Microfiltration isolation of human urinary exosomes for characterization by MS

Purpose: The purpose of this study was to address the hypothesis that small vesicular urinary particles known as exosomes could be selectively microfiltered using low protein‐binding size exclusion filters, thereby simplifying their use in clinical biomarker discovery studies. Experimental design: We characterized a microfiltration approach using a low protein binding, hydrophilized polyvinylidene difluoride membrane to easily and efficiently isolate urinary exosomes from fresh, room temperature or 4°C urine, with a simultaneous depletion of abundant urinary proteins. Using LC‐MS, immunoblot analysis, and electron microscopy methods, we demonstrate this method to isolate intact exosomes and thereby enrich for a low abundant urinary proteome. Results: In comparison to other standard methods of exosome isolation including ultracentrifugation and nanofiltration, we demonstrate equivalent enrichment of the exosome proteome with reduced co‐purification of abundant urinary proteins. Conclusion and clinical relevance: In conclusion, we demonstrate a microfiltration isolation method that preserves the exosome structure, reduces contamination from higher abundant urinary proteins, and can be easily implemented into mass spectrometry analysis for biomarker discovery efforts or incorporation into routine clinical laboratory applications to yield higher sample throughput.     

Biomarker discovery in glomerular diseases using urinary proteomics

Renal biopsy remains the gold standard test for definitive diagnosis of glomerular diseases. This invasive procedure; however, has a potential risk for serious complications and is contraindicated in some patients. It is therefore essential to search for noninvasive biomarkers for the diagnosis and prognosis of glomerular diseases. The urine is the most appropriate sample for biomarker discovery in glomerular diseases. Urinary proteomics has thus gained a wide acceptance and has been extensively applied to this area. This review focuses mainly on applications of proteomic technologies to urinary proteome profiling for biomarker discovery in various glomerular diseases, including diabetic nephropathy, IgA nephropathy, membranous nephropathy, focal segmental glomerulosclerosis, primary membranoproliferative glomerulonephritis, lupus nephritis, antiglomerular basement membrane disease, minimal change disease, and pediatric nephrotic syndrome. Recent findings from these studies are summarized and discussed. These data clearly underline the great promise of urinary proteomics in biomarker discovery for glomerular diseases.     

Proteomic analysis of serum, plasma, and lymph for the identification of biomarkers

Probably no topic has generated more excitement in the world of proteomics than the search for biomarkers. This excitement has been generated by two realities: the constant need for better biomarkers that can be used for disease diagnosis and prognosis, and the recent developments in proteomic technologies that are capable of scanning the individual proteins within varying complex clinical samples. Ideally a biomarker would be assayable from a noninvasively collected sample, therefore, much of the focus in proteomics has been on the analysis of biofluids such as serum, plasma, urine, cerebrospinal fluid, lymph, etc. While the discovery of biomarkers has been elusive, there have been many advances made in the understanding of the proteome content of various biofluids, and in the technologies used for their analysis, that continues to point the research community toward new methods for achieving the ultimate goal of identifying novel disease-specific biomarkers. In this review, we will describe and discuss many of the proteomic approaches taken in an attempt to find novel biomarkers in serum, plasma, and lymph.     

Urine proteomics for profiling of human disease using high accuracy mass spectrometry

Knowledge of the biologically relevant components of human tissues has enabled the invention of numerous clinically useful diagnostic tests, as well as non-invasive ways of monitoring disease and its response to treatment. Recent use of advanced MS-based proteomics revealed that the composition of human urine is more complex than anticipated. Here, we extend the current characterization of the human urinary proteome by extensively fractionating urine using ultra-centrifugation, gel electrophoresis, ion exchange and reverse-phase chromatography, effectively reducing mixture complexity while minimizing loss of material. By using high-accuracy mass measurements of the linear ion trap-Orbitrap mass spectrometer and LC-MS/MS of peptides generated from such extensively fractionated specimens, we identified 2362 proteins in routinely collected individual urine specimens, including more than 1000 proteins not described in previous studies. Many of these are biomedically significant molecules, including glomerularly filtered cytokines and shed cell surface molecules, as well as renally and urogenitally produced transporters and structural proteins. Annotation of the identified proteome reveals distinct patterns of enrichment, consistent with previously described specific physiologic mechanisms, including 336 proteins that appear to be expressed by a variety of distal organs and glomerularly filtered from serum. Comparison of the proteomes identified from 12 individual specimens revealed a subset of generally invariant proteins, as well as individually variable ones, suggesting that our approach may be used to study individual differences in age, physiologic state and clinical condition. Consistent with this, annotation of the identified proteome by using machine learning and text mining exposed possible associations with 27 common and more than 500 rare human diseases, establishing a widely useful resource for the study of human pathophysiology and biomarker discovery.     

Implementation of Proteomics Biomarkers in Nephrology: From Animal Models to Human Application?

Preclinical animal models are extensively used in nephrology. In this review, the utility of performing proteome analysis of kidney tissue or urine in such models and transfer of the results to human application has been assessed. Analysis of the literature identified 68 relevant publications. Pathway analysis of the reported proteins clearly indicated links with known biological processes in kidney disease providing validation of the observed changes in the preclinical models. However, although most studies focused on the identification of early markers of kidney disease or prediction of its progression, none of the identified makers has made it to substantial validation in the clinic or at least in human samples. Especially in renal disease where urine is an abundant source of biomarkers of diseases of the kidney and the urinary tract, it therefore appears that the focus should be on human material based discovery studies. In contrast, the most valid information of proteome analysis of preclinical models in nephrology for translation in human disease resides in studies focusing on drug evaluation, both efficacy for translation to the clinic and for mechanistic insight.     

Exosomes in bodily fluids are a highly stable resource of disease biomarkers

Biomarkers are measurable indicators of a biological state. As our understanding of diseases meliorates, it is generally accepted that early diagnosis renders the best chance to cure a disease. In the context of proteomics, the discovery phase of identifying bonafide biomarkers and the ensuing validation phase involving large cohort of patient samples are impeded by the complexity of bodily fluid samples. High abundant proteins found in blood plasma make it difficult for the detection of low abundant proteins that may be potential biomarkers. Extracellular vesicles (EVs) have reignited interest in the field of biomarker discovery. EVs contain a tissue-type signature wherein a rich cargo of proteins and RNA are selectively packaged. In addition, as EVs are membranous structures, the luminal contents are protected from degradation by extracellular proteases and are highly stable in storage conditions. Interestingly, an appealing feature of EV-based biomarker analysis is the significant reduction in the sample complexity compared to whole bodily fluids. With these prescribed attributes, which are the rate-limiting factors of traditional biomarker analysis, there is immense potential for the use of EVs for biomarker detection in clinical settings. This review will discuss the current issues with biomarker analysis and the potential use of EVs as reservoirs of disease biomarkers.     

Profiling of rat urinary proteomic patterns associated with drug-induced nephrotoxicity using CE coupled with MS as a potential model for detection of drug-induced adverse effects

We have investigated urine obtained from Sprague Dawley rats before and after administration of cis-Platin, aiming at the definition of biomarkers for drug-induced cytotoxicity. Rats were treated with 3 or 6 mg/kg cis-Platin (i.p., single injection) and urine samples were collected before and after drug or saline treatment. Analysis of the low molecular weight proteome (<20 kDa) using capillary-electrophoresis coupled mass spectrometry allowed us to tentatively identify 34 urinary peptides that show significant differences between control and treated animals, and hence may serve as a potential biomarker for cis-Platin-induced nephrotoxicity. These biomarkers were confirmed in a blinded assessment of additional samples. The blinded data also revealed time-dependency of induced changes. Some of the potential biomarkers could be sequenced. This information revealed great similarity between cis-Platin-induced changes and significant changes in the urinary proteome of patients suffering from tubular injury (Fanconi syndrome). Our study strongly suggests that (drug-induced) nephrotoxicity can be detected with high accuracy in laboratory rodents using urinary proteome analysis. The effects observed are very similar to those seen in corresponding human diseases and similar approaches may be very helpful in evaluating drug-induced organ damage in preclinical animal models. This study aiming at the definition of biomarkers for drug-induced cytotoxicity may serve as a proof-of-principle for the use of urinary proteomics in assessment of drug-induced nephrotoxicity.     

Proteomics in clinical prostate research

The incidence of early prostate cancer (PCa) has increased rapidly in recent years. The majority of newly diagnosed PCa are in early tumor phase. Presently, we do not have adequate biomarkers to assess tumor aggressiveness in individual cases. Consequently, too many patients are given curatively intended treatment. An exploration of the human proteome may provide clinically useful markers. 2-DE has been successfully used for analysis of the protein phenotype using clinical samples. Proteins are separated according to size and charge, gels are compared by image analysis, protein spots of interest are excised, and proteins identified by MS. This method is exploratory and allows protein identification. However, low-abundance proteins are difficult to detect and 2-DE is currently too labor-intensive for routine use. In recent years, nongel based techniques, such as LC-MS, SELDI-MS, and protein arrays have emerged. They require smaller sample sizes and can be more automated than 2-DE. In this review, we describe studies of the protein expression of benign prostatic tissue and PCa, which is likely to serve as the first step in prognostic biomarker discovery. The prostate proteome is still far from a complete mapping which would enhance our understanding of PCa biology.     

Large-scale protein identification of human urine proteome by multi-dimensional LC and MS/MS

Urine is a human specimen that is easily obtained non-invasively for clinical diagnosis. We attempted to enhance the resolution of current human urine proteomes and construct a comprehensive reference database for advanced studies, such as the discovery of biomarkers for renal diseases. Multi-dimensional LC-MS/MS was coupled with de novo sequencing and database matching. The proposed approach improved the identification of not only the proteins, but also the post-translational sites of urinary proteins. We identified 165, 200 and 259 unique gene products in the urine proteomes from males, females and pregnant women, respectively. When all of the results were combined and the redundancies removed, a total of 1095 distinct peptides were identified. Of these, 1016 peptides were associated with 334 unique gene products. In this study, over 100 gene products, including some disease-related proteins, were detected in urine for the first time by proteomic approaches. Various proteins with novel post-translational hydroxylation were identified using the MASCOT program and de novo sequencing. All proteins with peptide information were summarized into a comprehensive urine protein database. We believe that this comprehensive urine proteome database will assist in the identification of urinary proteins/polypeptides whose spectra are difficult to interpret in the discovery of urinary biomarkers.     

Dynamic urinary proteomic analysis reveals stable proteins to be potential biomarkers

Human urinary proteome analysis is a convenient and efficient approach for understanding disease processes affecting the kidney and urogenital tract. Many potential biomarkers have been identified in previous differential analyses; however, dynamic variations of the urinary proteome have not been intensively studied, and it is difficult to conclude that potential biomarkers are genuinely associated with disease rather then simply being physiological proteome variations. In this paper, pooled and individual urine samples were used to analyze dynamic variations in the urinary proteome. Five types of pooled samples (first morning void, second morning void, excessive water‐drinking void, random void, and 24 h void) collected in 1 day from six volunteers were used to analyze intra‐day variations. Six pairs of first morning voids collected a week apart were used to study inter‐day, inter‐individual, and inter‐gender variations. The intra‐day, inter‐day, inter‐individual, and inter‐gender variation analyses showed that many proteins were constantly present with relatively stable abundances, and some of these had earlier been reported as potential disease biomarkers. In terms of sensitivity, the main components of the five intra‐day urinary proteomes were similar, and the second morning void is recommended for clinical proteome analysis. The advantages and disadvantages of pooling samples are also discussed. The data presented describe a pool of stable urinary proteins seen under different physiological conditions. Any significant qualitative or quantitative changes in these stable proteins may mean that such proteins could serve as potential urinary biomarkers.     

Impact of allele-specific peptides in proteome quantification

MS-based proteome technologies have greatly improved our ability to detect and quantify proteomes across various biological samples. High throughput bottom-up proteome profiling in combination with targeted MS method, e.g. SRM assay, is emerging as a powerful approach in the field of biomarker discovery. In the past few years, increasing number of studies have attempted to integrate genomic and proteomic data for biomarker discovery. Here, we describe how allele-specific peptide can be applied in biomarker discovery and their impact in protein quantification.     

Non-invasive biomarker sampling and analysis of the exhaled breath proteome

Exhaled breath condensate (EBC) is a biological fluid that contains trace amounts of secreted pulmonary proteins, and is emerging as a potentially valuable and non-invasively obtained source of disease biomarkers. Proteome analysis of these samples could lead to the identification of prognostic indicators of airway diseases. The objective of this study was to develop a protocol for proteome analysis of EBC samples. In this report, an improved procedure for EBC sample preparation and concentration is presented, together with a method for comparison of the protein profiles between two groups. The presented approach enabled to study the condensed exhaled breath proteome for biomarker analysis, and revealed proteins not previously identified in an EBC proteomics approach. In a comparative pilot study, EBC protein profiles obtained from smokers and non-smokers showed distinct differences and are illustrative for its potential in clinical studies. EBC from smokers contained higher concentrations of the more abundant proteins, such as cytokeratins, compared to non-smokers, and calgranulin B was identified uniquely in EBC samples from smokers.     

Imaging mass spectrometry: Towards clinical diagnostics

Imaging MS (IMS) has emerged as a powerful tool for biomarker discovery. A key advantage of this technique is its ability to probe the proteome directly from a tissue section with preservation of the spatial relationships of the sample and minimal sample preparation. This allows for direct correlation of protein expression with histology. Here, we present the latest developments in imaging MS and their relevance to clinical mass spectral analysis. IMS allows for high throughput analysis of tissue samples and is fully compatible with biostatistical analysis without prior knowledge of protein expression. Several studies are presented of applications in which direct tissue mass spectral analysis has provided insight into clinical questions not readily available by other means. Examples include the determination of lymph node status from investigation of primary breast tumors, prediction of response of breast tumors to chemotherapy, classification and prediction of progression of lung lesions, and exploration of 'molecular' margins in invasive disease.     

Urinary proteomics in renal pathophysiology: Impact of proteinuria

Urinary differential proteomics is used to study renal pathophysiological mechanisms, find novel markers of biological processes and renal diseases, and stratify patients according to proteomic profiles. The proteomic procedure determines the pathophysiological meaning and clinical relevance of results. Urine samples for differential proteomic studies are usually normalized by protein content, regardless of its pathophysiological characteristics. In the field of nephrology, this approach translates into the comparison of a different fraction of the total daily urine output between proteinuric and nonproteinuric samples. Accordingly, alterations in the level of specific proteins found by this method reflect the relative presence of individual proteins in the urine; but they do not necessarily show alterations in their daily excretion, which is a key parameter for the understanding of the pathophysiological meaning of urinary components. For renal pathophysiology studies and clinical biomarker identification or determination, an alternative proteomic concept providing complementary information is based on sample normalization by daily urine output, which directly informs on changes in the daily excretion of individual proteins. This is clinically important because daily excretion (rather than absolute or relative concentration) is the only self-normalized way to evaluate the real meaning of urinary parameters, which is also independent of urine concentration.     

Profiling the proteome in renal transplantation

Improved monitoring of transplanted solid organs is one of the next crucial steps leading to an increase in both patient and allograft survival. This can be facilitated through one or a set of surrogate biomarker molecules that accurately and precisely indicate the health status of the transplanted organ. Recent developments in the field of high throughput "omic" methods including genomics and proteomics have facilitated robust and comprehensive analysis of genes and proteins. This development has stimulated efforts in the identification of effective and clinically applicable gene and protein biomarkers in solid organ transplantation, including kidney transplantation. Some achievements have been made through proteomics in terms of profiling proteins and identification of potential biomarkers. However, the road to a successful biomarker discovery and its clinical implementation has proved to be challenging, requiring a number of key issues to be addressed. Such issues are: the lack of widely accepted protocols, difficulty in sample processing and transportation and a lack of collaborative efforts to achieve significant sample sizes in clinical studies. In this review using our area of expertise, we describe the current strategies used for proteomic-based biomarker discovery in renal transplantation, discuss inherent issues associated with these efforts and propose better strategies for successful biomarker discovery.     

Proteome analysis of body fluids for amyotrophic lateral sclerosis biomarker discovery

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder of motor neurons leading to death of the patients, mostly within 2–5 years after disease onset. The pathomechanism of motor neuron degeneration is only partially understood and therapeutic strategies based on mechanistic insights are largely ineffective. The discovery of reliable biomarkers of disease diagnosis and progression is the sine qua non of both the revelation of insights into the ALS pathomechanism and the assessment of treatment efficacies. Proteomic approaches are an important pillar in ALS biomarker discovery. Cerebrospinal fluid is the most promising body fluid for differential proteome analyses, followed by blood (serum, plasma), and even urine and saliva. The present study provides an overview about reported peptide/protein biomarker candidates that showed significantly altered levels in certain body fluids of ALS patients. These findings have to be discussed according to proposed pathomechanisms to identify modifiers of disease progression and to pave the way for the development of potential therapeutic strategies. Furthermore, limitations and advantages of proteomic approaches for ALS biomarker discovery in different body fluids and reliable validation of biomarker candidates have been addressed.     

Human kidney glomerulus proteome and biomarker discovery of kidney diseases

The kidney glomerulus is the site of plasma filtration and production of primary urine in the kidney. The structure not only plays a pivotal role in ultrafiltration of plasma into urine but also is the locus of kidney diseases progressing to chronic renal failure. Patients afflicted with these glomerular diseases frequently progress to irreversible loss of renal function and inevitably require replacement therapies. The diagnosis and treatment of glomerular diseases are now based on clinical manifestations, urinary protein excretion level, and renal pathology of needle biopsy specimens. The molecular mechanisms underlying the progression of glomerular diseases are still obscure despite a great number of clinical and experimental studies. Proteomics is a particularly promising approach for the discovery of proteins relevant to physiological and pathophysiological processes, and has been recently employed in nephrology. Although until now most efforts of proteomic analysis have been conducted with urine, the biological fluid that is easily collected without invasive procedures, proteomic analysis of the glomerulus, the tissue most proximal to the disease loci, is the most straightforward approach. In this review, we attempt to outline the current status of clinical proteomics of the glomerulus and provide a perspective of protein biomarker discovery of glomerular diseases.     

Clinical applications of capillary electrophoresis coupled to mass spectrometry in biomarker discovery: Focus on bladder cancer

A major requirement in the application of proteins as clinical biomarkers is that they provide a highly sensitive and specific result in disease assessment. Since single biomarkers are generally of limited accuracy, a group or panel of well-characterized biomarkers appears appropriate, providing a more robust and sensitive MS-based analytical platform. CE coupled to MS has been successfully used in biomarker discovery and application, as it enables the selective detection of peptides and small proteins, combining the high separation capacity of CE with the advanced sensitivity of MS. CE-MS allows the characterization of highly complex samples (such as urine, plasma, and other biofluids) in a consistent and reproducible way. It has a range of applications, many focusing especially in studies on urinary peptide biomarkers in kidney and cardiovascular diseases. Another major field of interest has been malignancy of the genitourinary system. In the first part of this review, we cover technical aspects and performance characteristics of CE-MS, with special focus on the requirements for biomarker discovery and clinical application. In the second part, we review the potential and development of CE-MS in the management of genitourinary cancers, especially bladder cancer. CE-MS has been employed in several studies aimed at discovering biomarkers for bladder cancer that may be useful in diagnosis, monitoring for recurrence, and prediction of the risk for the muscle-invasive stage. In the last part of the review, we discuss current challenges and provide an outlook for ongoing and possible future developments.     

An evaluation of multidimensional fingerprinting in the context of clinical proteomics

Multidimensional fingerprinting (MDF) utilizes measurable peptide characteristics to identify proteins. In this study, 3‐D fingerprinting, namely, parent protein molecular weight, peptide mass, and peptide retention time on RPLC, is used to identify 331 differentially expressed proteins between normal and human colon cancer plasma membrane samples. A false discovery rate (FDR) procedure is introduced to evaluate the performance of MDF on the colon cancer dataset. This evaluation establishes a false protein identification rate below 15% for this dataset. Western blot analysis is performed to validate the differential expression of the MDF‐identified protein VDAC1 on the original tissue samples. The limits of MDF are further assessed by a simulation study where key parameters such as database size, query size, and mass accuracy are varied. The results of this simulation study demonstrate that fingerprinting with three dimensions yields low FDR values even for large queries on the complete human proteome without the need for prior peptide sequencing by tandem mass spectrometry. Specifically, when mass accuracy is 10 ppm or lower, full human proteome searches can achieve FDR values of 10% or less.