The accuracy of cystoscopy in predicting muscle invasion in newly diagnosed bladder cancer patients.

PURPOSE: The prognosis of muscle-invasive bladder cancer (MIBC) has not improved for three decades. Transurethral resection of the bladder tumor (TURBT) is the standard procedure for local tumor staging. TURBT has several limitations, including the spread of tumor cells. Therefore, an alternative is needed in patients with suspected MIBC. Recent studies have shown that mpMRI is very accurate in staging bladder tumors. Because the diagnostic efficacy of urethrocystoscopy (UCS) has been reported as good as the efficacy of mpMRI to predict muscle invasion we performed this prospective multicenter study in which we compare UCS with pathology. METHODS: From July 2020 until March 2022, 321 patients with suspected primary BC in seven participating Dutch hospitals were included in this study. A flexible UCS was performed by urologists, physician assistants, or residents. Predictions of muscle invasion using a 5-point Likert scale alongside the histopathology data were recorded. The sensitivity, specificity, predictive values, and 95% confidence intervals were determined using a standard contingency table. RESULTS: Of the 321 included patients, 232 (72.3%) received a histopathological diagnosis of non-muscle-invasive bladder cancer (NMIBC) and 71 (22.1%) were histopathologically diagnosed as MIBC. In 2 patients (0.6%), classification was not possible (Tx). Cystoscopy predicted muscle invasion with a sensitivity of 71.8% (95% CI 59.9-81.9), and a specificity of 89.9% (95% CI 85.4-93.3). This corresponds to a positive predictive value (PPV) of 67.1% and a negative predictive value (NPV) of 91.7%. CONCLUSION: Our study shows a moderate accuracy of cystoscopy to predict muscle invasion. This result does not support the use of cystoscopy only instead of TURBT for local staging.

Epigenetic markers in circulating cell-free DNA as prognostic markers for survival of castration-resistant prostate cancer patients.

BACKGROUND: Noninvasive biomarkers to guide personalized treatment for castration-resistant prostate cancer (CRPC) are needed. In this study, we analyzed hypermethylation patterns of two genes (GSTP1 and APC) in plasma cell-free DNA (cfDNA) of CRPC patients. The aim of this study was to analyze the cfDNA concentrations and levels of the epigenetic markers and to assess the value of these biomarkers for prognosis. METHODS: In this prospective study, patients were included before starting new treatment after developing CRPC. The blood samples were collected prior to start of the treatment and at three time points thereafter. cfDNA was extracted from 1.5 mL of plasma and before performing a methylation-specific PCR, bisulfate modification was carried out. RESULTS: The median levels of cfDNA, GSTP1, and APC copies in the baseline samples of CRPC patients (n = 47) were higher than in controls (n = 30). In the survival analysis, the group with baseline marker levels below median had significant less PCa-related deaths (P-values <0.02) and did not reach the median survival point. The survival distributions for the groups were statistically significant for the cfDNA concentration, GSTP1 and APC copies, as well as PSA combined with GSTP1 + APC (P-values <0.03). Furthermore, there were strong positive correlations between PSA and marker response after starting treatment (P-values <0.04). CONCLUSIONS: In conclusion, this study showed the kinetics of methylated cfDNA (GSTP1 and APC) in plasma of CRPC patients after starting treatment. Furthermore, the value of the markers before treatment is prognostic for overall survival. These results are promising for developing a test to guide treatment-decision-making for CRPC patients.

A urinary biomarker-based risk score correlates with multiparametric MRI for prostate cancer detection.

BACKGROUND: Prostate cancer (PCa) diagnostics would greatly benefit from more accurate, non-invasive techniques for the detection of clinically significant disease, leading to a reduction of over-diagnosis and over-treatment. The aim of this study was to determine the association between a novel urinary biomarker-based risk score (SelectMDx), multiparametric MRI (mpMRI) outcomes, and biopsy results for PCa detection. METHODS: This retrospective observational study used data from the validation study of the SelectMDx score, in which urine was collected after digital rectal examination from men undergoing prostate biopsies. A subset of these patients also underwent a mpMRI scan of the prostate. The indications for performing mpMRI were based on persistent clinical suspicion of PCa or local staging after PCa was found upon biopsy. All mpMRI images were centrally reviewed in 2016 by an experienced radiologist blinded for the urine test results and biopsy outcome. The PI-RADS version 2 was used. RESULTS: In total, 172 patients were included for analysis. Hundred (58%) patients had PCa detected upon prostate biopsy, of which 52 (52%) had high-grade disease correlated with a significantly higher SelectMDx score (P < 0.01). The median SelectMDx score was significantly higher in patients with a suspicious significant lesion on mpMRI compared to no suspicion of significant PCa (P < 0.01). For the prediction of mpMRI outcome, the area-under-the-curve of SelectMDx was 0.83 compared to 0.66 for PSA and 0.65 for PCA3. There was a positive association between SelectMDx score and the final PI-RADS grade. There was a statistically significant difference in SelectMDx score between PI-RADS 3 and 4 (P < 0.01) and between PI-RADS 4 and 5 (P < 0.01). CONCLUSIONS: The novel urinary biomarker-based SelectMDx score is a promising tool in PCa detection. This study showed promising results regarding the correlation between the SelectMDx score and mpMRI outcomes, outperforming PCA3. Our results suggest that this risk score could guide clinicians in identifying patients at risk for significant PCa and selecting patients for further radiological diagnostics to reduce unnecessary procedures.

Cost-effectiveness of a new urinary biomarker-based risk score compared to standard of care in prostate cancer diagnostics - a decision analytical model.

OBJECTIVE: To assess the cost-effectiveness of a new urinary biomarker-based risk score (SelectMDx; MDxHealth, Inc., Irvine, CA, USA) to identify patients for transrectal ultrasonography (TRUS)-guided biopsy and to compare this with the current standard of care (SOC), using only prostate-specific antigen (PSA) to select for TRUS-guided biopsy. MATERIALS AND METHODS: A decision tree and Markov model were developed to evaluate the cost-effectiveness of SelectMDx as a reflex test vs SOC in men with a PSA level of >3 ng/mL. Transition probabilities, utilities and costs were derived from the literature and expert opinion. Cost-effectiveness was expressed in quality-adjusted life years (QALYs) and healthcare costs of both diagnostic strategies, simulating the course of patients over a time horizon representing 18 years. Deterministic sensitivity analyses were performed to address uncertainty in assumptions. RESULTS: A diagnostic strategy including SelectMDx with a cut-off chosen at a sensitivity of 95.7% for high-grade prostate cancer resulted in savings of €128 and a gain of 0.025 QALY per patient compared to the SOC strategy. The sensitivity analyses showed that the disutility assigned to active surveillance had a high impact on the QALYs gained and the disutility attributed to TRUS-guided biopsy only slightly influenced the outcome of the model. CONCLUSION: Based on the currently available evidence, the reduction of over diagnosis and overtreatment due to the use of the SelectMDx test in men with PSA levels of >3 ng/mL may lead to a reduction in total costs per patient and a gain in QALYs.

Comparative analysis of prostate cancer specific biomarkers PCA3 and ERG in whole urine, urinary sediments and exosomes.

BACKGROUND: PCA3 and ERG are mRNA-based prostate cancer (PCa) specific biomarkers that can be detected in urine. However, urine is a complex substrate that can be separated in several fractions. In this study we compared the levels of PCa-specific biomarkers (PCA3 and ERG) and KLK3 as prostate-specific reference gene in three urine substrates-whole urine, urinary sediment (cell pellet) and exosomes-and evaluated the influence of performing a digital rectal examination (DRE) prior to urine sampling. METHODS: First-voided urine samples were prospectively obtained before and after DRE from 29 men undergoing prostate biopsies. The urine was separated in whole urine, cell pellet and exosomes and the biomarker levels were measured with RT-qPCR. RESULTS: PCa was identified in 52% (15/29) of men. In several samples the mRNA levels were below the analytical limit of detection (BDL). The biomarker levels were highest in whole urine and significantly higher after DRE in all substrates. In PCa patients higher levels of PCA3 and ERG were found in all urine substrates after DRE compared to non-PCa patients. CONCLUSIONS: This is the first study in which urinary PCa-specific biomarker levels were compared directly in three separate urine fractions. These results suggest that whole urine could be the urine substrate of choice for PCa-diagnostics based on analytical sensitivity, which is reflected directly in the high informative rate. Moreover, the significant positive effect of performing a DRE prior to urine sampling is confirmed. These findings could be of influence in the development of PCa-diagnostic urine tests.

KLK3, PCA3, and TMPRSS2-ERG expression in the peripheral blood mononuclear cell fraction from castration-resistant prostate cancer patients and response to docetaxel treatment.

BACKGROUND: To monitor systemic disease activity, the potential of circulating tumor cells (CTCs) bears great promise. As surrogate for CTCs we measured KLK3, PCA3, and TMPRSS2-ERG messenger RNA (mRNA) in the peripheral blood mononuclear cell (PBMC) fraction from a castration-resistant prostate cancer (CRPC) patient cohort and three control groups. Moreover, biomarker response to docetaxel treatment was evaluated in the patient group. METHODS: Blood samples from 20 CRPC patients were analyzed at four different time points (prior to docetaxel treatment, at 9 weeks, 27 weeks, and 2 months after treatment). Blood was drawn once from three control groups (10 age-matched men, 10 men under 35 years of age, 12 women). All samples were analyzed for KLK3, PCA3, and TMPRSS2-ERG mRNA by using a quantitative nucleic acid amplification assay with gene-specific primers in the complementary DNA synthesis. RESULTS: At baseline, mRNA for KLK3 was detected in 17 (89%, 95% CI 76-100%), PCA3 in 10 (53%, 95% CI 30-75%), and TMPRSS2-ERG in seven of 19 evaluable patients (37%, 95% CI 15-59%). In contrast, the blood samples from all 32 healthy volunteers were reproducible negative for all markers. In response to docetaxel treatment, KLK3 levels decreased in 80% (95% CI 60-100%), PCA3 in 89% (95% CI 68-100%), and TMPRSS2-ERG in 86% (95% CI 60-100%) of patients. CONCLUSIONS: The feasibility of a highly sensitive modified nucleic acid amplification assay to assess KLK3, PCA3, and TMPRSS2-ERG mRNA in the PBMC fraction from CRPC patients was demonstrated. Moreover, response of these markers to systemic treatment was shown.

Prostate cancer biomarker profiles in urinary sediments and exosomes.

PURPOSE: Urinary biomarker tests for diagnosing prostate cancer have gained considerable interest. Urine is a complex mixture that can be subfractionated. We evaluated 2 urinary fractions that contain nucleic acids, ie cell pellets and exosomes. The influence of digital rectal examination before urine collection was also studied and the prostate cancer specific biomarkers PCA3 and TMPRSS2-ERG were assayed. MATERIALS AND METHODS: Urine samples were prospectively obtained before and after digital rectal examination from 30 men scheduled for prostate biopsy. Cell pellet and exosomes were isolated and used for biomarker analysis. Analytical and diagnostic performance was tested using the Student t-test and ROC curves. RESULTS: Unlike the exosome fraction, urinary sediment gene expression analysis was compromised by amorphous precipitation in 10% of all specimens. Digital rectal examination resulted in increased mRNA levels in each fraction. This was particularly relevant for the exosomal fraction since after digital rectal examination the number of samples decreased in which cancer specific markers were below the analytical detection limit. Biomarker diagnostic performance was comparable to that in large clinical studies. In exosomes the biomarkers had to be normalized for prostate specific antigen mRNA while cell pellet absolute PCA3 levels had diagnostic value. CONCLUSIONS: Exosomes have characteristics that enable them to serve as a stable substrate for biomarker analysis. Thus, digital rectal examination enhances the analytical performance of biomarker analysis in exosomes and cell pellets. The diagnostic performance of biomarkers in exosomes differs from that of cell pellets. Clinical usefulness must be prospectively assessed in larger clinical cohorts.

The AVOCAT study: Bicalutamide monotherapy versus combined bicalutamide plus dutasteride therapy for patients with locally advanced or metastatic carcinoma of the prostate-a long-term follow-up comparison and quality of life analysis.

PURPOSE: Compare the efficacy and tolerability of dutasteride in combination with bicalutamide to bicalutamide monotherapy in the treatment of locally advanced and metastatic prostate cancer (PCa). METHODS: One-hundred-fifty PCa patients with locally advanced or metastatic disease were prospectively enrolled and randomly assigned to receive either bicalutamide monotherapy 150 mg once daily (79 patients) or bicalutamide 150 mg plus dutasteride 0.5 mg once daily (71 patients). Treatment response was assessed by serum PSA level measurement, and standard procedures for diagnosis of clinical progression were used during follow-up. Patient-reported quality of life (QoL) was assessed using validated questionnaires (EORTC QLQ-C30 and QLQ-PR25). RESULTS: At 3 years follow-up, PSA progression was found in 52 patients [65.8 %; 95 % confidence interval (CI) 55.4-76.3] in the monotherapy group compared to 38 patients (53.5 %; 95 % CI 41.9-65.1) in the combined therapy group (p = 0.134). At the time of analysis 37 men (46.8 %; 95 % CI 35.8-57.8) in the monotherapy group had died versus 30 men (42.3 %; 95 % CI 30.8-53.7) in the combined therapy group. Median survival time was 5.4 and 5.8 years, respectively (p = 0.694). There was no statistically significant difference in the presentation frequency of adverse events between groups (p = 0.683). QoL was good and comparable between the two groups. CONCLUSIONS: Both therapies were well tolerated with a good QoL. However, despite a trend toward higher efficacy of the combined therapy, progression-free survival and overall survival was not significantly different between the groups. Further research on this therapy should be performed.

Detection of High-grade Prostate Cancer Using a Urinary Molecular Biomarker-Based Risk Score.

BACKGROUND: To reduce overdiagnosis and overtreatment, a test is urgently needed to detect clinically significant prostate cancer (PCa). OBJECTIVE: To develop a multimodal model, incorporating previously identified messenger RNA (mRNA) biomarkers and traditional risk factors that could be used to identify patients with high-grade PCa (Gleason score ≥7) on prostate biopsy. DESIGN, SETTING, AND PARTICIPANTS: In two prospective multicenter studies, urine was collected for mRNA profiling after digital rectal examination (DRE) and prior to prostate biopsy. The multimodal risk score was developed on a first cohort (n=519) and subsequently validated clinically in an independent cohort (n=386). OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The mRNA levels were measured using reverse transcription quantitative polymerase chain reaction. Logistic regression was used to model patient risk and combine risk factors. Models were compared using the area under the curve (AUC) of the receiver operating characteristic, and clinical utility was evaluated with a decision curve analysis (DCA). RESULTS AND LIMITATIONS: HOXC6 and DLX1 mRNA levels were shown to be good predictors for the detection of high-grade PCa. The multimodal approach reached an overall AUC of 0.90 (95% confidence interval [CI], 0.85-0.95) in the validation cohort (AUC 0.86 in the training cohort), with the mRNA signature, prostate-specific antigen (PSA) density, and previous cancer-negative prostate biopsies as the strongest, most significant components, in addition to nonsignificant model contributions of PSA, age, and family history. For another model, which included DRE as an additional risk factor, an AUC of 0.86 (95% CI, 0.80-0.92) was obtained (AUC 0.90 in the training cohort). Both models were successfully validated, with no significant change in AUC in the validation cohort, and DCA indicated a strong net benefit and the best reduction in unnecessary biopsies compared with other clinical decision-making tools, such as the Prostate Cancer Prevention Trial risk calculator and the PCA3 assay. CONCLUSIONS: The risk score based on the mRNA liquid biopsy assay combined with traditional clinical risk factors identified men at risk of harboring high-grade PCa and resulted in a better patient risk stratification compared with current methods in clinical practice. Therefore, the risk score could reduce the number of unnecessary prostate biopsies. PATIENT SUMMARY: This study evaluated a novel urine-based assay that could be used as a noninvasive diagnostic aid for high-grade prostate cancer (PCa). When results of this assay are combined with traditional clinical risk factors, risk stratification for high-grade PCa and biopsy decision making are improved.

Potential utility of cancer-specific biomarkers for assessing response to hormonal treatments in metastatic prostate cancer.

Prostate cancer is the second leading cause of cancer death in men and there is an urgent clinical need to improve its detection and treatment. The introduction of prostate-specific antigen (PSA) as a biomarker for prostate cancer several decades ago represented an important step forward in our ability to diagnose this disease and offers the potential for earlier and more effective treatment. PSA measurements are now routinely conducted alongside digital rectal examination, with raised PSA levels leading to biopsy. PSA is also used to monitor disease and assess therapeutic response. However, there are some important limitations to its use, not least its lack of specificity for prostate cancer, and increased PSA screening may have resulted in overdiagnosis and overtreatment of early, low-risk prostate cancer. Therefore, there is a need for more specific and sensitive biomarkers for the diagnosis and monitoring of prostate cancer and treatment response; in particular, biomarkers of response to hormonal treatments in prostate cancer and predictive biomarkers to identify who is most likely to respond to these treatments. Here we review the current utilization of PSA and data on potentially more specific and sensitive biomarkers for the diagnosis and monitoring of prostate cancer: prostate cancer antigen 3 (PCA3) and the TMPRSS2-ERG fusion gene. A description of the design of an ongoing study of the 6-month extended release formulation of leuprorelin acetate (Eligard(®) 45 mg) will provide preliminary data on the potential utility of these new biomarkers for detecting therapeutic response after hormonal therapy.

Personalized management in low-risk prostate cancer: the role of biomarkers.

Current criteria to predict low-risk prostate cancer (PCa) are still subject to discussion as a substantial number of PCa patients who progress to a more aggressive disease seem to be missed, using these criteria. The main challenge in PCa diagnosis, therefore, is to distinguish patients with low-risk PCa who will show slow progression of disease from patients at risk for progression to a more aggressive cancer. The current discovered biomarkers could potentially guide in this management and improve detection, staging, and prognosis. This paper provides an overview of the current available serum-, urine-, and tissue-based biomarkers in PCa and evaluates the clinical usefulness of these biomarkers in the detection and management of low-risk PCa.