Prostate health index and prostate cancer gene 3 score but not percent-free Prostate Specific Antigen have a predictive role in differentiating histological prostatitis from PCa and other nonneoplastic lesions (BPH and HG-PIN) at repeat biopsy

Peripheral zone PSA density: a predominant variable to improve prostate cancer detection efficiency in men with PSA higher than 4 ng ml-1

To improve the diagnostic efficiency of prostate cancer (PCa) and reduce unnecessary biopsies, we defined and analyzed the diagnostic efficiency of peripheral zone prostate-specific antigen (PSA) density (PZ-PSAD). Patients who underwent systematic 12-core prostate biopsies in Shanghai General Hospital (Shanghai, China) between January 2012 and January 2018 were retrospectively identified (n = 529). Another group of patients with benign prostatic hyperplasia (n = 100) were randomly preselected to obtain the PSA density of the non-PCa cohort (N-PSAD). Prostate volumes and transition zone volumes were measured using multiparameter magnetic resonance imaging (mpMRI) and were combined with PSA and N-PSAD to obtain the PZ-PSAD from a specific algorithm. Receiver operating characteristic (ROC) curve analysis was used to assess the PCa detection efficiency in patients stratified by PSA level, and the area under the ROC curve (AUC) of PZ-PSAD was higher than that of PSA, PSA density (PSAD), and transition zone PSA density (TZ-PSAD). PZ-PSAD could amend the diagnosis for more than half of the patients with inaccurate transrectal ultrasonography (TRUS) and mpMRI results. When TRUS and mpMRI findings were ambiguous to predict PCa (PIRADS score ≤3), PZ-PSAD could increase the positive rate of biopsy from 21.7% to 54.7%, and help 63.8% (150/235) of patients avoid unnecessary prostate biopsy. In patients whose PSA was 4.0-10.0 ng ml-1, 10.1-20.0 ng ml-1, and >20.0 ng ml-1, the ideal PZ-PSAD cut-off value for predicting clinically significant PCa was 0.019 ng ml-2, 0.297 ng ml-2, and 1.180 ng ml-2, respectively (sensitivity >90%). Compared with PSA, PSAD, and TZ-PSAD, the efficiency of PZ-PSAD for predicting PCa is the highest, leading to fewer missed diagnoses and unnecessary biopsies.

The Percentage of Free PSA and Urinary Markers Distinguish Prostate Cancer from Benign Hyperplasia and Contribute to a More Accurate Indication for Prostate Biopsy

The main advantage of urinary biomarkers is their noninvasive character and the ability to detect multifocal prostate cancer (CaP). We have previously implemented a quadruplex assay of urinary markers into clinical practice (PCA3, AMACR, TRPM8 and MSMB with KLK3 normalization). In this study, we aimed to validate it in a larger cohort with serum PSA 2.5-10 ng/mL and test other selected transcripts and clinical parameters, including the percentage of free prostate-specific antigen (PSA) (% free PSA) and inflammation. In the main cohort of 299 men, we tested the quadruplex transcripts. In a subset of 146 men, we analyzed additional transcripts (CD45, EPCAM, EZH2, Ki67, PA2G4, PSGR, RHOA and TBP). After a prostate massage, the urine was collected, RNA isolated from a cell sediment and qRT-PCR performed. Ct values of KLK3 (i.e., PSA) were strongly correlated with Ct values of other genes which play a role in CaP (i.e., PCA3, AMACR, TRPM8, MSMB and PSGR). AMACR, PCA3, TRPM8 and EZH2 mRNA expression, as well as % free PSA, were significantly different for BPH and CaP. The best combined model (% free PSA plus PCA3 and AMACR) achieved an AUC of 0.728 in the main cohort. In the subset of patients, the best AUC 0.753 was achieved for the combination of PCA3, % free PSA, EPCAM and PSGR. PCA3 mRNA was increased in patients with inflammation, however, this did not affect the stratification of patients indicated for prostate biopsy. In conclusion, the percentage of free PSA and urinary markers contribute to a more accurate indication for prostate biopsy.

Impact of Histopathological Prostate Inflammation on Urine-Based Prostate Cancer Prediction Using the Prostate Cancer Gene 3 Score

INTRODUCTION

The Prostate Cancer gene 3 (PCA3) urine test has gained importance in the diagnostic workup of prostate cancer (PC). Limited evidence suggests that PCA3 is not altered in the presence of inflammation.

OBJECTIVE

To assess the impact of histological inflammation on PCA3.

METHODS

PCA3 was evaluated in patients prior to prostate biopsy (n = 193) and to radical prostatectomy (n = 197). In patients without PC, inflammation was assessed and quantified by individual scores integrating grade and extent. Uni- and multivariate analyses were performed to assess the impact of inflammation grade on PCA3.

RESULTS

The PCA3 scores prior to prostatectomy were lower (median 45) than those before positive biopsy (57; p = 0.008). Of 101 negative biopsies, 78% showed inflammation. The median PCA3 scores in the groups with no inflammation and with maximum grade 1 (n = 22), 2 (n = 38), and 3 (n = 19) inflammation were 45, 38, 27, and 25 (p = 0.016). The multivariate models revealed a decrease in PCA3 proportional to the grade and extent of inflammation (p < 0.04 each).

CONCLUSIONS

The present data imply that the PCA3 score decreases in the presence of inflammation, which is relevant, for instance, to testing after a recently performed biopsy. In general, inflammation should be regarded as a factor putatively influencing PCA3 and other available and upcoming PC tests.

Inflammation appears as high Prostate Imaging-Reporting and Data System scores on prostate magnetic resonance imaging (MRI) leading to false positive MRI fusion biopsy

Purpose

To investigate if inflammation as a potential cause of false-positive lesions from recent UroNav magnetic resonance imaging (MRI) fusion prostate biopsy patients.

Materials and Methods

We retrospectively identified 43 men with 61 MRI lesions noted on prostate MRI before MRI ultrasound-guided fusion prostate biopsy. Men underwent MRI with 3T Siemens TIM Trio MRI system (Siemens AG, Germany), and lesions were identified and marked in DynaCAD system (Invivo Corporation, USA) with subsequent biopsy with MRI fusion with UroNav. We obtained targeted and standard 12-core needle biopsies. We retrospectively reviewed pathology reports for inflammation.

Results

We noted a total of 43 (70.5%) false-positive lesions with 28 having no cancer on any cores, and 15 lesions with cancer noted on systematic biopsy but not in the target region. Of the men with cancer, 6 of the false positive lesions had inflammation in the location of the targeted region of interest (40.0%, 6/15). However, when we examine the 21/28 lesions with an identified lesion on MRI with no cancer in all cores, 54.5% had inflammation on prostate biopsy pathology (12/22, p=0.024). We noted the highest proportion of inflammation.

Conclusions

Inflammation can confound the interpretation of MRI by mimicking prostate cancer. We suggested focused efforts to differentiate inflammation and cancer on prostate MRI.

MultiParametric Magnetic Resonance Imaging-Based Nomogram for Predicting Prostate Cancer and Clinically Significant Prostate Cancer in Men Undergoing Repeat Prostate Biopsy

OBJECTIVE

To develop and internally validate nomograms based on multiparametric magnetic resonance imaging (mpMRI) to predict prostate cancer (PCa) and clinically significant prostate cancer (csPCa) in patients with a previous negative prostate biopsy.

MATERIALS AND METHODS

The clinicopathological parameters of 231 patients who underwent a repeat systematic prostate biopsy and mpMRI were reviewed. Based on Prostate Imaging and Reporting Data System, the mpMRI results were assigned into three groups: Groups "negative," "suspicious," and "positive." Two clinical nomograms for predicting the probabilities of PCa and csPCa were constructed. The performances of nomograms were assessed using area under the receiver operating characteristic curves (AUCs), calibrations, and decision curve analysis.

RESULTS

The median PSA was 15.03 ng/ml and abnormal DRE was presented in 14.3% of patients in the entire cohort. PCa was detected in 75 patients (32.5%), and 59 (25.5%) were diagnosed with csPCa. In multivariate analysis, age, prostate-specific antigen (PSA), prostate volume (PV), digital rectal examination (DRE), and mpMRI finding were significantly independent predictors for PCa and csPCa (all p < 0.01). Of those patients diagnosed with PCa or csPCa, 20/75 (26.7%) and 18/59 (30.5%) had abnormal DRE finding, respectively. Two mpMRI-based nomograms with super predictive accuracy were constructed (AUCs = 0.878 and 0.927, p < 0.001), and both exhibited excellent calibration. Decision curve analysis also demonstrated a high net benefit across a wide range of probability thresholds.

CONCLUSION

mpMRI combined with age, PSA, PV, and DRE can help predict the probability of PCa and csPCa in patients who underwent a repeat systematic prostate biopsy after a previous negative biopsy. The two nomograms may aid the decision-making process in men with prior benign histology before the performance of repeat prostate biopsy.

Quantitative Mass Spectrometry-Based Proteomic Profiling for Precision Medicine in Prostate Cancer

Prostate cancer (PCa) is one of the most frequently diagnosed cancer among men in the western societies. Many PCa patients bear tumors that will not threat their lives if left untreated or if treatment is delayed. Our inability for early identification of these patients has resulted in massive overtreatment. Therefore, there is a great need of finding biomarkers for patient stratification according to prognostic risk; as well as there is a need for novel targets that can allow the development of effective treatments for patients that progress to castration-resistant PCa. Most biomarkers in cancer are proteins, including the widely-used prostate-specific antigen (PSA). Recent developments in mass spectrometry allow the identification and quantification of thousands of proteins and posttranslational modifications from small amounts of biological material, including formalin-fixed paraffin-embedded tissues, and biological fluids. Novel diagnostic and prognostic biomarkers have been identified in tissue, blood, urine, and seminal plasma of PCa patients, and new insights in the ethology and progression of this disease have been achieved using this technology. In this review, we summarize these findings and discuss the potential of this technology to pave the way toward the clinical implementation of precision medicine in PCa.

Validity of Prostate Health Index and Percentage of [-2] Pro-Prostate-Specific Antigen as Novel Biomarkers in the Diagnosis of Prostate Cancer: Omani Tertiary Hospitals Experience

OBJECTIVES

Prostate cancer is the leading cancer in older men. The Ministry of Health Oman Cancer Incidence Registry 2013 lists cancer of the prostate as the first most common cancer in males. Therefore, early detection is important and prostate-specific antigen (PSA) is widely used as an established laboratory test. However, despite its wide use, its value in screening, particularly in asymptomatic males, is controversial when considering the risks and benefits of early detection.

METHODS

This prospective, observational study included 136 males (67.0±8.9 years; range 45-90) who were scheduled for a prostate biopsy in two different tertiary care teaching hospitals in Oman: the Royal Hospital and Sultan Qaboos University Hospital. Blood specimens from these patients were collected at the same setting before obtaining a prostatic biopsy. Three PSA markers (total PSA (tPSA), free PSA (fPSA), and [-2]proPSA (p2PSA)) were measured and the Prostate Health Index (phi) calculated. The histopathological report of the prostatic biopsy for each patient was obtained from the histopathology laboratory of the concerned hospital along with clinical and laboratory data through the hospital information system.

RESULTS

Phi has the highest validity markers compared with other prostate markers, with a sensitivity of 82.1%, specificity of 80.6%, and area under the curve (AUC) value of 0.81 at a cutoff of 41.9. The other prostatic markers showed sensitivities and specificities of 78.6% and 25.9% for tPSA; 35.7% and 92.6% for %fPSA; and 64.3% and 82.4% for %p2PSA, respectively. The AUCs at the best cutoff values were 0.67 at 10.1 µg/L for tPSA; 0.70 at 11.6% for %fPSA; and 0.55 at 1.4% for %p2PSA. An association between phi values and aggressiveness of prostate malignancy was noted. Of the 28 patients with prostate cancer, 22 patients had tPSA > 4 µg/L. However, no patient had phi in the low-risk category, and five, six, and 17 patients had phi in the moderate-, high-, and very high-risk categories, respectively.

CONCLUSIONS

Phi outperforms tPSA and fPSA when used alone or in combination, and appears to be more accurate than both markers in excluding prostate cancer before biopsy. Use of this biomarker helps clinicians to avoid unnecessary biopsies, particularly in patients with gray-zone tPSA level. Phi is the strongest marker that correlates proportionally with Gleason Score; therefore, it is also useful in predicting the aggressiveness of the disease. This is the first reported experience for the use of p2PSA and phi in Oman, the Middle East, and North Africa.