The glycolyzer: automated glycan annotation software for high performance mass spectrometry and its application to ovarian cancer glycan biomarker discovery

Tumor ratio of unsaturated to saturated sulfatide species is associated with disease-free survival in intrahepatic cholangiocarcinoma

PURPOSE

Cholangiocarcinoma (CCA) is a malignancy arising from the bile duct epithelium and has a poor outcome. Sulfatides are lipid components of lipid rafts, and are implicated in several cancer types. In the liver, sulfatides are specifically present in the bile ducts. Here, sulfatide abundance and composition were analyzed using mass spectrometry imaging in intrahepatic CCA (iCCA) tumor tissue, and correlated with tumor biology and clinical outcomes.

METHODS

Sulfatides were analyzed in iCCA (n = 17), hepatocellular carcinoma (HCC, n = 10) and colorectal liver metastasis (CRLM, n = 10) tumor samples, as well as tumor-distal samples (control, n = 16) using mass spectrometry imaging. Levels of sulfatides as well as the relative amount in structural classes were compared between groups, and were correlated with clinical outcomes for iCCA patients.

RESULTS

Sulfatide localization was limited to the respective tumor areas and the bile ducts. Sulfatide abundance was similar in iCCA and control tissue, while intensities were notably higher in CRLM in comparison with control (18-fold, P < 0.05) and HCC tissue (47-fold, P < 0.001). Considerable variation in sulfatide abundance was observed in iCCA tumors. A high ratio of unsaturated to saturated sulfatides was associated with reduced disease-free survival (10 vs. 20 months) in iCCA. The sulfatide pattern in HCC deviated from the other groups, with a higher relative abundance of odd- versus even-chain sulfatides.

CONCLUSION

Sulfatides were found in tumor tissue of patients with iCCA, with sulfatide abundance per pixel being similar to bile ducts. In this explorative study, sulfatide abundance was not related to overall survival of iCCA patients. A high ratio of unsaturated to saturated sulfatides was associated with earlier tumor recurrence in patients with iCCA.

Isomer-specific biomarker discovery in multiple myeloma with dual-derivatized N-glycans

As one of the most important post-translational modifications, protein glycosylation plays vital role in various physiological processes. With multitudinous glycosyltransferases, N-glycans present structural diversity in linkages and branching styles. Structure-specific glycan profiling may provide more potential biological information than compositional profiling. In this work, N-glycans released from human serum samples were derivatized with reduction and methylamination prior to profiling using nanoLC-ESI-MS with PGC as stationary phase. In addition, α 2-3 neuraminidase was also applied for distinguishing the linkage types of sialic acid corresponding to different isomers. Relative abundances of 280 isomeric N-glycans were compared and 20 isomers showed significant difference between multiple myeloma cases and healthy controls. ROC was performed to assess the significantly altered isomeric glycans and 6 AUCs have exceeded 0.80, providing high diagnostic accuracy for MM. PCA is also employed to establish the differences among sample sets. Furthermore, these specific isomers have also been used for early detection of multiple myeloma, presenting important clinical application value. Isomer-specific biomarker discovery in multiple myeloma with dual-derivatized N-glycans.

Discovery of Serotransferrin Glycoforms: Novel Markers for Diagnosis of Liver Periductal Fibrosis and Prediction of Cholangiocarcinoma

Cholangiocarcinoma (CCA) caused by chronic liver fluke infection is a major public health problem in Northeast Thailand. Identification of CCA risk groups is urgently needed for the control of CCA in this region. Periductal fibrosis (PDF) induced by chronic inflammation of bile ducts is known as a pre-neoplastic lesion of CCA. We aimed to identify the serum CCA and PDF biomarkers using mass spectrometry (UPLC-ESI-QqQ) with multiple reaction mode (MRM) analysis. Here, serum levels of serotransferrin glycoforms at the glycopeptide level were measured in the sera of CCA (n = 100), PDF (n = 50), and healthy control (n = 100) subjects. The results indicated that serotransferrin peptide levels were generally the same between the control and PDF groups, whereas CCA patients had reduced levels. Moreover, 56 serotransferrin glycoforms were detected, with nine increased in CCA compared to control subjects. Among them, the serum levels of four glycoforms were increased in PDF and CCA patients compared to control subjects. In particular, highly sialylated multi-branched glycans of serotransferrin serum were significantly correlated with poor prognosis and tumor stage in CCA patients. Taken together, these glycoforms could be used as risk biomarkers and prognosis and diagnosis markers of CCA.

Advancing Solutions to the Carbohydrate Sequencing Challenge

Carbohydrates possess a variety of distinct features with stereochemistry playing a particularly important role in distinguishing their structure and function. Monosaccharide building blocks are defined by a high density of chiral centers. Additionally, the anomericity and regiochemistry of the glycosidic linkages carry important biological information. Any carbohydrate-sequencing method needs to be precise in determining all aspects of this stereodiversity. Recently, several advances have been made in developing fast and precise analytical techniques that have the potential to address the stereochemical complexity of carbohydrates. This perspective seeks to provide an overview of some of these emerging techniques, focusing on those that are based on NMR and MS-hybridized technologies including ion mobility spectrometry and IR spectroscopy.

Serum IgA1 shows increased levels of α2,6-linked sialic acid in breast cancer

The lectin Helix pomatia agglutinin (HPA) recognizes altered glycosylation in solid cancers and the identification of HPA binding partners in tumour tissue and serum is an important aim. Among the many HPA binding proteins, IgA1 has been reported to be the most abundant in liver metastases. In this study, the glycosylation of IgA1 was evaluated using serum samples from patients with breast cancer (BCa) and the utility of IgA1 glycosylation as a biomarker was assessed. Detailed mass spectrometric structural analysis showed an increase in disialo-biantennary N-linked glycans on IgA1 from BCa patients (p < 0.0001: non-core fucosylated; p = 0.0345: core fucosylated) and increased asialo-Thomsen-Friedenreich antigen (TF) and disialo-TF antigens in the O-linked glycan preparations from IgA1 of cancer patients compared with healthy control individuals. An increase in Sambucus nigra binding was observed, suggestive of increased α2,6-linked sialic acid on IgA1 in BCa. Logistic regression analysis showed HPA binding to IgA1 and tumour size to be significant independent predictors of distant metastases (χ ² 13.359; n = 114; p = 0.020) with positive and negative predictive values of 65.7% and 64.6%, respectively. Immunohistochemical analysis of tumour tissue samples showed IgA1 to be detectable in BCa tissue. This report provides a detailed analysis of serum IgA1 glycosylation in BCa and illustrates the potential utility of IgA1 glycosylation as a biomarker for BCa prognostication.

The Interaction of the Gut Microbiota with the Mucus Barrier in Health and Disease in Human

Glycoproteins are major players in the mucus protective barrier in the gastrointestinal and other mucosal surfaces. In particular the mucus glycoproteins, or mucins, are responsible for the protective gel barrier. They are characterized by their high carbohydrate content, present in their variable number, tandem repeat domains. Throughout evolution the mucins have been maintained as integral components of the mucosal barrier, emphasizing their essential biological status. The glycosylation of the mucins is achieved through a series of biosynthetic pathways processes, which generate the wide range of glycans found in these molecules. Thus mucins are decorated with molecules having information in the form of a glycocode. The enteric microbiota interacts with the mucosal mucus barrier in a variety of ways in order to fulfill its many normal processes. How bacteria read the glycocode and link to normal and pathological processes is outlined in the review.

Inhibition of poly-LacNAc biosynthesis with release of CMP-Neu5Ac feedback inhibition increases the sialylation of recombinant EPO produced in CHO cells

Sialylation of recombinant therapeutic glycoproteins modulates their pharmacokinetic properties by affecting their in vivo half-life. N-glycan branching on glycoproteins increases the number of potential attachment sites for sialic acid. Here, we introduce a new approach for increasing the sialylation of recombinant human erythropoietin (rhEPO) produced in CHO cells by modulating poly-N-acetyllactosamine (poly-LacNAc) biosynthesis. We did not observe an increase in rhEPO sialylation, however, until the feedback inhibition by intracellular cytidine monophosphate-N-acetylneuraminic acid (CMP-Neu5Ac), which is a limiting factor for sialylation, was released. Thus, we found that a combined approach inhibiting poly-LacNAc biosynthesis and releasing CMP-Neu5Ac feedback inhibition produces the most significant increase in rhEPO sialylation in metabolically engineered CHO cells. Furthermore, a detailed analysis of the resulting N-glycan structures using LC/MS revealed increased tri- and tetra- sialylated N-glycan structures accompanied by a reduction of di-sialylated N-glycan structures. These results validate our new approach for glycosylation engineering, and we expect this approach will be useful in future efforts to enhance the efficacy of other therapeutic glycoproteins.

Large-scale identification and visualization of N-glycans with primary structures using GlySeeker

RATIONALE

Most of the current popular tandem mass spectrometers have the capability of resolving the primary structures (monosaccharide composition, sequence and linkage) of N-glycans; however, compositions or putative structures have mostly been reported so far. Identification and visualization tools of N-glycans are needed.

METHODS

The isotopic mass-to-charge ratio and envelope fingerprinting algorithm, which has been successfully used for intact protein database search and identification, was adapted for N-glycan database search, and a stand-alone N-glycan database search engine, GlySeeker, for automated N-glycan identification and visualization was developed and successfully benchmarked. Both pseudo 2D graph and one-line text formats with one-letter symbols for monosaccharides were proposed for representing N-glycans. N-glycans were identified with comprehensive interpretation of product ions and false discovery rate (FDR) control.

RESULTS

In a database search of reversed-phase liquid chromatography/tandem mass spectrometry (RPLC/MS/MS) datasets of the N-glycome enriched from OVCAR-3 ovarian cancer cells, with FDR ≤1% and number of best hits (NoBHs) = 1-30, 1525 N-glycans with comprehensive primary structural information (composition, sequence and linkage) were identified and visualized; among these 1525 N-glycans, 559 had NoBHs = 1, i.e. their structures were uniquely identified. This represents a large-scale identification and visualization of N-glycans with primary structures from tandem mass spectra.

CONCLUSIONS

A stand-alone N-glycan database search engine called GlySeeker has been developed for large-scale identification and visualization of N-glycans with comprehensive interpretation of tandem mass spectra and FDR control.

Comparison of the methods for profiling N-glycans—hepatocellular carcinoma serum glycomics study

Monitoring serum glycomics is one of the most important emerging approaches for diagnosis of various cancers, and the majority of previous studies were based on MALDI-MS or HPLC analysis. Considering the difference of these analytical methods employed for serum glycomics, it is necessary to compare the effectiveness of different analytical methods for monitoring the aberrant changes in serum glycomics. In this study, a strategy based on machine learning was firstly applied for comparing the analysis results of MALDI-MS and HPLC on the same serum glycomics of hepatocellular carcinoma (HCC) samples. The capability of these two analytical methods for identifying HCC is demonstrated by the classification results obtained from MALDI-MS and HPLC data. In addition, by comparing glycomics which were significantly correlated with HCC based on MALDI-MS and HPLC, some N-glycans which may be the potential biomarkers for HCC were identified, validating the capability of these two analytical methods for the differentiated identification in the analysis of glycomics. Meanwhile, it is noteworthy that various physiological and environmental factors may cause the aberrant changes in glycosylation, and all these interference factors may be minimized by analyzing the same sample sets of HCC. Overall, these results showed that MALDI-MS and HPLC are complementary in qualitative and quantitative analysis of serum glycomics.

Monitoring serum glycomics is one of the most important emerging approaches for diagnosis of various cancers, and the majority of previous studies were based on MALDI-MS or HPLC analysis.

Multiple Reaction Monitoring for the Quantitation of Serum Protein Glycosylation Profiles: Application to Ovarian Cancer

Protein glycosylation fingerprints are widely recognized as potential markers for disease states, and indeed differential glycosylation has been identified in multiple types of autoimmune diseases and several types of cancer. However, releasing the glycans leave the glycoproteins unknown; therefore, there exists a need for high-throughput methods that allow quantification of site- and protein-specific glycosylation patterns from complex biological mixtures. In this study, a targeted multiple reaction monitoring (MRM)-based method for the protein- and site-specific quantitation involving serum proteins immunoglobulins A, G and M, alpha-1-antitrypsin, transferrin, alpha-2-macroglobulin, haptoglobin, alpha-1-acid glycoprotein and complement C3 was developed. The method is based on tryptic digestion of serum glycoproteins, followed by immediate reverse phase UPLC-QQQ-MS analysis of glycopeptides. To quantitate protein glycosylation independent of the protein serum concentration, a nonglycosylated peptide was also monitored. Using this strategy, 178 glycopeptides and 18 peptides from serum glycoproteins are analyzed with good repeatability (interday CVs of 3.65-21-92%) in a single 17 min run. To assess the potential of the method, protein glycosylation was analyzed in serum samples from ovarian cancer patients and controls. A training set consisting of 40 cases and 40 controls was analyzed, and differential analyses were performed to identify aberrant glycopeptide levels. All findings were validated in an independent test set (n = 44 cases and n = 44 controls). In addition to the differential glycosylation on the immunoglobulins, which was reported previously, aberrant glycosylation was also observed on each of the glycoproteins, which could be corroborated in the test set. This report shows the development of a method for targeted protein- and site-specific glycosylation analysis and the potential of such methods in biomarker development.

Increased expression of the high-mannose M6N2 and NeuAc3H3N3M3N2F tri-antennary N-glycans in cholangiocarcinoma

Changes in protein glycosylation have been reported in various types of cancer, including cholangiocarcinoma (CCA). Nanospray ionization-linear ion trap mass spectrometry (NSI-MSⁿ) was used in the present study to determine the comparative structural glycomics of the N-linked glycans in the serum of patients with CCA compared with healthy controls. A total of 5 high-mannose and 4 complex N-linked glycans were detected. Mannose₇-N-acetyl-glucosamine₂ was the most abundant structure among the high-mannose types (control 12.12±2.54 vs. CCA 9.27±2.66%), whereas NeuAc2H2N2M3N2 predominated the complex types (control 61.17±2.55 vs. CCA 64.68±4.23%). The expression of 3 different N-glycans differed significantly between the CCA cases and controls. These included mannose₆-N-acetyl-glucosamine₂ (P=0.044), mannose₉-N-acetyl-glucosamine₂ (Ρ=0.030) and NeuAc3H3N3M3N2F (Ρ=0.002). These three glycan structures may therefore be associated with tumor progression in CCA and may be useful for its diagnosis.

Glycan characterization of the NIST RM monoclonal antibody using a total analytical solution: From sample preparation to data analysis

Glycosylation is an important attribute of biopharmaceutical products to monitor from development through production. However, glycosylation analysis has traditionally been a time-consuming process with long sample preparation protocols and manual interpretation of the data. To address the challenges associated with glycan analysis, we developed a streamlined analytical solution that covers the entire process from sample preparation to data analysis. In this communication, we describe the complete analytical solution that begins with a simplified and fast N-linked glycan sample preparation protocol that can be completed in less than 1 hr. The sample preparation includes labelling with RapiFluor-MS tag to improve both fluorescence (FLR) and mass spectral (MS) sensitivities. Following HILIC-UPLC/FLR/MS analyses, the data are processed and a library search based on glucose units has been included to expedite the task of structural assignment. We then applied this total analytical solution to characterize the glycosylation of the NIST Reference Material mAb 8761. For this glycoprotein, we confidently identified 35 N-linked glycans and all three major classes, high mannose, complex, and hybrid, were present. The majority of the glycans were neutral and fucosylated; glycans featuring N-glycolylneuraminic acid and those with two galactoses connected via an α1,3-linkage were also identified.

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2011-2012

This review is the seventh update of the original article published in 1999 on the application of MALDI mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2012. General aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, and fragmentation are covered in the first part of the review and applications to various structural types constitute the remainder. The main groups of compound are oligo- and poly-saccharides, glycoproteins, glycolipids, glycosides, and biopharmaceuticals. Much of this material is presented in tabular form. Also discussed are medical and industrial applications of the technique, studies of enzyme reactions, and applications to chemical synthesis. © 2015 Wiley Periodicals, Inc. Mass Spec Rev 36:255-422, 2017.

A Brief Review of Bioinformatics Tools for Glycosylation Analysis by Mass Spectrometry

The purpose of this review is to provide updated information regarding bioinformatic software for the use in the characterization of glycosylated structures since 2013. A comprehensive review by Woodin et al.Analyst 138: 2793-2803, 2013 (ref. 1) described two main approaches that are introduced for starting researchers in this area; analysis of released glycans and the identification of glycopeptide in enzymatic digests, respectively. Complementary to that report, this review focuses on mass spectrometry related bioinformatics tools for the characterization of N-linked and O-linked glycopeptides. Specifically, it also provides information regarding automated tools that can be used for glycan profiling using mass spectrometry.

The ascites N-glycome of epithelial ovarian cancer patients

Epithelial ovarian cancer (EOC) is worldwide the sixth most lethal form of cancer occurring in women. More than one third of ovarian patients have ascites at the time of diagnosis and almost all of them have it when recurrence occurs. Although its effect on tumor cell microenvironment remains poorly understood, its presence is correlated with bad diagnosis. In previous studies, we proposed a novel glycan-based biomarker for the diagnosis of EOC, which showed an improved sensitivity and specificity at any stage of the disease and an improved discrimination between malignant and benign ovarian tumors. In this work, we report for the first time the N-glycome profiles of ascitic fluid from primary serous EOC patients and compare them with the serum N-glycomes of the same patients as well as of healthy controls. N-Glycans were digested from equivalent amount of ascites and serum from 18 EOC patients and from serum of 20 age-matched controls and measured by MALDI-TOF-MS. Ascites N-glycome showed increased antennarity, branching, sialylation and Lewis^X motives compared to healthy serum. In addition, a correlation was established between ascites volume and degree of sialylation.

SIGNIFICANCE

Malignant ascitic fluid is the build-up of large volumes of fluid in the peritoneal cavity secondary to cancer. At least one-third of ovarian cancer patients develop ascites, a generally voluminous fluid containing cells of tumor origin, in the course of cancer and almost all when recurrence occurs. The proteome of ascites is known to be as complex as that of serum and contains high amount of proteins shed from inflammatory cells as well as from tumor cells. Although many attempts have been made to provide molecular insight into the proteomic and peptidomic content of malignant ascites, no data about the N-glycome of the ascitic fluid fraction from cancer patients has been reported to date. In this study, the N-glycosylation profile of ascites from 20 patients suffering from epithelial ovarian cancer (EOC) was analyzed by MALDI-TOF-mass spectrometry and compared to the pathologically modified N-glycan pattern obtained from serum of the same patients as well as to the pattern of serum from healthy individuals. Significant quantitative differences were observed in the ascites of EOC patients when compared to the serum of healthy subjects. The glycome of ascites shows typical features of inflammatory conditions, what was also found in the serum of patients suffering from EOC when compared to healthy serum. In addition, a correlation was established between ascites volume and degree of sialylation, showing that the high-volume ascites contains a higher amount of sialylated structures than the low-volume ascites.

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.

Automatic annotation and visualization tool for mass spectrometry based glycomics

RATIONALE

With the development of glycomics, a large number of glycan structures have been determined by using mass spectrometry (MS)-based techniques. However, most glycan MS data needs to be manually annotated which is time-consuming, unreliable and inaccurate.

METHODS

Herein we report a tool for automatically annotating and browsing N-glycan masses and isotopic distributions. We first constructed a training dataset using the Consortium for Functional Glycomics database, in conjunction with data preprocessing and filtering by composition matching. In addition, we improved a matching glycan isotope abundance algorithm through identifying potential overlap region and constructing an optimization model so that it can deconvolute the overlapped glycan isotopic clusters.

RESULTS

In the matching process, if the m/z difference of two detected ions was close to an integer from 1 to 5, the m/z range was considered as a potential overlapped region, from the lower m/z to m/z + 5. It was found that there were more than 20 potential overlap regions in each group of data from CHO sample and human testing sample. Because the training dataset was imbalanced, we combined the Supporting Vector Machines (SVMs) algorithm with different sampling techniques, including Synthetic Minority Over-sampling Technique (SMOTE), to classify all potential candidate compositions. The results demonstrated an average of 26.8% increase in annotation sensitivity through the SMOTE-SVMs algorithm. The source code can be obtained from https://sourceforge.net/projects/glycomaid/.

CONCLUSIONS

We have developed a new tool which facilities high-throughput glycomics research and assists mass spectrometrists in the interpretation and annotation of glycan samples. Copyright © 2016 John Wiley & Sons, Ltd.

GlycCompSoft: Software for Automated Comparison of Low Molecular Weight Heparins Using Top-Down LC/MS Data

Low molecular weight heparins are complex polycomponent drugs that have recently become amenable to top-down analysis using liquid chromatography-mass spectrometry. Even using open source deconvolution software, DeconTools, and automatic structural assignment software, GlycReSoft, the comparison of two or more low molecular weight heparins is extremely time-consuming, taking about a week for an expert analyst and provides no guarantee of accuracy. Efficient data processing tools are required to improve analysis. This study uses the programming language of Microsoft Excel™ Visual Basic for Applications to extend its standard functionality for macro functions and specific mathematical modules for mass spectrometric data processing. The program developed enables the comparison of top-down analytical glycomics data on two or more low molecular weight heparins. The current study describes a new program, GlycCompSoft, which has a low error rate with good time efficiency in the automatic processing of large data sets. The experimental results based on three lots of Lovenox®, Clexane® and three generic enoxaparin samples show that the run time of GlycCompSoft decreases from 11 to 2 seconds when the data processed decreases from 18000 to 1500 rows.

Glycoproteomic Analysis of Malignant Ovarian Cancer Ascites Fluid Identifies Unusual Glycopeptides

Ovarian cancer is a major cause of cancer mortality among women, largely due to late diagnosis of advanced metastatic disease. More extensive molecular analysis of metastatic ovarian cancer is needed to identify post-translational modifications of proteins, especially glycosylation that is particularly associated with metastatic disease to better understand the metastatic process and identify potential therapeutic targets. Glycoproteins in ascites fluid were enriched by affinity binding to lectins (ConA or WGA) and other affinity matrices. Separate glycomic, proteomic, and glycopeptide analyses were performed. Relative abundances of different N-glycan groups and proteins were identified from ascites fluids and a serum control. Levels of biomarkers CA125, MUC1, and fibronectin were also monitored in OC ascites samples by Western blot analysis. N-Glycan analysis of ascites fluids showed the presence of large, highly fucosylated and sialylated complex and hybrid glycans, some of which were not observed in normal serum. OC ascites glycoproteins, haptoglobin, fibronectin, lumican, fibulin, hemopexin, ceruloplasmin, alpha-1-antitrypsin, and alpha-1-antichymotrypsin were more abundant in OC ascites or not present in serum control samples. Further glycopeptide analysis of OC ascites identified N- and O-glycans in clusterin, hemopexin, and fibulin glycopeptides, some of which are unusual and may be important in OC metastasis.

Quantitative profiling of glycans and glycopeptides: an informatics' perspective

Experimental techniques to identify and quantify glycan structures in a given sample are continuously improving. However, as they advance data analysis and annotation seems to become more complex. To address this issue, much progress has been made in developing software for interpretation of quantitative glycan profiles. Here, we focus on these informatics tools for high/ultra performance liquid chromatography (H/UPLC), mass spectrometry (MS), tandem mass spectrometry (MSⁿ) and combinations thereof. Software for biomarker discovery, pathway, genomic and disease analysis and a final note on some future prospects for glycoinformatics are also mentioned.

Visual detection of serum asialohaptoglobin by plasmonic sandwich ELLSA--a new platform for cirrhosis diagnosis

The cirrhotic condition of the liver has long been acknowledged as the preface to liver cancer. The desialylation status of the serum acute phase protein, haptoglobin, has been introduced as a new diagnostic analyte for liver cirrhosis. The reliability of this new diagnostic molecule has been evaluated in 30 liver cirrhosis patients having a history of earlier viral hepatitis C (HCV-LC). A novel enzyme linked lectinosorbent assay has been developed coupled with the plasmon mechanism of gold nanoparticle aggregation as the colorimetric read out which can visually distinguish the cirrhotic liver patients from the normal healthy and hepatitis C controls. The assay can be useful for rapid point-of-care detection, and even an untrained person can execute it without a specialized instrument. This method employs Sambucus nigra agglutinin (SNA) to detect the extent of α-2,6 sialylation of serum haptoglobin, the new diagnostic molecule for liver cirrhosis.

Differential N-Glycosylation Patterns in Lung Adenocarcinoma Tissue

To decrease the mortality of lung cancer, better screening and diagnostic tools as well as treatment options are needed. Protein glycosylation is one of the major post-translational modifications that is altered in cancer, but it is not exactly clear which glycan structures are affected. A better understanding of the glycan structures that are differentially regulated in lung tumor tissue is highly desirable and will allow us to gain greater insight into the underlying biological mechanisms of aberrant glycosylation in lung cancer. Here, we assess differential glycosylation patterns of lung tumor tissue and nonmalignant tissue at the level of individual glycan structures using nLC-chip-TOF-MS. Using tissue samples from 42 lung adenocarcinoma patients, 29 differentially expressed (FDR < 0.05) glycan structures were identified. The levels of several oligomannose type glycans were upregulated in tumor tissue. Furthermore, levels of fully galactosylated glycans, some of which were of the hybrid type and mostly without fucose, were decreased in cancerous tissue, whereas levels of non- or low-galactosylated glycans mostly with fucose were increased. To further assess the regulation of the altered glycosylation, the glycomics data was compared to publicly available gene expression data from lung adenocarcinoma tissue compared to nonmalignant lung tissue. The results are consistent with the possibility that the observed N-glycan changes have their origin in differentially expressed glycosyltransferases. These results will be used as a starting point for the further development of clinical glycan applications in the fields of imaging, drug targeting, and biomarkers for lung cancer.

Benchmark study of automatic annotation of MALDI-TOF N-glycan profiles

Human experts can annotate peaks in MALDI-TOF profiles of detached N-glycans with some degree of accuracy. Even though MALDI-TOF profiles give only intact masses without any fragmentation information, expert knowledge of the most common glycans and biosynthetic pathways in the biological system can point to a small set of most likely glycan structures at the "cartoon" level of detail. Cartoonist is a recently developed, fully automatic annotation tool for MALDI-TOF glycan profiles. Here we benchmark Cartoonist's automatic annotations against human expert annotations on human and mouse N-glycan data from the Consortium for Functional Glycomics. We find that Cartoonist and expert annotations largely agree, but the expert tends to annotate more specifically, meaning fewer suggested structures per peak, and Cartoonist more comprehensively, meaning more annotated peaks. On peaks for which both Cartoonist and the expert give unique cartoons, the two cartoons agree in over 90% of all cases. This article is part of a Special Issue entitled: Computational Proteomics.

Glycans in the immune system and The Altered Glycan Theory of Autoimmunity: a critical review

Herein we will review the role of glycans in the immune system. Specific topics covered include: the glycosylation sites of IgE, IgM, IgD, IgE, IgA, and IgG; how glycans can encode "self" identity by functioning as either danger associated molecular patterns (DAMPs) or self-associated molecular patterns (SAMPs); the role of glycans as markers of protein integrity and age; how the glycocalyx can dictate the migration pattern of immune cells; and how the combination of Fc N-glycans and Ig isotype dictate the effector function of immunoglobulins. We speculate that the latter may be responsible for the well-documented association between alterations of the serum glycome and autoimmunity. Due to technological limitations, the extent of these autoimmune-associated glycan alterations and their role in disease pathophysiology has not been fully elucidated. Thus, we also review the current technologies available for glycan analysis, placing an emphasis on Multiple Reaction Monitoring (MRM), a rapid high-throughput technology that has great potential for glycan biomarker research. Finally, we put forth The Altered Glycan Theory of Autoimmunity, which states that each autoimmune disease will have a unique glycan signature characterized by the site-specific relative abundances of individual glycan structures on immune cells and extracellular proteins, especially the site-specific glycosylation patterns of the different immunoglobulin(Ig) classes and subclasses.

Clinical Glycomics Employing Graphitized Carbon Liquid Chromatography-Mass Spectrometry

Glycoconjugates and free glycan are involved in a variety of biological processes such as cell-cell interaction and cell trafficking. Alterations in the complex glycosylation machinery have been correlated with various pathological processes including cancer progression and metastasis. Mass Spectrometry (MS) has evolved as one of the most powerful tools in glycomics and glycoproteomics and in combination with porous graphitized carbon-liquid chromatography (PGC-LC) it is a versatile and sensitive technique for the analysis of glycans and to some extent also glycopeptides. PGC-LC-ESI-MS analysis is characterized by a high isomer separation power enabling a specific glycan compound analysis on the level of individual structures. This allows the investigation of the biological relevance of particular glycan structures and glycan features. Consequently, this strategy is a very powerful technique suitable for clinical research, such as cancer biomarker discovery, as well as in-depth analysis of recombinant glycoproteins. In this review, we will focus on how PGC in conjunction with MS detection can deliver specific structural information for clinical research on protein-bound N-glycans and mucin-type O-glycans. In addition, we will briefly review PGC analysis approaches for glycopeptides, glycosaminoglycans (GAGs) and human milk oligosaccharides (HMOs). The presented applications cover systems that vary vastly with regard to complexity such as purified glycoproteins, cells, tissue or body fluids revealing specific glycosylation changes associated with various biological processes including cancer and inflammation.

Exploring the glycoproteomics landscape with advanced MS technologies

The advance of glycoproteomic technologies has offered unique insights into the importance of glycosylation in determining the functional roles of a protein within a cell. Biologically active glycoproteins include the categories of enzymes, hormones, proteins involved in cell proliferation, cell membrane proteins involved in cell-cell recognition, and communication events or secreted proteins, just to name a few. The recent progress in analytical instrumentation, methodologies, and computational approaches has enabled a detailed exploration of glycan structure, connectivity, and heterogeneity, underscoring the staggering complexity of the glycome repertoire in a cell. A variety of approaches involving the use of spectroscopy, MS, separation, microfluidic, and microarray technologies have been used alone or in combination to tackle the glycoproteome challenge, the research results of these efforts being captured in an overwhelming number of annual publications. This work is aimed at reviewing the major developments and accomplishments in the field of glycoproteomics, with focus on the most recent advancements (2012-2014) that involve the use of capillary separations and MS detection.

Polysialylated N-glycans identified in human serum through combined developments in sample preparation, separations, and electrospray ionization-mass spectrometry

The N-glycan diversity of human serum glycoproteins, i.e., the human blood serum N-glycome, is both complex and constrained by the range of glycan structures potentially synthesizable by human glycosylation enzymes. The known glycome, however, has been further limited by methods of sample preparation, available analytical platforms, e.g., based upon electrospray ionization-mass spectrometry (ESI-MS), and software tools for data analysis. In this report several improvements have been implemented in sample preparation and analysis to extend ESI-MS glycan characterization and to include polysialylated N-glycans. Sample preparation improvements included acidified, microwave-accelerated, PNGase F N-glycan release to promote lactonization, and sodium borohydride reduction, that were both optimized to improve quantitative yields and conserve the number of glycoforms detected. Two-stage desalting (during solid phase extraction and on the analytical column) increased sensitivity by reducing analyte signal division between multiple reducing-end-forms or cation adducts. Online separations were improved by using extended length graphitized carbon columns and adding TFA as an acid modifier to a formic acid/reversed phase gradient, providing additional resolving power and significantly improved desorption of both large and heavily sialylated glycans. To improve MS sensitivity and provide gentler ionization conditions at the source-MS interface, subambient pressure ionization with nanoelectrospray (SPIN) was utilized. When these improved methods are combined together with the Glycomics Quintavariate Informed Quantification (GlyQ-IQ) recently described (Kronewitter et al. Anal. Chem. 2014, 86, 6268-6276), we are able to significantly extend glycan detection sensitivity and provide expanded glycan coverage. We demonstrated the application of these advances in the context of the human serum glycome, and for which our initial observations included the detection of a new class of heavily sialylated N-glycans, including polysialylated N-glycans.

GlyQ-IQ: glycomics quintavariate-informed quantification with high-performance computing and GlycoGrid 4D visualization

Glycomics quintavariate-informed quantification (GlyQ-IQ) is a biologically guided glycomics analysis tool for identifying N-glycans in liquid chromatography-mass spectrometry (LC-MS) data. Glycomics LC-MS data sets have convoluted extracted ion chromatograms that are challenging to deconvolve with existing software tools. LC deconvolution into constituent pieces is critical in glycomics data sets because chromatographic peaks correspond to different intact glycan structural isomers. The biological targeted analysis approach offers several key advantages to traditional LC-MS data processing. A priori glycan information about the individual target's elemental composition allows for improved sensitivity by utilizing the exact isotope profile information to focus chromatogram generation and LC peak fitting on the isotopic species having the highest intensity. Glycan target annotation utilizes glycan family relationships and in source fragmentation in addition to high specificity feature LC-MS detection to improve the specificity of the analysis. The GlyQ-IQ software was developed in this work and evaluated in the context of profiling the N-glycan compositions from human serum LC-MS data sets. A case study is presented to demonstrate how GlyQ-IQ identifies and removes confounding chromatographic peaks from high mannose glycan isomers from human blood serum. In addition, GlyQ-IQ was used to generate a broad human serum N-glycan profile from a high resolution nanoelectrospray-liquid chromatography-tandem mass spectrometry (nESI-LC-MS/MS) data set. A total of 156 glycan compositions and 640 glycan isomers were detected from a single sample. Over 99% of the GlyQ-IQ glycan-feature assignments passed manual validation and are backed with high-resolution mass spectra.

Evaluation of glycomic profiling as a diagnostic biomarker for epithelial ovarian cancer

BACKGROUND

Prior studies suggested that glycans were differentially expressed in patients with ovarian cancer and controls. We hypothesized that glycan-based biomarkers might serve as a diagnostic test for ovarian cancer and evaluated the ability of glycans to distinguish ovarian cancer cases from matched controls.

METHODS

Serum samples were obtained from the tissue-banking repository of the Gynecologic Oncology Group, and included healthy female controls (n = 100), women diagnosed with low malignant potential (LMP) tumors (n = 52), and epithelial ovarian cancers (EOC) cases (n = 147). Cases and controls were matched on age at enrollment within ±5 years. Serum samples were analyzed by glycomics analysis to detect abundance differences in glycan expression levels. A two-stage procedure was carried out for biomarker discovery and validation. Candidate classifiers of glycans that separated cases from controls were developed using a training set in the discovery phase and the classification performance of the candidate classifiers was assessed using independent test samples that were not used in discovery.

RESULTS

The patterns of glycans showed discriminatory power for distinguishing EOC and LMP cases from controls. Candidate glycan-based biomarkers developed on a training set (sensitivity, 86% and specificity, 95.8% for distinguishing EOC from controls through leave-one-out cross-validation) confirmed their potential use as a detection test using an independent test set (sensitivity, 70% and specificity, 86.5%).

CONCLUSION

Formal investigations of glycan biomarkers that distinguish cases and controls show great promise for an ovarian cancer diagnostic test. Further validation of a glycan-based test for detection of ovarian cancer is warranted.

IMPACT

An emerging diagnostic test based on the knowledge gained from understanding the glycobiology should lead to an assay that improves sensitivity and specificity and allows for early detection of ovarian cancer.

Serum glycan signatures of gastric cancer

Glycomics, a comprehensive study of glycans expressed in biologic systems, is emerging as a simple yet highly sensitive diagnostic tool for disease onset and progression. This study aimed to use glycomics to investigate glycan markers that would differentiate patients with gastric cancer from those with nonatrophic gastritis. Patients with duodenal ulcer were also included because they are thought to represent a biologically different response to infection with Helicobacter pylori, a bacterial infection that can cause either gastric cancer or duodenal ulcer. We collected 72 serum samples from patients in Mexico City that presented with nonatrophic gastritis, duodenal ulcer, or gastric cancer. N-glycans were released from serum samples using the generic method with PNGase F and were analyzed by matrix-assisted laser desorption/ionization Fourier transform-ion cyclotron resonance mass spectrometry. The corresponding glycan compositions were calculated based on accurate mass. ANOVA-based statistical analysis was performed to identify potential markers for each subgroup. Nineteen glycans were significantly different among the diagnostic groups. Generally, decreased levels of high-mannose-type glycans, glycans with one complex type antenna, bigalactosylated biantennary glycans, and increased levels of nongalactosylated biantennary glycans were observed in gastric cancer cases. Altered levels of serum glycans were also observed in duodenal ulcer, but differences were generally in the same direction as gastric cancer. Serum glycan profiles may provide biomarkers to differentiate gastric cancer cases from controls with nonatrophic gastritis. Further studies will be needed to validate these findings as biomarkers and identify the role of protein glycosylation in gastric cancer pathology.

Isomer-specific LC/MS and LC/MS/MS profiling of the mouse serum N-glycome revealing a number of novel sialylated N-glycans

Mice are the premier mammalian models for studies of human physiology and disease, bearing extensive biological similarity to humans with far fewer ethical, economic, or logistic complications. To facilitate glycomic studies based on the mouse model, we comprehensively profiled the mouse serum N-glycome using isomer-specific nano-LC/MS and -LC/MS/MS. N-Glycans were identified by accurate mass MS and structurally elucidated by MS/MS. Porous graphitized carbon nano-LC was able to separate out nearly 300 N-linked glycan compounds (including isomers) from just over 100 distinct N-linked glycan compositions. Additional MS/MS structural analysis was performed on a number of novel N-glycans, revealing the structural characteristics of modifications such as dehydration, O-acetylation, and lactylation. Experimental findings were combined with known glycobiology to generate a theoretical library of all biologically possible mouse serum N-glycan compositions. The library may be used for automated identification of complex mixtures of mouse N-glycans, with possible applications to a wide range of mouse-related research endeavors, including pharmaceutical drug development and biomarker discovery.

Analytical platform for glycomic characterization of recombinant erythropoietin biotherapeutics and biosimilars by MS

Background: Erythropoietin is a therapeutic glycoprotein that stimulates red blood cell production. The quality, safety and potency of recombinant erythropoietins are determined largely by their glycosylation. Small variations in cell culture conditions can significantly affect the glycosylation, and therefore the efficacy, of recombinant erythropoietins. Thus, detailed glycomic analyses are necessary to assess biotherapeutic quality. We have developed a platform for qualitative and quantitative glycomic analysis of recombinant erythropoietins. Results: The platform was used to profile native N-glycans from three production batches of darbepoetin alfa (also known as NESP), a common form of recombinant erythropoietin. Darbepoetin alfa was found to contain an abundance of large, multi-antennary N-glycans with high levels of sialylation, O-acetylation and dehydration. Results were verified by independent orthogonal analysis with both MALDI-TOF and nano-LC/Q-TOF MS. Conclusion: This platform may be applied to QC and batch analysis of not only recombinant erythropoietin, but also other complex, glycosylated biotherapeutics and biosimilars.

Developments in the identification of glycan biomarkers for the detection of cancer

Changes in glycosylation readily occur in cancer and other disease states. Thanks to recent advances in the development of analytical techniques and instrumentation, especially in mass spectrometry, it is now possible to identify blood-derived glycan-based biomarkers using glycomics strategies. This review is an overview of the developments made in the search for glycan-based cancer biomarkers and the technologies currently in use. It is anticipated that the progressing instrumental and bioinformatics developments will allow the identification of relevant glycan biomarkers for the diagnosis, early detection, and monitoring of cancer treatment with sufficient sensitivity and specificity for clinical use.

Improving N-glycan coverage using HPLC-MS with electrospray ionization at subambient pressure

Human serum glycan profiling with mass spectrometry (MS) has been employed to study several disease conditions and is demonstrating promise in, for example, clinical biomarker discovery. However, the low glycan ionization efficiency and the large dynamic range of glycan concentrations in human sera can hinder comprehensive profiling. In particular, large glycans are problematic because they are present at low concentrations and are prone to fragmentation. Here we show that, following liquid chromatographic separation on graphite columns, subambient pressure ionization with nanoelectrospray (SPIN)-MS can expand the serum glycome profile in comparison with the conventional atmospheric pressure electrospray ionization (ESI)-MS with a heated capillary inlet. Notably, the ions generated by the SPIN interface were observed at higher charge states for approximately half of the annotated glycans. Out of a total of 130 detected glycans, 34 were only detected with the SPIN-MS, resulting in improved coverage of glycan families as well as of glycans with larger numbers of labile monosaccharides.