Urine protein profiling with surface-enhanced laser-desorption/ionization time-of-flight mass spectrometry

Optimizing sample handling for urinary proteomics

Interrogation of the urinary proteome for clinically useful biomarkers of disease will require normalization of methods for protein extraction and sample handling. Variations in collection methods and other procedures may introduce significant discrepancies in qualitative and quantitative measurements. Here we demonstrate that the method of protein extraction, length of handling at room temperature, and repetitive freeze-thaw cycles do not seem to alter the urinary proteome at either the protein or peptide level in a manner that degrades information obtainable by mass spectrometry.

Post-collection, pre-measurement variables affecting VEGF levels in urine biospecimens

Angiogenesis, the development and recruitment of new blood vessels, plays an important role in tumour growth and metastasis.Vascular endothelial growth factor (VEGF) is an important stimulator of angiogenesis.Circulating and urinary VEGF levels have been suggested as clinically useful predictors of tumour behaviour, and investigations into these associations are ongoing.Despite recent interest in measuring VEGF levels in patients, little is known about the factors that influence VEGF levels in biospecimens. To begin to address this question, urine samples were collected from patients with solid tumours undergoing radiotherapy and healthy volunteers.Four factors were examined for their effects on VEGF concentrations as measured by chemiluminescent immunoassay: time from sample collection to freezing, number of specimen freeze–thaw cycles, specimen storage tube type and the inclusion or exclusion of urinary sediment. The results of this study indicate that time to freeze up to 4 hrs, number of freeze–thaw cycles between one and five, and different types of polypropylene tubes did not have statistically significant effects on measured urinary VEGF levels. Urinary sediment had higher VEGF levels than supernatant in five of six samples from healthy patients.It is not clear whether there is an active agent in the sediment causing this increase or if the sediment particles themselves are affecting the accuracy of the assay.Therefore, we recommend centrifuging urine, isolating the supernatant, and freezing the sample in polypropylene microcentrifuge tubes or cryogenic vials within 4 hrs of collection.In addition, we recommend the use of samples within five freeze–thaw cycles.

Prediction of acute cellular renal allograft rejection by urinary metabolomics using MALDI-FTMS

The present study investigated small molecule analysis of urinary samples as a noninvasive method to detect acute cellular renal allograft rejection. Matrix-assisted laser desorption/ionization Fourier transform mass spectrometry (MALDI-FTMS) was used to analyze 15 urinary samples from transplant patients with different grades of biopsy showing improved clinical acute cellular rejection (ACR) and 24 urinary samples from 8 transplant patients without evidence of rejection. Seven small molecules demonstrated highly successful diagnostic performance (m/z): 278.1 (t = 3.398, p = 0.004), 293.0 (t = 2.169, p = 0.048), 294.1 (t = 2.154, p = 0.05), 382.2 (t = 2.961, p = 0.010), 383.3 (t = 2.270, p = 0.040), 402.2 (t = 2.994, p = 0.010), 424.0 (t = 2.644, p = 0.019). Kidney transplant patients with ACR could be distinguished from those without ACR using four individual small molecules with a specificity of 100%. In conclusion, the combination of MALDI-FTMS technology with a clear definition of patient groups can detect urine small molecule associated with ACR.

Analysis of the urine proteome in patients with pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) accounts for over 213 000 deaths worldwide each year, largely due to late diagnosis. One of the risk factors for the development of PDAC is chronic pancreatitis (CP); the intense desmoplastic reaction makes differentiation between the two conditions extremely difficult. In order to identify biomarkers for noninvasive diagnosis, we performed 2-D DIGE analysis of urine samples from healthy individuals and patients with PDAC and CP. Despite considerable intersample heterogeneity, a total of 127 statistically valid (p<0.05), differentially expressed protein spots were detected, 101 of which were identified using MALDI-TOF MS. A number of these, including annexin A2, gelsolin and CD59 have already been associated with PDAC, however, their validation using immunoblotting proved challenging. This is probably due to extensive PTMs and processing thus indicating the need for raising specific antibodies for urinary proteins. Despite this, our study clearly demonstrates that urine is a valid source of noninvasive biomarkers in patients with pancreatic diseases.

CE-MS analysis of the human urinary proteome for biomarker discovery and disease diagnostics

Owing to its availability, ease of collection, and correlation with pathophysiology of diseases, urine is an attractive source for clinical proteomics. However, many proteomic studies have had only limited clinical impact, due to factors such as modest numbers of subjects, absence of disease controls, small numbers of defined biomarkers, and diversity of analytical platforms. Therefore, it is difficult to merge biomarkers from different studies into a broadly applicable human urinary proteome database. Ideally, the methodology for defining the biomarkers should combine a reasonable analysis time with high resolution, thereby enabling the profiling of adequate samples and recognition of sufficient features to yield robust diagnostic panels. Capillary electrophoresis coupled to mass spectrometry (CE-MS), which was used to analyze urine samples from healthy subjects and patients with various diseases, is a suitable approach for this task. The database of these datasets compiled from the urinary peptides enabled the diagnosis, classification, and monitoring of a wide range of diseases. CE-MS exhibits excellent performance for biomarker discovery and allows subsequent biomarker sequencing independent of the separation platform. This approach may elucidate the pathogenesis of many diseases, and better define especially renal and urological disorders at the molecular level.

Differential expression of serum proteomic spectra in rat model of pancreatic intraepithelial neoplasia and dimethylbenzanthracene-induced pancreatic carcinoma

AIM: To investigate relationship between differential expression of serum proteomic spectra in rat model of pancreatic intraepithelial neoplasia (PanIN) and dimethylbenzanthracene-induced pancreatic carcinoma (PC) using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) technology.

METHODS: Forty male SD rats were implanted with DMBA into the pancreas to induce rat model of PanIN and PC. Histopathology was evaluated according to PanIN classification system. And normal control group of twenty-six male SD rats was established. The serum protein spectra were detected using IMAC-Cu²⁺ proteinchip and SELDI-TOF MS. The data were analyzed using Biomarker Wizard 3.0 Software of Ciphergen Biosystem Co.

RESULTS: DMBA was implanted into pancreas of rats in PC group (n = 11) and PanIN group (n = 18). Compared with the normal control group, there were significant differences (P < 0.001) of 30 protein peaks in PanIN and PC of which 19 protein peaks were up-regulated and 11 down-regulated. The expression of 9 protein peaks, with a ratio of mass to charge (M/Z) of 5835.2, 4087.3, 4786.5, 4800.5, 3932.2, 5765.9, 5924.8, 5001.9, 3913.7 gradually increased from normal to PanIN and PC group, and 4 protein peaks with a M/Z ratio of 1096.9, 1478.9, 8572.9, 1007.1 gradually decreased.

CONCLUSION: Serum proteomic spectra were differentially expressed in rat model of PanIN and PC. Identification and function of these differentially expressed proteins necessitate further investigation.

Biomarkers of lupus nephritis determined by serial urine proteomics

Lupus nephritis is a frequent and serious complication of systemic lupus erythematosus (SLE), the treatment of which often requires the use of immunosuppressives that can have severe side effects. Here we determined the low-molecular weight proteome of serial lupus urine samples to uncover novel and predictive biomarkers of SLE renal flare. Urine from 25 flare cycles of 19 patients with WHO Class III, IV, and V SLE nephritis were obtained at baseline, pre-flare, flare and post-flare. Each sample was first fractionated to remove proteins larger than 30 kDa, then applied onto weak cation exchanger protein chips for analysis by SELDI-TOF mass spectrometry. We found 176 protein ions of which 27 were differentially expressed between specific flare intervals. On-chip peptide sequencing by integrated tandem mass spectrometry positively identified the 20 and 25 amino-acid isoforms of hepcidin, as well as fragments of alpha1-antitrypsin and albumin among the selected differentially expressed protein ions. Hepcidin 20 increased 4 months before renal flare and returned to baseline at renal flare, whereas hepcidin 25 decreased at renal flare and returned to baseline 4 months after the flare. These studies provide a beginning proteomic analysis aimed at predicting impending renal relapse, relapse severity, and the potential for recovery after SLE nephritis flare.

Using proteomics to identify preprocedural risk factors for contrast induced nephropathy

Contrast induced nephropathy (CIN) is the third leading cause of hospital acquired acute kidney injury (AKI). We conducted a cross-sectional study in children undergoing elective cardiac catheterization to determine if there is a distinct preprocedural urinary proteomic profile in subjects who subsequently develop CIN. Of 90 patients enrolled, AKI due to CIN (defined as a 50% or greater increase in serum creatinine) occurred in 10 participants by the 24 h postcontrast time point. Seven patients who did not develop AKI served as age and gender matched controls. SELDI-TOF-MS was performed using Protein Chips with different chromatographic surfaces. A 4480 Da biomarker displayed significantly greater peat intensities on three chromatographic surfaces (p = 0.02-0.001) in control patients at time = 0 with an area under the curve (AUC) of 0.89-0.99. This biomarker was identified as the 41 amino acid (a.a.) variant of human beta-defensin-1. Another biomarker of 4631 Da was found to have a significantly greater peak intensity (p = 0.03) in AKI patients at time = 0, with an AUC of 0.84. Thus, the presence of a 4631 Da peptide, as well as the absence of the 41 a.a. variant of human beta-defensin-1 in the pre-procedural urine, may prove to be useful biomarkers for the early prediction of CIN.

Sputum proteomics in inflammatory and suppurative respiratory diseases

RATIONALE

Markers of inflammatory activity are important for assessment and management of many respiratory diseases. Markers that are currently unrecognized may be more valuable than those presently believed to be useful.

OBJECTIVES

To identify potential biomarkers of suppurative and inflammatory lung disease in induced sputum samples.

METHODS

Induced sputum was collected from 20 healthy control subjects, 24 patients with asthma, 24 with chronic obstructive pulmonary disease, 28 with cystic fibrosis (CF), and 19 with bronchiectasis. Twelve patients with CF had sputum sampled before and after antibiotic therapy for an infective exacerbation. The fluid phase of induced sputum was analyzed by surface-enhanced laser desorption/ionization time-of-flight (SELDI-TOF) mass spectroscopy on three protein array surfaces. Some protein markers were selected for identification, and relevant ELISA assays sought. For 12 patients with CF, both SELDI-TOF and ELISA monitored changes in inflammatory responses during infective exacerbations.

MEASUREMENTS AND MAIN RESULTS

SELDI-TOF identified potential biomarkers that differentiated each of the disease groups from healthy control subjects: at a significance of P < 0.01, there were 105 for asthma, 113 for chronic obstructive pulmonary disease, 381 for CF, and 377 for bronchiectasis. Peaks selected for protein identification yielded calgranulin A, calgranulin B, calgranulin C, Clara cell secretory protein, lysosyme c, proline rich salivary peptide, cystatin s, and hemoglobin alpha. On treatment of an infective CF exacerbation, SELDI-TOF determined falls in levels of calgranulin A and calgranulin B that were mirrored by ELISA-measured falls in calprotectin (heterodimer of calgranulins A and B).

CONCLUSIONS

Proteomic screening of sputum yields potential biomarkers of inflammation. The early development of a clinically relevant assay from such data is demonstrated.

Proteomic profiling of urine for the detection of colon cancer

Background

Colorectal cancer is the second most common cause of cancer related death in the developed world. To date, no blood or stool biomarkers with both high sensitivity and specificity for potentially curable early stage disease have been validated for clinical use. SELDI and MALDI profiling are being used increasingly to search for biomarkers in both blood and urine. Both techniques provide information predominantly on the low molecular weight proteome (<15 kDa). There have been several reports that colorectal cancer is associated with changes in the serum proteome that are detectable by SELDI and we hypothesised that proteomic changes would also be detectable in urine.

Results

We collected urine from 67 patients with colorectal cancer and 72 non-cancer control subjects, diluted to a constant protein concentration and generated MALDI and SELDI spectra. The intensities of 19 peaks differed significantly between cancer and non-cancer patients by both t-tests and after adjusting for confounders using multiple linear regressions. Logistic regression classifiers based on peak intensities identified colorectal cancer with up to 78% sensitivity at 87% specificity. We identified and independently quantified 3 of the discriminatory peaks using synthetic stable isotope peptides (an 1885 Da fragment of fibrinogen and hepcidin-20) or ELISA (β2-microglobulin).

Conclusion

Changes in the urine proteome may aid in the early detection of colorectal cancer.

Decreased urinary beta-defensin-1 expression as a biomarker of response to arsenic

Ingestion of arsenic (As) through contaminated drinking water results in increased risks of skin, lung, kidney, and bladder cancers. Due to its association with kidney and bladder cancers, we hypothesized that analysis of the urinary proteome could provide insight into the mechanisms of As toxicity. Urine from participants in a cross-sectional As biomarker study conducted in Nevada, classified as having either high (>or= 100 microg total urinary As/l) or low exposure (< 100 microg total urinary As/l) was analyzed by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry. Two polypeptides, 2.21 and 4.37 kDa, were significantly decreased in the high exposure group (p < 0.05) and were limited to men when stratified by sex. To replicate these findings, urine from participants in a second As study in Chile was analyzed and results confirmed the decrease of the 4.37 kDa polypeptide as well as a 4.76 kDa polypeptide among highly exposed men. These peaks were identified and confirmed as human beta-defensin-1 (HBD-1) peptides. In a separate in vitro experiment, gene expression analysis of As-treated cell lines demonstrated reduced HBD1 mRNA confirming that the observed decrease in HBD-1 resulted from As exposure. HBD-1 is an antimicrobial peptide constitutively expressed in multiple tissues including epithelial cells of the respiratory and urogenital systems. Recent studies support its role as a tumor suppressor gene for urological cancers suggesting that decreased HBD-1 levels may play a role in the development of cancers associated with As exposure. Further studies are warranted to investigate the role of HBD-1 in As-related toxicity.

Urine sample preparation and protein profiling by two-dimensional electrophoresis and matrix-assisted laser desorption ionization time of flight mass spectroscopy

Urine represents the most easily attainable and consequently one of the most common samples in clinical analysis and diagnostics. However, urine is also considered one of the most difficult proteomic samples to work with due to its highly variable contents, as well as the presence of various proteins in low abundance or modified forms. In this chapter, we describe simple protocols and troubleshooting tips for urinary protein preparation and profiling by two-dimensional electrophoresis or directly via matrix-assisted laser desorption ionization time of flight mass spectroscopy. Direct dilution, protein precipitation, ultrafiltration, and solid phase extraction in combination to the above profiling technologies serve the means for reliable proteomics analysis of one of the most significant yet very complex biological samples.

Surface-enhanced laser desorption/ionization mass spectrometry for protein and Peptide profiling of body fluids

Recently, Ciphergen Biosystems (Fremont, CA, USA) has developed a technique called surface-enhanced laser desorption/ionization (SELDI). This technology is based on ProteinChips(R) with chemically or biochemically modified surfaces for the selective retention and enrichment of protein subsets from a complex protein mixture. The proteins or peptides of interest can then be identified by using mass spectrometry (SELDI-MS). This highly sensitive and high-throughput technique can detect minute differences in proteins and peptide profiles between biological samples. The versatility of this technology enables a wide variety of applications in basic research, clinical, proteomic, and drug discovery such as identification of novel biomarkers associated with certain diseases or treatments. Many disease biomarkers or biomarker patterns have been identified using SELDI-MS in various laboratories. In this chapter, we provide a general guide to the profiling of proteins or peptides as well as biomarker discovery using the most common body fluids such as serum/plasma, nipple aspiration fluid, and urine.

Discovery and validation of urinary biomarkers for prostate cancer

Only 30% of patients with elevated serum prostate specific antigen (PSA) levels who undergo prostate biopsy are diagnosed with prostate cancer (PCa). Novel methods are needed to reduce the number of unnecessary biopsies. We report on the identification and validation of a panel of 12 novel biomarkers for prostate cancer (PCaP), using CE coupled MS. The biomarkers could be defined by comparing first void urine of 51 men with PCa and 35 with negative prostate biopsy. In contrast, midstream urine samples did not allow the identification of discriminatory molecules, suggesting that prostatic fluids may be the source of the defined biomarkers. Consequently, first void urine samples were tested for sufficient amounts of prostatic fluid, using a prostatic fluid indicative panel ("informative" polypeptide panel; IPP). A combination of IPP and PCaP to predict positive prostate biopsy was evaluated in a blinded prospective study. Two hundred thirteen of 264 samples matched the IPP criterion. PCa was detected with 89% sensitivity, 51% specificity. Including age and percent free PSA to the proteomic signatures resulted in 91% sensitivity, 69% specificity.

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.

Applications of SELDI-MS technology in oncology

Considerable interest, speculation and controversy have been generated utilising surface-enhanced laser desorption/ionization in conjunction with mass spectrometry (SELDI-MS) for the diagnosis, prognosis and therapeutic monitoring of cancer and offers an attractive approach to cancer biomarker discovery from tissues and biological fluids. This technology utilises a combination of mass spectrometry and chromatography to facilitate protein profiling of complex biological mixtures. Compared to some other more traditional proteomic platforms, such as 2D polyacrylamide gel electrophoresis, it has a high-throughput capability and can resolve low-mass proteins. However, a considerable number of challenging issues related to the design of studies, including reproducibility, sensitivity, specificity, variation in sample collection, processing and storage, have been reported as problematic with this technology; albeit some of these concerns could perhaps also be lauded against other proteomic approaches that have attempted to address complex protein mixtures, such as plasma. Applications, successes and limitations of SELDI-MS in both clinical and basic science arenas will be reviewed in this article.

A novel approach using MALDI-TOF/TOF mass spectrometry and prestructured sample supports (AnchorChip Technology) for proteomic profiling and protein identification

Mass spectrometry (MS)-based proteomic profiling and protein identification has become a powerful tool for the discovery of new disease biomarkers. Among the MS platforms, matrix-assisted laser desorption/ionization time-of-flight/time-of-flight (MALDI-TOF/TOF) MS offers high sample throughput and the flexibility to couple with different off-line sample fractionation techniques. Here, we present a strategy using MALDI-TOF/TOF MS to analyze fractionated human serum samples for proteomic profiling and then identify serum peptides from these proteomic profiles. We achieve the profiling analyses by using different functionalized magnetic beads to enrich specific subsets of serum proteins/peptides based on their absorption to these beads. This step is followed by elution, transfer onto prestructured sample supports (AnchorChip targets), and analysis in a MALDI-TOF/TOF mass spectrometer. Selected serum peptides are then analyzed in the tandem MS (TOF/TOF) mode to generate fragment ions for determination of their amino acid sequences. We have demonstrated that using this approach, proteomic profiling and protein identification can be done in a single MS instrument.

[Capillary electrophoresis coupled to mass spectrometry for proteome analysis. An innovative diagnostic method for prostate and bladder cancer]

We developed a proteomics-based technology for the non-invasive detection of urothelial and prostate carcinoma. Using capillary electrophoresis coupled to mass spectrometry, disease-specific changes in the urinary proteome were detected and subsequently relevant polypeptides were employed as disease-specific biomarkers. Here we report the results of various studies including approximately 1,000 patients with different diseases and healthy volunteers. The results of these studies revealed that prostate and urothelial carcinoma can be detected by using disease-specific polypeptide patterns. Preliminary results also indicate that the tumour stage of an urothelial carcinoma can be estimated by this approach. In conclusion, this new and non-invasive application might help to improve the diagnostic methods already available.

Identification of a urinary proteomic signature for lupus nephritis in children

The quest for reliable biomarkers of systemic lupus erythematosus (SLE) nephritis is an area of intense contemporary research. In this study, surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) technology was used for urinary proteomic profiling of patients with SLE nephritis. Clinical, laboratory, and kidney biopsy data from pediatric patients with SLE (n = 32) were analyzed. Children with juvenile idiopathic arthritis (n = 11) served as controls. SELDI-TOF-MS was performed using ProteinChips with different chromatographic surfaces. The resulting spectra were analyzed with Bio-Rad Biomarker Wizard software. A consistent urinary proteomic signature for SLE nephritis was found, comprising eight biomarker proteins with peaks at m/z of 2.7, 22, 23, 44, 56, 79, 100, and 133 kDa. The peak intensities of these biomarkers were significantly greater in patients with SLE nephritis compared with controls and SLE patients without nephritis. These biomarkers were strongly correlated with renal disease activity and moderately with renal damage. For the diagnosis of active nephritis, the area under the receiver operating characteristic curve was > or =0.90 for 22, 23, 44, 79, and 100 kDa biomarkers. Thus, SELDI-TOF-MS has identified a urine proteomic signature strongly associated with SLE renal involvement and active SLE nephritis.

Body fluid proteomics for biomarker discovery: lessons from the past hold the key to success in the future

Sparked by the article from Lescuyer and colleagues in a recent issue, we aim here to further encourage interest in and discussion of clinically relevant biomarker research. We express our view on proteomics for biomarker discovery by addressing multiple relevant issues, including the inherent differences between biological fluids (and how these differences affect current analytical approaches) and experimental design to maximize the efficiency of moving from the bench to the bedside. Herein, we also include suggestions for definition of the term "biomarker", based on the use of a set of universal characterization/validation requirements, and illustrate several recent examples of successful transitions of benchtop proteomic studies work to clinical practice.

SELDI protein profiling of dunning R-3327 derived cell lines: identification of molecular markers of prostate cancer progression

BACKGROUND

We recently demonstrated the protein expression profiling of Dunning rat tumor cell lines of varying metastatic potential (G (0%), AT-1 ( approximately 20%), and MLL (100%)) using SELDI-TOF-MS. As a parallel effort, we have been pursuing the identification of the protein(s) comprising the individual discriminatory "peaks" and evaluating their utility as potential biomarkers for prostate cancer progression.

METHODS

To identify the observed SELDI-TOF-MS m/z (mass/charge) values with discriminatory expression between different sublines, we employed a combination of chemical pre-fractionation, liquid chromatography, gel electrophoresis and tandem mass spectroscopy. Identified proteins were then verified by immuno-assay and Western analysis.

RESULTS

A 17.5 K m/z SELDI-TOF-MS peak was found to retain discriminatory value in each of two separate study-sets with an increased expression in the metastatic MLL line. Sequence identification and subsequent immunoassays verified that Histone H2B is the observed 17.5 K m/z SELDI peak. SELDI-based immuno-assay and Western Blotting revealed that Histone H2B is specifically over-expressed in metastatic MLL lines.

CONCLUSIONS

SELDI-TOF MS analysis of the Dunning prostate cancer cell lines confirmed the consistent overexpression of a 17.5 K m/z peak in metastatic MLL subline. The 17.5 kDa protein from MLL has been isolated and identified as Histone H2B.

Application of surface-enhanced laser desorption/ionization time-of-flight mass spectrometry for early detection of pancreatic cancer

Pancreatic cancer is a devastating and lethal disease. Early detection continues to be a serious, unsolved problem. However, proteomics is emerging as a powerful new tool for the diagnosis of pancreatic cancer. Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) is a new technique that allows for rapid high-throughput screening of protein expression in clinical samples. The progress and challenges in applying SELDI-TOF MS to protein biomarker discovery in pancreatic cancer are reviewed in this paper.

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.

Characterization of Diabetic Nephropathy by Urinary Proteomic Analysis: Identification of a Processed Ubiquitin Form as a Differentially Excreted Protein in Diabetic Nephropathy Patients

Background: Identification of markers for prediction of the clinical course of diabetic nephropathy remains a major challenge in disease management. We established a proteomics approach for identification of diabetic nephropathy-related biomarkers in urine.

Methods: We used SELDI-TOF mass spectrometry and SAX2 protein arrays to compare protein profiles from urine of 4 defined patient groups. Samples from patients with type 2 diabetes (DM; n = 45) without nephropathy and without microalbuminuria (DM-WNP), patients with DM with macro- or microalbuminuria (DM-NP; n = 38), patients with proteinuria due to nondiabetic renal disease (n = 34), and healthy controls (n = 45) were analyzed. Anionic exchange, reversed-phase fractionation, gel electrophoresis, and mass spectrometry were used to isolate and identify proteins with high discriminatory power.

Results: A protein with m/z 6188 (P &lt;0.0000004) was strongly released in the urine of healthy controls, patients with proteinuria due to nondiabetic disease, and DM-WNP in contrast to DM-NP patients. An m/z 14 766 protein (P &lt;0.00008) was selectively excreted in the urine of DM-NP patients, whereas the protein with m/z 11 774 (P &lt;0.000004) was significantly excreted by patients with proteinuria and DM-NP. The m/z 11 774 and m/z 14 766 mass peaks were identified as β2-microglobulin and UbA52, a ubiquitin ribosomal fusion protein, respectively. The protein with m/z 6188 was identified as a processed form of ubiquitin.

Conclusion: The release of high amounts of UbA52 in urine of DM-NP patients could serve as a diagnostic marker, whereas the lack of the short form of ubiquitin raises interesting questions about the pathophysiology.

Mass spectrometry based proteomics in urine biomarker discovery

All organisms contain 1,000s of proteins and peptides in their body fluids, which undergo disease-specific changes. Advances in the understanding of the functional relevance of these polypeptides under different (patho)physiological conditions and the identification of indicative changes with disease would greatly enhance diagnosis and therapy. The low-molecular-weight proteome, also termed peptidome, provides a rich source of information. Due to its lower molecular weight, the peptidome can be assessed without the need for sample manipulation like tryptic digests. This advantage facilitates comparative analysis but it also raises technical challenges differing from those in proteomics. The first part of this manuscript, is focused on the low-molecular-weight urinary proteome and reviews methodological aspects of sample collection, preparation, analysis, and data evaluation. The second part summarizes the recent progress in the definition and identification of clinically relevant polypeptide markers.

Non-invasive markers of ureteropelvic junction obstruction

Non-invasive prognosis of the clinical progression of disease is of high interest, especially in newborn and children. Neonatal ureteropelvic (UPJ) junction obstruction needs close and invasive surveillance to determine the necessity of pyeloplasty. A number of groups have initiated research with the aim to find non-invasive biomarkers for UPJ obstruction. Two different strategies have been followed. One strategy, based on the knowledge obtained in animal models of UPJ obstruction, has identified a number of individual urinary markers of severe UPJ obstruction. Combining these markers might allow prediction of which patients will require surgery and in which patients UPJ obstruction will spontaneously resolve. The other strategy is based on urinary proteomics. In this strategy the entire urinary proteome is probed for a set of biomarkers that correlates with the degree of UPJ obstruction. In subsequent steps, these sets of urinary biomarkers are used for prediction of the clinical evolution of UPJ obstruction patients. This proteomic-based strategy allowed prediction, several months in advance, of the clinical evolution of neonates with UPJ-obstruction. Both strategies will be complementary and will hopefully replace in the near future the invasive follow-up of newborns with UPJ obstruction.

Biomarkers for prostate cancer

Novel biomarkers for prostate cancer (PCa) are currently being assessed for utility in PCa diagnosis. This article aims to provide concise information on the current findings that impact prostate cancer research. Results of enzyme-linked immunosorbent assays (ELISA) for single biomarkers, quantitative polymerase chain reaction (PCR)-based assays for DNA/RNA markers will be reviewed in addition to high-throughput proteomic profiling of PCa specimens. The advantages/disadvantages of tissue, blood, urine or seminal plasma as sources for potential biomarkers are discussed emphasizing the consequences for PCa diagnosis. In summary, the majority of promising marker candidates available today needs further validation. Some of the identified markers have the potential to yield novel prognostic tools for PCa, provide novel insights into its pathophysiology, and contribute to the establishment of novel treatment strategies.

Recent progress in urinary proteomics

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 kidney and nonkidney diseases. This field has been growing rapidly as indicated by >80 original research articles on urinary proteome analyses appearing since 2001, of which 28 (approximately 1/3) had been published within the year 2006. The most common technologies used in recent urinary proteome studies remain gel-based methods (1-DE, 2-DE and 2-D DIGE), whereas LC-MS/MS, SELDI-TOF MS, and CE-MS are other commonly used techniques. In addition, mass spectrometric immunoassay (MSIA) and array technology have also been applied. This review provides an extensive but concise summary of recent applications of urinary proteomics. Proteomic analyses of dialysate and ultrafiltrate fluids derived from renal replacement therapy (or artificial kidney) are also discussed.

High-resolution proteome/peptidome analysis of peptides and low-molecular-weight proteins in urine

All organisms contain thousands of proteins and peptides in their body fluids. A deeper insight into the functional relevance of these polypeptides under different physiological and pathophysiological conditions and the discovery of specific peptide biomarkers would greatly enhance diagnosis and therapy of specific diseases. The low-molecular-weight proteome, also termed peptidome, provides a rich source of information. Due to its unique features, the technical challenges differ somewhat from those in "common" proteomics. In this manuscript, we focus on the low-molecular-weight urinary proteome. We review the methodological aspects of sample collection, preparation, analysis, and subsequent data evaluation. In the second part of this review, we summarize the recent progress in the definition and identification of clinically relevant polypeptide markers.

Urine profiling by SELDI-TOF/MS: monitoring of the critical steps in sample collection, handling and analysis

The topic of this study is the impact of several pre-analytical and analytical variables on proteomic profiling of human urine by surface enhanced laser desorption/ionization time of flight-mass spectrometry (SELDI-TOF-MS) in healthy subjects. Urine storage at room temperature caused a progressive degradation of proteins, which was prevented by the addition of protease inhibitors only up to 2 h from the collection. The timing of collection over the day had only a minor impact on protein profile, although influencing the intensity of peaks. Repeated freeze/thaw cycles (up to five) did not affect either the number or the intensity of the peaks. A comparison of the protein profile from eight different healthy individuals showed fairly consistent inter-subject similarities, along with between-subject differences, which were markedly dependent on the sex and the type of ProteinChip array used. The addition of a variety of denaturing agents improved the quality of the spectra with all the chips tested (CM10, Q10 and H50), but not with the copper-coated IMAC-30 chip. Finally, SPA matrix allowed to achieve a better performance of SELDI-TOF/MS spectrum, as compared with CHCA, regardless of the ProteinChip array used and even in the low m/z range (2500-10,000). In conclusion, we suggest that a careful choice of a number of pre-analytical and analytical conditions is required to accomplish and define a unifying protocol for the analysis of human urine by SELDI-TOF/MS, in physiological and in pathological states.

[Identification of biomarkers and therapeutic targets for renal cell cancer using ProteinChip technology]

In order to understand tumour biology in its complexity, it is necessary to investigate the proteomics in addition to the DNA and RNA level. SELDI-TOF-MS represents a new technology allowing a highly sensitive high-throughput analysis to detect specific protein profiles. In renal cancer, it was possible to define specific protein patterns in serum. Several proteins have been identified, i.e. serum amyloid alpha (SAA). Analysis of tumour tissues leads to a better understanding of tumour biology and provides the basis for differential classification and evaluation of prognosis. Investigation of the proteome concerning therapy results opens up the possibility of assessing downstream effects on the one hand and identifying biomarkers for selection of patients and therapy monitoring on the other hand. This review presents the first results for renal cancer.

Urine proteomics--prospects for future diagnostics

This brief overview of the potential diagnostic, prognostic and pathophysiological value of studies into the urine proteome describes hypothesis-driven investigations of individual proteins and proteome-wide search for urinary biomarkers of various diseases and their progression. It is intended to illustrate the recent progress in the area of urine proteomics and proselytize for the promise of this centuries-old technique of uroscopy, yet to reveal its secrets, using modem approaches.

CE – a multifunctional application for clinical diagnosis

CE has been used widely as an analytical tool with high separation power taking advantage of size, charge-to-size ratio, or isoelectric point of various analytes. In combination with detection methods, such as UV absorption, electrochemical detection, fluorescence, or mass spectrometry (MS), it allows the separation and detection of inorganic and organic ions, as well as complex compounds, such as polypeptides, nucleic acids, including PCR amplicons from viruses or bacteria. Recent interest in identification of biomarkers of diseases using body fluids leads to development of CE-MS techniques. These applications allowed identification of new potential biomarkers for clinical diagnosis and monitoring of therapeutic interventions. In this report, we present a technical overview of various CE techniques and discuss their applications in clinical medicine.

Sample handling for mass spectrometric proteomic investigations of human sera

Proteomic investigations of sera are potentially of value for diagnosis, prognosis, choice of therapy, and disease activity assessment by virtue of discovering new biomarkers and biomarker patterns. Much debate focuses on the biological relevance and the need for identification of such biomarkers while less effort has been invested in devising standard procedures for sample preparation and storage in relation to model building based on complex sets of mass spectrometric (MS) data. Thus, development of standardized methods for collection and storage of patient samples together with standards for transportation and handling of samples are needed. This requires knowledge about how sample processing affects MS-based proteome analyses and thereby how nonbiological biased classification errors are avoided. In this study, we characterize the effects of sample handling, including clotting conditions, storage temperature, storage time, and freeze/thaw cycles, on MS-based proteomics of human serum by using principal components analysis, support vector machine learning, and clustering methods based on genetic algorithms as class modeling and prediction methods. Using spiking to artificially create differentiable sample groups, this integrated approach yields data that--even when working with sample groups that differ more than may be expected in biological studies--clearly demonstrate the need for comparable sampling conditions for samples used for modeling and for the samples that are going into the test set group. Also, the study emphasizes the difference between class prediction and class comparison studies as well as the advantages and disadvantages of different modeling methods.

Urinary proteomics: a tool to discover biomarkers of kidney diseases

There is intense interest in applying proteomics to urine analysis in order to promote a better understanding of kidney disease processes, develop new biomarkers for diagnosis and detect early factors that contribute to end-stage renal diseases. This interest creates numerous opportunities as well as challenges. To fulfill this task, proteomics requires, in its different stages of realization, various technological platforms with high sensitivity, high throughput and large automation ability. In this review, we will give an overview of promising proteomic methods that can be used for analyzing urinary proteome and detecting biomarkers for different kidney diseases. Furthermore, we will focus on the current status and future directions in investigating kidney diseases using urinary proteomics.

Diagnostic potential for urinary proteomics

Urine represents a modified ultrafiltrate of plasma, with protein concentrations typically approximately 1000-fold lower than plasma. Urine’s low protein concentration might suggest it to be a less promising diagnostic specimen than plasma. However, urine can be obtained noninvasively and tests of many urinary proteins are well-established in clinical practice. Proteomic technologies expand opportunities to analyze urinary proteins, identifying more than 1000 proteins and peptides in urine. Urine offers a sampling of most plasma proteins, with increased proportions of low-molecular-weight protein and peptide components. Urine also offers enriched sampling of proteins released along the urinary tract. Although urine presents some challenges as a diagnostic specimen, its diverse range of potential markers offers great potential for diagnosis of both systemic and kidney diseases. Examples of clinical situations where this may be of value are for more sensitive detection of kidney transplant rejection or of renal toxicity of medications.

Influence of blood sampling on protein profiling and pattern analysis using matrix-assisted laser desorption/ionisation mass spectrometry

OBJECTIVE

To describe the influence of blood sampling/sampling tubes on mass spectrometric and clustering results, and on clinical blood variables, in blood samples collected from healthy volunteers and patients with prostate cancer.

PATIENTS, SUBJECTS AND METHODS

Two venous blood samples were taken from 12 healthy volunteers and 12 patients with localized prostate cancer. Two blood samples were taken from each participant using two different venepuncture systems (group A and group B). The Kolmogorov-Smirnov test was used to identify the peaks distinguishing the different groups. In a 10-fold cross-validation study, decision trees for identifying discriminatory peaks that separate the benign from the malignant were constructed.

RESULTS

The decision tree separated samples measured by matrix-assisted laser desorption/ionization mass spectrometry (MALDI MS) from healthy volunteers from those of patients with prostate cancer, with a sensitivity of 93.6% and a specificity of 91.6%. Of special interest is that one peak at 6941 m/z was produced during blood sample preparation and had a very powerful influence on the results of the classification.

CONCLUSION

The results clearly showed that blood-sampling systems have a great influence on the recorded MALDI MS traces, and thus can markedly influence and confound the results of the MS analysis, whereas clinical variables might remain unchanged. MS profiling is a promising method of marker discovery, but as it could be shown well-designed studies are critical to allow proper interpretation for the identification of key variables as well as for the clinical use.

Advances in urinary proteome analysis and biomarker discovery

Noninvasive diagnosis of kidney diseases and assessment of the prognosis are still challenges in clinical nephrology. Definition of biomarkers on the basis of proteome analysis, especially of the urine, has advanced recently and may provide new tools to solve those challenges. This article highlights the most promising technological approaches toward deciphering the human proteome and applications of the knowledge in clinical nephrology, with emphasis on the urinary proteome. The data in the current literature indicate that although a thorough investigation of the entire urinary proteome is still a distant goal, clinical applications are already available. Progress in the analysis of human proteome in health and disease will depend more on the standardization of data and availability of suitable bioinformatics and software solutions than on new technological advances. It is predicted that proteomics will play an important role in clinical nephrology in the very near future and that this progress will require interactive dialogue and collaboration between clinicians and analytical specialists.

Metabolite profiling of human urine by CE-ESI-MS using separation electrolytes at low pH

We investigated the potential of CE coupled to electrospray MS (CE-ESI-MS) in metabolite profiling of human urine without any sample prefractionation step. A heterogeneous mixture of biologically relevant compounds covering a broad range of physicochemical properties was used to optimize separation conditions in fused-silica capillaries. A running electrolyte containing 50 mM of acetic acid and 50 mM of formic acid at pH 2.5 was used for the CE separations. A sheath-flow electrospray interface was employed for CE-ESI-MS analysis. Sheath liquids containing 80:20 v/v methanol/water with 0.1% v/v of acetic acid or 60:40 v/v isopropanol/water with 0.5% v/v of ammonia were selected for optimum detection in positive and negative ESI modes, respectively. Reproducibility and sensitivity were studied, and strategies for identification of the separated urinary compounds are suggested. We report major advantages and disadvantages of CE-ESI-MS for metabolite profiling of human body fluids. This work may be regarded as a first step in the use of CE-ESI-MS for reliable differential analysis of body fluids from healthy and diseased individuals.

Assessing the utility of SELDI-TOF and model averaging for serum proteomic biomarker discovery

The SELDI-TOF technique was used to profile serum proteins from Type 1 diabetes (T1D) patients and healthy autoantibody-negative (AbN) controls. Univariate and multivariate analyses were performed to identify putative biomarkers for T1D and to assess the reproducibility of the SELDI technique. We found 146 protein/peptide peaks (581 total peaks discovered) in human serum showing statistical differences in expression levels between T1D patients and controls, with 84% of these peaks showing technical replication. Because individual proteins did not offer great power for disease prediction, we used our model averaging approach that combines the information from multiple multivariate models to accurately classify T1D and control subjects (88.9% specificity and 90.0% sensitivity). Analyses of a test subset of the data showed less accuracy (82.8% specificity and 76.2% sensitivity), although the results are still positive. Unfortunately, no multivariate model could be replicated using the same samples. This first attempt of high throughput analyses of the human serum proteome in T1D patients suggests that model averaging is a viable method for developing biomarkers; however, the reproducibility of SELDI-TOF is currently not sufficient to be used for classification of complex diseases like T1D.

Standardized peptidome profiling of human urine by magnetic bead separation and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry

BACKGROUND

Peptidome profiling of human urine is a promising tool to identify novel disease-associated biomarkers; however, a wide range of preanalytical variables influence the results of peptidome analysis. Our aim was to develop a standardized protocol for reproducible urine peptidome profiling by means of magnetic bead (MB) separation followed by matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS).

METHODS

MBs with defined surface functionalities (hydrophobic interaction, cation exchange, and metal ion affinity) were used for peptide fractionation of urine. Mass accuracy and imprecision were calculated for 9 characteristic mass signals (M(r), 1000-10,000). Exogenous variables (instrument performance, urine sampling/storage conditions, freezing conditions, and freeze-thaw cycles) and endogenous variables (pH, urine salt and protein concentrations, and blood and bacteria interferences) were investigated with urine samples from 10 male and 10 female volunteers.

RESULTS

We detected 427 different mass signals in the urine of healthy donors. Within- and between-day imprecision in relative signal intensities ranged from 1% to 14% and from 4% to 16%, respectively. Weak cation-exchange and metal ion affinity MB preparations required adjustment of the urinary pH to 7. Storage time, storage temperature, the number of freeze-thaw cycles, and bacterial and blood contamination significantly influenced urine peptide patterns. Individual urine peptide patterns differed significantly within and between days. This imprecision was diminished by normalization to a urinary protein content of 3.5 microg.

CONCLUSION

This reliable pretreatment protocol allows standardization of preanalytical modalities and facilitates reproducible peptidome profiling of human urine by means of MB separation in combination with MALDI-TOF MS.

Mass spectrometry-based hepcidin measurements in serum and urine: analytical aspects and clinical implications

BACKGROUND

Discovery of the central role of hepcidin in body iron regulation has shed new light on the pathophysiology of iron disorders. Information is lacking on newer analytical approaches to measure hepcidin in serum and urine. Recent reports on the measurement of urine and serum hepcidin by surface-enhanced laser-desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) necessitate analytical and clinical evaluation of MS-based methodologies.

METHODS

We used SELDI-TOF MS, immunocapture, and tandem MS to identify and characterize hepcidin in serum and urine. In addition to diagnostic application, we investigated analytical reproducibility and biological and preanalytical variation for both serum and urine on Normal Phase 20 and Immobilized Metal Affinity Capture 30 ProteinChip arrays. We obtained samples from healthy controls and patients with documented iron-deficiency anemia, inflammation-induced anemia, thalassemia major, and hereditary hemochromatosis.

RESULTS

Proteomic techniques showed that hepcidin-20, -22, and -25 isoforms are present in urine. Hepcidin-25 in serum had the same amino acid sequence as hepcidin-25 in urine, whereas hepcidin-22 was not detected in serum. The interarray CV was 15% to 27%, and interspot CV was 11% to 13%. Preliminary studies showed that hepcidin-25 differentiated disorders of iron metabolism. Urine hepcidin is more affected by multiple freeze-thaw cycles and storage conditions, but less influenced by diurnal variation, than is serum hepcidin.

CONCLUSION

SELDI-TOF MS can be used to measure hepcidin in both serum and urine, but serum requires a standardized sampling protocol.

PrepMS: TOF MS data graphical preprocessing tool

We introduce a simple-to-use graphical tool that enables researchers to easily prepare time-of-flight mass spectrometry data for analysis. For ease of use, the graphical executable provides default parameter settings, experimentally determined to work well in most situations. These values, if desired, can be changed by the user. PrepMS is a stand-alone application made freely available (open source), and is under the General Public License (GPL). Its graphical user interface, default parameter settings, and display plots allow PrepMS to be used effectively for data preprocessing, peak detection and visual data quality assessment.

AVAILABILITY

Stand-alone executable files and Matlab toolbox are available for download at: http://sourceforge.net/projects/prepms

Proteomics profiling of urine with surface enhanced laser desorption/ionization time of flight mass spectrometry

BACKGROUND

Urine consists of a complex mixture of peptides and proteins and therefore is an interesting source of biomarkers. Because of its high throughput capacity SELDI-TOF-MS is a proteomics technology frequently used in biomarker studies. We compared the performance of seven SELDI protein chip types for profiling of urine using standard chip protocols.

RESULTS

Performance was assessed by determining the number of detectable peaks and spot to spot variation for the seven array types and two different matrices: SPA and CHCA. A urine sample taken from one healthy volunteer was applied in eight-fold for each chip type/matrix combination. Data were analyzed for total number of detected peaks (S/N > 5). Spot to spot variation was determined by calculating the average CV of peak intensities. In addition, an inventory was made of detectable peaks with each chip and matrix type. Also the redundancy in peaks detected with the different chip/matrix combinations was determined. A total of 425 peaks (136 non-redundant peaks) could be detected when combining the data from the seven chip types and the two matrices. Most peaks were detected with the CM10 chip with CHCA (57 peaks). The Q10 with CHCA (51 peaks), SEND (48 peaks) and CM10 with SPA (48 peaks) also performed well. The CM10 chip with CHCA also has the best reproducibility with an average CV for peak intensity of 13%.

CONCLUSION

The combination of SEND, CM10 with CHCA, CM10 with SPA, IMAC-Cu with SPA and H50 with CHCA provides the optimal information from the urine sample with good reproducibility. With this combination a total of 217 peaks (71 non-redundant peaks) can be detected with CV's ranging from 13 to 26%, depending on the chip and matrix type. Overall, CM10 with CHCA is the best performing chip type.