Recent progress in urinary proteomics

Integrated proteomic and metabolomic profiling of urine of renal anemia patients uncovers the molecular mechanisms of roxadustat

Roxadustat (FG-4592) is a hypoxia-inducible factor prolyl hydroxylase inhibitor (HIF-PHI) prescribed to patients with low hemoglobin associated with chronic kidney disease. Due to the various HIF-mediated adaptive responses, FG-4592 has attracted significant interest for therapeutic use against various diseases. However, the clinical application of Roxadustat remains limited due to a lack of understanding of its underlying mechanisms. Herein, we performed label-free quantitative liquid chromatography with tandem mass spectrometry (LC-MS-MS) proteomics and un-targeted metabolomics to study the protein and metabolite alterations in the urine of renal anemia patients before and after Roxadustat therapy. The results were validated by parallel reaction monitoring (PRM). A total of 46 proteins (including 15 upregulated and 31 downregulated proteins) and 207 metabolites were significantly altered after Roxadustat treatment in urine samples obtained from renal anemia patients. Then, the altered proteins were further validated by PRM. Finally, proteomics combined with metabolomics analysis revealed that the Ras signalling pathway, cysteine and methionine metabolism, arginine and proline metabolism, and cholesterol metabolism were the main pathways altered by Roxadustat treatment. The multi-omics analysis revealed that Roxadustat could alter the protein expression and reverse the potential metabolic changes to exert hypotensive, lipid metabolic regulation, and renoprotective effects in clinical practice.

Biliary Strictures and Cholangiocarcinoma - Untangling a Diagnostic Conundrum

Cholangiocarcinoma is an uncommon and highly aggressive biliary tract malignancy with few manifestations until late disease stages. Diagnosis is currently achieved through a combination of clinical, biochemical, radiological and histological techniques. A number of reported cancer biomarkers have the potential to be incorporated into diagnostic pathways, but all lack sufficient sensitivity and specificity limiting their possible use in screening and early diagnosis. The limitations of standard serum markers such as CA19-9, CA125 and CEA have driven researchers to identify multiple novel biomarkers, yet their clinical translation has been slow with a general requirement for further validation in larger patient cohorts. We review recent advances in the diagnostic pathway for suspected CCA as well as emerging diagnostic biomarkers for early detection, with a particular focus on non-invasive approaches.

A combination of urinary biomarker panel and PancRISK score for earlier detection of pancreatic cancer: A case-control study

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers, with around 9% of patients surviving >5 years. Asymptomatic in its initial stages, PDAC is mostly diagnosed late, when already a locally advanced or metastatic disease, as there are no useful biomarkers for detection in its early stages, when surgery can be curative. We have previously described a promising biomarker panel (LYVE1, REG1A, and TFF1) for earlier detection of PDAC in urine. Here, we aimed to establish the accuracy of an improved panel, including REG1B instead of REG1A, and an algorithm for data interpretation, the PancRISK score, in additional retrospectively collected urine specimens. We also assessed the complementarity of this panel with CA19-9 and explored the daily variation and stability of the biomarkers and their performance in common urinary tract cancers.

METHODS AND FINDINGS

Clinical specimens were obtained from multiple centres: Barts Pancreas Tissue Bank, University College London, University of Liverpool, Spanish National Cancer Research Center, Cambridge University Hospital, and University of Belgrade. The biomarker panel was assayed on 590 urine specimens: 183 control samples, 208 benign hepatobiliary disease samples (of which 119 were chronic pancreatitis), and 199 PDAC samples (102 stage I-II and 97 stage III-IV); 50.7% were from female individuals. PDAC samples were collected from patients before treatment. The samples were assayed using commercially available ELISAs. Statistical analyses were performed using non-parametric Kruskal-Wallis tests adjusted for multiple comparisons, and multiple logistic regression. Training and validation datasets for controls and PDAC samples were obtained after random division of the whole available dataset in a 1:1 ratio. The substitution of REG1A with REG1B enhanced the performance of the panel to detect resectable PDAC. In a comparison of controls and PDAC stage I-II samples, the areas under the receiver operating characteristic curve (AUCs) increased from 0.900 (95% CI 0.843-0.957) and 0.926 (95% CI 0.843-1.000) in the training (50% of the dataset) and validation sets, respectively, to 0.936 in both the training (95% CI 0.903-0.969) and the validation (95% CI 0.888-0.984) datasets for the new panel including REG1B. This improved panel showed both sensitivity (SN) and specificity (SP) to be >85%. Plasma CA19-9 enhanced the performance of this panel in discriminating PDAC I-II patients from controls, with AUC = 0.992 (95% CI 0.983-1.000), SN = 0.963 (95% CI 0.913-1.000), and SP = 0.967 (95% CI 0.924-1.000). We demonstrate that the biomarkers do not show significant daily variation, and that they are stable for up to 5 days at room temperature. The main limitation of our study is the low number of stage I-IIA PDAC samples (n = 27) and lack of samples from individuals with hereditary predisposition to PDAC, for which specimens collected from control individuals were used as a proxy.

CONCLUSIONS

We have successfully validated our urinary biomarker panel, which was improved by substituting REG1A with REG1B. At a pre-selected cutoff of >80% SN and SP for the affiliated PancRISK score, we demonstrate a clinically applicable risk stratification tool with a binary output for risk of developing PDAC ('elevated' or 'normal'). PancRISK provides a step towards precision surveillance for PDAC patients, which we will test in a prospective clinical study, UroPanc.

Clinical Proteomics for Post-Hematopoeitic Stem Cell Transplantation Outcomes

Allogeneic hematopoietic stem cell transplantation (HSCT) is the most effective form of tumor immunotherapy available to date. However, while HSCT can induce beneficial graft-versus-leukemia (GVL) effect, the adverse effect of graft-versus-host disease (GVHD), which is closely linked to GVL, is the major source of morbidity and mortality following HSCT. Until recently, available diagnostic and staging tools frequently fail to identify those at higher risk of disease progression or death. Furthermore, there are shortcomings in the prediction of the need for therapeutic interventions or the response rates to different forms of therapy. The past decade has been characterized by an explosive evolution of proteomics technologies, largely due to important advances in high-throughput MS instruments and bioinformatics. Building on these opportunities, blood biomarkers have been identified and validated both as promising diagnostic tools, prognostic tools that risk-stratify patients before future occurrence of GVHD and as predictive tools for responsiveness to GVHD therapy and non-relapse mortality. These biomarkers might facilitate timely and selective therapeutic intervention. This review summarizes current information on clinical proteomics for GVHD as well as other complications following HSCT. Finally, it proposes future directions for the translation of clinical proteomics to discovery of new potential therapeutic targets to the development of drugs.

Proteomic and metabolomic approaches in the search for biomarkers in chronic kidney disease

Chronic kidney disease (CKD) is an aging-related disorder that represents a major global public health burden. Current biochemical biomarkers, such as serum creatinine and urinary albumin, have important limitations when used to identify the earliest indication of CKD or in tracking the progression to more advanced CKD. These issues underline the importance of finding and testing new molecular biomarkers that are capable of successfully meeting this clinical need. The measurement of changes in nature and/or levels of proteins and metabolites in biological samples from patients provide insights into pathophysiological processes. Proteomic and metabolomic techniques provide opportunities to record dynamic chemical signatures in patients over time. This review article presents an overview of the recent developments in the fields of metabolomics and proteomics in relation to CKD. Among the many different proteomic biomarkers proposed, there is particular interest in the CKD273 classifier, a urinary proteome biomarker reported to predict CKD progression and with implementation potential. Other individual non-invasive peptidomic biomarkers that are potentially relevant for CKD detection include type 1 collagen, uromodulin and mucin-1. Despite the limited sample sizes and variability of the metabolomics studies, some metabolites such as trimethylamine N-oxide, kynurenine and citrulline stand out as potential biomarkers in CKD.

Urinary peptide-based classifier CKD273: towards clinical application in chronic kidney disease

Capillary electrophoresis coupled with mass spectrometry (CE-MS) has been used as a platform for discovery and validation of urinary peptides associated with chronic kidney disease (CKD). CKD affects ∼ 10% of the population, with high associated costs for treatments. A urinary proteome-based classifier (CKD273) has been discovered and validated in cross-sectional and longitudinal studies to assess and predict the progression of CKD. It has been implemented in studies employing cohorts of > 1000 patients. CKD273 is commercially available as an in vitro diagnostic test for early detection of CKD and is currently being used for patient stratification in a multicentre randomized clinical trial (PRIORITY). The validity of the CKD273 classifier has recently been evaluated applying the Oxford Evidence-Based Medicine and Southampton Oxford Retrieval Team guidelines and a letter of support for CKD273 was issued by the US Food and Drug Administration. In this article we review the current evidence published on CKD273 and the challenges associated with implementation. Definition of a possible surrogate early endpoint combined with CKD273 as a biomarker for patient stratification currently appears as the most promising strategy to enable the development of effective drugs to be used at an early time point when intervention can still be effective.

Urinary haptoglobin, alpha-1 anti-chymotrypsin and retinol binding protein identified by proteomics as potential biomarkers for lupus nephritis

The study was aimed at identification by proteomics and validation by enzyme-linked immunosorbent assay (ELISA) of potential urinary biomarkers for lupus nephritis. Study subjects comprised 88 systemic lupus erythematosus (SLE) patients and 60 controls (rheumatoid arthritis, diabetes mellitus and healthy individuals). Based on the SLE disease activity index (SLEDAI), patients were classified as active renal (AR), active non-renal (ANR) or inactive disease (ID). Urinary proteins from a group of patients with AR or ID were resolved by two-dimensional gel electrophoresis and identified by matrix-assisted laser desorption ionization-time of flight-mass spectrometry (MALDI-TOF-MS/MS). The selected biomarkers were validated by ELISA using samples from all patients and controls. AR patients were followed-up for 12 months after start of therapy. Three urinary proteins, alpha-1 anti-chymotrypsin (ACT), haptoglobin (HAP) and retinol binding protein (RBP), were detected in patients with AR and not ID. Upon validation, ACT levels were higher in AR patients than the other groups (P < 0·001) and showed good correlation with renal SLEDAI (r = 0·577, P < 0·001) as well as SLEDAI (r = 0·461, P < 0·001). Similarly, HAP levels were > 10-fold higher in AR than other groups (P < 0·001) and correlated well with renal SLEDAI (r = 0·594, P < 0·001) and SLEDAI (r = 0·371, P < 0·01). RBP levels were also higher in AR patients than in other groups (P < 0·05), except diabetes, and showed moderate correlation with renal SLEDAI (r = 0·284, P < 0·008) and SLEDAI (r = 0·316, P < 0·003). Upon follow-up with treatment, levels of all three proteins declined at 6 and 12 months (P < 0·01). Multiple logistic regression identified ACT as the best marker to differentiate AR from ANR. Urinary HAP, ACT and RBP are potential biomarkers for lupus nephritis activity.

Physiologic changes of urinary proteome by caffeine and excessive water intake

Background:

Diurnal variations and physiologic changes of urinary proteome have been suggested in the urinary proteomics field. However, no clear evidence has been demonstrated. The present study thus aimed to define changes in urinary proteome by physiological stimuli, i.e. caffeine intake and excessive water drinking, both of which cause physiologic diuresis.

Methods:

Urine samples were collected from 30 healthy individuals under three different conditions: (i) morning void as the control; (ii) after drinking a cup of coffee; and (iii) after drinking 1 L of water within 20 min. Thereafter, differentially excreted proteins were analyzed by 2-DE proteomics approach and validated by Western blotting and ELISA.

Results:

Spot matching, quantitative intensity analysis, and ANOVA followed by Tukey’s post-hoc multiple comparisons and the Bonferroni correction revealed significant differences in levels of five protein spots among three different conditions. These proteins were identified by quadrupole time-of-flight mass spectrometry (Q-TOF MS) and/or MS/MS analyses as kininogen 1 isoform 3, β-actin, prostaglandin D synthase (PGDS), fibrinogen α-chain and immunoglobulin light chain. Among these, the decreased level of immunoglobulin was successfully validated by Western blotting and ELISA.

Conclusions:

These data indicated that caffeine intake and excessive water drinking could affect urinary excretion of some proteins and may affect urinary proteome analysis.

Permanent proteins in the urine of healthy humans during the Mars-500 experiment

Urinary proteins serve as indicators of various conditions in human normal physiology and disease pathology. Using mass spectrometry proteome analysis, the permanent constituent of the urine was examined in the Mars-500 experiment (520 days isolation of healthy volunteers in a terrestrial complex with an autonomous life support system). Seven permanent proteins with predominant distribution in the liver and blood plasma as well as extracellular localization were identified. Analysis of the overrepresentation of the molecular functions and biological processes based on Gene Ontology revealed that the functional association among these proteins was low. The results showed that the identified proteins may be independent markers of the various conditions and processes in healthy humans and that they can be used as standards in determination of the concentration of other proteins in the urine.

Potential biomarkers for early detection of acute graft-versus-host disease

Acute graft-versus-host disease (aGVHD) is the main complication of allogeneic hematopoietic stem cell transplantation (HCT), resulting in considerable morbidity and mortality. Currently, the diagnosis of aGVHD is largely made based on clinical parameters and invasive biopsies. For the past 20 years, researchers have been trying to find reliable biomarkers to enable early and accurate diagnosis of aGVHD. Although a number of potential aGVHD biomarkers have been published, as yet, no validated diagnostic test is available. Proteomics encompasses a broad range of rapidly developing technologies, which have shown tremendous promise for early detection of aGVHD. In this article, we review the current state of aGVHD biomarker discovery, provide a summary of the key proteins of interest and the most common analytical procedures for the clinic, as well as outlining the significant challenges faced in their use.

Discovery and validation of graft-versus-host disease biomarkers

Allogeneic hematopoietic stem cell transplantation (allo-HSCT) is the most effective tumor immunotherapy available. Although allo-HSCT provides beneficial graft-versus-tumor effects, acute GVHD (aGVHD) is the primary source of morbidity and mortality after HSCT. Diagnosis of aGVHD is typically based on clinical symptoms in one or more of the main target organs (skin, liver, gastrointestinal tract) and confirmed by biopsy. However, currently available diagnostic and staging tools often fail to identify patients at higher risk of GVHD progression, unresponsiveness to therapy, or death. In addition, there are shortcomings in the prediction of GVHD before clinical signs develop, indicating the urgent need for noninvasive and reliable laboratory tests. Through the continuing evolution of proteomics technologies seen in recent years, plasma biomarkers have been identified and validated as promising diagnostic tools for GVHD and prognostic tools for nonrelapse mortality. These biomarkers may facilitate timely and selective therapeutic intervention but should be more widely validated and incorporated into a new grading system for risk stratification of patients and better-customized treatment. This review identifies biomarkers for detecting GVHD, summarizes current information on aGVHD biomarkers, proposes future prospects for the blinded evaluation of these biomarkers, and discusses the need for biomarkers of chronic GVHD.

Urinary proteomic shotgun approach for identification of potential acute rejection biomarkers in renal transplant recipients

BACKGROUND

Acute rejection (AR) episodes in renal transplant recipients are suspected when plasma creatinine is elevated and other potential causes out ruled. Graft biopsies are however needed for definite diagnosis. Non-invasive AR-biomarkers is an unmet clinical need. The urinary proteome is an interesting source in the search for such a biomarker in this population.

METHODS

In this proof of principle study, serial urine samples in the early post transplant phase from 6 patients with biopsy verified acute rejections and 6 age-matched controls without clinical signs of rejection were analyzed by shotgun proteomics.

RESULTS

Eleven proteins fulfilled predefined criteria for regulation in association with AR. They presented detectable regulation already several days before clinical suspicion of AR (increased plasma creatinine). The regulated proteins could be grouped by their biological function; proteins related to growth and proteins related to immune response. Growth-related proteins (IGFBP7, Vasorin, EGF and Galectin-3-binding protein) were significantly up-regulated in association with AR (P = 0.03) while proteins related to immune response (MASP2, C3, CD59, Ceruloplasmin, PiGR and CD74) tended to be up-regulated ( P = 0.13).

CONCLUSION

The use of shotgun proteomics provides a robust and sensitive method for identification of potentially predictive urinary biomarkers of AR. Further validation of the current findings is needed to establish their potential clinical role with regards to clinical AR diagnosis.

TRIAL REGISTRATION

ClinicalTrials.gov number NCT00139009.

A method for isolation and identification of urinary biomarkers in patients with diabetic nephropathy

PURPOSE

The poor performance of current tests for predicting the onset, progression and treatment response of diabetic nephropathy has engendered a search for more sensitive and specific urinary biomarkers. Our goal was to develop a new method for protein biomarker discovery in urine from these patients.

EXPERIMENTAL DESIGN

We analyzed urine from normal subjects and patients with early and advanced nephropathy. Proteins were separated using a novel analysis process including immunodepletion of high-abundance proteins followed by two-stage LC fractionation of low-abundance proteins. The proteins in the fractions were sequenced using MS/MS.

RESULTS

Immunodepletion of selected high-abundance proteins followed by two-stage LC produced approximately 700 fractions, each less complex and more amenable to analysis than the mixture and requiring minimal processing for MS identification. Comparison of fractions between normal and diabetic nephropathy subjects revealed several low-abundance proteins that reproducibly distinguished low glomerular filtration rate (GFR) from both high GFR diabetic and normal subjects, including uteroglobin, a protein previously associated with renal scarring.

CONCLUSIONS AND CLINICAL RELEVANCE

We developed a novel method to identify low-abundance urinary proteins that enables the discovery of potential biomarkers to improve the diagnosis and management of patients with diabetic nephropathy.

Proteomics and systems biology for understanding diabetic nephropathy

Like many diseases, diabetic nephropathy is defined in a histopathological context and studied using reductionist approaches that attempt to ameliorate structural changes. Novel technologies in mass spectrometry-based proteomics have the ability to provide a deeper understanding of the disease beyond classical histopathology, redefine the characteristics of the disease state, and identify novel approaches to reduce renal failure. The goal is to translate these new definitions into improved patient outcomes through diagnostic, prognostic, and therapeutic tools. Here, we review progress made in studying the proteomics of diabetic nephropathy and provide an introduction to the informatics tools used in the analysis of systems biology data, while pointing out statistical issues for consideration. Novel bioinformatics methods may increase biomarker identification, and other tools, including selective reaction monitoring, may hasten clinical validation.

"The quest for biomarkers": are we on the right technical track?

The discovery phase of biomarkers of diagnostic or therapeutic interest started a decade ago with the very rapid development of proteomic investigations. In spite of the development of innovative technologies and multiple approaches, the "harvest" is still modest. Various reasons justified the encountered difficulties and most of them have been circumvented by specific sample treatments or dedicated analytical approaches. Nevertheless, the situation of very modest biomarker discovery level did not change much. This review intends to specifically analyze the main approaches used for biomarker discovery phase and evaluate related advantages and disadvantages. Thus, preliminary sample treatments such as fractionation, depletion and reduction of dynamic concentration range will critically be discussed and then the main differential expression investigation methods analyzed. Combinations of technologies are also discussed along with possible proposals to federate associations of complementary technologies for better chances of success.

Urinary exosomes and proteomics

A number of highly abundant proteins in urine have been identified through proteomics approaches, and some have been considered as disease-biomarker candidates. These molecules might be clinically useful in diagnosis of various diseases. However, none has proven to be specifically indicative of perturbations of cellular processes in cells associated with urogenital diseases. Exosomes could be released into urine which flows through the kidney, ureter, bladder and urethra, with a process of filtration and reabsorption. Urinary exosomes have been recently suggested as alternative materials that offer new opportunities to identify useful biomarkers, because these exosomes secreted from epithelial cells lining the urinary track might reflect the cellular processes associated with the pathogenesis of diseases in their donor cells. Proteomic analysis of such urinary exosomes assists the search of urinary biomarkers reflecting pathogenesis of various diseases and also helps understanding the function of urinary exosomes in urinary systems. Thus, it has been recently suggested that urinary exosomes are one of the most valuable targets for biomarker development and to understand pathophysiology of relevant diseases.

Urinary proteomics analysis for renal injury in hypertensive disorders of pregnancy with iTRAQ labeling and LC-MS/MS

PURPOSE

As a noninvasive examination, urinary proteomics is a very useful tool to identify renal disease. The purpose of the present study was to find differential proteins among women with preeclampsia, gestational hypertension and normal pregnancy, and to screen potential biomarkers for the early diagnosis of preeclampsia.

EXPERIMENTAL DESIGN

Urinary proteins were identified by iTRAQ labeling coupled with 2-D LC-MS/MS. The bioinformatics analysis was performed with the Metacore software and the International Protein Index (IPI) and the Gene Ontology (GO) Database. The differentially expressed proteins were verified by ELISA.

RESULTS

362 nonredundant proteins were identified, 113 of which were expressed differentially between preeclampsia and normal pregnant group and 31 differential proteins among three groups. These differential proteins were associated with biological processes of blood coagulation, cell adhesion and differentiation, immune response and cytoskeleton development, etc. They interacted with each other in the network. The urinary angiotensinogen (AGT) was downregulated, which was consistent with the ELISA validation results.

CONCLUSIONS AND CLINICAL RELEVANCE

The present study found a multitude of differential proteins that might provide a clue for investigating the mechanism of proteinuria development in preeclampsia. Low urinary angiotensinogen levels were useful for identifying preeclampsia.

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.

Application of Preparative Electrophoresis for Clinical Proteomics in Urine: Is it Feasible?

Urine samples are easily attainable which makes them ideal substrates for biomarker research. Various techniques have been employed to unravel the urine proteome and identify disease biomarkers. Even though the presence of high abundance proteins in urine is not so pronounced as in the case of plasma, the presence of proteolytic products, many of which at low abundance, along with numerous frequently random chemical modifications, makes the analysis of urinary proteins challenging. To facilitate the detection of low abundance urinary proteins, in the study presented herein we applied two different electrophoretic techniques, preparative Lithium Dodecyl Sulfate (LDS)-PAGE in combination with 2-DE for urinary protein separation and enrichment. Our results indicate the effectiveness of this approach for the enrichment of low abundance and low molecular weight proteins and peptides in urine, and contribute towards the establishment of a urinary proteomic database. The application of this technique as a biomarker discovery tool faces several challenges: these include down-scaling of the technique, possible recompensation for the consequent expected decrease in protein resolution, by optimizing steps of the experimental workflow as well as getting a good understanding of the technical variability of the technique. Under these conditions, preparative electrophoresis can become an effective tool for clinical proteomics applications.

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.

Variation in protein levels obtained from human blood cells and biofluids for platelet, peripheral blood mononuclear cell, plasma, urine and saliva proteomics

Blood cells and biofluid proteomics are emerging as a valuable tool to assess effects of interventions on health and disease. This study is aimed to assess the amount and variability of proteins from platelets, peripheral blood mononuclear cells (PBMC), plasma, urine and saliva from ten healthy volunteers for proteomics analysis, and whether protein yield is affected by prolonged fasting. Volunteers provided blood, saliva and morning urine samples once a week for 4 weeks after an overnight fast. Volunteers were fasted for a further 24 h after the fourth sampling before providing their final samples. Each 10 mL whole blood provided 400-1,500 mug protein from platelets, and 100-600 mug from PBMC. 30 muL plasma depleted of albumin and IgG provided 350-650 mug protein. A sample of morning urine provided 0.9-8.6 mg protein/dL, and a sample of saliva provided 70-950 mug protein/mL. None of these yields were influenced by the degree of fasting (overnight or 36 h). In conclusion, in contrast to the yields from plasma, platelets and PBMC, the protein yields of urine and saliva samples were highly variable within and between subjects. Certain disease conditions may cause higher or lower PBMC counts and thus protein yields, or increased urinary protein levels.

Mass spectrometric analysis of body fluids for biomarker discovery

Hinging on the concept that extracellular proteins and polypeptides will provide information on the physiological state of specific organs, or even entire organisms, proteomic analysis of biological fluids for biomarker discovery has seen rapid expansion in recent years. Although multiple studies have had success using mass spectrometric analytical techniques for determination of proteins within a sample, inspection of naturally occurring species has been difficult, with most analyses using bottom-up methodology. We have applied a new fragmentation method, electron transfer dissociation (ETD), to this problem. We have previously illustrated the benefits to spectral quality and total identifications when using a combination of the complementary fragmentation techniques, ETD, and collision-activated dissociation, for analysis of naturally occurring proteins and polypeptides within biological fluids.

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.

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.

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.

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.

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.

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.