Urinary marker panels for aggressive prostate cancer detection.

Majority of patients with indolent prostate cancer (PCa) can be managed with active surveillance. Therefore, finding biomarkers for classifying patients between indolent and aggressive PCa is essential. In this study, we investigated urinary marker panels composed of urinary glycopeptides and/or urinary prostate-specific antigen (PSA) for their clinical utility in distinguishing non-aggressive (Grade Group 1) from aggressive (Grade Group ≥ 2) PCa. Urinary glycopeptides acquired via data-independent acquisition mass spectrometry (DIA-MS) were quantitatively analyzed, where prostatic acid phosphatase (ACPP), clusterin (CLU), alpha-1-acid glycoprotein 1 (ORM1), and CD antigen 97 (CD97) were selected to be evaluated in various combinations with and without urinary PSA. Targeted parallel reaction monitoring (PRM) assays of the glycopeptides from urinary ACPP and CLU were investigated along with urinary PSA for the ability of aggressive PCa detection. The multi-urinary marker panels, combined via logistic regression, were statistically evaluated using bootstrap resampling and validated by an independent cohort. Majority of the multi-urinary marker panels (e.g., a panel consisted of ACPP, CLU, and Urinary PSA) achieved area under the curve (AUC) ranged from 0.70 to 0.85. Thus, multi-marker panels investigated in this study showed clinically meaningful results on aggressive PCa detection to separate Grade Group 1 from Grade Group 2 and above warranting further evaluation in clinical setting in future.

Biomarcadores urinarios en el diagnóstico de cáncer de próstata / Urinary biomarkers in the diagnosis of prostate cáncer

INTRODUCCIÓN: El uso del antígenoprostático específico (PSA) es útil para el diagnósticodel cáncer de próstata. Su principal limitación es labaja especificidad, esto ha llevado a la búsqueda denuevos biomarcadores con el fin de identificar el cáncer de próstata clínicamente significativo y poder disminuir el sobrediagnóstico y sobretratamiento.El objetivo de este artículo es resumir la literaturaactual sobre los biomarcadores urinarios utilizados enel diagnóstico de cáncer de próstata.Se llevó a cabo una búsqueda bibliográfica en PubMed hasta diciembre del 2020. Hemos seleccionadolos artículos originales, ensayos clínicos y revisionesmás recientes que proporcionan información sobre eluso de biomarcadores.En esta revisión, hemos discutido cuatro importantes biomarcadores urinarios útiles para el diagnósticodel cáncer de próstata: PCA3, Select MDX, ExoDX, TMPRSS2:ERG.CONCLUSIÓN: El uso de biomarcadores urinariosha mejorado del diagnóstico de cáncer de próstata clínicamente significativo. Su uso reduce el número debiopsias innecesarias y evita el sobretratamiento delcáncer de próstata indolente. (AU)

INTRODUCTION: The use of prostatespecific antigen (PSA) is useful for the diagnosis ofprostate cancer. Its main limitation is its low specificity, which has led to the search for new biomarkersin order to identify clinically significant prostatecancer and to reduce overdiagnosis and overtreatment.The aim of this article is to summarize the current literature on urinary biomarkers used in thediagnosis of prostate cáncer.A PubMed-based literature search was conductedup to December 2020. We selected the most recentand relevant original articles, clinical trials and reviews that have provided relevant information onthe use of biomarkers.In this review, we have discussed four importanturinary biomarkers useful for prostate cancer diagnosis: PCA3, Select MDX, ExoDX, TMPRSS2:ERG.CONCLUSION: The use of urinary biomarkers hasimproved of clinically significant prostate cancerdiagnosis. Their use reduces the number of unnecessary biopsies and avoids overtreatment of indolent prostate cancer. (AU)

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.

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.

Prospective study of diagnostic accuracy in the detection of high-grade prostate cancer in biopsy-naïve patients with clinical suspicion of prostate cancer who underwent the Select MDx test.

OBJECTIVES: This study aimed to externally validate the diagnostic accuracy of the Select MDx test for Significant prostate cancer (Sig PCa) (ISUP > 1), in a contemporaneous, prospective, multicenter cohort with a prostate-specific antigen (PSA) between 3 and 10 ng/ml and a non-suspicious digital rectal examination. METHODS AND PARTICIPANTS: For all enrolled patients, the Select Mdx test, the risk calculator ERSPC3 + DRE, and a prostatic magnetic resonance imaging (MRI) were carried out. Subsequently, a systematic 12-core trans-rectal biopsy and a targeted biopsy, in the case of a prostate imaging-reporting and data system (PIRADS) > 2 lesion (max three lesions), were performed. To assess the accuracy of the Select MDx test in the detection of clinically Sig PCa, the test sensitivity was evaluated. Secondary objectives were specificity, negative predictive value (NPV), positive predictive value (PPV), and area under the curve (AUC). A direct comparison with the ERSPC + DRE risk calculator and MRI were also performed. We also studied the predictive ability to diagnose Sig PCa from the combination of the Select MDx test with MRI using clinical decision-curve analysis. RESULTS: There were 163 patients enrolled after meeting the inclusion criteria and study protocol. The Select MDx test showed a sensitivity of 76.9% (95% CI, 63.2-87.5), 49.6% specificity (95% CI, 39.9-59.2), 82.09% (95% CI, 70.8-90.4) NPV, and 41.67% (95% CI, 31.7-52.2) PPV for the diagnosis of Sig PCa. COR analysis was also performed, which showed an AUC of 0.63 (95% CI, 0.56-0.71). There were no differences in the accuracy of Select MDx, ERSPC + DRE, or MRI. The combination of Select MDX + MRI showed the highest impact in the decision-curve analysis, with an NPV of 93%. CONCLUSION: Our study showed a worse performance for the SelectMdx test than previously reported, within a cohort of patients with a PSA 3-10 ng/ml and a normal DRE, with results similar to those from ERSPC + DRE RC and MRI, but with an improvement in the usual PSA pathway. A combination of the Select Mdx test and MRI could improve accuracy, but studies specifically evaluating this scenario with a cost-effective analysis are needed.

Prospective evaluation of urinary steroids and prostate carcinoma-induced deviation: preliminary results.

BACKGROUND: The serum prostate-specific antigen is the most widespread biomarker for prostate disease. Its low specificity for prostatic malignancies is a matter of concern and the reason why new biomarkers for screening purposes are needed. The correlation between altered production of the main steroids and prostate carcinoma (PCa) occurrence is historically known. The purpose of this study is to evaluate the modifications of a comprehensive urinary endogenous steroidal profile (USP) induced by PCa, by multivariate statistical methods. METHODS: A total of 283 Italian subjects were included in the study, 139 controls and 144 PCa-affected patients. The USP, including 17 steroids and five urinary steroidal ratios, was quantitatively evaluated using gas chromatography coupled with single quadrupole mass spectrometry (GC-MS). The data were interpreted using a chemometric, multivariate approach (intrinsically more sensible to alterations with respect to traditional statistics) and a model for the discrimination of cancer-affected profiles was built. RESULTS: Two multivariate classification models were calculated, the former including three steroids with the highest statistical significance (e.g. testosterone, etiocholanolone and 7ß-OH-DHEA) and PSA values, the latter considering the three steroids' levels only. Both models yielded high sensitivity and specificity scores near to 70%, resulting significantly higher than PSA alone. CONCLUSIONS: Three USP steroids resulted significantly altered in our PCa population. These preliminary results, combined with the simplicity and low-cost of the analysis, open to further investigation of the potential role of this restricted USP in PCa diagnosis.

Development and validation of a 25-Gene Panel urine test for prostate cancer diagnosis and potential treatment follow-up.

BACKGROUND: Heterogeneity of prostate cancer (PCa) contributes to inaccurate cancer screening and diagnosis, unnecessary biopsies, and overtreatment. We intended to develop non-invasive urine tests for accurate PCa diagnosis to avoid unnecessary biopsies. METHODS: Using a machine learning program, we identified a 25-Gene Panel classifier for distinguishing PCa and benign prostate. A non-invasive test using pre-biopsy urine samples collected without digital rectal examination (DRE) was used to measure gene expression of the panel using cDNA preamplification followed by real-time qRT-PCR. The 25-Gene Panel urine test was validated in independent multi-center retrospective and prospective studies. The diagnostic performance of the test was assessed against the pathological diagnosis from biopsy by discriminant analysis. Uni- and multivariate logistic regression analysis was performed to assess its diagnostic improvement over PSA and risk factors. In addition, the 25-Gene Panel urine test was used to identify clinically significant PCa. Furthermore, the 25-Gene Panel urine test was assessed in a subset of patients to examine if cancer was detected after prostatectomy. RESULTS: The 25-Gene Panel urine test accurately detected cancer and benign prostate with AUC of 0.946 (95% CI 0.963-0.929) in the retrospective cohort (n = 614), AUC of 0.901 (0.929-0.873) in the prospective cohort (n = 396), and AUC of 0.936 (0.956-0.916) in the large combination cohort (n = 1010). It greatly improved diagnostic accuracy over PSA and risk factors (p < 0.0001). When it was combined with PSA, the AUC increased to 0.961 (0.980-0.942). Importantly, the 25-Gene Panel urine test was able to accurately identify clinically significant and insignificant PCa with AUC of 0.928 (95% CI 0.947-0.909) in the combination cohort (n = 727). In addition, it was able to show the absence of cancer after prostatectomy with high accuracy. CONCLUSIONS: The 25-Gene Panel urine test is the first highly accurate and non-invasive liquid biopsy method without DRE for PCa diagnosis. In clinical practice, it may be used for identifying patients in need of biopsy for cancer diagnosis and patients with clinically significant cancer for immediate treatment, and potentially assisting cancer treatment follow-up.

New Uses for the Personal Glucose Meter: Detection of Nucleic Acid Biomarkers for Prostate Cancer Screening.

A personal glucose meter (PGM)-based method for quantitative detection of a urinary nucleic acid biomarker in prostate cancer screening, the so-called PCA3, is reported herein. A sandwich-type genoassay is conducted on magnetic beads to collect the target from the sample by specific hybridization, making the assay appropriate for PCA3 detection in biological fluids. The success of the method hinges on the use of alkaline phosphatase (ALP) to link the amount of nucleic acid biomarker to the generation of glucose. In particular, specifically attached ALP molecules hydrolyze D-glucose-1-phosphate into D-glucose, thus enabling the amplification of the recorded signal on the personal glucose meter. The developed genoassay exhibits good sensitivity (3.3 ± 0.2 mg glucose dL-1 pM-1) for PCA3, with a dynamic range of 5 to 100 pM and a quantification limit of 5 pM. Likewise, it facilitates point-of-care testing of nucleic acid biomarkers by using off-the-shelf PGM instead of complex instrumentation involved in traditional laboratory-based tests.

Towards the differential diagnosis of prostate cancer by the pre-treatment of human urine using ionic liquids.

Prostate specific antigen (PSA) is the most widely used clinical biomarker for the diagnosis and monitoring of prostate cancer. Most available techniques for PSA quantification in human fluids require extensive sample processing and expensive immunoassays that are often unavailable in developing countries. The quantification of PSA in serum is the most common practice; however, PSA is also present in human urine, although less used in diagnosis. Herein we demonstrate the use of ionic-liquid-based aqueous biphasic systems (IL-based ABS) as effective pre-treatment strategies of human urine, allowing the PSA detection and quantification by more expedite equipment in a non-invasive matrix. If properly designed, IL-based ABS afford the simultaneous extraction and concentration of PSA (at least up to 250-fold) in the IL-rich phase. The best ABS not only allow to concentrate PSA but also other forms of PSA, which can be additionally quantified, paving the way to their use in differential prostate cancer diagnosis.

Targeted Mass Spectrometry of a Clinically Relevant PSA Variant from Post-DRE Urines for Quantitation and Genotype Determination.

PURPOSE: The rs17632542 single nucleotide polymorphism (SNP) results in lower serum prostate specific antigen (PSA) levels which may further mitigate against its clinical utility as a prostate cancer biomarker. Post-digital rectal exam (post-DRE) urine is a minimally invasive fluid that is currently utilized in prostate cancer diagnosis. To detect and quantitate the variant protein in urine. EXPERIMENTAL DESIGN: Fifty-three post-DRE urines from rs17632542 genotyped individuals processed and analyzed by liquid chromatography/mass spectrometry (LC-MS) in a double-blinded randomized study. The ability to distinguish between homozygous wild-type, heterozygous, or homozygous variant is examined before unblinding. RESULTS: Stable-isotope labeled peptides are used in the detection and quantitation of three peptides of interest in each sample using parallel reaction monitoring (PRM). Using these data, groupings are predicted using hierarchical clustering in R. Accuracy of the predictions show 100% concordance across the 53 samples, including individuals homozygous and heterozygous for the SNP. CONCLUSIONS AND CLINICAL RELEVANCE: The study demonstrates that MS based peptide variant quantitation in urine could be useful in determining patient genotype expression. This assay provides a tool to evaluate the utility of PSA variant (rs17632542) in parallel with current and forthcoming urine biomarker panels.

Beyond PSA: The Role of Prostate Health Index (phi).

BACKGROUND: Widespread use of prostate specific antigen (PSA) in screening procedures allowed early identification of an increasing number of prostate cancers (PCas), mainly including indolent cancer. Availability of different therapeutic strategies which have a very different impact on the patient's quality of life suggested a strong need for tools able to identify clinically significant cancer at diagnosis. Multi-parametric magnetic resonance showed very good performance in pre-biopsy diagnosis. However, it is an expensive tool and requires an experienced radiologist. In this context, a simple blood-based test is worth investigating. In this context, researchers focused their attention on the development of a laboratory test able to minimize overdiagnosis without losing the identification of aggressive tumors. RESULTS: Recent literature data on PCa biomarkers revealed a clear tendency towards the use of panels of biomarkers or a combination of biomarkers and clinical variables. Phi, the 4Kscore, and Stockholm3 as circulating biomarkers and the Mi-prostate score, Exo DX Prostate, and Select MD-X as urinary biomarker-based tests have been developed. In this scenario, phi is worthy of attention as a noninvasive test significantly associated with aggressive PCa. CONCLUSIONS: Literature data showed that phi had good diagnostic performance to identify clinically significant (cs) PCa, suggesting that it could be a useful tool for personalized treatment decision-making. In this review, phi potentialities, limitations, and comparisons with other blood- and urinary-based tests were explored.

A critical appraisal of biomarkers in prostate cancer.

PURPOSE: A number of urine and blood-based biomarker tests have been described for prostate cancer, although to date there has only been a limited exploration of the methodology behind the validation studies that underpin these tests. METHODS: In this review, a selection of commercially available urine and blood-based biomarker tests for prostate cancer are described, and the underlying key validation studies for each test are critically appraised using the Standards for Reporting Diagnostic Accuracy (STARD) 2015 statement. RESULTS: The ExoDx Prostate Intelliscore, SelectMDx, Progensa PCA3, Mi-Prostate Score, 4K Score, and Prostate Health Index (PHI) tests were reviewed. Most of the validation studies supporting these tests perform exploratory analyses to determine cut-off values in a post hoc manner, comprise cohorts that are primarily Caucasian, report receiver operating characteristic curves that combine the biomarker's result with established clinical nomograms and are based on a reference standard (prostate biopsy) that lacks central pathology review. Deficiencies in STARD reporting guidelines include frequent failure to provide a published study protocol, prospective study registration in a registry, a flow diagram, justification for sample size determination, a discussion of adverse events with testing, and information on how missing or indeterminate test results should be managed. CONCLUSIONS: Key validation studies that support many commercially available urine and blood-based biomarkers for prostate cancers have deficiencies in transparency based on STARD reporting guidelines, and limitations in methodology must be considered when deciding when these tests should be applied in clinical practice.

NMR-based metabolomics analysis identifies discriminatory metabolic disturbances in tissue and biofluid samples for progressive prostate cancer.

BACKGROUND: Prostate cancer (PCa) is one of the most common cancers in men, but its metabolic characteristics during tumor progression are still far from being fully understood. METHODS: The metabolic profiles of matched tissue, serum and urine samples from the same patients were analyzed using a 1H NMR-based metabolomics approach. We identified several important metabolites that significantly altered at different stages of PCa, including benign prostatic hyperplasia (BPH), early PCa (EPC), advanced PCa (APC), metastatic PCa (MPC) and castration-resistant PCa (CRPC). Metabolic correlation networks among tissue, serum and urine samples were examined using Pearson's correlation. RESULTS: The changes in metabolic phenotypes during the progression of PCa were more noticeable in tissue samples when compared with serum and urine samples. Herein we identified a series of important metabolic disturbances, including decreased trends of citrate, creatinine, acetate, leucine, valine, glycine, lysine, histidine, glutamine and choline as well as increased trends of uridine and formate. These metabolites are mainly implicated in energy metabolism, amino acid metabolism, choline and fatty acid metabolism as well as uridine metabolism. We also found that energy metabolism in tumor tissues was positively associated with amino acid metabolism in serum and urine. Additionally, CRPC patients had a peculiar metabolic phenotype, especially decreased amino acid metabolism in serum. CONCLUSIONS: The present study characterizes metabolic disturbances in both tissue and biofluid samples during PCa progression and provides potential diagnostic biomarkers and therapeutic targets for PCa.

Emissions of terbium metal-organic frameworks modulated by dispersive/agglomerated gold nanoparticles for the construction of prostate-specific antigen biosensor.

Herein, a universal and multifunctional fluorescence sensor platform is designed by the interaction of aggregation/dispersion gold nanoparticles (AuNPs) with Tb-metal-organic frameworks (Tb-MOFs). It is found that the dispersed AuNPs rather than the aggregated ones can quench effectively the fluorescence of Tb-MOFs, and the quenching process presumably involves the mechanism of inner filter effect (IFE), dynamic quenching effect (DQE), and fluorescence resonance energy transfer (FRET). The different affinities of aptamer and aptamer-target complex toward AuNPs are employed to modulate the fluorescence signal change of Tb-MOFs. As the proof of concept, prostate-specific antigen (PSA), an efficient tumor indicator for prostate cancer, is selected as the target. At first, the PSA aptamer can protect AuNPs against salt-induced aggregation, leading to the fluorescence of Tb-MOFs quenching. Subsequently, upon PSA introduction, the rigid aptamer-PSA complex is formed and cannot stabilize AuNPs in high salt conditions, so the AuNPs aggregate significantly and the fluorescence of Tb-MOFs is restored. The linear range of PSA is achieved from 1 to 100 ng/mL with a detection limit of 0.36 ng/mL. Finally, this method has been validated to be sensitive and specific for PSA in human urine samples. Graphical abstract.

A novel mass spectrometry method based on competitive non-covalent interaction for the detection of biomarkers.

We report a novel biosensor platform based on competitive non-covalent interaction between ssDNA and a mass tag towards AuNPs, which detects PSA biomarkers sensitively, observed using MALDI MS. A detection limit of 57 pg mL-1 has been achieved, showing an improvement of two orders of magnitude compared to the traditional spectroscopic method.

Improving the Specificity of PSA Screening with Serum and Urine Markers.

PURPOSE OF REVIEW: Prostate cancer remains a significant public health burden. In order to decrease the morbidity and mortality associated with prostate cancer, serum prostate-specific antigen (PSA) screening has been used since the 1990s. However, there is concern for overdiagnosis of prostate cancer with widespread PSA screening, which could lead to overtreatment and its attendant morbidities. RECENT FINDINGS: In order to avoid unnecessary biopsy and downstream effects including treatment of insignificant prostate cancer, a number of tests have been proposed to improve upon PSA screening. Increasing the specificity of prostate cancer screening above that of PSA testing should reduce the incidence of unnecessary prostate biopsy. However, an increase in specificity is associated with a decrease in sensitivity, so these tests must be balanced with the concern for missing the diagnosis of potentially significant disease. In this context, we present a review of six common biomarkers proposed to improve the specificity of prostate cancer screening-free PSA, prostate health index, 4Kscore, PCA3, Select MDx, and ExoDx Prostate(Intelliscore).

An In-Depth Glycosylation Assay for Urinary Prostate-Specific Antigen.

The concentration of prostate-specific antigen (PSA) in serum is used as an early detection method of prostate cancer (PCa); however, it shows low sensitivity, specificity, and a poor predictive value. Initial studies suggested the glycosylation of PSA to be a promising marker for a more specific yet noninvasive PCa diagnosis. Recent studies on the molecular features of PSA glycosylation (such as antenna modification and core fucosylation) were not successful in demonstrating its potential for an improved PCa diagnosis, probably due to the lack of analytical sensitivity and specificity of the applied assays. In this study, we established for the first time a high-performance PSA Glycomics Assay (PGA), allowing differentiation of α2,6- and α2,3-sialylated isomers, the latter one being suggested to be a hallmark of aggressive types of cancer. After affinity purification from urine and tryptic digestion, PSA samples were analyzed by CE-ESI-MS (capillary electrophoresis-electrospray ionization coupled to mass spectrometry). Based on positive controls, an average interday relative standard deviation of 14% for 41 N-glycopeptides was found. The assay was further verified by analyzing PSA captured from patients' urine samples. A total of 67 N-glycopeptides were identified from the PSA pooled from the patients. In summary, the first PGA successfully established in this study allows an in-depth relative quantitation of PSA glycoforms from urine. The PGA is a promising tool for the determination of potential glycomic biomarkers for the differentiation between aggressive PCa, indolent PCa, and benign prostate hyperplasia in larger cohort studies.

Differences in Urinary Amino Acid Patterns in Individuals with Different Types of Urological Tumor Urinary Amino Acid Patterns as Markers of Urological Tumors.

BACKGROUND: Insufficient specificity and invasiveness of currently used diagnostic methods raises the need for new markers of urological tumors. The aim of this study was to find a link between the urinary excretion of amino acids and the presence of urological tumors. MATERIALS AND METHODS: Using ion-exchange chromatography, we tested urine samples of patients with prostate cancer (n=30), urinary bladder cancer (n=28), renal cell carcinoma (n=16) and healthy volunteers (control group; n=21). RESULTS: In each category, we found a group of amino acids which differed in concentration compared to the control group. These differences were most significant in sarcosine in patients with prostate cancer; leucine, phenylalanine and arginine in those with bladder cancer; and sarcosine, glutamic acid, glycine, tyrosine and arginine in the those with renal cell carcinoma. CONCLUSION: Results of our research imply a possible connection between the occurrence of specific types of amino acids in the urine and the presence of urological tumors.

Analysis of urinary PSA glycosylation is not indicative of high-risk prostate cancer.

The levels of core fucosylation and α2,3-linked sialic acid in serum Prostate Specific Antigen (PSA), using the lectins Pholiota squarrosa lectin (PhoSL) and Sambucus nigra agglutinin (SNA), can discriminate between Benign Prostatic Hyperplasia (BPH) and indolent prostate cancer (PCa) from aggressive PCa. In the present work we evaluated whether these glycosylation determinants could also be altered in urinary PSA obtained after digital rectal examination (DRE) and could also be useful for diagnosis determinations. For this purpose, α2,6-sialic acid and α1,6-fucose levels of urinary PSA from 53 patients, 18 biopsy-negative and 35 PCa patients of different aggressiveness degree, were analyzed by sandwich ELLA (Enzyme Linked Lectin Assay) using PhoSL and SNA. Changes in the levels of specific glycosylation determinants, that in serum PSA samples were indicative of PCa aggressiveness, were not found in PSA from DRE urine samples. Although urine is a simpler matrix for analyzing PSA glycosylation compared to serum, an immunopurification step was necessary to specifically detect the glycans on the PSA molecule. Those specific glycosylation determinants on urinary PSA were however not useful to improve PCa diagnosis. This could be probably due to the low proportion of PSA from the tumor in urine samples, which precludes the identification of aberrantly glycosylated PSA.

Release of urinary extracellular vesicles in prostate cancer is associated with altered urinary N-glycosylation profile.

AIM: Nowadays, extracellular vesicles are of great interest in prostate cancer (PCa) research. Asparagine (N)-linked glycosylation could play a significant role in the pathological mechanism of these vesicles. We investigated if prostatic protein N-glycosylation profiles were related to urinary vesicle-associated prostate-specific antigen (PSA) extractability and if this parameter showed diagnostic potential for PCa. METHODS: Urinary extracellular vesicles were visualised using transmission electron microscopy. Urinary extracellular vesicles extraction by means of n-butanol allowed determination of urinary vesicle-associated PSA extractability. Diagnostic value was assessed between benign prostate hyperplasia (BPH; n=122) and patients with PCa (n=85). Additionally, correlation with urine N-glycosylation was assessed. RESULTS: Urinary extracellular vesicles with a diameter of approximately 100 nm were more abundantly present in urine of patients with PCa versus patients with BPH resulting in a higher vesicle-associated PSA extraction ratio (p<0.001). Next, vesicle-associated PSA extraction ratio was correlated to biantennary core-fucosylation (p=0.003). Finally, vesicle-associated PSA extraction ratio proved beneficial in PCa diagnosis, next to serum PSA and the urinary glycosylation marker (p=0.021). CONCLUSIONS: The urinary vesicle-associated PSA extraction ratio is increased in PCa which is a direct result of the abundant presence of extracellular vesicles in urine of patients with PCa. The urinary vesicle-associated PSA extraction ratio was associated with changes in N-glycoforms and showed diagnostic potential. Further research is warranted to unravel the pathological link between N-glycosylation and extracellular vesicles in cancer, as well as to assess the prognostic value of this biomarker.