Discovery of diagnostic serum biomarkers of gastric cancer using proteomics

Gastric cancer has significant morbidity and mortality worldwide and locally. Good prognosis relies on an early diagnosis. However, this remains a challenge due to the lack of specific and sensitive serum biomarkers for early detection. Hence, there is a constant search for these biomarkers for screening purposes. Proteomic profiling enables a new approach to the discovery of biomarkers in disease. This review presents recent attempts in search of gastric cancer serum biomarker using proteomics. Different methodologies and different types of samples were employed by different groups of researchers. Major difficulties were encountered in the discovery processes, including interference from abundant proteins and continuous changing serum proteomes from different individuals.     

A qualitative proteome investigation of the sediment portion of human urine: Implications in the biomarker discovery process

Inherent to the biomarker discovery process is a comparative analysis of physiological states. It is therefore critical that the proteome detection protocol does not bias the analysis. With urine, the sediment portion, obtained upon thawing frozen urine, is routinely discarded prior to proteome analysis. However, our results demonstrate that such a practice inadvertently induces bias, having significant implications in the biomarker discovery process. We present the first proteome investigation of human urinary sediments, identifying 60 proteins in this phase by MS. Many sediment proteins were also detected in the urinary supernatant, indicating that several proteins partition between the two phases. This partitioning is dependant on the pH of the sample, as well as the degree of sample agitation. As a consequence of discarding the sediment portion of urine, the concentration of potential candidate biomarkers in the supernatant phase will be altered or, in other instances, may be completely removed from the sample. To minimize this, the pH of all samples should first be normalized, and the samples vigorously vortexed prior to discarding the sediments. For more comprehensive biomarker investigations, we suggest that urinary sediments be analyzed along with the supernatant proteins.     

Differential expression of serum/plasma proteins in various infectious diseases: Specific or nonspecific signatures

Apart from direct detection of the infecting organisms or biomarker of the pathogen itself, surrogate host markers are also useful for sensitive and early diagnosis of pathogenic infections. Early detection of pathogenic infections, discrimination among closely related diseases with overlapping clinical manifestations, and monitoring of disease progression can be achieved by analyzing blood biomarkers. Therefore, over the last decade large numbers of proteomics studies have been conducted to identify differentially expressed human serum/plasma proteins in different infectious diseases with the intent of discovering novel potential diagnostic/prognostic biomarkers. However, in-depth review of the literature indicates that many reported biomarkers are altered in the same way in multiple infectious diseases, regardless of the type of infection. This might be a consequence of generic acute phase reactions, while the uniquely modulated candidates in different pathogenic infections could be indicators of some specific responses. In this review article, we will provide a comprehensive analysis of differentially expressed serum/plasma proteins in various infectious diseases and categorize the protein markers associated with generic or specific responses. The challenges associated with the discovery, validation, and translational phases of serum/plasma biomarker establishment are also discussed.     

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.     

Microfluidic platforms for discovery and detection of molecular biomarkers

Microfluidics has emerged as a promising platform for discovery and detection of molecular biomarkers recently. With this approach, the discovery of these biomarkers could be more efficient in time and consumes less samples and reagents. Furthermore, the entire discovery process could be automated since all the functional microfluidic devices such as micropumps and microvalves could be integrated on a single chip. Similarly, the detection of the discovered molecular biomarkers is also promising. Detection of nucleic acid biomarkers, protein biomarkers, and metabolite biomarkers has been demonstrated on microfluidic platforms recently. When compared with their large-scale counterparts, the miniature system can perform the detection of these biomarkers within less analysis time while a multiplexed detection scheme could be easily achieved. Furthermore, the entire detection process could be automated on the single chip as well. This review paper is therefore to review the recent development of microfluidic devices and systems for the discovery and detection of the molecular biomarker. Techniques for biomarker discovery, verification, and detection that have been adapted into microfluidics were first reviewed, and their advantages were highlighted. The new approach of biomarker screening based on in vitro-generated affinity reagents such as nucleic acid aptamers and peptide affinity reagents was then reviewed. Finally, in the biomarker detection section, this review placed a special emphasis on commercialized microfluidic-based diagnostics for molecular biomarkers.     

Quantification of Biomarker Proteins Using Reverse‐Phase Protein Arrays

It is expected that antibody‐based proteomics will soon occupy a pivotal position in the discovery and validation of biomarkers and therapeutic targets. The reverse‐phase protein array (RPPA) is an antibody‐based proteomic method that can quantify the expression of multiple posttranslationally modified proteins (such as those that have been phosphorylated) across a large number of protein samples. RPPA is highly sensitive and requires only very small protein samples. This feature, in combination with large antibody libraries, makes RPPA ideal for clinical proteomics, as well as the fact that it is an expandable multiplex assay. In Volume 14, Issue 1 of Proteomics Clinical Applications, Suzuki and colleagues report for the first time a study comparing RPPA and immunohistochemistry for quantification of seven biomarker proteins used for subtyping of diffuse large B‐cell lymphoma. Such combination of multiple biomarkers is likely to increase diagnostic accuracy and can be used for precise classification of this heterogeneous disease.     

Discovering cancer biomarkers from clinical samples by protein microarrays

Cancer biomarkers are of potential use in early cancer diagnosis, anticancer therapy development, and monitoring the responses to treatments. Protein-based cancer biomarkers are major forms in use, as they are much easier to be monitored in body fluids or tissues. For cancer biomarker discovery, high-throughput techniques such as protein microarrays hold great promises, because they are capable of global unbiased monitoring but with a miniaturized format. In doing so, novel and cancer type specific biomarkers can be systematically discovered at an affordable cost. In this review, we give a relatively complete picture on protein microarrays applied to clinical samples for cancer biomarker discovery, and conclude this review with the future perspectives.     

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.     

Proteomics of plaques and novel sources of potential biomarkers for atherosclerosis

Cardiovascular disease (CVD) is the leading cause of death and loss of productive life years in the world. The underlying syndrome of CVD, atherosclerosis, is a complex disease process, which involves lipid metabolism, inflammation, innate and adaptive immunity, and many other pathophysiological aspects. Furthermore, CVD is influenced by genetic as well as environmental factors. Early detection of CVD and identification of patients at risk are crucial to reduce the burden of disease and to allow personalized treatment. As established risk factors fail to accurately predict which part of the population is likely to suffer from the disease, novel biomarkers are urgently needed. Proteomics can play a significant role in identifying these biomarkers. In this review, we describe the progress made in proteome profiling of the atherosclerotic plaque and several novel sources of potential biomarkers, including circulating cells and plasma extracellular vesicles. The importance of longitudinal biobanking in biomarker discovery is highlighted and exemplified by several plaque proteins identified in the biobank study Athero-Express. Finally, we discuss the PTMs of proteins that are involved in atherosclerosis, which may become one of the foci in the ongoing quest for biomarkers through proteomics of plaque and other matrices relevant to the progression of atherosclerosis.     

Quantitative proteomic approaches for biomarker discovery

The rapid advances in proteomic technologies have made possible systematic analysis of hundreds to thousands of proteins in clinical samples with the promise of uncovering novel protein biomarkers for various disease conditions. We will discuss in this review article current MS and protein chip-based quantitative proteomic approaches and their application in biomarker discovery. The emphasis will be placed on new quantification strategies employing stable isotopic labeling coupled with MS/MS, and antibody-based protein chips and nanodevices. The strength and weakness of each technology are briefly highlighted.     

Body fluid proteomics: Prospects for biomarker discovery

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

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.     

Cardiovascular proteomics: translational studies to develop novel biomarkers in heart failure and left ventricular remodeling

Heart failure (HF) remains a severe disease with a poor prognosis. HF biomarkers may include demographic features, cardiac imaging, or genetic polymorphisms but this term is commonly applied to circulating serum or plasma analytes. Biomarkers may have at least three clinical uses in the context of HF: diagnosis, risk stratification, and guidance in the selection of therapy. Proteomic studies on HF biomarkers can be designed as case/control using clinical endpoints; alternatively, left ventricular remodeling can be used as a surrogate endpoint. The type of samples (tissue, cells, serum or plasma) used for proteomic analysis is a key factor in the research of biomarkers. Since the final aim is the discovery of circulating biomarkers, and since plasma and serum samples are easily accessible, proteomic analysis is frequently used for blood samples. However, standardization of sampling and access to low-abundance proteins remains problematic. Although, proteomics is playing a major role in the discovery phase of biomarkers, validation in independent populations is necessary by using more specific methods. The knowledge of new HF biomarkers may allow a more personalized medicine in the future.     

Multiplex assays for biomarker research and clinical application: translational science coming of age

Over the last decade, translational science has come into the focus of academic medicine, and significant intellectual and financial efforts have been made to initiate a multitude of bench-to-bedside projects. The quest for suitable biomarkers that will significantly change clinical practice has become one of the biggest challenges in translational medicine. Quantitative measurement of proteins is a critical step in biomarker discovery. Assessing a large number of potential protein biomarkers in a statistically significant number of samples and controls still constitutes a major technical hurdle. Multiplexed analysis offers significant advantages regarding time, reagent cost, sample requirements and the amount of data that can be generated. The two contemporary approaches in multiplexed and quantitative biomarker validation, antibody-based immunoassays and MS-based multiple (or selected) reaction monitoring, are based on different assay principles and instrument requirements. Both approaches have their own advantages and disadvantages and therefore have complementary roles in the multi-staged biomarker verification and validation process. In this review, we discuss quantitative immunoassay and multiple reaction monitoring/selected reaction monitoring assay principles and development. We also discuss choosing an appropriate platform, judging the performance of assays, obtaining reliable, quantitative results for translational research and clinical applications in the biomarker field.     

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.     

Implementation of Proteomics in Clinical Trials

The application of protein (or peptide) biomarkers in clinical studies is a dynamic, ever‐growing field. The introduction of clinical proteomics/peptidomics, such as mass spectrometry–based assays and multiplexed antibody–based protein arrays, has reshaped the landscape of biomarker identification and validation, allowing the discovery of novel biomarkers at an unprecedented rate and reliability. To reflect the current status with respect to implementation of protein/peptide biomarkers, an investigation of the most recent (last 6 years) clinical studies from clinicaltrials.gov is presented. Forty‐two clinical trials involving the direct use of protein or peptide biomarkers in patient stratification and/or disease diagnosis and prognosis are highlighted. Most of the clinical trials that include proteomics/protein assays are aiming toward implementation of non‐invasive diagnostic tools for early detection, while many of the clinical trials are targeting to correlate the protein abundance with the risk of a disease event. Less in number are the studies in which the protein biomarkers are applied to stratify the patients for intervention. All the above areas of application are considered of great importance for improving disease management, in an era where implementation toward precision medicine is the desired outcome of proteomics biomarker research.     

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.     

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.     

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.