Contribution of protein fractionation to depth of analysis of the serum and plasma proteomes

Revisiting Protein Reversed-Phase Chromatography for Bottom-Up Proteomics

We revisited protein reversed-phase chromatography (RP), using state-of-the-art RP columns developed for biopharmaceuticals, such as monoclonal antibodies, in order to evaluate the suitability of this methodology as a prefractionation step for bottom-up proteomics. The protein RP prefractionation (Prot-RP) method was compared with two other widely used prefractionation methods, SDS-PAGE and high-pH peptide RP (Pept-RP) by using cell lysates as samples. The overlap between fractions of Prot-RP was comparable to that of SDS-PAGE, and the protein recovery was approximately 2-fold higher. On the other hand, the overlap between fractions of Prot-RP was slightly larger than that of Pept-RP, but Prot-RP was able to identify more protein termini and more isoform-specific peptides than Pept-RP. Our results indicate that the combination of highly efficient protein prefractionation with modern mass spectrometers is particularly effective for proteoform profiling from cellular samples.

Immune capture and protein profiling of small extracellular vesicles from human plasma

Extracellular vesicles (EVs), the key players in inter-cellular communication, are produced by all cell types and are present in all body fluids. Analysis of the proteome content is an important approach in structural and functional studies of these vesicles. EVs circulating in human plasma are heterogeneous in size, cellular origin, and functions. This heterogeneity and the potential presence of contamination with plasma components such as lipoprotein particles and soluble plasma proteins represent a challenge in profiling the proteome of EV subsets by mass spectrometry. An immunocapture strategy prior to mass spectrometry may be used to isolate a homogeneous subpopulation of small EVs (sEV) with a specific endocytic origin from plasma or other biofluids. Immunocapture selectively separates EV subpopulations in biofluids based on the presence of a unique protein carried on the vesicle surface. The advantages and disadvantages of EV immune capture as a preparative step for mass spectrometry are discussed.

Differential Protease Specificity by Collagenase as a Novel Approach to Serum Proteomics That Includes Identification of Extracellular Matrix Proteins without Enrichment

Circulating extracellular matrix (ECM) proteins are serological biomarkers of interest due to their association with pathologies involving disease processes such as fibrosis and cancers. In this study, we investigate the potential for serum biomarker research using differential protease specificity (DPS), leveraging alternate protease specificity as a targeting mechanism to selectively digest circulating ECM protein serum proteins. A proof-of-concept study is presented using serum from patients with cirrhotic liver or hepatocellular carcinoma. The approach uses collagenase DPS for digestion of deglycosylated serum and liquid-chromatography-trapped ion mobility-tandem mass spectrometry (LC-TIMS-MS/MS) to enhance the detection of ECM proteins in serum. It requires no sample enrichment and minimizes the albumin average precursor intensity readout to less than 1.2%. We further demonstrate the capabilities for using the method as a high-throughput matrix-assisted laser/desorption ionization mass spectrometry (MALDI-MS) assay coupled with reference library searching. A goal is to improve the depth and breadth of biofluid proteomics for noninvasive assays.

Multiple reaction monitoring assays for large-scale quantitation of proteins from 20 mouse organs and tissues

Mouse is the mammalian model of choice to study human health and disease due to its size, ease of breeding and the natural occurrence of conditions mimicking human pathology. Here we design and validate multiple reaction monitoring mass spectrometry (MRM-MS) assays for quantitation of 2118 unique proteins in 20 murine tissues and organs. We provide open access to technical aspects of these assays to enable their implementation in other laboratories, and demonstrate their suitability for proteomic profiling in mice by measuring normal protein abundances in tissues from three mouse strains: C57BL/6NCrl, NOD/SCID, and BALB/cAnNCrl. Sex- and strain-specific differences in protein abundances are identified and described, and the measured values are freely accessible via our MouseQuaPro database: http://mousequapro.proteincentre.com . Together, this large library of quantitative MRM-MS assays established in mice and the measured baseline protein abundances represent an important resource for research involving mouse models.

Mass spectrometry methods for analysis of extracellular matrix components in neurological diseases

The brain extracellular matrix (ECM) is a highly glycosylated environment and plays important roles in many processes including cell communication, growth factor binding, and scaffolding. The formation of structures such as perineuronal nets (PNNs) is critical in neuroprotection and neural plasticity, and the formation of molecular networks is dependent in part on glycans. The ECM is also implicated in the neuropathophysiology of disorders such as Alzheimer's disease (AD), Parkinson's disease (PD), and Schizophrenia (SZ). As such, it is of interest to understand both the proteomic and glycomic makeup of healthy and diseased brain ECM. Further, there is a growing need for site-specific glycoproteomic information. Over the past decade, sample preparation, mass spectrometry, and bioinformatic methods have been developed and refined to provide comprehensive information about the glycoproteome. Core ECM molecules including versican, hyaluronan and proteoglycan link proteins, and tenascin are dysregulated in AD, PD, and SZ. Glycomic changes such as differential sialylation, sulfation, and branching are also associated with neurodegeneration. A more thorough understanding of the ECM and its proteomic, glycomic, and glycoproteomic changes in brain diseases may provide pathways to new therapeutic options.

Intraoperative plasma proteomic changes in cardiac surgery: In search of biomarkers of post-operative delirium

PURPOSE

Delirium presents a significant healthcare burden. It complicates post-operative care in up to 50% of cardiac surgical patients with worse outcomes, longer hospital stays and higher cost of care. Moreover, the nature of delirium following cardiac surgery with cardiopulmonary bypass (CPB) remains unclear, the underlying pathobiology is poorly understood, status quo diagnostic methods are subjective, and diagnostic biomarkers are currently lacking.

OBJECTIVE

To identify diagnostic biomarkers of delirium and for insights into possible neuronal pathomechanisms.

EXPERIMENTAL DESIGN

Comparative proteomic analyses were performed on plasma samples from a nested matched cohort of patients who underwent cardiac surgery. Validation by targeted proteomics was performed in an independent set of samples. Biomarkers were assessed for biological functions and diagnostic accuracy.

RESULTS

Forty-seven percent of subjects demonstrated delirium. Of 3803 proteins identified from patient samples by multiplexed quantitative proteomics, 16 were identified as signatures of exposure to CPB, and 11 biomarkers distinguished delirium cases from non-cases (AuROC = 93%). Notable among these biomarkers are C-reactive protein, serum amyloid A-1 and cathepsin-B.

CONCLUSIONS AND CLINICAL RELEVANCE

The interplay of systemic and central inflammatory markers sheds new light on delirium pathogenesis. This work suggests that accurate identification of cases may be achievable using panels of biomarkers.

Discovery and Visualization of Uncharacterized Drug-Protein Adducts Using Mass Spectrometry

Drugs are often metabolized to reactive intermediates that form protein adducts. Adducts can inhibit protein activity, elicit immune responses, and cause life-threatening adverse drug reactions. The masses of reactive metabolites are frequently unknown, rendering traditional mass spectrometry-based proteomics approaches incapable of adduct identification. Here, we present Magnum, an open-mass search algorithm optimized for adduct identification, and Limelight, a web-based data processing package for analysis and visualization of data from all existing algorithms. Limelight incorporates tools for sample comparisons and xenobiotic-adduct discovery. We validate our tools with three drug/protein combinations and apply our label-free workflow to identify novel xenobiotic-protein adducts in CYP3A4. Our new methods and software enable accurate identification of xenobiotic-protein adducts with no prior knowledge of adduct masses or protein targets. Magnum outperforms existing label-free tools in xenobiotic-protein adduct discovery, while Limelight fulfills a major need in the rapidly developing field of open-mass searching, which until now lacked comprehensive data visualization tools.

Rapid glycosylation analysis of mouse serum glycoproteins separated by supported molecular matrix electrophoresis

Previously, we developed a novel separation technique, namely, supported molecular matrix electrophoresis (SMME), which separates mucins on a PVDF membrane that impregnated with a hydrophilic polymer (such as polyvinyl alcohol), so it has the characteristics that are compatible with glycan analysis of the separated bands. Here, we describe the first instance of the application of SMME to mouse sera fractionation and demonstrate their differences from the pooled human sera fractionation by SMME. Furthermore, we have developed a fixation method for the lectin blotting of SMME-separated glycoproteins by immersing the SMME membranes into acetone solvent followed by heating. It showed that the amount of protein samples required for SMME were reduced more than 4-fold than that of the process of SDS-PAGE. We applied these techniques for the detection of glycosylation patterns of serum proteins from Fut8^+/+ and Fut8^-/- mice, further analyzed N-linked and O-linked glycans from the separated γ-bands by mass spectrometry, and demonstrated that there are α2,8-sialylated O-glycans contained in mouse sera glycoproteins. SMME can provide simple, rapid sera fractionation, glycan profiling differences between the bands of two samples and a new insight into the underlying mechanism that responsible for related diseases. SIGNIFICANCE: We describe that the first application of SMME can separate mouse serum proteins into six bands and identify the major protein components of each fraction in mouse serum separated by SMME. Furthermore, we successfully developed a fixation method for lectin blotting of SMME-separated glycoproteins and applied to the detection of glycosylation patterns of serum glycoproteins from Fut8^+/+ and Fut8^-/- mice, also, the method is promising for detecting glycan profiling differences between two samples in both research and clinical settings.

Analysis of differential strategies to enhance detection of low-abundance proteins in the bovine serum proteome

Serum-based biomarkers hold propitious applications for addressing livestock health, and management. However, discovery of protein biomarkers in complex biological fluids like serum is wholly intractable due to the large dynamic range of protein concentrations; that is, ˜10-12 high abundance proteins constitute >90% of the total protein content and effectively mask proteomic detection of low-abundance biomarkers. Toward addressing this limitation, we test a continuous elution size-based fractionation method, and two approaches that use affinity interaction-based separation of proteins in preparing bovine serum, and compare liquid chromatography tandem mass spectrometry protein identification to neat serum. Our results identify the high-abundance proteins in bovine serum, and demonstrate dynamic range compression and improved protein identification with the different enrichment methods. Although these findings indicate the highest protein number identified in bovine serum (445 proteins, all methods combined), and by any single sample processing method (312 proteins) to date, they still remain lower than levels deemed necessary for biomarker discovery. As such, this investigation revealed limitations to resolving the bovine serum proteome, and the need for species-specific tools for immunodepleting high-abundance proteins. In concert, this study represents a step toward advancing sample preparation methods for bovine serum biomarker identification.

A new strategy of studying protein-protein interactions: Integrated strong anion exchange/reversed-phase chromatography/immunoprecipitation coupled with mass spectrometry for large-scale identification of proteins interact with immunoglobulin G in HeLa cells

Recently, significant research efforts have been devoted to the development of technology for large-scale analysis of protein-protein interactions. Herein, a comprehensive method by coupling the first-dimension strong anion exchange chromatography with the second-dimension reversed-phase liquid chromatography via immunoprecipitation technique and high-resolution mass spectrometry analysis was developed for analyzing protein-protein interactions. After two-dimensional liquid chromatography separation, 108 fractions were obtained in one experiment. Immunoglobulin G from human serum was used as a model of an interacting protein. As a result, 919 proteins in these fractions were identified to interact with immunoglobulin G. By searching STRING database and data analysis, 27 of 919 proteins were inferred to directly interact with immunoglobulin G. Moreover, important target proteins that interacted with immunoglobulin G were mapped in the two-dimensional liquid chromatography system, which facilitated selection of these proteins from specific fractions. These results demonstrated that the proposed method can be useful for large-scale investigation of protein-protein interactions and as an advanced tool for the isolation of target proteins.

NanoTPOT: Enhanced Sample Preparation for Quantitative Nanoproteomic Analysis

With the ever-growing need for protein-level understanding in pathological research, proteomics researchers thrive to examine detailed proteome dynamics using crucial, yet often limited, primary and clinical samples. Aside from mass spectrometer instrumentation advancement, a single-tube-based high-throughput sample processing workflow is imperative to ensure sensitive, quantitative, and reproducible protein analysis for these increasingly sophisticated studies. Leveraging the benefits of an acid-cleavable detergent, RapiGest SF Surfactant (Waters Corporation), we developed and optimized a nanoproteomic workflow that we termed Nanogram TMT Processing in One Tube (NanoTPOT). Through the assessment of proteolytic digestion, tandem mass tag (TMT) labeling, online and offline fractionation strategies, our optimized workflow effectively eliminated the need for sample desalting and enabled compatible sample processing for mass spectrometry analysis. We further applied the NanoTPOT workflow to examine cellular response to stress caused by dithiothreitol in HeLa cells, where we identified and quantified 6935 and 5474 proteins in TMT 10-plex experiments with one microgram of lysate protein and 2000 sorted HeLa cells (roughly half microgram lysate protein) in each channel, respectively. Our workflow has been proven to be an effective alternative for current nanoproteomic sample processing to minimize sample loss in biological and clinical applications.

MAGIC biomarkers of acute graft-versus-host disease: Biology and clinical application

Acute graft-versus-host disease (GVHD) is the major complication of allogeneic hematopoietic cell transplantation and is the primary cause of early non-relapse mortality (NRM) after transplant. GVHD of the gastrointestinal (GI) tract fuels the systemic inflammatory reaction and consequently is the principal driver of mortality. Recently, the MAGIC algorithm probability (MAP) that is computed from two biomarkers of GI GVHD has been validated to accurately predict risk of NRM throughout the course of early acute GVHD. This review focuses on the biology, clinical evidence, and practical application of the biomarkers in the measurement of acute GVHD.

Serum Exosome Isolation by Size-Exclusion Chromatography for the Discovery and Validation of Preeclampsia-Associated Biomarkers

Exosomes are extracellular nanovesicles of complex and heterogeneous composition that are released in biofluids such as blood. The interest in the characterization of exosomal biochemistry has increased over the last few years as they convey cellular proteins, lipids, and RNA that might reflect the biological or pathological condition of the source cell. In particular, association of changes of exosome proteins with specific pathogenic processes arises as a promising method to identify disease biomarkers as for the pregnancy-related preeclampsia. However, the overlapping physicochemical and structural characteristics of different types of extracellular vesicles have hindered the consolidation of universally accepted and standardized purification or enrichment protocols. Thus, it has been recently demonstrated that the exosomal protein profile resulting from in-depth proteomics analyses is highly dependent on the preparation protocol used, which will determine the particle type specificity and the presence/absence of contaminating proteins.In this chapter, an isolation method of serum exosomes based on size-exclusion chromatography (SEC) using qEV columns (Izon) is described. We show that this method is fast and reliable, as the population of exosomes isolated is homogeneous in terms of size, morphology, and protein composition. This exosome enrichment method is compatible with downstream qualitative and quantitative proteomic analysis of the samples.

Preparation and Immunoaffinity Depletion of Fresh Frozen Tissue Homogenates for Mass Spectrometry-Based Proteomics in the Context of Drug Target/Biomarker Discovery

The discovery of novel drug targets and biomarkers via mass spectrometry (MS)-based proteomic analysis of clinical specimens has proven to be challenging. The wide dynamic range of protein concentration in clinical specimens and the high background/noise originating from highly abundant proteins in tissue homogenates and serum/plasma encompass two major analytical obstacles. Immunoaffinity depletion of highly abundant blood-derived proteins from serum/plasma is a well-established approach adopted by numerous researchers; however, the utilization of this technique for immunodepletion of tissue homogenates obtained from fresh frozen clinical specimens is lacking. We first developed immunoaffinity depletion of highly abundant blood-derived proteins from tissue homogenates, using renal cell carcinoma as a model disease, and followed this study by applying it to different tissue types. Tissue homogenate immunoaffinity depletion of highly abundant proteins may be equally important as is the recognized need for depletion of serum/plasma, enabling more sensitive MS-based discovery of novel drug targets, and/or clinical biomarkers from complex clinical samples. Provided is a detailed protocol designed to guide the researcher through the preparation and immunoaffinity depletion of fresh frozen tissue homogenates for two-dimensional liquid chromatography, tandem mass spectrometry (2D-LC-MS/MS)-based molecular profiling of tissue specimens in the context of drug target and/or biomarker discovery.

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.

Proteomic Analysis of Mesenchymal Stem Cells

Mesenchymal stem or stromal cells (MSCs) are of great interest in biomedical sciences and disease treatment because of their multipotency and wide range of applications for tissue repair and suppression of the immune system. Proteomic analysis of these unique cells has contributed to the identification of important pathways utilized by MSCs to differentiate into distinct tissues as well as important proteins responsible for their special function in vivo and in vitro. However, comparison of proteomic studies in MSCs still suffers from the heterogeneity of MSC preparations. In addition, as proteomics technology advances, several studies can be revisited in order to increase the depth of analysis and, therefore, elucidate more refined mechanisms involved in MSC functionalities. Here, we present detailed protocols to obtain MSCs, as well as protocols to perform in-depth profiling and quantification of alterations in MSC proteomes.

Simulation of the Protein-Shedding Kinetics of a Fully Vascularized Tumor

Circulating biomarkers are of significant interest for cancer detection and treatment personalization. However, the biophysical processes that determine how proteins are shed from cancer cells or their microenvironment, diffuse through tissue, enter blood vasculature, and persist in circulation remain poorly understood. Since approaches primarily focused on experimental evaluation are incapable of measuring the shedding and persistence for every possible marker candidate, we propose an interdisciplinary computational/experimental approach that includes computational modeling of tumor tissue heterogeneity. The model implements protein production, transport, and shedding based on tumor vascularization, cell proliferation, hypoxia, and necrosis, thus quantitatively relating the tumor and circulating proteomes. The results highlight the dynamics of shedding as a function of protein diffusivity and production. Linking the simulated tumor parameters to clinical tumor and vascularization measurements could potentially enable this approach to reveal the tumor-specific conditions based on the protein detected in circulation and thus help to more accurately manage cancer diagnosis and treatment.

Biomarkers for Diagnosis and Prognosis of Sinusoidal Obstruction Syndrome after Hematopoietic Cell Transplantation

Reliable, noninvasive methods for diagnosing and prognosing sinusoidal obstruction syndrome (SOS) early after hematopoietic cell transplantation (HCT) are needed. We used a quantitative mass spectrometry-based proteomics approach to identify candidate biomarkers of SOS by comparing plasma pooled from 20 patients with and 20 patients without SOS. Of 494 proteins quantified, we selected 6 proteins (L-Ficolin, vascular cell adhesion molecule-1 [VCAM1], tissue inhibitor of metalloproteinase-1, von Willebrand factor, intercellular adhesion molecule-1, and CD97) based on a differential heavy/light isotope ratio of at least 2 fold, information from the literature, and immunoassay availability. Next, we evaluated the diagnostic potential of these 6 proteins and 5 selected from the literature (suppression of tumorigenicity-2 [ST2], angiopoietin-2 (ANG2), hyaluronic acid [HA], thrombomodulin, and plasminogen activator inhibitor-1) in samples from 80 patients. The results demonstrate that together ST2, ANG2, L-Ficolin, HA, and VCAM1 compose a biomarker panel for diagnosis of SOS. L-Ficolin, HA, and VCAM1 also stratified patients at risk for SOS as early as the day of HCT. Prognostic Bayesian modeling for SOS onset based on L-Ficolin, HA, and VCAM1 levels on the day of HCT and clinical characteristics showed >80% correct prognosis of SOS onset. These biomarkers may provide opportunities for preemptive intervention to minimize SOS incidence and/or severity.

Neuronal Activity Promotes Glioma Growth through Neuroligin-3 Secretion

Active neurons exert a mitogenic effect on normal neural precursor and oligodendroglial precursor cells, the putative cellular origins of high-grade glioma (HGG). By using optogenetic control of cortical neuronal activity in a patient-derived pediatric glioblastoma xenograft model, we demonstrate that active neurons similarly promote HGG proliferation and growth in vivo. Conditioned medium from optogenetically stimulated cortical slices promoted proliferation of pediatric and adult patient-derived HGG cultures, indicating secretion of activity-regulated mitogen(s). The synaptic protein neuroligin-3 (NLGN3) was identified as the leading candidate mitogen, and soluble NLGN3 was sufficient and necessary to promote robust HGG cell proliferation. NLGN3 induced PI3K-mTOR pathway activity and feedforward expression of NLGN3 in glioma cells. NLGN3 expression levels in human HGG negatively correlated with patient overall survival. These findings indicate the important role of active neurons in the brain tumor microenvironment and identify secreted NLGN3 as an unexpected mechanism promoting neuronal activity-regulated cancer growth.

Search for breast cancer biomarkers in fractionated serum samples by protein profiling with SELDI-TOF MS

BACKGROUND

Many high-abundant acute phase reactants have been previously detected as potential breast cancer biomar-kers. However, they are unlikely to be specific for breast cancer. Cancer-specific biomarkers are thought to be among the lower abundant proteins.

METHODS

We aimed to detect lower abundant discriminating proteins by performing serum fractionation by strong anion exchange chromatography preceding protein profiling with SELDI-TOF MS. In a pilot study, we tested the different fractions resulting from fractionation, on several array types. Fraction 3 on IMAC30 and Fraction 6 on Q10 yielded the most discriminative proteins and were used for serum protein profiling of 73 incident breast cancer cases and 73 matched controls.

RESULTS

Eight peaks showed statistically significantly different intensities between cases and controls (P⧁0.05), and had less than 10% chance to be a false-positive finding. Seven of these were tentatively identified as apolipoprotein C-II (m/z 8,909), oxidized apolipoprotein C-II (m/z 8,925), apolipoprotein C-III (m/z 8,746), fragment of coagulation factor XIIIa (m/z 3,959), heterodimer of apolipoprotein A-I and apolipoprotein A-II (m/z 45,435), hemoglobin B-chain (m/z 15,915), and post-translational modified hemoglobin (m/z 15,346).

CONCLUSION

By extensive serum fractionation, we detected many more proteins than in previous studies without fractionation. However, discriminating proteins were still high abundant. Results indicate that either lower abundant proteins are less distinctive, or more rigorous fractionation and selective protein depletion, or a more sensitive assay, are needed to detect lower abundant discriminative proteins.

Optimization of plasma sample pretreatment for quantitative analysis using iTRAQ labeling and LC-MALDI-TOF/TOF

Shotgun proteomic methods involving iTRAQ (isobaric tags for relative and absolute quantitation) peptide labeling facilitate quantitative analyses of proteomes and searches for useful biomarkers. However, the plasma proteome's complexity and the highly dynamic plasma protein concentration range limit the ability of conventional approaches to analyze and identify a large number of proteins, including useful biomarkers. The goal of this paper is to elucidate the best approach for plasma sample pretreatment for MS- and iTRAQ-based analyses. Here, we systematically compared four approaches, which include centrifugal ultrafiltration, SCX chromatography with fractionation, affinity depletion, and plasma without fractionation, to reduce plasma sample complexity. We generated an optimized protocol for quantitative protein analysis using iTRAQ reagents and an UltrafleXtreme (Bruker Daltonics) MALDI TOF/TOF mass spectrometer. Moreover, we used a simple, rapid, efficient, but inexpensive sample pretreatment technique that generated an optimal opportunity for biomarker discovery. We discuss the results from the four sample pretreatment approaches and conclude that SCX chromatography without affinity depletion is the best plasma sample preparation pretreatment method for proteome analysis. Using this technique, we identified 1,780 unique proteins, including 1,427 that were quantified by iTRAQ with high reproducibility and accuracy.

A search for novel cancer/testis antigens in lung cancer identifies VCX/Y genes, expanding the repertoire of potential immunotherapeutic targets

Cancer/testis (CT) antigens are potential immunotherapeutic targets in cancer. However, the expression of particular antigens is limited to a subset of tumors of a given type. Thus, there is a need to identify antigens with complementary expression patterns for effective therapeutic intervention. In this study, we searched for genes that were distinctly expressed at a higher level in lung tumor tissue and the testes compared with other nontumor tissues and identified members of the VCX/Y gene family as novel CT antigens. VCX3A, a member of the VCX/Y gene family, was expressed at the protein level in approximately 20% of lung adenocarcinomas and 35% of squamous cell carcinomas, but not expressed in normal lung tissues. Among CT antigens with concordant mRNA and protein expression levels, four CT antigens, XAGE1, VCX, IL13RA2, and SYCE1, were expressed, alone or in combination, in about 80% of lung adenocarcinoma tumors. The CT antigen VCX/Y gene family broadens the spectrum of CT antigens expressed in lung adenocarcinomas for clinical applications.

Creation of a federated database of blood proteins: a powerful new tool for finding and characterizing biomarkers in serum

Protein biomarkers offer major benefits for diagnosis and monitoring of disease processes. Recent advances in protein mass spectrometry make it feasible to use this very sensitive technology to detect and quantify proteins in blood. To explore the potential of blood biomarkers, we conducted a thorough review to evaluate the reliability of data in the literature and to determine the spectrum of proteins reported to exist in blood with a goal of creating a Federated Database of Blood Proteins (FDBP). A unique feature of our approach is the use of a SQL database for all of the peptide data; the power of the SQL database combined with standard informatic algorithms such as BLAST and the statistical analysis system (SAS) allowed the rapid annotation and analysis of the database without the need to create special programs to manage the data. Our mathematical analysis and review shows that in addition to the usual secreted proteins found in blood, there are many reports of intracellular proteins and good agreement on transcription factors, DNA remodelling factors in addition to cellular receptors and their signal transduction enzymes. Overall, we have catalogued about 12,130 proteins identified by at least one unique peptide, and of these 3858 have 3 or more peptide correlations. The FDBP with annotations should facilitate testing blood for specific disease biomarkers.

Respiratory Proteomics Today: Are Technological Advances for the Identification of Biomarker Signatures Catching up with Their Promise? A Critical Review of the Literature in the Decade 2004-2013

To improve the knowledge on a variety of severe disorders, research has moved from the analysis of individual proteins to the investigation of all proteins expressed by a tissue/organism. This global proteomic approach could prove very useful: (i) for investigating the biochemical pathways involved in disease; (ii) for generating hypotheses; or (iii) as a tool for the identification of proteins differentially expressed in response to the disease state. Proteomics has not been used yet in the field of respiratory research as extensively as in other fields, only a few reproducible and clinically applicable molecular markers, which can assist in diagnosis, having been currently identified. The continuous advances in both instrumentation and methodology, which enable sensitive and quantitative proteomic analyses in much smaller amounts of biological material than before, will hopefully promote the identification of new candidate biomarkers in this area. The aim of this report is to critically review the application over the decade 2004-2013 of very sophisticated technologies to the study of respiratory disorders. The observed changes in protein expression profiles from tissues/fluids of patients affected by pulmonary disorders opens the route for the identification of novel pathological mediators of these disorders.

The secretome analysis by high-throughput proteomics and multiple reaction monitoring (MRM)

The secretome is a sub-proteome of great interest in several fields of biomedical sciences, especially as a source of diagnostics and therapeutic targets. Proteomics has been contributing significantly to elucidate the secretome of a great diversity of cells, tissues, and organisms, turning profiles of thousands of proteins a usual practice. After elucidation of long protein lists, targeted proteomics also plays important roles in accurate quantification and validation of such secreted proteins. Here we present detailed protocols to explore and quantify the secretome of cancer cells, even though this protocol can be employed to any kind of biological material.

Analysis of the plasma proteome in COPD: Novel low abundance proteins reflect the severity of lung remodeling

The search for COPD biomarkers has largely employed a targeted approach that focuses on plasma proteins involved in the systemic inflammatory response and in lung injury and repair. This proof of concept study was designed to test the idea that an open, unbiased, in-depth proteomics approach could identify novel, low abundance plasma proteins i.e., ng/mL concentration, which could serve as potential biomarkers. Differentially expressed proteins were identified in a discovery group with severe COPD (FEV1 <45% predicted; n = 10). Subjects with normal lung function matched for age, sex, ethnicity and smoking history served as controls (n = 10). Pooled plasma from each group was exhaustively immunodepleted of abundant proteins, d separated by 1-D gel electrophoresis and extensively fractionated prior to LC-tandem mass spectroscopy (GeLC-MS). Thirty one differentially expressed proteins were identified in the discovery group including markers of lung defense against oxidant stress, alveolar macrophage activation, and lung tissue injury and repair. Four of the 31 proteins (i.e., GRP78, soluble CD163, IL1AP and MSPT9) were measured in a separate verification group of 80 subjects with varying COPD severity by immunoassay. All 4 were significantly altered in COPD and 2 (GRP78 and soluble CD163) correlated with both FEV1 and the extent of emphysema. In-depth, plasma proteomic analysis identified a group of novel, differentially expressed, low abundance proteins that reflect known pathogenic mechanisms and the severity of lung remodeling in COPD. These proteins may also prove useful as COPD biomarkers.

A novel soluble form of Tim-3 associated with severe graft-versus-host disease

The T cell Ig and mucin domain 3 (Tim-3) receptor has been implicated as a negative regulator of adaptive immune responses. We have utilized a proteomic strategy to identify novel proteins associated with graft versus host disease (GVHD) after allogeneic hematopoietic cell transplantation (HCT). Mass spectrometry analysis of plasma from subjects with mid-gut and upper-gut GVHD compared with those without GVHD identified increased levels of a protein identified with high confidence as Tim-3. A follow-up validation study using an immunoassay to measure Tim-3 levels in individual plasma samples from 127 patients demonstrated significantly higher plasma Tim-3 concentrations in patients with the more severe mid-gut GVHD, compared with those with upper-gut GVHD (P = .005), patients without GVHD (P = .002), and normal controls (P < .0001). Surface expression of Tim-3 was increased on CD8(+) T cells from patients with grade 2 to 4 acute GVHD (P = .01). Mass spectrometry-based profiling of plasma from multiple subjects diagnosed with common diseases provided evidence for restricted release of soluble Tim-3 in the context of GVHD. These findings have mechanistic implications for the development of novel strategies for targeting the Tim-3 immune regulatory pathway as an approach to improving control of GVHD.

ST2 as a marker for risk of therapy-resistant graft-versus-host disease and death

BACKGROUND

No plasma biomarkers are associated with the response of acute graft-versus-host disease (GVHD) to therapy after allogeneic hematopoietic stem-cell transplantation.

METHODS

We compared 12 biomarkers in plasma obtained a median of 16 days after therapy initiation from 10 patients with a complete response by day 28 after therapy initiation and in plasma obtained from 10 patients with progressive GVHD during therapy. The lead biomarker, suppression of tumorigenicity 2 (ST2), was measured at the beginning of treatment for GVHD in plasma from 381 patients and during the first month after transplantation in three independent sets totaling 673 patients to determine the association of this biomarker with treatment-resistant GVHD and 6-month mortality after treatment or transplantation.

RESULTS

Of the 12 markers, ST2 had the most significant association with resistance to GVHD therapy and subsequent death without relapse. As compared with patients with low ST2 values at therapy initiation, patients with high ST2 values were 2.3 times as likely to have treatment-resistant GVHD (95% confidence interval [CI], 1.5 to 3.6) and 3.7 times as likely to die within 6 months after therapy (95% CI, 2.3 to 5.9). Patients with low ST2 values had lower mortality without relapse than patients with high ST2 values, regardless of the GVHD grade (11% vs. 31% among patients with grade I or II GVHD and 14% vs. 67% among patients with grade III or IV GVHD, P<0.001 for both comparisons). Plasma ST2 values at day 14 after transplantation were associated with 6-month mortality without relapse, regardless of the intensity of the conditioning regimen.

CONCLUSIONS

ST2 levels measured at the initiation of therapy for GVHD and during the first month after transplantation improved risk stratification for treatment-resistant GVHD and death without relapse after transplantation. (Funded by the National Institutes of Health.)

Evaluation and optimization of mass spectrometric settings during data-dependent acquisition mode: focus on LTQ-Orbitrap mass analyzers

Mass-spectrometry-based proteomics has evolved as the preferred method for the analysis of complex proteomes. Undoubtedly, recent advances in mass spectrometry instrumentation have greatly enhanced proteomic analysis. A popular instrument platform in proteomics research is the LTQ-Orbitrap mass analyzer. In this tutorial, we discuss the significance of evaluating and optimizing mass spectrometric settings on the LTQ-Orbitrap during CID data-dependent acquisition (DDA) mode to improve protein and peptide identification rates. We focus on those MS and MS/MS parameters that have been systematically examined and evaluated by several researchers and are commonly used during DDA. More specifically, we discuss the effect of mass resolving power, preview mode for FTMS scan, monoisotopic precursor selection, signal threshold for triggering MS/MS events, number of microscans per MS/MS scan, number of MS/MS events, automatic gain control target value (ion population) for MS and MS/MS, maximum ion injection time for MS/MS, rapid and normal scan rate, and prediction of ion injection time. We furthermore present data from the latest generation LTQ-Orbitrap system, the Orbitrap Elite, along with recommended MS and MS/MS parameters. The Orbitrap Elite outperforms the Orbitrap Classic in terms of scan speed, sensitivity, dynamic range, and resolving power and results in higher identification rates. Several of the optimized MS parameters determined on the LTQ-Orbitrap Classic and XL were easily transferable to the Orbitrap Elite, whereas others needed to be reevaluated. Finally, the Q Exactive and HCD are briefly discussed, as well as sample preparation, LC-optimization, and bioinformatics analysis. We hope this tutorial will serve as guidance for researchers new to the field of proteomics and assist in achieving optimal results.

A call for a fresh new look at the plasma proteome

Serum and plasma from which serum is derived represent a substantial challenge for proteomics due to their complexity. A landmark plasma proteome study was initiated a decade ago by the Human Proteome Organization (HUPO) that had as an objective to examine the capabilities of existing technologies. Given the advances in proteomics and the continued interest in the plasma proteome, it would timely reassess the depth and breadth of analysis of plasma that can be achieved with current methodology and instrumentation. A collaborative project to define the plasma proteome and its variation, with a plan to build a plasma proteome database would be timely.

Proteomics applied to transfusion plasma: the beginning of the story

'Safe blood' is and has always been the major concern in transfusion medicine. Plasma can undergo virus inactivation treatments based on physicochemical, photochemical or thermal methodologies for pathogen inactivation. The validation of these treatments is essentially based on clottability assays and clotting factors' titration; however, their impact on plasma proteins at the molecular level has not yet been evaluated. Proteomics appears as particularly adapted to identify, to localize and, consequently, to correlate these modifications to the biological activity change. At the crossroads of biology and analytical sciences, proteomics is the large-scale study of proteins in tissues, physiological fluids or cells at a given moment and in a precise environment. The proteomic strategy is based on a set of methodologies involving separative techniques like mono- and bidimensional gel electrophoresis and chromatography, analytical techniques, especially mass spectrometry, and bioinformatics. Even if plasma has been extensively studied since the very beginning of proteomics, its application to transfusion medicine has just begun. In the first part of this review, we present the principles of proteomics analysis. Then, we propose a state of the art of proteomics applied to plasma analysis. Finally, the use of proteomics for the evaluation of the impact of storage conditions and pathogen inactivation treatments applied to transfusion plasma and for the evaluation of therapeutic protein fractionated is discussed.

Identification of potential glycan cancer markers with sialic acid attached to sialic acid and up-regulated fucosylated galactose structures in epidermal growth factor receptor secreted from A431 cell line

We have used powerful HPLC-mass spectrometric approaches to characterize the secreted form of epidermal growth factor receptor (sEGFR). We demonstrated that the amino acid sequence lacked the cytoplasmic domain and was consistent with the primary sequence reported for EGFR purified from a human plasma pool. One of the sEGFR forms, attributed to the alternative RNA splicing, was also confirmed by transcriptional analysis (RNA sequencing). Two unusual types of glycan structures were observed in sEGFR as compared with membrane-bound EGFR from the A431 cell line. The unusual glycan structures were di-sialylated glycans (sialic acid attached to sialic acid) at Asn-151 and N-acetylhexosamine attached to a branched fucosylated galactose with N-acetylglucosamine moieties (HexNAc-(Fuc)Gal-GlcNAc) at Asn-420. These unusual glycans at specific sites were either present at a much lower level or were not observable in membrane-bound EGFR present in the A431 cell lysate. The observation of these di-sialylated glycan structures was consistent with the observed expression of the corresponding α-N-acetylneuraminide α-2,8-sialyltransferase 2 (ST8SiA2) and α-N-acetylneuraminide α-2,8-sialyltransferase 4 (ST8SiA4), by quantitative real time RT-PCR. The connectivity present at the branched fucosylated galactose was also confirmed by methylation of the glycans followed by analysis with sequential fragmentation in mass spectrometry. We hypothesize that the presence of such glycan structures could promote secretion via anionic or steric repulsion mechanisms and thus facilitate the observation of these glycan forms in the secreted fractions. We plan to use this model system to facilitate the search for novel glycan structures present at specific sites in sEGFR as well as other secreted oncoproteins such as Erbb2 as markers of disease progression in blood samples from cancer patients.

Affinity depletion of plasma and serum for mass spectrometry-based proteome analysis

Protein biomarker discovery in blood plasma and serum is severely hampered by the vast dynamic range of the proteome. With protein concentrations spanning 12 orders of magnitude, conventional mass spectrometric analysis allows for detection of only a few low-abundance proteins. Prior depletion of high-abundant proteins from the sample can increase analytical depth considerably and has become a widely used practice. We describe in detail an affinity depletion method that selectively removes 14 of the most abundant proteins in plasma and serum.

Have we made progress in the treatment of GVHD?

One reason for the lack of progress in the treatment of acute graft versus host disease (GVHD) is the lack of reliable biomarkers. GVHD of the gastrointestinal (GI) tract is closely associated with non-relapse mortality (NRM) following hematopoietic cell transplantation (HCT). Using an unbiased, large-scale, quantitative proteomic discovery approach, we identified candidate biomarkers that were increased in plasma from HCT patients with GI GVHD. We then validated the lead candidate, REG3α, by ELISA in samples from more than 1000 HCT patients from three transplant centers. Plasma REG3α concentrations were 3-fold higher in patients at GI GVHD onset than in all other patients. REG3α concentrations correlated most closely with lower GI GVHD at GVHD onset and predicted response to therapy at 4 weeks, 1-year NRM, and 1-year survival (P ≤ 0.001). Multivariate analysis showed that advanced clinical stage, severe histologic damage, and high REG3α concentrations at the diagnosis of GVHD independently predicted 1-year NRM, which progressively increased with higher numbers of onset risk factors present. We conclude that REG3α is a plasma biomarker of GI GVHD that can be combined with clinical stage and histologic grade to improve risk stratification of patients, perhaps providing a platform for advances in the treatment of high-risk GVHD.

Unleashing the power of proteomics to develop blood-based cancer markers

BACKGROUND

There is an urgent need for blood-based molecular tests to assist in the detection and diagnosis of cancers at an early stage, when curative interventions are still possible, and to predict and monitor response to treatment and disease recurrence. The rich content of proteins in blood that are impacted by tumor development and host factors provides an ideal opportunity to develop noninvasive diagnostics for cancer.

CONTENT

Mass spectrometry instrumentation has advanced sufficiently to allow the discovery of protein alterations directly in plasma across no less than 7 orders of magnitude of protein abundance. Moreover, the use of proteomics to harness the immune response in the form of seropositivity to tumor antigens has the potential to complement circulating protein biomarker panels for cancer detection. The depth of analysis currently possible in a discovery setting allows the detection of potential markers at concentrations of less than 1 μg/L. Such low concentrations may exceed the limits of detection of ELISAs and thus require the development of clinical assays with exquisite analytical sensitivity. Clearly the availability for discovery and validation of biospecimens that are highly relevant to the intended clinical application and have been collected, processed, and stored with the use of standard operating procedures is of crucial importance to the successful application of proteomics to the development of blood-based tests for cancer.

SUMMARY

The realization of the potential of proteomics to yield blood biomarkers will benefit from a collaborative approach and a substantial investment in resources.

Mass spectrometry for translational proteomics: progress and clinical implications

The utility of mass spectrometry (MS)-based proteomic analyses and their clinical applications have been increasingly recognized over the past decade due to their high sensitivity, specificity and throughput. MS-based proteomic measurements have been used in a wide range of biological and biomedical investigations, including analysis of cellular responses and disease-specific post-translational modifications. These studies greatly enhance our understanding of the complex and dynamic nature of the proteome in biology and disease. Some MS techniques, such as those for targeted analysis, are being successfully applied for biomarker verification, whereas others, including global quantitative analysis (for example, for biomarker discovery), are more challenging and require further development. However, recent technological improvements in sample processing, instrumental platforms, data acquisition approaches and informatics capabilities continue to advance MS-based applications. Improving the detection of significant changes in proteins through these advances shows great promise for the discovery of improved biomarker candidates that can be verified pre-clinically using targeted measurements, and ultimately used in clinical studies - for example, for early disease diagnosis or as targets for drug development and therapeutic intervention. Here, we review the current state of MS-based proteomics with regard to its advantages and current limitations, and we highlight its translational applications in studies of protein biomarkers.

Human mesenchymal stromal cell proteomics: contribution for identification of new markers and targets for medicine intervention

Mesenchymal stem or stromal cells (MSCs) have become of great interest for cell-based therapy owing to their roles in tissue repair and immune suppression. MSCs have the ability to differentiate into specialized tissues, including bone, cartilage and muscle, among several others. Furthermore, it has been found that MSCs can also serve as cellular factories that secrete mediators to stimulate in situ regeneration of injured tissues. Proteomics has contributed significantly to the identification of new proteins to improve cellular characterization of MSCs, to identify new targets for therapeutic intervention and to elucidate important pathways utilized by MSCs to differentiate into distinct tissues. As proteomics technology advances, several studies can be revisited and analyzed in depth, employing state-of-the-art approaches, helping to uncover the cellular mechanisms utilized by MSCs to exert their regenerative functionalities. In this article, we will review the progress made so far and discuss further opportunities for proteomics to contribute to the clinical applications of MSCs.

Clinical applications for biomarkers of acute and chronic graft-versus-host disease

Acute and chronic graft-versus-host disease (aGVHD, cGVHD) are serious complications of allogeneic hematopoietic cell transplantation. The complex pathophysiology of these disease processes is associated with immune system activation, the release of cytokines and chemokines, and alterations in cell populations. The blood levels of specific protein and cellular levels in patients with GVHD have correlated with the development, diagnosis, and prognosis of GVHD. Here, we review the most promising biomarkers for aGVHD and cGVHD with clinical relevance. The utility of GVHD biomarkers in clinical care of allogeneic hematopoietic cell transplantation recipients needs to be proven through clinical trials, and potential approaches to trial design are discussed.

Quantitative proteomic profiling identifies protein correlates to EGFR kinase inhibition

Clinical oncology is hampered by lack of tools to accurately assess a patient's response to pathway-targeted therapies. Serum and tumor cell surface proteins whose abundance, or change in abundance in response to therapy, differentiates patients responding to a therapy from patients not responding to a therapy could be usefully incorporated into tools for monitoring response. Here, we posit and then verify that proteomic discovery in in vitro tissue culture models can identify proteins with concordant in vivo behavior and further, can be a valuable approach for identifying tumor-derived serum proteins. In this study, we use stable isotope labeling of amino acids in culture (SILAC) with proteomic technologies to quantitatively analyze the gefitinib-related protein changes in a model system for sensitivity to EGF receptor (EGFR)-targeted tyrosine kinase inhibitors. We identified 3,707 intracellular proteins, 1,276 cell surface proteins, and 879 shed proteins. More than 75% of the proteins identified had quantitative information, and a subset consisting of 400 proteins showed a statistically significant change in abundance following gefitinib treatment. We validated the change in expression profile in vitro and screened our panel of response markers in an in vivo isogenic resistant model and showed that these were markers of gefitinib response and not simply markers of phospho-EGFR downregulation. In doing so, we also were able to identify which proteins might be useful as markers for monitoring response and which proteins might be useful as markers for a priori prediction of response.