Risk score predicts high-grade prostate cancer in DNA-methylation positive, histopathologically negative biopsies

A review of disease risk prediction methods and applications in the omics era

Risk prediction and disease prevention are the innovative care challenges of the 21st century. Apart from freeing the individual from the pain of disease, it will lead to low medical costs for society. Until very recently, risk assessments have ushered in a new era with the emergence of omics technologies, including genomics, transcriptomics, epigenomics, proteomics, and so on, which potentially advance the ability of biomarkers to aid prediction models. While risk prediction has achieved great success, there are still some challenges and limitations. We reviewed the general process of omics-based disease risk model construction and the applications in four typical diseases. Meanwhile, we highlighted the problems in current studies and explored the potential opportunities and challenges for future clinical practice.

Association of methylation risk score with incident type 2 diabetes mellitus: A nested case-control study

AIMS

To investigate the association of methylation risk score (MRS) and its interactions with environmental factors with type 2 diabetes mellitus (T2DM) risk.

METHODS

We conducted a nested case-control study with 241 onset cases and 241 matched controls. Conditional logistic regression models were employed to identify risk CpG sites. Simple and weighted MRSs were constructed based on the methylation levels of ATP-binding cassette G1 gene, fat mass and obesity associated gene, potassium voltage-gated channel member 1 gene, and thioredoxin-interacting protein gene previously associated with T2DM to estimate the association of MRS with T2DM risk. Stratified analyses were used to investigate interactions between MRS and environmental factors.

RESULTS

A total of 10 CpG loci were identified from the aforementioned genes to calculate MRS. After controlling for potential confounding factors, taking tertile 1 as reference, the odds ratios (ORs) and 95% confidence intervals (CIs) for T2DM of tertile 3 was 2.39 (1.36-4.20) for simple MRS and 2.59 (1.45-4.63) for weighted MRS. With per SD score increment in MRS, the OR (95% CI) was 1.66 (1.29-2.14) and 1.60 (1.24-2.08) for simple and weighted MRSs, respectively. J-curved associations were observed between both simple and weighted MRSs and T2DM risks. Additionally, multiplication interactions for smoking and hypertension with simple MRS on the risk of T2DM were found, similarly for smoking and obesity with weighted MRS on the risk of T2DM (all Pinteraction  < .05).

CONCLUSION

Elevated simple and weighted MRSs were associated with increased risk of T2DM. Environmental risk factors may influence the association between MRS and T2DM.

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.

PRADclass: Hybrid Gleason Grade-Informed Computational Strategy Identifies Consensus Biomarker Features Predictive of Aggressive Prostate Adenocarcinoma

BACKGROUND

Prostate adenocarcinoma (PRAD) is a common cancer diagnosis among men globally, yet large gaps in our knowledge persist with respect to the molecular bases of its progression and aggression. It is mostly indolent and slow-growing, but aggressive prostate cancers need to be recognized early for optimising treatment, with a view to reducing mortality.

METHODS

Based on TCGA transcriptomic data pertaining to PRAD and the associated clinical metadata, we determined the sample Gleason grade, and used it to execute: (i) Gleason-grade wise linear modeling, followed by five contrasts against controls and ten contrasts between grades; and (ii) Gleason-grade wise network modeling via weighted gene correlation network analysis (WGCNA). Candidate biomarkers were obtained from the above analysis and the consensus found. The consensus biomarkers were used as the feature space to train ML models for classifying a sample as benign, indolent or aggressive.

RESULTS

The statistical modeling yielded 77 Gleason grade-salient genes while the WGCNA algorithm yielded 1003 trait-specific key genes in grade-wise significant modules. Consensus analysis of the two approaches identified two genes in Grade-1 (SLC43A1 and PHGR1), 26 genes in Grade-4 (including LOC100128675, PPP1R3C, NECAB1, UBXN10, SERPINA5, CLU, RASL12, DGKG, FHL1, NCAM1, and CEND1), and seven genes in Grade-5 (CBX2, DPYS, FAM72B, SHCBP1, TMEM132A, TPX2, UBE2C). A RandomForest model trained and optimized on these 35 biomarkers for the ternary classification problem yielded a balanced accuracy ∼ 86% on external validation.

CONCLUSIONS

The consensus of multiple parallel computational strategies has unmasked candidate Gleason grade-specific biomarkers. PRADclass, a validated AI model featurizing these biomarkers achieved good performance, and could be trialed to predict the differentiation of prostate cancers. PRADclass is available for academic use at: https://apalania.shinyapps.io/pradclass (online) and https://github.com/apalania/pradclass (command-line interface).

Developing a diagnostic model for predicting prostate cancer: a retrospective study based on Chinese multicenter clinical data

The overdiagnosis of prostate cancer (PCa) caused by nonspecific elevation serum prostate-specific antigen (PSA) and the overtreatment of indolent PCa have become a global problem that needs to be solved urgently. We aimed to construct a prediction model and provide a risk stratification system to reduce unnecessary biopsies. In this retrospective study, clinical data of 1807 patients from three Chinese hospitals were used. The final model was built using stepwise logistic regression analysis. The apparent performance of the model was assessed by receiver operating characteristic curves, calibration plots, and decision curve analysis. Finally, a risk stratification system of clinically significant prostate cancer (csPCa) was created, and diagnosis-free survival analyses were performed. Following multivariable screening and evaluation of the diagnostic performances, a final diagnostic model comprised of the PSA density and Prostate Imaging-Reporting and Data System (PI-RADS) score was established. Model validation in the development cohort and two external cohorts showed excellent discrimination and calibration. Finally, we created a risk stratification system using risk thresholds of 0.05 and 0.60 as the cut-off values. The follow-up results indicated that the diagnosis-free survival rate for csPCa at 12 months and 24 months postoperatively was 99.7% and 99.4%, respectively, for patients with a risk threshold below 0.05 after the initial negative prostate biopsy, which was significantly better than patients with higher risk. Our diagnostic model and risk stratification system can achieve a personalized risk calculation of csPCa. It provides a standardized tool for Chinese patients and physicians when considering the necessity of prostate biopsy.

Biomarkers of Aggressive Prostate Cancer at Diagnosis

In the United States, prostate cancer (CaP) remains the second leading cause of cancer deaths in men. CaP is predominantly indolent at diagnosis, with a small fraction (25-30%) representing an aggressive subtype (Gleason score 7-10) that is prone to metastatic progression. This fact, coupled with the criticism surrounding the role of prostate specific antigen in prostate cancer screening, demonstrates the current need for a biomarker(s) that can identify clinically significant CaP and avoid unnecessary biopsy procedures and psychological implications of being diagnosed with low-risk prostate cancer. Although several diagnostic biomarkers are available to clinicians, very few comparative trials have been performed to assess the clinical effectiveness of these biomarkers. It is of note, however, that a majority of these clinical trials have been over-represented by men of Caucasian origin, despite the fact that African American men have a 1.7 times higher incidence and 2.1 times higher rate of mortality from prostate cancer. Biomarkers for CaP diagnosis based on the tissue of origin include urine-based gene expression assays (PCA3, Select MDx, ExoDx Prostate IntelliScore, Mi-Prostate Score, PCA3-PCGEM1 gene panel), blood-based protein biomarkers (4K, PHI), and tissue-based DNA biomarker (Confirm MDx). Another potential direction that has emerged to aid in the CaP diagnosis include multi-parametric magnetic resonance imaging (mpMRI) and bi-parametric magnetic resonance imaging (bpMRI), which in conjunction with clinically validated biomarkers may provide a better approach to predict clinically significant CaP at diagnosis. In this review, we discuss some of the adjunctive biomarker tests along with newer imaging modalities that are currently available to help clinicians decide which patients are at risk of having high-grade CaP on prostate biopsy with the emphasis on clinical utility of the tests across African American (AA) and Caucasian (CA) men.

Biomarkers for the Detection and Risk Stratification of Aggressive Prostate Cancer

Current strategies for the clinical management of prostate cancer are inadequate for a precise risk stratification between indolent and aggressive tumors. Recently developed tissue-based molecular biomarkers have refined the risk assessment of the disease. The characterization of tissue biopsy components and subsequent identification of relevant tissue-based molecular alterations have the potential to improve the clinical decision making and patient outcomes. However, tissue biopsies are invasive and spatially restricted due to tumor heterogeneity. Therefore, there is an urgent need for complementary diagnostic and prognostic options. Liquid biopsy approaches are minimally invasive with potential utility for the early detection, risk stratification, and monitoring of tumors. In this review, we focus on tissue and liquid biopsy biomarkers for early diagnosis and risk stratification of prostate cancer, including modifications on the genomic, epigenomic, transcriptomic, and proteomic levels. High-risk molecular alterations combined with orthogonal clinical parameters can improve the identification of aggressive tumors and increase patient survival.

An overview of prostate cancer (PCa) diagnosis: Potential role of miRNAs

Prostate cancer is the second most frequently diagnosed cancer among men worldwide, with the estimated sixth leading cause of cancer death. Despite major advancements in clinical biology and imaging, digital rectal examination (DRE), prostate-specific antigen (PSA), and biopsies indication remain the keystone for screening. Several kits are used to detect genomic changes and non-coding RNAs in the sample. However, its indication remains controversial for screening purposes. There is an urged need for non-invasive biomarkers to implement precision medicine. Recent research shows that miRNAs have an important role in the diagnostic, prognostic, and therapeutic agents as non-invasive biomarkers. Though prostate cancer data remains controversial in other cancer types, such as breast cancer, miR-21 expression is upregulated. Here, we reported a prolonged revision of miRNAs as prostate cancer prognostic, diagnostic, and predictive tools, including data on androgen receptor (AR) signaling, epithelial-mesenchymal transition (EMT) process, and cancer stem cells (CSCs) regulation. The combined utilization of miRNAs with other tests will help patients and clinicians to select the most appropriate personalized treatment and to avoid overdiagnosis and unnecessary biopsies. Future clinical applications of our reported novel miRNAs have a substantial role in the primary diagnosis of prostate cancer to help treatment decisions.

Ubiquitin-related lncRNAs: The new tool for prognosis prediction in prostate cancer

Objective

To establish a ubiquitin-related long noncoding ribonucleic acids (lncRNAs) prognosis prediction model for prostate cancer (Pca).

Methods

Data were acquired through The Cancer Genome Atlas (TCGA) database. Ubiquitin-related differentially expressed genes (DEGs) and lncRNAs in Pca were filtered out. UBE2S was selected as the representative gene and validated in vitro. Progression-free survival (PFS) predictive signature was established with ubiquitin-related lncRNAs screened by Cox regression analyses and internally validated. A nomogram was constructed to assess the prognosis of Pca patients. Gene enrichment analysis was performed to explore functional differences based on risk stratification. Between different risk groups, immune status and drug sensitivity were contrasted.

Results

A total of 254 ubiquitin-related genes were screened. UBE2S was shown to promote the proliferation of Pca cells in vitro. The predictive signature was established based on six ubiquitin-related lncRNAs and validated. The prognosis of Pca patients was worse with an increasing risk score. The area under the curve (AUC) of the signature was higher than that of clinicopathological variables (0.806 vs 0.504–0.701). The AUC was 0.811 for 1-year PFS, 0.807 for 3-year PFS, and 0.790 for 5-year PFS. The calibration curves of risk score-based nomogram demonstrated high consistency. By contrasting the expression of immune function, cells, and checkpoints, we found that the signature was closely related to immunity. The high-risk patients were more sensitive to gemcitabine, cisplatin, bortezomib, etc. and resistant to bicalutamide.

Conclusion

The ubiquitin-related lncRNAs can effectively predict the prognosis of Pca and may provide new treatment options for Pca.

Methylation risk scores for childhood aeroallergen sensitization: Results from the LISA birth cohort

BACKGROUND

Epigenomic (e.g., DNA methylation [DNAm]) changes have been hypothesized as intermediate step linking environmental exposures with allergic disease. Associations between individual DNAm at CpGs and allergic diseases have been reported, but their joint predictive capability is unknown.

METHODS

Data were obtained from 240 children of the German LISA cohort. DNAm was measured in blood clots at 6 (N = 234) and 10 years (N = 227) using the Illumina EPIC chip. Presence of aeroallergen sensitization was measured in blood at 6, 10, and 15 years. We calculated six methylation risk scores (MRS) for allergy-related phenotypes, like total and specific IgE, asthma, or any allergies, based on available publications and assessed their performances both cross-sectionally (biomarker) and prospectively (predictor of the disease). Dose-response associations between aeroallergen sensitization and MRS were evaluated.

RESULTS

All six allergy-related MRS were highly correlated (r > .86), and seven CpGs were included in more than one MRS. Cross-sectionally, we observed an 81% increased risk for aeroallergen sensitization at 6 years with an increased MRS by one standard deviation (best-performing MRS, 95% confidence interval = [43%; 227%]). Significant associations were also seen cross-sectionally at 10 years and prospectively, though the effect of the latter was attenuated when restricted to participants not sensitized at baseline. A clear dose-response relationship with levels of aeroallergen sensitization could be established cross-sectionally, but not prospectively.

CONCLUSION

We found good classification and prediction capabilities of calculated allergy-related MRS cross-sectionally, underlining the relevance of altered gene-regulation in allergic diseases and providing insights into potential DNAm biomarkers of aeroallergen sensitization.

Recent advances in nanomaterials for prostate cancer detection and diagnosis

Despite the significant progress in the discovery of biomarkers and the exploitation of technologies for prostate cancer (PCa) detection and diagnosis, the initial screening of these PCa-related biomarkers using current...

A Multivariate Diagnostic Model Based on Urinary EpCAM-CD9-Positive Extracellular Vesicles for Prostate Cancer Diagnosis

Introduction

Prostate cancer (PCa) is one of the most frequently diagnosed cancers and the leading cause of cancer death in males worldwide. Although prostate-specific antigen (PSA) screening has considerably improved the detection of PCa, it has also led to a dramatic increase in overdiagnosing indolent disease due to its low specificity. This study aimed to develop and validate a multivariate diagnostic model based on the urinary epithelial cell adhesion molecule (EpCAM)-CD9-positive extracellular vesicles (EVs) (uEV_EpCAM-CD9) to improve the diagnosis of PCa.

Methods

We investigated the performance of uEV_EpCAM-CD9 from urine samples of 193 participants (112 PCa patients, 55 benign prostatic hyperplasia patients, and 26 healthy donors) to diagnose PCa using our laboratory-developed chemiluminescent immunoassay. We applied machine learning to training sets and subsequently evaluated the multivariate diagnostic model based on uEV_EpCAM-CD9 in validation sets.

Results

Results showed that uEV_EpCAM-CD9 was able to distinguish PCa from controls, and a significant decrease of uEV_EpCAM-CD9 was observed after prostatectomy. We further used a training set (N = 116) and constructed an exclusive multivariate diagnostic model based on uEV_EpCAM-CD9, PSA, and other clinical parameters, which showed an enhanced diagnostic sensitivity and specificity and performed excellently to diagnose PCa [area under the curve (AUC) = 0.952, P < 0.0001]. When applied to a validation test (N = 77), the model achieved an AUC of 0.947 (P < 0.0001). Moreover, this diagnostic model also exhibited a superior diagnostic performance (AUC = 0.917, P < 0.0001) over PSA (AUC = 0.712, P = 0.0018) at the PSA gray zone.

Conclusions

The multivariate model based on uEV_EpCAM-CD9 achieved a notable diagnostic performance to diagnose PCa. In the future, this model may potentially be used to better select patients for prostate transrectal ultrasound (TRUS) biopsy.

Epigenome-Wide Association Study of Prostate Cancer in African Americans Identifies DNA Methylation Biomarkers for Aggressive Disease

DNA methylation plays important roles in prostate cancer (PCa) development and progression. African American men have higher incidence and mortality rates of PCa than other racial groups in U.S. The goal of this study was to identify differentially methylated CpG sites and genes between clinically defined aggressive and nonaggressive PCa in African Americans. We performed genome-wide DNA methylation profiling in leukocyte DNA from 280 African American PCa patients using Illumina MethylationEPIC array that contains about 860K CpG sties. There was a slight increase of overall methylation level (mean β value) with the increasing Gleason scores (GS = 6, GS = 7, GS ≥ 8, P for trend = 0.002). There were 78 differentially methylated CpG sites with P < 10-4 and 9 sites with P < 10-5 in the trend test. We also found 77 differentially methylated regions/genes (DMRs), including 10 homeobox genes and six zinc finger protein genes. A gene ontology (GO) molecular pathway enrichment analysis of these 77 DMRs found that the main enriched pathway was DNA-binding transcriptional factor activity. A few representative DMRs include HOXD8, SOX11, ZNF-471, and ZNF-577. Our study suggests that leukocyte DNA methylation may be valuable biomarkers for aggressive PCa and the identified differentially methylated genes provide biological insights into the modulation of immune response by aggressive PCa.

Evolution of Focal Therapy in Prostate Cancer: Past, Present, and Future

Organ sparing approaches for the management of localized prostate cancer were developed in part to overcome the morbidity associated with standard, whole gland treatment options. The first description of focal therapy was now over two decades ago and since that time much has changed. The evolution of patient selection, the approach to ablation, and surveillance after focal therapy have mirrored the technologic advancements in the field as well as the improved understanding of the biology of low-grade, low-risk prostate cancer. This review presents the evidence for the basis of focal therapy from the past to the present and future endeavors.

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.

Prostate Cancer Liquid Biopsy Biomarkers' Clinical Utility in Diagnosis and Prognosis

Prostate cancer (PCa) is the most common cancer in men worldwide. The current gold standard for diagnosing PCa relies on a transrectal ultrasound-guided systematic core needle biopsy indicated after detection changes in a digital rectal examination (DRE) and elevated prostate-specific antigen (PSA) level in the blood serum. PSA is a marker produced by prostate cells, not just cancer cells. Therefore, an elevated PSA level may be associated with other symptoms such as benign prostatic hyperplasia or inflammation of the prostate gland. Due to this marker's low specificity, a common problem is overdiagnosis, which leads to unnecessary biopsies and overtreatment. This is associated with various treatment complications (such as bleeding or infection) and generates unnecessary costs. Therefore, there is no doubt that the improvement of the current procedure by applying effective, sensitive and specific markers is an urgent need. Several non-invasive, cost-effective, high-accuracy liquid biopsy diagnostic biomarkers such as Progensa PCA3, MyProstateScore ExoDx, SelectMDx, PHI, 4K, Stockholm3 and ConfirmMDx have been developed in recent years. This article compares current knowledge about them and their potential application in clinical practice.

Tissue-Based Biomarkers for the Risk Stratification of Men With Clinically Localized Prostate Cancer

Risk stratification of men with clinically localized prostate cancer has historically relied on basic clinicopathologic parameters such as prostate specific antigen level, grade group, and clinical stage. However, prostate cancer often behaves in ways that cannot be accurately predicted by these parameters. Thus, recent efforts have focused on developing tissue-based genomic tests that provide greater insights into the risk of a given patient's disease. Multiple tests are now commercially available and provide additional prognostic information at various stages of the care pathway for prostate cancer. Indeed, early evidence suggests that these assays may have a significant impact on patient and physician decision-making. However, the impact of these tests on oncologic outcomes remains less clear. In this review, we highlight recent advances in the use of tissue-based biomarkers in the treatment of prostate cancer and identify the existing evidence supporting their clinical use.

A review of current clinical biomarkers for prostate cancer: towards personalised and targeted therapy

Background:

Prostate cancer is the most commonly diagnosed cancer in men and it is responsible for about 10% of all cancer mortality in Canadian men. The current ‘gold standard’ for the diagnosis of prostate cancer is a prostate biopsy and the decision on when to biopsy a patient with non-suspicious Digital Rectal Examination (DRE) result and total prostate specific antigen (tPSA) of 4–10 ng/ml can be challenging. In order to shift the treatment paradigm of prostate cancer toward more personalised and targeted therapy, there is the need for a clear system that makes its detection binary so as to decrease the rate of inaccurate detections. Therefore in recent years, there have been several investigations into the development of various biomarkers with high sensitivity and specificity for screening, early detection and personalised patient-specific targeted medicine from diagnosis to treatment of the disease.

Materials and methods:

This paper reports on nine currently available clinical biomarkers used in screening for early detection and diagnosis, to reduce the number of unnecessary biopsies, in risk assessment of aggressive disease and in monitoring treatment response of prostate cancer.

Conclusion:

Current clinical prostate cancer biomarkers have the potential for a personalised risk assessment of aggressive disease and the risk of developing distant metastatic disease and have been proven to be useful tools to guide clinicians in personalised patient-specific targeted treatment and in the shared decision making between patients and their physicians regarding prostate biopsy and treatment. Using biomarkers to select patients with a significant probability of aggressive prostate cancer would potentially avoid premature death from the disease, while at the same time would safely preclude patients who do not require unnecessary invasive intervention.

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.

How should radiologists incorporate non-imaging prostate cancer biomarkers into daily practice?

OBJECTIVE

To review the current body of evidence surrounding non-imaging biomarkers in patients with known or suspected prostate cancer.

RESULTS

Several non-imaging biomarkers have been developed and are available that aim to improve risk estimates at several clinical junctures. For patients with suspicion of prostate cancer who are considering first-time or repeat biopsy, blood- and urine-based assays can improve the prediction of harboring clinically significant disease and may reduce unnecessary biopsy. Blood- and urine-based biomarkers have been evaluated in association with prostate MRI, offering insights that might augment decision-making in the pre and post-MRI setting. Tissue-based genomic and proteomic assays have also been developed that provide independent assessments of prostate cancer aggressiveness that can complement imaging.

CONCLUSION

A growing number of non-imaging biomarkers are available to assist in clinical decision-making for men with known or suspected prostate cancer. An appreciation for the intersection of imaging and biomarkers may improve clinical care and resource utilization for men with prostate cancer.

Modern biomarkers in prostate cancer diagnosis

INTRODUCTION

The most common malignant neoplasm of the urinary tract is prostate cancer (PCa), which is a heterogeneous disease, ranging from very slowly developing and slightly benign to progressing, aggressive, metastatic and fatal, even when properly treated. Existing, imperfect diagnostic methods often lead to over-diagnosis and over-treatment of PCa. That is why new, better PCa biomarkers are being developed.

MATERIAL AND METHODS

This review summarizes the current results of the most promising and clinically used PCa biomarkers, as well as having the potential to create new diagnostic and prognostic tools, based on the Web of Science (www.apps.webofknowledge.com) and Scopus (www.scopus) databases. com).

RESULTS

Limited specificity of the prostate-specific antigen (PSA) test brings a need to develop new and better diagnostic tools. In the last few years, new approaches for providing significantly better biomarkers, an alternative to PSA, have been introduced. Modern biomarkers show improvement in being used as not only a diagnostic procedure, but also for staging, evaluating aggressiveness and managing the therapeutic process. We describe the methods recommended in the diagnosis of PCa and new PCa molecular diagnostics technologies. Individual biomarkers are used in various stages of the PCa diagnostic process, which was presented on the developed diagnostic flowchart describing the role of biomarkers in prostate cancer management.

CONCLUSIONS

Given the diverse nature of PCa, one diagnostic test will not answer all questions, so the use of several diagnostic methods will allow physicians to provide patients with better, personalized clinical advice.

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.

Prostate cancer and the role of biomarkers

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Clinical Applications of Molecular Biomarkers in Prostate Cancer

There is clinically relevant molecular heterogeneity in prostate cancer (PCa), but this biological diversity has had only a minimal impact on clinical practice. Treatment outcomes in patients with localised PCa are often highly variable, even among patients stratified to the same risk group or disease state based on standard clinical and pathological parameters. In recent years, the development of gene panels has provided valuable data on the differential expression of genes in patients with PCa. Nevertheless, there is an urgent need to identify and validate prognostic and predictive biomarkers that can be applied across clinical scenarios, ranging from localised disease to metastatic castration-resistant PCa. The availability of such tools would allow for precision medicine to finally reach PCa patients. In this review, we evaluate current data on molecular biomarkers for PCa, with an emphasis on the biomarkers and gene panels with the most robust evidence to support their application in routine clinical practice.

Can epigenetic and inflammatory biomarkers identify clinically aggressive prostate cancer?

Prostate cancer (PCa) is a highly prevalent malignancy and constitutes a major cause of cancer-related morbidity and mortality. It emerges through the acquisition of genetic and epigenetic alterations. Epigenetic modifications include DNA methylation, histone modifications and microRNA deregulation. These generate heritable transformations in the expression of genes but do not change the DNA sequence. Alterations in DNA methylation (hypo and hypermethylation) are the most characterized in PCa. They lead to genomic instability and inadequate gene expression. Major and minor-specific modifications in chromatin recasting are involved in PCa, with signs suggesting a dysfunction of enzymes modified by histones. MicroRNA deregulation also contributes to the initiation of PCa, including involvement in androgen receptor signalization and apoptosis. The influence of inflammation on prostate tumor carcinogenesis is currently much better known. Recent discoveries about microbial species resident in the urinary tract suggest that these are the initiators of chronic inflammation, promoting prostate inflammatory atrophy and eventually leading to PCa. Complete characterization of the relationship between the urinary microbiome and prostatic chronic inflammation will be crucial to develop plans for the prevention of PCa. The prevalent nature of epigenetic and inflammatory alterations may provide potential biomarkers for PCa diagnosis, treatment decisions, evaluation of prognosis and posttreatment surveillance.

The ternary complex factor protein ELK1 is an independent prognosticator of disease recurrence in prostate cancer

BACKGROUND

Both hormone-sensitive and castration- and enzalutamide-resistant prostate cancers (PCa) depend on the ternary complex factor (TCF) protein ELK1 to serve as a tethering protein for the androgen receptor (AR) to activate a critical set of growth genes. The two sites in ELK1 required for AR binding are conserved in other members of the TCF subfamily, ELK3 and ELK4. Here we examine the potential utility of the three proteins as prognosticators of disease recurrence in PCa.

METHODS

Transcriptional activity assays; Retrospective analysis of PCa recurrence using data on 501 patients in The Cancer Genome Atlas (TCGA) database; Unpaired Wilcoxon rank-sum test and multiple comparison correction using the Holm's method; Spearman's correlations; Kaplan-Meier methods; Univariable and multivariable Cox regression analyses; LASSO-based penalized Cox regression models; Time-dependent area under the receiver operating characteristic (ROC) curve.

RESULTS

ELK4 but not ELK3 was coactivated by AR similar to ELK1. Tumor expression of neither ELK3 nor ELK4 was associated with disease-free survival (DFS). ELK1 was associated with higher clinical T-stage, pathology T-stage, Gleason score, prognostic grade, and positive lymph node status. ELK1 was a negative prognosticator of DFS, independent of ELK3, ELK4, clinical T-stage, pathology T-stage, prognostic grade, lymph node status, age, and race. Inclusion of ELK1 increased the abilities of the Oncotype DX and Prolaris gene panels to predict disease recurrence, correctly predicting disease recurrence in a unique subset of patients.

CONCLUSIONS

ELK1 is a strong, independent prognosticator of disease recurrence in PCa, underscoring its unique role in PCa growth. Inclusion of ELK1 may enhance the utility of currently used prognosticators for clinical decision making in prostate cancer.

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.

Methodological challenges in constructing DNA methylation risk scores

Polygenic approaches often access more variance of complex traits than is possible by single variant approaches. For genotype data, genetic risk scores (GRS) are widely used for risk prediction as well as in association and interaction studies. Recently, interest has been growing in transferring GRS approaches to DNA methylation data (methylation risk scores, MRS), which can be used 1) as biomarkers for environmental exposures, 2) in association analyses in which single CpG sites do not achieve significance, 3) as dimension reduction approach in interaction and mediation analyses, and 4) to predict individual risks of disease or treatment success. Most GRS approaches can directly be transferred to methylation data. However, since methylation data is more sensitive to confounding, e.g. by age and tissue, it is more complex to find appropriate external weights. In this review, we will outline the adaption of current GRS approaches to methylation data and highlight occurring challenges.

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.

DNA Methylation Cancer Biomarkers: Translation to the Clinic

Carcinogenesis is accompanied by widespread DNA methylation changes within the cell. These changes are characterized by a globally hypomethylated genome with focal hypermethylation of numerous 5’-cytosine-phosphate-guanine-3’ (CpG) islands, often spanning gene promoters and first exons. Many of these epigenetic changes occur early in tumorigenesis and are highly pervasive across a tumor type. This allows DNA methylation cancer biomarkers to be suitable for early detection and also to have utility across a range of areas relevant to cancer detection and treatment. Such tests are also simple in construction, as only one or a few loci need to be targeted for good test coverage. These properties make cancer-associated DNA methylation changes very attractive for development of cancer biomarker tests with substantive clinical utility. Across the patient journey from initial detection, to treatment and then monitoring, there are several points where DNA methylation assays can inform clinical practice. Assays on surgically removed tumor tissue are useful to determine indicators of treatment resistance, prognostication of outcome, or to molecularly characterize, classify, and determine the tissue of origin of a tumor. Cancer-associated DNA methylation changes can also be detected with accuracy in the cell-free DNA present in blood, stool, urine, and other biosamples. Such tests hold great promise for the development of simple, economical, and highly specific cancer detection tests suitable for population-wide screening, with several successfully translated examples already. The ability of circulating tumor DNA liquid biopsy assays to monitor cancer in situ also allows for the ability to monitor response to therapy, to detect minimal residual disease and as an early biomarker for cancer recurrence. This review will summarize existing DNA methylation cancer biomarkers used in clinical practice across the application domains above, discuss what makes a suitable DNA methylation cancer biomarker, and identify barriers to translation. We discuss technical factors such as the analytical performance and product-market fit, factors that contribute to successful downstream investment, including geography, and how this impacts intellectual property, regulatory hurdles, and the future of the marketplace and healthcare system.

Multi-omics Biomarker Pipeline Reveals Elevated Levels of Protein-glutamine Gamma-glutamyltransferase 4 in Seminal Plasma of Prostate Cancer Patients

Seminal plasma, because of its proximity to prostate, is a promising fluid for biomarker discovery and noninvasive diagnostics. In this study, we investigated if seminal plasma proteins could increase diagnostic specificity of detecting primary prostate cancer and discriminate between high- and low-grade cancers. To select 147 most promising biomarker candidates, we combined proteins identified through five independent experimental or data mining approaches: tissue transcriptomics, seminal plasma proteomics, cell line secretomics, tissue specificity, and androgen regulation. A rigorous biomarker development pipeline based on selected reaction monitoring assays was designed to evaluate the most promising candidates. As a result, we qualified 76, and verified 19 proteins in seminal plasma of 67 negative biopsy and 152 prostate cancer patients. Verification revealed a prostate-specific, secreted and androgen-regulated protein-glutamine gamma-glutamyltransferase 4 (TGM4), which predicted prostate cancer on biopsy and outperformed age and serum Prostate-Specific Antigen (PSA). A machine-learning approach for data analysis provided improved multi-marker combinations for diagnosis and prognosis. In the independent verification set measured by an in-house immunoassay, TGM4 protein was upregulated 3.7-fold (p = 0.006) and revealed AUC = 0.66 for detecting prostate cancer on biopsy for patients with serum PSA ≥4 ng/ml and age ≥50. Very low levels of TGM4 (120 pg/ml) were detected in blood serum. Collectively, our study demonstrated rigorous evaluation of one of the remaining and not well-explored prostate-specific proteins within the medium-abundance proteome of seminal plasma. Performance of TGM4 warrants its further investigation within the distinct genomic subtypes and evaluation for the inclusion into emerging multi-biomarker panels.

Prostate biopsy: guidelines and evidence

PURPOSE OF REVIEW

To summarize the highest level evidence that was acquired within the last years, with regard to diagnosis of prostate cancer. With many secondary diagnostic tools becoming available, and not being mentioned in the guidelines, this review is meant to assist clinical decision-making in initial biopsy and rebiopsy settings.

RECENT FINDINGS

The PROMIS Trial delivered level 1b evidence about the diagnostic accuracy of prostate multiparametric MRI (mpMRI) as a triage tool for prostate biopsy. MRI-ultrasound-fusions-targeted biopsy has been evaluated and compared with the standard of care, and has been found to have a higher cancer detection rate. The different approaches to MRI-guided biopsies do not show significant differences. Urine biomarkers analysing RNA as well as genetic assays of biopsy specimen have also shown to be helpful in the decision to (re-)biopsy a patient, especially in combination with MRI.

SUMMARY

Patients and doctors alike have been trying to avoid prostate biopsies, the risks, and the side effects of potential overtreatment. Imaging and other biomarkers are used to increase diagnostic accuracy, yielding more precise information to act on. None of these secondary diagnostic tools are perfect, yet they can, and should be used if one stays aware of their limitations.

Screening of urine identifies PLA2G16 as a field defect methylation biomarker for prostate cancer detection

BACKGROUND

Prostate cancer (PC) is a multifocal disease. DNA methylation alterations are not restricted to the immediate peritumor environment, but spatially widespread in the adjacent and distant histologically normal prostate tissues. In the current study, we utilized high-throughput methylation arrays to identify epigenetic changes in the urine from men with and without cancer.

DESIGN, SETTING, AND PARTICIPANTS

DNA urine samples were enriched for methylated fragments using MBD methyl-binding antibodies and applied to high density CytoScanHD arrays. Significant loci were validated using quantitative pyrosequencing and binary logistic regression modeling applied to urine sample analyses in a training (n = 83) and validation approach (n = 84). Methylation alterations in prostate tissues using pyrosequencing at the PLA2G16 locus were examined in 38 histologically normal specimens from men with (TA, n = 26) and without (NTA, n = 12) cancer and correlated to gene expression.

RESULTS

Methylation microarrays identified 3,986 loci showing significantly altered methylation in the urine samples from patients with PC compared to those without (TA vs NTA; p<0.01). These loci were then compared against subjects with their prostates removed to exclude non-prostate cell markers yielding 196 significant regions. Multiple CpGs adjacent to PLA2G16 CpG island showed increased methylation in TA compared to NTA (p<0.01) in a large validation study of urine samples. The predictive accuracy of PLA2G16 methylation at CG2 showed the highest predictive value at 0.8 (odds ratio, 1.37; 95% confidence interval, 1.16-1.62; p<0.001). Using a probability cutoff of 0.065, the sensitivity and specificity of the multivariate model was 92% and 35%. When histologically normal prostate tissues/biopsies from patients with PC (TA) were compared to subjects without cancer, significant hypermethylation of PLA2G16 was noted (odds ratio, 1.35; 95% confidence interval, 1.07-1.71; p = 0.01).

CONCLUSION

PLA2G16 methylation defines an extensive field defect in histologically normal prostate tissue associated with PC. PLA2G16 methylation in urine and prostate tissues can detect the presence of PC.

A Rich Array of Prostate Cancer Molecular Biomarkers: Opportunities and Challenges

Prostate cancer is the most prevalent non-skin cancer in men and is the leading cause of cancer-related death. Early detection of prostate cancer is largely determined by a widely used prostate specific antigen (PSA) blood test and biopsy is performed for definitive diagnosis. Prostate cancer is asymptomatic in the early stage of the disease, comprises of diverse clinico-pathologic and progression features, and is characterized by a large subset of the indolent cancer type. Therefore, it is critical to develop an individualized approach for early detection, disease stratification (indolent vs. aggressive), and prediction of treatment response for prostate cancer. There has been remarkable progress in prostate cancer biomarker discovery, largely through advancements in genomic technologies. A rich array of prostate cancer diagnostic and prognostic tests has emerged for serum (4K, phi), urine (Progensa, T2-ERG, ExoDx, SelectMDx), and tumor tissue (ConfirmMDx, Prolaris, Oncoytype DX, Decipher). The development of these assays has created new opportunities for improving prostate cancer diagnosis, prognosis, and treatment decisions. While opening exciting opportunities, these developments also pose unique challenges in terms of selecting and incorporating these assays into the continuum of prostate cancer patient care.

GSTP1 methylation in cancer: a liquid biopsy biomarker?

The coding region of GSTP1 gene is preceded by a large CpG-rich region that is frequently affected by methylation. In many cancer types, GSTP1 is affected by hypermethylation and, as a consequence, it has a low expression. The aim of this review is to give an overview on GSTP1 methylation studies with a special focus on liquid biopsy, thus to summarize methods, results, sample types, different diseases, to have a complete information regarding this promising epigenetic biomarker. We used all the most valuable scientific search engines (PubMed, Medline, Scopus and Web of Science) searching the following keywords: GSTP1, methylation, cancer, urine, serum, plasma and blood. GSTP1 is a largely investigated tissue biomarker in several malignancies such as prostate, breast, lung and hepatocellular carcinoma with good performances especially for diagnostic purposes. As a liquid biopsy biomarker, it has been mainly investigated in prostate cancer (PCa) where it showed a high specificity but a low sensitivity; thus, it is recommended in combination with other biomarkers. Despite the large number of published papers and the promising results, GSTP1 has not yet entered the clinical practice even for PCa diagnosis. For this reason, further large and prospective studies are needed to validate this assay.

Creating a potential diagnostic for prostate cancer risk stratification (InformMDx™) by translating novel scientific discoveries concerning cAMP degrading phosphodiesterase-4D7 (PDE4D7)

Increased PSA-based screening for prostate cancer has resulted in a growing number of diagnosed cases. However, around half of these are ‘indolent’, neither metastasizing nor leading to disease specific death. Treating non-progressing tumours with invasive therapies is currently regarded as unnecessary over-treatment with patients being considered for conservative regimens, such as active surveillance (AS). However, this raises both compliance and protocol issues. Great clinical benefit could accrue from a biomarker able to predict long-term patient outcome accurately at the time of biopsy and initial diagnosis. Here we delineate the translation of a laboratory discovery through to the precision development of a clinically validated, novel prognostic biomarker assay (InformMDx™). This centres on determining transcript levels for phosphodiesterase-4D7 (PDE4D7), an enzyme that breaks down cyclic AMP, a signalling molecule intimately connected with proliferation and androgen receptor function. Quantifiable detection of PDE4D7 mRNA transcripts informs on the longitudinal outcome of post-surgical disease progression. The risk of post-surgical progression increases steeply for patients with very low ‘PDE4D7 scores’, while risk decreases markedly for those patients with very high ‘PDE4D7 scores’. Combining clinical risk variables, such as the Gleason or CAPRA (Cancer of the Prostate Risk Assessment) score, with the ‘PDE4D7 score’ further enhances the prognostic power of this personalized, precision assessment. Thus the ‘PDE4D7 score’ has the potential to define, more effectively, appropriate medical intervention/AS strategies for individual prostate cancer patients.

epiCaPture: A Urine DNA Methylation Test for Early Detection of Aggressive Prostate Cancer

Purpose

Liquid biopsies that noninvasively detect molecular correlates of aggressive prostate cancer (PCa) could be used to triage patients, reducing the burdens of unnecessary invasive prostate biopsy and enabling early detection of high-risk disease. DNA hypermethylation is among the earliest and most frequent aberrations in PCa. We investigated the accuracy of a six-gene DNA methylation panel (Epigenetic Cancer of the Prostate Test in Urine [epiCaPture]) at detecting PCa, high-grade (Gleason score greater than or equal to 8) and high-risk (D’Amico and Cancer of the Prostate Risk Assessment] PCa from urine.

Patients and Methods

Prognostic utility of epiCaPture genes was first validated in two independent prostate tissue cohorts. epiCaPture was assessed in a multicenter prospective study of 463 men undergoing prostate biopsy. epiCaPture was performed by quantitative methylation-specific polymerase chain reaction in DNA isolated from prebiopsy urine sediments and evaluated by receiver operating characteristic and decision curves (clinical benefit). The epiCaPture score was developed and validated on a two thirds training set to one third test set.

Results

Higher methylation of epiCaPture genes was significantly associated with increasing aggressiveness in PCa tissues. In urine, area under the receiver operating characteristic curve was 0.64, 0.86, and 0.83 for detecting PCa, high-grade PCa, and high-risk PCa, respectively. Decision curves revealed a net benefit across relevant threshold probabilities. Independent analysis of two epiCaPture genes in the same clinical cohort provided analytical validation. Parallel epiCaPture analysis in urine and matched biopsy cores showed added value of a liquid biopsy.

Conclusion

epiCaPture is a urine DNA methylation test for high-risk PCa. Its tumor specificity out-performs that of prostate-specific antigen (greater than 3 ng/mL). Used as an adjunct to prostate-specific antigen, epiCaPture could aid patient stratification to determine need for biopsy.

Comparing diagnostic and prognostic performance of two-gene promoter methylation panels in tissue biopsies and urines of prostate cancer patients

Background

Prostate cancer (PCa) is one of the most common cancers among men worldwide. Current screening methods for PCa display limited sensitivity and specificity, not stratifying for disease aggressiveness. Hence, development and validation of new molecular markers is needed. Aberrant gene promoter methylation is common in PCa and has shown promise as clinical biomarker. Herein, we assessed and compared the diagnostic and prognostic performance of two-gene panel promoter methylation in the same sample sets.

Methods

Promoter methylation of panel #1 (singleplex-miR-34b/c and miR-193b) and panel #2 (multiplex-APC, GSTP1, and RARβ2) was evaluated using MethyLight methodology in two different cohorts [prostate biopsy (#1) and urine sediment (#2)]. Biomarkers’ diagnostic (validity estimates) and prognostic (disease-specific survival, disease-free survival, and progression-free survival) performance was assessed.

Results

Promoter methylation levels of both panels showed the highest levels in PCa samples in both cohorts. In tissue samples, methylation panel #1 and panel #2 detected PCa with AUC of 0.9775 and 1.0, respectively, whereas in urine samples, panel #2 demonstrated superior performance although a combination of miR-34b/c, miR-193b, APC, and RARβ2 disclosed the best results (AUC = 0.9817). Furthermore, higher mir-34b/c and panel #2 methylation independently predicted for shorter DSS. Furthermore, time-dependent ROC curves showed that both miR-34b/c and GSTP1 methylation levels identify with impressive performance patients that relapse up to 15 years after diagnosis (AUC = 0.751 and AUC = 0.765, respectively).

Conclusions

We concluded that quantitative gene panel promoter methylation might be a clinically useful tool for PCa non-invasive detection and risk stratification for disease aggressiveness in both tissue biopsies and urines.

Electronic supplementary material

The online version of this article (10.1186/s13148-018-0564-2) contains supplementary material, which is available to authorized users.

Unfavorable Pathology, Tissue Biomarkers and Genomic Tests With Clinical Implications in Prostate Cancer Management

Prostate cancer management has traditionally relied upon risk stratification of patients based on Gleason score, pretreatment prostate-specific antigen and clinical tumor stage. However, these factors alone do not adequately reflect the inherent complexity and heterogeneity of prostate cancer. Accurate and individualized risk stratification at the time of diagnosis is instrumental to facilitate clinical decision-making and treatment selection tailored to each patient. The incorporation of tissue and genetic biomarkers into current prostate cancer prediction models may optimize decision-making and improve patient outcomes. In this review we discuss the clinical significance of unfavorable morphologic features such as cribriform architecture and intraductal carcinoma of the prostate, tissue biomarkers and genomic tests and assess their potential use in prostate cancer risk assessment and treatment selection.

Genomic biomarkers in prostate cancer

Prostate cancer is the most common non-cutaneous cancer among men in the United States. In the last decade there has been a rapid expansion in the field of biomarker assays for diagnosis, prognosis, and treatment prediction in prostate cancer. The evidence base for these assays is rapidly evolving. With several commercial assays available at each stage of the disease, deciding which genomic assays are appropriate for which patients can be nuanced for physicians. In an effort to help guide these decisions in clinical practice, we aim to give an update on the current status of the biomarker field of prostate cancer.

A narrative review and update on management following negative prostate biopsy

PURPOSE OF REVIEW

Prostate cancer has traditionally been diagnosed using systematic transrectal ultrasound-guided biopsy. However, given the inherent nature of sampling, a negative biopsy does not exclude clinically significant prostate cancer (csPCa), and continued controversy exists in the optimal management following initial biopsy. Numerous avenues for evaluation include multiparametric MRI (mpMRI), use of molecular biomarkers, repeat biopsy, and observation.

RECENT FINDINGS

mpMRI has shown promise in guiding further biopsy management: for individuals with identified target lesions, increased accuracy and detection using combination targeted and systematic sampling has been repeatedly demonstrated in the literature as an effective strategy. For those with negative MRIs and/or negative biomarker (blood, urinary, tissue) studies, increasing evidence has suggested that these individuals may be able to avoid biopsy altogether, albeit at a small risk of missing csPCa. Observation should be based on an individual's risk of csPCa versus their competing health risks, and saturation biopsy reserved for rare cases with high clinical suspicion.

SUMMARY

Management following an initial negative prostate biopsy requires careful discussion with the patient, their risk tolerance, and threshold for intervention. Although subject to availability, mpMRI and molecular biomarkers may better risk stratify patients, identify target lesions, and in certain cases, spare biopsy altogether.

Evaluation of an Epigenetic Assay for Predicting Repeat Prostate Biopsy Outcome in African American Men

OBJECTIVE

To evaluate an epigenetic assay performed on tissue from negative prostate biopsies in a group of African American (AA) men undergoing repeat biopsy, and to compare accuracy for predicting repeat biopsy outcome to prior studies conducted in predominantly Caucasian populations.

MATERIALS AND METHODS

The study population consisted of 211 AA men from 7 urology centers across the United States; all of whom were undergoing 12-core transrectal ultrasound-guided repeat biopsy within 30 months from a negative index biopsy. All biopsy cores from the negative index biopsy were profiled for the epigenetic biomarkers GSTP1, APC, and RASSF1 using ConfirmMDx for Prostate Cancer (MDxHealth, Irvine, CA).

RESULTS

Upon repeat biopsy, 130 of 211 subjects (62%) had no prostate cancer (PCa) detected and 81 of 211 (38%) were diagnosed with PCa. Of the subjects with PCa, 54 (67%) were diagnosed with Gleason score (GS) ≤6 PCa and 27 (33%) with GS ≥7 disease. For detection of PCa at repeat biopsy, ConfirmMDx sensitivity was 74.1% and specificity was 60.0%, equivalent to prior studies (P = .235 and .697, respectively). For detection of GS ≥7 PCa, sensitivity was 78% and specificity was 53%. The negative predictive values for detection of all PCa and GS ≥7 PCa were 78.8% and 94.2%, respectively.

CONCLUSION

In this group of AA men, we successfully validated an epigenetic assay to assess the need for repeat biopsy. Results were consistent with previous studies from predominantly Caucasian populations. Therefore, the ConfirmMDx assay is a useful tool for risk stratification of AA men who had an initial negative biopsy.

Biomarker potential of ST6GALNAC3 and ZNF660 promoter hypermethylation in prostate cancer tissue and liquid biopsies

Current diagnostic and prognostic tools for prostate cancer (PC) are suboptimal, leading to overdiagnosis and overtreatment. Aberrant promoter hypermethylation of specific genes has been suggested as novel candidate biomarkers for PC that may improve diagnosis and prognosis. We here analyzed ST6GALNAC3 and ZNF660 promoter methylation in prostate tissues, and ST6GALNAC3,ZNF660,CCDC181, and HAPLN3 promoter methylation in liquid biopsies. First, using four independent patient sample sets, including a total of 110 nonmalignant (NM) and 705 PC tissue samples, analyzed by methylation‐specific qPCR or methylation array, we found that hypermethylation of ST6GALNAC3 and ZNF660 was highly cancer‐specific with areas under the curve (AUC) of receiver operating characteristic (ROC) curve analysis of 0.917–0.995 and 0.846–0.903, respectively. Furthermore, ZNF660 hypermethylation was significantly associated with biochemical recurrence in two radical prostatectomy (RP) cohorts of 158 and 392 patients and remained significant also in the subsets of patients with Gleason score ≤7 (univariate Cox regression and log‐rank tests, P < 0.05), suggesting that ZNF660 methylation analysis can potentially help to stratify low‐/intermediate‐grade PCs into indolent vs. more aggressive subtypes. Notably, ZNF660 hypermethylation was also significantly associated with poor overall and PC‐specific survival in the RP cohort (n = 158) with long clinical follow‐up available. Moreover, as proof of principle, we successfully detected highly PC‐specific hypermethylated circulating tumor DNA (ctDNA) for ST6GALNAC3,ZNF660,HAPLN3, and CCDC181 in liquid biopsies (serum) from 27 patients with PC vs. 10 patients with BPH, using droplet digital methylation‐specific PCR analysis. Finally, we generated a three‐gene (ST6GALNAC3/CCDC181/HAPLN3) ctDNA hypermethylation model, which detected PC with 100% specificity and 67% sensitivity. In conclusion, we here for the first time demonstrate diagnostic biomarker potential of ST6GALNAC3 and ZNF660 methylation, as well as prognostic biomarker potential of ZNF660. Furthermore, we show that hypermethylation of four genes can be detected in ctDNA in liquid biopsies (serum) from patients with PC.

New biomarkers for diagnosis and prognosis of localized prostate cancer

The diagnostics and management of localized prostate cancer is complicated because of cancer heterogeneity and differentiated progression in various subgroups of patients. As a prostate cancer biomarker, FDA-approved detection assay for serum prostate specific antigen (PSA) and its derivatives are not potent enough to diagnose prostate cancer, especially high-grade disease (Gleason ≥7). To date, a collection of new biomarkers was developed. Some of these markers are superior for primary screening while others are particularly helpful for cancer risk stratification, detection of high-grade cancer, and prediction of adverse events. Two of those markers such as proPSA (a part of the Prostate Health Index (PHI)) and prostate specific antigen 3 (PCA3) (a part of the PCA3 Progensa test) were recently approved by FDA for clinical use. Other markers are not PDA-approved yet but are available from Clinical Laboratory Improvement Amendment (CLIA)-certified clinical laboratories. In this review, we characterize diagnostic performance of these markers and their diagnostic and prognostic utility for prostate cancer.