The diagnostic value of urine heat shock protein 70 and prostatic exosomal protein in chronic prostatitis.

OBJECTIVE: To explore the diagnostic value of the levels of prostatic exosomal protein (PSEP) and heat shock protein 70 (HSP70) in the urine of patients with chronic prostatitis (CP). METHOD: Urine samples from 210 CP patients (70 cases of the USA National Institutes of Health Category II [NIH-II], 70 NIH-IIIa, and 70 NIH-IIIb patients) and 70 control subjects were collected between May 2018 and February 2020. The levels of PSEP and HSP70 in urine were detected by enzyme-linked immunosorbent assay. The differences in urine PSEP and HSP70 levels between the groups were analyzed, and receiver operating characteristic (ROC) curves were used to analyze the clinical value of PSEP and HSP70 in the diagnosis of CP. RESULTS: The PSEP levels of CP patients were significantly higher than those of the control group (p < 0.001), but there was no difference in PSEP levels among CP subgroups. The level of HSP70 in the urine of the NIH-II patients was significantly lower than the levels in the NIH-IIIa and NIH-IIIb subgroups and the control group, but there was no difference in HSP70 levels between the NIH-IIIa and NIH-IIIb subgroups and the control group. ROC curve analysis results showed that the area under the curve (AUC) of PSEP for the NIH-II, NIH-IIIa, and NIH-IIIb patients was 0.751, 0.776, and 0.731, respectively. The AUC of HSP70 in NIH-II patients was 0.784, and the AUC of combined detection of PSEP and HSP70 in NIH-II patients was 0.858. CONCLUSION: Urine PSEP can be used as a marker for the diagnosis of CP, but it cannot distinguish between the various types of CP, and HSP70 can be used as a diagnostic index for NIH-II classification.

The clinical value of the prostatic exosomal protein expression in the diagnosis of chronic prostatitis: a single-center study.

OBJECTIVE: Levels of urinary prostatic exosomal protein (PSEP) were detected to evaluate the clinical potential of PSEP as a diagnostic marker of chronic prostatitis (CP). MATERIALS AND METHODS: The level of urinary PSEP was measured in 412 cases by an enzyme-linked immunosorbent assay kit, including 202 controls and 210 CP cases. Of the CP patients, 116 cases met the definition of the USA National Institutes of Health category III (NIH-III), with 60 cases of NIH-IIIA and 56 cases of NIH-IIIB. The ages, body mass indexes (BMI), white blood cell (WBC) levels in expressed prostatic secretions (EPS), lecithin body counts in EPS, urine PSEP levels both before and after prostate massage obtained from the CP patients and NIH-CPSI scores were analyzed. RESULTS: In the diagnosis of CP, the PSEP contents in the urine samples before and after prostate massage manifested a sensitivity of 86.93% vs. 61.06%, and a total coincidence rate of 85.24% vs. 61.06%, respectively. The area under the ROC curve was 0.926 vs. 0.709 for the before and after massage PSEP contents, respectively. Besides, during the follow-up of patients with CP, the improvement in symptoms was not correlated with the level changes of PSEP. CONCLUSION: Measurement of PSEP levels for the clinical diagnosis of CP is objective and painless. It could be a novel, simple, and noninvasive method for the diagnosis of CP. However, differences in fluid intake may result in a concentration or dilution of urine, which would ultimately affect the judgment of PSEP results.

MALDI MS profiling of post-DRE urine samples highlights the potential of ß-microseminoprotein as a marker for prostatic diseases.

BACKGROUND: To use spectra acquired by matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS) from pre- and post-digital rectal examination (DRE) urine samples to search for discriminating peaks that can adequately distinguish between benign and malignant prostate conditions, and identify the peaks' underlying biomolecules. METHODS: Twenty-five participants with prostate cancer (PCa) and 27 participants with a variety of benign prostatic conditions as confirmed by a 10-core tissue biopsy were included. Pre- and post-DRE urine samples were prepared for MALDI MS profiling using an automated clean-up procedure. Following mass spectra collection and processing, peak mass and intensity were extracted and subjected to statistical analysis to identify peaks capable of distinguishing between benign and cancer. Logistic regression was used to combine markers to create a sensitive and specific test. RESULTS: A peak at m/z 10,760 was identified as ß-microseminoprotein (ß-MSMB) and found to be statistically lower in urine from PCa participants using the peak's average areas. By combining serum prostate-specific antigen (PSA) levels with MALDI MS-measured ß-MSMB levels, optimum threshold values obtained from Receiver Operator characteristics curves gave an increased sensitivity of 96% at a specificity of 26%. CONCLUSIONS: These results demonstrate that with a simple sample clean-up followed by MALDI MS profiling, significant differences of MSMB abundance were found in post-DRE urine samples. In combination with PSA serum levels, obtained from a classic clinical assay led to high classification accuracy for PCa in the studied sample set. Our results need to be validated in a larger multicenter prospective randomized clinical trial.

Identification of differentially expressed proteins in direct expressed prostatic secretions of men with organ-confined versus extracapsular prostate cancer.

Current protocols for the screening of prostate cancer cannot accurately discriminate clinically indolent tumors from more aggressive ones. One reliable indicator of outcome has been the determination of organ-confined versus nonorgan-confined disease but even this determination is often only made following prostatectomy. This underscores the need to explore alternate avenues to enhance outcome prediction of prostate cancer patients. Fluids that are proximal to the prostate, such as expressed prostatic secretions (EPS), are attractive sources of potential prostate cancer biomarkers as these fluids likely bathe the tumor. Direct-EPS samples from 16 individuals with extracapsular (n = 8) or organ-confined (n = 8) prostate cancer were used as a discovery cohort, and were analyzed in duplicate by a nine-step MudPIT on a LTQ-Orbitrap XL mass spectrometer. A total of 624 unique proteins were identified by at least two unique peptides with a 0.2% false discovery rate. A semiquantitative spectral counting algorithm identified 133 significantly differentially expressed proteins in the discovery cohort. Integrative data mining prioritized 14 candidates, including two known prostate cancer biomarkers: prostate-specific antigen and prostatic acid phosphatase, which were significantly elevated in the direct-EPS from the organ-confined cancer group. These and five other candidates (SFN, MME, PARK7, TIMP1, and TGM4) were verified by Western blotting in an independent set of direct-EPS from patients with biochemically recurrent disease (n = 5) versus patients with no evidence of recurrence upon follow-up (n = 10). Lastly, we performed proof-of-concept SRM-MS-based relative quantification of the five candidates using unpurified heavy isotope-labeled synthetic peptides spiked into pools of EPS-urines from men with extracapsular and organ-confined prostate tumors. This study represents the first efforts to define the direct-EPS proteome from two major subclasses of prostate cancer using shotgun proteomics and verification in EPS-urine by SRM-MS.

Identification of prostate-enriched proteins by in-depth proteomic analyses of expressed prostatic secretions in urine.

Urinary expressed prostatic secretion or "EPS-urine" is proximal tissue fluid that is collected after a digital rectal exam (DRE). EPS-urine is a rich source of prostate-derived proteins that can be used for biomarker discovery for prostate cancer (PCa) and other prostatic diseases. We previously conducted a comprehensive proteome analysis of direct expressed prostatic secretions (EPS). In the current study, we defined the proteome of EPS-urine employing Multidimensional Protein Identification Technology (MudPIT) and providing a comprehensive catalogue of this body fluid for future biomarker studies. We identified 1022 unique proteins in a heterogeneous cohort of 11 EPS-urines derived from biopsy negative noncancer diagnoses with some benign prostatic diseases (BPH) and low-grade PCa, representative of secreted prostate and immune system-derived proteins in a urine background. We further applied MudPIT-based proteomics to generate and compare the differential proteome from a subset of pooled urines (pre-DRE) and EPS-urines (post-DRE) from noncancer and PCa patients. The direct proteomic comparison of these highly controlled patient sample pools enabled us to define a list of prostate-enriched proteins detectable in EPS-urine and distinguishable from a complex urine protein background. A combinatorial analysis of both proteomics data sets and systematic integration with publicly available proteomics data of related body fluids, human tissue transcriptomic data, and immunohistochemistry images from the Human Protein Atlas database allowed us to demarcate a robust panel of 49 prostate-derived proteins in EPS-urine. Finally, we validated the expression of seven of these proteins using Western blotting, supporting the likelihood that they originate from the prostate. The definition of these prostatic proteins in EPS-urine samples provides a reference for future investigations for prostatic-disease biomarker studies.

The rs10993994 risk allele for prostate cancer results in clinically relevant changes in microseminoprotein-beta expression in tissue and urine.

BACKGROUND: Microseminoprotein-beta (MSMB) regulates apoptosis and using genome-wide association studies the rs10993994 single nucleotide polymorphism in the MSMB promoter has been linked to an increased risk of developing prostate cancer. The promoter location of the risk allele, and its ability to reduce promoter activity, suggested that the rs10993994 risk allele could result in lowered MSMB in benign tissue leading to increased prostate cancer risk. METHODOLOGY/PRINCIPAL FINDINGS: MSMB expression in benign and malignant prostate tissue was examined using immunohistochemistry and compared with the rs10993994 genotype. Urinary MSMB concentrations were determined by ELISA and correlated with urinary PSA, the presence or absence of cancer, rs10993994 genotype and age of onset. MSMB levels in prostate tissue and urine were greatly reduced with tumourigenesis. Urinary MSMB was better than urinary PSA at differentiating men with prostate cancer at all Gleason grades. The high risk allele was associated with heterogeneity of MSMB staining and loss of MSMB in both tissue and urine in benign prostate. CONCLUSIONS: These data show that some high risk alleles discovered using genome-wide association studies produce phenotypic effects with potential clinical utility. We provide the first link between a low penetrance polymorphism for prostate cancer and a potential test in human tissue and bodily fluids. There is potential to develop tissue and urinary MSMB for a biomarker of prostate cancer risk, diagnosis and disease monitoring.