Development of serum glycoproteomic profiling technique; simultaneous identification of glycosylation sites and site-specific quantification of glycan structure changes

Recent advances in N-glycan biomarker discovery among human diseases

N-glycans play important roles in a variety of biological processes. In recent years, analytical technologies with high resolution and sensitivity have advanced exponentially, enabling analysts to investigate N-glycomic changes in different states. Specific glycan and glycosylation signatures have been identified in multiple diseases, including cancer, autoimmune diseases, nervous system disorders, and metabolic and cardiovascular diseases. These glycans demonstrate comparable or superior indicating capability in disease diagnosis and prognosis over routine biomarkers. Moreover, synchronous glycan alterations concurrent with disease initiation and progression provide novel insights into pathogenetic mechanisms and potential treatment targets. This review elucidates the biological significance of N-glycans, compares the existing glycomic technologies, and delineates the clinical performance of N-glycans across a range of diseases.

The Utility of Differential Scanning Calorimetry Curves of Blood Plasma for Diagnosis, Subtype Differentiation and Predicted Survival in Lung Cancer

Early detection of lung cancer (LC) significantly increases the likelihood of successful treatment and improves LC survival rates. Currently, screening (mainly low-dose CT scans) is recommended for individuals at high risk. However, the recent increase in the number of LC cases unrelated to the well-known risk factors, and the high false-positive rate of low-dose CT, indicate a need to develop new, non-invasive methods for LC detection. Therefore, we evaluated the use of differential scanning calorimetry (DSC) for LC patients' diagnosis and predicted survival. Additionally, by applying mass spectrometry, we investigated whether changes in O- and N-glycosylation of plasma proteins could be an underlying mechanism responsible for observed differences in DSC curves of LC and control subjects. Our results indicate selected DSC curve features could be useful for differentiation of LC patients from controls with some capable of distinction between subtypes and stages of LC. DSC curve features also correlate with LC patients' overall/progression free survival. Moreover, the development of classification models combining patients' DSC curves with selected plasma protein glycosylation levels that changed in the presence of LC could improve the sensitivity and specificity of the detection of LC. With further optimization and development of the classification method, DSC could provide an accurate, non-invasive, radiation-free strategy for LC screening and diagnosis.

Identification of Fucosylated SERPINA1 as a Novel Plasma Marker for Pancreatic Cancer Using Lectin Affinity Capture Coupled with iTRAQ-Based Quantitative Glycoproteomics

Pancreatic cancer (PC) is an aggressive cancer with a high mortality rate, necessitating the development of effective diagnostic, prognostic and predictive biomarkers for disease management. Aberrantly fucosylated proteins in PC are considered a valuable resource of clinically useful biomarkers. The main objective of the present study was to identify novel plasma glycobiomarkers of PC using the iTRAQ quantitative proteomics approach coupled with Aleuria aurantia lectin (AAL)-based glycopeptide enrichment and isotope-coded glycosylation site-specific tagging, with a view to analyzing the glycoproteome profiles of plasma samples from patients with non-metastatic and metastatic PC and gallstones (GS). As a result, 22 glycopeptides with significantly elevated levels in plasma samples of PC were identified. Fucosylated SERPINA1 (fuco-SERPINA1) was selected for further validation in 121 plasma samples (50 GS and 71 PC) using an AAL-based reverse lectin ELISA technique developed in-house. Our analyses revealed significantly higher plasma levels of fuco-SERPINA1 in PC than GS subjects (310.7 ng/mL v.s. 153.6 ng/mL, p = 0.0114). Elevated fuco-SERPINA1 levels were associated with higher TNM stage (p = 0.024) and poorer prognosis for overall survival (log-rank test, p = 0.0083). The increased plasma fuco-SERPINA1 levels support the utility of this protein as a novel prognosticator for PC.

Resin and Magnetic Nanoparticle-Based Free Radical Probes for Glycan Capture, Isolation, and Structural Characterization

By combining the merits of solid supports and free radical activated glycan sequencing (FRAGS) reagents, we develop a multifunctional solid-supported free radical probe (SS-FRAGS) that enables glycan enrichment and characterization. SS-FRAGS comprises a solid support, free radical precursor, disulfide bond, pyridyl, and hydrazine moieties. Thio-activated resin and magnetic nanoparticles (MNPs) are chosen as the solid support to selectively capture free glycans via the hydrazine moiety, allowing for their enrichment and isolation. The disulfide bond acts as a temporary covalent linkage between the solid support and the captured glycan, allowing the release of glycans via the cleavage of the disulfide bond by dithiothreitol. The basic pyridyl functional group provides a site for the formation of a fixed charge, enabling detection by mass spectrometry and avoiding glycan rearrangement during collisional activation. The free radical precursor generates a nascent free radical upon collisional activation and thus simultaneously induces systematic and predictable fragmentation for glycan structure elucidation. A radical-driven glycan deconstruction diagram (R-DECON) is developed to visually summarize the MS² results and thus allow for the assembly of the glycan skeleton, making the differentiation of isobaric glycan isomers unambiguous. For application to a real-world sample, we demonstrate the efficacy of the SS-FRAGS by analyzing glycan structures enzymatically cleaved from RNase-B.

Relevance of MIC-1 in the Era of PSA as a Serum Based Predictor of Prostate Cancer: A Critical Evaluation

To reduce the ambiguity of contradictory observations in different studies regarding the expression level of Macrophage Inhibitory Cytokine-1 (MIC-1) in serum in prostate cancer (PC), benign prostatic hyperplasia (BPH) and healthy controls (HC), we designed this double-blind study. The study comprises 240 sera from PC, BPH and HC subjects. The expression level of MIC-1 in PC, BPH and HC were appraised using Western blot (WB) and ELISA based approach. WB and ELISA appraisal reveals that the expression level of MIC-1 is significantly higher in PC than in HC or BPH subjects. Regression analysis revealed a significant correlation between MIC-1 vs. PSA (r = 0.09; p < 0.001) and MIC-1 vs. GS (r = 0.7; p < 0.001). ROC analysis using discriminant predicted probability revealed that the MIC-1 was better than PSA. Moreover, the combination of MIC-1 and PSA was allowing 99.1% AUC for the differentiation of BPH + PC from HC, 97.9% AUC for differentiation of BPH from HC, 98.6% AUC for differentiation of PC from HC, and 96.7% AUC for the differentiation of PC from BPH. The augmented expression of MIC-1 in PC compared to BPH and HC subjects is in concurrent of the over-expression of MIC-1 in PC reports and confiscates the contradictory findings of other studies.

Glycans and glycoproteins as specific biomarkers for cancer

Protein glycosylation and other post-translational modifications are involved in potentially all aspects of human growth and development. Defective glycosylation has adverse effects on human physiological conditions and accompanies many chronic and infectious diseases. Altered glycosylation can occur at the onset and/or during tumor progression. Identifying these changes at early disease stages may aid in making decisions regarding treatments, as early intervention can greatly enhance survival. This review highlights some of the efforts being made to identify N- and O-glycosylation profile shifts in cancer using mass spectrometry. The analysis of single or panels of potential glycoprotein cancer markers are covered. Other emerging technologies such as global glycan release and site-specific glycosylation analysis and quantitation are also discussed. Graphical Abstract Steps involved in the biomarker discovery.

Quantitative mass spectrometric analysis of glycoproteins combined with enrichment methods

Mass spectrometry (MS) has been a core technology for high sensitive and high-throughput analysis of the enriched glycoproteome in aspects of quantitative assays as well as qualitative profiling of glycoproteins. Because it has been widely recognized that aberrant glycosylation in a glycoprotein may involve in progression of a certain disease, the development of efficient analysis tool for the aberrant glycoproteins is very important for deep understanding about pathological function of the glycoprotein and new biomarker development. This review first describes the protein glycosylation-targeting enrichment technologies mainly employing solid-phase extraction methods such as hydrizide-capturing, lectin-specific capturing, and affinity separation techniques based on porous graphitized carbon, hydrophilic interaction chromatography, or immobilized boronic acid. Second, MS-based quantitative analysis strategies coupled with the protein glycosylation-targeting enrichment technologies, by using a label-free MS, stable isotope-labeling, or targeted multiple reaction monitoring (MRM) MS, are summarized with recent published studies.

Mass spectrometry-based N-glycoproteomics for cancer biomarker discovery

Glycosylation is estimated to be found in over 50% of human proteins. Aberrant protein glycosylation and alteration of glycans are closely related to many diseases. More than half of the cancer biomarkers are glycosylated-proteins, and specific glycoforms of glycosylated-proteins may serve as biomarkers for either the early detection of disease or the evaluation of therapeutic efficacy for treatment of diseases. Glycoproteomics, therefore, becomes an emerging field that can make unique contributions to the discovery of biomarkers of cancers. The recent advances in mass spectrometry (MS)-based glycoproteomics, which can analyze thousands of glycosylated-proteins in a single experiment, have shown great promise for this purpose. Herein, we described the MS-based strategies that are available for glycoproteomics, and discussed the sensitivity and high throughput in both qualitative and quantitative manners. The discovery of glycosylated-proteins as biomarkers in some representative diseases by employing glycoproteomics was also summarized.

Glycoprotein biomarker panel for pancreatic cancer discovered by quantitative proteomics analysis

Pancreatic cancer is a lethal disease where specific early detection biomarkers would be very valuable to improve outcomes in patients. Many previous studies have compared biosamples from pancreatic cancer patients with healthy controls to find potential biomarkers. However, a range of related disease conditions can influence the performance of these putative biomarkers, including pancreatitis and diabetes. In this study, quantitative proteomics methods were applied to discover potential serum glycoprotein biomarkers that distinguish pancreatic cancer from other pancreas related conditions (diabetes, cyst, chronic pancreatitis, obstructive jaundice) and healthy controls. Aleuria aurantia lectin (AAL) was used to extract fucosylated glycoproteins and then both TMT protein-level labeling and label-free quantitative analysis were performed to analyze glycoprotein differences from 179 serum samples across the six different conditions. A total of 243 and 354 serum proteins were identified and quantified by label-free and TMT protein-level quantitative strategies, respectively. Nineteen and 25 proteins were found to show significant differences in samples between the pancreatic cancer and other conditions using the label-free and TMT strategies, respectively, with 7 proteins considered significant in both methods. Significantly different glycoproteins were further validated by lectin-ELISA and ELISA assays. Four candidates were identified as potential markers with profiles found to be highly complementary with CA 19–9 (p < 0.001). Obstructive jaundice (OJ) was found to have a significant impact on the performance of every marker protein, including CA 19–9. The combination of α-1-antichymotrypsin (AACT), thrombospondin-1 (THBS1), and haptoglobin (HPT) outperformed CA 19–9 in distinguishing pancreatic cancer from normal controls (AUC = 0.95), diabetes (AUC = 0.89), cyst (AUC = 0.82), and chronic pancreatitis (AUC = 0.90). A marker panel of AACT, THBS1, HPT, and CA 19–9 showed a high diagnostic potential in distinguishing pancreatic cancer from other conditions with OJ (AUC = 0.92) or without OJ (AUC = 0.95).

Glycoproteomics using fluid-based specimens in the discovery of lung cancer protein biomarkers: promise and challenge

Lung cancer is the leading cancer in the United States and worldwide. In spite of the rapid progression in personalized treatments, the overall survival rate of lung cancer patients is still suboptimal. Over the past decade, tremendous efforts have been focused on the discovery of protein biomarkers to facilitate the early detection and monitoring of lung cancer progression during treatment. In addition to tumor tissues and cancer cell lines, a variety of biological material has been studied. Particularly in recent years, studies using fluid-based specimen or so-called "fluid-biopsy" specimens have progressed rapidly. Fluid specimens are relatively easier to collect than tumor tissue, and they can be repeatedly sampled during the disease progression. Glycoproteins are the major content of fluid specimens and have long been recognized to play fundamental roles in many physiological and pathological processes. In this review, we focus the discussion on recent advances of glycoproteomics, particularly in the identification of potential glyco protein biomarkers using fluid-based specimens in lung cancer. The purpose of this review is to summarize current strategies, achievements, and perspectives in the field. This insight will highlight the discovery of tumor-associated glycoprotein biomarkers in lung cancer and their potential clinical applications.

Absolute quantitation of immunoglobulin G and its glycoforms using multiple reaction monitoring

Studies aimed toward glycan biomarker discovery have focused on glycan characterization by the global profiling of released glycans. Site-specific glycosylation analysis is less developed but may provide new types of biomarkers with higher sensitivity and specificity. Quantitation of peptide-conjugated glycans directly facilitates the differential analysis of distinct glycoforms associated with specific proteins at distinct sites. We have developed a method using MRM to monitor protein glycosylation normalized to absolute protein concentrations to examine quantitative changes in glycosylation at a site-specific level. This new approach provides information regarding both the absolute amount of protein and the site-specific glycosylation profile and will thus be useful to determine if altered glycosylation profiles in serum/plasma are due to a change in protein glycosylation or a change in protein concentration. The remarkable sensitivity and selectivity of MRM enable the detection of low abundance IgG glycopeptides, even when IgG was digested directly in serum with no cleanup prior to the liquid chromatography. Our results show a low limit of detection of 60 amol and a wide dynamic range of 3 orders magnitude for IgG protein quantitation. The results show that IgG glycopeptides can be analyzed directly from serum (without enrichment) and yield more accurate abundances when normalized to the protein content. This report represents the most comprehensive study so far of the use of multiple reaction monitoring for the quantitation of glycoproteins and their glycosylation patterns in biofluids.

Characterization of disease-associated N-linked glycoproteins

N-linked glycoproteins play important roles in biological processes, including cell-to-cell recognition, growth, differentiation, and programmed cell death. Specific N-linked glycoprotein changes are associated with disease progression and identification of these N-linked glycoproteins has potential for use in disease diagnosis, prognosis, and prediction of treatments. In this review, we summarize common strategies for N-linked glycoprotein characterization and applications of these strategies to identification of glycoprotein changes associated with disease states. We also review the N-linked glycoproteins altered in diseases such as breast cancer, lung cancer, and prostate cancer. Although assays for these glycoproteins have potential clinical utility, research is needed to translate these glycoproteins to clinical biomarkers.

Capillary isoelectric focusing-tandem mass spectrometry and reversed-phase liquid chromatography-tandem mass spectrometry for quantitative proteomic analysis of differentiating PC12 cells by eight-plex isobaric tags for relative and absolute quantification

We report the application of capillary isoelectric focusing for quantitative analysis of a complex proteome. Biological duplicates were generated from PC12 cells at days 0, 3, 7, and 12 following treatment with nerve growth factor. These biological duplicates were digested with trypsin, labeled using eight-plex isobaric tags for relative and absolute quantification (iTRAQ) chemistry, and pooled. The pooled peptides were separated into 25 fractions using reversed-phase liquid chromatography (RPLC). Technical duplicates of each fraction were separated by capillary isoelectric focusing (cIEF) using a set of amino acids as ampholytes. The cIEF column was interfaced to an Orbitrap Velos mass spectrometer with an electrokinetically pumped sheath-flow nanospray interface. This HPLC-cIEF-electrospray-tandem mass spectrometry (ESI-MS/MS) approach identified 835 protein groups and produced 2,329 unique peptides IDs. The biological duplicates were analyzed in parallel using conventional strong-cation exchange (SCX)-RPLC-ESI-MS/MS. The iTRAQ peptides were first separated into eight fractions using SCX. Each fraction was then analyzed by RPLC-ESI-MS/MS. The SCX-RPLC approach generated 1,369 protein groups and 3,494 unique peptide IDs. For protein quantitation, 96 and 198 differentially expressed proteins were obtained with RPLC-cIEF and SCX-RPLC, respectively. The combined set identified 231 proteins. Protein expression changes measured by RPLC-cEIF and SCX-RPLC were highly correlated.

The GlycoFilter: a simple and comprehensive sample preparation platform for proteomics, N-glycomics and glycosylation site assignment

Current strategies to study N-glycoproteins in complex samples are often discrete, focusing on either N-glycans or N-glycosites enriched by sugar-based techniques. In this study we report a simple and rapid sample preparation platform, the GlycoFilter, which allows a comprehensive characterization of N-glycans, N-glycosites, and proteins in a single workflow. Both PNGase F catalyzed de-N-glycosylation and trypsin digestions are accelerated by microwave irradiation and performed sequentially in a single spin filter. Both N-glycans and peptides (including de-N-glycosylated peptides) are separately collected by filtration. The condition to effectively collect complex and heterogeneous N-glycans was established on model glycoproteins, bovine ribonuclease B, bovine fetuin, and human serum IgG. With this platform, the N-glycome, N-glycoproteome and proteome of human urine and plasma were characterized. Overall, a total of 865 and 295 N-glycosites were identified from three pairs of urine and plasma samples, respectively. Many sites were defined unambiguously as partially occupied by the detection of their nonsugar-modified peptides (128 from urine and 61 from plasma), demonstrating that partial occupancy of N-glycosylation occurs frequently. Given the likely high prevalence and variability of partial occupancy, glycoprotein quantification based exclusively on deglycosylated peptides may lead to inaccurate quantification.

Preapoptotic protease calpain-2 is frequently suppressed in adult T-cell leukemia

Adult T-cell leukemia (ATL) is one of the most aggressive hematologic malignancies caused by human T-lymphotropic virus type 1 (HTLV-1) infection. The prognosis of ATL is extremely poor; however, effective strategies for diagnosis and treatment have not been established. To identify novel therapeutic targets and diagnostic markers for ATL, we employed focused proteomic profiling of the CD4(+)CD25(+)CCR4(+) T-cell subpopulation in which HTLV-1-infected cells were enriched. Comprehensive quantification of 14 064 peptides and subsequent 2-step statistical analysis using 29 cases (6 uninfected controls, 5 asymptomatic carriers, 9 HTLV-1-associated myelopathy/tropical spastic paraparesis patients, 9 ATL patients) identified 91 peptide determinants that statistically classified 4 clinical groups with an accuracy rate of 92.2% by cross-validation test. Among the identified 17 classifier proteins, α-II spectrin was drastically accumulated in infected T cells derived from ATL patients, whereas its digestive protease calpain-2 (CAN2) was significantly downregulated. Further cell cycle analysis and cell growth assay revealed that rescue of CAN2 activity by overexpressing constitutively active CAN2 (Δ(19)CAN2) could induce remarkable cell death on ATL cells accompanied by reduction of α-II spectrin. These results support that proteomic profiling of HTLV-1-infected T cells could provide potential diagnostic biomarkers and an attractive resource of therapeutic targets for ATL.

Solid-phase glycan isolation for glycomics analysis

Glycosylation is one of the most significant protein PTMs. The biological activities of proteins are dramatically changed by the glycans associated with them. Thus, structural analysis of the glycans of glycoproteins in complex biological or clinical samples is critical in correlation with the functions of glycans with diseases. Profiling of glycans by HPLC-MS is a commonly used technique in analyzing glycan structures and quantifying their relative abundance in different biological systems. Methods relied on MS require isolation of glycans from negligible salts and other contaminant ions since salts and ions may interfere with the glycans, resulting in poor glycan ionization. To accomplish those objectives, glycan isolation and clean-up methods including SPE, liquid-phase extraction, chromatography, and electrophoresis have been developed. Traditionally, glycans are isolated from proteins or peptides using a combination of hydrophobic and hydrophilic columns: proteins and peptides remain on hydrophobic absorbent while glycans, salts, and other hydrophilic reagents are collected as flowthrough. The glycans in the flowthrough are then purified through graphite-activated carbon column by hydrophilic interaction LC. Yet, the drawback in these affinity-based approaches is nonspecific binding. As a result, chemical methods by hydrazide or oxime have been developed for solid-phase isolation of glycans with high specificity and yield. Combined with high-resolution MS, specific glycan isolation techniques provide tremendous potentials as useful tools for glycomics analysis.

Large-scale quantitative glycoproteomics analysis of site-specific glycosylation occupancy

Disease-associated aberrant glycosylation may be protein specific and glycosylation site specific. Quantitative assessment of glycosylation changes at a site-specific molecular level may represent one of the initial steps for systematically revealing the glycosylation abnormalities associated with a disease or biological state. Comparative quantitative profiling of glycoproteome to provide accurate quantification of site-specific glycosylation occupancy has been a challenging task, requiring a concerted approach drawing from a variety of techniques. In this report, we present a quantitative glycoproteomics method that allows global scale identification and comparative quantification of glycosylation site occupancy using mass spectrometry. We further demonstrated this approach by quantitatively characterizing the N-glycoproteome of human pancreas.

Application of glycoproteomics for the discovery of biomarkers in lung cancer

Lung cancer is the leading cause of cancer-related deaths in the United States. Approximately 40-60% of lung cancer patients present with locally advanced or metastatic disease at the time of diagnosis. Lung cancer development and progression are a multistep process that is characterized by abnormal gene and protein expressions ultimately leading to phenotypic change. Glycoproteins have long been recognized to play fundamental roles in many physiological and pathological processes, particularly in cancer genesis and progression. In order to improve the survival rate of lung cancer patients, the discovery of early diagnostic and prognostic biomarkers is urgently needed. Herein, we reviewed the recent technological developments of glycoproteomics and published data in the field of glycoprotein biomarkers in lung cancer, and discussed their utility and limitations for the discovery of potential biomarkers in lung cancer. Although numerous papers have already acknowledged the importance of the discovery of cancer biomarkers, the systemic study of glycoproteins in lung cancer using glycoproteomic approaches is still suboptimal. Recent development in the glycoproteomics will provide new platforms for identification of potential protein biomarkers in lung cancers.

Glycoproteomics enabled by tagging sialic acid- or galactose-terminated glycans

In this paper, we present two complementary strategies for enrichment of glycoproteins on living cells that combine the desirable attributes of "robust enrichment" afforded by covalent-labeling techniques and "specificity for glycoproteins" typically provided by lectin or antibody affinity reagents. Our strategy involves the selective introduction of aldehydes either into sialic acids by periodate oxidation (periodate oxidation and aniline-catalyzed oxime ligation (PAL)) or into terminal galactose and N-acetylgalactosamine residues by galactose oxidase (galactose oxidase and aniline-catalyzed oxime ligation (GAL)), followed by aniline-catalyzed oxime ligation with aminooxy-biotin to biotinylate the glycans of glycoprotein subpopulations with high efficiency and cell viability. As expected, the two methods exhibit reciprocal tagging efficiencies when applied to fully sialylated cells compared with sialic acid-deficient cells. To assess the utility of these labeling methods for glycoproteomics, we enriched the PAL- and GAL-labeled (biotinylated) glycoproteome by adsorption onto immobilized streptavidin. Glycoprotein identities (IDs) and N-glycosylation site information were then obtained by liquid chromatography-tandem mass spectrometry on total tryptic peptides and on peptides subsequently released from N-glycans still bound to the beads using peptide N-glycosidase F. A total of 175 unique N-glycosylation sites were identified, belonging to 108 nonredundant glycoproteins. Of the 108 glycoproteins, 48 were identified by both methods of labeling and the remainder was identified using PAL on sialylated cells (40) or GAL on sialic acid-deficient cells (20). Our results demonstrate that PAL and GAL can be employed as complementary methods of chemical tagging for targeted proteomics of glycoprotein subpopulations and identification of glycosylation sites of proteins on cells with an altered sialylation status.

Investigation of ovarian cancer associated sialylation changes in N-linked glycopeptides by quantitative proteomics

Background

In approximately 80% of patients, ovarian cancer is diagnosed when the patient is already in the advanced stages of the disease. CA125 is currently used as the marker for ovarian cancer; however, it lacks specificity and sensitivity for detecting early stage disease. There is a critical unmet need for sensitive and specific routine screening tests for early diagnosis that can reduce ovarian cancer lethality by reliably detecting the disease at its earliest and treatable stages.

Results

In this study, we investigated the N-linked sialylated glycopeptides in serum samples from healthy and ovarian cancer patients using Lectin-directed Tandem Labeling (LTL) and iTRAQ quantitative proteomics methods. We identified 45 N-linked sialylated glycopeptides containing 46 glycosylation sites. Among those, ten sialylated glycopeptides were significantly up-regulated in ovarian cancer patients’ serum samples. LC-MS/MS analysis of the non-glycosylated peptides from the same samples, western blot data using lectin enriched glycoproteins of various ovarian cancer type samples, and PNGase F (+/−) treatment confirmed the sialylation changes in the ovarian cancer samples.

Conclusion

Herein, we demonstrated that several proteins are aberrantly sialylated in N-linked glycopeptides in ovarian cancer and detection of glycopeptides with abnormal sialylation changes may have the potential to serve as biomarkers for ovarian cancer.

Recent progress in quantitative glycoproteomics

Protein glycosylation is acknowledged as one of the major posttranslational modifications that elicit significant effects on protein folding, conformation, distribution, stability, and activity. The changes in glycoprotein abundance, glycosylation degree, and glycan structure are associated with a variety of diseases. Therefore, the quantitative study of glycoproteomics has become a new and popular research topic, and is quickly emerging as an important technique for biomarker discovery. Mass spectrometry-based protein quantification technologies provide a powerful tool for the systematic and quantitative assessment of the quantitative differences in the protein profiles of different samples. Combined with various glycoprotein/glycopeptide enrichment strategies and other glycoprotein analysis methods, these techniques have been further developed for application in quantitative glycoproteomics. A comprehensive quantitative analysis of the glycoproteome in a complex biological sample remains challenging because of the enormous complexity of biological samples, intrinsic characteristics of glycoproteins, and lack of universal quantitative technology. In this review, recently developed technologies in quantitative glycoproteome, especially those focused on two of the most common types of glycosylation (N-linked and O-linked glycoproteome), were summarized. The strengths and weaknesses of the various approaches were also discussed.

Semi-automated identification of N-Glycopeptides by hydrophilic interaction chromatography, nano-reverse-phase LC-MS/MS, and glycan database search

Glycoproteins fulfill many indispensable biological functions, and changes in protein glycosylation have been observed in various diseases. Improved analytical methods are needed to allow a complete characterization of this complex and common post-translational modification. In this study, we present a workflow for the analysis of the microheterogeneity of N-glycoproteins that couples hydrophilic interaction and nanoreverse-phase C18 chromatography to tandem QTOF mass spectrometric analysis. A glycan database search program, GlycoPeptideSearch, was developed to match N-glycopeptide MS/MS spectra with the glycopeptides comprised of a glycan drawn from the GlycomeDB glycan structure database and a peptide from a user-specified set of potentially glycosylated peptides. Application of the workflow to human haptoglobin and hemopexin, two microheterogeneous N-glycoproteins, identified a total of 57 distinct site-specific glycoforms in the case of haptoglobin and 14 site-specific glycoforms of hemopexin. Using glycan oxonium ions and peptide-characteristic glycopeptide fragment ions and by collapsing topologically redundant glycans, the search software was able to make unique N-glycopeptide assignments for 51% of assigned spectra, with the remaining assignments primarily representing isobaric topological rearrangements. The optimized workflow, coupled with GlycoPeptideSearch, is expected to make high-throughput semiautomated glycopeptide identification feasible for a wide range of users.

Targeted mass spectrometric approach for biomarker discovery and validation with nonglycosylated tryptic peptides from N-linked glycoproteins in human plasma

A simple mass spectrometric approach for the discovery and validation of biomarkers in human plasma was developed by targeting nonglycosylated tryptic peptides adjacent to glycosylation sites in an N-linked glycoprotein, one of the most important biomarkers for early detection, prognoses, and disease therapies. The discovery and validation of novel biomarkers requires complex sample pretreatment steps, such as depletion of highly abundant proteins, enrichment of desired proteins, or the development of new antibodies. The current study exploited the steric hindrance of glycan units in N-linked glycoproteins, which significantly affects the efficiency of proteolytic digestion if an enzymatically active amino acid is adjacent to the N-linked glycosylation site. Proteolytic digestion then results in quantitatively different peptide products in accordance with the degree of glycosylation. The effect of glycan steric hindrance on tryptic digestion was first demonstrated using alpha-1-acid glycoprotein (AGP) as a model compound versus deglycosylated alpha-1-acid glycoprotein. Second, nonglycosylated tryptic peptide biomarkers, which generally show much higher sensitivity in mass spectrometric analyses than their glycosylated counterparts, were quantified in human hepatocellular carcinoma plasma using a label-free method with no need for N-linked glycoprotein enrichment. Finally, the method was validated using a multiple reaction monitoring analysis, demonstrating that the newly discovered nonglycosylated tryptic peptide targets were present at different levels in normal and hepatocellular carcinoma plasmas. The area under the receiver operating characteristic curve generated through analyses of nonglycosylated tryptic peptide from vitronectin precursor protein was 0.978, the highest observed in a group of patients with hepatocellular carcinoma. This work provides a targeted means of discovering and validating nonglycosylated tryptic peptides as biomarkers in human plasma, without the need for complex enrichment processes or expensive antibody preparations.

A comprehensive peptidome profiling technology for the identification of early detection biomarkers for lung adenocarcinoma

The mass spectrometry-based peptidomics approaches have proven its usefulness in several areas such as the discovery of physiologically active peptides or biomarker candidates derived from various biological fluids including blood and cerebrospinal fluid. However, to identify biomarkers that are reproducible and clinically applicable, development of a novel technology, which enables rapid, sensitive, and quantitative analysis using hundreds of clinical specimens, has been eagerly awaited. Here we report an integrative peptidomic approach for identification of lung cancer-specific serum peptide biomarkers. It is based on the one-step effective enrichment of peptidome fractions (molecular weight of 1,000–5,000) with size exclusion chromatography in combination with the precise label-free quantification analysis of nano-LC/MS/MS data set using Expressionist proteome server platform. We applied this method to 92 serum samples well-managed with our SOP (standard operating procedure) (30 healthy controls and 62 lung adenocarcinoma patients), and quantitatively assessed the detected 3,537 peptide signals. Among them, 118 peptides showed significantly altered serum levels between the control and lung cancer groups (p<0.01 and fold change >5.0). Subsequently we identified peptide sequences by MS/MS analysis and further assessed the reproducibility of Expressionist-based quantification results and their diagnostic powers by MRM-based relative-quantification analysis for 96 independently prepared serum samples and found that APOA4 273–283, FIBA 5–16, and LBN 306–313 should be clinically useful biomarkers for both early detection and tumor staging of lung cancer. Our peptidome profiling technology can provide simple, high-throughput, and reliable quantification of a large number of clinical samples, which is applicable for diverse peptidome-targeting biomarker discoveries using any types of biological specimens.