Evaluation of multiprotein immunoaffinity subtraction for plasma proteomics and candidate biomarker discovery using mass spectrometry

Proteomic Discovery and Validation of Novel Fluid Biomarkers for Improved Patient Selection and Prediction of Clinical Outcomes in Alzheimer’s Disease Patient Cohorts

Alzheimer’s disease (AD) is an irreversible neurodegenerative disease characterized by progressive cognitive decline. The two cardinal neuropathological hallmarks of AD include the buildup of cerebral β amyloid (Aβ) plaques and neurofibrillary tangles of hyperphosphorylated tau. The current disease-modifying treatments are still not effective enough to lower the rate of cognitive decline. There is an urgent need to identify early detection and disease progression biomarkers that can facilitate AD drug development. The current established readouts based on the expression levels of amyloid beta, tau, and phospho-tau have shown many discrepancies in patient samples when linked to disease progression. There is an urgent need to identify diagnostic and disease progression biomarkers from blood, cerebrospinal fluid (CSF), or other biofluids that can facilitate the early detection of the disease and provide pharmacodynamic readouts for new drugs being tested in clinical trials. Advances in proteomic approaches using state-of-the-art mass spectrometry are now being increasingly applied to study AD disease mechanisms and identify drug targets and novel disease biomarkers. In this report, we describe the application of quantitative proteomic approaches for understanding AD pathophysiology, summarize the current knowledge gained from proteomic investigations of AD, and discuss the development and validation of new predictive and diagnostic disease biomarkers.

Proteomic study of mesothelial and endothelial cross-talk: key lessons

INTRODUCTION

The peritoneum, pleura, and pericardium are yet understudied multicellular systems where mesothelial cells (MCs) and endothelial cells (ECs) are in close proximity. Crosstalk between these cell types likely plays role in molecular transport, immunological reactions, and metabolic processes in health, disease, and therapeutic intervention.

AREAS COVERED

In this review, we discuss recent proteomic efforts to characterize the crosstalk between MC and EC. We describe the proteomic methods necessary for investigation of crosstalk between MC and EC, as well as the in-vitro models that can be employed. Potential experimental approaches range from conditioned medium, via co-culture on semi-permeable membranes, to 3D cell culture based organoid models. While the biological and clinical relevance of the models may increase with their ability to mimic close cell communication, the practicality of these complex experiments corresponds vice versa, making standardization more difficult and expensive.

EXPERT OPINION

Currently, data and reports on mesothelial-to-endothelial crosstalk are still very scarce. In our opinion, the in-vitro model using semi-permeable cell culture inserts will allow to establish a basic understanding of cellular crosstalk that may occur between those cell types. Later-on, more sophisticated 3D cell cultures may be better able to simulate the transport dynamics within the peritoneal membrane.

Exploratory study reveals far reaching systemic and cellular effects of verapamil treatment in subjects with type 1 diabetes

Currently, no oral medications are available for type 1 diabetes (T1D). While our recent randomized placebo-controlled T1D trial revealed that oral verapamil had short-term beneficial effects, their duration and underlying mechanisms remained elusive. Now, our global T1D serum proteomics analysis identified chromogranin A (CHGA), a T1D-autoantigen, as the top protein altered by verapamil and as a potential therapeutic marker and revealed that verapamil normalizes serum CHGA levels and reverses T1D-induced elevations in circulating proinflammatory T-follicular-helper cell markers. RNA-sequencing further confirmed that verapamil regulates the thioredoxin system and promotes an anti-oxidative, anti-apoptotic and immunomodulatory gene expression profile in human islets. Moreover, continuous use of oral verapamil delayed T1D progression, promoted endogenous beta-cell function and lowered insulin requirements and serum CHGA levels for at least 2 years and these benefits were lost upon discontinuation. Thus, the current studies provide crucial mechanistic and clinical insight into the beneficial effects of verapamil in T1D.

Antibody-Based Affinity Capture Combined with LC-MS Analysis for Identification of COVID-19 Disease Serum Biomarkers

Blood serum or plasma proteins are potentially useful in COVID-19 research as biomarkers for risk prediction, diagnosis, stratification, and treatment monitoring. However, serum protein-based biomarker identification and validation is complicated due to the wide concentration range of these proteins, which spans more than ten orders of magnitude. Here we present a combined affinity purification-liquid chromatography mass spectrometry approach which allows identification and quantitation of the most abundant serum proteins along with the nonspecifically bound and interaction proteins. This led to the reproducible identification of more than 100 proteins that were not specifically targeted by the affinity column. Many of these have already been implicated in COVID-19 disease.

Tutorial: best practices and considerations for mass-spectrometry-based protein biomarker discovery and validation

Mass-spectrometry-based proteomic analysis is a powerful approach for discovering new disease biomarkers. However, certain critical steps of study design such as cohort selection, evaluation of statistical power, sample blinding and randomization, and sample/data quality control are often neglected or underappreciated during experimental design and execution. This tutorial discusses important steps for designing and implementing a liquid-chromatography-mass-spectrometry-based biomarker discovery study. We describe the rationale, considerations and possible failures in each step of such studies, including experimental design, sample collection and processing, and data collection. We also provide guidance for major steps of data processing and final statistical analysis for meaningful biological interpretations along with highlights of several successful biomarker studies. The provided guidelines from study design to implementation to data interpretation serve as a reference for improving rigor and reproducibility of biomarker development studies.

Proteomic Interrogation in Cancer Biomarker

Biomarkers factor into the diagnosis and treatment of almost every patient with cancer. The innovation in proteomics follows improvement of mass spectrometry techniques and data processing strategy. Recently, proteomics and typical biological studies have been the answer for clinical applications. The clinical proteomics techniques are now actively adapted to protein identification in large patient cohort, biomarker development for more sensitive and specific screening based on quantitative data. And, it is important for clinical, translational researchers to be acutely aware of the issues surrounding appropriate biomarker development, in order to facilitate entry of clinically useful biomarkers into the clinic. Here, we discuss in detail include the case research for clinical proteomics. Furthermore, we give an overview on the current developments and novel findings in proteomics-based cancer biomarker research.

High-throughput, in-depth and estimated absolute quantification of plasma proteome using data-independent acquisition/mass spectrometry ("HIAP-DIA")

Mass spectrometry-based plasma proteomics has been demonstrated to be a useful tool capable of quantifying hundreds of proteins in a single LC-MS/MS experiment, for biomarker discovery or elucidation of disease mechanisms. We developed a novel data-independent acquisition (DIA)/MS-based workflow for high-throughput, in-depth and estimated absolute quantification of plasma proteins (termed HIAP-DIA), without depleting high-abundant proteins, in a single-shot experiment. In HIAP-DIA workflow, we generated an ultra-deep cumulative undepleted and depleted spectral library which contained 55,157 peptides and 5,328 proteins, optimized column length (50 cm) and gradient (90 min) of liquid chromatography instrumentation, optimized 50 DIA segments with average isolation window 17 Th, and selected reference proteins for estimated absolute quantification of all plasma proteins. A total of 606 proteins were quantified in triplicate, and 427 proteins were quantified with CV <20% in plasma proteome. R-squared value of overlapped 208 endogenous PQ500 estimated protein amounts from HIAP-DIA and absolute quantification with internal standards was 0.82, indicating high quantification accuracy of HIAP-DIA. As a pilot study, the HIAP-DIA approach described here was applied to a myelodysplastic syndromes (MDS) disease cohort. We achieved absolute quantification of 789 plasma proteins in 22 clinical plasma samples, spanning less than six orders of magnitude with quantification limit 10-20 ng/mL, and discovered 95 differentially expressed proteins providing insights into MDS pathophysiology.

Development of a Clinical MALDI-ToF Mass Spectrometry Assay for SARS-CoV-2: Rational Design and Multi-Disciplinary Team Work

The COVID-19 pandemic caused by the SARS-CoV-2 coronavirus has stretched national testing capacities to breaking points in almost all countries of the world. The need to rapidly screen vast numbers of a country's population in order to control the spread of the infection is paramount. However, the logistical requirement for reagent supply (and associated cost) of RT-PCR based testing (the current front-line test) have been hugely problematic. Mass spectrometry-based methods using swab and gargle samples have been reported with promise, but have not approached the task from a systematic analysis of the entire diagnostic process. Here, the pipeline from sample processing, the biological characteristics of the pathogen in human biofluid, the downstream bio- and physical-chemistry and the all-important data processing with clinical interpretation and reporting, are carefully compiled into a single high-throughput and reproducible rapid process. Utilizing MALDI-ToF mass spectrometric detection to viral envelope glycoproteins in a systems biology-multidisciplinary team approach, we have achieved a multifaceted clinical MALDI ToF MS screening test, primarily (but not limited to) SARS-CoV-2, with direct application to other future epidemics/pandemics that may arise. The clinical information generated not only includes SARS-CoV-2 coronavirus detection-(Spike protein fragments S1, S2b, S2a peaks), but other respiratory viral infections detected as well as an assessment of generalised oral upper respiratory immune response (elevated total Ig light chain peak) and a measure of the viral immune response (elevated intensity of IgA heavy chain peak). The advantages of the method include; (1) ease of sampling, (2) speed of analysis, and much reduced cost of testing. These features reveal the diagnostic utility of MALDI-ToF mass spectrometry as a powerful and economically attractive global solution.

Longitudinal proteomics analysis in the immediate microenvironment of islet allografts during progression of rejection

The applicability and benefits of pancreatic islet transplantation are limited due to various issues including the need to avoid immune-mediated rejection. Here, we used our experimental platform of allogeneic islet transplant in the anterior chamber of the eye (ACE-platform) to longitudinally monitor the progress of rejection in mice and obtain aqueous humor samples representative of the microenvironment of the graft for accurately-timed proteomic analyses. LC-MS/MS-based proteomics performed on such mass-limited samples (~5 μL) identified a total of 1296 proteins. Various analyses revealed distinct protein patterns associated with the mounting of the inflammatory and immune responses and their evolution with the progression of the rejection. Pathway analyses indicated predominant changes in cytotoxic functions, cell movement, and innate and adaptive immune responses. Network prediction analyses revealed transition from humoral to cellular immune response and exacerbation of pro-inflammatory signaling. One of the proteins identified by this localized proteomics as a candidate biomarker of islet rejection, Cystatin 3, was further validated by ELISA in the aqueous humor. This study provides (1) experimental evidence demonstrating the feasibility of longitudinal localized proteomics using small aqueous humor samples and (2) proof-of-concept for the discovery of biomarkers of impending immune attack from the immediate local microenvironment of ACE-transplanted islets. SIGNIFICANCE: The combination of the ACE-platform and longitudinal localized proteomics offers a powerful approach to biomarker discovery during the various stages of immune reactions mounted against transplanted tissues including pancreatic islets. It also supports proteomics-assisted drug discovery and development efforts aimed at preventing rejection through efficacy assessment of new agents by noninvasive and longitudinal graft monitoring.

A preliminary investigation of circulating extracellular vesicles and biomarker discovery associated with treatment response in head and neck squamous cell carcinoma

BACKGROUND

There is a paucity of plasma-based biomarkers that prospectively segregate the outcome of patients with head and neck squamous-cell carcinoma (HNSCC) treated with chemoradiation therapy (CRT). Plasma extracellular vesicles (EVs) might be an alternative source for discovery of new specific markers present in patients with HNSCC, which could help to re-direct patients to appropriate curative therapies without delay.

METHODS

In order to identify new markers in plasma compartments, Cholerae toxin B chain (CTB) and Annexin V (AV) were used to isolate EVs from pooled plasma samples from patients with locally advanced HNSCC who responded (CR, n = 6) or presented incomplete response (NR, n = 6) to CRT. The crude plasma and EVs cargo were screened by antibody array.

RESULTS

Of the 370 polypeptides detected, 119 proteins were specific to NR patients while 38 were exclusive of the CR subjects. The Gene Set Enrichment Analysis (GSEA) and Search Tool for the Retrieval of Interacting Genes (STRING) database analysis indicated that the content of circulating plasma EVs might have a relevant function for the tumor intercellular communication in the HNSCC patients.

CONCLUSION

This study provides a list of potential markers present in plasma compartments that might contribute to the development of tools for prediction and assessment of CRT response and potentially guide therapeutic decisions in this context.

Quantitative assessment of serum heat shock protein 27 for the diagnosis of epithelial ovarian cancer using targeted proteomics coupled with immunoaffinity enrichment

BACKGROUND

Heat shock protein 27 (HSP27) may take part in the epithelial ovarian cancer (EOC) malignant process because it is elevated in the serum of EOC patients, suggesting that HSP27 may serve as an EOC biomarker to complement the standard serum carbohydrate antigen 125 (CA125) test. Thus, accurate quantification of serum HSP27 would assist the diagnosis of EOC.

METHODS

Liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based targeted proteomics coupled with an immunoaffinity enrichment assay was developed and validated to monitor HSP27 concentrations in serum.

RESULTS

Tryptic peptide 80QLSSGVSEIR89 was selected as a surrogate analyte for quantification, and an immuno-depleted serum extract was used as a surrogate matrix. Immunoaffinity enrichment was effective for protein enrichment and sensitivity enhancement, and the resulting LOQ was 500 pg/ml (>10-fold increase). Then, serum HSP27 concentrations in EOC patients, benign ovarian tumors patients and healthy volunteers were accurately determined to be 4.95 ± 0.37 ng/ml, 2.98 ± 0.16 ng/ml and 2.82 ± 0.15 ng/ml, respectively, suggesting that the EOC samples had significantly higher concentrations of HSP27 than a sample from benign ovarian tumor patients. The experimental values for the samples were compared with those obtained from enzyme-linked immune sorbent assays (ELISAs). The ROC curve analysis showed that the combined area under the curve (AUC) for CA125 and HSP27 was 0.88, which is significantly superior to that of CA125 alone.

CONCLUSIONS

Targeted proteomics coupled with immunoaffinity enrichment may provide more accurate quantification of low-abundant proteins.

Individual Variability of Protein Expression in Human Tissues

Human tissues are known to exhibit interindividual variability, but a deeper understanding of the different factors affecting protein expression is necessary to further apply this knowledge. Our goal was to explore the proteomic variability between individuals as well as between healthy and diseased samples, and to test the efficacy of machine learning classifiers. In order to investigate whether disparate proteomics data sets may be combined, we performed a retrospective analysis of proteomics data from 9 different human tissues. These data sets represent several different sample prep methods, mass spectrometry instruments, and tissue health. Using these data, we examined interindividual and intertissue variability in peptide expression, and analyzed the methods required to build accurate tissue classifiers. We also evaluated the limits of tissue classification by downsampling the peptide data to simulate situations where less data is available, such as clinical biopsies, laser capture microdissection or potentially single-cell proteomics. Our findings reveal the strong potential for utilizing proteomics data to build robust tissue classifiers, which has many prospective clinical applications for evaluating the applicability of model clinical systems.

Serum responsive proteome reveals correlation between oxidative phosphorylation and morphogenesis in Candida albicans ATCC10231

To understand the impact of fetal bovine serum (FBS) on metabolism and cellular architecture in addition to morphogenesis, we have identified FBS responsive proteome of Candida albicans. FBS induced 34% hyphae and 60% pseudohyphae in C. albicans at 30 °C while 98% hyphae at 37 °C. LC-MS/MS analysis revealed that 285 proteins modulated significantly in response to FBS at 30 °C and 37 °C. Out of which 152 were upregulated and 62 were downregulated at 30 °C while 18 were up and 53 were downregulated at 37 °C. Functional annotation suggests that FBS may inhibit glycolysis and fermentative pathway and enhance oxidative phosphorylation (OxPhos), TCA cycle, amino acid and fatty acid metabolism indicating a use of alternative energy source by C. albicans. OxPhos inhibition assay using sodium azide corroborated the correlation between inhibition of glycolysis and enhanced OxPhos with pseudohyphae formation. C. albicans induced hyphae in response to FBS irrespective of down regulation of Ras1,Asr1/Asr2, indicates the possible involvement of MAPK and cAMP-PKA independent pathway. The Cell wall of cells grown in presence of FBS at 30 °C was rich in mannan, Beta 1,3-glucan and chitin while membranes were rich in ergosterol compared to those grown at 37 °C.

SIGNIFICANCE OF THE STUDY

This is the first study suggesting a correlation between OxPhos and morphogenesis especially pseudohyphae formation in C. albicans. Our data also indicate that fetal bovine serum (FBS) induced morphogenesis is multifactorial and may involve MAPK and cAMP-PKA independent pathway. In addition to morphogenesis, our study provides an insight in to the modulation of metabolism and cellular architecture of C. albicans in response to FBS.

Enrichment of high affinity subclasses and glycoforms from serum-derived IgG using FcγRs as affinity ligands

As antibodies continue to gain predominance in drug discovery and development pipelines, efforts to control and optimize their activity in vivo have matured to incorporate sophisticated abilities to manipulate engagement of specific Fc binding partners. Such efforts to promote diverse functional outcomes include modulating IgG-Fc affinity for FcγRs to alternatively potentiate or reduce effector functions, such as antibody-dependent cellular cytotoxicity and phagocytosis. While a number of natural and engineered Fc features capable of eliciting variable effector functions have been demonstrated in vitro and in vivo, elucidation of these important functional relationships has taken significant effort through use of diverse genetic, cellular and enzymatic techniques. As an orthogonal approach, we demonstrate use of FcγR as chromatographic affinity ligands to enrich and therefore simultaneously identify favored binding species from a complex mixture of serum-derived pooled polycloncal human IgG, a load material that contains the natural repertoire of Fc variants and post-translational modifications. The FcγR-enriched IgG was characterized for subclass and glycoform composition and the impact of this bioseparation step on antibody activity was measured in cell-based effector function assays including Natural Killer cell activation and monocyte phagocytosis. This work demonstrates a tractable means to rapidly distinguish complex functional relationships between two or more interacting biological agents by leveraging affinity chromatography followed by secondary analysis with high-resolution biophysical and functional assays and emphasizes a platform capable of surveying diverse natural post-translational modifications that may not be easily produced with high purity or easily accessible with recombinant expression techniques.

Plasma Protein Turnover Rates in Rats Using Stable Isotope Labeling, Global Proteomics, and Activity-Based Protein Profiling

Protein turnover is important for general health on cellular and organism scales providing a strategy to replace old, damaged, or dysfunctional proteins. Protein turnover also informs of biomarker kinetics, as a better understanding of synthesis and degradation of proteins increases the clinical utility of biomarkers. Here, turnover rates of plasma proteins in rats were measured in vivo using a pulse-chase stable isotope labeling experiment. During the pulse, rats (n = 5) were fed ¹³C₆-labeled lysine ("heavy") feed for 23 days to label proteins. During the chase, feed was changed to an unlabeled equivalent feed ("light"), and blood was repeatedly sampled from rats over 10 time points for 28 days. Plasma samples were digested with trypsin and analyzed with liquid chromatography-tandem mass spectrometry (LC-MS/MS). MaxQuant was used to identify peptides and proteins and quantify heavy/light lysine ratios. A system of ordinary differential equations was used to calculate protein turnover rates. Using this approach, 273 proteins were identified, and turnover rates were quantified for 157 plasma proteins with half-lives ranging 0.3-103 days. For the ∼70 most abundant proteins, variability in turnover rates among rats was low (median coefficient of variation: 0.09). Activity-based protein profiling was applied to pooled plasma samples to enrich serine hydrolases using a fluorophosphonate (FP2) activity-based probe. This enrichment resulted in turnover rates for an additional 17 proteins. This study is the first to measure global plasma protein turnover rates in rats in vivo, measure variability of protein turnover rates in any animal model, and utilize activity-based protein profiling for enhancing turnover measurements of targeted, low-abundant proteins, such as those commonly used as biomarkers. Measured protein turnover rates will be important for understanding of the role of protein turnover in cellular and organism health as well as increasing the utility of protein biomarkers through better understanding of processes governing biomarker kinetics.

Inference and quantification of peptidoforms in large sample cohorts by SWATH-MS

Consistent detection and quantification of protein post-translational modifications (PTMs) across sample cohorts is a prerequisite for functional analysis of biological processes. Data-independent acquisition (DIA) is a bottom-up mass spectrometry approach that provides complete information on precursor and fragment ions. However, owing to the convoluted structure of DIA data sets, confident, systematic identification and quantification of peptidoforms has remained challenging. Here, we present inference of peptidoforms (IPF), a fully automated algorithm that uses spectral libraries to query, validate and quantify peptidoforms in DIA data sets. The method was developed on data acquired by the DIA method SWATH-MS and benchmarked using a synthetic phosphopeptide reference data set and phosphopeptide-enriched samples. IPF reduced false site-localization by more than sevenfold compared with previous approaches, while recovering 85.4% of the true signals. Using IPF, we quantified peptidoforms in DIA data acquired from >200 samples of blood plasma of a human twin cohort and assessed the contribution of heritable, environmental and longitudinal effects on their PTMs.

Enhanced Detection of Low-Abundance Human Plasma Proteins by Integrating Polyethylene Glycol Fractionation and Immunoaffinity Depletion

The enormous depth complexity of the human plasma proteome poses a significant challenge for current mass spectrometry-based proteomic technologies in terms of detecting low-level proteins in plasma, which is essential for successful biomarker discovery efforts. Typically, a single-step analytical approach cannot reduce this intrinsic complexity. Current simplex immunodepletion techniques offer limited capacity for detecting low-abundance proteins, and integrated strategies are thus desirable. In this respect, we developed an improved strategy for analyzing the human plasma proteome by integrating polyethylene glycol (PEG) fractionation with immunoaffinity depletion. PEG fractionation of plasma proteins is simple, rapid, efficient, and compatible with a downstream immunodepletion step. Compared with immunodepletion alone, our integrated strategy substantially improved the proteome coverage afforded by PEG fractionation. Coupling this new protocol with liquid chromatography-tandem mass spectrometry, 135 proteins with reported normal concentrations below 100 ng/mL were confidently identified as common low-abundance proteins. A side-by-side comparison indicated that our integrated strategy was increased by average 43.0% in the identification rate of low-abundance proteins, relying on an average 65.8% increase of the corresponding unique peptides. Further investigation demonstrated that this combined strategy could effectively alleviate the signal-suppressive effects of the major high-abundance proteins by affinity depletion, especially with moderate-abundance proteins after incorporating PEG fractionation, thereby greatly enhancing the detection of low-abundance proteins. In sum, the newly developed strategy of incorporating PEG fractionation to immunodepletion methods can potentially aid in the discovery of plasma biomarkers of therapeutic and clinical interest.

The omic approach to parasitic trematode research-a review of techniques and developments within the past 5 years

The evolution of technologies to explore parasite biology at a detailed level has made significant advances in recent years, particularly with the development of omic-based strategies. Whilst extensive efforts have been made in the past to develop therapeutic and prophylactic control strategies for trematode parasites, only the therapeutic anthelmintic approach can be regarded as usable in clinical practice. Currently, there is no commercialised prophylactic strategy (such as vaccination) for protection of the definitive host against any trematode parasite. Since 2010 in particular, the integration of omic technologies, including liquid chromatography-mass spectrometry (LC-MS) and next-generation sequencing (NGS), has been increasingly reported in trematode-related studies. Both LC-MS and NGS facilitate a better understanding of the biology of trematodes and provide a promising route to identifying clinically important biological characteristics of parasitic trematodes. In this review, we focus on the application, advantages, and disadvantages of omic technologies (LC-MS and NGS) in trematode research within the past 5 years and explore the use and translation of the omic-based research results into practical tools to deal with infection.

Identification and Characterization of Potential Biomarkers by Quantitative Tissue Proteomics of Primary Lung Adenocarcinoma

Lung cancer is the leading cause of cancer-related death worldwide. Both diagnostic and prognostic biomarkers are urgently needed to increase patient survival. In this study, we identified/quantified 1763 proteins from paired adenocarcinoma (ADC) tissues with different extents of lymph node (LN) involvement using an iTRAQ-based quantitative proteomic analysis. Based on a bioinformatics analysis and literature search, we selected six candidates (ERO1L, PABPC4, RCC1, RPS25, NARS, and TARS) from a set of 133 proteins that presented a 1.5-fold increase in expression in ADC tumors without LN metastasis compared with adjacent normal tissues. These six proteins were further verified using immunohistochemical staining and Western blot analyses. The protein levels of these six candidates were higher in tumor tissues compared with adjacent normal tissues. The ERO1L and NARS levels were positively associated with LN metastasis. Importantly, ERO1L overexpression in patients with early-stage ADC was positively correlated with poor survival, suggesting that ERO1L overexpression in primary sites of early-stage cancer tissues indicates a high risk for cancer micrometastasis. Moreover, we found that knockdown of either ERO1L or NARS reduced the viability and migration ability of ADC cells. Our results collectively provide a potential biomarker data set for ADC diagnosis/prognosis and reveal novel roles of ERO1L and NARS in ADC progression.

Mining the human plasma proteome with three-dimensional strategies by high-resolution Quadrupole Orbitrap Mass Spectrometry

Human plasma is a readily available clinical sample that reflects the status of the body in normal physiological and disease states. Although the wide dynamic range and immense complexity of plasma proteins are obstacles, comprehensive proteomic analysis of human plasma is necessary for biomarker discovery and further verification. Various methods such as immunodepletion, protein equalization and hyper fractionation have been applied to reduce the influence of high-abundance proteins (HAPs) and to reduce the high level of complexity. However, the depth at which the human plasma proteome has been explored in a relatively short time frame has been limited, which impedes the transfer of proteomic techniques to clinical research. Development of an optimal strategy is expected to improve the efficiency of human plasma proteome profiling. Here, five three-dimensional strategies combining HAP depletion (the 1st dimension) and protein fractionation (the 2nd dimension), followed by LC-MS/MS analysis (the 3rd dimension) were developed and compared for human plasma proteome profiling. Pros and cons of the five strategies are discussed for two issues: HAP depletion and complexity reduction. Strategies A and B used proteome equalization and tandem Seppro IgY14 immunodepletion, respectively, as the first dimension. Proteome equalization (strategy A) was biased toward the enrichment of basic and low-molecular weight proteins and had limited ability to enrich low-abundance proteins. By tandem removal of HAPs (strategy B), the efficiency of HAP depletion was significantly increased, whereas more off-target proteins were subtracted simultaneously. In the comparison of complexity reduction, strategy D involved a deglycosylation step before high-pH RPLC separation. However, the increase in sequence coverage did not increase the protein number as expected. Strategy E introduced SDS-PAGE separation of proteins, and the results showed oversampling of HAPs and identification of fewer proteins. Strategy C combined single Seppro IgY14 immunodepletion, high-pH RPLC fractionation and LC-MS/MS analysis. It generated the largest dataset, containing 1544 plasma protein groups and 258 newly identified proteins in a 30-h-machine-time analysis, making it the optimum three-dimensional strategy in our study. Further analysis of the integrated data from the five strategies showed identical distribution patterns in terms of sequence features and GO functional analysis with the 1929-plasma-protein dataset, further supporting the reliability of our plasma protein identifications. The characterization of 20 cytokines in the concentration range from sub-nanograms/milliliter to micrograms/milliliter demonstrated the sensitivity of the current strategies.

Contributions of immunoaffinity chromatography to deep proteome profiling of human biofluids

Human biofluids, especially blood plasma or serum, hold great potential as the sources of candidate biomarkers for various diseases; however, the enormous dynamic range of protein concentrations in biofluids represents a significant analytical challenge for detecting promising low-abundance proteins. Over the last decade, various immunoaffinity chromatographic methods have been developed and routinely applied for separating low-abundance proteins from the high- and moderate-abundance proteins, thus enabling much more effective detection of low-abundance proteins. Herein, we review the advances of immunoaffinity separation methods and their contributions to the proteomic applications in human biofluids. The limitations and future perspectives of immunoaffinity separation methods are also discussed.

Multiplexed Immunoaffinity Enrichment of Peptides with Anti-peptide Antibodies and Quantification by Stable Isotope Dilution Multiple Reaction Monitoring Mass Spectrometry

Immunoaffinity enrichment of peptides using anti-peptide antibodies and their subsequent analysis by targeted mass spectrometry using stable isotope-labeled peptide standards is a sensitive and relatively high-throughput assay technology for unmodified and modified peptides in cells, tissues, and biofluids. Suppliers of antibodies and peptides are increasingly aware of this technique and have started incorporating customized quality measures and production protocols to increase the success rate, performance, and supply of the necessary reagents. Over the past decade, analytical biochemists, clinical diagnosticians, antibody experts, and mass spectrometry specialists have shared ideas, instrumentation, reagents, and protocols, to demonstrate that immuno-MRM-MS is reproducible across laboratories. Assay performance is now suitable for verification of candidate biomarkers from large scale discovery "omics" studies, measuring diagnostic proteins in plasma in the clinical laboratory, and for developing a companion assay for preclinical drug studies. Here we illustrate the process for developing these assays with a step-by-step guide for a 20-plex immuno-MRM-MS assay. We emphasize the need for analytical validation of the assay to insure that antibodies, peptides, and mass spectrometer are working as intended, in a multiplexed manner, with suitable assay performance (median values for 20 peptides: CV = 12.4% at 740 amol/μL, LOD = 310 amol/μL) for applications in quantitative biology and candidate biomarker verification. The assays described conform to Tier 2 (of 3) level of analytical assay validation (1), meaning that the assays are capable of repeatedly measuring sets of analytes of interest within and across samples/experiments and employ internal standards for each analyte for confident detection and precise quantification.

Evaluating the effects of preanalytical variables on the stability of the human plasma proteome

High quality clinical biospecimens are vital for biomarker discovery, verification, and validation. Variations in blood processing and handling can affect protein abundances and assay reliability. Using an untargeted LC-MS approach, we systematically measured the impact of preanalytical variables on the plasma proteome. Time prior to processing was the only variable that affected the plasma protein levels. LC-MS quantification showed that preprocessing times <6h had minimal effects on the immunodepleted plasma proteome, but by 4 days significant changes were apparent. Elevated levels of many proteins were observed, suggesting that in addition to proteolytic degradation during the preanalytical phase, changes in protein structure are also important considerations for protocols using antibody depletion. As to processing variables, a comparison of single- vs double-spun plasma showed minimal differences. After processing, the impact ⩽3 freeze-thaw cycles was negligible regardless of whether freshly collected samples were processed in short succession or the cycles occurred during 14-17 years of frozen storage (-80 °C). Thus, clinical workflows that necessitate modest delays in blood processing times or employ different centrifugation steps can yield valuable samples for biomarker discovery and verification studies.

Multiplexed, Quantitative Workflow for Sensitive Biomarker Discovery in Plasma Yields Novel Candidates for Early Myocardial Injury

We have developed a novel plasma protein analysis platform with optimized sample preparation, chromatography, and MS analysis protocols. The workflow, which utilizes chemical isobaric mass tag labeling for relative quantification of plasma proteins, achieves far greater depth of proteome detection and quantification while simultaneously having increased sample throughput than prior methods. We applied the new workflow to a time series of plasma samples from patients undergoing a therapeutic, "planned" myocardial infarction for hypertrophic cardiomyopathy, a unique human model in which each person serves as their own biologic control. Over 5300 proteins were confidently identified in our experiments with an average of 4600 proteins identified per sample (with two or more distinct peptides identified per protein) using iTRAQ four-plex labeling. Nearly 3400 proteins were quantified in common across all 16 patient samples. Compared with a previously published label-free approach, the new method quantified almost fivefold more proteins/sample and provided a six- to nine-fold increase in sample analysis throughput. Moreover, this study provides the largest high-confidence plasma proteome dataset available to date. The reliability of relative quantification was also greatly improved relative to the label-free approach, with measured iTRAQ ratios and temporal trends correlating well with results from a 23-plex immunoMRM (iMRM) assay containing a subset of the candidate proteins applied to the same patient samples. The functional importance of improved detection and quantification was reflected in a markedly expanded list of significantly regulated proteins that provided many new candidate biomarker proteins. Preliminary evaluation of plasma sample labeling with TMT six-plex and ten-plex reagents suggests that even further increases in multiplexing of plasma analysis are practically achievable without significant losses in depth of detection relative to iTRAQ four-plex. These results obtained with our novel platform provide clear demonstration of the value of using isobaric mass tag reagents in plasma-based biomarker discovery experiments.

Large-Scale Interlaboratory Study to Develop, Analytically Validate and Apply Highly Multiplexed, Quantitative Peptide Assays to Measure Cancer-Relevant Proteins in Plasma

There is an increasing need in biology and clinical medicine to robustly and reliably measure tens to hundreds of peptides and proteins in clinical and biological samples with high sensitivity, specificity, reproducibility, and repeatability. Previously, we demonstrated that LC-MRM-MS with isotope dilution has suitable performance for quantitative measurements of small numbers of relatively abundant proteins in human plasma and that the resulting assays can be transferred across laboratories while maintaining high reproducibility and quantitative precision. Here, we significantly extend that earlier work, demonstrating that 11 laboratories using 14 LC-MS systems can develop, determine analytical figures of merit, and apply highly multiplexed MRM-MS assays targeting 125 peptides derived from 27 cancer-relevant proteins and seven control proteins to precisely and reproducibly measure the analytes in human plasma. To ensure consistent generation of high quality data, we incorporated a system suitability protocol (SSP) into our experimental design. The SSP enabled real-time monitoring of LC-MRM-MS performance during assay development and implementation, facilitating early detection and correction of chromatographic and instrumental problems. Low to subnanogram/ml sensitivity for proteins in plasma was achieved by one-step immunoaffinity depletion of 14 abundant plasma proteins prior to analysis. Median intra- and interlaboratory reproducibility was <20%, sufficient for most biological studies and candidate protein biomarker verification. Digestion recovery of peptides was assessed and quantitative accuracy improved using heavy-isotope-labeled versions of the proteins as internal standards. Using the highly multiplexed assay, participating laboratories were able to precisely and reproducibly determine the levels of a series of analytes in blinded samples used to simulate an interlaboratory clinical study of patient samples. Our study further establishes that LC-MRM-MS using stable isotope dilution, with appropriate attention to analytical validation and appropriate quality control measures, enables sensitive, specific, reproducible, and quantitative measurements of proteins and peptides in complex biological matrices such as plasma.

The effects of eating marine- or vegetable-fed farmed trout on the human plasma proteome profiles of healthy men

Most human intervention studies have examined the effects on a subset of risk factors, some of which may require long-term exposure. The plasma proteome may reflect the underlying changes in protein expression and activation, and this could be used to identify early risk markers. The aim of the present study was to evaluate the impact of regular fish intake on the plasma proteome. We recruited thirty healthy men aged 40 to 70 years, who were randomly allocated to a daily meal of chicken or trout raised on vegetable or marine feeds. Blood samples were collected before and after 8 weeks of intervention, and after the removal of the twelve most abundant proteins, plasma proteins were separated by two-dimensional gel electrophoresis. Protein spots < 66 kDa with a pI >4·3 visualised by silver staining were matched by two-dimensional imaging software. Within-subject changes in spots were compared between the treatment groups. Differentially affected spots were identified by matrix-assisted laser desorption ionisation-time of flight/time of flight MS and the human Swiss-Prot database. We found 23/681 abundant plasma protein spots, which were up- or down-regulated by the dietary treatment (P< 0·05, q< 0·30), and eighteen of these were identified. In each trout group, ten spots differed from those in subjects given the chicken meal, but only three of these were common, and only one spot differed between the two trout groups. In both groups, the affected plasma proteins were involved in biological processes such as regulation of vitamin A and haem transport, blood fibrinolysis and oxidative defence. Thus, regular fish intake affects the plasma proteome, and the changes may indicate novel mechanisms of effect.

Microscale depletion of high abundance proteins in human biofluids using IgY14 immunoaffinity resin: analysis of human plasma and cerebrospinal fluid

Removal of highly abundant proteins in plasma is often carried out using immunoaffinity depletion to extend the dynamic range of measurements to lower abundance species. While commercial depletion columns are available for this purpose, they generally are not applicable to limited sample quantities (<20 μL) due to low yields stemming from losses caused by nonspecific binding to the column matrix and concentration of large eluent volumes. Additionally, the cost of the depletion media can be prohibitive for larger-scale studies. Modern LC-MS instrumentation provides the sensitivity necessary to scale-down depletion methods with minimal sacrifice to proteome coverage, which makes smaller volume depletion columns desirable for maximizing sample recovery when samples are limited, as well as for reducing the expense of large-scale studies. We characterized the performance of a 346 μL column volume microscale depletion system, using four different flow rates to determine the most effective depletion conditions for ∼6-μL injections of human plasma proteins and then evaluated depletion reproducibility at the optimum flow rate condition. Depletion of plasma using a commercial 10-mL depletion column served as the control. Results showed depletion efficiency of the microscale column increased as flow rate decreased, and that our microdepletion was reproducible. In an initial application, a 600-μL sample of human cerebrospinal fluid (CSF) pooled from multiple sclerosis patients was depleted and then analyzed using reversed phase liquid chromatography-mass spectrometry to demonstrate the utility of the system for this important biofluid where sample quantities are more commonly limited.

Technological advances for deciphering the complexity of psychiatric disorders: merging proteomics with cell biology

Proteomic studies have increased our understanding of the molecular pathways affected in psychiatric disorders. Mass spectrometry and two-dimensional gel electrophoresis analyses of post-mortem brain samples from psychiatric patients have revealed effects on synaptic, cytoskeletal, antioxidant and mitochondrial protein networks. Multiplex immunoassay profiling studies have found alterations in hormones, growth factors, transport and inflammation-related proteins in serum and plasma from living first-onset patients. Despite these advances, there are still difficulties in translating these findings into platforms for improved treatment of patients and for discovery of new drugs with better efficacy and side effect profiles. This review describes how the next phase of proteomic investigations in psychiatry should include stringent replication studies for validation of biomarker candidates and functional follow-up studies which can be used to test the impact on physiological function. All biomarker candidates should now be tested in series with traditional and emerging cell biological approaches. This should include investigations of the effects of post-translational modifications, protein dynamics and network analyses using targeted proteomic approaches. Most importantly, there is still an urgent need for development of disease-relevant cellular models for improved translation of proteomic findings into a means of developing novel drug treatments for patients with these life-altering disorders.

Quantitative proteomics in cardiovascular research: global and targeted strategies

Extensive technical advances in the past decade have substantially expanded quantitative proteomics in cardiovascular research. This has great promise for elucidating the mechanisms of cardiovascular diseases and the discovery of cardiac biomarkers used for diagnosis and treatment evaluation. Global and targeted proteomics are the two major avenues of quantitative proteomics. While global approaches enable unbiased discovery of altered proteins via relative quantification at the proteome level, targeted techniques provide higher sensitivity and accuracy, and are capable of multiplexed absolute quantification in numerous clinical/biological samples. While promising, technical challenges need to be overcome to enable full utilization of these techniques in cardiovascular medicine. Here, we discuss recent advances in quantitative proteomics and summarize applications in cardiovascular research with an emphasis on biomarker discovery and elucidating molecular mechanisms of disease. We propose the integration of global and targeted strategies as a high-throughput pipeline for cardiovascular proteomics. Targeted approaches enable rapid, extensive validation of biomarker candidates discovered by global proteomics. These approaches provide a promising alternative to immunoassays and other low-throughput means currently used for limited validation.

Identification of plasma biomarker candidates in glioblastoma using an antibody-array-based proteomic approach

Background

Glioblastoma multiforme (GBM) is a brain tumour with a very high patient mortality rate, with a median survival of 47 weeks. This might be improved by the identification of novel diagnostic, prognostic and predictive therapy-response biomarkers, preferentially through the monitoring of the patient blood. The aim of this study was to define the impact of GBM in terms of alterations of the plasma protein levels in these patients.

Materials and methods.

We used a commercially available antibody array that includes 656 antibodies to analyse blood plasma samples from 17 healthy volunteers in comparison with 17 blood plasma samples from patients with GBM.

Results

We identified 11 plasma proteins that are statistically most strongly associated with the presence of GBM. These proteins belong to three functional signalling pathways: T-cell signalling and immune responses; cell adhesion and migration; and cell-cycle control and apoptosis. Thus, we can consider this identified set of proteins as potential diagnostic biomarker candidates for GBM. In addition, a set of 16 plasma proteins were significantly associated with the overall survival of these patients with GBM. Guanine nucleotide binding protein alpha (GNAO1) was associated with both GBM presence and survival of patients with GBM.

Conclusions

Antibody array analysis represents a useful tool for the screening of plasma samples for potential cancer biomarker candidates in small-scale exploratory experiments; however, clinical validation of these candidates requires their further evaluation in a larger study on an independent cohort of patients.

Absolute quantitation of low abundance plasma APL1β peptides at sub-fmol/mL Level by SRM/MRM without immunoaffinity enrichment

Selected/multiple reaction monitoring (SRM/MRM) has been widely used for the quantification of specific proteins/peptides, although it is still challenging to quantitate low abundant proteins/peptides in complex samples such as plasma/serum. To overcome this problem, enrichment of target proteins/peptides is needed, such as immunoprecipitation; however, this is labor-intense and generation of antibodies is highly expensive. In this study, we attempted to quantify plasma low abundant APLP1-derived Aβ-like peptides (APL1β), a surrogate marker for Alzheimer's disease, by SRM/MRM using stable isotope-labeled reference peptides without immunoaffinity enrichment. A combination of Cibacron Blue dye mediated albumin removal and acetonitrile extraction followed by C18-strong cation exchange multi-StageTip purification was used to deplete plasma proteins and unnecessary peptides. Optimal and validated precursor ions to fragment ion transitions of APL1β were developed on a triple quadruple mass spectrometer, and the nanoliquid chromatography gradient for peptide separation was optimized to minimize the biological interference of plasma. Using the stable isotope-labeled (SI) peptide as an internal control, absolute concentrations of plasma APL1β peptide could be quantified as several hundred amol/mL. To our knowledge, this is the lowest detection level of endogenous plasma peptide quantified by SRM/MRM.

Large-scale, ion-current-based proteomics investigation of bronchoalveolar lavage fluid in chronic obstructive pulmonary disease patients

Proteomic analysis of bronchoalveolar lavage fluid (BALF) in chronic obstructive pulmonary disease (COPD) patients may provide new biomarkers and deeper understanding of the disease mechanisms but remains challenging. Here we describe an ion-current-based strategy for comparative analysis of BALF proteomes from patients with moderate and stable COPD versus healthy controls. The strategy includes an efficient preparation procedure providing quantitative recovery and a nano-LC/MS analysis with a long, heated column. Under optimized conditions, high efficiency and reproducibility were achieved for each step, enabling a "20-plex" comparison of clinical subjects (n = 10/group). Without depletion/fractionation, a total of 423 unique protein groups were quantified under stringent criteria with at least two quantifiable peptides. Seventy-six proteins were determined as significantly altered in COPD, which represent a diversity of biological processes such as alcohol metabolic process, gluconeogenesis/glycolysis, inflammatory response, proteolysis, and oxidation reduction. Interestingly, altered alcohol metabolism responding to oxidant stress is a novel observation in COPD. The prominently elevated key enzymes involved in alcohol metabolism (e.g., ADH1B, ALDH2, and ALDH3A1) may provide a reasonable explanation for a bewildering observation in COPD patients known for decades: the underestimation of the blood alcohol concentrations through breath tests. These discoveries could provide new insights for identifying novel biomarkers and pathological mediators in clinical studies.

Proteomic Workflows for Biomarker Identification Using Mass Spectrometry - Technical and Statistical Considerations during Initial Discovery

Identification of biomarkers capable of differentiating between pathophysiological states of an individual is a laudable goal in the field of proteomics. Protein biomarker discovery generally employs high throughput sample characterization by mass spectrometry (MS), being capable of identifying and quantifying thousands of proteins per sample. While MS-based technologies have rapidly matured, the identification of truly informative biomarkers remains elusive, with only a handful of clinically applicable tests stemming from proteomic workflows. This underlying lack of progress is attributed in large part to erroneous experimental design, biased sample handling, as well as improper statistical analysis of the resulting data. This review will discuss in detail the importance of experimental design and provide some insight into the overall workflow required for biomarker identification experiments. Proper balance between the degree of biological vs. technical replication is required for confident biomarker identification.

Dried blood spot proteomics: surface extraction of endogenous proteins coupled with automated sample preparation and mass spectrometry analysis

Dried blood spots offer many advantages as a sample format including ease and safety of transport and handling. To date, the majority of mass spectrometry analyses of dried blood spots have focused on small molecules or hemoglobin. However, dried blood spots are a potentially rich source of protein biomarkers, an area that has been overlooked. To address this issue, we have applied an untargeted bottom-up proteomics approach to the analysis of dried blood spots. We present an automated and integrated method for extraction of endogenous proteins from the surface of dried blood spots and sample preparation via trypsin digestion by use of the Advion Biosciences Triversa Nanomate robotic platform. Liquid chromatography tandem mass spectrometry of the resulting digests enabled identification of 120 proteins from a single dried blood spot. The proteins identified cross a concentration range of four orders of magnitude. The method is evaluated and the results discussed in terms of the proteins identified and their potential use as biomarkers in screening programs.

Determination of burn patient outcome by large-scale quantitative discovery proteomics

OBJECTIVES

Emerging proteomics techniques can be used to establish proteomic outcome signatures and to identify candidate biomarkers for survival following traumatic injury. We applied high-resolution liquid chromatography-mass spectrometry and multiplex cytokine analysis to profile the plasma proteome of survivors and nonsurvivors of massive burn injury to determine the proteomic survival signature following a major burn injury.

DESIGN

Proteomic discovery study.

SETTING

Five burn hospitals across the United States.

PATIENTS

Thirty-two burn patients (16 nonsurvivors and 16 survivors), 19-89 years old, were admitted within 96 hours of injury to the participating hospitals with burns covering more than 20% of the total body surface area and required at least one surgical intervention.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

We found differences in circulating levels of 43 proteins involved in the acute-phase response, hepatic signaling, the complement cascade, inflammation, and insulin resistance. Thirty-two of the proteins identified were not previously known to play a role in the response to burn. Interleukin-4, interleukin-8, granulocyte macrophage colony-stimulating factor, monocyte chemotactic protein-1, and β2-microglobulin correlated well with survival and may serve as clinical biomarkers.

CONCLUSIONS

These results demonstrate the utility of these techniques for establishing proteomic survival signatures and for use as a discovery tool to identify candidate biomarkers for survival. This is the first clinical application of a high-throughput, large-scale liquid chromatography-mass spectrometry-based quantitative plasma proteomic approach for biomarker discovery for the prediction of patient outcome following burn, trauma, or critical illness.

Development of a validated liquid chromatography tandem mass spectrometry assay for a PEGylated adnectin in cynomolgus monkey plasma using protein precipitation and trypsin digestion

A liquid chromatography tandem mass spectrometry (LC-MS/MS) method has been developed and validated for a PEGylated adnectin therapeutic protein in cynomolgus monkey plasma. The validated method was performed using protein precipitation coupled with trypsin digestion, followed by LC-MS/MS detection of a surrogate peptide generated from the PEGylated adnectin protein. A tryptic peptide generated from a PEGylated adnectin protein analog was used as the internal standard to standardize the digestion, extraction, and quantitation processes. The protein precipitation extraction of the protein from cynomolgus plasma was performed using an acidic 2-propanol organic solution. Following the extraction, the supernatant was removed and a 45min trypsin digestion was performed at 60°C on the supernatant layer. The linear dynamic range of the assay was 50.0-25,000ng/mL. Chromatographic separation was performed with an Acquity BEH C18 (1.7μm particle size, 2.1mm×50mm) column using gradient elution. The assay proved to have robust accuracy, precision, and stability for the representative surrogate peptide of the PEGylated adnectin protein being evaluated. The validated method was implemented as a high throughput assay for a PEGylated adnectin protein using a similar PEGylated adnectin therapeutic protein as the internal standard that can be used for future monkey toxicokinetic (TK) studies.

Protein isoform-specific validation defines multiple chloride intracellular channel and tropomyosin isoforms as serological biomarkers of ovarian cancer

New serological biomarkers for early detection and clinical management of ovarian cancer are urgently needed, and many candidates have been reported. A major challenge frequently encountered when validating candidates in patients is establishing quantitative assays that distinguish between highly homologous proteins. The current study tested whether multiple members of two recently discovered ovarian cancer biomarker protein families, chloride intracellular channel (CLIC) proteins and tropomyosins (TPM), were detectable in ovarian cancer patient sera. A multiplexed, label-free multiple reaction monitoring (MRM) assay was established to target peptides specific to all detected CLIC and TPM family members, and their serum levels were quantitated for ovarian cancer patients and non-cancer controls. In addition to CLIC1 and TPM1, which were the proteins initially discovered in a xenograft mouse model, CLIC4, TPM2, TPM3, and TPM4 were present in ovarian cancer patient sera at significantly elevated levels compared with controls. Some of the additional biomarkers identified in this homolog-centric verification and validation approach may be superior to the previously identified biomarkers at discriminating between ovarian cancer and non-cancer patients. This demonstrates the importance of considering all potential protein homologs and using quantitative assays for cancer biomarker validation with well-defined isoform specificity.

BIOLOGICAL SIGNIFICANCE

This manuscript addresses the importance of distinguishing between protein homologs and isoforms when identifying and validating cancer biomarkers in plasma or serum. Specifically, it describes the use of targeted in-depth LC-MS/MS analysis to determine the members of two protein families, chloride intracellular channel (CLIC) and tropomyosin (TPM) proteins that are detectable in sera of ovarian cancer patients. It then establishes a multiplexed isoform- and homology-specific MRM assay to quantify all observed gene products in these two protein families as well as many of the closely related tropomyosin isoforms. Using this assay, levels of all detected CLICs and TPMs were quantified in ovarian cancer patient and control subject sera. These results demonstrate that in addition to the previously known CLIC1, multiple tropomyosins and CLIC4 are promising new ovarian cancer biomarkers. Based on these initial validation studies, these new ovarian cancer biomarkers appear to be superior to most previously known ovarian cancer biomarkers.

Targeted quantification of low ng/mL level proteins in human serum without immunoaffinity depletion

We recently reported an antibody-free targeted protein quantification strategy, termed high-pressure, high-resolution separations with intelligent selection and multiplexing (PRISM), for achieving significantly enhanced sensitivity using selected reaction monitoring (SRM) mass spectrometry. Integrating PRISM with front-end IgY14 immunoaffinity depletion, sensitive detection of targeted proteins at 50-100 pg/mL levels in human blood plasma/serum was demonstrated. However, immunoaffinity depletion is often associated with undesired losses of target proteins of interest. Herein we report further evaluation of PRISM-SRM quantification of low-abundance serum proteins without immunoaffinity depletion. Limits of quantification (LOQ) at low ng/mL levels with a median coefficient of variation (CV) of ∼12% were achieved for proteins spiked into human female serum. PRISM-SRM provided >100-fold improvement in the LOQ when compared to conventional LC-SRM measurements. PRISM-SRM was then applied to measure several low-abundance endogenous serum proteins, including prostate-specific antigen (PSA), in clinical prostate cancer patient sera. PRISM-SRM enabled confident detection of all target endogenous serum proteins except the low pg/mL-level cardiac troponin T. A correlation coefficient >0.99 was observed for PSA between the results from PRISM-SRM and immunoassays. Our results demonstrate that PRISM-SRM can successfully quantify low ng/mL proteins in human plasma or serum without depletion. We anticipate broad applications for PRISM-SRM quantification of low-abundance proteins in candidate biomarker verification and systems biology studies.

Ultradepletion of human plasma using chicken antibodies: a proof of concept study

Human plasma arguably represents the most comprehensive version of the human proteome. Despite its immense theoretical discovery potential, plasma has many high and medium abundance proteins that mask low abundance protein disease biomarkers of relevance, making the discovery of novel diagnostic markers particularly difficult. Some form of protein depletion and/or fractionation is essential in order to detect markers of low abundance. Here, we describe a "proof of concept" two-pronged approach to immunodeplete abundant proteins from human plasma. The method, called API (Abundant Protein Immunodepletion), involves the fractionation of plasma using dual ion exchange columns (protein repetitive orthogonal offline fractionation (PROOF)) to simplify the proteome, the production of polyclonal IgY against each fraction and finally using the purified antibodies in a immunodepletion column. We explored the use of this product for immunodepletion of human plasma and identified a total of 165 nonredundant proteins after depletion. Of these, 38 proteins that were not previously identified in nondepleted plasma were now detected. It is envisaged that further optimization of the method as well as its cyclic implementation (by reinjecting depleted plasma into chickens for second round of antibody production) can make this technology highly robust, extremely cost-effective, and ideal for high throughput biomarker discovery.

Proteome-base biomarkers in diabetes mellitus: progress on biofluids' protein profiling using mass spectrometry

The worldwide number of individuals suffering from diabetes mellitus (DM) has been projected to rise from 171 million in 2000 to 366 million in 2030. Identification of specific biomarkers for prediction and monitoring of DM is needed not only for the adequate screening diagnosis but also to assist the design of interventions to prevent or delay progression of this pathology and its attendant complications. Proteomic methods based on MS hold special promise for the identification of novel biomarkers that might form the foundation for new clinical tests, but to date, their contribution has been somehow unfruitful. Indeed, from more than 300 proteins found differently modulated in body fluids from diabetic patients, approximately 50 were validated with other approaches like ELISA or Western blotting and the clinical trials are being initiated to employ biofluids' proteomics (specifically urinary proteomics) in clinical decision. This review provides an overview of MS-based applications in the identification of potential biomarkers for DM, emphasizing the methodological challenges involved.