually all biomolecules (including DNA, mRNA, microRNA, long non-coding RNA, proteins and lipids) packaged into EVs have been tested as biomarkers in blood and urine samples. The results are very heterogeneous, but promising biomarker candidates have been identified. Differing methods of EV isolation, characterization and analysis of their content have been used owing to a lack of international consensus; hence, comparing study results is challenging. Furthermore, validation of potential biomarkers in independent cohorts or prospective trials has rarely been performed. Future efforts to establish EV-derived biomarkers need to adequately address these points. In addition, emerging technologies such as mass spectroscopy and chip-based approaches can identify surface markers specific for cancer-associated EVs and will enable specific separation from blood and urine EVs, which probably will improve their performance as biomarkers. Moreover, EVs could be harnessed as therapeutic drug delivery vehicles for precise and effective anticancer therapy.

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.

LacdiNAc-Glycosylated Prostate-specific Antigen Density is a Potential Biomarker of Prostate Cancer

BACKGROUND

Serum LacdiNAc-glycosylated prostate-specific antigen (LDN-PSA) and LDN-PSA density together with PSA and PSA density (PSAD) were measured as a diagnostic tool for prostate cancer (PCa).

PATIENTS AND METHODS

We included 150 patients with PCa without hormonal therapy and 41 patients without PCa obtained from the Kyoto University Hospital between 2012 and 2017. LDN-PSA levels were measured through a WFA-anti-PSA antibody sandwich immunoassay using a highly sensitive surface plasmon field-enhanced fluorescence spectroscopy (SPFS) system. Diagnostic performance of serum LDN-PSA and LDN-PSAD was evaluated by measuring the area under the receiver-operating characteristic curve (AUC).

RESULTS

The AUCs of LDN-PSA, LDN-PSAD, and PSAD levels (0.780, 0.848, and 0.835, respectively) detected in patients with PCa were significantly higher (P = .0001, P < .0001, and P < .0001, respectively) than that of PSA (0.590). Moreover, among 143 patients with PCa who received radical prostatectomy (RP), the AUCs of LDN-PSA, LDN-PSAD, and PSAD levels (0.750, 0.812, and 0.769, respectively) detected in patients with a pathologic Gleason grade group ≥ 2 were significantly higher (P = .0170, P = .0028, and P = .0003, respectively) than that of PSA (0.578). In the group comprising 35 patients who received RP with a Gleason grade group 1-graded biopsy, the LDN-PSA, LDN-PSAD, and PSAD levels were significantly different (P = .0097, P = .0024, and P = .0312, respectively). However, PSA alone could not discriminate cases with adverse features (P = .454).

CONCLUSIONS

LDN-PSAD is a potential marker for detecting PCa and selecting candidates for RP.

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.

The previously uncharacterized lncRNA APP promotes prostate cancer progression by acting as a competing endogenous RNA

Long noncoding RNAs (lncRNAs) promote cell proliferation, migration, invasion and castration resistance in prostate cancer (PCa). Understanding the inherited molecular mechanisms by which lncRNAs contribute to the progression of PCa to a lethal disease could have an important impact on cancer detection, diagnosis and prognosis. In our study, PCa-associated lncRNA transcripts from RNA-seq data were identified and screened via bioinformatics analysis, NCBI annotations and literature review. We identified a novel lncRNA, lncAPP (lncRNA activated in PCa progression), which activates in PCa progression and is expressed in primary tumor tissues and urine samples of patients with localized or advanced PCa. Urinary-based lncAPP is a promising biomarker for predicting PCa progression. In vitro and in vivo studies demonstrated that lncAPP enhanced cell proliferation and promoted migration and invasion. The underlying mechanism of lncRNA was investigated by RNA immunoprecipitation, dual-luciferase reporter system assay, etc. Upregulation of lncAPP promoted cell migration and invasion via competitively binding miR218 to facilitate ZEB2/CDH2 expression. In addition, in vivo subcutaneous tumor xenograft models and tail intravenously injection metastatic models were constructed to evaluate lncRNA function. Targeting lncAPP/miR218 axis in cell lines and tumor xenografts restrained tumor progression properties both in vitro and in vivo. These results establish that lncAPP/miR218 axis plays a critical role in PCa progression, and they also suggest new strategies to prevent tumor progression for therapeutic purposes.

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.

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.

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.