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

The diagnostic value of PCA3 gene-based analysis of urine sediments after digital rectal examination for prostate cancer in a Chinese population

Prostate cancer gene 3 (PCA3) encodes a prostate-specific mRNA that has shown promise as a prostate cancer (PCa) diagnostic tool and is detectable in prostate cancer cells shedding into urine after digital rectal examination (DRE). In our earlier studies, a tissue test for PCA3 appeared to have greater specificity for PCa. There, we performed a clinical evaluation of PCA3 mRNA assay in urine sediments after DRE enriched with prostate cells in a Chinese population. PCA3 mRNA was detected by real-time fluorescent quantitative reverse transcription-polymerase chain reaction (FQ-RT-PCR) in the urine sediments. PSA mRNA detected also by real-time FQ-RT-PCR was used to confirm the yield of prostate cells in the urine sediments beforehand and normalize PCA3 mRNA signals. The data were summarized in a receiver operating characteristic (ROC) curve to visualize the efficacy of ratio PCA3/PSA mRNA as a marker; sensitivity and specificity were calculated also. We also correlated the ratio PCA3/PSA mRNA to the biopsy results (including the presence or absence of malignancy and the Gleason score of the malignancy cases) and to the bone metastasis to evaluate its clinical value. The PCA3 mRNA expression (PCA3/PSA mRNA) in the PCa group was significantly higher than that in the BPH group. The AUC-ROC was 0.786 (95% CI: 0.683-0.889). When the cutoff value was set as 0.107, the sensitivity and specificity were 62.9% and 90.6%, respectively. The positive predictive value and negative predictive value of the PCA3 urine test was 78.6% and 81.7%, respectively. No significant correlation was found between urine PCA3 expression and Gleason score or bone metastasis. Results indicated the clinical usefulness of the PCA3/PSA mRNA of urine sediments after DRE as a molecular marker in the early diagnosis of prostate cancer, which appears to be highly specific for PCa. As a non-invasive and sample accessible assay, the PCA3/PSA mRNA may therefore be useful as an aid in the diagnosis of PCa.

The application of mass-spectrometry-based protein biomarker discovery to theragnostics

Over the last decade rapid developments in mass spectrometry have allowed the identification of multiple proteins in complex biological samples. This proteomic approach has been applied to biomarker discovery in the context of clinical pharmacology (the combination of biomarker and drug now being termed 'theragnostics'). In this review we provide a roadmap for early protein biomarker discovery studies, focusing on some key questions that regularly confront researchers.

Identification of a uromodulin fragment for diagnosis of IgA nephropathy

IgA nephropathy (IgAN) is one of the most common types of glomerulonephritis worldwide and is diagnosed only with a renal biopsy. The purpose of the present studies was to identify the potential biomarkers for the non-invasive diagnosis of IgAN. The combination of a magnetic bead separation system with matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) was used to analyze urinary peptides of IgAN patients, other glomerulopathy patients, and healthy controls. ClinProTools v.2.0 software was also applied to establish a diagnostic model for IgAN. Our results demonstrated that 11 features had optimal discriminatory performance (p <0.00001). Among these features, the peptide with m/z 1913.14 was identified as a fragment of uromodulin. Receiver operating characteristic (ROC) analysis for m/z 1913.14 showed that the area under the curve (AUC) was 0.998 for distinguishing IgAN versus healthy controls, and 0.815 for distinguishing IgAN versus other glomerulopathy. Analysis of urine peptides patterns by the magnetic bead separation system and MALDI-TOF-MS was a non-invasive diagnostic tool. We conclude that the urinary peptide with m/z 1913.14, which was identified as a uromodulin fragment, may be used as a biomarker for the non-invasive diagnosis of IgAN clinically.

Urinary proteomics as a novel tool for biomarker discovery in kidney diseases

Urine has become one of the most attractive biofluids in clinical proteomics, for its procurement is easy and noninvasive and it contains sufficient proteins and peptides. Urinary proteomics has thus rapidly developed and has been extensively applied to biomarker discovery in clinical diseases, especially kidney diseases. In this review, we discuss two important aspects of urinary proteomics in detail, namely, sample preparation and proteomic technologies. In addition, data mining in urinary proteomics is also briefly introduced. At last, we present several successful examples on the application of urinary proteomics for biomarker discovery in kidney diseases, including diabetic nephropathy, IgA nephropathy, lupus nephritis, renal Fanconi syndrome, acute kidney injury, and renal allograft rejection.

Quantitation of hepcidin in serum using ultra-high-pressure liquid chromatography and a linear ion trap mass spectrometer

Hepcidin is a peptide hormone that functions as a key regulator of mammalian iron metabolism. Biological levels are increased in end-stage renal disease and during inflammation but suppressed in hemochromatosis. Thus hepcidin levels have diagnostic importance. This study describes the development of an analytical method for the quantitative determination of the concentration of hepcidin in clinical samples. The fragmentation of hepcidin was investigated using triple quadrupole and linear ion trap mass spectrometers. A standard quantity of a stable isotopically labelled hepcidin internal standard was added to serum samples. Extraction was performed by protein precipitation and weak cation-exchange magnetic nanoparticles. Chromatography was carried out on sub 2 microm particle stationary phase, using ultra-high-pressure liquid chromatography and a linear ion trap for quantitation. The lower limit of quantitation was 0.4 nmol/L with less than 20% accuracy and precision. The mean hepcidin concentration in sera for controls was 4.6 +/- 2.7 nmol/L, in patients with sickle cell disease, 7.0 +/- 8.9 nmol/L; in patients with end-stage renal disease, 30.5 +/- 15.7 nmol/L; and patients with penetrant hereditary hemochromatosis, 1.4 +/- 0.8 nmol/L.

Effects of pretreatment protocols on human amniotic fluid protein profiling with SELDI-TOF MS using protein chips and magnetic beads

BACKGROUND

There is increasing interest in the use of human amniotic fluid (AF) proteomics with surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) for diagnosing pregnancy-associated abnormalities. A critical parameter of diagnostic biomarkers is the accuracy and reproducibility of protein patterns. We evaluated the effects of common pretreatment protocols on protein patterns generated using SELDI mass spectrometry with two different protein capture strategies (including functional protein chips and functionalized magnetic beads prior to MS analysis) in AF.

METHOD

Various extrinsic factors involved in processing and storing amniotic fluid, including matrix composition, sample storage time, temperature and freeze-thaw cycles, were analyzed regarding their impact on AF protein patterns using SELDI mass spectrometry with 2 different protein capture strategies.

RESULTS

Three extrinsic factors (sample storage for 3days at either room temperature or 4 degrees C or freeze-thawing the sample 5 times) significantly decreased the number or intensities of protein peaks detected in AF. Matrix dilutions also changed the spectra of AF, with more peaks and higher intensities observed with 50% alpha-cyano-4-hydroxycinnamic acid (CHCA). Moreover, protein chips captured more proteins or peptides than magnetic beads on SELDI-TOF MS profiling of AF.

CONCLUSIONS

These results suggest that extrinsic factors must be taken into account for valid data interpretation to ensure good reproducibility of AF profiling by SELDI mass spectrometry.

The effect of preanalytical factors on stability of the proteome and selected metabolites in cerebrospinal fluid (CSF)

To standardize the use of cerebrospinal fluid (CSF) for biomarker research, a set of stability studies have been performed on porcine samples to investigate the influence of common sample handling procedures on proteins, peptides, metabolites and free amino acids. This study focuses at the effect on proteins and peptides, analyzed by applying label-free quantitation using microfluidics nanoscale liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (chipLC-MS) as well as matrix-assisted laser desorption ionization Fourier transform ion cyclotron resonance mass spectrometry (MALDI-FT-ICR-MS) and Orbitrap LC-MS/MS to trypsin-digested CSF samples. The factors assessed were a 30 or 120 min time delay at room temperature before storage at -80 degrees C after the collection of CSF in order to mimic potential delays in the clinic (delayed storage), storage at 4 degrees C after trypsin digestion to mimic the time that samples remain in the cooled autosampler of the analyzer, and repeated freeze-thaw cycles to mimic storage and handling procedures in the laboratory. The delayed storage factor was also analyzed by gas chromatography mass spectrometry (GC-MS) and liquid chromatography mass spectrometry (LC-MS) for changes of metabolites and free amino acids, respectively. Our results show that repeated freeze/thawing introduced changes in transthyretin peptide levels. The trypsin digested samples left at 4 degrees C in the autosampler showed a time-dependent decrease of peak areas for peptides from prostaglandin D-synthase and serotransferrin. Delayed storage of CSF led to changes in prostaglandin D-synthase derived peptides as well as to increased levels of certain amino acids and metabolites. The changes of metabolites, amino acids and proteins in the delayed storage study appear to be related to remaining white blood cells. Our recommendations are to centrifuge CSF samples immediately after collection to remove white blood cells, aliquot, and then snap-freeze the supernatant in liquid nitrogen for storage at -80 degrees C. Preferably samples should not be left in the autosampler for more than 24 h and freeze/thaw cycles should be avoided if at all possible.

Time for new guidelines in advanced diabetes care: Paradigm change from delayed interventional approach to predictive, preventive & personalized medicine

Global burden of diabetes mellitus clearly demonstrate inadequacy of current diabetes care measures: the costs of caring for patients with diabetes mellitus are the highest compared to other frequent pathologies. Nonetheless, for every 10 s one patient dies of diabetes-related consequences. Thus, there is urgent need for highly effective measures that would lead to reduced prevalence, better long-term outcomes and improved quality of life for diabetic patients reducing associated economic burden. Such targeted measures would require the creation of new guidelines for advanced diabetes care that would provide for regulation, for timely predictive diagnostics as well as an effective prevention and creation of individualized treatment algorithms. Effective communication among the research community healthcare providers, policy-makers, educators and organized patient groups (Federations of Diabetics) is of paramount importance and essential for (pre)diabetes care. The ultimate mission of the "European Association for Predictive, Preventive & Personalised Medicine" is to promote this process in Europe and across the globe.

The feasibility of MS and advanced data processing for monitoring Schistosoma mansoni infection

PURPOSE

Sensitive diagnosis, monitoring of disease progression and the evaluation of chemotherapeutic interventions are of prime importance for the improvement of control and prevention strategies for Schistosomiasis. The aim of the present study was to identify novel markers of Schistosoma mansoni infection and disease using urine samples from a large cohort from an area endemic for S. mansoni.

EXPERIMENTAL DESIGN

Urine samples were collected and processed on an automated sample clean-up and fractionation system combining strong cation exchange and reversed phase, and analyzed by MS (MALDI ToF MS). The ClinPro Tools(™) (CPT) software and the Discrete Wavelet Transformation-Support Vector Machine (DWT-SVM) procedure were used for classification and statistical analysis.

RESULTS

We observed a large difference in urinary peptide profiles between children and adults but classification based on infection was possible only for children. Here, in the external validation data set, 93% of the infected children were classified correctly with DWT-SVM (versus 76% for CPT). In addition 91% of low-infected children were classified correctly using DWT-SVM (versus 85% for CPT). The discriminating peptides were identified as fragments of collagen 1A1 and 1A3, and uromodulin.

CONCLUSIONS AND CLINICAL RELEVANCE

In conclusion, we provide the usefulness of a peptidomics profiling approach combined with DWT-SVM in the monitoring of S. mansoni infection.

Analytical error reduction using single point calibration for accurate and precise metabolomic phenotyping

Analytical errors caused by suboptimal performance of the chosen platform for a number of metabolites and instrumental drift are a major issue in large-scale metabolomics studies. Especially for MS-based methods, which are gaining common ground within metabolomics, it is difficult to control the analytical data quality without the availability of suitable labeled internal standards and calibration standards even within one laboratory. In this paper, we suggest a workflow for significant reduction of the analytical error using pooled calibration samples and multiple internal standard strategy. Between and within batch calibration techniques are applied and the analytical error is reduced significantly (increase of 25% of peaks with RSD lower than 20%) and does not hamper or interfere with statistical analysis of the final data.

Comprehensive human urine standards for comparability and standardization in clinical proteome analysis

PURPOSE

Urine proteomics is emerging as a powerful tool for biomarker discovery. The purpose of this study is the development of a well-characterized "real life" sample that can be used as reference standard in urine clinical proteomics studies.

EXPERIMENTAL DESIGN

We report on the generation of male and female urine samples that are extensively characterized by different platforms and methods (CE-MS, LC-MS, LC-MS/MS, 1-D gel analysis in combination with nano-LC MS/MS (using LTQ-FT ultra), and 2-DE-MS) for their proteome and peptidome. In several cases analysis involved a definition of the actual biochemical entities, i.e. proteins/peptides associated with molecular mass and detected PTMs and the relative abundance of these compounds.

RESULTS

The combination of different technologies allowed coverage of a wide mass range revealing the advantages and complementarities of the different technologies. Application of these samples in "inter-laboratory" and "inter-platform" data comparison is also demonstrated.

CONCLUSIONS AND CLINICAL RELEVANCE

These well-characterized urine samples are freely available upon request to enable data comparison especially in the context of biomarker discovery and validation studies. It is also expected that they will provide the basis for the comprehensive characterization of the urinary proteome.

The emerging role of biomarkers in diabetic and hypertensive chronic kidney disease

Currently used measures to assess kidney function and injury are largely inadequate. Markers such as serum creatinine, formulas to estimate glomerular filtration rate, cystatin C, and proteinuria largely identify an underlying disease process that is well established. Thus, there has been a recent effort to identify new biomarkers that reflect kidney function, early injury, and/or repair that ultimately can relate to progression or regression of damage. Several biomarkers emerged recently that are able to detect kidney damage earlier than is currently possible with traditional biomarkers such as serum creatinine and proteinuria. Identification of urine biomarkers has proven to be beneficial in recent years because of ease of handling, stability, and the ability to standardize the various markers to creatinine or other peptides generally already present in the urine. Recent markers such as neutrophil gelatinase-associated lipocalin (NGAL), kidney injury molecule-1 (KIM-1), and podocin have garnered a lot of attention. The emergence of these and other biomarkers is largely because of the evolution of novel genomic and proteomic applications in investigations of acute kidney injury and chronic kidney disease. In this article, we focus on the applications of these biomarkers in disease.

Urinary proteomic profiling for diagnostic bladder cancer biomarkers

The ability to detect and monitor bladder cancer in noninvasively obtained urine samples is a major goal. While a number of protein biomarkers have been identified and commercially developed, none have greatly improved the accuracy of sample evaluation over invasive cystoscopy. The ongoing development of high-throughput proteomic profiling technologies will facilitate the identification of molecular signatures that are associated with bladder disease. The appropriate use of these approaches has the potential to provide efficient biomarkers for the early detection and monitoring of recurrent bladder cancer. Identification of disease-associated proteins will also advance our knowledge of tumor biology, which, in turn, will enable development of targeted therapeutics aimed at reducing morbidity from bladder cancer. In this article, we focus on the accumulating proteomic signatures of urine in health and disease, and discuss expected future developments in this field of research.

Challenges of genomics and proteomics in nephrology

An increasing number of patients suffering from renal diseases and limitations in standard diagnostic and therapeutic approaches has created an intense interest in applying genomics and proteomics in the field of nephrology. Genomics has provided a vast amount of information, linking the gene activity with disease. However, proteomic technologies allow us to understand proteins and their modifications, elucidating properties of cellular behavior that may not be reflected in analysis of gene expression. The application of these innovative approaches has recently yielded the promising new urinary biomarkers for acute kidney injury and chronic kidney disease, thus providing a better insight in renal pathophysiology and establishing the basis for new therapeutic strategies. Despite significant improvements in therapeutics, the mortality and morbidity associated with acute renal failure (ARF) remain high. The lack of early markers for ARF causes an unacceptable delay in initiating therapy. These biomarker panels will probably be useful for assessing the duration and severity of ARF, and for predicting progression and adverse clinical outcomes. Kidney failure leads to the uremic syndrome characterized by accumulation of uremic toxins, which are normally cleared by the kidneys. Proteomics has gained considerable interest in this field, as a new and promising analytical approach to identify new uremic toxins. The urinary proteome as a tool for biomarker discovery is still in its early phase. A major challenge will be the integration of proteomics with genomics data and their functional interpretation in conjunction with clinical results and epidemiology.

Urinary proteome profiling using 2D-DIGE and LC-MS/MS

Proteomic methodologies have been at the forefront of cancer research for several years. The use of proteomic strategies to study all expressed genes aims to discover biomarkers indicative of the physiological state of cancer cells at specific time points, enabling early diagnosis, following cancer development/progression, screening and monitoring the efficacy of new therapeutic agents. Onco-proteomics has the potential to impact on oncology practice by delivering individualised highly selective clinical care. 2D-DIGE (2D difference in gel electrophoresis) enables simultaneous examination and comparison of multiple samples using cyanine dyes to label amino acid residues that are then separated based on charge and mass. These advantages combined with universal availability have until recently made 2D-DIGE a first method of choice in cancer proteome analysis of diverse specimens, including tissues, cell lines, blood and other body fluids.

Advances in urinary proteome analysis and biomarker discovery in pediatric renal disease

Recent progress in proteomic analysis and strategies for the identification of clinically useful biomarkers in biofluids has led to the identification of urine as an excellent non-invasive reservoir for biomarkers of disease. Urinary biomarkers have been identified and validated on independent cohorts in different high-incidence adult renal diseases, including diabetic nephropathy, chronic kidney disease and immunoglobulin A-nephropathy, but also in extrarenal disease, such as coronary artery disease. Unfortunately, this type of research is underrepresented in the pediatric population. Here, we present the rare studies in the pediatric population that identified potential clinically useful urinary biomarkers in ureteropelvic junction (UPJ) obstruction and renal Fanconi syndrome. These studies, although limited in number, clearly show the potential of urinary proteomics, especially in the pediatric population. It is anticipated that the advances made in the adult population, the lessons learned on the use of appropriate statistics and the inclusion of independent blinded validation cohorts in these types of studies will rapidly lead to clinical useful urinary biomarkers for other pediatric (renal) disease in a population where non-invasive analysis is particularly appreciated.

Standardized preprocessing of urine for proteome analysis

Proteome/peptidome profiling of human urine is a promising tool for the discovery of novel disease-associated biomarkers. However, a wide range of preanalytic variables influence the results of proteome/peptidome analysis regardless of the method used. We present a validated pretreatment protocol, which allows standardization of preanalytic modalities and facilitates reproducible peptidome profiling of human urine by means of magnetic bead (MB) separation in combination with MALDI-TOF MS. Such a procedure is necessary for generating consistent and reliable data from which meaningful results may be obtained for biomarker discovery and general proteomic experiments.

Urinary proteins for the diagnosis of obstructive sleep apnea syndrome

Approximately 2-3% of all children in the United States suffer from obstructive sleep apnea (OSA). This condition is characterized by repeated events of partial or complete obstruction of the upper airways during sleep leading to recurring episodes of hypercapnia, hypoxemia, and arousal throughout the night as well as snoring, which afflicts 7-10% of all children. Since clinical history and physical examination are unreliable in the differentiation between children with OSA and children with primary snoring (PS) who have no apparent alteration in sleep architecture, current diagnostic approaches for OSA require an overnight sleep study (ONP). ONP is onerous, relatively unavailable, labor intensive, and inconvenient, leading to long waiting periods and unnecessary delays in diagnosis and treatment. Development of noninvasive biomarker(s) capable of reliably distinguishing children with PS from those with OSA would greatly facilitate timely screening and diagnosis of OSA in children. Therefore, we hypothesized that proteomic strategies in the urine may permit the identification of biomarker(s) that reliably screen for OSA. In this study, time-of-flight mass spectrometry was used to profile proteins in the first morning void urines from children. We discovered that urocortins are increased in OSA and provide a noninvasive approach for quick and convenient diagnosis otf OSA in snoring children.

A review of experimental design best practices for proteomics based biomarker discovery: focus on SELDI-TOF

Surface Enhanced Laser/Desorption Ionization-time of flight (SELDI-TOF) mass spectrometry is a technique uniquely suited to the study of the urine proteome due to its salt tolerance, high-throughput, and small sample requirements. However, due to the extreme sensitivity of the technique, sample collection and storage conditions, as well as instrument protocols and analysis conditions, must be rigorously controlled to ensure that data generated and collected is accurate and free from artifacts. Robust and reproducible data sets can be generated and compared between clinical sites when experimental protocols are carefully standardized. This chapter aims to review known factors that cause irreproducible results so that the experiments may be designed with appropriate sample and process controls for successful biomarker discovery. A suggested protocol follows the review. A number of issues for study design are discussed and these are generally applicable to biomarker discovery experiments.

Challenges for biomarker discovery in body fluids using SELDI-TOF-MS

Protein profiling using SELDI-TOF-MS has gained over the past few years an increasing interest in the field of biomarker discovery. The technology presents great potential if some parameters, such as sample handling, SELDI settings, and data analysis, are strictly controlled. Practical considerations to set up a robust and sensitive strategy for biomarker discovery are presented. This paper also reviews biological fluids generally available including a description of their peculiar properties and the preanalytical challenges inherent to sample collection and storage. Finally, some new insights for biomarker identification and validation challenges are provided.

Urinary Proteome Analysis using Capillary Electrophoresis Coupled to Mass Spectrometry: A Powerful Tool in Clinical Diagnosis, Prognosis and Therapy Evaluation

Proteome analysis has emerged as a powerful tool to decipher (patho) physiological processes, resulting in the establishment of the field of clinical proteomics. One of the main goals is to discover biomarkers for diseases from tissues and body fluids. Due to the enormous complexity of the proteome, a separation step is required for mass spectrometry (MS)-based proteome analysis. In this review, the advantages and limitations of protein separation by two-dimensional gel electrophoresis, liquid chromatography, surface-enhanced laser desorption/ionization and capillary electrophoresis (CE) for proteomic analysis are described, focusing on CE-MS. CE-MS enables separation and detection of the small molecular weight proteome in biological fluids with high reproducibility and accuracy in one single processing step and in a short time. As sensitive and specific single biomarkers generally may not exist, a strategy to overcome this diagnostic void is shifting from single analyte detection to simultaneous analysis of multiple analytes that together form a disease-specific pattern. Such approaches, however, are accompanied with additional challenges, which we will outline in this review. Besides the choice of adequate technological platforms, a high level of standardization of proteomic measurements and data processing is also necessary to establish proteomic profiling. In this regard, demands concerning study design, choice of specimens, sample preparation, proteomic data mining, and clinical evaluation should be considered before performing a proteomic study.

An introspective comparison of random forest-based classifiers for the analysis of cluster-correlated data by way of RF++

Many mass spectrometry-based studies, as well as other biological experiments produce cluster-correlated data. Failure to account for correlation among observations may result in a classification algorithm overfitting the training data and producing overoptimistic estimated error rates and may make subsequent classifications unreliable. Current common practice for dealing with replicated data is to average each subject replicate sample set, reducing the dataset size and incurring loss of information. In this manuscript we compare three approaches to dealing with cluster-correlated data: unmodified Breiman's Random Forest (URF), forest grown using subject-level averages (SLA), and RF++ with subject-level bootstrapping (SLB). RF++, a novel Random Forest-based algorithm implemented in C++, handles cluster-correlated data through a modification of the original resampling algorithm and accommodates subject-level classification. Subject-level bootstrapping is an alternative sampling method that obviates the need to average or otherwise reduce each set of replicates to a single independent sample. Our experiments show nearly identical median classification and variable selection accuracy for SLB forests and URF forests when applied to both simulated and real datasets. However, the run-time estimated error rate was severely underestimated for URF forests. Predictably, SLA forests were found to be more severely affected by the reduction in sample size which led to poorer classification and variable selection accuracy. Perhaps most importantly our results suggest that it is reasonable to utilize URF for the analysis of cluster-correlated data. Two caveats should be noted: first, correct classification error rates must be obtained using a separate test dataset, and second, an additional post-processing step is required to obtain subject-level classifications. RF++ is shown to be an effective alternative for classifying both clustered and non-clustered data. Source code and stand-alone compiled versions of command-line and easy-to-use graphical user interface (GUI) versions of RF++ for Windows and Linux as well as a user manual (Supplementary File S2) are available for download at: http://sourceforge.org/projects/rfpp/ under the GNU public license.

Capillary electrophoresis-mass spectrometry as a powerful tool in biomarker discovery and clinical diagnosis: an update of recent developments

Proteome analysis has emerged as a powerful technology to decipher biological processes. One of the main goals is to discover biomarkers for diseases from tissues and body fluids. However, the complexity and wide dynamic range of protein expression present an enormous challenge to separation technologies and mass spectrometry (MS). In this review, we examine the limitations of proteomics, and aim towards the definition of the current key prerequisites. We focus on capillary electrophoresis coupled to mass spectrometry (CE-MS), because this technique continues to show great promise. We discuss CE-MS from an application point of view, and evaluate its merits and vices for biomarker discovery and clinical applications. Finally, we present several examples on the use of CE-MS to determine urinary biomarkers and implications for disease diagnosis, prognosis, and therapy evaluation.

Interpreting the proteome and peptidome in transplantation

Publication of the human proteome has prompted efforts to develop high-throughput techniques that can catalogue and quantify proteins and peptides present in different tissue types. The field of proteomics aims to identify, quantify, analyze, and functionally define a large number of proteins in cellular processes in different disease states on a global scale. Peptidomics, a newer name in the -omics world, measures and identifies naturally occurring low molecular weight peptides, also providing an insight into enzymatic processes and molecular events occurring in the system of interest. One area of major interest is the use of proteomics to identify diagnostic and prognostic biomarkers for different diseases as well as for various clinical phenotypes in organ transplantation that can advance targeted therapy for various forms of graft injury. Outcomes in organ transplantation can be potentially improved by identifying noninvasive biomarkers that will serve as triggers that predate graft injury, and can offer a means to customize patient treatment by differentiating among causes of acute and chronic graft injury. Proteomic and peptidomic strategies can be harnessed for frequent noninvasive measurements in tissue fluids, allowing for serial monitoring of organ disease. In this review, we describe the basic techniques used in proteomic and peptidomic approaches, point out special considerations in using these methods, and discuss their applications in recently published studies in organ transplantation.

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.

SELDI-TOF as a method for biomarker discovery in the urine of aristolochic-acid-treated mice

Aristolochic acids (AAs) present in Aristolochia plants are substances responsible for Chinese herbs nephropathy. Recently, strong indications have also been presented, which dietary poisoning with AA is responsible for endemic (Balkan) nephropathy (EN), an enigmatic renal disease that affects rural population living in some countries in Southeastern Europe. A mouse model was applied to follow the effects of two forms of AA, AAI and AAII. SDS-PAGE and SELDI-TOF mass spectrometry with normal phase chips were used to evaluate changes in the urine of treated animals. These two methods are demonstrated to be comparable. The use of SELDI-TOF MS for rapid analysis of a large number of samples and the combination of this method with nano-LC-ESI MS/MS for protein identification were demonstrated. Biomarker discovery after analysis of large cohort of EN patients will be the final aim of these investigations.

Mass Spectrometry in Diagnostic Oncoproteomics

Diagnostic oncoproteomics is the application of proteomic techniques for the diagnosis of malignancies. A new mass spectrometric technology involves surface enhanced laser desorption ionization combined with time-of flight mass analysis (SELDI-TOF-MS), using special protein chips. After the description of the relevant principles of the technique, including approaches to proteomic pattern diagnostics, applications are reviewed for the diagnosis of ovarian, breast, prostate, bladder, pancreatic, and head and neck cancers, and also several other malignancies. Finally, problems and prospects of the approach are discussed.

Sample preparation and fractionation for proteome analysis and cancer biomarker discovery by mass spectrometry

Sample preparation and fractionation technologies are one of the most crucial processes in proteomic analysis and biomarker discovery in solubilized samples. Chromatographic or electrophoretic proteomic technologies are also available for separation of cellular protein components. There are, however, considerable limitations in currently available proteomic technologies as none of them allows for the analysis of the entire proteome in a simple step because of the large number of peptides, and because of the wide concentration dynamic range of the proteome in clinical blood samples. The results of any undertaken experiment depend on the condition of the starting material. Therefore, proper experimental design and pertinent sample preparation is essential to obtain meaningful results, particularly in comparative clinical proteomics in which one is looking for minor differences between experimental (diseased) and control (nondiseased) samples. This review discusses problems associated with general and specialized strategies of sample preparation and fractionation, dealing with samples that are solution or suspension, in a frozen tissue state, or formalin-preserved tissue archival samples, and illustrates how sample processing might influence detection with mass spectrometric techniques. Strategies that dramatically improve the potential for cancer biomarker discovery in minimally invasive, blood-collected human samples are also presented.

Temporal stability of the urinary proteome after kidney transplant: more sensitive than protein composition?

The temporal urinary proteome was examined in 4 groups of individuals in order to determine the temporal stability of diverse individuals with apparently good kidney health. The groups consisted of (1) healthy volunteers at zero time, 1 and 6 months, (2) kidney donors before and after surgery, (3) recipients immediately after surgery, and (4) successful kidney transplant recipients from 1 month to 4 years after transplant. Proteins were detected by reverse phase extraction of urine followed by MALDI-TOF profile and by iTRAQ analysis. Unusual components of the MALDI-TOF profiles found only in transplant subjects occurred at m/ z = 3370, 3441 and 3385 (human neutrophil defensins), 4303, 10350, and 11732 (beta-2 microglobulin, B2M). The peaks at m/ z = 4303 and 11732 were also quite intense among kidney donors following surgery. The peaks at m/ z = 4303 and 10350 in transplant recipients were associated with higher serum creatinine. Several additional proteins detected by iTRAQ were up-regulated in a manner that correlated closely with B2M. Overall, despite large differences between protein composition in different transplant recipients, there was remarkable stability for each individual as detected by either MALDI-TOF or iTRAQ analyses. These results suggested that, within limits, stability of profile components may be as important as protein content for definition of kidney health. Longitudinal study of urinary proteins from kidney recipients may demonstrate instability as a sensitive biomarker of adverse kidney health.

Evaluation of urine proteome pattern analysis for its potential to reflect coronary artery atherosclerosis in symptomatic patients

Coronary artery disease (CAD) is a major cause of mortality and morbidity. Noninvasive proteome analysis could guide clinical evaluation and early/preventive treatment. Under routine clinical conditions, urine of 67 patients presenting with symptoms suspicious for CAD were analyzed by capillary electrophoresis directly coupled with mass spectrometry (CE-MS). All patients were subjected to coronary angiography and either assigned to a CAD or non-CAD group. A training set of 29 patients was used to establish CAD and non-CAD-associated proteome patterns of plasma as well as urine. Significant discriminatory power was achieved in urine but not in plasma. Therefore, urine proteomic analysis of further 38 patients was performed in a blinded study. A combination of 17 urinary polypeptides allowed separation of both groups in the test set with a sensitivity of 81%, a specificity of 92%, and an accuracy of 84%. Sequencing of urinary marker peptides identified fragments of collagen alpha1 (I and III), which we furthermore demonstrated to be expressed in atherosclerotic plaques of human aorta. In conclusion, specific CE-MS polypeptide patterns in urine were associated with significant CAD in patients with angina-typical symptoms. These promising findings need to be further evaluated in regard to reliability of a urine-based screening method with the potential of improving the diagnostic approaches for CAD.

Proteomic analysis of urine from proteinuric patients shows a proteolitic activity directed against albumin

BACKGROUND

Nephrotic syndrome is a condition that is clinically associated with poor outcome. In this study, we compared different techniques of urine sample preparation in order to develop a robust analytical protocol to define the differential urinary proteome of urinary abnormalities compared to nephrotic proteinuria.

METHODS

We recruited 5 normal control subjects, 16 patients with urinary abnormalities and 16 patients with nephrotic syndrome. Proteins from normal urine were processed using three different protocols [acetone, ultrafiltration and trichloroacetic acid (TCA) precipitation], depletion of albumin and IgGs and then analysed by two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) gels and mass spectrometry.

RESULTS

Comparing the three extraction methods by visual inspection of gels after 2D gel electrophoresis, the acetone precipitation and TCA methods yielded the best quality of protein extraction, while the acetone precipitation method was the most efficient. Furthermore, we tested three commercial kits for albumin and IgG depletion. We applied the optimized acetone extraction protocol to compare urinary samples from nephrotic patients (NP) to urinary samples obtained from patients presenting with urinary abnormalities (UAP). We observed a proteolytic activity directed against albumin. This observation was more prevalent in urinary samples from NP than from UAP. Within both groups, there was some inter-individual variability in the observed proteolytic activity. An increased concentration of alpha1 antitrypsin was also observed in urine of NP. We analysed albumin fragmentation by 1D and 2D western blots in the same samples skipping the albumin and IgG depletion steps to avoid the possible confound of albumin fragment removal. The analysis confirmed a stronger proteolytic activity in the nephrotic group.

CONCLUSIONS

The proteolytic activity against albumin and the anti-proteolytic activity of alpha1 antitrypsin are likely linked and could play an important role in the nephrotic process. If replicated in larger samples, this methodology may lead to a better understanding of the underlying pathophysiological process of nephrotic syndrome.

Searching for Potential Ovarian Cancer Biomarkers with Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry

Ovarian cancer is a common gynecological malignant disease, causing more deaths among women .The key objective in the treatment of ovarian cancer is early diagnosis. The objective of our study was to seek new ovarian cancer biomarkers based on a serum protein profile with the aim of discriminating ovarian cancer patients from healthy controls. An MB-WCX kit was used to analyze serum samples obtained from 20 ovarian cancer patients and 20 healthy controls and then we generated MALDI-TOF protein profiles from the analysis. After pre-processing of the spectra, linear analysis with ClinProTools bioinformatics software was used to classify protein profiles and search for prominent peaks that could be used as potential ovarian cancer biomarkers. Using ClinproTools bioinformatics and statistical software, we found 5 prominent expressed proteins in the ovarian cancer and healthy control groups. The mass to charge ratio were 4648.21(m/z), 9294.03(m/z), 3886.1(m/z), 9066.38(m/z) and 4254.71(m/z), respectively, and the former four proteins were expressed higher in the ovarian cancer patients, but the later one was expressed at lower levels in the cancer patients. The sensitivity and specificity were both more than 90%. From our study, we found that MALDI-TOF MS is a high-throughput sample preparation method and is a new potential tool for the diagnosis of human disease, not only to search for new early detection biomarkers in the ovarian cancer patients' serum samples, but also with a potential use for routine clinical work.

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.

Evaluation of urinary biomarkers for coronary artery disease, diabetes, and diabetic kidney disease

BACKGROUND

In this study we sought to validate urinary biomarkers for diabetes and two common complications, coronary artery disease (CAD) and diabetic nephropathy (DN).

METHODS

A CAD score calculated by summing the product of a classification coefficient and signal amplitude of 15 urinary polypeptides was previously developed. Five sequences of biomarkers in the panel were identified as fragments of collagen alpha-1(I) and alpha-1(III). Prospectively collected urine samples available for analysis from 19 out of 20 individuals with CAD (15 with type 1 diabetes [T1D] and four without diabetes) and age-, sex-, and diabetes-matched controls enrolled in the Coronary Artery Calcification in Type 1 Diabetes study were analyzed for the CAD score using capillary electrophoresis and electrospray ionization mass spectrometry. Two panels of biomarkers that were previously defined to distinguish diabetes status were analyzed to determine their relationship to T1D. Three biomarker panels developed to distinguish DN (DNS) and two biomarker panels developed to distinguish renal disease (RDS) were examined to determine their relationship with renal function.

RESULTS

The CAD score was associated with CAD (odds ratio with 95% confidence interval, 2.2 [1.3-5.2]; P = 0.0016) and remained significant when adjusted individually for age, albumin excretion rate (AER), blood pressure, waist circumference, intraabdominal fat, glycosylated hemoglobin, and lipids. DNS and RDS were significantly correlated with AER, cystatin C, and serum creatinine. The biomarker panels for diabetes were both significantly associated with T1D status (P < 0.05 for both).

CONCLUSIONS

We validated a urinary proteome pattern associated with CAD and urinary proteome patterns associated with T1D and DN.

A new strategy for faster urinary biomarkers identification by Nano-LC-MALDI-TOF/TOF mass spectrometry

BACKGROUND

LC-MALDI-TOF/TOF analysis is a potent tool in biomarkers discovery characterized by its high sensitivity and high throughput capacity. However, methods based on MALDI-TOF/TOF for biomarkers discovery still need optimization, in particular to reduce analysis time and to evaluate their reproducibility for peak intensities measurement. The aims of this methodological study were: (i) to optimize and critically evaluate each step of urine biomarker discovery method based on Nano-LC coupled off-line to MALDI-TOF/TOF, taking full advantage of the dual decoupling between Nano-LC, MS and MS/MS to reduce the overall analysis time; (ii) to evaluate the quantitative performance and reproducibility of nano-LC-MALDI analysis in biomarker discovery; and (iii) to evaluate the robustness of biomarkers selection.

RESULTS

A pool of urine sample spiked at increasing concentrations with a mixture of standard peptides was used as a specimen for biological samples with or without biomarkers. Extraction and nano-LC-MS variabilities were estimated by analyzing in triplicates and hexaplicates, respectively. The stability of chromatographic fractions immobilised with MALDI matrix on MALDI plates was evaluated by successive MS acquisitions after different storage times at different temperatures.Low coefficient of variation (CV%: 10-22%) and high correlation (R2 > 0.96) values were obtained for the quantification of the spiked peptides, allowing quantification of these peptides in the low fentomole range, correct group discrimination and selection of "specific" markers using principal component analysis. Excellent peptide integrity and stable signal intensity were found when MALDI plates were stored for periods of up to 2 months at +4 degrees C. This allowed storage of MALDI plates between LC separation and MS acquisition (first decoupling), and between MS and MSMS acquisitions while the selection of inter-group discriminative ions is done (second decoupling). Finally the recording of MSMS spectra to obtain structural information was focused only on discriminative ions in order to minimize analysis time.

CONCLUSION

Contrary to other classical approaches with direct online coupling of chromatographic separation and on the flight MS and/or MSMS data acquisition for all detected analytes, our dual decoupling strategy allowed us to focus on the most discriminative analytes, giving us more time to acquire more replicates of the same urine samples thus increasing detection sensitivity and mass precision.

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.

Urinary protein profiling with surface-enhanced laser desorption/ionization time-of-flight mass spectrometry in ETB receptor-deficient rats

The pathways leading to salt-sensitive hypertension and renal damage in rescued ETB receptor-deficient (ETBRd) rats are still unknown. The objective of the study was therefore to identify modifications of urinary peptide and protein expression in ETBRd rats (n = 9) and wild-type controls (n = 6) using SDS - polyacrylamide gel electrophoresis (SDS-PAGE) and surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) technology. Glomerular filtration rate, glomerulosclerosis, and tubulointerstitial fibrosis did not differ between the groups. ETBRd rats showed slightly higher blood pressure (p < 0.001), media/lumen ratio of intrarenal arteries (p < 0.01), and albuminuria (p < 0.01). SDS-PAGE confirmed albuminuria, but showed no differences in the urinary excretion of low molecular weight proteins (<60 kDa). SELDI-TOF-MS profiling revealed 9 proteomic features at molecular masses (Da) of 2720, 2980, 3130, 3345, 6466, 6682, 8550, 18 729, and 37 492, which were significantly elevated (p < 0.02) in urine of ETBRd rats. The results demonstrate that, independent of structural changes in the kidneys, ETB-receptor deficiency causes specific differences in urinary peptide and protein excretion. SELDI-TOF-MS may be a valuable tool for the characterization of urinary biomarkers helping to uncover the mechanism of ETBR action in the kidney.

Urine in clinical proteomics

Urine has become one of the most attractive biofluids in clinical proteomics as it can be obtained non-invasively in large quantities and is stable compared with other biofluids. The urinary proteome has been studied by almost any proteomics technology, but mass spectrometry-based urinary protein and peptide profiling has emerged as most suitable for clinical application. After a period of descriptive urinary proteomics the field is moving out of the discovery phase into an era of validation of urinary biomarkers in larger prospective studies. Although mainly due to the site of production of urine, the majority of these studies apply to the kidney and the urinary tract, but recent data show that analysis of the urinary proteome can also be highly informative on non-urogenital diseases and used in their classification. Despite this progress in urinary biomarker discovery, the contribution of urinary proteomics to the understanding of the pathophysiology of disease upon analysis of the urinary proteome is still modest mainly because of problems associated to sequence identification of the biomarkers. Until now, research has focused on the highly abundant urinary proteins and peptides, but analysis of the less abundant and naturally existing urinary proteins and peptides still remains a challenge. In conclusion, urine has evolved as one of the most attractive body fluids in clinical proteomics with potentially a rapid application in the clinic.