Urine TMPRSS2:ERG fusion transcript stratifies prostate cancer risk in men with elevated serum PSA

Disrupting prostate cancer research: Challenge accepted; report from the 2023 Coffey-Holden Prostate Cancer Academy Meeting

INTRODUCTION

The 2023 Coffey-Holden Prostate Cancer Academy (CHPCA) Meeting, themed "Disrupting Prostate Cancer Research: Challenge Accepted," was convened at the University of California, Los Angeles, Luskin Conference Center, in Los Angeles, CA, from June 22 to 25, 2023.

METHODS

The 2023 marked the 10th Annual CHPCA Meeting, a discussion-oriented scientific think-tank conference convened annually by the Prostate Cancer Foundation, which centers on innovative and emerging research topics deemed pivotal for advancing critical unmet needs in prostate cancer research and clinical care. The 2023 CHPCA Meeting was attended by 81 academic investigators and included 40 talks across 8 sessions.

RESULTS

The central topic areas covered at the meeting included: targeting transcription factor neo-enhancesomes in cancer, AR as a pro-differentiation and oncogenic transcription factor, why few are cured with androgen deprivation therapy and how to change dogma to cure metastatic prostate cancer without castration, reducing prostate cancer morbidity and mortality with genetics, opportunities for radiation to enhance therapeutic benefit in oligometastatic prostate cancer, novel immunotherapeutic approaches, and the new era of artificial intelligence-driven precision medicine.

DISCUSSION

This article provides an overview of the scientific presentations delivered at the 2023 CHPCA Meeting, such that this knowledge can help in facilitating the advancement of prostate cancer research worldwide.

Established and emerging liquid biomarkers for prostate cancer detection: A review

Prostate cancer remains one of the most frequently diagnosed cancers among men in the world today. Since its introduction in 1987 and FDA approval in 1994, prostate specific antigen (PSA) has reduced prostate cancer specific mortality considerably. However, the positive and negative predictive value of PSA is less than ideal and can lead to the over-detection of clinically insignificant prostate cancer. In the search for better screening measures to identify this cohort, liquid biomarkers for prostate cancer have emerged. In this review we will explore the commonly used urine and blood based prostate cancer liquid biomarkers. We detail the mechanism of each test and the validation studies that underscore their efficacy. Additionally, we will examine each test's effect on shared decision making as well as their cost efficacy in clinical practice.

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

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

Prostate cancer: Novel genetic and immunologic biomarkers

Prostate cancer (PCa) is considered one of the most prevalent male malignancies worldwide with a global burden estimated to increase over the next two decades. Due to significant mortality and debilitation of survival, early diagnosis has been described as key. Unfortunately, current diagnostic serum-based strategies have low specificity and sensitivity. Histologic examination is invasive and not useful for treatment and monitoring purposes. Hence, a plethora of studies have been conducted to identify and validate an efficient noninvasive approach in the diagnosis, staging, and prognosis of PCa. These investigations may be categorized as genetic (non-coding biomarkers and gene markers), immunologic (immune cells, interleukins, cytokines, antibodies, and auto-antibodies), and heterogenous (PSA-related markers, PHI-related indices, and urinary biomarkers) subgroups. This review examines current approaches and potential strategies using biomarker panels in PCa.

Acquired copy number variation in prostate tumours: a review of common somatic copy number alterations, how they are formed and their clinical utility

Prostate cancer is one of the most commonly diagnosed cancers in men and unfortunately, disease will progress in up to a third of patients despite primary treatment. Currently, there is a significant lack of prognostic tests that accurately predict disease course; however, the acquisition of somatic chromosomal variation in the form of DNA copy number variants may help understand disease progression. Notably, studies have found that a higher burden of somatic copy number alterations (SCNA) correlates with more aggressive disease, recurrence after surgery and metastasis. Here we will review the literature surrounding SCNA formation, including the roles of key tumour suppressors and oncogenes (PTEN, BRCA2, NKX3.1, ERG and AR), and their potential to inform diagnostic and prognostic clinical testing to improve predictive value. Ultimately, SCNAs, or inherited germline alterations that predispose to SCNAs, could have significant clinical utility in diagnostic and prognostic tests, in addition to guiding therapeutic selection.

Decoding Oncofusions: Unveiling Mechanisms, Clinical Impact, and Prospects for Personalized Cancer Therapies

Cancer-associated gene fusions, also known as oncofusions, have emerged as influential drivers of oncogenesis across a diverse range of cancer types. These genetic events occur via chromosomal translocations, deletions, and inversions, leading to the fusion of previously separate genes. Due to the drastic nature of these mutations, they often result in profound alterations of cellular behavior. The identification of oncofusions has revolutionized cancer research, with advancements in sequencing technologies facilitating the discovery of novel fusion events at an accelerated pace. Oncofusions exert their effects through the manipulation of critical cellular signaling pathways that regulate processes such as proliferation, differentiation, and survival. Extensive investigations have been conducted to understand the roles of oncofusions in solid tumors, leukemias, and lymphomas. Large-scale initiatives, including the Cancer Genome Atlas, have played a pivotal role in unraveling the landscape of oncofusions by characterizing a vast number of cancer samples across different tumor types. While validating the functional relevance of oncofusions remains a challenge, even non-driver mutations can hold significance in cancer treatment. Oncofusions have demonstrated potential value in the context of immunotherapy through the production of neoantigens. Their clinical importance has been observed in both treatment and diagnostic settings, with specific fusion events serving as therapeutic targets or diagnostic markers. However, despite the progress made, there is still considerable untapped potential within the field of oncofusions. Further research and validation efforts are necessary to understand their effects on a functional basis and to exploit the new targeted treatment avenues offered by oncofusions. Through further functional and clinical studies, oncofusions will enable the advancement of precision medicine and the drive towards more effective and specific treatments for cancer patients.

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.

Engineering the MoS2 /MXene Heterostructure for Precise and Noninvasive Diagnosis of Prostate Cancer with Clinical Specimens

High-throughput metabolic fingerprinting has been deemed one of the most promising strategies for addressing the high false positive rate of prostate cancer (PCa) diagnosis in the prostate-specific antigen (PSA) gray zone. However, the current metabolic fingerprinting remains challenging in achieving high-precision metabolite detection in complex biological samples (e.g., serum and urine). Herein, a novel self-assembly MoS₂ /MXene heterostructure nanocomposite with a tailored doping ratio of 10% is presented as a matrix for laser desorption ionization mass spectrometry analysis in clinical biosamples. Notably, owing to the two-dimensional architecture and doping effect, MoS₂ /MXene demonstrates favorable laser desorption ionization performance with low adsorption energy, which is evidenced by efficient urinary metabolic fingerprinting with an enhanced area under curve (AUC) diagnosis capability of 0.959 relative to that of serum metabolic fingerprinting (AUC = 0.902) for the diagnosis of PCa in the PSA gray zone. Thus, this MoS₂ /MXene heterostructure is anticipated to offer a novel strategy to precisely and noninvasively diagnose PCa in the PSA gray zone.

Convolutional Neural Network Quantification of Gleason Pattern 4 and Association with Biochemical Recurrence in Intermediate Grade Prostate Tumors

Differential classification of prostate cancer (CaP) grade group (GG) 2 and 3 tumors remains challenging, likely due to the subjective quantification of percentage of Gleason pattern 4 (%GP4). Artificial intelligence assessment of %GP4 may improve its accuracy and reproducibility and provide information for prognosis prediction. To investigate this potential, a convolutional neural network (CNN) model was trained to objectively identify and quantify Gleason pattern (GP) 3 and 4 areas, estimate %GP4, and assess whether CNN-assessed %GP4 is associated with biochemical recurrence (BCR) risk in intermediate risk GG 2 and 3 tumors. The study was conducted in a radical prostatectomy cohort (1999-2012) of African American men from the Henry Ford Health System (Detroit, Michigan). A CNN model that could discriminate four tissue types (stroma, benign glands, GP3 glands, and GP4 glands) was developed using histopathologic images containing GG 1 (n=45) and 4 (n=20) tumor foci. The CNN model was applied to GG 2 (n=153) and 3 (n=62) for %GP4 estimation, and Cox proportional hazard modeling was used to assess the association of %GP4 and BCR, accounting for other clinicopathologic features including GG. The CNN model achieved an overall accuracy of 86% in distinguishing the four tissue types. Further, CNN-assessed %GP4 was significantly higher in GG 3 compared with GG 2 tumors (p=7.2*10^-11). %GP4 was associated with an increased risk of BCR (adjusted HR=1.09 per 10% increase in %GP4, p=0.010) in GG 2 and 3 tumors. Within GG 2 tumors specifically, %GP4 was more strongly associated with BCR (adjusted HR=1.12, p=0.006). Our findings demonstrate the feasibility of CNN-assessed %GP4 estimation, which is associated with BCR risk. This objective approach could be added to the standard pathological assessment for patients with GG 2 and 3 tumors and act as a surrogate for specialist genitourinary pathologist evaluation when such consultation is not available.

Prevalence of genotoxic bacteria in men undergoing biopsy for prostate cancer

BACKGROUND

New evidence suggests that bacteria-produced DNA toxins may have a role in the development or progression of prostate cancer. To determine the prevalence of these genes in a noninfection (i.e., colonized) state, we screened urine specimens in men before undergoing a biopsy for prostate cancer detection.

METHODS

We developed a multiplex polymerase chain reaction using three of the most described bacterial genotoxin gene primers: Colibactin (polyketone synthase [pks] gene island: clbN and clbB), cytotoxic necrotizing factor (cnf1) toxin, and cytolethal distending toxin B (cdtB) represented gene islands. After calibration on Escherichia coli samples of known genotypes, we used a training and validation cohort. We performed multiplex testing on a training cohort of previously collected urine from 45 men undergoing prostate biopsy. For the validation cohort, we utilized baseline urine samples from a previous randomized clinical trial (n = 263) with known prostate cancer outcomes.

RESULTS

The prevalence of four common bacterial genotoxin genes detected in the urine before prostate biopsy for prostate cancer is 8% (25/311). The prevalence of pks island (clbN and clbB), cnf1, and cdt toxin genes are 6.1%, 2.4%, and 1.7%, respectively. We found no association between urinary genotoxins and prostate cancer (p = 0.83). We did identify a higher proportion of low-grade cancer (92% vs. 44%) in those men positive for urinary genotoxin and higher-grade cancer in those genotoxin negative (8% vs. 56%, p = 0.001).

CONCLUSIONS

The prevalence of urinary genotoxins is low and does not correspond to a prostate cancer diagnosis. The urine was taken at one point in time and does not rule out the possibility of previous exposure.

Detection of rare prostate cancer cells in human urine offers prospect of non-invasive diagnosis

Two molecular cytology approaches, (i) time-gated immunoluminescence assay (TGiA) and (ii) Raman-active immunolabeling assay (RiA), have been developed to detect prostate cancer (PCa) cells in urine from five prostate cancer patients. For TGiA, PCa cells stained by a biocompatible europium chelate antibody-conjugated probe were quantitated by automated time-gated microscopy (OSAM). For RiA, PCa cells labeled by antibody-conjugated Raman probe were detected by Raman spectrometer. TGiA and RiA were first optimized by the detection of PCa cultured cells (DU145) spiked into control urine, with TGiA-OSAM showing single-cell PCa detection sensitivity, while RiA had a limit of detection of 4-10 cells/mL. Blinded analysis of each patient urine sample, using MIL-38 antibody specific for PCa cells, was performed using both assays in parallel with control urine. Both assays detected very low abundance PCa cells in patient urine (3-20 PCa cells per mL by TGiA, 4-13 cells/mL by RiA). The normalized mean of the detected PCa cells per 1 ml of urine was plotted against the clinical data including prostate specific antigen (PSA) level and Clinical Risk Assessment for each patient. Both cell detection assays showed correlation with PSA in the high risk patients but aligned with the Clinical Assessment rather than with PSA levels of the low/intermediate risk patients. Despite the limited available urine samples of PCa patients, the data presented in this proof-of-principle work is promising for the development of highly sensitive diagnostic urine tests for PCa.

Identification of candidate hub genes correlated with the pathogenesis, diagnosis, and prognosis of prostate cancer by integrated bioinformatics analysis

Background

Prostate cancer (PCa) has the second highest morbidity and mortality rates in men. Concurrently, novel diagnostic and prognostic biomarkers of PCa remain crucial.

Methods

This study utilized integrated bioinformatics method to identify and validate the potential hub genes with high diagnostic and prognostic value for PCa.

Results

Four Gene Expression Omnibus (GEO) datasets including 123 PCa samples and 76 normal samples were screened and a total of 368 differentially expressed genes (DEGs), including 120 up-regulated DEGs and 248 down-regulated DEGs, were identified. Subsequent Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that the DEGs were majorly enriched in focal adhesion, chemical carcinogenesis, drug metabolism, and cytochrome P450 pathways. Then, 11 hub genes were identified from the protein-protein interaction (PPI) network of the DEGs; 7 of the 11 genes showed the ability of distinguishing PCa from normal prostate based on receiver operating characteristic (ROC) curve analysis. And 5 of the 11 genes were correlated with clinical attributes. Lower CAV1, KRT5, SNAI2 and MYLK expression level were associated with higer Gleason score, advanced pathological T stage and N stage. Lower KRT5 and MYLK expression level were significantly correlated with poor disease-free survival, and lower KRT5 and PTGS2 expression level were significantly related to biochemical recurrence (BCR) status of PCa patients.

Conclusions

In conclusion, CAV1, KRT5, SNAI2, and MYLK show potential clinical diagnostic and prognostic value and could be used as novel candidate biomarkers and therapeutic targets for PCa.

Integrated analysis of mRNA-single nucleotide polymorphism-microRNA interaction network to identify biomarkers associated with prostate cancer

Background: Prostate cancer is one of the most common malignancies among men worldwide currently. However, specific mechanisms of prostate cancer were still not fully understood due to lack of integrated molecular analyses. We performed this study to establish an mRNA-single nucleotide polymorphism (SNP)-microRNA (miRNA) interaction network by comprehensive bioinformatics analysis, and search for novel biomarkers for prostate cancer.

Materials and methods: mRNA, miRNA, and SNP data were acquired from Gene Expression Omnibus (GEO) database. Differential expression analysis was performed to identify differentially expressed genes (DEGs) and miRNAs (DEMs). Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses, protein-protein interaction (PPI) analysis and expression quantitative trait loci (eQTL) analysis of DEGs were conducted. SNPs related to DEMs (miRSNPs) were downloaded from the open-source website MirSNP and PolymiRTS 3.0. TargetScan and miRDB databases were used for the target mRNA prediction of miRNA. The mRNA-SNP-miRNA interaction network was then constructed and visualized by Cytoscape 3.9.0. Selected key biomarkers were further validated using the Cancer Genome Atlas (TCGA) database. A nomogram model was constructed to predict the risk of prostate cancer.

Results: In our study, 266 DEGs and 11 DEMs were identified. KEGG pathway analysis showed that DEGs were strikingly enriched in focal adhesion and PI3K-Akt signaling pathway. A total of 60 mRNA-SNP-miRNAs trios were identified to establish the mRNA-SNP-miRNA interaction network. Seven mRNAs in mRNA-SNP-miRNA network were consistent with the predicted target mRNAs of miRNA. These results were largely validated by the TCGA database analysis. A nomogram was constructed that contained four variables (ITGB8, hsa-miR-21, hsa-miR-30b and prostate-specific antigen (PSA) value) for predicting the risk of prostate cancer.

Conclusion: Our study established the mRNA-SNP-miRNA interaction network in prostate cancer. The interaction network showed that hsa-miR-21, hsa-miR-30b, and ITGB8 may be utilized as new biomarkers for prostate cancer.

Past, Current, and Future Strategies to Target ERG Fusion-Positive Prostate Cancer

Simple Summary

In addition to its role in development and in the vascular and hematopoietic systems, ERG plays a central role in prostate cancer. Approximately 40–50% of prostate cancer cases are characterized by ERG gene fusions, which lead to ERG overexpression. Importantly, inhibition of ERG activity in prostate cancer cells decreases their viability. Therefore, inhibiting ERG might represent an important step to improve treatment efficacy for patients with ERG-positive prostate tumors. Here, we summarize the attempts made over the past years to repress ERG activity, the current use of ERG fusion detection and the strategies that might be utilized in the future to treat ERG fusion-positive tumors.

Abstract

The ETS family member ERG is a transcription factor with physiological roles during development and in the vascular and hematopoietic systems. ERG oncogenic activity characterizes several malignancies, including Ewing’s sarcoma, leukemia and prostate cancer (PCa). In PCa, ERG rearrangements with androgen-regulated genes—mostly TMPRSS2—characterize a large subset of patients across disease progression and result in androgen receptor (AR)-mediated overexpression of ERG in the prostate cells. Importantly, PCa cells overexpressing ERG are dependent on ERG activity for survival, further highlighting its therapeutic potential. Here, we review the current understanding of the role of ERG and its partners in PCa. We discuss the strategies developed in recent years to inhibit ERG activity, the current therapeutic utility of ERG fusion detection in PCa patients, and the possible future approaches to target ERG fusion-positive tumors.

Exosomes as A Next-Generation Diagnostic and Therapeutic Tool in Prostate Cancer

Extracellular vesicles (EVs) have brought great momentum to the non-invasive liquid biopsy procedure for the detection, characterization, and monitoring of cancer. Despite the common use of PSA (prostate-specific antigen) as a biomarker for prostate cancer, there is an unmet need for a more specific diagnostic tool to detect tumor progression and recurrence. Exosomes, which are EVs that are released from all cells, play a large role in physiology and pathology, including cancer. They are involved in intercellular communication, immune function, and they are present in every bodily fluid studied—making them an excellent window into how cells are operating. With liquid biopsy, EVs can be isolated and analyzed, enabling an insight into a potential therapeutic value, serving as a vehicle for drugs or nucleic acids that have anti-neoplastic effects. The current application of advanced technology also points to higher-sensitivity detection methods that are minimally invasive. In this review, we discuss the current understanding of the significance of exosomes in prostate cancer and the potential diagnostic value of these EVs in disease progression.

Biomarkers for detection of clinically significant prostate cancer: contemporary clinical data and future directions

Use of serum prostate-specific antigen (PSA) testing for early detection of prostate cancer appears to reduce cancer-specific mortality. Due to the limited specificity of PSA for clinically significant [Grade Group (GG) ≥2] cancer, however, screening carries substantial risks, including frequent unnecessary prostate biopsies and overdetection of non-aggressive cancers. To that end, serum and urine biomarkers with improved specificity for GG ≥2 cancer have been proposed for clinical use following PSA. In the current article, we present clinical validation data for five such biomarkers: PHI, 4Kscore, SelectMDx, ExoDx, and MPS. For all studies, we specify the study population (overall biopsy referral vs. pre-specified PSA ranges), previous biopsy status (biopsy-naïve vs. previous negative biopsy), and the proportion of subjects diagnosed with GG ≥2 cancer. Outcomes include test performance characteristics: sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV). Published data were used to compute the number of unnecessary biopsies avoided and number of GG ≥2 cancers missed if the biomarker had been used clinically to select for prostate biopsy. The evidence review is preceded by a primer on these and other clinically-relevant summary statistics.

Biomarker in Active Surveillance for Prostate Cancer: A Systematic Review

Active surveillance (AS) in prostate cancer (PCa) represents a curative alternative for men with localised low-risk PCa. Continuous improvement of AS patient's selection and surveillance modalities aims at reducing misclassification, simplifying modalities of surveillance and decreasing need for invasive procedures such repeated biopsies. Biomarkers represent interesting tools to evaluate PCa diagnosis and prognosis, of which many are readily available or under evaluation. The aim of this review is to investigate the biomarker performance for AS selection and patient outcome prediction. Blood, urinary and tissue biomarkers were studied and a brief description of use was proposed along with a summary of major findings. Biomarkers represent promising tools which could be part of a more tailored risk AS strategy aiming to offer personalized medicine and to individualize the treatment and monitoring of each patient. The usefulness of biomarkers has mainly been suggested for AS selection, whereas few studies have investigated their role during the monitoring phase. Randomized prospective studies dealing with imaging are needed as well as larger prospective studies with long-term follow-up and strong oncologic endpoints.

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.

Association of Urinary MyProstateScore, Age, and Prostate Volume in a Longitudinal Cohort of Healthy Men: Long-term Findings from the Olmsted County Study

Background

Serum prostate-specific antigen (PSA), used in prostate cancer screening, is nonspecific for cancer and is affected by age and prostate volume. More specific biomarkers could be more accurate for early detection of prostate cancer and reduce unnecessary prostate biopsies.

Objective

To evaluate the association of age and prostate volume with urinary MyProstateScore (MPS) in a screened, longitudinal cohort without evidence of prostate cancer.

Design setting and participants

The Olmsted County Study included men aged 40-79 yr who underwent biennial prostate cancer screening. PSA ≥4.0 ng/ml or abnormal rectal examination triggered prostate biopsy, and patients with cancer were excluded. The remaining men submitted urinary specimens for PCA3 and TMPRSS2:ERG testing.

Outcome measurements and statistical analysis

MPS was calculated using the validated, locked model for grade group ≥2 cancer that includes serum PSA, urinary PCA3, and urinary TMPRSS2:ERG. The associations of age and volume with biomarkers were assessed in multivariable regression models. The t statistic was used to quantify the strength of associations independent of the unit of measurement, and R ² values were used to estimate the proportion of biomarker variance explained by each factor.

Results and limitations

The study included 314 screened men without evidence of cancer. In multivariable models including age and volume, PCA3 score was significantly associated with age (t = 7.51; p < 0.001), while T2:ERG score was not associated with age or volume. MPS was significantly associated with both age (t = 7.45; p < 0.001) and volume (t = 3.56; p < 0.001), but accounting for age alone explained the variability observed (R ² = 0.29) in a similar way to the model including age and volume (R ² = 0.31). The variability of PCA3, T2:ERG, and MPS was less dependent on age and volume than the variability for PSA (R ² = 0.45).

Conclusions

In a cohort of longitudinally screened men without evidence of cancer, we found that MPS demonstrated less variability with noncancer factors (age, prostate volume) than PSA did. These findings support the biology of these markers as more cancer-specific than PSA and highlight their promise in reducing the morbidity associated with PSA-based screening.

Patient summary

In a group of men with no evidence of prostate cancer, we found that each of three urine-based markers of cancer-PCA3, T2:ERG, and the commercially available MyProstateScore test-showed less variability with noncancer factors (age and prostate volume) than serum PSA (prostate-specific antigen) did. These findings support their proposed use as noninvasive markers of prostate cancer that could improve the accuracy of early detection.

Current State of Personalized Genitourinary Cancer Radiotherapy in the Era of Precision Medicine

Radiation therapy plays a crucial role for the management of genitourinary malignancies, with technological advancements that have led to improvements in outcomes and decrease in treatment toxicities. However, better risk-stratification and identification of patients for appropriate treatments is necessary. Recent advancements in imaging and novel genomic techniques can provide additional individualized tumor and patient information to further inform and guide treatment decisions for genitourinary cancer patients. In addition, the development and use of targeted molecular therapies based on tumor biology can result in individualized treatment recommendations. In this review, we discuss the advances in precision oncology techniques along with current applications for personalized genitourinary cancer management. We also highlight the opportunities and challenges when applying precision medicine principles to the field of radiation oncology. The identification, development and validation of biomarkers has the potential to personalize radiation therapy for genitourinary malignancies so that we may improve treatment outcomes, decrease radiation-specific toxicities, and lead to better long-term quality of life for GU cancer survivors.

High-Throughput and Automated Acoustic Trapping of Extracellular Vesicles to Identify microRNAs With Diagnostic Potential for Prostate Cancer

Molecular profiling of extracellular vesicles (EVs) offers novel opportunities for diagnostic applications, but the current major obstacle for clinical translation is the lack of efficient, robust, and reproducible isolation methods. To bridge that gap, we developed a microfluidic, non-contact, and low-input volume compatible acoustic trapping technology for EV isolation that enabled downstream small RNA sequencing. In the current study, we have further automated the acoustic microfluidics-based EV enrichment technique that enables us to serially process 32 clinical samples per run. We utilized the system to enrich EVs from urine collected as the first morning void from 207 men referred to 10-core prostate biopsy performed the same day. Using automated acoustic trapping, we successfully enriched EVs from 199/207 samples (96%). After RNA extraction, size selection, and library preparation, a total of 173/199 samples (87%) provided sufficient materials for next-generation sequencing that generated an average of 2 × 10⁶ reads per sample mapping to the human reference genome. The predominant RNA species identified were fragments of long RNAs such as protein coding and retained introns, whereas small RNAs such as microRNAs (miRNA) accounted for less than 1% of the reads suggesting that partially degraded long RNAs out-competed miRNAs during sequencing. We found that the expression of six miRNAs was significantly different (P_adj < 0.05) in EVs isolated from patients found to have high grade prostate cancer [ISUP 2005 Grade Group (GG) 4 or higher] compared to those with GG3 or lower, including those with no evidence of prostate cancer at biopsy. These included miR-23b-3p, miR-27a-3p, and miR-27b-3p showing higher expression in patients with GG4 or high grade prostate cancer, whereas miR-1-3p, miR-10a-5p, and miR-423-3p had lower expression in the GG4 PCa cases. Cross referencing our differentially expressed miRNAs to two large prostate cancer datasets revealed that the putative tumor suppressors miR-1, miR-23b, and miR-27a are consistently deregulated in prostate cancer. Taken together, this is the first time that our automated microfluidic EV enrichment technique has been found to be capable of enriching EVs on a large scale from 900 μl of urine for small RNA sequencing in a robust and disease discriminatory manner.

Gene fusion neoantigens: Emerging targets for cancer immunotherapy

Tumor neoantigens play an important role in current cancer immunotherapies. The most commonly studied class of tumor neoantigens contains those derived from single-nucleotide variants (SNVs) and insertions or deletions (Indels). However, gene fusions are also ideal sources of tumor neoantigens, as they can form new open reading frames (ORFs). Compared with SNV and Indel (SNV&Indel) neoantigens, fusion gene neoantigens tend to be more immunogenic, have more targets per mutation, and are more broadly shared across different cancer types. As a result, they are an important class of tumor neoantigens and emerging targets for cancer immunotherapies, with uses as prognostic biomarkers of immune checkpoint blockade (ICB) and in the development of tumor vaccines, adoptive cell therapies and tumor immune microenvironment modulation. In this review, we introduce the chromosomal basis and characteristics of gene fusions. Then, we summarize the predictive tools, mutation burden and immunogenicity of gene fusion neoantigens. Further, we discuss applications and future improvements of gene fusion neoantigens with respect to current cancer immunotherapies and novel developments in cancer treatment.

Prevalence and clinical application of TMPRSS2-ERG fusion in Asian prostate cancer patients: a large-sample study in Chinese people and a systematic review

Fusion between the transmembrane protease serine 2 and v-ets erythroblastosis virus E26 oncogene homolog (TMPRSS2-ERG fusion) is a common genetic alteration in prostate cancer among Western populations and has been suggested as playing a role in tumorigenesis and progression of prostate cancer. However, the prevalence of TMPRSS2-ERG fusion differs among different ethnic groups, and contradictory results have been reported in Asian patients. We aim to evaluate the prevalence and significance of TMPRSS2-ERG fusion as a molecular subtyping and prognosis indicator of prostate cancer in Asians. We identified the fusion status in 669 samples from prostate biopsy and radical prostatectomy by fluorescence in situ hybridization and/or immunohistochemistry in China. We examined the association of TMPRSS2-ERG fusion with clinicopathological characteristics and biochemical recurrence by Chi-square test and Kaplan–Meier analysis. Finally, a systematic review was performed to investigate the positive rate of the fusion in Asian prostate cancer patients. McNemar's test was employed to compare the positive rates of TMPRSS2-ERG fusion detected using different methods. The positive rates of TMPRSS2-ERG fusion were 16% in our samples and 27% in Asian patients. In our samples, 9.4% and 19.3% of cases were recognized as fusion positive by fluorescence in situ hybridization and immunohistochemistry, respectively. No significant association between the fusion and clinical parameters was observed. TMPRSS2-ERG fusion is not a frequent genomic alteration among Asian prostate cancer patients and has limited significance in clinical practices in China. Besides ethnic difference, detection methods potentially influence the results showing a positive rate of TMPRSS2-ERG fusion.

Clinical utility of current biomarkers for prostate cancer detection

Although prostate-specific antigen (PSA) remains the most used test to detect prostate cancer (PCa), the limited specificity and an elevated rate of overdiagnosis are the main problems associated with PSA testing. Over the last three decades, a large body of evidence has indicated that PSA screening methods for PCa are problematic, although PSA screening significantly reduces PCa-specific mortality. A number of novel biomarkers have been introduced to overcome these limitations of PSA in the clinical setting. These biomarkers have demonstrated an increased ability to select patients for biopsy and identify men at risk for clinically significant PCa. Although a number of assays require further validation, initial data are promising. Forthcoming results will ultimately determine the clinical utility and commercial availability of these assays. Extensive efforts have recently been made to identify and commercialize novel PCa biomarkers for more effective detection of PCa, either alone or in combination with currently available clinical tools. This review highlights the role of existing and promising serum and urinary biomarkers for the detection and prognostication of PCa before prostate biopsy.

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.

Prostate Cancer Biomarker Development: National Cancer Institute's Early Detection Research Network Prostate Cancer Collaborative Group Review

Prostate cancer remains the most common non-skin cancer and second leading cause of death among men in the United States. Although progress has been made in diagnosis and risk assessment, many clinical questions remain regarding early identification of prostate cancer and management. The early detection of aggressive disease continues to provide high curative rates if diagnosed in a localized state. Unfortunately, prostate cancer displays significant heterogeneity within the prostate organ and between individual patients making detection and treatment strategies complex. Although prostate cancer is common among men, the majority will not die from prostate cancer, introducing the issue of overtreatment as a major concern in clinical management of the disease. The focus of the future is to identify those at highest risk for aggressive prostate cancer and to develop prevention and screening strategies, as well as discerning the difference in malignant potential of diagnosed tumors. The Prostate Cancer Research Group of the National Cancer Institute's Early Detection Research Network has contributed to the progress in addressing these concerns. This summary is an overview of the activities of the group.See all articles in this CEBP Focus section, "NCI Early Detection Research Network: Making Cancer Detection Possible."

Urinary glycoproteins associated with aggressive prostate cancer

Background: There is an urgent need for the detection of aggressive prostate cancer. Glycoproteins play essential roles in cancer development, while urine is a noninvasive and easily obtainable biological fluid that contains secretory glycoproteins from the urogenital system. Therefore, here we aimed to identify urinary glycoproteins that are capable of differentiating aggressive from non-aggressive prostate cancer.

Methods: Quantitative mass spectrometry data of glycopeptides from a discovery cohort comprised of 74 aggressive (Gleason score ≥8) and 68 non-aggressive (Gleason score = 6) prostate cancer urine specimens were acquired via a data independent acquisition approach. The glycopeptides showing distinct expression profiles in aggressive relative to non-aggressive prostate cancer were further evaluated for their performance in distinguishing the two groups either individually or in combination with others using repeated 5-fold cross validation with logistic regression to build predictive models. Predictive models showing good performance from the discovery cohort were further evaluated using a validation cohort.

Results: Among the 20 candidate glycoproteins, urinary ACPP outperformed the other candidates. Urinary ACPP can also serve as an adjunct to serum PSA to further improve the discrimination power for aggressive prostate cancer (AUC= 0.82, 95% confidence interval 0.75 to 0.89). A three-signature panel including urinary ACPP, urinary CLU, and serum PSA displayed the ability to distinguish aggressive prostate cancer from non-aggressive prostate cancer with an AUC of 0.86 (95% confidence interval 0.8 to 0.92). Another three-signature panel containing urinary ACPP, urinary LOX, and serum PSA also demonstrated its ability in recognizing aggressive prostate cancer (AUC=0.82, 95% confidence interval 0.75 to 0.9). Moreover, consistent performance was observed from each panel when evaluated using a validation cohort.

Conclusion: We have identified glycopeptides of urinary glycoproteins associated with aggressive prostate cancer using a quantitative mass spectrometry-based glycoproteomic approach and demonstrated their potential to serve as noninvasive urinary glycoprotein biomarkers worthy of further validation by a multi-center study.

Advances in the diagnostic options for prostate cancer

Over the past decade, despite the controversies surrounding prostate cancer screening, significant refinements have improved its application. PSA screening, although it has been questioned, appears to confer a mortality benefit and remains the most effective way to identify the possible presence of prostate cancer. Methods to improve the specificity of PSA screening and limit overdiagnosis of indolent cancers, including risk-stratified screening regimens, are currently being utilized. Certain imaging modalities, such as multiparametric MRI, have proven to be excellent adjuncts providing improved risk stratification and the ability for targeted biopsies; however, concerns over variability in interpretation and generalizability persist. A number of novel biomarkers have become available with nearly all demonstrating the ability to improve upon the specificity of PSA screening; however, optimal timing, direct comparisons, and usefulness in conjunction with imaging modalities remain to be elucidated. With the improvement in testing options and recognition of the risk/benefit ratio for men undergoing screening for prostate cancer, the increasing role of shared decision making in the process is emphasized.

Genetic testing for the clinician in prostate cancer

INTRODUCTION

Prostate cancer (PCa) is one of the most common cancers worldwide and a leading cause of cancer-related mortality. Although the diagnosis and treatment of prostate cancer has improved substantially in recent years, new molecular biomarkers are needed to further prolong survival and improve the quality of life in these patients.

AREAS COVERED

This review analyzes the current evidence for prognostic and predictive molecular biomarkers that can be applied across different clinical scenarios, ranging from localized disease to metastatic castration-resistant PCa, with a particular emphasis on the biomarkers likely to become available in routine clinical practice in the near future.

EXPERT OPINION

There is a growing need for molecular testing to identify the most indolent types of prostate cancer to help optimize treatment strategies and spare treatment in these patients when possible. Current trends in the treatment of prostate cancer underscore the unmet clinical need for biomarkers to improve decision-making in a challenging clinical setting.

Regulation of Skeletal Muscle Atrophy in Cachexia by MicroRNAs and Long Non-coding RNAs

Skeletal muscle atrophy is a common complication of cachexia, characterized by progressive bodyweight loss and decreased muscle strength, and it significantly increases the risks of morbidity and mortality in the population with atrophy. Numerous complications associated with decreased muscle function can activate catabolism, reduce anabolism, and impair muscle regeneration, leading to muscle wasting. microRNAs (miRNAs) and long non-coding RNAs (lncRNAs), types of non-coding RNAs, are important for regulation of skeletal muscle development. Few studies have specifically identified the roles of miRNAs and lncRNAs in cellular or animal models of muscular atrophy during cachexia, and the pathogenesis of skeletal muscle wasting in cachexia is not entirely understood. To develop potential approaches to improve skeletal muscle mass, strength, and function, a more comprehensive understanding of the known key pathophysiological processes leading to muscular atrophy is needed. In this review, we summarize the known miRNAs, lncRNAs, and corresponding signaling pathways involved in regulating skeletal muscle atrophy in cachexia and other diseases. A comprehensive understanding of the functions and mechanisms of miRNAs and lncRNAs during skeletal muscle wasting in cachexia and other diseases will, therefore, promote therapeutic treatments for muscle atrophy.

Temporal Stability and Prognostic Biomarker Potential of the Prostate Cancer Urine miRNA Transcriptome

BACKGROUND

The development of noninvasive tests for the early detection of aggressive prostate tumors is a major unmet clinical need. miRNAs are promising noninvasive biomarkers: they play essential roles in tumorigenesis, are stable under diverse analytical conditions, and can be detected in body fluids.

METHODS

We measured the longitudinal stability of 673 miRNAs by collecting serial urine samples from 10 patients with localized prostate cancer. We then measured temporally stable miRNAs in an independent training cohort (n = 99) and created a biomarker predictive of Gleason grade using machine-learning techniques. Finally, we validated this biomarker in an independent validation cohort (n = 40).

RESULTS

We found that each individual has a specific urine miRNA fingerprint. These fingerprints are temporally stable and associated with specific biological functions. We identified seven miRNAs that were stable over time within individual patients and integrated them with machine-learning techniques to create a novel biomarker for prostate cancer that overcomes interindividual variability. Our urine biomarker robustly identified high-risk patients and achieved similar accuracy as tissue-based prognostic markers (area under the receiver operating characteristic = 0.72, 95% confidence interval = 0.69 to 0.76 in the training cohort, and area under the receiver operating characteristic curve = 0.74, 95% confidence interval = 0.55 to 0.92 in the validation cohort).

CONCLUSIONS

These data highlight the importance of quantifying intra- and intertumoral heterogeneity in biomarker development. This noninvasive biomarker may usefully supplement invasive or expensive radiologic- and tissue-based assays.

Overdiagnosis and Lives Saved by Reflex Testing Men With Intermediate Prostate-Specific Antigen Levels

BACKGROUND

Several prostate cancer (PCa) early-detection biomarkers are available for reflex testing in men with intermediate prostate-specific antigen (PSA) levels. Studies of these biomarkers typically provide information about diagnostic performance but not about overdiagnosis and lives saved, the primary drivers of associated harm and benefit.

METHODS

We projected overdiagnoses and lives saved using an established microsimulation model of PCa incidence and mortality with screening and treatment efficacy based on randomized trials. We used this framework to evaluate four urinary reflex biomarkers (measured in 1112 men presenting for prostate biopsy at 10 US academic or community clinics) and two hypothetical ideal biomarkers (with 100% sensitivity or specificity for any or for high-grade PCa) at one-time screening tests at ages 55 and 65 years.

RESULTS

Compared with biopsying all men with elevated PSA, reflex testing reduced overdiagnoses (range across ages and biomarkers = 8.8-60.6%) but also reduced lives saved (by 7.3-64.9%), producing similar overdiagnoses per life saved. The ideal biomarker for high-grade disease improved this ratio (by 35.2% at age 55 years and 42.0% at age 65 years). Results were similar under continued screening for men not diagnosed at age 55 years, but the ideal biomarker for high-grade disease produced smaller incremental improvement.

CONCLUSIONS

Modeling is a useful tool for projecting the implications of using reflex biomarkers for long-term PCa outcomes. Under simplified conditions, reflex testing with urinary biomarkers is expected to reduce overdiagnoses but also produce commensurate reductions in lives saved. Reflex testing that accurately identifies high-grade PCa could improve the net benefit of screening.

Clonal evaluation of prostate cancer molecular heterogeneity in biopsy samples by dual immunohistochemistry and dual RNA in situ hybridization

Prostate cancer is frequently multifocal. Although there may be morphological variation, the genetic underpinnings of each tumor are not clearly understood. To assess the inter and intra tumor molecular heterogeneity in prostate biopsy samples, we developed a combined immunohistochemistry and RNA in situ hybridization method for the simultaneous evaluation of ERG, SPINK1, ETV1, and ETV4. Screening of 601 biopsy cores from 120 consecutive patients revealed multiple alterations in a mutually exclusive manner in 37% of patients, suggesting multifocal tumors with considerable genetic differences. Furthermore, the incidence of molecular heterogeneity was higher in African Americans patients compared with Caucasian American patients. About 47% of the biopsy cores with discontinuous tumor foci showed clonal differences with distinct molecular aberrations. ERG positivity occurred in low-grade cancer, whereas ETV4 expression was observed mostly in high-grade cancer. Further studies revealed correlation between the incidence of molecular markers and clinical and pathologic findings, suggesting potential implications for diagnostic pathology practice, such as defining dominant tumor nodules and discriminating juxtaposed but molecularly different tumors of different grade patterns.

Impact of the MyProstateScore (MPS) Test on the Clinical Decision to Undergo Prostate Biopsy: Results From a Contemporary Academic Practice

OBJECTIVE

To evaluate the association of the MyProstateScore (MPS) urine test on the decision to undergo biopsy in men referred for prostate biopsy in urology practice.

METHODS

MPS testing was offered as an alternative to immediate biopsy in men referred to the University of Michigan for prostate biopsy from October 2013 through October 2016. The primary endpoint was the decision to perform biopsy. The proportion of patients undergoing biopsy was compared to predicted risk scores from the Prostate Cancer Prevention Trial risk calculator (PCPTrc). Analyses were stratified by the use of multiparametric magnetic resonance imaging (mpMRI). The associations of PCPTrc, MPS, and mpMRI with the decision to undergo biopsy were explored in a multivariable logistic regression model.

RESULTS

Of 248 patients, 134 (54%) proceeded to prostate biopsy. MPS was significantly higher in biopsied patients (median 29 vs14, P < .001). The use of biopsy was strongly associated with MPS, with biopsy rates of 26%, 38%, 58%, 90%, and 85% in the first through fifth quintiles, respectively (P < .001). MPS association with biopsy persisted upon stratification by mpMRI. On multivariable analysis, MPS was strongly associated with the decision to undergo biopsy when modeled as both a continuous (odds ratio [OR] 1.05, 95%; confidence interval [CI] 1.04-1.08; <.001) and binary (OR 7.76, 95%; CI 4.14-14.5; P < .001) variable.

CONCLUSION

Many patients (46%) undergoing clinical MPS testing as an alternative to immediate prostate biopsy were able to avoid biopsy. Increasing MPS was strongly associated with biopsy rates. These findings were robust to use of mpMRI.

Recent advances of long noncoding RNAs involved in the development of multiple sclerosis

Given the rapid increase of patients with autoimmune diseases and the lack of satisfactory therapies, the discovery of novel and effective therapeutic targets have been in an urgent demand. Recent studies have revealed that long noncoding RNAs (lncRNAs) play crucial roles in the development of multiple sclerosis (MS), which provides a new opportunity of uncovering novel mechanism associated with the progression of MS. This review highlights the dysregulation of lncRNAs in the development of MS in patients and animal models. Additionally, the potential clinical relevance of lncRNAs severed as therapeutic targets and diagnostic markers are discussed.

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.

The Role of Non-coding RNAs in Oncology

For decades, research into cancer biology focused on the involvement of protein-coding genes. Only recently was it discovered that an entire class of molecules, termed non-coding RNA (ncRNA), plays key regulatory roles in shaping cellular activity. An explosion of studies into ncRNA biology has since shown that they represent a diverse and prevalent group of RNAs, including both oncogenic molecules and those that work in a tumor suppressive manner. As a result, hundreds of cancer-focused clinical trials involving ncRNAs as novel biomarkers or therapies have begun and these are likely just the beginning.

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.

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.

KPNA2/ERG Coexpression is Associated With Early Recurrence in Advanced Prostate Cancers

Most prostate cancers (PC) overexpress the ERG oncogene and karyopherin α 2 (KPNA2). These genes play a role in prostatic carcinogenesis, but their prognostic significance is still debated. The aim of this study was to determine the prognostic significance of ERG and KPNA2 expression, and their association to early prostate-specific antigen (PSA) biochemical recurrence in advanced PC with lymph node metastases. A series of 65 consecutive pN1 M0 R0 PC samples obtained by radical prostatectomy with lymphadenectomy has been analyzed for ERG and KPNA2 expression by immunohistochemistry. For each case, the following clinical data were collected: age, preoperative serum PSA levels, Gleason grade group, TNM stage, and follow-up. PC recurrence was investigated by serum PSA assay and defined by a PSA concentration >0.2 ng/mL after a nadir of <0.1 ng/mL following radical prostatectomy. ERG-positive staining was found in 25/65 cases (38%), and KPNA2 in 56/65 cases (86%); neither was detected in normal prostatic tissue. Immunohistochemical concordance was found between primary tumor and lymph node metastases in 24/25 (96%) of ERG and 53/56 (95%) of KPNA2-positive cases. The follow-up was known in all cases, and early PSA recurrence occurred in 25/65 cases (38%). ERG positivity, both alone and in conjunction with KPNA2 positivity, was strongly associated with early PSA recurrence [both ERG+ and KPNA+, odds ratio: 22.2 (95% confidence interval, 6.0-82.3); ERG+ alone odds ratio: 17.9 (95% confidence interval, 5.1-63.5); P<0.0001 for both]. KPNA2 expression was significantly associated with the tumor stage (P<0.00001). The results suggest that the ERG+ phenotype might be selected in metastasis-initiating clones. ERG and KPNA2 may have a prognostic value, and their positivity in PC might warrant more aggressive treatments.

Detection of Novel Fusion Transcript VTI1A-CFAP46 in Hepatocellular Carcinoma

Background

Hepatocellular carcinoma (HCC) is now the second-highest cause of cancer death worldwide. Recent studies have discovered a wide range of somatic mutations in HCC. These mutations involve various vital signaling pathways such as: Wnt/β-Catenin, p53, telome-rase reverse transcriptase (TERT), chromatin remodeling, RAS/MAPK signaling, and oxidative stress. However, fusion transcripts have not been broadly explored in HCC.

Methods

To identify novel fusion transcripts in HCC, in the first phase of our study, we performed targeted RNA sequencing (in HCC and paired non-HCC tissues) on 6 patients with a diagnosis of HCC undergoing liver transplantation.

Results

As a result of these studies, we discovered the novel fusion transcript, VTI1A-CFAP46. In the second phase of our study, we measured the expression of wild-type VTI1A in 21 HCC specimens, which showed that 10 of 21 exhibited upregulation of wild-type VTI1A in their tumors. VTI1A (Vesicle Transport via Interaction with t-SNARE homolog 1A) is a member of the Soluble N-ethylmaleimide-Sensitive Factor (NSF) attachment protein receptor (SNARE) gene family, which is essential for membrane trafficking and function in endocytosis, autophagy, and Golgi transport. Notably, it is known that autophagy is involved in HCC.

Conclusions

The link between novel fusion transcript VTI1A-CFAP46 and autophagy as a potential therapeutic target in HCC patients deserves further investigation. Moreover, this study shows that fusion transcripts are worthy of additional exploration in HCC.

Performance of PCA3 and TMPRSS2:ERG urinary biomarkers in prediction of biopsy outcome in the Canary Prostate Active Surveillance Study (PASS)

BACKGROUND

For men on active surveillance for prostate cancer, biomarkers may improve prediction of reclassification to higher grade or volume cancer. This study examined the association of urinary PCA3 and TMPRSS2:ERG (T2:ERG) with biopsy-based reclassification.

METHODS

Urine was collected at baseline, 6, 12, and 24 months in the multi-institutional Canary Prostate Active Surveillance Study (PASS), and PCA3 and T2:ERG levels were quantitated. Reclassification was an increase in Gleason score or ratio of biopsy cores with cancer to ≥34%. The association of biomarker scores, adjusted for common clinical variables, with short- and long-term reclassification was evaluated. Discriminatory capacity of models with clinical variables alone or with biomarkers was assessed using receiver operating characteristic (ROC) curves and decision curve analysis (DCA).

RESULTS

Seven hundred and eighty-two men contributed 2069 urine specimens. After adjusting for PSA, prostate size, and ratio of biopsy cores with cancer, PCA3 but not T2:ERG was associated with short-term reclassification at the first surveillance biopsy (OR = 1.3; 95% CI 1.0-1.7, p = 0.02). The addition of PCA3 to a model with clinical variables improved area under the curve from 0.743 to 0.753 and increased net benefit minimally. After adjusting for clinical variables, neither marker nor marker kinetics was associated with time to reclassification in subsequent biopsies.

CONCLUSIONS

PCA3 but not T2:ERG was associated with cancer reclassification in the first surveillance biopsy but has negligible improvement over clinical variables alone in ROC or DCA analyses. Neither marker was associated with reclassification in subsequent biopsies.

NMR-Based Metabolomic Profiling of Urine: Evaluation for Application in Prostate Cancer Detection

Detection of prostate cancer (PCa) and distinguishing indolent versus aggressive forms of the disease is a critical clinical challenge. The current clinical test is circulating prostate-specific antigen levels, which faces particular challenges in cancer diagnosis in the range of 4 to 10 ng/mL. Thus, a concerted effort toward building a noninvasive biomarker panel has developed. In this report, the hypothesis that nuclear magnetic resonance (NMR)-derived metabolomic profiles measured in the urine of biopsy-negative versus biopsy-positive individuals would nominate a selection of potential biomarker signals was investigated. 1H NMR spectra of urine samples from 317 individuals (111 biopsy-negative, 206 biopsy-positive) were analyzed. A double cross-validation partial least squares-discriminant analysis modeling technique was utilized to nominate signals capable of distinguishing the two classes. It was observed that after variable selection protocols were applied, a subset of 29 variables produced an area under the curve (AUC) value of 0.94 after logistic regression analysis, whereas a “master list” of 18 variables produced a receiver operating characteristic ROC) AUC of 0.80. As proof of principle, this study demonstrates the utility of NMR-based metabolomic profiling of urine biospecimens in the nomination of PCa-specific biomarker signals and suggests that further investigation is certainly warranted.

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.

Investigation on core-fucosylated prostate-specific antigen as a refined biomarker for differentiation of benign prostate hyperplasia and prostate cancer of different aggressiveness

Prostate cancer represents a major cause of cancer death in men worldwide. Novel non-invasive methods are still required for differentiation of non-aggressive from aggressive tumors. Recently, changes in prostate-specific antigen glycosylation pattern, such as core-fucosylation, have been described in prostate cancer. The objective of this study was to evaluate whether the core-fucosylation determinant of serum prostate-specific antigen may serve as refined marker for differentiation between benign prostate hyperplasia and prostate cancer or identification of aggressive prostate cancer. A previously developed liquid chromatography-mass spectrometry/mass spectrometry-based strategy was used for multiplex analysis of core-fucosylated prostate-specific antigen (fuc-PSA) and total prostate-specific antigen levels in sera from 50 benign prostate hyperplasia and 100 prostate cancer patients of different aggressiveness (Gleason scores, 5-10) covering the critical gray area (2-10 ng/mL). For identification of aggressive prostate cancer, the ratio of fuc-PSA to total prostate-specific antigen (%-fuc-PSA) yielded a 5%-8% increase in the area under the curve (0.60) compared to the currently used total prostate-specific antigen (area under the curve = 0.52) and %-free prostate-specific antigen (area under the curve = 0.55) tests. However, our data showed that aggressive prostate cancer (Gleason score > 6) and non-aggressive prostate cancer (Gleason score ≤ 6) could not significantly (p-value = 0.08) be differentiated by usage of %-fuc-PSA. In addition, both non-standardized fuc-PSA and standardized %-fuc-PSA had no diagnostic value for differentiation of benign prostate hyperplasia from prostate cancer. The %-fuc-PSA serum levels could not improve the differentiation of non-aggressive and aggressive prostate cancer compared to conventional diagnostic prostate cancer markers. Still, it is unclear whether these limitations come from the biomarker, the used patient cohort, or the imprecision of the applied method itself. Therefore, %-fuc-PSA should be further investigated, especially by more precise methods whether it could be clinically used in prostate cancer diagnosis.

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.

Glycans as Biomarkers in Prostate Cancer

Prostate cancer is the most commonly diagnosed malignancy in men, claiming over350,000 lives worldwide annually. Current diagnosis relies on prostate-specific antigen (PSA)testing, but this misses some aggressive tumours, and leads to the overtreatment of non-harmfuldisease. Hence, there is an urgent unmet clinical need to identify new diagnostic and prognosticbiomarkers. As prostate cancer is a heterogeneous and multifocal disease, it is likely that multiplebiomarkers will be needed to guide clinical decisions. Fluid-based biomarkers would be ideal, andattention is now turning to minimally invasive liquid biopsies, which enable the analysis oftumour components in patient blood or urine. Effective diagnostics using liquid biopsies willrequire a multifaceted approach, and a recent high-profile review discussed combining multipleanalytes, including changes to the tumour transcriptome, epigenome, proteome, and metabolome.However, the concentration on genomics-based paramaters for analysing liquid biopsies ispotentially missing a goldmine. Glycans have shown huge promise as disease biomarkers, anddata suggests that integrating biomarkers across multi-omic platforms (including changes to theglycome) can improve the stratification of patients with prostate cancer. A wide range ofalterations to glycans have been observed in prostate cancer, including changes to PSAglycosylation, increased sialylation and core fucosylation, increased O-GlcNacylation, theemergence of cryptic and branched N-glyans, and changes to galectins and proteoglycans. In thisreview, we discuss the huge potential to exploit glycans as diagnostic and prognostic biomarkersfor prostate cancer, and argue that the inclusion of glycans in a multi-analyte liquid biopsy test forprostate cancer will help maximise clinical utility.

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.