Urinary glycoprotein biomarker discovery for bladder cancer detection using LC/MS-MS and label-free quantification

Transduction of Glycan-Lectin Binding via an Impedimetric Sensor for Glycoprotein Detection

Glycoproteins are produced by glycosylation modification of proteins, and a number of glycoproteins have served as important tumor biomarkers in clinical application. Alpha-fetoprotein (AFP) is one of the representative glycoproteins that has been employed as a useful predictive and prognostic biomarker for hepatocellular carcinoma. Human AFP has an N-glycan portion at the asparagine residue, which includes four N-acetyl-glucosamine and three mannoses. In this work, building upon lectin-glycan interactions, one type of facile and capable impedimetric biosensor was fabricated utilizing microwave-prepared NH2-MIL-101(Fe) to decorate lectins as a recognition element. Two different lectins of wheat-germ agglutinin (WGA) and concanavalin A (Con A) were employed to target the N-acetyl-glucosamine and mannose of N-glycan in AFP, respectively. This work has not only accomplished the sensitive impedimetric biosensing of the AFP tumor marker (with the limit of detection down to 0.5 pg/mL and linear concentration spanning 5 orders of magnitude from 10-2 to 103 ng/mL) but also replied on two kinds of lectins to "read" the sugar chain, transducing the minor difference of this process to impedimetric signals for display. The impedimetric data shed some light on the local microenvironment of the lectin-glycan binding event, providing some electrochemical experimental support for the biantennary structure of N-glycan in AFP. The mannoses were "buried" in the interior core of the whole N-glycan, increasing steric hindrance for Con A to approach and thus rendering the WGA@MIL-101(Fe)-based biosensor more superior sensing responses.

Application of raman spectroscopy in the non-invasive diagnosis of urological diseases via urine

OBJECTIVES

The objective of this review is to provide a comprehensive overview of the utilization of Raman spectroscopy in urinary system diseases, highlighting its potential in non-invasive diagnostic methodologies for early diagnosis and prognostic assessment of urinary ailments.

METHODS

We searched PubMed, Web of Science, and Google Scholar using 'raman,' 'bladder,' 'kidney,' 'prostate,' 'cancer,' 'infection,' 'stone or urinary calculi,' and 'urine or urinary,' along with 'AND' and 'OR' to refine our search. We excluded irrelevant articles and screened potential ones based on titles and abstracts before assessing the full texts for relevance and quality.

FINDINGS

The findings indicate that RS can furnish data on biomolecules in urine, which is significant for non-invasive diagnostic approaches. It has shown potential within non-invasive diagnostic methodologies and is expected to play a pivotal role in the early diagnosis and prognostic assessment of urinary system diseases, such as malignancies, urinary tract infections, kidney diseases, urolithiasis, and other urinary conditions.

CONCLUSIONS

Raman spectroscopy has demonstrated significant potential in providing precise and rapid diagnostic approaches for clinical use in the context of urinary system diseases. Its ability to analyze biomolecules non-invasively positions it as an increasingly important tool in the early diagnosis and prognostic assessment of these conditions.

Temporal Assessment of Protein Stability in Dried Blood Spots

The use of protein biomarkers in blood for clinical settings is limited by the cost and accessibility of traditional venipuncture sampling. The dried blood spot (DBS) technique offers a less invasive and more accessible alternative. However, protein stability in DBS has not been well evaluated. Herein, we deployed a quantitative LC-MS/MS system to construct proteomic atlases of whole blood, DBSs, plasma, and blood cells. Approximately 4% of detected proteins' abundance was significantly altered during blood drying into blood spots, with overwhelming disturbances in cytoplasmic fraction. We also reported a novel finding suggesting a decrease in the level of membrane/cytoskeletal proteins (SLC4A1, RHAG, DSC1, DSP, and JUP) and an increase in the level of proteins (ATG3, SEC14L4, and NRBP1) related to intracellular trafficking. Furthermore, we identified 19 temporally dynamic proteins in DBS samples stored at room temperature for up to 6 months. There were three declined cytoskeleton-related proteins (RDX, SH3BGRL3, and MYH9) and four elevated proteins (XPO7, RAN, SLC2A1, and SLC29A1) involved in cytoplasmic transport as representatives. The instability was governed predominantly by hydrophilic proteins and enhanced significantly with an increasing storage time. Our analyses provide comprehensive knowledge of both short- and long-term storage stability of DBS proteins, forming the foundation for the widespread use of DBS in clinical proteomics and other analytical applications.

Identification of novel protein biomarkers from the blood and urine for the early diagnosis of bladder cancer via proximity extension analysis

BACKGROUND

Bladder cancer (BC) is a very common urinary tract malignancy that has a high incidence and lethality. In this study, we identified BC biomarkers and described a new noninvasive detection method using serum and urine samples for the early detection of BC.

METHODS

Serum and urine samples were retrospectively collected from patients with BC (n = 99) and healthy controls (HC) (n = 50), and the expression levels of 92 inflammation-related proteins were examined via the proximity extension analysis (PEA) technique. Differential protein expression was then evaluated by univariate analysis (p < 0.05). The expression of the selected potential marker was further verified in BC and adjacent tissues by immunohistochemistry (IHC) and single-cell sequencing. A model was constructed to differentiate BC from HC by LASSO regression and compared to the detection capability of FISH.

RESULTS

The univariate analysis revealed significant differences in the expression levels of 40 proteins in the serum (p < 0.05) and 17 proteins in the urine (p < 0.05) between BC patients and HC. Six proteins (AREG, RET, WFDC2, FGFBP1, ESM-1, and PVRL4) were selected as potential BC biomarkers, and their expression was evaluated at the protein and transcriptome levels by IHC and single-cell sequencing, respectively. A diagnostic model (a signature) consisting of 14 protein markers (11 in serum and three in urine) was also established using LASSO regression to distinguish between BC patients and HC (area under the curve = 0.91, PPV = 0.91, sensitivity = 0.87, and specificity = 0.82). Our model showed better diagnostic efficacy than FISH, especially for early-stage, small, and low-grade BC.

CONCLUSION

Using the PEA method, we identified a panel of potential protein markers in the serum and urine of BC patients. These proteins are associated with the development of BC. A total of 14 of these proteins can be used to detect early-stage, small, low-grade BC. Thus, these markers are promising for clinical translation to improve the prognosis of BC patients.

Urinary markers for bladder cancer diagnosis: A review of current status and future challenges

Bladder cancer is a common urological cancer with a high recurrence rate that requires long-term follow-up, and early detection positively affects prognosis. To date, the initial diagnosis and follow-up for bladder cancer rely on cystoscopy, which is an invasive and expensive procedure. Therefore, urinary markers for the detection of bladder cancer have attracted research attention for decades to reduce unnecessary cystoscopies. Urine, which is in continuous contact with bladder cancer, is considered a suitable fluid for providing tumor information. Urinary cytology is the only widely used urinary marker in clinical practice; however, it has poor sensitivity for low-grade tumors; indicating the need for novel urinary markers. Considerable research has been conducted on this topic over the years, resulting in a complex landscape with a wide range of urinary markers, including protein-, exfoliated cell-, RNA-, DNA-, and extracellular vesicle-based markers. Although some of these markers have been approved by the U.S. Food and Drug Administration and are commercially available, their use in clinical practice is limited. To facilitate clinical application, potential urinary markers must withstand prospective clinical trials and be easy for patients and clinicians to understand and utilize in a clinical context. This review provides a comprehensive overview of currently available and recently reported promising urinary markers for bladder cancer. Additionally, the challenges and the prospects of these urinary markers for clinical implementation in bladder cancer treatment were discussed.

Recent progress in mass spectrometry-based urinary proteomics

Serum or plasma is frequently utilized in biomedical research; however, its application is impeded by the requirement for invasive sample collection. The non-invasive nature of urine collection makes it an attractive alternative for disease characterization and biomarker discovery. Mass spectrometry-based protein profiling of urine has led to the discovery of several disease-associated biomarkers. Proteomic analysis of urine has not only been applied to disorders of the kidney and urinary bladder but also to conditions affecting distant organs because proteins excreted in the urine originate from multiple organs. This review provides a progress update on urinary proteomics carried out over the past decade. Studies summarized in this review have expanded the catalog of proteins detected in the urine in a variety of clinical conditions. The wide range of applications of urine analysis-from characterizing diseases to discovering predictive, diagnostic and prognostic markers-continues to drive investigations of the urinary proteome.

Facial on-line enrichment of glycoproteins by capillary electrophoresis with boronate-functionalized poly(glycidyl methacrylate) microparticles coated column

A facial and rapid method for glycoproteins enrichment by capillary electrophoresis was developed. The 3-aminophenylboronic acid-functionalized poly(glycidyl methacrylate) microparticles (PGMA@APBA) were attached to the capillary inlet (length of ∼1.5 cm) by electrostatic self-assemble action to prepare a partially coated capillary column. The process is simple and reversible, allowing for easy renewal of the PGMA@APBA coating when its enrichment efficiency decreases. By utilizing the coated column, glycoproteins can be enriched within 2 min. The column exhibits a specific enrichment for glycoproteins and can be consecutively used for approximately 60 runs. The relative standard deviations (RSDs) of peak area of run-to-run (n = 5) and batch-to-batch (n = 3) were 1.5 % and 1.0%, respectively. The method was successfully applied to enrich glycoproteins from 1 × 1012-fold diluted real egg white sample, indicating its practical applicability.

Exploration of potential biomarkers for early bladder cancer based on urine proteomics

Background

Bladder cancer is a common malignant tumor of the urinary system. The progression of the condition is associated with a poor prognosis, so it is necessary to identify new biomarkers to improve the diagnostic rate of bladder cancer.

Methods

In this study, 338 urine samples (144 bladder cancer, 123 healthy control, 32 cystitis, and 39 upper urinary tract cancer samples) were collected, among which 238 samples (discovery group) were analyzed by LC-MS. The urinary proteome characteristics of each group were compared with those of bladder cancer, and the differential proteins were defined by bioinformatics analysis. The pathways and functional enrichments were annotated. The selected proteins with the highest AUC score were used to construct a diagnostic panel. One hundred samples (validation group) were used to test the effect of the panel by ELISA.

Results

Compared with the healthy control, cystitis and upper urinary tract cancer samples, the number of differential proteins in the bladder cancer samples was 325, 158 and 473, respectively. The differentially expressed proteins were mainly related to lipid metabolism and iron metabolism and were involved in the proliferation, metabolism and necrosis of bladder cancer cells. The AUC of the panel of APOL1 and ITIH3 was 0.96 in the discovery group. ELISA detection showed an AUC of 0.92 in the validation group.

Conclusion

This study showed that urinary proteins can reflect the pathophysiological changes in bladder cancer and that important molecules can be used as biomarkers for bladder cancer screening. These findings will benefit the application of the urine proteome in clinical research.

Glycosylation Analysis of Urinary Peptidome Highlights IGF2 Glycopeptides in Association with CKD

Chronic kidney disease (CKD) is prevalent in 10% of world’s adult population. The role of protein glycosylation in causal mechanisms of CKD progression is largely unknown. The aim of this study was to identify urinary O-linked glycopeptides in association to CKD for better characterization of CKD molecular manifestations. Urine samples from eight CKD and two healthy subjects were analyzed by CE-MS/MS and glycopeptides were identified by a specific software followed by manual inspection of the spectra. Distribution of the identified glycopeptides and their correlation with Age, eGFR and Albuminuria were evaluated in 3810 existing datasets. In total, 17 O-linked glycopeptides from 7 different proteins were identified, derived primarily from Insulin-like growth factor-II (IGF2). Glycosylation occurred at the surface exposed IGF2 Threonine 96 position. Three glycopeptides (DVStPPTVLPDNFPRYPVGKF, DVStPPTVLPDNFPRYPVG and DVStPPTVLPDNFPRYP) exhibited positive correlation with Age. The IGF2 glycopeptide (tPPTVLPDNFPRYP) showed a strong negative association with eGFR. These results suggest that with aging and deteriorating kidney function, alterations in IGF2 proteoforms take place, which may reflect changes in mature IGF2 protein. Further experiments corroborated this hypothesis as IGF2 increased plasma levels were observed in CKD patients. Protease predictions, considering also available transcriptomics data, suggest activation of cathepsin S with CKD, meriting further investigation.

Protein glycosylation in urine as a biomarker of diseases

Human body fluids have become an indispensable resource for clinical research, diagnosis and prognosis. Urine is widely used to discover disease-specific glycoprotein biomarkers because of its recurrently non-invasive collection and disease-indicating properties. While urine is an unstable fluid in that its composition changes with ingested nutrients and further as it is excreted through micturition, urinary proteins are more stable and their abnormal glycosylation is associated with diseases. It is known that aberrant glycosylation can define tumor malignancy and indicate disease initiation and progression. However, a thorough and translational survey of urinary glycosylation in diseases has not been performed. In this article, we evaluate the clinical applications of urine, introduce methods for urine glycosylation analysis, and discuss urine glycoprotein biomarkers. We emphasize the importance of mining urinary glycoproteins and searching for disease-specific glycosylation in various diseases (including cancer, neurodegenerative diseases, diabetes, and viral infections). With advances in mass spectrometry-based glycomics/glycoproteomics/glycopeptidomics, characterization of disease-specific glycosylation will optimistically lead to the discovery of disease-related urinary biomarkers with better sensitivity and specificity in the near future.

Cancer-Associated Membrane Protein as Targeted Therapy for Bladder Cancer

Bladder cancer (BC) recurrence is one of the primary clinical problems encountered by patients following chemotherapy. However, the mechanisms underlying their resistance to chemotherapy remain unclear. Alteration in the pattern of membrane proteins (MPs) is thought to be associated with this recurrence outcome, often leading to cell dysfunction. Since MPs are found throughout the cell membrane, they have become the focus of attention for cancer diagnosis and treatment. Identifying specific and sensitive biomarkers for BC, therefore, requires a major collaborative effort. This review describes studies on membrane proteins as potential biomarkers to facilitate personalised medicine. It aims to introduce and discuss the types and significant functions of membrane proteins as potential biomarkers for future medicine. Other types of biomarkers such as DNA-, RNA- or metabolite-based biomarkers are not included in this review, but the focus is mainly on cell membrane surface protein-based biomarkers.

A Diagnostic Gene Expression Signature for Bladder Cancer Can Stratify Cases into Prescribed Molecular Subtypes and Predict Outcome

Bladder cancer is a biologically heterogeneous disease with variable clinical presentations, outcomes and responses to therapy. Thus, the clinical utility of single biomarkers for the detection and prediction of biological behavior of bladder cancer is limited. We have previously identified and validated a bladder cancer diagnostic signature composed of 10 biomarkers, which has been incorporated into a multiplex immunoassay bladder cancer test, Oncuria™. In this study, we evaluate whether these 10 biomarkers can assist in the prediction of bladder cancer clinical outcomes. Tumor gene expression and patient survival data from bladder cancer cases from The Cancer Genome Atlas (TCGA) were analyzed. Alignment between the mRNA expression of 10 biomarkers and the TCGA 2017 subtype classification was assessed. Kaplan-Meier analysis of multiple gene expression datasets indicated that high expression of the combined 10 biomarkers correlated with a significant reduction in overall survival. The analysis of three independent, publicly available gene expression datasets confirmed that multiplex prognostic models outperformed single biomarkers. In total, 8 of the 10 biomarkers from the Oncuria™ test were significantly associated with either luminal or basal molecular subtypes, and thus, the test has the potential to assist in the prediction of clinical outcome.

Proteomics for Early Detection of Non-Muscle-Invasive Bladder Cancer: Clinically Useful Urine Protein Biomarkers

Bladder cancer is the fourth most common cancer in men, and most cases are non-muscle-invasive. A high recurrence rate is a critical problem in non-muscle-invasive bladder cancer. The availability of few urine tests hinders the effective detection of superficial and small bladder tumors. Cystoscopy is the gold standard for diagnosis; however, it is associated with urinary tract infections, hematuria, and pain. Early detection is imperative, as intervention influences recurrence. Therefore, urinary biomarkers need to be developed to detect these bladder cancers. Recently, several protein candidates in the urine have been identified as biomarkers. In the present narrative review, the current status of the development of urinary protein biomarkers, including FDA-approved biomarkers, is summarized. Additionally, contemporary proteomic technologies, such as antibody-based methods, mass-spectrometry-based methods, and machine-learning-based diagnosis, are reported. Furthermore, new strategies for the rapid and correct profiling of potential biomarkers of bladder cancer in urine are introduced, along with their limitations. The advantages of urinary protein biomarkers and the development of several related technologies are highlighted in this review. Moreover, an in-depth understanding of the scientific background and available protocols in research and clinical applications of the surveillance of non-muscle bladder cancer is provided.

Application of a multiplex urinalysis test for the prediction of intravesical BCG treatment response: A pilot study

BACKGROUND

Intravesical Bacillus Calmette-Guerin (BCG), a live attenuated tuberculosis vaccine that acts as a non-specific immune system stimulant, is the most effective adjuvant treatment for patients with intermediate or high-risk non-muscle-invasive bladder cancer (NMIBC). However, to date, there are no reliable tests that are predictive of BCG treatment response. In this study, we evaluated the performance of OncuriaTM, a bladder cancer detection test, to predict response to intravesical BCG.

METHODS

OncuriaTM data was evaluated in voided urine samples obtained from a prospectively collected cohort of 64 subjects with intermediate or high risk NMIBC prior to treatment with intravesical BCG. The OncuriaTM test, which measures 10 cancer-associated biomarkers was performed in an independent clinical laboratory. The ability of the test to identify those patients in whom BCG is ineffective against tumor recurrence was tested. Predictive models were derived using supervised learning and cross-validation analyses. Model performance was assessed using ROC curves.

RESULTS

Pre-treatment urinary concentrations of MMP9, VEGFA, CA9, SDC1, PAI1, APOE, A1AT, ANG and MMP10 were increased in patients who developed disease recurrence. A combinatorial predictive model of treatment outcome achieved an AUROC 0.89 [95% CI: 0.80-0.99], outperforming any single biomarker, with a test sensitivity of 81.8% and a specificity of 84.9%. Hazard ratio analysis revealed that patients with higher urinary levels of ANG, CA9 and MMP10 had a significantly higher risk of disease recurrence.

CONCLUSIONS

Monitoring the urinary levels of a cancer-associated biomarker panel enabled the discrimination of patients who did not respond to intravesical BCG therapy. With further study, the multiplex OncuriaTM test may be applicable for the clinical evaluation of bladder cancer patients considering intravesical BCG treatment.

Blood-based protein biomarkers in bladder urothelial tumors

Bladder cancer (BC) is the fifth most common cancer with a high prevalence rate. It is classically classified in two groups, namely non-muscle invasive (NMIBC) and muscle invasive (MIBC). NMIBC accounts for 75% of cases and has a better prognosis than MIBC. However, 30-50% of the NMIBC patients will show recurrences throughout their lives, and about 10-20% of them will progress to MIBC, with frequent metastasis and a reduced survival rate. The diagnosis of bladder cancer is confirmed by direct visualization of the tumour and other mucosal abnormalities with endoscopic excision using cystoscopy and transurethral resection of the bladder (TURBT). An adequate TURBT requires complete resection of all visible tumour with appropriate sampling of the bladder to assess the depth of invasion. However, for many years, researchers have attempted to identify and utilise urinary markers for bladder cancer detection. Voided urine cytology has been the mainstay of urine-based diagnosis of bladder cancer since originally described by Papanicolau and Marshall. Nonetheless, urine cytology has several drawbacks, including a poor sensitivity for low-grade/stage tumours, a lack of interobserver consistency and a variable range of readings (e.g., atypical, atypical-suspicious, non-diagnostic). These shortcomings have inspired the search for more sensitive bladder cancer biomarkers. To bring precision medicine to genitourinary oncology, the analysis of the plasma/serum wide genome and proteome offers promising possibilities.

Influencing Factors on the Oncuria™ Urinalysis Assay: An Experimental Model

Background: The Oncuria™ urine test for the detection of bladder cancer measures a multiplex protein signature. In this study, we investigated the influence of urinary cellularity, protein, and hematuria on the performance of the Oncuria™ test in an ex vivo experimental model. Materials and Methods: Pooled urine from healthy subjects was spiked with cultured benign (UROtsa) or malignant cells (T24), cellular proteins, or whole blood. The resulting samples were analyzed using the Oncuria™ test following the manufacturer’s instructions. Results: Urine samples obtained from healthy subjects were negative for bladder cancer by Oncuria™ test criteria. The majority of the manipulated conditions did not result in a false-positive test. The addition of whole blood (high concentration) did result in a false-positive result, but this was abrogated by sample centrifugation prior to analysis. The addition of cellular proteins (high concentration) resulted in a positive Oncuria™ test, and this was unaffected by pre-analysis sample centrifugation. Conclusions: The Oncuria™ multiplex test performed well in the ex vivo experimental model and shows promise for clinical application. The identification of patients who require additional clinical evaluation could reduce the need to subject patients who do not have bladder cancer to frequent, uncomfortable and expensive cystoscopic examinations, thus benefiting both patients and the healthcare system.

Diagnostic performance of Oncuria™, a urinalysis test for bladder cancer

BACKGROUND

Due to insufficient accuracy, urine-based assays currently have a limited role in the management of patients with bladder cancer. The identification of multiplex molecular signatures associated with disease has the potential to address this deficiency and to assist with accurate, non-invasive diagnosis and monitoring.

METHODS

To evaluate the performance of Oncuria™, a multiplex immunoassay for bladder detection in voided urine samples. The test was evaluated in a multi-institutional cohort of 362 prospectively collected subjects presenting for bladder cancer evaluation. The parallel measurement of 10 biomarkers (A1AT, APOE, ANG, CA9, IL8, MMP9, MMP10, PAI1, SDC1 and VEGFA) was performed in an independent clinical laboratory. The ability of the test to identify patients harboring bladder cancer was assessed. Bladder cancer status was confirmed by cystoscopy and tissue biopsy. The association of biomarkers and demographic factors was evaluated using linear discriminant analysis (LDA) and predictive models were derived using supervised learning and cross-validation analyses. Diagnostic performance was assessed using ROC curves.

RESULTS

The combination of the 10 biomarkers provided an AUROC 0.93 [95% CI 0.87-0.98], outperforming any single biomarker. The addition of demographic data (age, sex, and race) into a hybrid signature improved the diagnostic performance AUROC 0.95 [95% CI 0.90-1.00]. The hybrid signature achieved an overall sensitivity of 0.93, specificity of 0.93, PPV of 0.65 and NPV of 0.99 for bladder cancer classification. Sensitivity values of the diagnostic panel for high-grade bladder cancer, low-grade bladder cancer, MIBC and NMIBC were 0.94, 0.89, 0.97 and 0.93, respectively.

CONCLUSIONS

Urinary levels of a biomarker panel enabled the accurate discrimination of bladder cancer patients and controls. The multiplex Oncuria™ test can achieve the efficient and accurate detection and monitoring of bladder cancer in a non-invasive patient setting.

Discovery of Novel Protein Biomarkers in Urine for Diagnosis of Urothelial Cancer Using iTRAQ Proteomics

Urothelial carcinoma (UC) is the ninth most prevalent malignancy worldwide. Noninvasive and efficient biomarkers with high accuracy are imperative for the surveillance and diagnosis of UC. CKD patients were enrolled as a control group in this study for the discovery of highly specific urinary protein markers of UC. An iTRAQ-labeled quantitative proteomic approach was used to discover novel potential markers. These markers were further validated with 501 samples by ELISA assay, and their diagnostic accuracies were compared to those of other reported UC markers. BRDT, CYBP, GARS, and HDGF were identified as novel urinary UC biomarkers with a high discrimination ability in a population comprising CKD and healthy subjects. The diagnostic values of the four novel UC markers were better than that of a panel of well-known or FDA-approved urinary protein markers CYFR21.1, Midkine, and NUMA1. Three of our discovered markers (BRDT, HDGF, GARS) and one well-known marker (CYFR21.1) were finally selected and combined as a marker panel having AUC values of 0.962 (95% CI, 0.94-0.98) and 0.860 (95% CI, 0.83-0.89) for the discrimination between UC and normal groups and UC and control (healthy + CKD) groups, respectively.

Identification of potential glycoprotein biomarkers in oral squamous cell carcinoma using sweet strategies

The prevalence of oral squamous cell carcinoma (OSCC) is high in South and Southeast Asia regions. Most OSCC patients are detected at advanced stages low 5-year survival rates. Aberrant expression of glycosylated proteins was found to be associated with malignant transformation and cancer progression. Hence, identification of cancer-associated glycoproteins could be used as potential biomarkers that are beneficial for diagnosis or clinical management of patients. This study aims to identify the differentially expressed glycoproteins using lectin-based glycoproteomics approaches. Serum samples of 40 patients with OSCC, 10 patients with oral potentially malignant disorder (OPMD), and 10 healthy individuals as control group were subjected to two-dimensional gel electrophoresis (2-DE) coupled with lectin Concanavalin A and Jacalin that specifically bind to N- and O-glycosylated proteins, respectively. Five differentially expressed N- and O-glycoproteins with various potential glycosylation sites were identified, namely N-glycosylated α1-antitrypsin (AAT), α2-HS-glycoprotein (AHSG), apolipoprotein A-I (APOA1), and haptoglobin (HP); as well as O-glycosylated AHSG and clusterin (CLU). Among them, AAT and APOA1 were further validated using enzyme-linked immunosorbent assay (ELISA) (n = 120). It was found that AAT and APOA1 are significantly upregulated in OSCC and these glycoproteins are independent risk factors of OSCC. The clinical utility of AAT and APOA1 as potential biomarkers of OSCC is needed for further evaluation.

Analytical validation of ONCURIA™ a multiplex bead-based immunoassay for the non-invasive bladder cancer detection

Background

The objective of our study was to assess the analytical performance of a multiplex assay (Oncuria™) to quantify protein biomarkers towards a bladder cancer associated diagnostic signature in voided urine.

Method

ology: Using Luminex xMAP technology, a custom immunoassay was developed to measure the concentrations of 10 urinary analytes (angiogenin, ANG; apolipoprotein E, APOE; alpha-1 antitrypsin, A1AT; carbonic anhydrase 9, CA9; interleukin 8, IL8; matrix metallopeptidase 9, MMP9; matrix metallopeptidase 10, MMP10; plasminogen activator inhibitor 1, PAI1; syndecan 1, SDC1; vascular endothelial growth factor, VEGF). Selectivity, sensitivity, specificity, precision, linearity, dynamic range, and detection threshold were assessed using recombinant proteins and human urine samples. Analytical variability with respect to batch size, run, day, operator, and interference were also evaluated.

Results

Analytical evaluation demonstrated a) all antigen cross-reactivity was noted to be <1% of the tested concentration, b) minimal detected dose ranged from 0.295 ​pg/mL in IL8 to 31.1 ​pg/mL in APOE, c) highly reproducible and accurate noting coefficient of variation (CV) and relative error (RE) values below 15% for all analytes and d) minimal interference. The assay can be completed in <5 ​h using as little as 150 ​μL of voided urine.

Conclusion

To our knowledge, this is the first multiplex bead-based immunoassay for the non-invasive detection of bladder cancer that has been analytically validated as a tool with the potential to help clinicians manage patients at risk of harboring bladder cancer.

•

Cytology has changed little since its inception in 1947 and suffers from low detection sensitivity for bladder cancer.

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Oncuria™ is a multiplex bead-based immunoassay.

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Oncuria™ has limited antigen cross-reactivity and interference and favorable detected dose and reproducibility.

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Oncuria ™, an accurate multiplex detection assay for bladder cancer, can be performed on <200 ul of urine in <5 hrs.

Metabolic signature of eyelid basal cell carcinoma

PURPOSE

Eyelid basal cell carcinoma (BCC) is the most common eyelid malignancy. Metabolic reprogramming is critical in tumorigenesis, but the metabolic feature of eyelid BCC remains elusive. In this study, we aim to reveal the metabolic profile in eyelid BCC using targeted metabolomics. Eyelid samples were collected from patients who had removal of BCC and from control patients who underwent blepharoplasty. Multivariate analysis of metabolomics data distinguished the two groups, indicating that eyelid BCC has significantly different metabolome than the healthy tissue. We found 16 increased and 11 decreased metabolites in the BCC tissues. These metabolites were highly enriched in the metabolism of nicotinamide adenine dinucleotide (NAD), glutathione metabolism, polyamine metabolism, and the metabolism of glycine, serine, threonine, arginine and proline. amino acid metabolism. Metabolites from NAD metabolism (Nicotinamide; Nicotinamide riboside; N1-Methylnicotinamide) had the highest sensitivity, specificity, and prediction accuracy in a prediction model for eyelid BCC. In conclusion, eyelid BCC has a signature change of cell metabolome. Metabolites in NAD metabolic pathways could potentially be biomarkers or therapeutic targets for eyelid BCC.

Prognostic Significance of Lymphocyte Infiltration and a Stromal Immunostaining of a Bladder Cancer Associated Diagnostic Panel in Urothelial Carcinoma

We set out to expand on our previous work in which we reported the epithelial expression pattern of a urine-based bladder cancer-associated diagnostic panel (A1AT, ANG, APOE, CA9, IL8, MMP9, MMP10, PAI1, SDC1, and VEGFA). Since many of the analytes in the bladder cancer-associated diagnostic signature were chemokines, cytokines, or secreted proteins, we set out to report the stromal staining pattern of the diagnostic signature as well as CD3⁺ (T-cell) cell and CD68⁺ (macrophage) cell staining in human bladder tumors as a snapshot of the tumor immune landscape. Immunohistochemical staining was performed on 213 tumor specimens and 74 benign controls. Images were digitally captured and quantitated using Aperio (Vista, CA). The expression patterns were correlated with tumor grade, tumor stage, and outcome measures. We noted a positive correlation of seven of the 10 proteins (excluding A1AT and IL8 which had a negative association and VEGFA had no association) in bladder cancer. The overexpression of MMP10 was associated with higher grade disease, while overexpression of MMP10, PAI1, SDC1 and ANG were associated with high stage bladder cancer and CA9 was associated with low stage bladder cancer. Increased tumor infiltration of CD68⁺ cells were associated with higher stage disease. Overall survival was significantly reduced in bladder cancer patients' whose tumors expressed eight or more of the 10 proteins that comprise the bladder cancer diagnostic panel. These findings confirm that the chemokines, cytokines, and secreted proteins in a urine-based diagnostic panel are atypically expressed, not only in the epithelial component of bladder tumors, but also in the stromal component of bladder tumors and portends a worse overall survival. Thus, when assessing immunohistochemical staining, it is important to report staining patterns within the stroma as well as the entire stroma itself.

Comparison of Commercial ELISA Kits, a Prototype Multiplex Electrochemoluminescent Assay, and a Multiplex Bead-Based Immunoassay for Detecting a Urine-Based Bladder-Cancer-Associated Diagnostic Signature

The ability to accurately measure multiple proteins simultaneously in a single assay has the potential to markedly improve the efficiency of clinical tests composed of multiple biomarkers. We investigated the diagnostic accuracy of the two multiplex protein array platforms for detecting a bladder-cancer-associated diagnostic signature in samples from a cohort of 80 subjects (40 with bladder cancer). Banked urine samples collected from Kyoto and Nara Universities were compared to histologically determined bladder cancer. The concentrations of the 10 proteins (A1AT; apolipoprotein E—APOE; angiogenin—ANG; carbonic anhydrase 9—CA9; interleukin 8—IL-8; matrix metalloproteinase 9—MMP-9; matrix metalloproteinase 10—MMP10; plasminogen activator inhibitor 1—PAI-1; syndecan—SDC1; and vascular endothelial growth factor—VEGF) were monitored using two prototype multiplex array platforms and an enzyme-linked immunosorbent assay (ELISA) according to the manufacturer’s technical specifications. The range for detecting each biomarker was improved in the multiplex assays, even though the lower limit of quantification (LLOQ) was typically lower in the commercial ELISA kits. The area under the receiver operating characteristics (AUROC) of the prototype multiplex assays was reported to be 0.97 for the multiplex bead-based immunoassay (MBA) and 0.86 for the multiplex electrochemoluminescent assay (MEA). The sensitivities and specificities for MBA were 0.93 and 0.95, respectively, and for MEA were 0.85 and 0.80, respectively. Accuracy, positive predictive values (PPV), and negative predictive values (NPV) for MBA were 0.94, 0.95, and 0.93, respectively, and for MEA were 0.83, 0.81, and 0.84, respectively. Based on these encouraging preliminary data, we believe that a multiplex protein array is a viable platform that can be utilized as an efficient and highly accurate tool to quantitate multiple proteins within biologic specimens.

Recent advances in mass spectrometry (MS)-based glycoproteomics in complex biological samples

Protein glycosylation plays a key role in various biological processes and disease-related pathological progression. Mass spectrometry (MS)-based glycoproteomics is a powerful approach that provides a system-wide profiling of the glycoproteome in a high-throughput manner. There have been numerous significant technological advances in this field, including improved glycopeptide enrichment, hybrid fragmentation techniques, emerging specialized software packages, and effective quantitation strategies, as well as more dedicated workflows. With increasingly sophisticated glycoproteomics tools on hand, researchers have extensively adapted this approach to explore different biological systems both in terms of in-depth glycoproteome profiling and comparative glycoproteome analysis. Quantitative glycoproteomics enables researchers to discover novel glycosylation-based biomarkers in various diseases with potential to offer better sensitivity and specificity for disease diagnosis. In this review, we present recent methodological developments in MS-based glycoproteomics and highlight its utility and applications in answering various questions in complex biological systems.

Recent advances in mass spectrometry (MS)-based glycoproteomics in complex biological samples

Protein glycosylation plays a key role in various biological processes and disease-related pathological progression. Mass spectrometry (MS)-based glycoproteomics is a powerful approach that provides a system-wide profiling of the glycoproteome in a high-throughput manner. There have been numerous significant technological advances in this field, including improved glycopeptide enrichment, hybrid fragmentation techniques, emerging specialized software packages, and effective quantitation strategies, as well as more dedicated workflows. With increasingly sophisticated glycoproteomics tools on hand, researchers have extensively adapted this approach to explore different biological systems both in terms of in-depth glycoproteome profiling and comparative glycoproteome analysis. Quantitative glycoproteomics enables researchers to discover novel glycosylation-based biomarkers in various diseases with potential to offer better sensitivity and specificity for disease diagnosis. In this review, we present recent methodological developments in MS-based glycoproteomics and highlight its utility and applications in answering various questions in complex biological systems.

Simple Tip-Based Sample Processing Method for Urinary Proteomic Analysis

Mass spectrometry-based urinary proteomics is one of the most attractive strategies to discover proteins for diagnosis, prognosis, monitoring, or prediction of therapeutic responses of urological diseases involving the kidney, prostate, and bladder; however, interfering compounds found in urine necessitate sample preparation strategies that are currently not suitable for urinary proteomics in the clinical setting. Herein, we describe the C4-tip method, comprising a simple, automated strategy utilizing a reverse-phase resin tip-based format and "on-tip" digestion to examine the urine proteome. We first determined the optimal conditions for protein isolation and protease digestion on the C4-tip using the standard protein bovine fetuin. Next, we applied the C4-tip method to urinary proteomics, identifying a total of 813 protein groups using LC-MS/MS, with identified proteins from the C4-tip method displaying a similar distribution of gene ontology (GO) cellular component assignments compared to identified proteins from an ultrafiltration preparation method. Finally, we assessed the reproducibility of the C4-tip method, revealing a high Spearman correlation R-value for shared proteins identified across all tips. Together, we have shown the C4-tip method to be a simple, robust method for high-throughput analysis of the urinary proteome by mass spectrometry in the clinical setting.

Development of biomarkers of genitourinary cancer using mass spectrometry-based clinical proteomics

Prostate, bladder and kidney cancer are the three most common types of genitourinary cancer in the world. Of these, prostate and bladder cancers are within the top 10 most common cancers in men. Notably, kidney cancer causes no obvious symptoms in the early stages. To satisfy clinical-management requirements, researchers have developed numerous biomarkers by applying proteomic approaches using clinical serum, urine and tissue specimens, as well as cell and animal models. Through application of biomarker pipeline protocols, including discovery, verification and validation phases, and mass-spectrometric based proteomic platforms coupled with multiplexed quantification assays, these studies have led to recent rapid progress in this area. With improvements in mass-spectrometric based proteomic techniques, numerous promising biomarker candidates and marker panels for various clinical purposes have been proposed. Verification of novel protein biomarker candidates is very resource demanding (e.g. on the clinical and laboratory sides). With the support of national consortia, it is now possible to investigate the future clinical use of such biomarker strategies and assess their cost-effectiveness in personalized medicine.

Preparation of a thickness-controlled Mg-MOFs-based magnetic graphene composite as a novel hydrophilic matrix for the effective identification of the glycopeptide in the human urine

The highly effective analysis of glycopeptides from complex biological samples is an attractive and critical topic all the time. In this study, a novel thickness-controlled hydrophilic Mg-metal organic frameworks (Mg-MOFs) coating-functionalized magnetic graphene composite (MagG@Mg-MOFs-1C) was prepared for the capture of the glycopeptides. The as-synthesized composite exhibits an ultralow limit of detection (0.1 fmol μL-1), a perfect size-exclusion effect (HRP digests/BSA protein/HRP protein, 1 : 500 : 500, w/w/w), and a high binding capacity (150 mg g-1), satisfying reusability and high recovery in the recognition of glycopeptides due to its outstanding characteristics including strong magnetic property, large surface area (617 m2 g-1), plenty of affinity sites, and excellent hydrophilicity. Furthermore, the MagG@Mg-MOFs-1C composite was successfully applied to selectively enriched glycopeptides in human urine. More excitingly, 406 N-glycosylation peptides corresponding to 185 glycoproteins were identified in the urine of the bladder cancer patients, in which these identified glycoproteins include the potential biomarkers (α-2-macroglobulin, complement C4-B, and α-1-antitrypsin) for the bladder cancer. This study suggests that the hydrophilic porous MOFs-functionalized composite has a great potential in the large-scale characterization of the low-abundance biomolecules in urine, opening a new avenue for the rapid and convenient diagnosis of the disease.

Proteomics biomarkers for solid tumors: Current status and future prospects

Cancer is a heterogeneous multifactorial disease, which continues to be one of the main causes of death worldwide. Despite the extensive efforts for establishing accurate diagnostic assays and efficient therapeutic schemes, disease prevalence is on the rise, in part, however, also due to improved early detection. For years, studies were focused on genomics and transcriptomics, aiming at the discovery of new tests with diagnostic or prognostic potential. However, cancer phenotypic characteristics seem most likely to be a direct reflection of changes in protein metabolism and function, which are also the targets of most drugs. Investigations at the protein level are therefore advantageous particularly in the case of in-depth characterization of tumor progression and invasiveness. Innovative high-throughput proteomic technologies are available to accurately evaluate cancer formation and progression and to investigate the functional role of key proteins in cancer. Employing these new highly sensitive proteomic technologies, cancer biomarkers may be detectable that contribute to diagnosis and guide curative treatment when still possible. In this review, the recent advances in proteomic biomarker research in cancer are outlined, with special emphasis placed on the identification of diagnostic and prognostic biomarkers for solid tumors. In view of the increasing number of screening programs and clinical trials investigating new treatment options, we discuss the molecular connections of the biomarkers as well as their potential as clinically useful tools for diagnosis, risk stratification and therapy monitoring of solid tumors.

Differential proteome analysis of diabetes mellitus type 2 and its pathophysiological complications

The prevalence of Diabetes Mellitus Type 2 (DM 2) is increasing every passing year due to some global changes in lifestyles of people. The exact underlying mechanisms of the progression of this disease are not yet known. However recent advances in the combined omics more particularly in proteomics and genomics have opened a gateway towards the understanding of predetermined genetic factors, progression, complications and treatment of this disease. Here we shall review the recent advances in proteomics that have led to an early and better diagnostic approaches in controlling DM 2 more importantly the comparison of structural and functional protein biomarkers that are modified in the diseased state. By applying these advanced and promising proteomic strategies with bioinformatics applications and bio-statistical tools the prevalence of DM 2 and its associated disorders i-e nephropathy and retinopathy are expected to be controlled.

Urinary Glycopeptide Analysis for the Investigation of Novel Biomarkers

PURPOSE

Urine is a rich source of potential biomarkers, including glycoproteins. Glycoproteomic analysis remains difficult due to the high heterogeneity of glycans. Nevertheless, recent advances in glycoproteomics software solutions facilitate glycopeptide identification and characterization. The aim is to investigate intact glycopeptides in the urinary peptide profiles of normal subjects using a novel PTM-centric software-Byonic.

EXPERIMENTAL DESIGN

The urinary peptide profiles of 238 normal subjects, previously analyzed using CE-MS and CE-MS/MS and/or LC-MS/MS, are subjected to glycopeptide analysis. Additionally, glycopeptide distribution is assessed in a set of 969 patients with five different cancer types: bladder, prostate and pancreatic cancer, cholangiocarcinoma, and renal cell carcinoma.

RESULTS

A total of 37 intact O-glycopeptides and 23 intact N-glycopeptides are identified in the urinary profiles of 238 normal subjects. Among the most commonly identified O-glycoproteins are Apolipoprotein C-III and insulin-like growth factor II, while titin among the N-glycoproteins. Further statistical analysis reveals that three O-glycopeptides and five N-glycopeptides differed significantly in their abundance among the different cancer types, comparing to normal subjects.

CONCLUSIONS AND CLINICAL RELEVANCE

Through the established glycoproteomics workflow, intact O- and N-glycopeptides in human urine are identified and characterized, providing novel insights for further exploration of the glycoproteome with respect to specific diseases.

Liquid Biopsy Biomarkers in Bladder Cancer: A Current Need for Patient Diagnosis and Monitoring

Bladder Cancer (BC) represents a clinical and social challenge due to its high incidence and recurrence rates, as well as the limited advances in effective disease management. Currently, a combination of cytology and cystoscopy is the routinely used methodology for diagnosis, prognosis and disease surveillance. However, both the poor sensitivity of cytology tests as well as the high invasiveness and big variation in tumour stage and grade interpretation using cystoscopy, emphasizes the urgent need for improvements in BC clinical guidance. Liquid biopsy represents a new non-invasive approach that has been extensively studied over the last decade and holds great promise. Even though its clinical use is still compromised, multiple studies have recently focused on the potential application of biomarkers in liquid biopsies for BC, including circulating tumour cells and DNA, RNAs, proteins and peptides, metabolites and extracellular vesicles. In this review, we summarize the present knowledge on the different types of biomarkers, their potential use in liquid biopsy and clinical applications in BC.

Urinary Protein Markers for the Detection and Prognostication of Urothelial Carcinoma

Bladder cancer diagnosis and surveillance is mainly based on cystoscopy and urine cytology. However, both methods have significant limitations; urine cytology has a low sensitivity for low-grade tumors, while cystoscopy is uncomfortable for the patients. Therefore, in the last decade urine analysis was the subject of intensive research resulting in the identification of many potential biomarkers for the detection, surveillance, or prognostic stratification of bladder cancer. Current trends move toward the development of multiparametric models to improve the diagnostic accuracy compared with single molecular markers. Recent technical advances for high-throughput and more sensitive measurements have led to the development of multiplex assays showing potential for more efficient tools toward future clinical application. In this review, we focus on the findings of urinary protein research in the context of detection and prognostication of bladder cancer. Furthermore, we provide an up-to-date overview on the recommendations for the quality evaluation of published studies as well as for the conduction of future urinary biomarker studies.

Meta-analysis of a 10-plex urine-based biomarker assay for the detection of bladder cancer

A 10-plex urine-based bladder cancer (BCa) diagnostic signature has the potential to non-invasively predict the presence of BCa in at-risk patients, as reported in various case-control studies. The present meta-analysis was performed to re-evaluate and demonstrate the robustness and consistency of the diagnostic utility of the 10-plex urine-based diagnostic assay. We re-analyzed primary data collected in five previously published case-control studies on the 10-plex diagnostic assay. Studies reported the sensitivity and specificity of ten urinary protein biomarkers for the detection of BCa, including interleukin 8, matrix metalloproteinases 9 and 10, angiogenin, apolipoprotein E, syndecan 1, alpha-1 antitrypsin, plasminogen activator inhibitor-1, carbonic anhydrase 9, and vascular endothelial growth factor A. Data were extracted and reviewed independently by two investigators. Log odds ratios (ORs) were calculated to determine how strongly the 10-plex biomarker panel and individual biomarkers are associated with the presence of BCa. Data pooled from 1,173 patients were analyzed. The log OR for each biomarker was improved by 1.5 or greater with smaller 95% CI in our meta-analysis of the overall cohort compared with each analysis of an individual cohort. The combination of the ten biomarkers showed a higher log OR (log OR: 3.46, 95% CI: 2.60–4.31) than did any single biomarker irrespective of histological grade or disease stage of tumors. We concluded that the 10-plex BCa-associated diagnostic signature demonstrated a higher potential to identify BCa when compared to any single biomarker. Our results justify further advancement of the 10-plex protein-based diagnostic signature toward clinical application.

Association of MMP-2, RB and PAI-1 with decreased recurrence-free survival and overall survival in bladder cancer patients

Background

We previously reported an accurate urine-based bladder cancer (BCa)-associated diagnostic signature that can be used to non-invasively detect BCa. In this study, we investigated whether a component of this signature could risk stratify patients with BCa.

Methods

Utilizing immunohistochemistry, we investigated angiogenin, MMP-2, p53, RB and PAI-1 expression from 939 patients with BCa. The expression levels were scored by assigning a proportion score and an intensity score to yield a total staining score for each protein. The expressions of each protein individually and as an aggregate were then correlated with progression-free survival (PFS), cancer-specific survival (CSS) and overall survival (OS).

Results

Differential expressions of these markers were noted in BCa. With multivariate analysis in non-muscle invasive bladder cancer (NMIBC) age, tumor grade portended a worse PFS, while age, tumor grade, nodal status, MMP2, RB and PAI-1 expression portended a worse OS. As for multivariate analysis in muscle invasive bladder cancer (MIBC), age MMP-2 and RB were associated with a worse PFS, while age, nodal status, MMP-2, RB and PAI-1 were associated with a worse OS. Using Kaplan-Meier survival analysis, we noted a significant reduction in OS as more of the five biomarkers were expressed in a tumor. Thus, overall, high expressions of MMP-2, RB and/or PAI-1 in bladder tumors were markers of poor prognosis.

Conclusion

Individually, MMP-2, RB and PAI-1, as well as in aggregate correlated with poor survival in patients with BCa. Thus, patients whose bladder tumors express these biomarkers may benefit from early radical treatment and/or neoadjuvant or adjuvant therapies.

Effects of arginine vasopressin on the urine proteome in rats

Biomarkers are the measurable changes associated with a physiological or pathophysiological process. The content of urine frequently changes because it is not controlled by homeostatic mechanisms, and these alterations can be a source of biomarkers. However, urine is affected by many factors. In this study, vasoconstrictor and antidiuretic arginine vasopressin (AVP) were infused into rats using an osmotic pump. The rats’ urinary proteome after one week of infusion was analyzed by label-free LC-MS/MS. A total of 408 proteins were identified; among these proteins, eight and 10 proteins had significantly altered expression in the low and high dose groups, respectively, compared with the control group using the one-way ANOVA analysis followed by post hoc analysis with the least significant difference (LSD) test or Dunnett’s T3 test. Three differential proteins were described in prior studies as related to AVP physiological processes, and nine differential proteins are known disease biomarkers. Sixteen of the 17 differential proteins have human orthologs. These results suggest that we should consider the effects of AVP on urinary proteins in future urinary disease biomarker researches. The study data provide clues regarding underlying mechanisms associated with AVP for future physiological researches on AVP. This study provide a sensitive changes associated with AVP. However, the limitation of this result is that the candidate biomarkers should be further verified and filtered. Large clinical samples must be examined to verify the differential proteins identified in this study before these proteins are used as biomarkers for pathological AVP increased diseases, such as syndrome of inappropriate antidiuretic hormone secretion (SIADH).

A novel strategy for global mapping of O-GlcNAc proteins and peptides using selective enzymatic deglycosylation, HILIC enrichment and mass spectrometry identification

O-GlcNAcylation is a kind of dynamic O-linked glycosylation of nucleocytoplasmic and mitochondrial proteins. It serves as a major nutrient sensor to regulate numerous biological processes including transcriptional regulation, cell metabolism, cellular signaling, and protein degradation. Dysregulation of cellular O-GlcNAcylated levels contributes to the etiologies of many diseases such as diabetes, neurodegenerative disease and cancer. However, deeper insight into the biological mechanism of O-GlcNAcylation is hampered by its extremely low stoichiometry and the lack of efficient enrichment approaches for large-scale identification by mass spectrometry. Herein, we developed a novel strategy for the global identification of O-GlcNAc proteins and peptides using selective enzymatic deglycosylation, HILIC enrichment and mass spectrometry analysis. Standard O-GlcNAc peptides can be efficiently enriched even in the presence of 500-fold more abundant non-O-GlcNAc peptides and identified by mass spectrometry with a low nanogram detection sensitivity. This strategy successfully achieved the first large-scale enrichment and characterization of O-GlcNAc proteins and peptides in human urine. A total of 474 O-GlcNAc peptides corresponding to 457 O-GlcNAc proteins were identified by mass spectrometry analysis, which is at least three times more than that obtained by commonly used enrichment methods. A large number of unreported O-GlcNAc proteins related to cell cycle, biological regulation, metabolic and developmental process were found in our data. The above results demonstrated that this novel strategy is highly efficient in the global enrichment and identification of O-GlcNAc peptides. These data provide new insights into the biological function of O-GlcNAcylation in human urine, which is correlated with the physiological states and pathological changes of human body and therefore indicate the potential of this strategy for biomarker discovery from human urine.

Ten Years of Proteomics in Bladder Cancer: Progress and Future Directions

Research efforts targeting the identification of bladder cancer biomarkers have been extensive during the past decade. Investigations have been performed at the genome, transcriptome, proteome, and metabolome levels and outputs have started appearing including the sketching of disease molecular subtypes. Proteins are directly linked to cell phenotype hence they accumulate special interest as both biomarkers and therapeutic targets. Multiple technical challenges exist, of the main, being the protein concentration vast dynamic range and presence of proteins in modified forms. The scope of this review is to summarize the contribution of proteomics research in this quest of bladder cancer biomarkers. To obtain an unbiased and comprehensive overview, the scientific literature was searched for manuscripts describing proteomic studies on urothelial cancer from the last ten years and those including independent verification studies in urine, tissue and blood are briefly presented. General observations include: a) in most cases, suboptimal experimental design including healthy controls in biomarker discovery and frequently biomarker verification, is followed; b) variability in protein findings between studies can be observed, to some extent reflecting complexity of experimental approaches and proteome itself; c) consistently reported biomarkers include mainly plasma proteins and d) compilation of protein markers into diagnostic panels appears the most promising way forward. Two main avenues of research can now be foreseen: targeting integration of the existing disparate data with proteomic findings being placed in the context of existing knowledge on bladder cancer subtypes and in parallel, accumulation of clinical samples to support proper validation studies of promising marker combinations.

Fabrication of Surface Protein-Imprinted Biofuel Cell for Sensitive Self-Powered Glycoprotein Detection

Glycoproteins are important biomarkers and therapeutic targets in clinical diagnostics. The conventional analytical methods for glycoprotein are usually faced with some challenges, such as the complex pretreatment of samples, poor availability, and limited stability of antibody, making them not suitable for point-of-care and on-site application. Herein, we demonstrate a novel miniaturized biofuel cells (BFCs)-based self-powered nanosensor for the specific and sensitive determination of glycoproteins in complex samples through the combination of boronate-affinity molecularly imprinted polymer (MIP) and the boronate affinity functionalized biliroxidase-carbon nanotube nanocomposites. The above MIP and the nanocomposites act as both signal probe and biocatalyst at the cathode. The as-obtained self-powered MIP-BFC-based biosensor can detect horseradish peroxidase (a type of glycoprotein) with a wide linear range of 1 ng/mL to 10 μg/mL and a very low detection limit of 1 ng/mL. Especially, it shows high tolerance for different interferences (e.g., sugars and other glycoproteins) and can even measure the α-fetoprotein level in serum samples. Moreover, it exhibits significant advantages over the conventional assays in terms of cost efficiency, stability, and speed, especially inexpensive instrument needed. Our novel approach for construction of the sensor paves a simple and economical way to fabricate portable devices for point-of-care and on-site application.

Three-Dimensionally Functionalized Reverse Phase Glycoprotein Array for Cancer Biomarker Discovery and Validation

Glycoproteins have vast structural diversity that plays an important role in many biological processes and have great potential as disease biomarkers. Here, we report a novel functionalized reverse phase protein array (RPPA), termed polymer-based reverse phase glycoprotein array (polyGPA), to capture and profile glycoproteomes specifically, and validate glycoproteins. Nitrocellulose membrane functionalized with globular hydroxyaminodendrimers was used to covalently capture preoxidized glycans on glycoproteins from complex protein samples such as biofluids. The captured glycoproteins were subsequently detected using the same validated antibodies as in RPPA. We demonstrated the outstanding specificity, sensitivity, and quantitative capabilities of polyGPA by capturing and detecting purified as well as endogenous α-1-acid glycoprotein (AGP) in human plasma. We further applied quantitative N-glycoproteomics and the strategy to validate a panel of glycoproteins identified as potential biomarkers for bladder cancer by analyzing urine glycoproteins from bladder cancer patients or matched healthy individuals.

A multiplex urinary immunoassay for bladder cancer detection: analysis of a Japanese cohort

BACKGROUND

Bladder cancer (BCa) is among the most commonly diagnosed malignancies worldwide, and due the high rate of post-operative disease recurrence, it is one of the most prevalent in many countries. The development of non-invasive molecular assays that can accurately detect and monitor BCa would be a major advance, benefiting both patients and healthcare systems. We have previously identified a urinary protein biomarker panel that is being developed for application in at-risk patient cohorts. Here, we investigated the potential utility of the multiplex assay in a Japanese cohort.

METHODS

The Japanese study cohort collected from urology clinics at two institutions was comprised of a total of 288 subjects. The protein biomarker panel (IL8, MMP9, MMP10, ANG, APOE, SDC1, A1AT, PAI1, CA9, VEGFA) was monitored in voided urine samples collected prior to cystoscopy using a custom multiplex ELISA assay. The diagnostic performance of the biomarker panel was assessed using receiver operator curves, predictive modeling and descriptive statistics.

RESULTS

Urinary biomarker concentrations were significantly elevated in cases versus controls, and in cases with high-grade and muscle-invasive tumors. The AUC for the 10-biomarker assay was 0.892 (95 % confidence interval 0.850-0.934), with an overall diagnostic sensitivity specificity of 0.85 and 0.81, respectively. A predictive model trained on the larger institutional cohort correctly identified 99 % of the cases from the second institution.

CONCLUSIONS

Urinary levels of a 10-biomarker panel enabled discrimination of patients with BCa. The multiplex urinary diagnostic assay has the potential to be developed for the non-invasive detection of BCa in at-risk Japanese patients.