Diagnostic potential for urinary proteomics

TRAIL and EGFR Pathways Targeting microRNAs are Predominantly Regulated in Human Diabetic Nephropathy

BACKGROUND

Unbiased microRNA profiling of renal tissue and urinary extracellular vesicles (uEVs) from diabetic nephropathy (DN) subjects may unravel novel targets with diagnostic and therapeutic potential. Here we used the miRNA profile of uEVs and renal biopsies from DN subjects available on the GEO database.

METHODS

The miR expression profiles of kidney tissue (GSE51674) and urinary exosomes (GSE48318) from DN and control subjects were obtained by GEO2R tools from Gene Expression Omnibus (GEO) databases. Differentially expressed miRNAs in DN samples, relative to controls, were identified using a bioinformatic pipeline. Targets of miRs commonly regulated in both sample types were predicted by miRWalk, followed by functional gene enrichment analysis. Gene targets were identified by MiRTarBase, TargetScan and MiRDB.

RESULTS

Eight miRs, including let-7c, miR-10a, miR-10b and miR-181c, were significantly regulated in kidney tissue and uEVs in DN subjects versus controls. The top 10 significant pathways targeted by these miRs included TRAIL, EGFR, Proteoglycan syndecan, VEGF and Integrin Pathway. Gene target analysis by miRwalk upon validation using ShinyGO 70 targets with significant miRNA-mRNA interaction.

CONCLUSION

In silico analysis showed that miRs targeting TRAIL and EGFR signaling are predominately regulated in uEVs and renal tissue of DN subjects. After wet-lab validation, the identified miRstarget pairs may be explored for their diagnostic and/or therapeutic potential in diabetic nephropathy.

Urinary Proteomics in Kidney Transplantation

Although kidney transplantation is the best treatment option for end stage kidney disease, it is still associated with long-term graft failure. One of the greater challenges for transplant professionals is the ability to identify grafts with a high risk of failure before initial decline of eGFR with irreversible graft changes. Transplantation medicine is facing an emerging need for novel disease end point-specific biomarkers, with practical application in preventive screening, early diagnostic, and improved prognostic and therapeutic utility. The aim of our review was to evaluate the clinical application of urinary proteomics in kidney transplant recipients at risk for any type of future graft failure.

Development of a sensitive and reliable ELISA kit of urinary haptoglobin to predict progress of diabetic kidney disease

AIMS

Urinary haptoglobin (UHp) is a potential biomarker for predicting progress of diabetic kidney disease (DKD) to remedy the defects of currently used urinary albumin. The clinical application of UHp is however limited, owing to the extremely low level in urine. This study aims to establish an enzyme-linked immunosorbent assay (ELISA) kit specifically for detecting UHp in urine samples of patients with diabetes and DKD.

MATERIALS AND METHODS

Supersensitive human haptoglobin antibodies were generated for ELISA kit development, and the sensitivity, specificity and reproducibility of the kit was evaluated. This kit was used to detect UHp in 246 healthy individuals and 83 patients with type 2 diabetes (T2D). The interference of blood haptoglobin genotypes on UHp measurement was analysed.

RESULTS

The UHp ELISA kit had a standard curve ranging from 5 to 200 ng/ml. The low detection limit was 0.11 ng/ml. The coefficients of variation of intra- and interassay were 5.5% and 8.3%, respectively. The kit showed high accuracy with 100.9% mean recovery rate, and linearity R²  = 0.999. The reference range of UHp was 0-42.3 ng/g creatinine (0-Q95) in the healthy individuals. UHp level was significantly higher in T2D patients with microalbuminuria and macroalbuminuria than that in T2D without microalbuminuria (p < 0.01). The UHp concentration measured by this kit was not affected by haptoglobin genotypes.

CONCLUSIONS

We have generated an ELISA kit to accurately detect UHp levels, which is potentially a reliable biomarker of DKD.

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.

Comparative Proteomics Analysis of Urine Reveals Down-Regulation of Acute Phase Response Signaling and LXR/RXR Activation Pathways in Prostate Cancer

Detecting prostate cancer (PCa) using non-invasive diagnostic markers still remains a challenge. The aim of this study was the identification of urine proteins that are sufficiently sensitive and specific to detect PCa in the early stages. Comparative proteomics profiling of urine from patients with PCa, benign prostate hyperplasia, bladder cancer, and renal cancer, coupled with bioinformatics analysis, were performed. Statistically significant difference in abundance showed 20 and 85 proteins in the 2-D DIGE/MS and label-free LC-MS/MS experiments, respectively. In silico analysis indicated activation, binding, and cell movement of subset of immune cells as the top affected cellular functions in PCa, together with the down-regulation of Acute Phase Response Signaling and Liver X Receptor/ Retinoid X Receptor (LXR/RXR) activation pathways. The most promising biomarkers were 35, altered in PCa when compared to more than one group. Half of these have confirmed localization in normal or PCa tissues. Twenty proteins (CD14, AHSG, ENO1, ANXA1, CLU, COL6A1, C3, FGA, FGG, HPX, PTGDS, S100A9, LMAN2, ITIH4, ACTA2, GRN, HBB, PEBP1, CTSB, SPP1) are oncogenes, tumor suppressors, and multifunctional proteins with highly confirmed involvement in PCa, while 9 (AZU1, IGHG1, RNASE2, PZP, REG1A, AMY1A, AMY2A, ACTG2, COL18A1) have been associated with different cancers, but not with PCa so far, and may represent novel findings. LC-MS/MS data are available via ProteomeXchange with identifier PXD008407.

EDTA-functionalized magnetic nanoparticles: A suitable platform for the analysis of low abundance urinary proteins

Urine is a highly attractive source of biological information and disease biomarkers, whose proteome characterization is ongoing. To that end, depletion/enrichment strategies for protein analysis can be of great convenience. We have thus developed a method based on the use of EDTA-functionalized magnetic nanoparticles (NPs@EDTA), to fractionate urine samples before liquid chromatography-mass spectrometry analysis and compared the identified proteins with those obtained from ultrafiltrated/unfractionated (UF) urine samples. NPs@EDTA allowed larger urine volumes to be processed, resulting in a greater number of protein identifications (~2-fold) at a lower cost when compared to UF samples. Proteins of greater abundance (such as albumin and uromodulin) were, at least partially, depleted with NPs@EDTA while those of lower abundance were enriched. Bioinformatics analysis showed that approximately 27% of NPs@EDTA-enriched proteins were annotated as displaying enzymatic activity, most of these being hydrolytic enzymes (56%), particularly proteases/peptidases (48%). Also, post-translational modifications were prominently predicted across NPs@EDTA-enriched proteins (90%), particularly glycosylation (52%), phosphorylation (47%) and acetylation (30%). NPs@EDTA allowed the identification of 109 proteins in urine for the first time, showing high potential as a platform for urine's fractionation prior to proteomic analysis.

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.

Comparison of Depletion Strategies for the Enrichment of Low-Abundance Proteins in Urine

Proteome analysis of complex biological samples for biomarker identification remains challenging, among others due to the extended range of protein concentrations. High-abundance proteins like albumin or IgG of plasma and urine, may interfere with the detection of potential disease biomarkers. Currently, several options are available for the depletion of abundant proteins in plasma. However, the applicability of these methods in urine has not been thoroughly investigated. In this study, we compared different, commercially available immunodepletion and ion-exchange based approaches on urine samples from both healthy subjects and CKD patients, for their reproducibility and efficiency in protein depletion. A starting urine volume of 500 μL was used to simulate conditions of a multi-institutional biomarker discovery study. All depletion approaches showed satisfactory reproducibility (n=5) in protein identification as well as protein abundance. Comparison of the depletion efficiency between the unfractionated and fractionated samples and the different depletion strategies, showed efficient depletion in all cases, with the exception of the ion-exchange kit. The depletion efficiency was found slightly higher in normal than in CKD samples and normal samples yielded more protein identifications than CKD samples when using both initial as well as corresponding depleted fractions. Along these lines, decrease in the amount of albumin and other targets as applicable, following depletion, was observed. Nevertheless, these depletion strategies did not yield a higher number of identifications in neither the urine from normal nor CKD patients. Collectively, when analyzing urine in the context of CKD biomarker identification, no added value of depletion strategies can be observed and analysis of unfractionated starting urine appears to be preferable.

Urinary proteomics and metabolomics in the diagnosis of pediatric disorders

Proteomics is the study of structures and functions of proteins, while metabolomics is the study of small-molecule metabolites in the cells, tissues, and organs of the organism. Proteomic technologies have wide applications in medical field. The current revolution in proteomics has led to the discovery of several new protein markers for various disorders. Urinary proteomics and metabolomics have also evolved in the recent years, for the diagnosis of both renal and nonrenal disorders. The urinary proteome varies in normal and abnormal conditions. Different techniques are employed for the analysis of pediatric urinary proteome, the commonest being MS. Before introduction into clinical use, there is the need for careful standardization. Available data suggest that there are differences in urinary proteome between adult and pediatric populations. It is noted that infant urine contains proteins involved in translation and transcription, cellular growth, and metabolic processes, which are not predominant in adult urine. Available data on urinary proteomic and metabolomic profile in common pediatric disorders are also reviewed here.

Proteomics analysis of urine reveals acute phase response proteins as candidate diagnostic biomarkers for prostate cancer

Despite the overall success of prostate specific antigen (PSA) in screening and detection of prostate cancer (PCa), its use has been limited due to the lack of specificity. The principal driving goal currently within PCa research is to identify non-invasive biomarker(s) for early detection of aggressive tumors with greater sensitivity and specificity than PSA. In this study, we focused on identification of non-invasive biomarkers in urine with higher specificity than PSA. We tested urine samples from PCa and benign prostatic hyperplasia (BPH) patients by 2-D DIGE coupled with MS and bioinformatics analysis. Statistically significant (p < 0.05), 1.8 fold variation or more in abundance, showed 41 spots, corresponding to 23 proteins. The Ingenuity Pathway Analysis showed significant association with the Acute Phase Response Signaling pathway. Nine proteins with differential abundances were included in this pathway: AMBP, APOA1, FGA, FGG, HP, ITIH4, SERPINA1, TF and TTR. The expression pattern of 4 acute phase response proteins differed from the defined expression in the canonical pathway. The urine levels of TF, AMPB and HP were measured by immunoturbidimetry in an independent validation set. The concentration of AMPB in urine was significantly higher in PCa while levels of TF and HP were opposite (p < 0.05). The AUC for the individual proteins ranged from 0.723 to 0.754. The combination of HP and AMBP yielded the highest accuracy (AUC = 0.848), greater than PSA. The proposed biomarker set is quickly quantifiable and economical with potential to improve the sensitivity and specificity of PCa detection.

Quantitative mass spectrometry of urinary biomarkers

The effectiveness of treatment of renal diseases is limited because the lack of diagnostic, prognostic and therapeutic markers. Despite the more than a decade of intensive investigation of urinary biomarkers, no new clinical biomarkers were approved. This is in part because the early expectations toward proteomics in biomarkers discovery were significantly higher than the capability of technology at the time. However, during the last decade, proteomic technology has made dramatic progress in both the hardware and software methods. In this review we are discussing modern quantitative methods of mass-spectrometry and providing several examples of their applications for discovery and validation of renal disease biomarkers. We are optimistic about future prospects for the development of novel of specific clinical urinary biomarkers.

Mapping and Identification of the Urine Proteome of Prostate Cancer Patients by 2D PAGE/MS

Proteome analysis of the urine has shown that urine contains disease-specific information for a variety of urogenital system disorders, including prostate cancer (PCa). The aim of this study was to determine the protein components of urine from PCa patients. Urine from 8 patients with clinically and histologically confirmed PCa was analyzed by conventional 2D PAGE. The MS identification of the most prominent 125 spots from the urine map revealed 45 distinct proteins. According to Gene Ontology, the identified proteins are involved in a variety of biological processes, majority of them are secreted (71%), and half of them are enzymes or transporters. Comparison with the normal urine proteome revealed 11 proteins distinctive for PCa. Using Ingenuity Pathways Analysis, we have found 3 proteins (E3 ubiquitin-protein ligase rififylin, tumor protein D52, and thymidine phosphorylase) associated with cellular growth and proliferation (p = 8.35 × 10⁻⁴ − 3.41 × 10⁻²). The top network of functional associations between 11 proteins was Cell Death and Survival, Cell-To-Cell Signaling and Interaction, and System Development and Function (p = 10⁻³⁰). In summary, we have created an initial proteomic map of PCa patient's urine. The results from this study provide some leads to understand the molecular bases of prostate cancer.

Emerging biomarkers and metabolomics for assessing toxic nephropathy and acute kidney injury (AKI) in neonatology

Identification of novel drug-induced toxic nephropathy and acute kidney injury (AKI) biomarkers has been designated as a top priority by the American Society of Nephrology. Increasing knowledge in the science of biology and medicine is leading to the discovery of still more new biomarkers and of their roles in molecular pathways triggered by physiological and pathological conditions. Concomitantly, the development of the so-called "omics" allows the progressive clinical utilization of a multitude of information, from those related to the human genome (genomics) and proteome (proteomics), including the emerging epigenomics, to those related to metabolites (metabolomics). In preterm newborns, one of the most important factors causing the pathogenesis and the progression of AKI is the interaction between the individual genetic code, the environment, the gestational age, and the disease. By analyzing a small urine sample, metabolomics allows to identify instantly any change in phenotype, including changes due to genetic modifications. The role of liquid chromatography-mass spectrometry (LC-MS), proton nuclear magnetic resonance (1H NMR), and other emerging technologies is strategic, contributing basically to the sudden development of new biochemical and molecular tests. Urine neutrophil gelatinase-associated lipocalin (uNGAL) and kidney injury molecule-1 (KIM-1) are closely correlated with the severity of kidney injury, representing noninvasive sensitive surrogate biomarkers for diagnosing, monitoring, and quantifying kidney damage. To become routine tests, uNGAL and KIM-1 should be carefully tested in multicenter clinical trials and should be measured in biological fluids by robust, standardized analytical methods.

Cancer biomarker discovery for cholangiocarcinoma: the high-throughput approaches

Cholangiocarcinoma (CCA) is difficult to diagnose at an early stage and most tumors are detected at late stage where surgery or other therapy is ineffective. Many advanced techniques are applied to diagnose CCA; however, most are expensive and have varying degrees of accuracy. A less invasive and simpler procedure such as serum markers would be of substantial clinical benefit for diagnosis, monitoring, and predicting outcome for CCA patients. Recent advances in "Omics" technologies offer remarkable opportunities for establishment of biomarker-related to diseases. In this review, the potential biomarkers obtained from proteomics and glycomic studies are evaluated. Several protein markers were discovered from patient specimen, using two dimensional-differential gel electrophoresis couple with liquid chromatography tandem mass spectrometry (2D-DIGE/LC-MS-MS), matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF-MS), surface enhanced laser desorption/ionization (SELDI)-TOF-MS and capillary electrophoresis (CE)-MS, etc. Newly reported CCA-associated glyco-biomarkers were identified using lectin-assisted, monoclonal antibody-assisted or specific-target strategies. The combination between carbohydrate binding-lectin and core protein-binding mAb significantly increased the values for detection of the glyco-biomarkers for CCA. Searching for specific and sensitive molecular markers to be used for population screening is worth being evaluated. This could lead to earlier diagnosis and improve outcome. Further investigation of those biomarker functions is also of value in order to better understand the tumor biology and use them as targets for future therapeutic agents.

An automated RP-SCX solid-phase extraction procedure for urinary peptidomics biomarker discovery studies

Urine represents the most easily obtainable body fluid and consequently one of the most common samples in clinical chemistry. The majority of pathological changes in human organs may well be reflected in urine. In this way, urine analysis can aid in disease diagnosis, treatment monitoring, and prognosis. Currently, the most commonly used method for identification of new urine biomarkers involves centrifugation of the urine sample to collect either the soluble urine proteins or the urinary exosomes followed by 1 or 2 protein purification and separation steps before visualization and finally identification of potential biomarkers, usually by mass spectrometry. Here we present a generally applicable, rapid, and robust method for screening large number of urine samples, resulting in a broad spectrum of native peptides, as a tool to be used for biomarker discovery. The method combines online sample pretreatment with a well-established mass spectrometric technique. Native peptides are extracted from urine samples on a miniaturized reverse-phase-strong cation exchange cartridge system. As the proper identification of native peptides often requires combination of data acquired on different mass analyzers, we have aimed at a procedure providing us with sufficient material to identify and characterize the differentially expressed markers.

Albuminuria, proteinuria, and urinary albumin to protein ratio in chronic kidney disease

BACKGROUND

Both albuminuria and proteinuria are important disease markers of chronic kidney disease (CKD). Their relationship and the ratio between urinary albumin and protein in patients with CKD have not been investigated. Whether clinical features can affect these measurements is not clear.

METHODS

We conducted a cross-sectional study in 602 CKD patients. Demographic data, including age, gender, and co-morbidity such as diabetes, hypertension, hyperuricemia, and hyperlipidemia, were reviewed and recorded. Their urinary albumin, total protein, and creatinine were determined and urinary albumin to creatinine ratio (UACR), total protein to creatinine ratio (UPCR), and albumin to total protein ratio (UAPR) were calculated. Their estimated glomerular filtration rate (eGFR) was calculated according to serum creatinine. The correlation between UACR and UPCR was thus analyzed. We also investigated factors associated with these urinary measurements.

RESULTS

UACR and UPCR increased progressively as renal function deteriorated, while UAPR increased to a plateau in CKD stage 4. There was direct relationship between UACR and UPCR. UAPR rose exponentially with the increase of both UACR and UPCR when UACR <500 mg/g or UPCR <1,000 mg/g. Multivariate regression analysis revealed diabetes and hyperuricemia were associated with increased UACR and UPCR, while both urinary parameters were inversely related to male gender and eGFR. Diabetes and hyperuricemia were associated with increased UAPR and UAPR was negatively correlated with age and eGFR.

CONCLUSION

There was a significant association between UACR and UPCR in patients with CKD. Characteristics of patients, renal function, and co-morbidities all affected UACR, UPCR, and UAPR.

Proteomic analysis of formalin-fixed paraffin-embedded pancreatic tissue using liquid chromatography tandem mass spectrometry

OBJECTIVES

FFPE tissue is a standard method of specimen preservation for hospital pathology departments. Formalin-fixed paraffin-embedded tissue banks are a resource of histologically characterized specimens for retrospective biomarker investigation. We aim to establish liquid chromatography coupled with tandem mass spectrometry analysis of FFPE pancreatic tissue as a suitable strategy for the study of the pancreas proteome.

METHODS

We investigated the proteomic profile of FFPE pancreatic tissue specimens, using liquid chromatography coupled with tandem mass spectrometry, from 9 archived specimens that were histologically classified as normal (n = 3), chronic pancreatitis (n = 3), and pancreatic cancer (n = 3).

RESULTS

We identified 525 nonredundant proteins from 9 specimens. Implementing our filtering criteria, 78, 15, and 21 proteins were identified exclusively in normal, chronic pancreatitis, and pancreatic cancer specimens, respectively. Several proteins were identified exclusively in specimens with no pancreatic disease: spink 1, retinol dehydrogenase, and common pancreatic enzymes. Similarly, proteins were identified exclusively in chronic pancreatitis specimens: collagen α1 (XIV), filamin A, collagen α3 (VI), and SNC73. Proteins identified exclusively in pancreatic cancer included annexin 4A and fibronectin.

CONCLUSIONS

We report that differentially expressed proteins can be identified among FFPE tissue specimens originating from individuals with different pancreatic histologic findings. The mass spectrometry-based method used herein has the potential to enhance biomarker discovery and chronic pancreatitis research.

Searching for new biomarkers of renal diseases through proteomics

BACKGROUND

Technological advances have resulted in a renaissance of proteomic studies directed at finding markers of disease progression, diagnosis, or responsiveness to therapy. Renal diseases are ideally suited for such research, given that urine is an easily accessible biofluid and its protein content is derived mainly from the kidney. Current renal prognostic markers have limited value, and renal biopsy remains the sole method for establishing a diagnosis. Mass spectrometry instruments, which can detect thousands of proteins at nanomolar (or even femtomolar) concentrations, may be expected to allow the discovery of improved markers of progression, diagnosis, or treatment responsiveness.

CONTENT

In this review we describe the strengths and limitations of proteomic methods and the drawbacks of existing biomarkers, and provide an overview of opportunities in the field. We also highlight several proteomic studies of biomarkers of renal diseases selected from the plethora of studies performed.

SUMMARY

It is clear that the field of proteomics has not yet fulfilled its promise. However, ongoing efforts to standardize sample collection and preparation, improve study designs, perform multicenter validations, and create joint industry-regulatory bodies offer promise for the recognition of novel molecules that could change clinical nephrology forever.

[Urinary peptides and calcium oxalate nephrolithiasis, a combined approach: MALDI-TOF mass spectrometry and MicroBCA Protein Assay]

BACKGROUND

Urinary lithiasis is one of the most common benign urological diseases. There is growing evidence that a delicate equilibrium regulated by the function of proteins, soluble peptides, membrane proteins and intracellular mechanisms actually exists. We have studied the urinary protein composition of patients affected by calcium oxalate nephrolithiasis in order to discover a biomarker or any predisposing factors.

METHODS

The urinary protein composition of 17 patients (11 males, 6 females; mean age 45yrs ± 14SD), affected by calcium oxalate nephrolithiasis, was assessed in comparison with 17 healthy subjects. A qualitative assay was performed using MALDI-TOF mass spectrometry in a spectrum between 1 and 5kDa (medium size peptides), and a numerical (quantitative) assay using specific filters and MicroBCA Protein Assay.

RESULTS

No differences were detected in the mass spectrums between patients and control subjects: all peaks overlapped perfectly. The results of the numerical assay suggest that concentrations of protein species <5kDa in control samples were actually higher than those which were found in patients. The differences are statistically significant.

CONCLUSIONS

The study detected neither a biomarker nor any predisposing factors in "stone former" patients. The assessment of the results obtained, in terms of quantitative differences, indicate the need for further research.

Mass spectrometry-based proteomics of endoscopically collected pancreatic fluid in chronic pancreatitis research

MS-based investigation of pancreatic fluid enables the high-throughput identification of proteins present in the pancreatic secretome. Pancreatic fluid is a complex admixture of digestive, inflammatory, and other proteins secreted by the pancreas into the duodenum, and thus is amenable to MS-based proteomic analysis. Recent advances in endoscopic techniques, in particular the endoscopic pancreatic function test (ePFT), have improved the collection methodology of pancreatic fluid for proteomic analysis. Here, we provide an overview of MS-based proteomic techniques as applied to the study of pancreatic fluid. We address sample collection, protein extraction, MS sample preparation and analysis, and bioinformatic approaches, and summarize current MS-based investigations of pancreatic fluid. We then examine the limitations and the future potential of such technologies in the investigation of pancreatic disease. We conclude that pancreatic fluid represents a rich reservoir of potential biomarkers and that the study of the molecular mechanisms of chronic pancreatitis may benefit substantially from MS-based proteomics.

Urinary peptide profiling identifies a panel of putative biomarkers for diagnosing and staging endometriosis

OBJECTIVE

To identify a potential diagnostic endometriosis marker using matrix-enhanced laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS)-based urinary proteomics.

DESIGN

Prospective randomized pilot study.

SETTING

University hospital, tertiary referral center for endometriosis.

PATIENT(S)

53 women undergoing laparoscopic surgery for pain and/or infertility comprising 30 women without endometriosis and 23 with endometriosis.

INTERVENTION(S)

Laparoscopy and urine specimens.

MAIN OUTCOME MEASURE(S)

Urinary peptide profiles.

RESULT(S)

We observed distinct patterns of peptide profiles in the urine samples of women presenting with typical clinical symptoms of endometriosis. Six statistically significant putative peptide markers were identified (four during the periovulatory phase and two during the luteal phase) by comparing controls with moderate/severe endometriosis patients. The periovulatory peptide mass of 1,767.1 Da and the luteal peptide mass of 1,824.3 Da both showed a sensitivity of 75% and a specificity of 85% and 71%, respectively. Also detected were seven peptide markers (two during the periovulatory phase and five during the luteal phase) by comparing the urinary peptide profiles of patients with minimal/mild to moderate/severe endometriosis. The periovulatory peptide mass of 3,280.9 Da and the luteal peptide mass of 1,933.8 Da showed a sensitivity of 82% and 75% and a specificity of 88% and 75%, respectively.

CONCLUSION(S)

Urinary proteomic analysis may provide a novel method of diagnosing and staging endometriosis.

Optimized sample preparation of endoscopic collected pancreatic fluid for SDS-PAGE analysis

The standardization of methods for human body fluid protein isolation is a critical initial step for proteomic analyses aimed to discover clinically relevant biomarkers. Several caveats have hindered pancreatic fluid proteomics, including the heterogeneity of samples and protein degradation. We aim to optimize sample handling of pancreatic fluid that has been collected using a safe and effective endoscopic collection method (endoscopic pancreatic function test). Using SDS-PAGE protein profiling, we investigate (i) precipitation techniques to maximize protein extraction, (ii) auto-digestion of pancreatic fluid following prolonged exposure to a range of temperatures, (iii) effects of multiple freeze-thaw cycles on protein stability, and (iv) the utility of protease inhibitors. Our experiments revealed that TCA precipitation resulted in the most efficient extraction of protein from pancreatic fluid of the eight methods we investigated. In addition, our data reveal that although auto-digestion of proteins is prevalent at 23 and 37 degrees C, incubation on ice significantly slows such degradation. Similarly, when the sample is maintained on ice, proteolysis is minimal during multiple freeze-thaw cycles. We have also determined the addition of protease inhibitors to be assay-dependent. Our optimized sample preparation strategy can be applied to future proteomic analyses of pancreatic fluid.

Comparison of different depletion strategies for improving resolution of the human urine proteome

BACKGROUND

Urine, being an ultrafiltrate of plasma, is a rich source for biomarker discovery. Since potential new disease markers are often present in low concentrations, a prefractionation/enrichment step could be useful in the discovery process. To enhance the detection of low-abundance proteins, three immuno-affinity depletion approaches were evaluated.

METHODS

To remove the most abundant proteins from a human urine sample, GenWay Spin IgY-12 kit, HPLC Agilent Hu-PL7 and a home-made column vs. human serum albumin [immuno-affinity column (IAC)] were compared. Quantification of total proteins, 2-D gel electrophoresis (2-DE), Progenesis gel images analysis and mass spectrometric proteins identification were applied to evaluate these strategies.

RESULTS

Reproducibility of depletion columns, by estimating protein content of unbound fractions, were: 343+/-20.0 microg, 5.8%; 186.3+/-13.3 microg, 7.2%; 292+/-20.6 microg, 8.8% [mean+/- standard deviation (SD), CV%], for GenWay, Agilent and IAC methods, respectively. To isolate urinary protein after depletion, ethanol precipitation provided the highest recovery (80%). Applying 2-DE and Progenesis analysis, the number of spots visualized on the gels was 468+/-21, 331+/-7, 368+/-22 and 304+/-7 (mean+/-SD) for GenWay, Agilent, IAC, and the undepleted urine pool sample, respectively, with a significant difference p<0.001 compared to the GenWay procedure.

CONCLUSIONS

The sequential procedure of urine samples using multi-protein immuno-affinity depletion represents a valid tool for simplifying 2-DE analysis of the urine proteome. Particularly, the GenWay kit followed by ethanol precipitation was found to be the most efficient method for exploring the urine proteome.

The Quest for Renal Disease Proteomic Signatures: Where Should We Look?

Renal diseases are prevalent and important. However, despite significant strides in medicine, clinical nephrology still relies on nonspecific and inadequate markers such as serum creatinine and total urine protein for monitoring and diagnosis of renal disease. In case of glomerular renal diseases, biopsy is often necessary to establish the diagnosis. With new developments in proteomics technology, numerous studies have emerged, searching for better markers of kidney disease diagnosis and/or prognosis. Blood, urine, and renal biopsy tissue have been explored as potential sources of biomarkers. Some interesting individual or multiparametric biomarkers have been found; however, none have yet been validated or entered clinical practice. This review focuses on some studies of biomarkers of glomerular renal diseases, as well as addresses the question of which sample type(s) might be most promising in preliminary discovery phases of candidate proteins.

Urinary proteomics--a tool for biomarker discovery

The strong need for the discovery of novel disease markers together with the development of high-throughput techniques that provide highly sensitive analysis of protein content in tissues and bodily fluids, using proteomics, has opened the completely new chapter in biomarker discovery. The detection of biomarkers based on urinary proteome analysis is rapidly advancing and may provide new tools to improve non-invasive diagnostics, prognostics, and therapy enhancement. As a tool for biomarker discovery, urinary proteomics is especially fruitful in the area of early diagnostics and differentiation of renal damage, and it possesses enormous potential for improving and expanding non-invasive cancer diagnostics. An abundance of urinary proteins could provide a wide variety of biomarkers for the diagnosis and follow-up of many systemic diseases as well. This article reviews the utility of urinary proteomics for biomarker discovery from the perspective of clinical application. Despite huge potential and prompt development of urinary proteomics, many challenges are still in front of us. Research effort and financial investment have to be oriented on providing strategies for exceeding current methodological and technical obstacles in a way to ensure the successful validation and implementation of newly discovered urinary biomarkers. The result is expected to be the development of new non-invasive tests and procedures able to guarantee higher efficiency of patient care and provide needed personalized medical approach.

Proteomic analysis of pancreatic secretory trypsin inhibitor/tumor-associated trypsin inhibitor from urine of patients with pancreatitis or prostate cancer

The development of proteomic methods, especially mass spectrometry, has brought new possibilities to tumor marker research. Pancreatic secretory trypsin inhibitor (PSTI), a common known biomarker for various malignancies, occurs on genetic variants that we are able to detect at the protein level with proteomic techniques using immunoaffinity capture prior to liquid chromatography-mass spectrometry (LC-MS). We also show that PSTI can be detected in urine from cancer patients using a two-step peptide enrichment technique and LC-MS. These results show that tumor-associated peptides can be detected in urine by proteomic techniques.

The non-invasive biopsy--will urinary proteomics make the renal tissue biopsy redundant?

Proteomics is a rapidly advancing technique which gives functional insight into gene expression in living organisms. Urine is an ideal medium for study as it is readily available, easily obtained and less complex than other bodily fluids. Considerable progress has been made over the last 5 years in the study of urinary proteomics as a diagnostic tool for renal disease. Advantages over the traditional renal biopsy include accessibility, safety, the possibility of serial sampling and the potential for non-invasive prognostic and diagnostic monitoring of disease and an individual's response to treatment. Urinary proteomics is now moving from a discovery phase in small studies to a validation phase in much larger numbers of patients with renal disease. Whilst there are still some limitations in methodology, which are assessed in this review, the possibility of urinary proteomics replacing the invasive tissue biopsy for diagnosis of renal disease is becoming an increasingly realistic option.

Proteinuria without albuminuria: urinary protein excretion by a subset of patients with burn injuries

BACKGROUND

There is disagreement regarding the utility of urinary albumin excretion as a marker for capillary injury in patients with severe burn injuries. We examined protein components in urine specimens from patients with burn injury.

METHODS

Detailed analysis was performed for a set of 5 urine specimens selected based on a high ratio of albumin-sized molecules by size-exclusion HPLC (Accumin) versus albumin by immunoassay methods. Specimens were analyzed for total protein, alpha(1)-microglobulin, alpha(1)-acid glycoprotein, cystatin C, and retinol-binding protein. Urine components were analyzed by chromatographic and electrophoretic methods. Major components were identified by mass spectrometry of tryptic peptides.

RESULTS

A subset of urine specimens had increased total protein with slight increases in albumin by immunoassay or by polyacrylamide gel electrophoresis. Albumin values by size-exclusion HPLC were more than 10-fold higher. Immunoassays for alpha(1)-microglobulin and alpha(1)-acid glycoprotein yielded concentrations 5-10 fold higher than for albumin. Other major components identified included zinc-alpha(2)-glycoprotein and leucine-rich-alpha(2)-glycoprotein.

CONCLUSIONS

A subset of patients with burn injury had increased total urinary protein resulting primarily from increased excretion of proteins such as alpha(1)-microglobulin and alpha(1)-acid glycoprotein with little increase in albumin excretion. The unusual composition of urinary proteins in these patients may relate to decreased filtered load of albumin and increased filtered load of acute phase reactants or to alterations in renal tubular protein processing. Thus, measurement of urinary albumin may have decreased sensitivity for detecting kidney injury in burn patients.

Adapting mass spectrometry-based platforms for clinical proteomics applications: The capillary electrophoresis coupled mass spectrometry paradigm

Single biomarker detection is common in clinical laboratories due to the currently available method spectrum. For various diseases, however, no specific single biomarker could be identified. A strategy to overcome this diagnostic void is to shift from single analyte detection to multiplexed biomarker profiling. Mass spectrometric methods were employed for biomarker discovery in body fluids. The enormous complexity of biofluidic proteome compartments implies upstream fractionation. For this reason, mass spectrometry (MS) was coupled to two-dimensional gel electrophoresis, liquid chromatography, surface-enhanced laser desorption/ionization, or capillary electrophoresis (CE). Differences in performance and operating characteristics make them differentially suited for routine laboratory applications. Progress in the field of clinical proteomics relies not only on the use of an adequate technological platform, but also on a fast and efficient proteomic workflow including standardized sample preparation, proteomic data processing, statistical validation of biomarker selection, and sample classification. Based on CE-MS analysis, we describe how proteomic technology can be implemented in a clinical laboratory environment. In the last part of this review, we give an overview of CE-MS-based clinical studies and present information on identity and biological significance of the identified peptide biomarkers providing evidence of disease-induced changes in proteolytic processing and posttranslational modification.

Novel automated biomarker discovery work flow for urinary peptidomics

BACKGROUND

Urine is potentially a rich source of peptide biomarkers, but reproducible, high-throughput peptidomic analysis is often hampered by the inherent variability in factors such as pH and salt concentration. Our goal was to develop a generally applicable, rapid, and robust method for screening large numbers of urine samples, resulting in a broad spectrum of native peptides, as a tool to be used for biomarker discovery.

METHODS

Peptide samples were trapped, desalted, pH-normalized, and fractionated on a miniaturized automatic reverse-phase strong cation exchange (RP-SCX) cartridge system. We analyzed eluted peptides using MALDI-TOF, Fourier transform ion cyclotron resonance, and liquid chromatography-iontrap mass spectrometry. We determined qualitative and quantitative reproducibility of the system and robustness of the method using BSA digests and urine samples, and we used a selected set of urine samples from Schistosoma haematobium-infected individuals to evaluate clinical applicability.

RESULTS

The automated RP-SCX sample cleanup and fractionation system exhibits a high qualitative and quantitative reproducibility, with both BSA standards and urine samples. Because of the relatively high cartridge binding capacity (1-2 mL urine), eluted peptides can be measured with high sensitivity using multiple mass spectrometric techniques. As proof of principle, hemoglobin-derived peptides were identified in urine samples from S. haematobium-infected individuals, even when the microhematuria test was negative.

CONCLUSIONS

We present a practical, step-by-step method for screening and identification of urinary peptides. Alongside the analytical method evaluation on standard samples, we demonstrate its feasibility with actual clinical material.

Biomarker discovery in psychiatric disorders

Schizophrenia is a multifaceted neuropsychiatric disorder. Its onset is the result of complex interactions between genetic, developmental and environmental factors. It almost certainly presents a heterogeneous group of aetiologies which may not be reflected in the symptomatic/clinical presentation of patients. Therefore, a better molecular understanding of the disease onset and progression is urgently needed. The high complexity of the disorder and the heterogeneity of patient populations account for the slow progress of biomarker discovery approaches. Multi-omics profiling approaches can be employed to investigate large numbers of patient and control samples in a single experiment. These large scale experiments are required to identify disease intrinsic molecular signatures as well as patient subgroups with potentially distinct biochemical pathways underpinning their symptoms. In this overview, we describe some of the most important challenges for biomarker discovery for psychiatric disorders and emphasize how these problems contribute to the requirement of large sample numbers. Results of MS-based protein profiling studies in schizophrenia research are reviewed and technical advantages and difficulties of the methodologies described. We outline recent technological advances that generated impressive results in other areas of research and point to their applicability for biomarker discovery in psychiatric disorders.

Proteomic strategies in bladder cancer: From tissue to fluid and back

We have applied protein expression profiling technologies in combination with immunohistochemistry, using fresh tissue and urine samples, to assess bladder cancer heterogeneity and prognosis as well as to generate protein markers for tumor progression and early diagnosis of the disease. Here, we review some selected lines of investigation and approaches undertaken by our laboratory, drawing on more than 15 years of experience in bladder cancer proteomics, to highlight a number of issues that may be useful for researchers entering the field. In particular, we address the identification of markers for bladder cancer progression and exemplify the potential of gel-based proteomic profiling of urine samples for the early detection of urothelial carcinomas. In addition, we provide a brief description of a novel and highly promising source of biomarkers, the tumor interstitial fluid (TIF) that perfuses the tumor microenvironment.

Proteomics for biomarker discovery in acute kidney injury

Acute kidney injury (AKI), previously referred to as acute renal failure, represents a common and devastating problem in clinical medicine. Despite significant improvements in therapeutics, the mortality and morbidity associated with AKI remain high. A major reason for this is the lack of early markers for AKI, and hence an unacceptable delay in initiating therapy. Fortunately, the application of innovative technologies such as functional genomics and proteomics to human and animal models of AKI has uncovered several novel biomarkers and therapeutic targets. The most promising of these are chronicled in this review. These include the identification of biomarker panels in plasma (neutrophil gelatinase-associated lipocalin and cystatin C) and urine (neutrophil gelatinase-associated lipocalin, kidney injury molecule-1, interleukin-18, cystatin C, alpha1-microglobulin, Fetuin-A, Gro-alpha, and meprin). It is likely that the AKI panels will be useful for timing the initial insult, and assessing the duration and severity of AKI. It is also probable that the AKI panels will distinguish between the various etiologies of AKI and predict clinical outcomes. It will be important in future studies to validate the sensitivity and specificity of these biomarker panels in clinical samples from large cohorts and from multiple clinical situations. Such studies will be facilitated markedly by the development of commercial tools for the reproducible measurement of biomarkers across different laboratories.

Reactivity of Urinary Albumin (Microalbumin) Assays with Fragmented or Modified Albumin

Background: Controversy exists regarding occurrence and measurement of structural variants of albumin in urine. In this study, we examined cross-reactivity of in vitro modified albumins in assays for urine albumin (microalbumin).

Methods: We analyzed albumin modified by reagents, trypsin, or physical treatments or differing in primary sequence (animal albumins) with an immunoturbidimetric assay (Beckman LX20) using goat antiserum and a competitive immunoassay (Siemens Immulite) using a monoclonal antibody. We assessed occurrence of albumin fragments in urine by use of Western blotting of 24 specimens.

Results: Chemical modification, modest sequence substitution (gorilla albumin), or cleavage of albumin by cyanogen bromide (CNBr) had little effect on reactivity in the LX20 assay. Albumin extensively cleaved with trypsin retained partial reactivity. The Immulite assay generally was affected more severely by albumin modifications and sequence changes. Western blots of fresh urine specimens or specimens stored at −80 °C showed little albumin fragmentation, but some specimens stored for 3 years at −20 °C had extensively fragmented albumin that was detected by the LX20 but not the Immulite assay.

Conclusions: Nearly equivalent reactivity of intact albumin and CNBr fragments in the immunoturbidimetric assay indicates reactivity of antibodies with multiple epitopes throughout albumin. Therefore, it is difficult to abolish reactivity of albumin in this type of urine albumin assay. Differential sensitivity of 2 assays to albumin modification identifies a potential source of assay nonequivalence in measuring urinary albumin, particularly for specimens stored at −20 °C.

Practical Points in Urinary Proteomics

During the proteomic era, one of the most rapidly growing areas in biomedical research is biomarker discovery, particularly using proteomic technologies. Urinary proteomics has become one of the most attractive subdisciplines in clinical proteomics, as the urine is an ideal source for the discovery of noninvasive biomarkers for human diseases. However, there are several barriers to the success of the field and urinary proteome analysis is not a simple task because the urine has low protein concentration, high levels of salts or other interfering compounds, and more importantly, high degree of variations (both intra-individual and inter-individual variabilities). This article provides step-by-step practical points to perform urinary proteome analysis, covering detailed information for study design, sample collection, sample storage, sample preparation, proteomic analysis, and data interpretation. The discussion herein should stimulate further discussion and refinement to develop guidelines and standardizations for urinary proteome study.

Body fluid proteomics: Prospects for biomarker discovery

Many diseases are caused by perturbations of cellular signaling pathways and related pathway networks as a result of genetic aberrations. These perturbations are manifested by altered cellular protein profiles in the fluids bathing tissue/organs (i.e., the tissue interstitial fluid, TIF). A major challenge of clinical chemistry is to quantitatively map these perturbed protein profiles - the so-called "signatures of disease" - using modern proteomic technologies. This information can be utilized to design protein biomarkers for the early detection of disease, monitoring disease progression and efficacy of drug action. Here, we discuss the use of body fluids in the context of prospective biomarker discovery, and the marked 1000-1500-fold dilution of body fluid proteins, during their passage from TIF to the circulatory system. Further, we discuss proteomics strategies aimed at depleting major serum proteins, especially albumin, in order to focus on low-abundance protein/peptides in plasma. A major limitation of depletion strategies is the removal of low-molecular weight protein/peptides which specifically bind major plasma proteins. We present a prototype model, using albumin, for understanding the multifaceted nature of biomarker research, highlighting the involvement of albumin in Alzheimer's disease. This model underscores the need for a system-level understanding for biomarker research and personalized medicine.