Differential Quantitative Determination of Site-Specific Intact N-Glycopeptides in Serum Haptoglobin between Hepatocellular Carcinoma and Cirrhosis Using LC-EThcD-MS/MS

Data Independent Acquisition Mass Spectrometry Enhanced Personalized Glycosylation Profiling of Haptoglobin in Hepatocellular Carcinoma

Aberrant glycosylation has gained significant interest for biomarker discovery. However, low detectability, complex glycan structures, and heterogeneity present challenges in glycoprotein assay development. Using haptoglobin (Hp) as a model, we developed an integrated platform combining functionalized magnetic nanoparticles and zwitterionic hydrophilic interaction liquid chromatography (ZIC-HILIC) for highly specific glycopeptide enrichment, followed by a data-independent acquisition (DIA) strategy to establish a deep cancer-specific Hp-glycosylation profile in hepatitis B virus (HBV, n = 5) and hepatocellular carcinoma (HCC, n = 5) patients. The DIA strategy established one of the deepest Hp-glycosylation landscapes (1029 glycopeptides, 130 glycans) across serum samples, including 54 glycopeptides exclusively detected in HCC patients. Additionally, single-shot DIA searches against a DIA-based spectral library outperformed the DDA approach by 2-3-fold glycopeptide coverage across patients. Among the four N-glycan sites on Hp (N-184, N-207, N-211, N-241), the total glycan type distribution revealed significantly enhanced detection of combined fucosylated-sialylated glycans, which were the most dominant glycoforms identified in HCC patients. Quantitation analysis revealed 48 glycopeptides significantly enriched in HCC (p < 0.05), including a hybrid monosialylated triantennary glycopeptide on the N-184 site with nearly none-to-all elevation to differentiate HCC from the HBV group (HCC/HBV ratio: 2462 ± 766, p < 0.05). In summary, DIA-MS presents an unbiased and comprehensive alternative for targeted glycoproteomics to guide discovery and validation of glyco-biomarkers.

In Silico Study on a Binding Mechanism of ssDNA Aptamers Targeting Glycosidic Bond-Containing Small Molecules

Aptamer-based detection targeting glycoconjugates has attracted significant attention for its remarkable potential in identifying structural changes in saccharides in different stages of various diseases. However, the challenges in screening aptamers for small carbohydrates or glycoconjugates, which contain highly flexible and diverse glycosidic bonds, have hindered their application and commercialization. In this study, we investigated the binding conformations between three glycosidic bond-containing small molecules (GlySMs; glucose, N-acetylneuraminic acid, and neomycin) and their corresponding aptamers in silico, and analyzed factors contributing to their binding affinities. Based on the findings, a novel binding mechanism was proposed, highlighting the central role of the stem structure of the aptamer in binding and recognizing GlySMs and the auxiliary role of the mismatched bases in the adjacent loop. Guided by this binding mechanism, an aptamer with a higher 6'-sialyllactose binding affinity was designed, achieving a KD value of 4.54 ± 0.64 μM in vitro through a single shear and one mutation. The binding mechanism offers crucial guidance for designing high-affinity aptamers, enhancing the virtual screening efficiency for GlySMs. This streamlined workflow filters out ineffective binding sites, accelerating aptamer development and providing novel insights into glycan-nucleic acid interactions.

The role of N-glycosylation in cancer

Despite advances in understanding the development and progression of cancer in recent years, there remains a lack of comprehensive characterization of the cancer glycoproteome. Glycoproteins play an important role in medicine and are involved in various human disease conditions including cancer. Glycan-moieties participate in fundamental cancer processes like cell signaling, invasion, angiogenesis, and metastasis. Aberrant N-glycosylation significantly impacts cancer processes and targeted therapies in clinic. Therefore, understanding N-glycosylation in a tumor is essential for comprehending disease progression and discovering anti-cancer targets and biomarkers for therapy monitoring and diagnosis. This review presents the fundamental process of protein N-glycosylation and summarizes glycosylation changes in tumor cells, including increased terminal sialylation, N-glycan branching, and core-fucosylation. Also, the role of N-glycosylation in tumor signaling pathways, migration, and metabolism are discussed. Glycoproteins and glycopeptides as potential biomarkers for early detection of cancer based on site specificity have been introduced. Collectively, understanding and exploring the cancer glycoproteome, along with its role in medicine, implication in cancer and other human diseases, highlights the significance of N-glycosylation in tumor processes, necessitating further research for potential anti-cancer targets and biomarkers.

Discovery of a haptoglobin glycopeptides biomarker panel for early diagnosis of hepatocellular carcinoma

Background

There is a need for new serum biomarkers for early detection of hepatocellular carcinoma (HCC). Haptoglobin (Hp) N-glycosylation is altered in HCC, but the diagnostic value of site-specific Hp glycobiomarkers is rarely reported. We aimed to determine the site-specific glycosylation profile of Hp for early-stage HCC diagnosis.

Method

Hp glycosylation was analyzed in the plasma of patients with liver diseases (n=57; controls), early-stage HCC (n=50) and late-stage HCC (n=32). Hp phenotype was determined by immunoblotting. Hp was immunoisolated and digested into peptides. N-glycopeptides were identified and quantified using liquid chromatography-mass spectrometry. Cohort samples were compared using Wilcoxon rank-sum (Mann-Whitney U) tests. Diagnostic performance was assessed using receiver operating characteristic (ROC) curves and area under curve (AUC).

Results

Significantly higher fucosylation, branching and sialylation of Hp glycans, and expression of high-mannose glycans, was observed as disease progressed from cirrhosis to early- and late-stage HCC. Several glycopeptides demonstrated high values for early diagnosis of HCC, with an AUC of 93% (n=1), >80% (n=3), >75% (n=13) and >70% (n=11), compared with alpha-fetoprotein (AFP; AUC of 79%). The diagnostic performance of the identified biomarkers was only slightly affected by Hp phenotype.

Conclusion

We identified a panel of Hp glycopeptides that are significantly differentially regulated in early- and late-stage HCC. Some glycobiomarkers exceeded the diagnostic value of AFP (the most commonly used biomarker for HCC diagnosis). Our findings provide evidence that glycobiomarkers can be effective in the diagnosis of early HCC - individually, as a panel of glycopeptides or combined with conventional serological biomarkers.

MS-based glycomics and glycoproteomics methods enabling isomeric characterization

Glycosylation is one of the most significant and abundant posttranslational modifications in mammalian cells. It mediates a wide range of biofunctions, including cell adhesion, cell communication, immune cell trafficking, and protein stability. Also, aberrant glycosylation has been associated with various diseases such as diabetes, Alzheimer's disease, inflammation, immune deficiencies, congenital disorders, and cancers. The alterations in the distributions of glycan and glycopeptide isomers are involved in the development and progression of several human diseases. However, the microheterogeneity of glycosylation brings a great challenge to glycomic and glycoproteomic analysis, including the characterization of isomers. Over several decades, different methods and approaches have been developed to facilitate the characterization of glycan and glycopeptide isomers. Mass spectrometry (MS) has been a powerful tool utilized for glycomic and glycoproteomic isomeric analysis due to its high sensitivity and rich structural information using different fragmentation techniques. However, a comprehensive characterization of glycan and glycopeptide isomers remains a challenge when utilizing MS alone. Therefore, various separation methods, including liquid chromatography, capillary electrophoresis, and ion mobility, were developed to resolve glycan and glycopeptide isomers before MS. These separation techniques were coupled to MS for a better identification and quantitation of glycan and glycopeptide isomers. Additionally, bioinformatic tools are essential for the automated processing of glycan and glycopeptide isomeric data to facilitate isomeric studies in biological cohorts. Here in this review, we discuss commonly employed MS-based techniques, separation hyphenated MS methods, and software, facilitating the separation, identification, and quantitation of glycan and glycopeptide isomers.

The next "sweet" spot for pancreatic ductal adenocarcinoma: Glycoprotein for early detection

Pancreatic ductal adenocarcinoma (PDAC) is the most common neoplastic disease of the pancreas, accounting for more than 90% of all pancreatic malignancies. As a highly lethal malignancy, PDAC is the fourth leading cause of cancer-related deaths worldwide with a 5-year overall survival of less than 8%. The efficacy and outcome of PDAC treatment largely depend on the stage of disease at the time of diagnosis. Surgical resection followed by adjuvant chemotherapy remains the only possibly curative therapy, yet 80%-90% of PDAC patients present with nonresectable PDAC stages at the time of clinical presentation. Despite our advancing knowledge of PDAC, the prognosis remains strikingly poor, which is primarily due to the difficulty of diagnosing PDAC at the early stages. Recent advances in glycoproteomics and glycomics based on mass spectrometry have shown that aberrations in protein glycosylation plays a critical role in carcinogenesis, tumor progression, metastasis, chemoresistance, and immuno-response of PDAC and other types of cancers. A growing interest has thus been placed upon protein glycosylation as a potential early detection biomarker for PDAC. We herein take stock of the advancements in the early detection of PDAC that were carried out with mass spectrometry, with special focus on protein glycosylation.

Methods for quantification of glycopeptides by liquid separation and mass spectrometry

Recent advances in analytical techniques provide the opportunity to quantify even low-abundance glycopeptides derived from complex biological mixtures, allowing for the identification of glycosylation differences between healthy samples and those derived from disease states. Herein, we discuss the sample preparation procedures and the mass spectrometry (MS) strategies that have facilitated glycopeptide quantification, as well as the standards used for glycopeptide quantification. For sample preparation, various glycopeptide enrichment methods are summarized including the columns used for glycopeptide separation in liquid chromatography separation. For MS analysis strategies, MS1 level-based quantification and MS2 level-based quantification are described, either with or without labeling, where we have covered isotope labeling, TMT/iTRAQ labeling, data dependent acquisition, data independent acquisition, multiple reaction monitoring, and parallel reaction monitoring. The strengths and weaknesses of these methods are compared, particularly those associated with the figures of merit that are important for clinical biomarker studies and the pathological and functional studies of glycoproteins in various diseases. Possible future developments for glycopeptide quantification are discussed.

GlycoSLASH: Concurrent Glycopeptide Identification from Multiple Related LC-MS/MS Data Sets by Using Spectral Clustering and Library Searching

Liquid chromatography coupled with tandem mass spectrometry is commonly adopted in large-scale glycoproteomic studies involving hundreds of disease and control samples. The software for glycopeptide identification in such data (e.g., the commercial software Byonic) analyzes the individual data set and does not exploit the redundant spectra of glycopeptides presented in the related data sets. Herein, we present a novel concurrent approach for glycopeptide identification in multiple related glycoproteomic data sets by using spectral clustering and spectral library searching. The evaluation on two large-scale glycoproteomic data sets showed that the concurrent approach can identify 105%-224% more spectra as glycopeptides compared to the glycopeptide identification on individual data sets using Byonic alone. The improvement of glycopeptide identification also enabled the discovery of several potential biomarkers of protein glycosylations in hepatocellular carcinoma patients.

Quantitative clinical glycomics strategies: A guide for selecting the best analysis approach

Glycans introduce complexity to the proteins to which they are attached. These modifications vary during the progression of many diseases; thus, they serve as potential biomarkers for disease diagnosis and prognosis. The immense structural diversity of glycans makes glycosylation analysis and quantitation difficult. Fortunately, recent advances in analytical techniques provide the opportunity to quantify even low-abundant glycopeptides and glycans derived from complex biological mixtures, allowing for the identification of glycosylation differences between healthy samples and those derived from disease states. Understanding the strengths and weaknesses of different quantitative glycomics analysis methods is important for selecting the best strategy to analyze glycosylation changes in any given set of clinical samples. To provide guidance towards selecting the proper approach, we discuss four widely used quantitative glycomics analysis platforms, including fluorescence-based analysis of released N-linked glycans and three different varieties of MS-based analysis: liquid chromatography (LC)-mass spectrometry (MS) analysis of glycopeptides, matrix-assisted laser desorption ionization-time of flight MS, and LC-ESI-MS analysis of released N-linked glycans. These methods' strengths and weaknesses are compared, particularly associated with the figures of merit that are important for clinical biomarker studies, including: the initial sample requirements, the methods' throughput, sample preparation time, the number of species identified, the methods' utility for isomer separation and structural characterization, method-related challenges associated with quantitation, repeatability, the expertise required, and the cost for each analysis. This review, therefore, provides unique guidance to researchers who endeavor to undertake a clinical glycomics analysis by offering insights on the available analysis technologies.

Site-Specific Intact N-Linked Glycopeptide Characterization of Prostate-Specific Membrane Antigen from Metastatic Prostate Cancer Cells

The composition of N-linked glycans that are conjugated to the prostate-specific membrane antigen (PSMA) and their functional significance in prostate cancer progression have not been fully characterized. PSMA was isolated from two metastatic prostate cancer cell lines, LNCaP and MDAPCa2b, which have different tissue tropism and localization. Isolated PSMA was trypsin-digested, and intact glycopeptides were subjected to LC-HCD-EThcD-MS/MS analysis on a Tribrid Orbitrap Fusion Lumos mass spectrometer. Differential qualitative and quantitative analysis of site-specific N-glycopeptides was performed using Byonic and Byologic software. Comparative quantitative analysis demonstrates that multiple glycopeptides at asparagine residues 51, 76, 121, 195, 336, 459, 476, and 638 were in significantly different abundance in the two cell lines (p < 0.05). Biochemical analysis using endoglycosidase treatment and lectin capture confirm the MS and site occupancy data. The data demonstrate the effectiveness of the strategy for comprehensive analysis of PSMA glycopeptides. This approach will form the basis of ongoing experiments to identify site-specific glycan changes in PSMA isolated from disease-stratified clinical samples to uncover targets that may be associated with disease progression and metastatic phenotypes.

Glycopeptides with Sialyl Lewis Antigen in Serum Haptoglobin as Candidate Biomarkers for Nonalcoholic Steatohepatitis Hepatocellular Carcinoma Using a Higher-Energy Collision-Induced Dissociation Parallel Reaction Monitoring-Mass Spectrometry Method

Nonalcoholic steatohepatitis (NASH) is the fastest growing cause of hepatocellular carcinoma (HCC) in the United States. Changes in N-glycosylation on specific glycosites of serum proteins have been investigated as potential markers for the early detection of NASH-related HCC. Herein, we report a glycopeptide with a Sialyl Lewis structure derived from serum haptoglobin (Hp) as a potential marker for NASH related HCCs among 95 patients with NASH, including 46 cirrhosis, 32 early-stage HCC, and 17 late-stage HCC. Hp immuno-isolated from patient serum was analyzed using LC-HCD-PRM-MS/MS followed by data analysis via Skyline software. Two glycopeptides involving site N184 and four glycopeptides involving site N241 were significantly changed in patients with HCC vs NASH cirrhosis (P < 0.05). The two-marker panel using N-glycopeptide N241_A4G4F2S4 showed the best performance for HCC detection when combined with α-fetoprotein (AFP), with an improved estimated area under the curve (AUC) = 0.898 (95% CI: 0.835, 0.951), compared to the AUC of 0.790(95% CI, 0.697 0.872) using AFP alone (P = 0.048). At 90% specificity, the combination of N241_A4G4F2S4 + AFP had an improved sensitivity of 63.3%, compared to the sensitivity of 52.3% using AFP alone. When using three markers, the panel of AFP + N241_A2G2F1S2 + N241_A4G4F2S4 yielded an estimated AUC of 0.928 (95% CI: 0.877, 0.970). Our findings indicated that N241_A4G4F2S4 may play an important role in distinguishing HCC from NASH cirrhosis.

Integrated N-glycoproteomics Analysis of Human Saliva for Lung Cancer

Aberrant protein N-glycosylation is a cancer hallmark, which has great potential for cancer detection. However, large-scale and in-depth analysis of N-glycosylation remains challenging because of its high heterogeneity, complexity, and low abundance. Human saliva is an attractive diagnostic body fluid, while few efforts explored its N-glycoproteome for lung cancer. Here, we utilized a zwitterionic-hydrophilic interaction chromatography-based strategy to specifically enrich salivary glycopeptides. Through quantitative proteomics analysis, 1492 and 1234 intact N-glycopeptides were confidently identified from pooled saliva samples of 10 subjects in the nonsmall-cell lung cancer group and 10 subjects in the normal control group. Accordingly, 575 and 404 N-glycosites were revealed for the lung cancer group and normal control group. In particular, 154 N-glycosites and 259 site-specific glycoforms were significantly dysregulated in the lung cancer group. Several N-glycosites located at the same glycoprotein and glycans attached to the same N-glycosites were observed with differential expressions, including haptoglobin, Mucin-5B, lactotransferrin, and α-1-acid glycoprotein 1. These N-glycoproteins were mainly related to inflammatory responses, infectious diseases, and cancers. Our study achieved comprehensive characterization of salivary N-glycoproteome, and dysregulated site-specific glycoforms hold promise for noninvasive detection of lung cancer.

Progress of proteomics-driven precision medicine: From a glycosylation view

Currently, cancer is one of the leading causes of death worldwide, partially owing to the lack of early diagnosis methods and effective therapies. With the rapid development of various omics, the precision medicine strategy becomes a promising way to increase the survival rates by considering individual differences. Glycosylation is one of the most essential protein post-translational modifications and plays important roles in a variety of biological processes. Therefore, it is highly possible to acquire understanding of the molecular mechanisms as well as discover novel potential markers for diagnosis and prognosis based on glycoproteomics research. This review summarizes the recent glycoproteomics studies about N-glycosylation of several cancer types, mainly in the past 5 years. We also highlight corresponding mass spectrometry-based analytical methods to give a brief overview on the main techniques applied in glycoproteomics.

A New Strategy for High-Efficient Tandem Enrichment and Simultaneous Profiling of N-Glycopeptides and Phosphopeptides in Lung Cancer Tissue

N-glycosylation and phosphorylation, two common posttranslational modifications, play important roles in various biological processes and are extensively studied for biomarker and drug target screening. Because of their low abundance, enrichment of N-glycopeptides and phosphopeptides prior to LC–MS/MS analysis is essential. However, simultaneous characterization of these two types of posttranslational modifications in complex biological samples is still challenging, especially for tiny amount of samples obtained in tissue biopsy. Here, we introduced a new strategy for the highly efficient tandem enrichment of N-glycopeptides and phosphopeptides using HILIC and TiO₂ microparticles. The N-glycopeptides and phosphosites obtained by tandem enrichment were 21%–377% and 22%–263% higher than those obtained by enriching the two PTM peptides separately, respectively, using 160–20 μg tryptic digested peptides as the starting material. Under the optimized conditions, 2798 N-glycopeptides from 434 N-glycoproteins and 5130 phosphosites from 1986 phosphoproteins were confidently identified from three technical replicates of HeLa cells by mass spectrometry analysis. Application of this tandem enrichment strategy in a lung cancer study led to simultaneous characterization of the two PTM peptides and discovery of hundreds of differentially expressed N-glycosylated and phosphorylated proteins between cancer and normal tissues, demonstrating the high sensitivity of this strategy for investigation of dysregulated PTMs using very limited clinical samples.

High-Resolution Native Mass Spectrometry

Native mass spectrometry (MS) involves the analysis and characterization of macromolecules, predominantly intact proteins and protein complexes, whereby as much as possible the native structural features of the analytes are retained. As such, native MS enables the study of secondary, tertiary, and even quaternary structure of proteins and other biomolecules. Native MS represents a relatively recent addition to the analytical toolbox of mass spectrometry and has over the past decade experienced immense growth, especially in enhancing sensitivity and resolving power but also in ease of use. With the advent of dedicated mass analyzers, sample preparation and separation approaches, targeted fragmentation techniques, and software solutions, the number of practitioners and novel applications has risen in both academia and industry. This review focuses on recent developments, particularly in high-resolution native MS, describing applications in the structural analysis of protein assemblies, proteoform profiling of─among others─biopharmaceuticals and plasma proteins, and quantitative and qualitative analysis of protein-ligand interactions, with the latter covering lipid, drug, and carbohydrate molecules, to name a few.

A Fucosylated Glycopeptide as a Candidate Biomarker for Early Diagnosis of NASH Hepatocellular Carcinoma Using a Stepped HCD Method and PRM Evaluation

Aberrant specific N-glycosylation, especially the increase in fucosylation on specific peptide sites of serum proteins have been investigated as potential markers for diagnosis of nonalcoholic steatohepatitis (NASH)-related HCC. We have combined a workflow involving broad scale marker discovery in serum followed by targeted marker evaluation of these fucosylated glycopeptides. This workflow involved an LC-Stepped HCD-DDA-MS/MS method coupled with offline peptide fractionation for large-scale identification of N-glycopeptides directly from pooled serum samples (each n=10) as well as differential determination of N-glycosylation changes between disease states. We then evaluated the fucosylation level of the glycoprotein ceruloplasmin among 62 patient samples (35 cirrhosis, 27 early-stage NASH HCC) by LC-Stepped HCD-PRM-MS/MS to quantitatively analyze 18 targeted glycopeptides. Of these targets, we found the ratio of fucosylation of a tri-antennary glycopeptide from site N762, involving N762_ HexNAc(5)Hex(6)Fuc(2)NeuAc(3) (P=0.0486), increased significantly from cirrhosis to early HCC. This fucosylation ratio of a tri-antennary glycopeptide in CERU could be a potential biomarker for further validation in a larger sample set and could be a promising candidate for early detection of NASH HCC.

Serum Glycoprotein Markers in Nonalcoholic Steatohepatitis and Hepatocellular Carcinoma

Fatty liver disease progresses through stages of fat accumulation and inflammation to nonalcoholic steatohepatitis (NASH), fibrosis and cirrhosis, and eventually hepatocellular carcinoma (HCC). Currently available diagnostic tools for HCC lack sensitivity and specificity. In this study, we investigated the use of circulating serum glycoproteins to identify a panel of potential prognostic markers that may be indicative of progression from the healthy state to NASH and further to HCC. Serum samples were processed and analyzed using a novel high-throughput glycoproteomics platform. Our initial dataset contained healthy, NASH, and HCC serum samples. We analyzed 413 glycopeptides, representing 57 abundant serum proteins, and compared among the three phenotypes. We studied the normalized abundance of common glycoforms and found 40 glycopeptides with statistically significant differences in abundances in NASH and HCC compared to controls. Summary level relative abundances of core-fucosylated, sialylated, and branched glycans containing glycopeptides were higher in NASH and HCC as compared to controls. We replicated some of our findings in an independent set of samples of individuals with benign liver conditions and HCC. Our results may be of value in the management of liver diseases. Data generated in this work can be downloaded from MassIVE (https://massive.ucsd.edu) with identifier MSV000088809.

Strategies for Proteome-Wide Quantification of Glycosylation Macro- and Micro-Heterogeneity

Protein glycosylation governs key physiological and pathological processes in human cells. Aberrant glycosylation is thus closely associated with disease progression. Mass spectrometry (MS)-based glycoproteomics has emerged as an indispensable tool for investigating glycosylation changes in biological samples with high sensitivity. Following rapid improvements in methodologies for reliable intact glycopeptide identification, site-specific quantification of glycopeptide macro- and micro-heterogeneity at the proteome scale has become an urgent need for exploring glycosylation regulations. Here, we summarize recent advances in N- and O-linked glycoproteomic quantification strategies and discuss their limitations. We further describe a strategy to propagate MS data for multilayered glycopeptide quantification, enabling a more comprehensive examination of global and site-specific glycosylation changes. Altogether, we show how quantitative glycoproteomics methods explore glycosylation regulation in human diseases and promote the discovery of biomarkers and therapeutic targets.

Relative Quantification of N-Glycopeptide Sialic Acid Linkage Isomers by Ion Mobility Mass Spectrometry

Sialic acids decorate the surface of glycoproteins and play important roles in a variety of pathological processes. Although the mass spectrometry (MS) based linkage-specific analysis of sialylated N-glycopeptide is developing rapidly, quantitative analysis of these isomers still remains a challenge. Herein, we reported a novel quantitative strategy that can unambiguously identify and relatively quantify linkage-specific N-glycopeptides using ion mobility mass spectrometry (IM-MS). Without the assistance of derivatization, this method can relatively quantify sialic acid isomers of intact glycopeptides by using their characteristic fragment ions in IM-MS. Moreover, good linearity (R² > 0.99) of relative quantification within a dynamic range of 2 orders of magnitude and high reproducibility (coefficient of variation (CV) < 10%, n = 3) were demonstrated. Finally, our results illustrated the aberrant sialylation of haptoglobin (Hp) in hepatocellular carcinoma (HCC), where the ratios of α2,3 to α2,6 sialylation of seven N-glycopeptides were found to be significantly altered (p < 0.01) in HCC individuals (n = 27) compared with healthy controls (n = 27).

The opportunity cost of automated glycopeptide analysis: case study profiling the SARS-CoV-2 S glycoprotein

Glycosylation analysis of viral glycoproteins contributes significantly to vaccine design and development. Among other benefits, glycosylation analysis allows vaccine developers to assess the impact of construct design or producer cell line choices for vaccine production, and it is a key measure by which glycoproteins that are produced for use in vaccination can be compared to their native viral forms. Because many viral glycoproteins are multiply glycosylated, glycopeptide analysis is a preferrable approach for mapping the glycans, yet the analysis of glycopeptide data can be cumbersome and requires the expertise of an experienced analyst. In recent years, a commercial software product, Byonic, has been implemented in several instances to facilitate glycopeptide analysis on viral glycoproteins and other glycoproteomics data sets, and the purpose of the study herein is to determine the strengths and limitations of using this software, particularly in cases relevant to vaccine development. The glycopeptides from a recombinantly expressed trimeric S glycoprotein of the SARS-CoV-2 virus were first analyzed using an expert-based analysis strategy; subsequently, analysis of the same data set was completed using Byonic. Careful assessment of instances where the two methods produced different results revealed that the glycopeptide assignments from Byonic contained more false positives than true positives, even when the data were assessed using a 1% false discovery rate. The work herein provides a roadmap for removing the spurious assignments that Byonic generates, and it provides an assessment of the opportunity cost for relying on automated assignments for glycopeptide data sets from viral glycoproteins.

The Hitchhiker's guide to glycoproteomics

Protein glycosylation is one of the most common post-translational modifications that are essential for cell function across all domains of life. Changes in glycosylation are considered a hallmark of many diseases, thus making glycoproteins important diagnostic and prognostic biomarker candidates and therapeutic targets. Glycoproteomics, the study of glycans and their carrier proteins in a system-wide context, is becoming a powerful tool in glycobiology that enables the functional analysis of protein glycosylation. This 'Hitchhiker's guide to glycoproteomics' is intended as a starting point for anyone who wants to explore the emerging world of glycoproteomics. The review moves from the techniques that have been developed for the characterisation of single glycoproteins to technologies that may be used for a successful complex glycoproteome characterisation. Examples of the variety of approaches, methodologies, and technologies currently used in the field are given. This review introduces the common strategies to capture glycoprotein-specific and system-wide glycoproteome data from tissues, body fluids, or cells, and a perspective on how integration into a multi-omics workflow enables a deep identification and characterisation of glycoproteins - a class of biomolecules essential in regulating cell function.

ZIC-cHILIC Functionalized Magnetic Nanoparticle for Rapid and Sensitive Glycopeptide Enrichment from <1 µL Serum

Due to their unique glycan composition and linkage, protein glycosylation plays significant roles in cellular function and is associated with various diseases. For comprehensive characterization of their extreme structural complexity occurring in >50% of human proteins, time-consuming multi-step enrichment of glycopeptides is required. Here we report zwitterionic n-dodecylphosphocholine-functionalized magnetic nanoparticles (ZIC-cHILIC@MNPs) as a highly efficient affinity nanoprobe for large-scale enrichment of glycopeptides. We demonstrate that ZIC-cHILIC@MNPs possess excellent affinity, with 80-91% specificity for glycopeptide enrichment, especially for sialylated glycopeptide (90%) from biofluid specimens. This strategy provides rapidity (~10 min) and high sensitivity (<1 μL serum) for the whole enrichment process in patient serum, likely due to the rapid separation using magnetic nanoparticles, fast reaction, and high performance of the affinity nanoprobe at nanoscale. Using this strategy, we achieved personalized profiles of patients with hepatitis B virus (HBV, n = 3) and hepatocellular carcinoma (HCC, n = 3) at the depth of >3000 glycopeptides, especially for the large-scale identification of under-explored sialylated glycopeptides. The glycoproteomics atlas also revealed the differential pattern of sialylated glycopeptides between HBV and HCC groups. The ZIC-cHILIC@MNPs could be a generic tool for advancing the glycoproteome analysis, and contribute to the screening of glycoprotein biomarkers.

PRM-MS Quantitative Analysis of Isomeric N-Glycopeptides Derived from Human Serum Haptoglobin of Patients with Cirrhosis and Hepatocellular Carcinoma

Currently, surveillance strategies have inadequate performance for cirrhosis and early detection of hepatocellular carcinoma (HCC). The glycosylation of serum haptoglobin has shown to have significant differences between cirrhosis and HCC, thus can be used for diagnosis. We performed a comprehensive liquid chromatography—parallel reaction monitoring—mass spectrometry (LC-PRM-MS) approach, where a targeted parallel reaction monitoring (PRM) strategy was coupled to a powerful LC system, to study the site-specific isomerism of haptoglobin (Hp) extracted from cirrhosis and HCC patients. We found that our strategy was able to identify a large number of isomeric N-glycopeptides, mainly located in the Hp glycosylation site Asn207. Four N-glycopeptides were found to have significant changes in abundance between cirrhosis and HCC samples (p < 0.05). Strategic combinations of the significant N-glycopeptides, either with alpha-fetoprotein (AFP) or themselves, better estimate the areas under the curve (AUC) of their respective receiver operating characteristic (ROC) curves with respect to AFP. The combination of AFP with the isomeric sialylated fucosylated N-glycopeptides Asn207 + 5-6-1-2 and Asn207 + 5-6-1-3, resulted with an AUC value of 0.98, while the AUC value for AFP alone was 0.85. When comparing cirrhosis vs. early HCC, the isomeric N-glycopeptide Asn207 + 5-6-0-1 better estimated AUC with respect to AFP (AUC_AFP = 0.81, and AUC_Asn207 + 5-6-0-1 = 0.88, respectively).

Quantification of Intact O-Glycopeptides on Haptoglobin in Sera of Patients With Hepatocellular Carcinoma and Liver Cirrhosis

Haptoglobin (Hp) is one of the acute-phase response proteins secreted by the liver, and its aberrant N-glycosylation was previously reported in hepatocellular carcinoma (HCC). Limited studies on Hp O-glycosylation have been previously reported. In this study, we aimed to discover and confirm its O-glycosylation in HCC based on lectin binding and mass spectrometry (MS) detection. First, serum Hp was purified from patients with liver cirrhosis (LC) and HCC, respectively. Then, five lectins with Gal or GalNAc monosaccharide specificity were chosen to perform lectin blot, and the results showed that Hp in HCC bound to these lectins in a much stronger manner than that in LC. Furthermore, label-free quantification based on MS was performed. A total of 26 intact O-glycopeptides were identified on Hp, and most of them were elevated in HCC as compared to LC. Among them, the intensity of HYEGS³¹⁶TVPEK (H1N1S1) on Hp was the highest in HCC patients. Increased HYEGS³¹⁶TVPEK (H1N1S1) in HCC was quantified and confirmed using the MS method based on ¹⁸O/¹⁶O C-terminal labeling and multiple reaction monitoring. This study provided a comprehensive understanding of the glycosylation of Hp in liver diseases.

Detection of Aberrant Glycosylation of Serum Haptoglobin for Gastric Cancer Diagnosis Using a Middle-Up-Down Glycoproteome Platform

Gastric cancer is a frequently occurring cancer and is the leading cause of cancer-related deaths. Recent studies have shown that aberrant glycosylation of serum haptoglobin is closely related to gastric cancer and has enormous potential for use in diagnosis. However, there is no platform with high reliability and high reproducibility to comprehensively analyze haptoglobin glycosylation covering microheterogeneity to macroheterogeneity for clinical applications. In this study, we developed a middle-up-down glycoproteome platform for fast and accurate monitoring of haptoglobin glycosylation. This platform utilizes an online purification of LC for sample desalting, and an in silico haptoglobin glycopeptide library constructed by combining peptides and N-glycans to readily identify glycopeptides. In addition, site-specific glycosylation with glycan heterogeneity can be obtained through only a single MS analysis. Haptoglobin glycosylation in clinical samples consisting of healthy controls (n = 47) and gastric cancer patients (n = 43) was extensively investigated using three groups of tryptic glycopeptides: GP1 (including Asn184), GP2 (including Asn207 and Asn211), and GP3 (including Asn241). A total of 23 individual glycopeptides were determined as potential biomarkers (p < 0.00001). In addition, to improve diagnostic efficacy, we derived representative group biomarkers with high AUC values (0.929 to 0.977) through logistic regression analysis for each GP group. It has been found that glycosylation of haptoglobin is highly associated with gastric cancer, especially the glycosite Asn241. Our assay not only allows to quickly and easily obtain information on glycosylation heterogeneity of a target glycoprotein but also makes it an efficient tool for biomarker discovery and clinical diagnosis.

GlycoHybridSeq: Automated Identification of N-Linked Glycopeptides Using Electron Transfer/High-Energy Collision Dissociation (EThcD)

Glycosylation is one of the most common post-translational modifications (PTM) occurring in a large variety of proteins with important biological functions in human and other higher organisms. Liquid chromatography tandem mass spectrometry (LC-MS/MS) has been routinely used to characterize site-specific protein glycosylation at high throughput in complex glycoproteomic samples. Recently, electron transfer/high-energy collision dissociation (EThcD) was introduced for glycopeptide identification, which offers rich structural information on glycopepides with the fragment ions from the cleavages of both the glycan and the peptide backbone. Herein, we present the software GlycoHybridSeq for automated interpretation of EThcD-MS/MS spectra from glycoproteomic data using a customized scoring function, which enables the functionalities of identifying glycopeptides, characterizing glycosylation sites, and distinguishing some isomeric glycans. We evaluate GlycoHybridSeq on glycoproteomic data collected for cancer biomarker discovery. The results showed that it achieved comparable or better performance than that of Byonic and MSFragger. GlycoHybridSeq is released as an open source software and is ready to be used in large-scale glycoproteomic data analyses.

A Panel of Glycopeptides as Candidate Biomarkers for Early Diagnosis of NASH Hepatocellular Carcinoma Using a Stepped HCD Method and PRM Evaluation

Changes in N-glycosylation on specific peptide sites of serum proteins have been investigated as potential markers for diagnosis of nonalcoholic steatohepatitis (NASH)-related HCC. To accomplish this work, a novel workflow involving broad-scale marker discovery in serum followed by targeted marker evaluation of these glycopeptides were combined. The workflow involved an LC-Stepped HCD-DDA-MS/MS method coupled with offline peptide fractionation for large-scale identification of N-glycopeptides directly from pooled serum samples (each n = 10) as well as differential determination of N-glycosylation changes between disease states. We then evaluated several potentially diagnostic N-glycopeptides among 78 individual patient samples (40 cirrhosis, 28 early stage NASH HCC, and 10 late-stage NASH HCC) by LC-Stepped HCD-PRM-MS/MS to quantitatively analyze 65 targeted glycopeptides from 7 glycoproteins. Of these targets, we found site-specific N-glycopeptides n¹⁶⁹GSLFAFR_HexNAc(4)Hex(5)NeuAc(2) and n²⁴²ISDGFDGIPDNVDAALALPAHSYSGR_HexNAc(5)Hex(6)Fuc(1)NeuAc(3) from VTNC were significantly increased comparing samples from patients with NASH cirrhosis and NASH HCC (p < 0.05). When combining results of these 2 glycopeptides with AFP, the ROC curve analysis demonstrated the AUC value increased to 0.834 (95% CI, 0.748-0.921) and 0.847 (95% CI, 0.766-0.932), respectively, as compared to that of AFP alone (AUC = 0.791, 95% CI, 0.690-0.892). These 2 glycopeptides may serve as potential biomarkers for early HCC diagnosis in patients with NASH related cirrhosis.

Optimal Dissociation Methods Differ for N- and O-Glycopeptides

Site-specific characterization of glycosylation requires intact glycopeptide analysis, and recent efforts have focused on how to best interrogate glycopeptides using tandem mass spectrometry (MS/MS). Beam-type collisional activation, i.e., higher-energy collisional dissociation (HCD), has been a valuable approach, but stepped collision energy HCD (sceHCD) and electron transfer dissociation with HCD supplemental activation (EThcD) have emerged as potentially more suitable alternatives. Both sceHCD and EThcD have been used with success in large-scale glycoproteomic experiments, but they each incur some degree of compromise. Most progress has occurred in the area of N-glycoproteomics. There is growing interest in extending this progress to O-glycoproteomics, which necessitates comparisons of method performance for the two classes of glycopeptides. Here, we systematically explore the advantages and disadvantages of conventional HCD, sceHCD, ETD, and EThcD for intact glycopeptide analysis and determine their suitability for both N- and O-glycoproteomic applications. For N-glycopeptides, HCD and sceHCD generate similar numbers of identifications, although sceHCD generally provides higher quality spectra. Both significantly outperform EThcD methods in terms of identifications, indicating that ETD-based methods are not required for routine N-glycoproteomics even if they can generate higher quality spectra. Conversely, ETD-based methods, especially EThcD, are indispensable for site-specific analyses of O-glycopeptides. Our data show that O-glycopeptides cannot be robustly characterized with HCD-centric methods that are sufficient for N-glycopeptides, and glycoproteomic methods aiming to characterize O-glycopeptides must be constructed accordingly.

Quantitative Analysis of α-1-Antitrypsin Glycosylation Isoforms in HCC Patients Using LC-HCD-PRM-MS

The change in glycosylation of serum proteins is often associated with the development of various diseases and thus can be used for diagnosis. In this study, a liquid chromatography-tandem mass spectrometry-based method is used for accurate structural analysis and quantification of site-specific glycoforms of serum α-1-antitrypsin (A1AT) in early-stage HCC and cirrhosis patients. Serum protein A1AT was purified from patient sera by immunoprecipitation with anti-A1AT antibody conjugated agarose beads, and the isolated A1AT protein was digested and analyzed by LC-MS/MS. Two tandem mass spectrometry strategies are integrated in this study: a nontargeted stepped HCD strategy for structural analysis of A1AT glycopeptides and a targeted parallel reaction monitoring (PRM) strategy for quantification of site-specific glycoforms of A1AT in HCC and cirrhosis patient sera. Accordingly, pGlyco2.0 software was used for glycopeptide identification, and Skyline software was used for glycoform quantification using the Y1 ion (peptide+GlcNAc) in MS/MS spectra. Ten site-specific glycopeptides of A1AT were identified with stepped HCD-MS/MS in patient samples, 7 of which were further quantified using HCD-PRM-MS among patient samples. We found that our strategy was able to distinguish isomers of glycopeptides where several isomers showed distinctly different patterns between cirrhosis and HCC patients. We also found that the ratio of different charge states (2+/3+) of one glycopeptide of A1AT can significantly discriminate early-stage HCC from cirrhosis with the area under the receiver operating characteristic curve AUC of 0.9. Further analysis showed that the difference may be related to the sialic acid/galactose linkage of the glycan motif.

Glycopeptide Biomarkers in Serum Haptoglobin for Hepatocellular Carcinoma Detection in Patients with Nonalcoholic Steatohepatitis

Nonalcoholic steatohepatitis (NASH) is rising in prevalence in the United States and is a growing cause of hepatocellular carcinomas (HCCs). Site-specific glycan heterogeneity on glycoproteins has been shown as a potential diagnostic biomarker for HCC. Herein, we have performed a comprehensive screening of site-specific N-glycopeptides in serum haptoglobin (Hp), a reporter molecule for aberrant glycosylation in HCC, to characterize glycopeptide markers for NASH-related HCCs. In total, 70 NASH patients (22 early HCC, 15 advanced HCC, and 33 cirrhosis cases) were analyzed, with Hp purified from 20 μL of serum in each patient, and 140 sets of mass spectrometry (MS) data were collected using liquid chromatography coupled with electron-transfer high-energy collisional dissociation tandem MS (LC-EThcD-MS/MS) for quantitative analysis on a novel software platform, Byos. Differential quantitation analysis revealed that five N-glycopeptides at sites N184 and N241 were significantly elevated during the progression from NASH cirrhosis to HCC (p < 0.05). Receiver operating characteristic (ROC) curve analysis demonstrated that the N-glycopeptides at sites N184 and N241 bearing a monofucosylated triantennary glycan A3G3F1S3 had the best diagnostic performance in detection of early NASH HCC, area under the curve (AUC) = 0.733 and 0.775, respectively, whereas α-fetoprotein (AFP) had an AUC of 0.692. When combined with AFP, the two panels improved the sensitivity for early NASH HCC from 59% (AFP alone) to 73% while maintaining a specificity of 70%, based on the optimal cutoff. Two-dimensional (2-D) scatter plots of the AFP value and N-glycopeptides showed that these N-glycopeptide markers detected 58% of AFP-negative HCC patients as distinct from cirrhosis. These site-specific N-glycopeptides could serve as potential markers for early detection of HCC in patients with NASH-related cirrhosis.

Signature-Ion-Triggered Mass Spectrometry Approach Enabled Discovery of N- and O-Linked Glycosylated Neuropeptides in the Crustacean Nervous System

Crustaceans are commonly used model organisms to study neuromodulation. Despite numerous reported crustacean neuropeptide families and their functions, there has been no report on neuropeptide glycosylation. This is in part due to a lack of sensitive methods that enable deciphering this intricate low-abundance post-translational modification, even though glycosylation has been shown to play an important role in neuromodulation. Here, we describe the discovery of glycosylated neuropeptides with an enrichment-free approach, taking advantage of signature oxonium ions produced in higher-energy collision dissociation (HCD) MS/MS spectra. The detection of the oxonium ions in the HCD scans suggests glycan attachment to peptides, allowing electron-transfer/higher-energy collision dissociation (EThcD) to be performed to selectively elucidate structural information of glycosylated neuropeptides that are buried in nonglycosylated peptides. Overall, 4 N-linked and 14 O-linked glycosylated neuropeptides have been identified for the first time in the crustacean nervous system. In addition, 91 novel putative neuropeptides have been discovered based on the collected HCD scans. This hybrid approach, coupling a shotgun method for neuropeptide discovery and targeted strategy for glycosylation characterization, enables the first report on glycosylated neuropeptides in crustaceans and the discovery of additional neuropeptides simultaneously. The elucidation of novel glycosylated neuropeptides sheds light on the crustacean peptidome and offers novel insights into future neuropeptide functional studies.

N-glycopeptide Signatures of IgA2 in Serum from Patients with Hepatitis B Virus-related Liver Diseases

N-glycosylation alteration has been reported in liver diseases. Characterizing N-glycopeptides that correspond to N-glycan structure with specific site information enables better understanding of the molecular pathogenesis of liver damage and cancer. Here, unbiased quantification of N-glycopeptides of a cluster of serum glycoproteins with 40-55 kDa molecular weight (40-kDa band) was investigated in hepatitis B virus (HBV)-related liver diseases. We used an N-glycopeptide method based on 18O/16O C-terminal labeling to obtain 82 comparisons of serum from patients with HBV-related hepatocellular carcinoma (HCC) and liver cirrhosis (LC). Then, multiple reaction monitoring (MRM) was performed to quantify N-glycopeptide relative to the protein content, especially in the healthy donor-HBV-LC-HCC cascade. TPLTAN205ITK (H5N5S1F1) and (H5N4S2F1) corresponding to the glycopeptides of IgA2 were significantly elevated in serum from patients with HBV infection and even higher in HBV-related LC patients, as compared with healthy donor. In contrast, the two glycopeptides of IgA2 fell back down in HBV-related HCC patients. In addition, the variation in the abundance of two glycopeptides was not caused by its protein concentration. The altered N-glycopeptides might be part of a unique glycan signature indicating an IgA-mediated mechanism and providing potential diagnostic clues in HBV-related liver diseases.

Disease-specific haptoglobin-β chain N-glycosylation as biomarker to differentiate non-small cell lung cancer from benign lung diseases

Background: The association of pathological states with N-glycosylation of haptoglobin-β has attracted increasing attention.

Materials & Methods: In the present study, disease-specific haptoglobin-β (DSHp-β) was separated from serum immunoinflammation-related protein complexes (IIRPCs) of 600 participants including 300 patients with benign lung diseases (BLDs) and 300 patients with non-small cell lung cancer (NSCLC). The enriched glycopeptides of the tryptic digests of the DSHp-β were analyzed using matrix assisted laser desorption/ionization-Fourier transform ion cyclotron resonance mass spectrometry (MALDI-FTICR MS).

Results: 20 of glycopeptides were detected for each sample. The statistical analysis has indicated that significant changes in the sialylation of DSHp-β between BLDs and NSCLC patients were observed. The age- and sex-matched participants were randomly clarified into the training set and the validation set. Receiver operating characteristic (ROC) analysis has revealed that the level ratio of glycopeptides (G2G3/G2G3S4) at the sites of Asn207/211 has potential capability to distinguish BLDs from NSCLC, with the sensitivity of 74.4%, the specificity of 82.8%, and the area under curve (AUC) of 0.805.

Conclusion: The glycosylation of DSHp-β can distinguish NSCLC from BLDs with high diagnostic accuracy compared with current clinical available serum markers.

Isolation and characterization of glycosylated neuropeptides

Glycosylation is one of the most ubiquitous and complex post-translational modifications (PTMs). It plays pivotal roles in various biological processes. Studies at the glycopeptide level are typically considered as a downstream work resulting from enzymatic digested glycoproteins. Less attention has been focused on glycosylated endogenous signaling peptides due to their low abundance, structural heterogeneity and the lack of enabling analytical tools. Here, protocols are presented to isolate and characterize glycosylated neuropeptides utilizing nanoflow liquid chromatography coupled with mass spectrometry (LC-MS). We first demonstrate how to extract neuropeptides from raw tissues and perform further separation/cleanup before MS analysis. Then we describe hybrid MS methods for glycosylated neuropeptide profiling and site-specific analysis. We also include recommendations for data analysis to identify glycosylated neuropeptides in crustaceans where a complete neuropeptide database is still lacking. Other strategies and future directions are discussed to provide readers with alternative approaches and further unravel biological complexity rendered by glycosylation.

Simply Extending the Mass Range in Electron Transfer Higher Energy Collisional Dissociation Increases Confidence in N-Glycopeptide Identification

Glycopeptide-centric mass spectrometry has become a popular approach for studying protein glycosylation. However, current approaches still utilize fragmentation schemes and ranges originally optimized and intended for the analysis of typically much smaller unmodified tryptic peptides. Here, we show that by merely increasing the tandem mass spectrometry m/z range from 2000 to 4000 during electron transfer higher energy collisional dissociation (EThcD) fragmentation, a wealth of highly informative c and z ion fragment ions are additionally detected, facilitating improved identification of glycopeptides. We demonstrate the benefit of this extended mass range on various classes of glycopeptides containing phosphorylated, fucosylated, and/or sialylated N-glycans. We conclude that the current software solutions for glycopeptide identification also require further improvements to realize the full potential of extended mass range glycoproteomics. To stimulate further developments, we provide data sets containing all classes of glycopeptides (high mannose, hybrid, and complex) measured with standard (2000) and extended (4000) m/z range that can be used as test cases for future development of software solutions enhancing automated glycopeptide analysis.

Glycoproteomic markers of hepatocellular carcinoma-mass spectrometry based approaches

Hepatocellular carcinoma (HCC) is the third most-common cause of cancer-related death worldwide. Most cases of HCC develop in patients that already have liver cirrhosis and have been recommended for surveillance for an early onset of HCC. Cirrhosis is the final common pathway for several etiologies of liver disease, including hepatitis B and C, alcohol, and increasingly non-alcoholic fatty liver disease. Only 20-30% of patients with HCC are eligible for curative therapy due primarily to inadequate early-detection strategies. Reliable, accurate biomarkers for HCC early detection provide the highest likelihood of curative therapy and survival; however, current early-detection methods that use abdominal ultrasound and serum alpha fetoprotein are inadequate due to poor adherence and limited sensitivity and specificity. There is an urgent need for convenient and highly accurate validated biomarkers for HCC early detection. The theme of this review is the development of new methods to discover glycoprotein-based markers for detection of HCC with mass spectrometry approaches. We outline the non-mass spectrometry based methods that have been used to discover HCC markers including immunoassays, capillary electrophoresis, 2-D gel electrophoresis, and lectin-FLISA assays. We describe the development and results of mass spectrometry-based assays for glycan screening based on either MALDI-MS or ESI analysis. These analyses might be based on the glycan content of serum or on glycan screening for target molecules from serum. We describe some of the specific markers that have been developed as a result, including for proteins such as Haptoglobin, Hemopexin, Kininogen, and others. We discuss the potential role for other technologies, including PGC chromatography and ion mobility, to separate isoforms of glycan markers. Analyses of glycopeptides based on new technologies and innovative softwares are described and also their potential role in discovery of markers of HCC. These technologies include new fragmentation methods such as EThcD and stepped HCD, which can identify large numbers of glycopeptide structures from serum. The key role of lectin extraction in various assays for intact glycopeptides or their truncated versions is also described, where various core-fucosylated and hyperfucosylated glycopeptides have been identified as potential markers of HCC. Finally, we describe the role of LC-MRMs or lectin-FLISA MRMs as a means to validate these glycoprotein markers from patient samples. These technological advancements in mass spectrometry have the potential to lead to novel biomarkers to improve the early detection of HCC.