Urinary extracellular vesicle-derived miR-126-3p predicts lymph node invasion in patients with high-risk prostate cancer.

To investigate extracellular vesicles (EVs), biomarkers for predicting lymph node invasion (LNI) in patients with high-risk prostate cancer (HRPCa), plasma, and/or urine samples were prospectively collected from 45 patients with prostate cancer (PCa) and five with benign prostatic hyperplasia (BPH). Small RNA sequencing was performed to identify miRNAs in the EVs. All patients with PCa underwent radical prostatectomy and extended pelvic lymph node dissection. Differentially expressed miRNAs were identified in patients with and without pathologically-verified LNI. The candidate miRNAs were validated in low-risk prostate cancer (LRPCa) and BPH. Four miRNA species (e.g., miR-126-3p) and three miRNA species (e.g., miR-27a-3p) were more abundant in urinary and plasma EVs, respectively, of patients with PCa. None of these miRNA species were shared between urinary and plasma EVs. miR-126-3p was significantly more abundant in patients with HR PCa with LNI than in those without (P = 0.018). miR-126-3p was significantly more abundant in the urinary EVs of patients with HRPCa than in those with LRPCa (P = 0.017) and BPH (P = 0.011). In conclusion, urinary EVs-derived miR-126-3p may serve as a good biomarker for predicting LNI in patients with HRPCa.

Comprehensive Prostate Fluid-Based Spectral Libraries for Enhanced Protein Detection in Urine.

Biofluids contain molecules in circulation and from nearby organs that can be indicative of disease states. Characterizing the proteome of biofluids with DIA-MS is an emerging area of interest for biomarker discovery; yet, there is limited consensus on DIA-MS data analysis approaches for analyzing large numbers of biofluids. To evaluate various DIA-MS workflows, we collected urine from a clinically heterogeneous cohort of prostate cancer patients and acquired data in DDA and DIA scan modes. We then searched the DIA data against urine spectral libraries generated using common library generation approaches or a library-free method. We show that DIA-MS doubles the sample throughput compared to standard DDA-MS with minimal losses to peptide detection. We further demonstrate that using a sample-specific spectral library generated from individual urines maximizes peptide detection compared to a library-free approach, a pan-human library, or libraries generated from pooled, fractionated urines. Adding urine subproteomes, such as the urinary extracellular vesicular proteome, to the urine spectral library further improves the detection of prostate proteins in unfractionated urine. Altogether, we present an optimized DIA-MS workflow and provide several high-quality, comprehensive prostate cancer urine spectral libraries that can streamline future biomarker discovery studies of prostate cancer using DIA-MS.

VOC-based detection of prostate cancer using an electronic nose and ion mobility spectrometry: A novel urine-based approach.

BACKGROUND: Many diseases leave behind specific metabolites which can be detected from breath and urine as volatile organic compounds (VOC). Our group previously described VOC-based methods for the detection of bladder cancer and urinary tract infections. This study investigated whether prostate cancer can be diagnosed from VOCs in urine headspace. METHODS: For this pilot study, mid-stream urine samples were collected from 56 patients with histologically confirmed prostate cancer. A control group was formed with 53 healthy male volunteers matched for age who had recently undergone a negative screening by prostate-specific antigen (PSA) and digital rectal exam. Headspace measurements were performed with the electronic nose Cyranose 320TM. Statistical comparison was performed using principal component analysis, calculating Mahalanobis distance, and linear discriminant analysis. Further measurements were carried out with ion mobility spectrometry (IMS) to compare detection accuracy and to identify potential individual analytes. Bonferroni correction was applied for multiple testing. RESULTS: The electronic nose yielded a sensitivity of 77% and specificity of 62%. Mahalanobis distance was 0.964, which is indicative of limited group separation. IMS identified a total of 38 individual analytical peaks, two of which showed significant differences between groups (p < 0.05). To discriminate between tumor and controls, a decision tree with nine steps was generated. This model led to a sensitivity of 98% and specificity of 100%. CONCLUSIONS: VOC-based detection of prostate cancer seems feasible in principle. While the first results with an electronic nose show some limitations, the approach can compete with other urine-based marker systems. However, it seems less reliable than PSA testing. IMS is more accurate than the electronic nose with promising sensitivity and specificity, which warrants further research. The individual relevant metabolites identified by IMS should further be characterized using gas chromatography/mass spectrometry to facilitate potential targeted rapid testing.

Prediction of clinically significant prostate cancer through urine metabolomic signatures: A large-scale validated study.

PURPOSE: Currently, there are no accurate markers for predicting potentially lethal prostate cancer (PC) before biopsy. This study aimed to develop urine tests to predict clinically significant PC (sPC) in men at risk. METHODS: Urine samples from 928 men, namely, 660 PC patients and 268 benign subjects, were analyzed by gas chromatography/quadrupole time-of-flight mass spectrophotometry (GC/Q-TOF MS) metabolomic profiling to construct four predictive models. Model I discriminated between PC and benign cases. Models II, III, and GS, respectively, predicted sPC in those classified as having favorable intermediate risk or higher, unfavorable intermediate risk or higher (according to the National Comprehensive Cancer Network risk groupings), and a Gleason sum (GS) of ≥ 7. Multivariable logistic regression was used to evaluate the area under the receiver operating characteristic curves (AUC). RESULTS: In Models I, II, III, and GS, the best AUCs (0.94, 0.85, 0.82, and 0.80, respectively; training cohort, N = 603) involved 26, 24, 26, and 22 metabolites, respectively. The addition of five clinical risk factors (serum prostate-specific antigen, patient age, previous negative biopsy, digital rectal examination, and family history) significantly improved the AUCs of the models (0.95, 0.92, 0.92, and 0.87, respectively). At 90% sensitivity, 48%, 47%, 50%, and 36% of unnecessary biopsies could be avoided. These models were successfully validated against an independent validation cohort (N = 325). Decision curve analysis showed a significant clinical net benefit with each combined model at low threshold probabilities. Models II and III were more robust and clinically relevant than Model GS. CONCLUSION: This urine test, which combines urine metabolic markers and clinical factors, may be used to predict sPC and thereby inform the necessity of biopsy in men with an elevated PC risk.

Nanoarchitectonics-Assisted Simultaneous Fluorescence Detection of Urinary Dual miRNAs for Noninvasive Diagnosis of Prostate Cancer.

Herein, we report a fluorescence strategy for the homogeneous and simultaneous analysis of urine miRNA-375 and miRNA-148a. The target miRNAs in urine bonded the devised dumbbell-shaped "C-Ag+-C" and "T-Hg2+-T" hairpin structures that could trigger cascade enzyme-free amplification. Then, the fluorescent CdTe quantum dots (QDs) and carbon dots (CDs) could selectively recognize Ag+ and Hg2+, to quantify the dual miRNAs concurrently. Under optimized conditions, the linear range was from 0.1 to 1000 fM and the limits of detection (LOD) for dual miRNAs reached 30 and 25 aM, respectively. The practicality was further evaluated with 45 clinical urine samples including prostate cancer (PC) and other patients, and the results were consistent with the clinical polymerase chain reaction (PCR) kit and ultrasonic and pathological findings. The receiver operating characteristic (ROC) curve analysis showed that the estimates of the area under the curve (AUC) were 0.739 for the serum prostate-specific antigen (PSA) and 0.941 for miRNA-375 and 0.946 for miRNA-148a. The sensitivity and specificity reached 75 and 100% for miRNA-375 and 71 and 94% for miRNA-148a, respectively, which was better than serum PSA. This strategy constructed a reliable system for dual miRNA detection in urine samples and proposed new insights into the rapid and noninvasive diagnosis of PC.

Urine-derived exosomal PSMA is a promising diagnostic biomarker for the detection of prostate cancer on initial biopsy

Purpose It is well-established that the lack of accurate diagnostic modalities for prostate cancer (PCa) leads to overdiagnosis and overtreatments. Accordingly, this study aimed to assess the value of urine-derived exosomal prostate-specific membrane antigen (PSMA) as a biomarker for the diagnosis of PCa and clinically significant prostate cancer (csPCa). Methods A total of 284 urine samples were collected from patients after the digital rectal examination (DRE). Urinary exosomes were extracted using commercial kits, and urine-derived exosomal PSMA was determined via enzyme-linked immunosorbent assay (ELISA). Evaluation of diagnostic accuracy of PSMA was performed via receiver operating characteristic (ROC) analysis, decision curve analysis (DCA), and waterfall plots. Results We found that urine-derived exosomal PSMA was significantly higher in PCa and csPCa than in benign prostatic hyperplasia (BPH) and BPH + non-aggressive prostate cancer (naPCa) groups (P < 0.001). Furthermore, the urine-derived exosome PSMA yielded area under the ROC curve (AUC) values of 0.876 and 0.826 for detecting PCa and csPCa, respectively, suggesting better performance than traditional clinical biomarkers. Besides, when the cutoff value used corresponded to a sensitivity of 95%, urine-derived exosomal PSMA could avoid unnecessary biopsies in 41.2% of cases and missed only 0.7% of csPCa cases. Conclusions Urine-derived exosomal PSMA exhibits a good diagnostic yield for detecting PCa and csPCa. Findings of the present study provide the foothold for future studies on cancer management and research in this patient population (AU)

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.

Tracking Prostate Carcinogenesis over Time through Urine Proteome Profiling in an Animal Model: An Exploratory Approach.

Prostate cancer (PCa) is one of the most lethal diseases in men, which justifies the search for new diagnostic tools. The aim of the present study was to gain new insights into the progression of prostate carcinogenesis by analyzing the urine proteome. To this end, urine from healthy animals and animals with prostate adenocarcinoma was analyzed at two time points: 27 and 54 weeks. After 54 weeks, the incidence of pre-neoplastic and neoplastic lesions in the PCa animals was 100%. GeLC-MS/MS and subsequent bioinformatics analyses revealed several proteins involved in prostate carcinogenesis. Increased levels of retinol-binding protein 4 and decreased levels of cadherin-2 appear to be characteristic of early stages of the disease, whereas increased levels of enolase-1 and T-kininogen 2 and decreased levels of isocitrate dehydrogenase 2 describe more advanced stages. With increasing age, urinary levels of clusterin and corticosteroid-binding globulin increased and neprilysin levels decreased, all of which appear to play a role in prostate hyperplasia or carcinogenesis. The present exploratory analysis can be considered as a starting point for studies targeting specific human urine proteins for early detection of age-related maladaptive changes in the prostate that may lead to cancer.

Aptamer-antibody hybrid ELONA that uses hybridization chain reaction to detect a urinary biomarker EN2 for bladder and prostate cancer.

We report an EN2-specific (Kd = 8.26 nM) aptamer, and a sensitive and specific enzyme-linked oligonucleotide assay (ELONA) for rapid and sensitive colorimetric detection of bladder and prostate cancer biomarker EN2 in urine. The assay relies on an aptamer-mediated hybridization chain reaction (HCR) to generate DNA nanostructures that bind to EN2 and simultaneously amplify signals. The assay can be performed within 2.5 h, and has a limit of detection of 0.34 nM in buffer and 2.69 nM in artificial urine. Moreover, this assay showed high specificity as it did not detect other urinary proteins, including biomarkers of other cancers. The proposed ELONA is inexpensive, highly reproducible, and has great chemical stability, so it may enable development of a simple, sensitive and accurate diagnostic tool to detect bladder and prostate cancers early.

Accuracy of a new electronic nose for prostate cancer diagnosis in urine samples.

OBJECTIVE: To evaluate the accuracy of a new electronic nose to recognize prostate cancer in urine samples. METHODS: A blind, prospective study on consecutive patients was designed. Overall, 174 subjects were included in the study: 88 (50.6%) in prostate cancer group, and 86 (49.4%) in control group. Electronic nose performance for prostate cancer was assessed using sensitivity and specificity. The diagnostic accuracy of electronic nose was reported as area under the receiver operating characteristic curve. RESULTS: The electronic nose in the study population reached a sensitivity 85.2% (95% confidence interval 76.1-91.9; 13 false negatives out of 88), a specificity 79.1% (95% confidence interval 69.0-87.1; 18 false positives out of 86). The accuracy of the electronic nose represented as area under the receiver operating characteristic curve 0.821 (95% confidence interval 0.764-0.879). CONCLUSIONS: The diagnostic accuracy of electronic nose for recognizing prostate cancer in urine samples is high, promising and susceptible to supplemental improvement. Additionally, further studies will be necessary to design a clinical trial to validate electronic nose application in diagnostic prostate cancer nomograms.

The ReIMAGINE prostate cancer risk study protocol: A prospective cohort study in men with a suspicion of prostate cancer who are referred onto an MRI-based diagnostic pathway with donation of tissue, blood and urine for biomarker analyses.

INTRODUCTION: The ReIMAGINE Consortium was conceived to develop risk-stratification models that might incorporate the full range of novel prostate cancer (PCa) diagnostics (both commercial and academic). METHODS: ReIMAGINE Risk is an ethics approved (19/LO/1128) multicentre, prospective, observational cohort study which will recruit 1000 treatment-naive men undergoing a multi-parametric MRI (mpMRI) due to an elevated PSA (≤20ng/ml) or abnormal prostate examination who subsequently had a suspicious mpMRI (score≥3, stage ≤T3bN0M0). Primary outcomes include the detection of ≥Gleason 7 PCa at baseline and time to clinical progression, metastasis and death. Baseline blood, urine, and biopsy cores for fresh prostate tissue samples (2 targeted and 1 non-targeted) will be biobanked for future analysis. High-resolution scanning of pathology whole-slide imaging and MRI-DICOM images will be collected. Consortium partners will be granted access to data and biobanks to develop and validate biomarkers using correlation to mpMRI, biopsy-based disease status and long-term clinical outcomes. RESULTS: Recruitment began in September 2019(n = 533). A first site opened in September 2019 (n = 296), a second in November 2019 (n = 210) and a third in December 2020 (n = 27). Acceptance to the study has been 65% and a mean of 36.5ml(SD+/-10.0), 12.9ml(SD+/-3.7) and 2.8ml(SD+/-0.7) urine, plasma and serum donated for research, respectively. There are currently 4 academic and 15 commercial partners spanning imaging (~9 radiomics, artificial intelligence/machine learning), fluidic (~3 blood-based and ~2urine-based) and tissue-based (~1) biomarkers. CONCLUSION: The consortium will develop, or adjust, risk models for PCa, and provide a platform for evaluating the role of novel diagnostics in the era of pre-biopsy MRI and targeted biopsy.

Detecting disease associated biomarkers by luminescence modulating phages.

Assessment of risk for a given disease and the diagnosis of diseases is often based on assays detecting biomarkers. Antibody-based biomarker-assays for diseases such as prostate cancer are often ambiguous and biomarker proteins are frequently also elevated for reasons that are unspecific. We have opted to use luminescence modulating phages for the analysis of known acute inflammatory response biomarker CRP (C-reactive protein) and biomarkers of prostate cancer in urine samples. Firstly, CRP was used to simulate the detection process in a controlled chemical environment. Secondly, we tried to classify more challenging lethal prostate cancer samples from control samples. Our unique method utilizes a special biopanning process in order to create special phages capable of capturing a dye necessary for detection and potential biomarkers. As the biomarker-molecules interfere with the phages, dye is repelled from the phage network resulting in an altered reporter luminescence. These changes can be observed with an absorbance reader and even with the naked eye. The simple method could present an alternative for screening of disease biomarkers. For prostate cancer urine samples, we achieved a sensitivity of 80% and specificity of 75% to detect Grade Group (GG) 4 and 5 prostate cancer.

Liquid biomarkers in active surveillance.

PURPOSE: In the past two decades, new biomarkers for prostate cancer detection and risk prediction have become available for clinical use. While tissue-based gene expression assays offer molecular risk assessment after diagnoses, several serum- and urine-based 'liquid' biomarkers are available for the pre-biopsy setting which may also play a role for active surveillance (AS). METHODS: The medical literature was queried utilizing PubMed (pubmed.ncbi.nlm.nih.gov) for all relevant original publications describing prostate cancer biomarkers that can be identified in the blood, urine, or semen. Referenced studies must have defined patient inclusion criteria and descriptions of the biomarkers. Included studies investigated the utility of liquid biomarkers for selection or monitoring of men with prostate cancer for active surveillance. RESULTS: PSA is the most common and readily available biomarker for prostate cancer diagnosis and treatment. Contemporary AS guidelines consider diagnostic PSA level in addition to other clinical factors when selecting men for this approach, with most recommending that initial PSA should be under 10 ng/ml. Serum PSA changes are associated with outcomes on AS but are not adequately sensitive so drive men to secondary treatment in isolation. PSA derivates including the Prostate Health Index (phi) and the 4K Score can predict higher grade cancer and may help tailor repeat prostate biopsy strategies, but further data are needed prior to routine clinic use. Several urine-based biomarkers including PCA3 and TMPRSS2:ERG levels have also been studied in the AS setting. CONCLUSIONS: Multiple serum- and urine-based liquid biomarkers are available for use in men with prostate cancer. For AS, serum PSA is utilized in part for patient selection as well as to monitor disease over time. Models that incorporate PSA kinetics with other clinical characteristics may help tailor surveillance strategies to reduce disease burden and health care costs over time. Several novel liquid biomarkers demonstrate promise and may eventually have applications for prostate cancer surveillance as well.

Association of MyProstateScore (MPS) with prostate cancer grade in the radical prostatectomy specimen.

BACKGROUND: To evaluate the association between urinary MyProstateScore (MPS) and pathologic grade group (GG) at surgery in men diagnosed with GG1 prostate cancer (PCa) on biopsy. METHODS: Using an institutional biospecimen protocol, we identified men with GG1 PCa on biopsy and PSA ≤10 ng/ml who underwent radical prostatectomy (RP) at the University of Michigan. MPS was retrospectively calculated using prospectively collected, post-DRE urine samples. The primary outcome was upgrading on RP pathology, defined as GG ≥ 2. The associations of MPS, PSA, and PSA density (PSAD) with upgrading were assessed on univariable logistic regression, and the predictive accuracy of each marker was estimated by the area under the receiver operating characteristic curve (AUC). RESULTS: There were 52 men with urinary specimens available that met study criteria, based on biopsy Gleason Grade and specimen collection. At RP, 17 men (33%) had GG1 cancer and 35 (67%) had GG ≥ 2 cancer. Preoperative MPS was significantly higher in patients with GG ≥ 2 cancer at surgery (median 37.8 [IQR, 22.2-52.4]) as compared to GG1 (19.3 [IQR, 9.2-29.4]; P = 0.001). On univariable logistic regression, increasing MPS values were significantly associated with upgrading (odds ratio 1.07 per one-unit MPS increase, 95% confidence interval 1.02-1.12, P = 0.004), while PSA and PSAD were not significantly associated with upgrading. Similarly, the discriminative ability of the MPS model (AUC 0.78) for upgrading at RP was higher compared to models based on PSA (AUC 0.52) and PSAD (AUC 0.62). CONCLUSIONS: In men diagnosed with GG1 PCa who underwent surgery, MPS was significantly associated with RP cancer grade. In this limited cohort of men, these findings suggest that MPS could help identify patients with undetected high-grade cancer. Additional studies are needed to better characterize this association.

Potential of miRNAs in urinary extracellular vesicles for management of active surveillance in prostate cancer patients.

BACKGROUND: Active surveillance is an alternative to radical treatment for patients with low-risk prostate cancer, which could also benefit some patients with intermediate risk. We have investigated the use of miRNA in urinary extracellular vesicles to stratify these patients. METHODS: NGS was performed to profile the miRNAs from small urinary extracellular vesicles in a cohort of 70 patients with prostate cancer ISUP Grade 1, 2 or 3. The most promising candidates were then analysed by RT-qPCR in a new cohort of 60 patients. RESULTS: NGS analysis identified nine miRNAs differentially expressed in at least one of the comparisons. The largest differences were found with miR-1290 (Grade 3 vs. 1), miR-320a-3p (Grade 3 vs. 2) and miR-155-5p (Grade 2 vs. 1). Combinations of 2-3 miRNAs were able to differentiate between two ISUP grades with an AUC 0.79-0.88. RT-qPCR analysis showed a similar trend for miR-186-5p and miR-30e-5p to separate Grade 3 from 2, and miR-320a-3p to separate Grade 2 from 1. CONCLUSIONS: Using NGS, we have identified several miRNAs that discriminate between prostate cancer patients with ISUP Grades 1, 2 and 3. Moreover, miR-186-5p, miR-320a-3p and miR-30e-5p showed a similar behaviour in an independent cohort using an alternative analytical method. Our results show that miRNAs from urinary vesicles can be potentially useful as liquid biopsies for active surveillance.

Optimization of training and measurement protocol for eNose analysis of urine headspace aimed at prostate cancer diagnosis.

More than one million new cases of prostate cancer (PCa) were reported worldwide in 2020, and a significant increase of PCa incidence up to 2040 is estimated. Despite potential treatability in early stages, PCa diagnosis is challenging because of late symptoms' onset and limits of current screening procedures. It has been now accepted that cell transformation leads to release of volatile organic compounds in biologic fluids, including urine. Thus, several studies proposed the possibility to develop new diagnostic tools based on urine analysis. Among these, electronic noses (eNoses) represent one of the most promising devices, because of their potential to provide a non-invasive diagnosis. Here we describe the approach aimed at defining the experimental protocol for eNose application for PCa diagnosis. Our research investigates effects of sample preparation and analysis on eNose responses and repeatability. The dependence of eNose diagnostic performance on urine portion analysed, techniques involved for extracting urine volatiles and conditioning temperature were analysed. 192 subjects (132 PCa patients and 60 controls) were involved. The developed experimental protocol has resulted in accuracy, sensitivity and specificity of 83% (CI95% 77-89), 82% (CI95% 73-88) and 87% (CI95% 75-94), respectively. Our findings define eNoses as valuable diagnostic tool allowing rapid and non-invasive PCa diagnosis.

Isolation and characterization of urine microvesicles from prostate cancer patients: different approaches, different visions.

BACKGROUND: Because of their specific and biologically relevant cargo, urine extracellular vesicles (EVs) constitute a valuable source of potential non-invasive biomarkers that could support the clinical decision-making to improve the management of prostate cancer (PCa) patients. Different EV isolation methods differ in terms of complexity and yield, conditioning, as consequence, the analytical result. METHODS: The aim of this study was to compare three different isolation methods for urine EVs: ultracentrifugation (UC), size exclusion chromatography (SEC), and a commercial kit (Exolute® Urine Kit). Urine samples were collected from 6 PCa patients and 4 healthy donors. After filtered through 0.22 µm filters, urine was divided in 3 equal volumes to perform EVs isolation with each of the three approaches. Isolated EVs were characterized by spectrophotometric protein quantification, nanoparticle tracking analysis, transmission electron microscopy, AlphaScreen Technology, and whole miRNA Transcriptome. RESULTS: Our results showed that UC and SEC provided better results in terms of EVs yield and purity than Exolute®, non-significant differences were observed in terms of EV-size. Interestingly, luminescent AlphaScreen assay demonstrated a significant enrichment of CD9 and CD63 positive microvesicles in SEC and UC methods compared with Exolute®. This heterogeneity was also demonstrated in terms of miRNA content indicating that the best correlation was observed between UC and SEC. CONCLUSIONS: Our study highlights the importance of standardizing the urine EV isolation methods to guaranty the analytical reproducibility necessary for their implementation in a clinical setting.

Hope for Ostomates: A Carbon and Zeolite Impregnated Polyester Fabric Inhibits Urine Odor in Cancer Patients: A Randomized Experimental Study.

OBJECTIVE: Many individuals with bladder cancer have undergone a surgical urostomy and often complain of being self-conscious of the unpleasant smell of their own urine. The focus of this study was to test the efficacy of a pouch cover made of a carbon and zeolite containing polyester material to inhibit the smell of urine by comparing two trained dogs' response time in detecting volatile organic compounds (VOCs) in urine, with and without the fabric covering the samples. METHODS: This study used a randomized, blinded experimental design to evaluate the efficacy of a fabric to interfere with two highly trained dogs' ability to detect specific VOCs present in the urine of prostate cancer patient. Ninety urine samples were analyzed in this study. RESULTS: Prior to the experiment, both dogs accurately detected VOCs in the uncovered test urine samples of men with prostate cancer with a sensitivity and specificity of nearly 100%. Both dogs recognized the "uncovered" urine samples of men with prostate cancer within two seconds. When the test sample was covered with the study fabric, the test urine samples were detected within 30-40 seconds and in some instances the dogs were not able to identify the covered samples, whatsoever. CONCLUSION: The findings of this study demonstrate that the carbon and zeolite containing polyester fabric did significantly interfere with the ability of the dogs to detect VOCs in urine of men with prostate cancer. The fabric may show promise as a pouch cover in controlling offensive urine odor which many ostomates experience.

Identification of the metabolic signatures of prostate cancer by mass spectrometry-based plasma and urine metabolomics analysis.

OBJECTIVE: Prostate cancer (PCa) is one of the most commonly diagnosed cancers among men which is associated with profound metabolic changes. Systematic analysis of the metabolic alterations and identification of new biomarkers may benefit PCa diagnosis and a deep understanding of the pathological mechanism. The purpose of this study was to determine the metabolic features of PCa. METHODS: Plasma and urine metabolites from 89 prostate cancer (PCa) patients, 84 benign prostatic hyperplasia (BPH) patients, and 70 healthy males were analyzed using LC-MS/MS and GC-MS. The Orthogonalised Partial Least Squares Discriminant Analysis (OPLS-DA) was used to find the significantly changed metabolites. The clinical value of the candidate markers was examined by receiver operating characteristic curve analysis and compared with prostate-specific antigen (PSA). RESULTS: Multivariate statistical analyses found a series of altered metabolites, which related to the urea cycle, tricarboxylic acid cycle (TCA), fatty acid metabolism, and the glycine cleavage system. Plasma Glu/Gln showed the highest predictive value (AUC = 0.984) when differentiating PCa patients from healthy controls, with a higher sensitivity than PSA (96.6% vs. 94.4%). Both Glu/Gln and PSA displayed a low specificity when differentiating PCa patients from BPH patients (<53.2%), while the combination of Glu/Gln and PSA can further increase the diagnostic specificity to 66.9%. CONCLUSIONS: The present study showed the metabolic features of PCa, provided strong evidence that the amide nitrogen and the energy metabolic pathways could be a valuable source of markers for PCa. Several candidate markers identified in this study were clinically valuable for further assessment.

A urine extracellular vesicle circRNA classifier for detection of high-grade prostate cancer in patients with prostate-specific antigen 2-10 ng/mL at initial biopsy.

The aim of this study was to identify a urine extracellular vesicle circular RNA (circRNA) classifier that could detect high-grade prostate cancer (PCa) of Grade Group (GG) 2 or greater. For this purpose, we used RNA sequencing to identify candidate circRNAs from urinary extracellular vesicles from 11 patients with high-grade PCa and 11 case-matched patients with benign prostatic hyperplasia. Using ddPCR in a training cohort (n = 263), we built a urine extracellular vesicle circRNA classifier (Ccirc, containing circPDLIM5, circSCAF8, circPLXDC2, circSCAMP1, and circCCNT2), which was evaluated in two independent cohorts (n = 497, n = 505). Ccirc showed higher accuracy than two standard of care risk calculators (RCs) (PCPT-RC 2.0 and ERSPC-RC) in both the training cohort and the validation cohorts. In all three cohorts, this novel urine extracellular vesicle circRNA classifier plus RCs was statistically more predictive than RCs alone for predicting ≥ GG2 PCa. This assay, which does not require precollection digital rectal examination nor special handling, is repeatable, noninvasive, and can be easily implemented as part of the basic clinical workflow.