Analysis of human plasma proteins: a focus on sample collection and separation using free-flow electrophoresis

Due to ease of accessibility, plasma has become the sample of choice for proteomics studies directed towards biomarker discovery intended for use in diagnostics, prognostics and even in theranostics. The result of these extensive efforts is a long list of potential biomarkers, very few of which have led to clinical utility. Why have so many potential biomarkers failed validation? Herein, we address certain issues encountered, which complicate biomarker discovery efforts originating from plasma. The advantages of stabilizing the sample at collection by the addition of protease inhibitors are discussed. The principles of free-flow electrophoresis (FFE) separation are provided together with examples applying to various studies. Finally, particular attention is given to plasma or serum analysis using multidimensional separation strategies into which the FFE is incorporated. The advantages of using FFE separation in these workflows are discussed.     

Utilizing human blood plasma for proteomic biomarker discovery

Candidate proteomic biomarker discovery from human plasma holds both incredible clinical potential as well as significant challenges. The dynamic range of proteins within plasma is known to exceed 10(10), and many potential biomarkers are likely present at lower protein abundances. At present, proteomic based MS analyses provide a dynamic range typically not exceeding approximately 10(3) in a single spectrum, and approximately 10(4)-10(6) when combined with on-line separations (e.g., reversed-phase gradient liquid chromatography), and thus are generally insufficient for low level biomarker detection directly from human plasma. This limitation is providing an impetus for the development of experimental methodologies and strategies to increase the possible number of detections within this biofluid. Discussed is the diversity of available approaches currently used by our laboratory and others to utilize human plasma as a viable medium for biomarker discovery. Various separation, depletion, enrichment, and quantitative efforts as well as recent improvements in MS capabilities have resulted in measurable improvements in the detection and identification of lower abundance proteins (by approximately 10-10(2)). Despite these improvements, further advances are needed to provide a basis for discovery of candidate biomarkers at very low levels. Continued development of depletion and enrichment techniques, coupled with improved pre-MS separations (both at the protein and peptide level) holds promise in extending the dynamic range of proteomic analysis.     

Efficient prefractionation of low-abundance proteins in human plasma and construction of a two-dimensional map

Human plasma is the most clinically valuable specimen, containing not only a dynamic concentration range of protein components, but also several groups of high-abundance proteins that seriously interfere with the detection of low-abundance potential biomarker proteins. To establish a high-throughput method for efficient depletion of high-abundance proteins and subsequent fractionation, prior to molecular analysis of proteins, we explored how coupled immunoaffinity columns, commercially available as multiple affinity removal columns (MARC) and free flow electrophoresis (FFE), could apply to the HUPO plasma proteome project. Here we report identification of proteins and construction of a human plasma 2-DE map devoid of six major abundance proteins (albumin, transferrin, IgG, IgA, haptoglobin, and antitrypsin) using MARC. The proteins were identified by PMF, matching with various internal 2-DE maps, resulting in a total of 144 nonredundant proteins that were identified from 398 spots. Tissue plasminogen activator, usually present at 10-60 ng/mL plasma, was also identified, indicative of a potentially low-abundance biomarker. Comparison of representative 2-D gel images of three ethnic groups (Caucasian, Asian-American, African-American) plasma exhibited minor differences in certain proteins between races and sample pretreatment. To establish a throughput fractionation of plasma samples by FFE, either MARC flow-through fractions or untreated samples of Korean serum were subjected to FFE. After separation of samples on FFE, an aliquot of each fraction was analyzed by 1-D gel, in which MARC separation was a prerequisite for FFE work. Thus, a working scheme of MARC --> FFE --> 1-D PAGE --> 2-D-nanoLC-MS/MS may be considered as a widely applicable standard platform technology for fractionation of complex samples like plasma.     

Methodological advances in the discovery of protein and peptide disease markers

The quest for biomarkers has seen a renaissance due to the application of newly developed separation methodologies and advances in biomolecular mass spectrometry. It can be argued that each disease influences the physiology of an organism and that these changes should be measurable. Many diagnostic and therapeutic decisions are supported by measurable biochemical or cellular changes in plasma, serum or urine but it is unquestionable that there is a great lack in better markers for early disease detection and prevention. In this review we cover recent developments in the areas of separation science, sample preparation and mass spectrometry as applied to biomarker discovery. We focus, in particular, on the use of LC-MS and SELDI-TOF-MS as two approaches that have seen an upswing in recent years. While validation of newly discovered biomarkers or biomarker patterns and their introduction into diagnostic practice will be a long process, it is our believe that many future diagnostic tests will be based on markers discovered through novel profiling technologies as those outlined in this article.     

Towards proteome standards: The use of absolute quantitation in high-throughput biomarker discovery

The use of proteomics to profile biological fluids and identify therein biomarkers for cancer and other diseases was initially received with considerable excitement. However, results have fallen short of the expectations. Traditionally, protein biomarkers have been identified by measurement of relative expression changes between case and control samples from which differentially expressed proteins are then considered to represent biomarker candidates.We argue that current individual proteomics-based biomarker discovery studies lack the statistical strength for the identification of high-confidence biomarkers. Instead, multi-group efforts are necessary to facilitate the generation of sufficient sample sizes. This is contingent on the ability to collate and cross-compare data from different studies, which will require the use of a common metric or standards.Though profound, the technical challenges for absolute protein quantification can be overcome. The use of matrix specific, shared standards for absolute quantitation presents an opportunity to facilitate the much needed, but currently impossible, comparisons of different studies. In addition to community-wide approaches to standardize pre-analytical biomarker research studies, it is also important to establish means to integrate experimental data from different studies in order to assess the usefulness of proposed biomarkers with sufficient statistical certainty.     

Evaluation of a novel, integrated approach using functionalized magnetic beads, bench-top MALDI-TOF-MS with prestructured sample supports, and pattern recognition software for profiling potential biomarkers in human plasma.

The advantage of using proteins and peptides as biomarkers is that they can be found readily in blood, urine, and other biological fluids. Such sample types are easily obtained and represent a potentially rich palette of biologically informative molecules. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) represents a key tool for rapidly interrogating such sample types. The goal of clinical proteomics is to harness the power of this tool for identifying novel, condition-specific protein fingerprints that may, in turn, lead to the elucidation and use of diseasespecific biomarkers that may be used to diagnose disease as well as to evaluate disease severity, disease progression, and intervention efficacy. Here we have evaluated a simple, affordable bench-top MALDI-TOF mass spectrometer to generate protein profiles from human plasma samples of asthma patients and healthy individuals. We achieve this profiling by using C8-functionalized magnetic beads that enrich a specific subset of plasma proteins based on their absorption by this resin. This step is followed by elution, transfer onto a prestructured sample support (AnchorChip technology), and analysis in a bench-top MALDI-TOF mass spectrometer (OmniFLEX) with AutoXecute acquisition control which enables automated operation with reproducible results. Resulting spectra are compiled and analyzed through the pattern recognition component of ClinProTools software. This approach in combination with ClinProTools software permits the investigator to rapidly scan for potential biomarker peptides/proteins in human plasma. The reproducibility of plasma profiles within and between days has been evaluated. The results show that the novel and facile approach with manual magnetic-bead sample preparation and a low-cost bench-top MALDI-TOF mass spectrometer is suitable for preliminary biomarker discovery studies.     

A systematic analysis of eluted fraction of plasma post immunoaffinity depletion: implications in biomarker discovery

Plasma is the most easily accessible source for biomarker discovery in clinical proteomics. However, identifying potential biomarkers from plasma is a challenge given the large dynamic range of proteins. The potential biomarkers in plasma are generally present at very low abundance levels and hence identification of these low abundance proteins necessitates the depletion of highly abundant proteins. Sample pre-fractionation using immuno-depletion of high abundance proteins using multi-affinity removal system (MARS) has been a popular method to deplete multiple high abundance proteins. However, depletion of these abundant proteins can result in concomitant removal of low abundant proteins. Although there are some reports suggesting the removal of non-targeted proteins, the predominant view is that number of such proteins is small. In this study, we identified proteins that are removed along with the targeted high abundant proteins. Three plasma samples were depleted using each of the three MARS (Hu-6, Hu-14 and Proteoprep 20) cartridges. The affinity bound fractions were subjected to gelC-MS using an LTQ-Orbitrap instrument. Using four database search algorithms including MassWiz (developed in house), we selected the peptides identified at <1% FDR. Peptides identified by at least two algorithms were selected for protein identification. After this rigorous bioinformatics analysis, we identified 101 proteins with high confidence. Thus, we believe that for biomarker discovery and proper quantitation of proteins, it might be better to study both bound and depleted fractions from any MARS depleted plasma sample.     

Peptides and proteins in plasma and cerebrospinal fluid as biomarkers for the prediction, diagnosis, and monitoring of therapeutic efficacy of Alzheimer's disease

Alzheimer's disease (AD) affects millions of persons worldwide. Earlier detection and/or diagnosis of AD would permit earlier intervention, which conceivably could delay progression of this dementing disorder. In order to accomplish this goal, reliable and specific biomarkers are needed. Biomarkers are multidimensional and have the potential to aid in various facets of AD such as diagnostic prediction, assessment of disease stage, discrimination from normally cognitive controls as well as other forms of dementia, and therapeutic efficacy of AD drugs. To date, biomarker research has focused on plasma and cerebrospinal fluid (CSF), two bodily fluids believed to contain the richest source of biomarkers for AD. CSF is the fluid surrounding the central nervous system (CNS), and is the most indicative obtainable fluid of brain pathology. Blood plasma contains proteins that affect brain processes from the periphery, as well as proteins/peptides exported from the brain; this fluid would be ideal for biomarker discovery due to the ease and non-invasive process of sample collection. However, it seems reasonable that biomarker discovery will result in combinations of CSF, plasma, and other fluids such as urine, to serve the aforementioned purposes. This review focuses on proteins and peptides identified from CSF, plasma, and urine that may serve as biomarkers in AD.     

Proteomics in prostate cancer biomarker discovery

Despite advances in molecular medicine, genomics, proteomics and translational research, prostate cancer remains the second most common cause of cancer-related mortality for men in the Western world. Clearly, early detection, targeted treatment and post-treatment monitoring are vital tools to combat this disease. Tumor markers can be useful for diagnosis and early detection of cancer, assessment of prognosis, prediction of therapeutic effect and treatment monitoring. Such tumor markers include prostate-specific antigen (prostate), cancer antigen (CA)15.3 (breast), CA125 (ovarian), CA19.9 (gastrointestinal) and serum α-fetoprotein (testicular cancer). However, all of these biomarkers lack sensitivity and specificity and, therefore, there is a large drive towards proteomic biomarker discovery. Current research efforts are directed towards discovering biosignatures from biological samples using novel proteomic technologies that provide high-throughput, in-depth analysis and quantification of the proteome. Several of these studies have revealed promising biomarkers for use in diagnosis, assessment of prognosis, and targeting treatment of prostate cancer. This review focuses on prostate cancer proteomic biomarker discovery and its future potential.     

Proteomics and its applications for biomarker discovery in human saliva

Human saliva is a biological fluid with enormous diagnostic potential. Because saliva can be non-invasively collected, it provides an attractive alternative for blood, serum or plasma. It has been postulated that the blood concentrations of many components are reflected in saliva. Saliva harbors a wide array of proteins, which can be informative for the detection of diseases. Profiling the proteins in saliva over the course of disease progression could reveal potential biomarkers indicative of different stages of diseases, which may be useful in medical diagnostics. With advanced instrumentation and developed refined analytical techniques, proteomics is widely envisioned as a useful and powerful approach for salivary proteomic biomarker discovery. As proteomic technologies continue to mature, salivary proteomics have great potential for biomarker research and clinical applications. The progress and current status of salivary proteomics and its application in the biomarker discovery of oral and systematic diseases will be reviewed. The scientific and clinical challenges underlying this approach will also be discussed.     

Proteomics and its applications for biomarker discovery in human saliva

Human saliva is a biological fluid with enormous diagnostic potential. Because saliva can be non-invasively collected, it provides an attractive alternative for blood, serum or plasma. It has been postulated that the blood concentrations of many components are reflected in saliva. Saliva harbors a wide array of proteins, which can be informative for the detection of diseases. Profiling the proteins in saliva over the course of disease progression could reveal potential biomarkers indicative of different stages of diseases, which may be useful in medical diagnostics. With advanced instrumentation and developed refined analytical techniques, proteomics is widely envisioned as a useful and powerful approach for salivary proteomic biomarker discovery. As proteomic technologies continue to mature, salivary proteomics have great potential for biomarker research and clinical applications. The progress and current status of salivary proteomics and its application in the biomarker discovery of oral and systematic diseases will be reviewed. The scientific and clinical challenges underlying this approach will also be discussed.     

Biomarkers for the lung cancer diagnosis and their advances in proteomics

Over a last decade, intense interest has been focused on biomarker discovery and their clinical uses. This interest is accelerated by the completion of human genome project and the progress of techniques in proteomics. Especially, cancer biomarker discovery is eminent in this field due to its anticipated critical role in early diagnosis, therapy guidance, and prognosis monitoring of cancers. Among cancers, lung cancer, one of the top three major cancers, is the one showing the highest mortality because of failure in early diagnosis. Numerous potential DNA biomarkers such as hypermethylations of the promoters and mutations in K-ras, p53, and protein biomarkers; carcinoembryonic antigen (CEA), CYFRA21-1, plasma kallikrein B1 (KLKB1), Neuron-specific enolase, etc. have been discovered as lung cancer biomarkers. Despite extensive studies thus far, few are turned out to be useful in clinic. Even those used in clinic do not show enough sensitivity, specificity and reproducibility for general use. This review describes what the cancer biomarkers are for, various types of lung cancer biomarkers discovered at present and predicted future advance in lung cancer biomarker discovery with proteomics technology.     

Advances in proximal fluid proteomics for disease biomarker discovery

Although serum/plasma has been the preferred source for identification of disease biomarkers, these efforts have been met with little success, in large part due the relatively small number of highly abundant proteins that render the reliable detection of low abundant disease-related proteins challenging due to the expansive dynamic range of concentration of proteins in this sample. Proximal fluid, the fluid derived from the extracellular milieu of tissues, contains a large repertoire of shed and secreted proteins that are likely to be present at higher concentrations relative to plasma/serum. It is hypothesized that many, if not all, proximal fluid proteins exchange with peripheral circulation, which has provided significant motivation for utilizing proximal fluids as a primary sample source for protein biomarker discovery. The present review highlights recent advances in proximal fluid proteomics, including the various protocols utilized to harvest proximal fluids along with detailing the results from mass spectrometry- and antibody-based analyses.     

Computational Biomarker Pipeline from Discovery to Clinical Implementation: Plasma Proteomic Biomarkers for Cardiac Transplantation

Recent technical advances in the field of quantitative proteomics have stimulated a large number of biomarker discovery studies of various diseases, providing avenues for new treatments and diagnostics. However, inherent challenges have limited the successful translation of candidate biomarkers into clinical use, thus highlighting the need for a robust analytical methodology to transition from biomarker discovery to clinical implementation. We have developed an end-to-end computational proteomic pipeline for biomarkers studies. At the discovery stage, the pipeline emphasizes different aspects of experimental design, appropriate statistical methodologies, and quality assessment of results. At the validation stage, the pipeline focuses on the migration of the results to a platform appropriate for external validation, and the development of a classifier score based on corroborated protein biomarkers. At the last stage towards clinical implementation, the main aims are to develop and validate an assay suitable for clinical deployment, and to calibrate the biomarker classifier using the developed assay. The proposed pipeline was applied to a biomarker study in cardiac transplantation aimed at developing a minimally invasive clinical test to monitor acute rejection. Starting with an untargeted screening of the human plasma proteome, five candidate biomarker proteins were identified. Rejection-regulated proteins reflect cellular and humoral immune responses, acute phase inflammatory pathways, and lipid metabolism biological processes. A multiplex multiple reaction monitoring mass-spectrometry (MRM-MS) assay was developed for the five candidate biomarkers and validated by enzyme-linked immune-sorbent (ELISA) and immunonephelometric assays (INA). A classifier score based on corroborated proteins demonstrated that the developed MRM-MS assay provides an appropriate methodology for an external validation, which is still in progress. Plasma proteomic biomarkers of acute cardiac rejection may offer a relevant post-transplant monitoring tool to effectively guide clinical care. The proposed computational pipeline is highly applicable to a wide range of biomarker proteomic studies.     

Clinical application of urinary proteomics/peptidomics

The technology platforms for proteome analysis have advanced considerably over the last few years. Driven by these advancements in technology, the number of studies on the analysis of the proteome/peptidome, with the aim of defining clinically relevant biomarkers, has substantially risen. Urine has become an increasingly relevant target for clinically oriented proteome analysis; the first clinical trials based on urinary proteomics have been initiated, and studies including several hundred patients have been published. In this article, we summarize the relevant technical aspects in biomarkers discovery and the course from biomarker discovery or ‘potential’ biomarkers to those that have been validated and are clinically important. We discuss experimental design based on the statistics calculated to produce a clinically important end point. We present several examples of proteomic studies that have defined urinary biomarkers for clinical applications, focusing on capillary electrophoresis coupled to mass spectrometry as a technology. Finally, current challenges and considerations for future studies will be discussed.     

Shotgun proteomics of human bile in hilar cholangiocarcinoma

The need to find biomarkers for hepatobiliary diseases including cholangiocarcinoma (CCA) has led to an interest in using bile as a proximal fluid in biomarker discovery experiments, although there are inherent challenges both in its acquisition and analysis. The study described here greatly extends previous studies that have started to characterise the bile proteome. Bile from four patients with hilar CCA was depleted of albumin and immunoglobulin G and analysed by GeLC-MS/MS. The number of proteins identified per bile sample was between 378 and 741. Overall, the products of 813 unique genes were identified, considerably extending current knowledge of the malignant bile proteome. Of these, 268 were present in at least 3 out of 4 patients. This data set represents the largest catalogue of bile proteins to date and together with other studies in the literature constitutes an important prelude to the potential promise of expression proteomics and subsequent validation studies in CCA biomarker discovery.     

4th International Peptide Symposium in conjunction with the 7th Australian Peptide Symposium and the 2nd Asia–Pacific International Peptide Symposium

The identification and clinical use of more sensitive and specific biomarkers in the field of solid organ transplantation is an urgent need in medicine. Solid organ transplantation has seen improvements in the short-term survival of transplanted organs due to recent advancements in immunosuppressive therapy. However, the currently available methods of allograft monitoring are not optimal. Recent advancements in assaying methods for biomolecules such as genes, mRNA and proteins have helped to identify surrogate biomarkers that can be used to monitor the transplanted organ. These high-throughput ‘omic’ methods can help researchers to significantly speed up the identification and the validation steps, which are crucial factors for biomarker discovery efforts. Still, the progress towards identifying more sensitive and specific biomarkers remains a great deal slower than expected. In this article, we have evaluated the current status of biomarker discovery using proteomics tools in different solid organ transplants in recent years. This article summarizes recent reports and current status, along with the hurdles in efficient biomarker discovery of protein biomarkers using proteomics approaches. Finally, we will touch upon personalized medicine as a future direction for better management of transplanted organs, and provide what we think could be a recipe for success in this field.     

Quantitative profiling of serum samples using TMT protein labelling, fractionation and LC-MS/MS

Blood-borne biomarkers are urgently required for the early detection, accurate diagnosis and prognosis of disease. Additionally, improved methods of profiling serum and plasma proteins for biomarker discovery efforts are needed. Herein, we report a quantitative method based on amino-group labelling of serum proteins (rather than peptides) with isobaric tandem mass tags (TMT) and incorporating immune-based depletion, gel-based and strong anion exchange separation of proteins prior to differential endoproteinase treatment and liquid chromatography tandem mass spectrometry. We report a generally higher level of quantitative coverage of the serum proteome compared to other peptide-based isobaric tagging approaches and show the potential of the method by applying it to a set of unique samples that pre-date the diagnosis of pancreatic cancer.     

Recent advances in biomarker discovery in solid organ transplant by proteomics

The identification and clinical use of more sensitive and specific biomarkers in the field of solid organ transplantation is an urgent need in medicine. Solid organ transplantation has seen improvements in the short-term survival of transplanted organs due to recent advancements in immunosuppressive therapy. However, the currently available methods of allograft monitoring are not optimal. Recent advancements in assaying methods for biomolecules such as genes, mRNA and proteins have helped to identify surrogate biomarkers that can be used to monitor the transplanted organ. These high-throughput 'omic' methods can help researchers to significantly speed up the identification and the validation steps, which are crucial factors for biomarker discovery efforts. Still, the progress towards identifying more sensitive and specific biomarkers remains a great deal slower than expected. In this article, we have evaluated the current status of biomarker discovery using proteomics tools in different solid organ transplants in recent years. This article summarizes recent reports and current status, along with the hurdles in efficient biomarker discovery of protein biomarkers using proteomics approaches. Finally, we will touch upon personalized medicine as a future direction for better management of transplanted organs, and provide what we think could be a recipe for success in this field.