Addressing the need for repeat prostate biopsy: new technology and approaches

Increased α2,3-sialyl N-glycosylated prostate-specific membrane antigen (PSMA) in post-DRE urine is associated with high grade group prostate cancer

INTRODUCTION

Aberrant glycosylation of proteins is an important hallmark in multiple cancers. Prostate-specific membrane antigen (PSMA), a highly glycosylated protein with 10 N-linked glycosylation sites, is an Food and Drug Administration approved theranostic for prostate cancer. However, glycosylation changes in PSMA that are associated with prostate cancer disease progression have not been fully characterized.

METHODS

We investigated whether urinary PSMA sialylation correlate with high-grade prostate cancer. Urine samples were collected from men after digital rectal examination (DRE) before prostate biopsy. Lectin-antibody enzyme-linked immunoassay was used to quantify α2,3-sialyl PSMA in post-DRE urine samples from subjects with benign prostate tumors, Grade Group 1 prostate cancer and those with Grade Group ≥2 disease.

RESULTS

There are significant increases in α2,3-sialylated PSMA in patients with Grade Group ≥2 disease compared to benign (p = 0.0009) and those with Grade Group 1 disease (p = 0.0063). There were no significant differences in α2,3-sialyl PSMA levels between Grade Group 1 and benign prostate tumors (p = 0.7947).

CONCLUSIONS

Our study shows that there are significant differences in the abundance of α2,3-sialylated PSMA in post-DRE urines from disease stratified prostate cancer patients, and the increase is correlated with progression and disease severity. The detection of increased PSMA sialyation in post-DRE urines from patients with higher Grade Group ≥2 disease states provides novel untapped potential for the development of prognostic biomarkers for prostate cancer. Specifically, quantitation of α2,3-sialylated PSMA shows potential for discriminating between benign to intermediate grade disease, which is a significant clinical challenge in staging and risk stratification of prostate cancer.

Prostate-specific membrane antigen (PSMA) glycoforms in prostate cancer patients seminal plasma

INTRODUCTION

Prostate-specific membrane antigen (PSMA) is a US Food and Drug Administration-approved theranostic target for prostate cancer (PCa). Although PSMA is known to be glycosylated, the composition and functional roles of its N-linked glycoforms have not been fully characterized.

METHODS

PSMA was isolated from pooled seminal plasma from low-risk grade Groups 1 and 2 PCa patients. Intact glycopeptides were analyzed by mass spectrometry to identify site-specific glycoforms.

RESULTS

We observed a rich distribution of PSMA glycoforms in seminal plasma from low and low-intermediate-risk PCa patients. Some interesting generalities can be drawn based on the predicted topology of PSMA on the plasma membrane. The glycoforms at ASN-459, ASN-476, and ASN-638 residues that are located at the basal domain facing the plasma membrane in cells, are predominantly high mannose glycans. ASN-76 which is located in the interdomain region adjacent to the apical domain of the protein shows a mixture of high mannose glycans and complex glycans, whereas ASN-121, ASN-195 and ASN-336 that are located and are exposed at the apical domain of the protein predominantly possess complex sialylated and fucosylated N-linked glycans. These highly accessible glycosites display the greatest diversity in isoforms across the patient samples.

CONCLUSIONS

Our study provides novel qualitative insights into PSMA glycoforms that are present in the seminal fluid of PCa patients. The presence of a rich diversity of glycoforms in seminal plasma provides untapped potential for glycoprotein biomarker discovery and as a clinical sample for noninvasive diagnostics of male urological disorders and diseases including PCa. Specifically, our glycomics approach will be critical in uncovering PSMA glycoforms with utility in staging and risk stratification of PCa.

MyProstateScore in men considering repeat biopsy: validation of a simple testing approach

BACKGROUND

Men with persistent risk of Grade Group (GG) ≥ 2 cancer after a negative biopsy present a unique clinical challenge. The validated MyProstateScore test is clinically-available for pre-biopsy risk stratification. In biopsy-naïve patients, we recently validated a straightforward testing approach to rule-out GG ≥ 2 cancer with 98% negative predictive value (NPV) and 97% sensitivity. In the current study, we established a practical MPS-based testing approach in men with a previous negative biopsy being considered for repeat biopsy.

METHODS

Patients provided post-digital rectal examination urine prior to repeat biopsy. MyProstateScore was calculated using the validated, locked model including urinary PCA3 and TMPRSS2:ERG scores with serum PSA. In a clinically-appropriate primary (i.e., training) cohort, we identified a lower (rule-out) threshold approximating 90% sensitivity and an upper (rule-in) threshold approximating 80% specificity for GG ≥ 2 cancer. These thresholds were applied to an external validation cohort, and performance measures and clinical outcomes associated with their use were calculated.

RESULTS

MyProstateScore thresholds of 15 and 40 met pre-defined performance criteria in the primary cohort (422 patients; median PSA 6.4, IQR 4.3-9.1). In the 268-patient validation cohort, 25 men (9.3%) had GG ≥ 2 cancer on repeat biopsy. The rule-out threshold of 15 provided 100% NPV and sensitivity for GG ≥ 2 cancer and would have prevented 23% of unnecessary biopsies. Use of MyProstateScore >40 to rule-in biopsy would have prevented 67% of biopsies while maintaining 95% NPV. In the validation cohort, the prevalence of GG ≥ 2 cancer was 0% for MyProstateScore 0-15, 6.5% for MyProstateScore 15-40, and 19% for MyProstateScore >40.

CONCLUSIONS

In patients who previously underwent a negative prostate biopsy, the MyProstateScore values of 15 and 40 yielded clinically-actionable rule-in and rule-out risk groups. Using this straightforward testing approach, MyProstateScore can meaningfully inform patients and physicians weighing the need for repeat biopsy.

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.

Site-Specific Intact N-Linked Glycopeptide Characterization of Prostate-Specific Membrane Antigen from Metastatic Prostate Cancer Cells

The composition of N-linked glycans that are conjugated to the prostate-specific membrane antigen (PSMA) and their functional significance in prostate cancer progression have not been fully characterized. PSMA was isolated from two metastatic prostate cancer cell lines, LNCaP and MDAPCa2b, which have different tissue tropism and localization. Isolated PSMA was trypsin-digested, and intact glycopeptides were subjected to LC-HCD-EThcD-MS/MS analysis on a Tribrid Orbitrap Fusion Lumos mass spectrometer. Differential qualitative and quantitative analysis of site-specific N-glycopeptides was performed using Byonic and Byologic software. Comparative quantitative analysis demonstrates that multiple glycopeptides at asparagine residues 51, 76, 121, 195, 336, 459, 476, and 638 were in significantly different abundance in the two cell lines (p < 0.05). Biochemical analysis using endoglycosidase treatment and lectin capture confirm the MS and site occupancy data. The data demonstrate the effectiveness of the strategy for comprehensive analysis of PSMA glycopeptides. This approach will form the basis of ongoing experiments to identify site-specific glycan changes in PSMA isolated from disease-stratified clinical samples to uncover targets that may be associated with disease progression and metastatic phenotypes.

On the Road to Accurate Protein Biomarkers in Prostate Cancer Diagnosis and Prognosis: Current Status and Future Advances

Prostate cancer (PC) is a leading cause of morbidity and mortality among men worldwide. Molecular biomarkers work in conjunction with existing clinicopathologic tools to help physicians decide who to biopsy, re-biopsy, treat, or re-treat. The past decade has witnessed the commercialization of multiple PC protein biomarkers with improved performance, remarkable progress in proteomic technologies for global discovery and targeted validation of novel protein biomarkers from clinical specimens, and the emergence of novel, promising PC protein biomarkers. In this review, we summarize these advances and discuss the challenges and potential solutions for identifying and validating clinically useful protein biomarkers in PC diagnosis and prognosis. The identification of multi-protein biomarkers with high sensitivity and specificity, as well as their integration with clinicopathologic parameters, imaging, and other molecular biomarkers, bodes well for optimal personalized management of PC patients.

Affinity Captured Urinary Extracellular Vesicles Provide mRNA and miRNA Biomarkers for Improved Accuracy of Prostate Cancer Detection: A Pilot Study

Serum prostate-specific antigen (sPSA) testing has helped to increase early detection of and decrease mortality from prostate cancer. However, since sPSA lacks specificity, an invasive prostate tissue biopsy is required to confirm cancer diagnosis. Using urinary extracellular vesicles (EVs) as a minimally invasive biomarker source, our goal was to develop a biomarker panel able to distinguish prostate cancer from benign conditions with high accuracy. We enrolled 56 patients in our study, 28 negative and 28 positive for cancer based on tissue biopsy results. Using our Vn96 peptide affinity method, we isolated EVs from post-digital rectal exam urines and used quantitative polymerase chain reaction to measure several mRNA and miRNA targets. We identified a panel of seven mRNA biomarkers whose expression ratio discriminated non-cancer from cancer with an area under the curve (AUC) of 0.825, sensitivity of 75% and specificity of 84%. We also identified two miRNAs whose combined score yielded an AUC of 0.744. A model pairing the seven mRNA and two miRNA panels yielded an AUC of 0.843, sensitivity of 79% and specificity of 89%. Addition of EV-derived PCA3 levels and clinical characteristics to the biomarker model further improved test accuracy. An AUC of 0.955, sensitivity of 86% and specificity of 93% were obtained. Hence, Vn96-isolated urinary EVs are a clinically applicable and minimally invasive source of mRNA and miRNA biomarkers with potential to improve on the accuracy of prostate cancer screening and diagnosis.

Establishing a novel prediction model for improving the positive rate of prostate biopsy

Background

At present, prostate-specific antigen (PSA) is the primary evaluation index for judging the necessity of prostate cancer (PCa) biopsy. However, there is a high false-positive rate and a low predictive value due to many interference factors. In this study, we tried to find a novel prediction model that could improve the positive rate of prostate biopsy and reduce unnecessary biopsy.

Methods

We retrospectively studied 237 patients, including their age, body mass index (BMI), PSA, prostate volume (PV), prostate imaging-reporting and data system (PI-RADS) v2 score, neutrophil-lymphocyte ratio (NLR), biopsy Gleason score (BGS), and other information. The univariate and multivariate logistic analyses were used to screen out indicators related to PCa. After establishing a prediction formula model, we used receiver operating characteristic (ROC) curves to assess its prediction performance.

Results

Our study found that age, PSA, PI-RADS v2 score, and diabetes significantly correlated with PCa. Based on multivariate logistic regression analysis results, we created the following prediction formula: Y = 2.599 × PI-RADS v2 score + 1.766 × diabetes + 0.052 × age + 1.005 × PSAD - 9.119. ROC curves showed the formula's threshold was 0.3543. The composite formula had an excellent capacity to detect PCa with the area under the curve (AUC) of 0.91. In addition, the composite formula also achieved significantly better sensitivity, specificity, and diagnostic accuracy than PSA, PSA density (PSAD), and PI-RADS v2 score alone.

Conclusions

Our predictive formula predicted performance better than PSA, PSAD, and PI-RADS v2 score. It can thus contribute to the diagnosis of PCa and be used as an indicator for prostate biopsy, thereby reducing unnecessary biopsy.

Validation of an epigenetic field of susceptibility to detect significant prostate cancer from non-tumor biopsies

Background

An epigenetic field of cancer susceptibility exists for prostate cancer (PC) that gives rise to multifocal disease in the peripheral prostate. In previous work, genome-wide DNA methylation profiling identified altered regions in the normal prostate tissue of men with PC. In the current multicenter study, we examined the predictive strength of a panel of loci to detect cancer presence and grade in patients with negative biopsy tissue.

Results

Four centers contributed benign prostate biopsy tissues blocks from 129 subjects that were either tumor associated (TA, Grade Group [GG] ≥ 2, n = 77) or non-tumor associated (NTA, n = 52). Biopsies were analyzed using pyrosequencing for DNA methylation encompassing CpG loci near CAV1, EVX1, FGF1, NCR2, PLA2G16, and SPAG4 and methylation differences were detected within all gene regions (p < 0.05). A multiplex regression model for biomarker performance incorporating a gene combination discriminated TA from NTA tissues (area under the curve [AUC] 0.747, p = 0.004). A multiplex model incorporating all the above genes and clinical information (PSA, age) identified patients with GG ≥ 2 PC (AUC 0.815, p < 0.0001). In patients with cancer, increased variation in gene methylation levels occurs between biopsies across the prostate.

Conclusions

A widespread epigenetic field defect is utilized to detect GG ≥ 2 PC in patients with histologically negative biopsies. These alterations in non-tumor cells display increased heterogeneity of methylation extent and are spatially distant from tumor foci. These findings have the potential to decrease the need for repeated prostate biopsy.

Approaches to urinary detection of prostate cancer

Background:

Prostate cancer is the most common cancer in American men that ranges from low risk states amenable to active surveillance to high risk states that can be lethal especially if untreated. There is a critical need to develop relatively non-invasive and clinically useful methods for screening, detection, prognosis, disease monitoring, and prediction of treatment efficacy. In this review, we focus on important advances as well as future efforts needed to drive clinical innovation in this area of urine biomarker research for prostate cancer detection and prognostication.

Methods:

We provide a review of current literature on urinary biomarkers for prostate cancer. We evaluate the strengths and limitations of a variety of approaches that vary in sampling strategies and targets measured; discuss reported urine tests for prostate cancer with respect to their technical, analytical, and clinical parameters; and provide our perspectives on critical considerations in approaches to developing a urine-based test for prostate cancer.

Results:

There has been an extensive history of exploring urine as a source of biomarkers for prostate cancer that has resulted in a variety of urine tests that are in current clinical use. Importantly, at least three tests have demonstrated high sensitivity (~90%) and negative predictive value (~95%) for clinically significant tumors; however, there has not been widespread adoption of these tests.

Conclusions:

Conceptual and methodological advances in the field will help to drive the development of novel urinary tests that in turn may lead to a shift in the clinical paradigm for prostate cancer diagnosis and management.

Retrospective Study of the Significant Predictive Role of Inflammatory Degree in Initial and Repeat Prostate Biopsy Specimens for Detecting Prostate Cancer

Purpose

The purpose of this study was to determine whether histologic inflammation (HI) in initial and repeat prostate biopsy specimens was significantly associated with the detection of prostate cancer.

Materials and Methods

Between 2005 and 2017, the clinicopathological records of patients with high prostatespecific antigen (PSA) levels who underwent initial and repeat prostate biopsies were retrospectively reviewed. The presence of HI and its degree in each biopsied specimen were interpreted by one uropathologist with 20 years of experience. The association between HI and cancer diagnosis was statistically assessed, with p < 0.05 considered significant, and the cancer and non-cancer groups were compared.

Results

Among the 522 patients with a median PSA levels of 6.5 ng/dL, including 258 (49.4%) whose cancer was diagnosed following repeat biopsy, the median degrees of HI in the initial and repeat biopsies were 25.0% and 41.7%, respectively. Furthermore, 211 (40.4%) and 247 (47.3%) patients had HI (> 0%) on biopsied specimens, respectively. Comparison of the cancer and noncancer groups revealed that a greater rate of HI specimens in the initial biopsy was associated with fewer prostate cancer diagnoses following repeat biopsy (p < 0.001). Other comparisons between the cancer and non-cancer groups showed that the cancer group had a significantly higher rate of hypertension, whereas those non-cancer group had a significantly higher rate of benign prostatic hyperplasia and prostatitis (p < 0.05).

Conclusion

A finding of a lesser degree of HI in the initial and a greater degree of HI in the repeat biopsied specimens was associated with the higher probability of cancer diagnosis in patients with high PSA levels.

Clinical evaluation of the iXip index to reduce prostate re-biopsies

BACKGROUND

Prostate biopsy is the gold standard for prostate cancer (PCa) diagnosis, but it's invasive and associated with adverse events. Novel reliable tumor biomarkers and accurate non-invasive tests are required to avoid biopsies. The immune complex PSA-IgM is a new marker for PCa, and it has been included in an algorithm to generate the diagnostic index iXip, which determines the probability of having PCa. In this study we evaluated the ability of iXip to reduce the number of repeat biopsies in patients with a previous negative biopsy and suspicious for PCa.

PATIENTS AND METHODS

219 patients referred for prostate rebiopsy were included in the study. Each patient underwent a trans-rectal ultrasound-guided prostate biopsy and prostate volume examination. Blood samples were collected before any prostatic manipulation to determine the serological levels of PSA-IgM and PSA. The iXip index was calculated as previously reported using an online calculator.

RESULTS

iXip values in patients with a positive biopsy were significantly higher than the ones observed in negative patients (p-value = 0.001). Based on iXip values, patients were divided in five risk groups: those with iXip < 0.2 had 0% probability of having PCa. High values of the Gleason score (≥7) were observed mostly in patients with iXip 0.3-0.8.

CONCLUSION

Our preliminary results show that iXip identifies a sub-group of patients who can safely avoid rebiopsy because they do not have PCa. The index is a promising tool that could reduce the number of unnecessary prostate biopsies and the relative clinical complications and expenses.

Management of men with previous negative prostate biopsy

PURPOSE OF REVIEW

Up to 70% of prostate biopsies are negative in men with suspected prostate cancer. Because of inherent limitations in biopsy strategies, a significant proportion of cancers are missed on initial biopsy. Following negative biopsy, men frequently exhibit persistently elevated prostate-specific antigen - raising concerns for missed diagnosis. We highlight the recent updates in the management of negative prostate biopsy.

RECENT FINDINGS

Advances in noninvasive diagnostics are available and assist clinicians in further substratifying risk of prostate cancer. Despite limited data, urinary prostate cancer antigen 3 and transmembrane protease serine 2 appear to have a promising predictive value for patients suspected of prostate cancer. The advent of multiparametricMRI allows the visualization of intermediate and high-grade prostate cancer, particularly in the troublesome anterior prostate. This modality may further provide the potential for magnetic resonance-guided targeted biopsies. Current data suggest that in the presence of suspicious radiological findings, magnetic resonance-guided biopsies have superior sensitivity profiles compared with traditional rebiopsy approaches. In the absence of multiparametricMRI or suspicious findings, traditional saturation biopsies are sufficient.

SUMMARY

The management of negative biopsies is evolving rapidly with emerging diagnostics to stratify risk of prostate cancer in men with previous negative biopsies. An increasing body of information supports the use of magnetic resonance-guided biopsies.

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.

Alterations in expressed prostate secretion-urine PSA N-glycosylation discriminate prostate cancer from benign prostate hyperplasia

The prostate specific antigen (PSA) test is widely used for early diagnosis of prostate cancer (PCa). However, its limited sensitivity has led to over-diagnosis and over-treatment of PCa. Glycosylation alteration is a common phenomenon in cancer development. Different PSA glycan subforms have been proposed as diagnostic markers to better differentiate PCa from benign prostate hyperplasia (BPH). In this study, we purified PSA from expressed prostate secretions (EPS)-urine samples from 32 BPH and 30 PCa patients and provided detailed PSA glycan profiles in Chinese population. We found that most of the PSA glycans from EPS-urine were complex type biantennary glycans. We observed two major patterns in PSA glycan profiles. Overall there was no distinct separation of PSA glycan profiles between BPH and PCa patients. However, we detected a significant increase of glycan FA2 and FM5A2G2S1 in PCa when compared with BPH patients. Furthermore, we observed that the composition of FA2 glycan increased significantly in advanced PCa with Gleason score ≥8, which potentially could be translated to clinic as a marker for aggressive PCa.

Evaluation of Prostate HistoScanning as a Method for Targeted Biopsy in Routine Practice

BACKGROUND

Prostate HistoScanning (PHS) is a tissue characterization system used to enhance prostate cancer (PCa) detection via transrectal ultrasound imaging.

OBJECTIVE

To assess the impact of supplementing systematic transrectal biopsy with up to three PHS true targeting (TT) guided biopsies on the PCa detection rate and preclinical patient assessment.

DESIGN, SETTING, AND PARTICIPANTS

This was a prospective study involving a cohort of 611 consecutive patients referred for transrectal prostate biopsy following suspicion of PCa. PHS-TT guided cores were obtained from up to three PHS lesions of ≥0.5cm³ per prostate and only one core per single PHS lesion. Histological outcomes from a systematic extended 12-core biopsy (Bx) scheme and additional PHS-TT guided cores were compared.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Comparison of PHS results and histopathology was performed per sextant. The χ² and Mann-Whitney test were used to assess differences. Statistical significance was set at p<0.05.

RESULTS AND LIMITATIONS

PHS showed lesions of ≥0.5cm³ in 312 out of the 611 patients recruited. In this group, Bx detected PCa in 59% (185/312) and PHS-TT in 87% (270/312; p<0.001). The detection rate was 25% (944/3744 cores) for Bx and 68% (387/573 cores) for PHS-TT (p<0.001). Preclinical assessment was significantly better when using PHS-TT: Bx found 18.6% (58/312) and 8.3% (26/312), while PHS-TT found 42.3% (132/312) and 20.8% (65/312) of Gleason 7 and 8 cases, respectively (p<0.001). PHS-TT attributed Gleason score 6 to fewer patients (23.4%, 73/312) than Bx did (32.4%, 101/312; p=0.0021).

CONCLUSIONS

Patients with a suspicion of PCa may benefit from addition of a few PHS-TT cores to the standard Bx workflow.

PATIENT SUMMARY

Targeted biopsies of the prostate are proving to be equivalent to or better than standard systematic random sampling in many studies. Our study results support supplementing the standard schematic transrectal ultrasound-guided biopsy with a few guided cores harvested using the ultrasound-based prostate HistoScanning true targeting approach in cases for which multiparametric magnetic resonance imaging is not available.

A biopsy-integrated algorithm for determining Gleason 6 upgrading risk stratifies risk of active surveillance failure in prostate cancer

INTRODUCTION

A significant proportion of patients that fail active surveillance (AS) for prostate cancer management do so because of cancer upgrading. A previously validated upgrading nomogram generates a score that predicts risk of biopsy Gleason 6 upgrading following radical prostatectomy in lower-risk populations that are candidates for Active Surveillance (Cancer, 2013).

OBJECTIVES

We hypothesize that the upgrading risk (UR) score generated by this nomogram at diagnosis improves the ability to predict patients that will subsequently fail AS.

METHODS

To evaluate the nomogram, retrospective data from several institutional cohorts of patients who met AS criteria, group 1 (n = 75) and group 2 (n = 1230), were independently examined. A UR score was generated using the coefficients from the nomogram consisting of PSA density (PSAD), BMI, maximum % core involvement (MCI), and number of positive cores. AS failure was defined as Gleason score (GS) >6, >50 % maximum core involvement, or >2 positive cores on biopsy. Univariate and multivariate Cox proportional-hazards regression models, upgrading risk score, and other clinicopathologic features were each assessed for their ability to predict AS failure.

RESULTS

Clinicopathologic parameters were similar in both groups with the exception of mean PSAD (0.13 vs. 0.11, p < 0.01) and follow-up (2.1 vs. 3.2 years, p = 0.2). Most common cause of AS failure was GS > 6 (group 1) compared to >2 positive cores (group 2). On univariate analysis in both populations, features at diagnosis including PSAD and the UR score were significant in predicting AS failure by upgrading (Gleason > 6) and any failure. Multivariate analysis revealed the UR score predicts AS failure by GS upgrading (HR 1.8, 95 % CI 1.12-2.93; p = 0.01) and any failure criteria (HR 1.7, 95 % CI 1.06-2.65); p = 0.02) for group 1. Likewise, the UR score in group 2 predicts AS failure with GS upgrading (HR 1.3, 95 % CI 1.15-1.42; p < 0.0001) and any failure criteria (HR 1.18, 95 % CI 1.18-1.38; p < 0.0001). An ROC generated an AUC of 0.66. Decision curve analysis demonstrated a high net benefit for the UR score across a range of threshold probabilities. Based on these outcomes, at 3 years, patients in the lowest risk quartile have a 15 % risk of AS failure versus a 46 % risk in the highest quartile (p < 0.0001).

CONCLUSIONS

The UR score was predictive of pathologic AS failure on multivariate analysis in several AS cohorts. It outperformed single clinicopathologic criteria and may provide a useful adjunct using clinicopathologic data to stratify patients considering AS.

MicroRNA-410-5p as a potential serum biomarker for the diagnosis of prostate cancer

Background

Prostate cancer (PCa) remains to be a diagnostic challenge due to its variable presentation and the lack of reliable diagnosis tool. MicroRNAs (miRNAs) regulate gene in extensive range of pathophysiologic processes. Plasma miRNAs are ideal biomarkers in heart failure, diabetes and other disease. However, using circulating miRNAs as biomarkers for the diagnosis of PCa is still unknown.

Methods

149 PCa patients, 57 healthy controls, and 121 non-cancer patients (benign prostatic hyperplasia and other urinary diseases) were enrolled in this study. The reverse transcription of miRNA and SYBR-Green-based double standards curve miRNA quantitative polymerase chain reactions (qPCR) were used to evaluate the dysregulated miR-410-5p. Receiver operator characteristic (ROC) curve analysis was used to evaluate the diagnostic accuracy of miR-410-5p identified as the alternative biomarker.

Results

Circulating miRNA-410-5p (miR-410-5p) level was significantly higher in the PCa patients than in healthy controls or non-cancer patients. ROC curve analysis showed that plasma miR-410-5p was a specific diagnostic biomarker of PCa with an area under curve(AUC) of 0.8097 (95 % confidence interval, 0.7371–0.8823; P < 0.001).

Conclusions

The serum miR-410-5p level is a potential biomarker for the diagnosis of PCa.

Recent progress in urinary proteome analysis for prostate cancer diagnosis and management

Prostate cancer (PCa) is fifth leading cause of cancer-associated deaths in men worldwide. Although the application of the serum prostate-specific antigen (PSA) screening test resulted in an increase in the PCa diagnosed cases, it demonstrated a negligible benefit regarding the associated mortality. Treatment options vary, with active surveillance to be preferable for patients with low-risk PCa and therapy of advanced castration-resistant PCa to rely on α-emitters and cytotoxic chemotherapy. Although recent developments have led to the approval of novel drugs for the treatment of castration-resistant PCa, the optimal sequence and timing of medication have not been yet determined. New screening modalities could improve the discriminatory accuracy between tumors with favorable clinical prognosis. Implementation of proteomic-based biomarkers appears to be a promising improvement, which could enable a more accurate diagnosis, guide treatment and improve patient outcome. Reviewed here are urinary proteome-based approaches for detection of PCa and patient management.