Discovery and validation of urinary biomarkers for prostate cancer

Urinary peptide analysis to predict the response to blood pressure medication

BACKGROUND

The risk of diabetic kidney disease (DKD) progression is significant despite treatment with renin-angiotensin system (RAS) blocking agents. Current clinical tools cannot predict whether or not patients will respond to treatment with RAS inhibitors (RASi). We aimed to investigate whether proteome analysis could identify urinary peptides as biomarkers that could predict the response to angiotensin-converting enzyme inhibitor and angiotensin-receptor blockers treatment to avoid DKD progression. Furthermore, we investigated the comparability of the estimated glomerular filtration rate (eGFR), calculated using four different GFR equations, for DKD progression.

METHODS

We evaluated urine samples from a discovery cohort of 199 diabetic patients treated with RASi. DKD progression was defined based on eGFR percentage slope results between visits (∼1 year) and for the entire period (∼3 years) based on the eGFR values of each GFR equation. Urine samples were analysed using capillary electrophoresis-coupled mass spectrometry. Statistical analysis was performed between the uncontrolled (patients who did not respond to RASi treatment) and controlled kidney function groups (patients who responded to the RASi treatment). Peptides were combined in a support vector machine-based model. The area under the receiver operating characteristic curve was used to evaluate the risk prediction models in two independent validation cohorts treated with RASi.

RESULTS

The classification of patients into uncontrolled and controlled kidney function varies depending on the GFR equation used, despite the same sample set. We identified 227 peptides showing nominal significant difference and consistent fold changes between uncontrolled and controlled patients in at least three methods of eGFR calculation. These included fragments of collagens, alpha-1-antitrypsin, antithrombin-III, CD99 antigen and uromodulin. A model based on 189 of 227 peptides (DKDp189) showed a significant prediction of non-response to the treatment/DKD progression in two independent cohorts.

CONCLUSIONS

The DKDp189 model demonstrates potential as a predictive tool for guiding treatment with RASi in diabetic patients.

Urinary biomarkers in children with neurogenic and non-neurogenic lower urinary tract dysfunction: A systematic review and meta-analysis

AIM

The aim of this systematic review is to assess urinary biomarkers studied in children with neurogenic and non-neurogenic lower urinary tract dysfunction (LUTD).

MATERIALS AND METHODS

The systematic review was conducted in accordance with the PRISMA guidelines. The screening was performed on PUBMED without any publication date limitation. Only original articles were included. Parameters related to the following topics were obtained: study design, characteristics of participants, number of participants, age, control group, types of biomarkers, measurement technique in urine, subgroup analysis, urodynamic findings, and outcome. Dutch Cochrane Checklist (DCC) and level of evidence by EBRO platform were used for quality assessment. Meta-analysis was performed with the Comprehensive Meta-Analysis Version 4 program.

RESULTS

A total of 494 studies were screened and 16 studies were included. 11 (68.75%) were conducted in children with non-neurogenic LUTD and 5 (31.25%) neurogenic LUTD. Nerve growth factor (NGF) was evaluated in 12 studies, brain-derived neurotrophic factor (BDNF) in 5, Tissue Inhibitor of Metalloproteinase-2 (TIMP-2) in 2, transforming growth factor beta-1 (TGF Beta-1) in 2, neutrophil gelatinase-associated lipocalin (NGAL) in 1, and Aquaporin-2 in 1. According to DCC, 10 (62.5%) articles were evaluated on 4 (37.5%) items and 4 articles on 5 items. The average score was 3.91+/-0.56. The level of evidence was found as B for 13 (81.25%) articles and C for 3 (18.75%). In meta-analysis, urinary NGF levels in children with non-neurogenic LUTS were significantly higher than in the healthy control group (Hedges's g = 1.867, standard error = 0.344, variance = 0.119, p = 0.0001).

CONCLUSION

Urinary biomarkers are promising for the future with their noninvasive features. However, prospective studies with larger sample sizes are needed to better understand the potential of urinary biomarkers to reflect urodynamic and clinical findings in children with LUTD.

Systematic Review: Urine Biomarker Discovery for Inflammatory Bowel Disease Diagnosis

Inflammatory bowel diseases (IBDs) are chronic, heterogeneous, and inflammatory conditions mainly affecting the gastrointestinal tract. Currently, endoscopy is the gold standard test for assessing mucosal activity and healing in clinical practice; however, it is a costly, time-consuming, invasive, and uncomfortable procedure for the patients. Therefore, there is an urgent need for sensitive, specific, fast and non-invasive biomarkers for the diagnosis of IBD in medical research. Urine is an excellent biofluid for discovering biomarkers because it is non-invasive to sample. In this review, we aimed to summarize proteomics and metabolomics studies performed in both animal models of IBD and humans that identify urinary biomarkers for IBD diagnosis. Future large-scale multi-omics studies should be conducted in collaboration with clinicians, researchers, and industry to make progress toward the development of sensitive and specific diagnostic biomarkers, thereby making personalized medicine possible.

Urine biomarkers in cancer detection: A systematic review of preanalytical parameters and applied methods

The aim of this review was to explore the status of urine sampling as a liquid biopsy for noninvasive cancer research by reviewing used preanalytical parameters and protocols. We searched two main health sciences databases, PubMed and Web of Science. From all eligible publications (2010-2022), information was extracted regarding: (a) study population characteristics, (b) cancer type, (c) urine preanalytics, (d) analyte class, (e) isolation method, (f) detection method, (g) comparator used, (h) biomarker type, (i) conclusion and (j) sensitivity and specificity. The search query identified 7835 records, of which 924 unique publications remained after screening the title, abstract and full text. Our analysis demonstrated that many publications did not report information about the preanalytical parameters of their urine samples, even though several other studies have shown the importance of standardization of sample handling. Interestingly, it was noted that urine is used for many cancer types and not just cancers originating from the urogenital tract. Many different types of relevant analytes have been shown to be found in urine. Additionally, future considerations and recommendations are discussed: (a) the heterogeneous nature of urine, (b) the need for standardized practice protocols and (c) the road toward the clinic. Urine is an emerging liquid biopsy with broad applicability in different analytes and several cancer types. However, standard practice protocols for sample handling and processing would help to elaborate the clinical utility of urine in cancer research, detection and disease monitoring.

Nurturing the marriages of urinary liquid biopsies and nano-diagnostics for precision urinalysis of prostate cancer

Prostate cancer remains the second-most common cancer diagnosed in men, despite the increasingly widespread use of serum prostate-specific antigen (PSA) screening. The controversial clinical implications and cost benefits of PSA screening have been highlighted due to its poor specificity, resulting in a high rate of overdiagnosis and underdiagnosis. Thus, the development of novel biomarkers for prostate cancer detection remains an intriguing challenge. Urine is emerging as a source for prostate cancer biomarker discovery. Currently, new urine biomarkers already outperform serum PSA in clinical diagnosis. Meanwhile, the advances in nanotechnology have provided a suite of diagnostic tools to study prostate cancer in more detail, sparking a new era of biomarker discoveries. In this review, we envision that future prostate cancer diagnosis will probably integrate multiplex nano-diagnostic approaches to detect novel urinary biomarkers. However, challenges remain in differentiating indolent from aggressive cancers to better inform treatment decisions, and clinical translation still needs to be overcome.

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.

A Model to Detect Significant Prostate Cancer Integrating Urinary Peptide and Extracellular Vesicle RNA Data

There is a clinical need to improve assessment of biopsy-naïve patients for the presence of clinically significant prostate cancer (PCa). In this study, we investigated whether the robust integration of expression data from urinary extracellular vesicle RNA (EV-RNA) with urine proteomic metabolites can accurately predict PCa biopsy outcome. Urine samples collected within the Movember GAP1 Urine Biomarker study (n = 192) were analysed by both mass spectrometry-based urine-proteomics and NanoString gene-expression analysis (167 gene-probes). Cross-validated LASSO penalised regression and Random Forests identified a combination of clinical and urinary biomarkers for predictive modelling of significant disease (Gleason Score (Gs) ≥ 3 + 4). Four predictive models were developed: ‘MassSpec’ (CE-MS proteomics), ‘EV-RNA’, and ‘SoC’ (standard of care) clinical data models, alongside a fully integrated omics-model, deemed ‘ExoSpec’. ExoSpec (incorporating four gene transcripts, six peptides, and two clinical variables) is the best model for predicting Gs ≥ 3 + 4 at initial biopsy (AUC = 0.83, 95% CI: 0.77−0.88) and is superior to a standard of care (SoC) model utilising clinical data alone (AUC = 0.71, p < 0.001, 1000 resamples). As the ExoSpec Risk Score increases, the likelihood of higher-grade PCa on biopsy is significantly greater (OR = 2.8, 95% CI: 2.1−3.7). The decision curve analyses reveals that ExoSpec provides a net benefit over SoC and could reduce unnecessary biopsies by 30%.

Urine proteomics for prediction of disease progression in patients with IgA nephropathy

BACKGROUND

Risk of kidney function decline in immunoglobulin A (IgA) nephropathy (IgAN) is significant and may not be predicted by available clinical and histological tools. To serve this unmet need, we aimed at developing a urinary biomarker-based algorithm that predicts rapid disease progression in IgAN, thus enabling a personalized risk stratification.

METHODS

In this multicentre study, urine samples were collected in 209 patients with biopsy-proven IgAN. Progression was defined by tertiles of the annual change of estimated glomerular filtration rate (eGFR) during follow-up. Urine samples were analysed using capillary electrophoresis coupled mass spectrometry. The area under the receiver operating characteristic curve (AUC) was used to evaluate the risk prediction models.

RESULTS

Of the 209 patients, 64% were male. Mean age was 42 years, mean eGFR was 63 mL/min/1.73 m2 and median proteinuria was 1.2 g/day. We identified 237 urine peptides showing significant difference in abundance according to the tertile of eGFR change. These included fragments of apolipoprotein C-III, alpha-1 antitrypsin, different collagens, fibrinogen alpha and beta, titin, haemoglobin subunits, sodium/potassium-transporting ATPase subunit gamma, uromodulin, mucin-2, fractalkine, polymeric Ig receptor and insulin. An algorithm based on these protein fragments (IgAN237) showed a significant added value for the prediction of IgAN progression [AUC 0.89; 95% confidence interval (CI) 0.83-0.95], as compared with the clinical parameters (age, gender, proteinuria, eGFR and mean arterial pressure) alone (0.72; 95% CI 0.64-0.81).

CONCLUSIONS

A urinary peptide classifier predicts progressive loss of kidney function in patients with IgAN significantly better than clinical parameters alone.

Proteomic discovery of non-invasive biomarkers of localized prostate cancer using mass spectrometry

Prostate cancer is the second most frequently diagnosed non-skin cancer in men worldwide. Patient outcomes are remarkably heterogeneous and the best existing clinical prognostic tools such as International Society of Urological Pathology Grade Group, pretreatment serum PSA concentration and T-category, do not accurately predict disease outcome for individual patients. Thus, patients newly diagnosed with prostate cancer are often overtreated or undertreated, reducing quality of life and increasing disease-specific mortality. Biomarkers that can improve the risk stratification of these patients are, therefore, urgently needed. The ideal biomarker in this setting will be non-invasive and affordable, enabling longitudinal evaluation of disease status. Prostatic secretions, urine and blood can be sources of biomarker discovery, validation and clinical implementation, and mass spectrometry can be used to detect and quantify proteins in these fluids. Protein biomarkers currently in use for diagnosis, prognosis and relapse-monitoring of localized prostate cancer in fluids remain centred around PSA and its variants, and opportunities exist for clinically validating novel and complimentary candidate protein biomarkers and deploying them into the clinic.

Peptidomics and Capillary Electrophoresis

Peptides play a crucial role in many vitally important functions of living organisms. The goal of peptidomics is the identification of the "peptidome," the whole peptide content of a cell, organ, tissue, body fluid, or organism. In peptidomic or proteomic studies, capillary electrophoresis (CE) is an alternative technique for liquid chromatography. It is a highly efficient and fast separation method requiring extremely low amounts of sample. In peptidomic approaches, CE is commonly combined with mass spectrometric (MS) detection. Most often, CE is coupled with electrospray ionization MS and less frequently with matrix-assisted laser desorption/ionization MS. CE-MS has been employed in numerous studies dealing with determination of peptide biomarkers in different body fluids for various diseases, or in food peptidomic research for the analysis and identification of peptides with special biological activities. In addition to the above topics, sample preparation techniques commonly applied in peptidomics before CE separation and possibilities for peptide identification and quantification by CE-MS or CE-MS/MS methods are discussed in this chapter.

Current applications of capillary electrophoresis-mass spectrometry for the analysis of biologically important analytes in urine (2017 to mid-2021): A review

Capillary electrophoresis coupled online with mass detection is a modern tool for analyzing wide ranges of compounds in complex samples, including urine. Capillary electrophoresis with mass spectrometry allows the separation and identification of various analytes spanning from small ions to high molecular weight protein complexes. Similarly to the much more common liquid chromatography‐mass spectrometry techniques, the capillary electrophoresis separation reduces the complexity of the mixture of analytes entering the mass spectrometer resulting in reduced ion suppression and a more straightforward interpretation of the mass spectrometry data. This review summarizes capillary electrophoresis with mass spectrometry studies published between the years 2017 and 2021, aiming at the determination of various compounds excreted in urine. The properties of the urine, including its diagnostical and analytical features and chemical composition, are also discussed including general protocols for the urine sample preparation. The mechanism of the electrophoretic separation and the instrumentation for capillary electrophoresis with mass spectrometry coupling is also included. This review shows the potential of the capillary electrophoresis with mass spectrometry technique for the analyses of different kinds of analytes in a complex biological matrix. The discussed applications are divided into two main groups (capillary electrophoresis with mass spectrometry for the determination of drugs and drugs of abuse in urine and capillary electrophoresis with mass spectrometry for the studies of urinary metabolome).

Pathophysiological Implications of Urinary Peptides in Hepatocellular Carcinoma

Simple Summary

In this study, the application of capillary electrophoresis mass spectrometry enabled identification of 31 urinary peptides significantly associated with hepatocellular carcinoma diagnosis and prognosis. Further assessment of these peptides lead to prediction of cellular proteases involved in their development namely Meprin A subunit α and Kallikrein-6. Subsequent identification of the proteases was verified by immunohistochemistry in normal liver, cirrhosis and hepatocellular carcinoma. Histopathological assessment of the proteases revealed numerical gradient staining signifying their involvement in liver fibrosis and hepatocellular carcinoma formation. The discovered urinary peptides offered a potential noninvasive tool for diagnosis and prognosis of hepatocellular carcinoma.

Abstract

Hepatocellular carcinoma (HCC) is known to be associated with protein alterations and extracellular fibrous deposition. We investigated the urinary proteomic profiles of HCC patients in this prospective cross sectional multicentre study. 195 patients were recruited from the UK (Coventry) and Germany (Hannover) between 1 January 2013 and 30 June 2019. Out of these, 57 were HCC patients with a background of liver cirrhosis (LC) and 138 were non-HCC controls; 72 patients with LC, 57 with non-cirrhotic liver disease and 9 with normal liver function. Analysis of the urine samples was performed by capillary electrophoresis (CE) coupled to mass spectrometry (MS). Peptide sequences were obtained and 31 specific peptide markers for HCC were identified and further integrated into a multivariate classification model. The peptide model demonstrated 79.5% sensitivity and 85.1% specificity (95% CI: 0.81–0.93, p < 0.0001) for HCC and 4.1-fold increased risk of death (95% CI: 1.7–9.8, p = 0.0005). Proteases potentially involved in HCC progression were mapped to the N- and C-terminal sequence motifs of the CE-MS peptide markers. In silico protease prediction revealed that kallikrein-6 (KLK6) elicits increased activity, whilst Meprin A subunit α (MEP1A) has reduced activity in HCC compared to the controls. Tissue expression of KLK6 and MEP1A was subsequently verified by immunohistochemistry.

[Diagnostic markers in urology]

Cancer diagnostics can be supplemented by disease-related biomarkers. In the course of modern patient-tailored cancer treatment, the importance of correct risk stratification, prognosis and monitoring has significantly increased. In recent years, a multitude of biomarkers and related test procedures have emerged to fulfil this purpose. The following review article summarizes the most recent developments with respect to the use of biomarkers in the diagnostics of urological cancers.

A Suite of Activity-Based Probes To Dissect the KLK Activome in Drug-Resistant Prostate Cancer

Kallikrein-related peptidases (KLKs) are a family of secreted serine proteases, which form a network (the KLK activome) with an important role in proteolysis and signaling. In prostate cancer (PCa), increased KLK activity promotes tumor growth and metastasis through multiple biochemical pathways, and specific quantification and tracking of changes in the KLK activome could contribute to validation of KLKs as potential drug targets. Herein we report a technology platform based on novel activity-based probes (ABPs) and inhibitors enabling simultaneous orthogonal analysis of KLK2, KLK3, and KLK14 activity in hormone-responsive PCa cell lines and tumor homogenates. Importantly, we identifed a significant decoupling of KLK activity and abundance and suggest that KLK proteolysis should be considered as an additional parameter, along with the PSA blood test, for accurate PCa diagnosis and monitoring. Using selective inhibitors and multiplexed fluorescent activity-based protein profiling (ABPP), we dissect the KLK activome in PCa cells and show that increased KLK14 activity leads to a migratory phenotype. Furthermore, using biotinylated ABPs, we show that active KLK molecules are secreted into the bone microenvironment by PCa cells following stimulation by osteoblasts suggesting KLK-mediated signaling mechanisms could contribute to PCa metastasis to bone. Together our findings show that ABPP is a powerful approach to dissect dysregulation of the KLK activome as a promising and previously underappreciated therapeutic target in advanced PCa.

A novel urinary mRNA signature using the droplet digital polymerase chain reaction platform improves discrimination between prostate cancer and benign prostatic hyperplasia within the prostate-specific antigen gray zone

Purpose

The aim of this study was to identify a noninvasive urinary marker for prostate cancer (PCa) diagnosis and to validate the clinical performance of this novel urinary mRNA signature using the droplet digital polymerase chain reaction (ddPCR) approach.

Materials and Methods

A gene expression microarray (HT-12, Illumina Inc., USA) was used to identify genes differentially expressed between 16 PCa and 8 benign prostatic hyperplasia (BPH) tissues; ddPCR (QX200; Bio-Rad Laboratories, USA) was carried out to quantify the expression of selected genes in urine. The urinary molecular PCa risk score (UMPCaRS) was calculated by using the sum of three upregulated genes as the numerator and the sum of three downregulated genes as the denominator. The diagnostic utility of the UMPCaRS was validated by using a screening set (10 PCa and 10 BPH samples) and a validation set (131 PCa and 105 BPH samples).

Results

Three upregulated genes (PDLIM5, GDF-15, THBS4) and three downregulated genes (UPK1A, SSTR3, NPFFR2) were selected from the microarray and subjected to ddPCR. The UMPCaRS for PCa in the screening and validation sets was significantly higher than that for BPH. For the validation set, the diagnostic accuracy of the UMPCaRS was comparable with that of prostate-specific antigen (PSA). Importantly, in the "PSA gray zone" (3-10 ng/mL), the AUC for the UMPCaRS was 0.843 and that for PSA was 0.628 (p<0.001).

Conclusions

The data demonstrate that the UMPCaRS is useful for discriminating between PCa and BPH in the "PSA gray zone".

Cancer metabolomic markers in urine: evidence, techniques and recommendations

Urinary tests have been used as noninvasive, cost-effective tools for screening, diagnosis and monitoring of diseases since ancient times. As we progress through the 21st century, modern analytical platforms have enabled effective measurement of metabolites, with promising results for both a deeper understanding of cancer pathophysiology and, ultimately, clinical translation. The first study to measure metabolomic urinary cancer biomarkers using NMR and mass spectrometry (MS) was published in 2006 and, since then, these techniques have been used to detect cancers of the urological system (kidney, prostate and bladder) and nonurological tumours including those of the breast, ovary, lung, liver, gastrointestinal tract, pancreas, bone and blood. This growing field warrants an assessment of the current status of research developments and recommendations to help systematize future research.

Nuclear magnetic resonance-based metabolomics and metabolic pathway networks from patient-matched esophageal carcinoma, adjacent noncancerous tissues and urine

BACKGROUND

Several studies have demonstrated a correlation between esophageal cancer (EC) and perturbed urinary metabolomic profiles, but none has described the correlation between urine metabolite profiles and those of the tumor and adjacent esophageal mucosa in the same patient.

AIM

To investigate how urinary metabolic phenotypes were linked to the changes in the biochemical landscape of esophageal tumors.

METHODS

Nuclear magnetic resonance-based metabolomics were applied to esophageal tumor tissues and adjacent normal mucosal tissues alongside patient-matched urine samples.

RESULTS

Analysis revealed that specific metabolite changes overlapped across both metrics, including glucose, glutamate, citrate, glycine, creatinine and taurine, indicating that the networks for metabolic pathway perturbations in EC, potentially involved in but not limited to disruption of fatty acid metabolism, glucose and glycolytic metabolism, tricarboxylic acid cycle and glutaminolysis. Additionally, changes in most urinary biomarkers correlated with changes in biomarker candidates in EC tissues, implying enhanced energy production for rapid cell proliferation.

CONCLUSION

Overall, these associations provide evidence for distinct metabolic signatures and pathway disturbances between the tumor tissues and urine of EC patients, and changes in urinary metabolic signature could reflect reprogramming of the aforementioned metabolic pathways in EC tissues. Further investigation is needed to validate these initial findings using larger samples and to establish the underlying mechanism of EC progression.

Quantitative proteomic analysis of a genetically induced prostate inflammation mouse model via custom 4-plex DiLeu isobaric labeling

Inflammation is involved in many prostate pathologies including infection, benign prostatic hyperplasia, and prostate cancer. Preclinical models are critical to our understanding of disease mechanisms, yet few models are genetically tractable. Here, we present a comparative quantitative proteomic analysis of urine from mice with and without prostate-specific inflammation induced by conditional prostate epithelial IL-1β expression. Relative quantification and sample multiplexing was achieved using custom 4-plex N,N-dimethyl leucine (DiLeu) isobaric tags and nanoflow ultrahigh-performance liquid chromatography coupled to high-resolution tandem mass spectrometry. Each set of 4-plex DiLeu reagents allows four urine samples to be analyzed simultaneously, providing high-throughput and accurate quantification of urinary proteins. Proteins involved in the acute phase response, including haptoglobin, inter-α-trypsin inhibitor, and α1-antitrypsin 1-1, were differentially represented in the urine of mice with prostate inflammation. Mass spectrometry-based quantitative urinary proteomics represents a promising bioanalytical strategy for biomarker discovery and the elucidation of molecular mechanisms in urological research.

CE-MS-based urinary biomarkers to distinguish non-significant from significant prostate cancer

Background

Prostate cancer progresses slowly when present in low risk forms but can be lethal when it progresses to metastatic disease. A non-invasive test that can detect significant prostate cancer is needed to guide patient management.

Methods

Capillary electrophoresis/mass spectrometry has been employed to identify urinary peptides that may accurately detect significant prostate cancer. Urine samples from 823 patients with PSA (<15 ng/ml) were collected prior to biopsy. A case–control comparison was performed in a training set of 543 patients (n_Sig = 98; n_non-Sig = 445) and a validation set of 280 patients (n_Sig = 48, n_non-Sig = 232). Totally, 19 significant peptides were subsequently combined by a support vector machine algorithm.

Results

Independent validation of the 19-biomarker model in 280 patients resulted in a 90% sensitivity and 59% specificity, with an AUC of 0.81, outperforming PSA (AUC = 0.58) and the ERSPC-3/4 risk calculator (AUC = 0.69) in the validation set.

Conclusions

This multi-parametric model holds promise to improve the current diagnosis of significant prostate cancer. This test as a guide to biopsy could help to decrease the number of biopsies and guide intervention. Nevertheless, further prospective validation in an external clinical cohort is required to assess the exact performance characteristics.

Peptidomic analysis of cartilage and subchondral bone in OA patients

BACKGROUND

The objective of this study was to develop a method for directly analysing osteochondral samples straight out of the operating room without cell culturing, thereby enabling identification of potential peptide biomarkers to better understand the mechanisms involved in the development of osteoarthritis and pain.

MATERIAL AND METHODS

Osteochondral plugs from wounded and macroscopically nonwounded zones of the femur condyle were collected from six patients with manifest osteoarthritis (OA) undergoing total knee arthroplasty (TKA). The samples were demineralized and supernatant was collected and isotopically marked with Tandem Mass Tag (TMT) labelling and analysed using liquid chromatography coupled with tandem mass spectrometry LC-MS/MS.

RESULTS

Using peptidomics, 6292 endogenous peptides were identified. Five hundred sixty-six peptides (8 identified endogenous peptides) differed significantly (P-value 0.10) from wounded zones compared to nonwounded zones.

CONCLUSION

This pilot study shows promising results for enabling peptidomic analysis of cartilage and bone straight out of the operating room. With further refinement, peptidomics can potentially become a diagnostic tool for OA, and improve the knowledge of disease progression and genesis of pain.

Evaluation of the 'Colli-Pee', a first-void urine collection device for self-sampling at home for the detection of sexually transmitted infections, versus a routine clinic-based urine collection in a one-to-one comparison study design: efficacy and acceptability among MSM in Belgium

OBJECTIVES

Pre-exposure prophylaxis (PrEP) users are screened bi-annual for sexually transmitted infections (STIs). A novel device, called the Colli-Pee, collects first-void urine in a standardised way and the collector tube can be easily delivered by regular post to a certified laboratory. The aim of the study was a one-to-one comparison between the STI test results obtained with the urine collected in the clinic, versus urine collected at home in a real-life setting by Men who have Sex with Men (MSM) in Belgium. The user-friendliness and acceptability of the Colli-Pee device by the users was also evaluated.

DESIGN

A single-site nested substudy in a prospective PrEP demonstration project (Be-PrEP-ared) among MSM in Belgium.

PARTICIPANTS

A total of 473 home-based samples from 213 MSM were received with a mean age of 38.5 years.

INTERVENTIONS

Participants were requested to collect a urine sample at home using the Colli-Pee device and to send it to the laboratory via regular mail.

PRIMARY AND SECONDARY OUTCOME MEASURES

The presence of Chlamydia trachomatis (CT), Neisseria gonorrhoeae (NG), Mycoplasma genitalium (MG) and Trichomonas vaginalis (TV) was determined using molecular amplification assays. Agreement between test results of samples collected at the clinic and collected at home were evaluated using Cohen's kappa statistic.

RESULTS

TV was not detected. A very good to almost perfect agreement was found for CT, NG and MG of κ=0.75, 0.87 and 0.85, respectively. Using the Colli-Pee device only one low positive CT and two MG infections were missed, however, three additional CT, two NG and six MG infections were detected.

CONCLUSIONS

The Colli-Pee device is a feasible and convenient way to collect urine at home for STI testing. This may be particularly relevant for populations that need frequent STI testing, such as PrEP users and patients who prefer home-sampling.

TRIAL REGISTRATION NUMBER

NCT02552914; Pre-results.

MALDI-TOF-MS Analysis in the Identification of Urine Proteomic Patterns of Gestational Trophoblastic Disease

Gestational trophoblastic disease (GTD) is a group of highly aggressive, rare tumors. Human chorionic gonadotropin is a common biomarker used in the diagnosis and monitoring of GTD. To improve our knowledge of the pathology of GTD, we performed protein-peptide profiling on the urine of patients affected with gestational trophoblastic neoplasm (GTN). We analyzed urine samples from patients diagnosed with GTN (n = 26) and from healthy pregnant and non-pregnant controls (n = 17) using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS). Ions were examined in a linear mode over a m/z range of 1000–10,000. All GTN urine samples were analyzed before and after treatment and compared with those of the controls. The statistical analyses included multivariate classification algorithms as well as ROC curves. Urine sample analyses revealed there were significant differences in the composition of the ions between the evaluated groups. Comparing the pre-treatment and group with the pregnant controls, we identified two discriminatory proteins: hemoglobin subunit α (m/z = 1951.81) and complement C4A (m/z = 1895.43). Then, comparing urine samples from the post-treatment cases with those from the non-pregnant controls, we identified the peptides uromodulin fragments (m/z = 1682.34 and 1913.54) and complement C4A (m/z = 1895.43).

Liquid Biopsy Potential Biomarkers in Prostate Cancer

Prostate cancer (PCa) is the second most common cancer in men worldwide with an incidence of 14.8% and a mortality of 6.6%. Shortcomings in comprehensive medical check-ups in low- and middle-income countries lead to delayed detection of PCa and are causative of high numbers of advanced PCa cases at first diagnosis. The performance of available biomarkers is still insufficient and limited applicability, including logistical and financial burdens, impedes comprehensive implementation into health care systems. There is broad agreement on the need of new biomarkers to improve (i) early detection of PCa, (ii) risk stratification, (iii) prognosis, and (iv) treatment monitoring. This review focuses on liquid biopsy tests distinguishing high-grade significant (Gleason score (GS) ≥ 7) from low-grade indolent PCa. Available biomarkers still lack performance in risk stratification of biopsy naïve patients. However, biomarkers with highly negative predictive values may help to reduce unnecessary biopsies. Risk calculators using integrative scoring systems clearly improve decision-making for invasive prostate biopsy. Emerging biomarkers have the potential to substitute PSA and improve the overall performance of risk calculators. Until then, PSA should be used and may be replaced whenever enough evidence has accumulated for better performance of a new biomarker.

Promise and Implementation of Proteomic Prostate Cancer Biomarkers

Prostate cancer is one of the most commonly diagnosed malignancy and the fifth leading cause of cancer mortality in men. Despite the broad use of prostate-specific antigen test that resulted in an increase in number of diagnosed cases, disease management needs to be improved. Proteomic biomarkers alone and or in combination with clinical and pathological risk calculators are expected to improve on decreasing the unnecessary biopsies, stratify low risk patients, and predict response to treatment. To this end, significant efforts have been undertaken to identify novel biomarkers that can accurately discriminate between indolent and aggressive cancer forms and indicate those men at high risk for developing prostate cancer that require immediate treatment. In the era of “big data” and “personalized medicine” proteomics-based biomarkers hold great promise to provide clinically applicable tools, as proteins regulate all biological functions, and integrate genomic information with the environmental impact. In this review article, we aim to provide a critical assessment of the current proteomics-based biomarkers for prostate cancer and their actual clinical applicability. For that purpose, a systematic review of the literature published within the last 10 years was performed using the Web of Science Database. We specifically discuss the potential and prospects of use for diagnostic, prognostic and predictive proteomics-based biomarkers, including both body fluid- and tissue-based markers.

Approaches to the discovery of non-invasive urinary biomarkers of prostate cancer

Prostate cancer (PCa) continues to be one of the most common cancers in men worldwide. Prostate specific antigen (PSA) measured in blood has been used for decades as an aid for physicians to detect the presence of prostate cancer. However, the PSA test has limited sensitivity and specificity, leading to unnecessary biopsies, overdiagnosis and overtreatment of patients. For these reasons, there is an urgent need for more accurate PCa biomarkers that can detect PCa with high sensitivity and specificity. Urine is a unique source of potential protein biomarkers that can be measured in a non-invasive way. This review comprehensively summarizes state of the art approaches used in the discovery and validation of urinary biomarkers for PCa. Numerous strategies are currently being used in the discovery of urinary biomarkers for prostate cancer including gel-based separation techniques, mass spectrometry, activity-based proteomic assays and software approaches. Antibody-based approaches remain preferred method for validation of candidate biomarkers with rapidly advancing multiplex immunoassays and MS-based targeted approaches. In the last decade, there has been a dramatic acceleration in the development of new techniques and approaches in the discovery of protein biomarkers for prostate cancer including computational, statistical and data mining methods. Many urinary-based protein biomarkers have been identified and have shown significant promise in initial studies. Examples of these potential biomarkers and the methods utilized in their discovery are also discussed in this review.

Reprint of: Proteomics in cardiovascular diseases: Unveiling sex and gender differences in the era of precision medicine

Cardiovascular diseases (CVDs) represent the most important cause of mortality in women and in men. Contrary to the long-standing notion that the effects of the major risk factors on CVD outcomes are the same in both sexes, recent evidence recognizes new, potentially independent, sex/gender-related risk factors for CVDs, and sex/gender-differences in the clinical presentation of CVDs have been demonstrated. Furthermore, some therapeutic options may not be equally effective and safe in men and women. In this context, proteomics offers an extremely useful and versatile analytical platform for biomedical researches that expand from the screening of early diagnostic and prognostic biomarkers to the investigation of the molecular mechanisms underlying CDVs. In this review, we summarized the current applications of proteomics in the cardiovascular field, with emphasis on sex and gender-related differences in CVDs.

SIGNIFICANCE

Increasing evidence supports the profound effect of sex and gender on cardiovascular physio-pathology and the response to drugs. A clear understanding of the mechanisms underlying sexual dimorphisms in CVDs would not only improve our knowledge of the etiology of these diseases, but could also inform health policy makers and guideline committees in tailoring specific interventions for the prevention, treatment and management of CVDs in both men and women.

Urinary CE-MS peptide marker pattern for detection of solid tumors

Urinary profiling datasets, previously acquired by capillary electrophoresis coupled to mass-spectrometry were investigated to identify a general urinary marker pattern for detection of solid tumors by targeting common systemic events associated with tumor-related inflammation. A total of 2,055 urinary profiles were analyzed, derived from a) a cancer group of patients (n = 969) with bladder, prostate, and pancreatic cancers, renal cell carcinoma, and cholangiocarcinoma and b) a control group of patients with benign diseases (n = 556), inflammatory diseases (n = 199) and healthy individuals (n = 331). Statistical analysis was conducted in a discovery set of 676 cancer cases and 744 controls. 193 peptides differing at statistically significant levels between cases and controls were selected and combined to a multi-dimensional marker pattern using support vector machine algorithms. Independent validation in a set of 635 patients (293 cancer cases and 342 controls) showed an AUC of 0.82. Inclusion of age as independent variable, significantly increased the AUC value to 0.85. Among the identified peptides were mucins, fibrinogen and collagen fragments. Further studies are planned to assess the pattern value to monitor patients for tumor recurrence. In this proof-of-concept study, a general tumor marker pattern was developed to detect cancer based on shared biomarkers, likely indicative of cancer-related features.

Diagnosis of prostate cancer by analyzing oxidative stress in human seminal plasma: developing unsophisticated tools for noninvasive prostate cancer diagnosis

Prostate-specific antigen blood testing has improved early detection of prostate cancer (PCa); however, PCa mortality has not decreased accordingly and a prostate biopsy is still required for a definitive diagnosis. Proteomic biomarker screening in easily available body fluids such as seminal plasma is now increasingly being proposed as a solution to improve PCa detection and prognosis. PCa cells typically produce high levels of reactive oxygen species (ROS). In this study, we therefore investigated ROS levels in semen samples from patients with a negative or a positive prostate biopsy to predict PCa diagnosis. Multiple clinicopathological parameters (digital rectal examination, prostate-specific antigen scoring, prostate biopsy, and ROS levels) of patients examined for PCa were measured. No significant differences in ROS levels were detected in relation to PCa diagnosis. Although seminal plasma is a well-suited medium for prostate-related biomarkers, no significant differences in ROS levels were observed between the patient groups. Comparison with ROS levels encountered in semen of larger patient groups is the next logical step.

Optimization for Peptide Sample Preparation for Urine Peptidomics

Analysis of native or endogenous peptides in biofluids can provide valuable insight into disease mechanisms. Furthermore, the detected peptides may also have utility as potential biomarkers for noninvasive monitoring of human diseases. The noninvasive nature of urine collection and the abundance of peptides in the urine make analysis by high-throughput "peptidomics" methods an attractive approach for investigating the pathogenesis of renal disease. However, urine peptidomics methodologies can be problematic with regard to difficulties associated with sample preparation. The urine matrix can provide significant background interference in making the analytical measurements, in that it hampers both the identification of peptides and the depth of the peptidomics read when utilizing LC-MS-based peptidome analysis. We report on a novel adaptation of the standard solid-phase extraction (SPE) method to a modified SPE (mSPE) approach for improved peptide yield and analysis sensitivity with LC-MS-based peptidomics, in terms of time, cost, clogging of the LC-MS column, peptide yield, peptide quality, and number of peptides identified by each method. The mSPE method provides significantly improved efficiencies for the preparation of samples from urine. The mSPE method is found to be superior to the conventional, standard SPE method for urine peptide sample preparation when applying LC-MS peptidomics analysis, due to optimized sample cleanup that provides improved experimental inference from confidently identified peptides.

Proteomics in cardiovascular diseases: Unveiling sex and gender differences in the era of precision medicine

Cardiovascular diseases (CVDs) represent the most important cause of mortality in women and in men. Contrary to the long-standing notion that the effects of the major risk factors on CVD outcomes are the same in both sexes, recent evidence recognizes new, potentially independent, sex/gender-related risk factors for CVDs, and sex/gender-differences in the clinical presentation of CVDs have been demonstrated. Furthermore, some therapeutic options may not be equally effective and safe in men and women. In this context, proteomics offers an extremely useful and versatile analytical platform for biomedical researches that expand from the screening of early diagnostic and prognostic biomarkers to the investigation of the molecular mechanisms underlying CDVs. In this review, we summarized the current applications of proteomics in the cardiovascular field, with emphasis on sex and gender-related differences in CVDs.

SIGNIFICANCE

Increasing evidence supports the profound effect of sex and gender on cardiovascular physio-pathology and the response to drugs. A clear understanding of the mechanisms underlying sexual dimorphisms in CVDs would not only improve our knowledge of the etiology of these diseases, but could also inform health policy makers and guideline committees in tailoring specific interventions for the prevention, treatment and management of CVDs in both men and women.

Current state of the art for enhancing urine biomarker discovery

INTRODUCTION

Urine is a highly desirable biospecimen for biomarker analysis because it can be collected recurrently by non-invasive techniques, in relatively large volumes. Urine contains cellular elements, biochemicals, and proteins derived from glomerular filtration of plasma, renal tubule excretion, and urogenital tract secretions that reflect, at a given time point, an individual's metabolic and pathophysiologic state.

AREAS COVERED

High-resolution mass spectrometry, coupled with state of the art fractionation systems are revealing the plethora of diagnostic/prognostic proteomic information existing within urinary exosomes, glycoproteins, and proteins. Affinity capture pre-processing techniques such as combinatorial peptide ligand libraries and biomarker harvesting hydrogel nanoparticles are enabling measurement/identification of previously undetectable urinary proteins. Expert commentary: Future challenges in the urinary proteomics field include a) defining either single or multiple, universally applicable data normalization methods for comparing results within and between individual patients/data sets, and b) defining expected urinary protein levels in healthy individuals.

Whole-genome gene expression analysis in urine samples of patients with prostate cancer and benign prostate hyperplasia

OBJECTIVE

There is an urgent need to find new biomarkers with higher specificity and sensitivity for using early detection of prostate cancer (PrCa) and reducing recurrent unnecessary biopsy rates, psychological and physical stress on the patient, and costs. Being noninvasive, urine-based tests might be suitable in routine practice. The aim of this study was to report the first whole-genome gene expression analysis in urine samples, as noninvasive method, that were obtained from PrCa, benign prostate hyperplasia (BPH), and control groups by using the microarray system from Turkey, to our knowledge.

METHODS

Whole-genome gene expression profiling was conducted in urine samples of 25 patients with PrCa, 24 patients with BPH, and 11 healthy males by using the Illumina Hi Scan microarray system.

RESULTS

The number of probes showing a significant change at the level of expression were 101 and 75 in PrCa-control and BPH-control comparison groups, respectively. Further, 51 of them were the same in both comparison groups. There was no significant change at the level of expression in PrCa-BPH comparison group.

CONCLUSION

This study revealed several candidate biomarkers for early diagnosis of PrCa and contributed to the literature by detecting the differences of gene expression profiles in urine samples of PrCa-control and BPH-control comparison groups using the microarray. However, further studies are needed in larger groups.

Liquid biopsy: a step forward towards precision medicine in urologic malignancies

There is a growing trend towards exploring the use of a minimally invasive "liquid biopsy" to identify biomarkers in a number of cancers, including urologic malignancies. Multiple aspects can be assessed in circulating cell-free DNA, including cell-free DNA levels, integrity, methylation and mutations. Other prospective liquid biopsy markers include circulating tumor cells, circulating RNAs (miRNA, lncRNAs and mRNAs), cell-free proteins, peptides and exosomes have also emerged as non-invasive cancer biomarkers. These circulating molecules can be detected in various biological fluids, including blood, urine, saliva and seminal plasma. Liquid biopsies hold great promise for personalized medicine due to their ability to provide multiple non-invasive global snapshots of the primary and metastatic tumors. Molecular profiling of circulating molecules has been a stepping-stone to the successful introduction of several non-invasive multi-marker tests into the clinic. In this review, we provide an overview of the current state of cell-free DNA-based kidney, prostate and bladder cancer biomarker research and discuss the potential utility other circulating molecules. We will also discuss the challenges and limitations facing non-invasive cancer biomarker discovery and the benefits of this growing area of translational research.

Evaluation of sulfur isotopic enrichment of urine metabolites for the differentiation of healthy and prostate cancer mice after the administration of 34S labelled yeast

Sulfur isotopic enrichment of urine metabolites in healthy and prostate cancer mice using ³⁴S enriched yeast and High Performance Liquid Chromatography coupled to Multicollector Inductively Coupled Plasma Mass Spectrometry (HPLC-MC-ICP-MS) has been evaluated. A 30 weeks experiment (since the eleventh to the fortieth week of life) was carried out collecting the urine of three healthy mice and three transgenic mice with prostate cancer during 24h after a single oral administration of a ³⁴S enriched yeast slurry. The isotopic enrichment of different sulphur metabolites was monitored by coupling a C18 reverse phase HPLC column with a multicollector ICP-MS using a membrane desolvating system. Quantification of sulfur in the chromatographic peaks was carried out by post-column isotope dilution using a ³³S enriched spike. Differences between the ³⁴S enrichment in the urine metabolites of healthy and prostate cancer mice were found from the beginning of the disease. Both populations could be differentiated using a principal component analysis (PCA). Finally, 7 unknown mice were correctly classified in each population using a linear discriminant analysis.

Urinary biomarkers for renal tract malformations

INTRODUCTION

Renal tract malformations (RTMs) are congenital anomalies of the kidneys and urinary tract, which are the major cause of end-stage renal disease in children. Using immunoassay-based approaches (ELISA, western blot), individual urinary proteins including transforming growth factor β, tumor necrosis factor and monocyte attractant proteins 1 were found to be associated to RTMs. However, only mass spectrometry (MS) based methods leading to the identification of panels of protein-based markers composed of fragments of the extracellular matrix allowed the prediction of progression of RTMs and its complications. Areas covered: In this review, we summarized relevant studies identified in "Pubmed" using the keywords "urinary biomarkers" and "proteomics" and "renal tract malformations" or "hydronephrosis" or "ureteropelvic junction obstruction" or "posterior urethral valves" or "vesicoureteral reflux". These publications represent studies on potential protein-based biomarkers, either individually or combined in panels, of RTMs in human and animal models. Expert commentary: Successful use in the clinic of these protein-based biomarkers will need to involve larger scale studies to reach sufficient power. Improved performance will potentially come from combining immunoassay- and MS-based markers.

Proteomics and peptidomics: moving toward precision medicine in urological malignancies

Urological malignancies are a major cause of morbidity and mortality worldwide. Advances in early detection, diagnosis, prognosis and prediction of treatment response can significantly improve patient care. Proteomic and peptidomic profiling studies are at the center of kidney, prostate and bladder cancer biomarker discovery and have shown great promise for improved clinical assessment. Mass spectrometry (MS) is the most widely employed method for proteomic and peptidomic analyses. A number of MS platforms have been developed to facilitate accurate identification of clinically relevant markers in various complex biological samples including tissue, urine and blood. Furthermore, protein profiling studies have been instrumental in the successful introduction of several diagnostic multimarker tests into the clinic. In this review, we will provide a brief overview of high-throughput technologies for protein and peptide based biomarker discovery. We will also examine the current state of kidney, prostate and bladder cancer biomarker research as well as review the journey toward successful clinical implementation.

Amyloid-β Precursor Protein Modulates the Sorting of Testican-1 and Contributes to Its Accumulation in Brain Tissue and Cerebrospinal Fluid from Patients with Alzheimer Disease

The mechanisms leading to amyloid-β (Aβ) accumulation in sporadic Alzheimer disease (AD) are unknown but both increased production or impaired clearance likely contribute to aggregation. To understand the potential roles of the extracellular matrix proteoglycan Testican-1 in the pathophysiology of AD, we used samples from AD patients and controls and an in vitro approach. Protein expression analysis showed increased levels of Testican-1 in frontal and temporal cortex of AD patients; histological analysis showed that Testican-1 accumulates and co-aggregates with Aβ plaques in the frontal, temporal and entorhinal cortices of AD patients. Proteomic analysis identified 10 fragments of Testican-1 in cerebrospinal fluid (CSF) from AD patients. HEK293T cells expressing human wild type or mutant Aβ precursor protein (APP) were transfected with Testican-1. The co-expression of both proteins modified the sorting of Testican-1 into the endocytic pathway leading to its transient accumulation in Golgi, which seemed to affect APP processing, as indicated by reduced Aβ40 and Aβ42 levels in APP mutant cells. In conclusion, patient data reflect a clearance impairment that may favor Aβ accumulation in AD brains and our in vitro model supports the notion that the interaction between APP and Testican-1 may be a key step in the production and aggregation of Aβ species.

Urine proteome analysis as a discovery tool in patients with deep vein thrombosis and pulmonary embolism

PURPOSE

Early and accurate detection of deep vein thrombosis (DVT) is an important clinical need. Based on the hypothesis that urinary peptides may hold information on DVT in conjunction with pulmonary embolism (PE), the study was aimed at identifying such peptide biomarkers using capillary electrophoresis coupled mass spectrometry.

EXPERIMENTAL DESIGN

Patients with symptoms of unprovoked/idiopathic DVT and/or PE were examined by doppler-sonography or angio-computed tomography. Urinary proteome analysis allowed for identification of respective peptide biomarkers. To confirm their biological relevance, we induced PE in mice and assessed human ex vivo thrombi.

RESULTS

We identified 62 urinary peptides as DVT-specific biomarkers, i.e. fragments of collagen type I and a fragment of fibrinogen β-chain. The presence of fibrinogen α/β in the acute thrombus, and collagen type I and osteopontin in the older, organized thrombus was demonstrated. The classifier DVT62 established through support vector machine (SVM) modeling based on the 62 identified peptides was validated in an independent cohort of 47 subjects (six cases and 41 controls) with a sensitivity of 100% and specificity of 83%.

CONCLUSIONS AND CLINICAL RELEVANCE

Urine proteome analysis enabled the detection of DVT-specific peptides, which were validated in human and mouse tissue. Furthermore, it allowed for the establishment of an urinary-proteome based classifier that is relatively specific for DVT. The data provide the basis for assessment of these biomarkers in a prospective clinical study.

Urinary proteomics and metabolomics studies to monitor bladder health and urological diseases

Background

Assays of molecular biomarkers in urine are non-invasive compared to other body fluids and can be easily repeated. Based on the hypothesis that the secreted markers from the diseased organs may locally release into the body fluid in the vicinity of the injury, urine-based assays have been considered beneficial to monitoring bladder health and urological diseases. The urine proteome is much less complex than the serum and tissues, but nevertheless can contain biomarkers for diagnosis and prognosis of diseases. The urine metabolome has a much higher number and concentration of low-molecular metabolites than the serum or tissues, with a far lower lipid concentration, yet informs directly about dietary and microbial metabolism.

Discussion

We here discuss the use of mass spectrometry-based proteomics and metabolomics for urine biomarker assays, specifically with respect to the underlying mechanisms that trigger the pathological condition.

Conclusion

Molecular biomarker profiles, based on proteomics and metabolomics studies, reliably distinguish patients from healthy controls, stratify sub-populations with respect to treatment options, and predict therapeutic response of patients with urological disease.

Implementation of CE-MS-identified proteome-based biomarker panels in drug development and patient management

The recent advancements in clinical proteomics enabled identification of biomarker panels for a large range of diseases. A number of CE-MS-identified biomarker panels were verified and implemented in clinical studies. Despite multiple challenges, accumulating evidence supports the value and the need for proteome-based biomarker panels. In this perspective, we provide an overview of clinical studies indicating the added value of CE-MS biomarker panels over traditional diagnostics and monitoring methods. We outline apparent advantages of applying novel proteomic biomarker panels for disease diagnosis, prognosis, staging, drug development and patient management. Facing the plethora of benefits associated with the use of CE-MS biomarker panels, we envision their implementation into the medical practice in the near future.

Recent progress in urinary proteome analysis for prostate cancer diagnosis and management

Prostate cancer (PCa) is fifth leading cause of cancer-associated deaths in men worldwide. Although the application of the serum prostate-specific antigen (PSA) screening test resulted in an increase in the PCa diagnosed cases, it demonstrated a negligible benefit regarding the associated mortality. Treatment options vary, with active surveillance to be preferable for patients with low-risk PCa and therapy of advanced castration-resistant PCa to rely on α-emitters and cytotoxic chemotherapy. Although recent developments have led to the approval of novel drugs for the treatment of castration-resistant PCa, the optimal sequence and timing of medication have not been yet determined. New screening modalities could improve the discriminatory accuracy between tumors with favorable clinical prognosis. Implementation of proteomic-based biomarkers appears to be a promising improvement, which could enable a more accurate diagnosis, guide treatment and improve patient outcome. Reviewed here are urinary proteome-based approaches for detection of PCa and patient management.