Site-Specific N-Linked Glycosylation Analysis of Human Carcinoembryonic Antigen by Sheathless Capillary Electrophoresis-Tandem Mass Spectrometry

Recent advances in microscale separation techniques for glycome analysis

The glycomic analysis holds significant appeal due to the diverse roles that glycans and glycoconjugates play, acting as modulators and mediators in cellular interactions, cell/organism structure, drugs, energy sources, glyconanomaterials, and more. The glycomic analysis relies on liquid-phase separation technologies for molecular purification, separation, and identification. As a miniaturized form of liquid-phase separation technology, microscale separation technologies offer various advantages such as environmental friendliness, high resolution, sensitivity, fast speed, and integration capabilities. For glycan analysis, microscale separation technologies are continuously evolving to address the increasing challenges in their unique manners. This review discusses the fundamentals and applications of microscale separation technologies for glycomic analysis. It covers liquid-phase separation technologies operating at scales generally less than 100 µm, including capillary electrophoresis, nanoflow liquid chromatography, and microchip electrophoresis. We will provide a brief overview of glycomic analysis and describe new strategies in microscale separation and their applications in glycan analysis from 2014 to 2023.

Decoding the glycoproteome: a new frontier for biomarker discovery in cancer

Cancer early detection and treatment response prediction continue to pose significant challenges. Cancer liquid biopsies focusing on detecting circulating tumor cells (CTCs) and DNA (ctDNA) have shown enormous potential due to their non-invasive nature and the implications in precision cancer management. Recently, liquid biopsy has been further expanded to profile glycoproteins, which are the products of post-translational modifications of proteins and play key roles in both normal and pathological processes, including cancers. The advancements in chemical and mass spectrometry-based technologies and artificial intelligence-based platforms have enabled extensive studies of cancer and organ-specific changes in glycans and glycoproteins through glycomics and glycoproteomics. Glycoproteomic analysis has emerged as a promising tool for biomarker discovery and development in early detection of cancers and prediction of treatment efficacy including response to immunotherapies. These biomarkers could play a crucial role in aiding in early intervention and personalized therapy decisions. In this review, we summarize the significant advance in cancer glycoproteomic biomarker studies and the promise and challenges in integration into clinical practice to improve cancer patient care.

Multiplexed Antibody Glycosylation Profiling Using Dual Enzyme Digestion and Liquid Chromatography-Triple Quadrupole Mass Spectrometry Method

Antibody glycosylation plays a crucial role in the humoral immune response by regulating effector functions and influencing the binding affinity to immune cell receptors. Previous studies have focused mainly on the immunoglobulin G (IgG) isotype owing to the analytical challenges associated with other isotypes. Thus, the development of a sensitive and accurate analytical platform is necessary to characterize antibody glycosylation across multiple isotypes. In this study, we have developed an analytical workflow using antibody-light-chain affinity beads to purify IgG, IgA, and IgM from 16 μL of human plasma. Dual enzymes, trypsin and Glu-C, were used during on-bead digestion to obtain enzymatic glycopeptides and protein-specific surrogate peptides. Ultra-high-performance liquid chromatography coupled with triple quadrupole mass spectrometry was used in order to determine the sensitivity and specificity. Our platform targets 95 glycopeptides across the IgG, IgA, and IgM isotypes, as well as eight surrogate peptides representing total IgG, four IgG classes, two IgA classes, and IgM. Four stable isotope-labeled internal standards were added after antibody purification to calibrate the preparation and instrumental bias during analysis. Calibration curves constructed using serially diluted plasma samples showed good curve fitting (R2 > 0.959). The intrabatch and interbatch precision for all the targets had relative standard deviation of less than 29.6%. This method was applied to 19 human plasma samples, and the glycosylation percentages were calculated, which were comparable to those reported in the literature. The developed method is sensitive and accurate for Ig glycosylation profiling. It can be used in clinical investigations, particularly for detailed humoral immune profiling.

Diagnostic Potential of Serum Glycome Analysis in Lung Cancer: A Glycopattern Study

Lung cancer is the leading cause of cancer-related death, with high morbidity and mortality rates due to the lack of reliable methods for diagnosing lung cancer at an early stage. Low-dose computed tomography can help detect abnormal areas in the lungs, but only 16% of cases are diagnosed early. Tests for lung cancer markers are often employed to determine genetic expression or mutations in lung carcinogenesis. Serum glycome analysis is a promising new method for early lung cancer diagnosis as glycopatterns exhibit significant differences in lung cancer patients. In this study, we employed a solid-phase chemoenzymatic method to systematically compare glycopatterns in benign cases, adenocarcinoma before and after surgery, and advanced stages of adenocarcinoma. Our findings indicate that serum high-mannose levels are elevated in both benign cases and adenocarcinoma, while complex N-glycans, including fucose and 2,6-linked sialic acid, are downregulated in the serum. Subsequently, we developed an algorithm that utilizes 16 altered N-glycans, 7 upregulated and 9 downregulated, to generate a score based on their intensity. This score can predict the stages of cancer progression in patients through glycan characterization. This methodology offers a potential means of diagnosing lung cancer through serum glycome analysis.

Chemical Proteomic Approach for In-Depth Glycosylation Profiling of Plasma Carcinoembryonic Antigen in Cancer Patients

Carcinoembryonic antigen (CEA) of human plasma is a biomarker of many cancer diseases, and its N-glycosylation accounts for 60% of molecular mass. It is highly desirable to characterize its glycoforms for providing additional dimension of features to increase its performance in prognosis and diagnosis of cancers. However, to systematically characterize its site-specific glycosylation is challenging because of its low abundance. Here, we developed a highly sensitive strategy for in-depth glycosylation profiling of plasma CEA through chemical proteomics combined with multienzymatic digestion. A trifunctional probe was utilized to generate covalent bond of plasma CEA and its antibody upon UV irradiation. As low as 1 ng/ml CEA in plasma could be captured and digested with trypsin and chymotrypsin for intact glycopeptide characterization. Twenty six of 28 potential N-glycosylation sites were well identified, which were the most comprehensive N-glycosylation site characterization of CEA on intact glycopeptide level as far as we known. Importantly, this strategy was applied to the glycosylation analysis of plasma CEA in cancer patients. Differential site-specific glycoforms of plasma CEA were observed in patients with colorectal cancers (CRCs) and lung cancer. The distributions of site-specific glycoforms were different as the progression of CRC, and most site-specific glycoforms were overexpressed in stage II of CRC. Overall, we established a highly sensitive chemical proteomic method to profile site-specific glycosylation of plasma CEA, which should generally applicable to other well-established cancer glycoprotein biomarkers for improving their cancer diagnosis and monitoring performance.

Cyst fluid glycoproteins accurately distinguishing malignancies of pancreatic cystic neoplasm

Pancreatic cystic neoplasms (PCNs) are recognized as precursor lesions of pancreatic cancer, with a marked increase in prevalence. Early detection of malignant PCNs is crucial for improving prognosis; however, current diagnostic methods are insufficient for accurately identifying malignant PCNs. Here, we utilized mass spectrometry (MS)-based glycosite- and glycoform-specific glycoproteomics, combined with proteomics, to explore potential cyst fluid diagnostic biomarkers for PCN. The glycoproteomic and proteomic landscape of pancreatic cyst fluid samples from PCN patients was comprehensively investigated, and its characteristics during the malignant transformation of PCN were analyzed. Under the criteria of screening specific cyst fluid biomarkers for the diagnosis of PCN, a group of cyst fluid glycoprotein biomarkers was identified. Through parallel reaction monitoring (PRM)-based targeted glycoproteomic analysis, we validated these chosen glycoprotein biomarkers in a second cohort, ultimately confirming N-glycosylated PHKB (Asn-935, H5N2F0S0; Asn-935, H4N4F0S0; Asn-935, H5N4F0S0), CEACAM5 (Asn-197, H5N4F0S0) and ATP6V0A4 (Asn-367, H6N4F0S0) as promising diagnostic biomarkers for distinguishing malignant PCNs. These glycoprotein biomarkers exhibited robust performance, with an area under the curve ranging from 0.771 to 0.948. In conclusion, we successfully established and conducted MS-based glycoproteomic analysis to identify novel cyst fluid glycoprotein biomarkers for PCN. These findings hold significant clinical implications, providing valuable insights for PCN decision-making, and potentially offering therapeutic targets for PCN treatment.

Capitalizing glycomic changes for improved biomarker-based cancer diagnostics

Cancer serum biomarkers are valuable or even indispensable for cancer diagnostics and/or monitoring and, currently, many cancer serum markers are routinely used in the clinic. Most of those markers are glycoproteins, carrying cancer-specific glycan structures that can provide extra-information for cancer monitoring. Nonetheless, in the majority of cases, this differential feature is not exploited and the corresponding analytical assays detect only the protein amount, disregarding the analysis of the aberrant glycoform. Two exceptions to this trend are the biomarkers α-fetoprotein (AFP) and cancer antigen 19-9 (CA19-9), which are clinically monitored for their cancer-related glycan changes, and only the AFP assay includes quantification of both the protein amount and the altered glycoform. This narrative review demonstrates, through several examples, the advantages of the combined quantification of protein cancer biomarkers and the respective glycoform analysis, which enable to yield the maximum information and overcome the weaknesses of each individual analysis. This strategy allows to achieve higher sensitivity and specificity in the detection of cancer, enhancing the diagnostic power of biomarker-based cancer detection tests.

The role of clinical glyco(proteo)mics in precision medicine

Glycoproteomics reveals site-specific O- and N-glycosylation that may influence protein properties including binding, activity and half-life. The increasingly mature toolbox with glycomic- and glycoproteomic strategies is applied for the development of biopharmaceuticals and discovery and clinical evaluation of glycobiomarkers in various disease fields. Notwithstanding the contributions of glycoscience in identifying new drug targets, the current report is focused on the biomarker modality that is of interest for diagnostic and monitoring purposes. To this end it is noted that the identification of biomarkers has received more attention than corresponding quantification. Most analytical methods are very efficient in detecting large numbers of analytes but developments to accurately quantify these have so far been limited. In this perspective a parallel is made with earlier proposed tiers for protein quantification using mass spectrometry. Moreover, the foreseen reporting of multimarker readouts is discussed to describe an individual's health or disease state and their role in clinical decision-making. The potential of longitudinal sampling and monitoring of glycomic features for diagnosis and treatment monitoring is emphasized. Finally, different strategies that address quantification of a multimarker panel will be discussed.

Sensitive Analysis of Recombinant Human Erythropoietin Glycopeptides by On-Line Phenylboronic Acid Solid-Phase Extraction Capillary Electrophoresis Mass Spectrometry

In this study, several chromatographic sorbents: porous graphitic carbon (PGC), aminopropyl hydrophilic interaction (aminopropyl-HILIC), and phenylboronic acid (PBA) were assessed for the analysis of glycopeptides by on-line solid-phase extraction capillary electrophoresis mass spectrometry (SPE-CE-MS). As the PBA sorbent provided the most promising results, a PBA-SPE-CE-MS method was developed for the selective and sensitive preconcentration of glycopeptides from enzymatic digests of glycoproteins. Recombinant human erythropoietin (rhEPO) was selected as the model glycoprotein and subjected to enzymatic digestion with several proteases. The tryptic O₁₂₆ and N₈₃ glycopeptides from rhEPO were targeted to optimize the methodology. Under the optimized conditions, intraday precision, linearity, limits of detection (LODs), and microcartridge lifetime were evaluated, obtaining improved results compared to that from a previously reported TiO₂-SPE-CE-MS method, especially for LODs of N-glycopeptides (up to 500 times lower than by CE-MS and up to 200 times lower than by TiO₂-SPE-CE-MS). Moreover, rhEPO Glu-C digests were also analyzed by PBA-SPE-CE-MS to better characterize N₂₄ and N₃₈ glycopeptides. Finally, the established method was used to analyze two rhEPO products (EPOCIM and NeuroEPO plus), demonstrating its applicability in biopharmaceutical analysis. The sensitivity of the proposed PBA-SPE-CE-MS method improves the existing CE-MS methodologies for glycopeptide analysis and shows a great potential in glycoprotein analysis to deeply characterize protein glycosites even at low concentrations of the protein digest.

In-Depth Analysis of the N-Glycome of Colorectal Cancer Cell Lines

Colorectal cancer (CRC) is the third most commonly diagnosed cancer and the second leading cause of cancer deaths worldwide. A well-known hallmark of cancer is altered glycosylation. Analyzing the N-glycosylation of CRC cell lines may provide potential therapeutic or diagnostic targets. In this study, an in-depth N-glycomic analysis of 25 CRC cell lines was conducted using porous graphitized carbon nano-liquid chromatography coupled to electrospray ionization mass spectrometry. This method allows for the separation of isomers and performs structural characterization, revealing profound N-glycomic diversity among the studied CRC cell lines with the elucidation of a number of 139 N-glycans. A high degree of similarity between the two N-glycan datasets measured on the two different platforms (porous graphitized carbon nano-liquid chromatography electrospray ionization tandem mass spectrometry (PGC-nano-LC-ESI-MS) and matrix-assisted laser desorption/ionization time of flight-mass spectrometry (MALDI-TOF-MS)) was discovered. Furthermore, we studied the associations between glycosylation features, glycosyltransferases (GTs), and transcription factors (TFs). While no significant correlations between the glycosylation features and GTs were found, the association between TF CDX1 and (s)Le antigen expression and relevant GTs FUT3/6 suggests that CDX1 contributes to the expression of the (s)Le antigen through the regulation of FUT3/6. Our study provides a comprehensive characterization of the N-glycome of CRC cell lines, which may contribute to the future discovery of novel glyco-biomarkers of CRC.

Mining the Immunopeptidome for Antigenic Peptides in Cancer

Simple Summary

The immunopeptidome of cancer cells is a treasure trove of neoantigens bound to MHC molecules, thus a great source for mining immunopeptides for immunotherapy applications, including cancer vaccines. Immunopeptides may encompass post-translational modifications that are overlooked by genomic and transcriptomic tools. We review post-translational modifications that have been uncovered, and how this information could be harnessed for cancer vaccines.

Abstract

Although harnessing the immune system for cancer therapy has shown success, response to immunotherapy has been limited. The immunopeptidome of cancer cells presents an opportunity to discover novel antigens for immunotherapy applications. These neoantigens bind to MHC class I and class II molecules. Remarkably, the immunopeptidome encompasses protein post-translation modifications (PTMs) that may not be evident from genome or transcriptome profiling. A case in point is citrullination, which has been demonstrated to induce a strong immune response. In this review, we cover how the immunopeptidome, with a special focus on PTMs, can be utilized to identify cancer-specific antigens for immunotherapeutic applications.

A protein identification method for proteomics using amino acid composition analysis with IoT-based remote control

In the present study, we developed a protein identification method using low-cost and easy-to-operate amino acid composition analysis. The identification program automatically compares the quantitative result for each amino acid concentration obtained from the amino acid analysis to the amino acid composition data retrieved from the UniProt protein database. We found that the accuracy of protein identification using amino acid composition analysis was comparable to that of mass spectrometry analysis. The method was able to distinguish and identify differences in amino acid substitutions of several residues between proteins with high sequence homology. The identification accuracy of proteins was also improved by correcting the concentrations in the program for Cys, Trp, and Ile residues, which cannot be quantified by general sample preparation for amino acid analysis. Moreover, the amino acid analyzer was remotely controlled in accordance with the growing demand for remote work. The measured amino acid data were automatically uploaded to the IoT portal within a few minutes of each measurement, allowing researchers to download data and analyze them using the identification program anywhere and at any time by connecting to a network. The results indicated that the present method is useful for protein identification.

Site-specific N-glycosylation analysis of human thyroid thyroglobulin by mass spectrometry-based Glyco-analytical strategies

Human thyroglobulin (Tg), which has many glycosylation sites, is an essential protein produced by the human thyroid glands. Although human Tg N-glycans play critical roles in the cellular events of the Thyroid gland, the site-specific distribution of glycan structures has not been studied in detail. This study aimed to profile human Tg N-glycosylation sites and their glycan contents by using high-throughput glyco-analytical strategies, including glycopeptide and glycan levels. The sulfated complex and hybrid type N-glycan species were determined by the analysis of the human Tg samples with HPLC-HILIC-FLD-MS/MS. It was found that all fucosylated N-glycans carried fucose residue on their N-glycan core structure. The human Tg was digested with multiple enzymes by applying both in-gel and in-solution protocols to enhance site-specific glycosylation analysis. In total, 17 out of 20 N-glycosylation sites were characterized. It was noticed that 6 N-glycosylation sites contain only high-mannose type glycans, while other regions include complex and hybrid type glycans. In addition, sulfated glycoform structures were detected at the glycopeptide level in glycosylation sites containing complex and hybrid type glycans. It is expected that the results obtained from this study will contribute to functional studies to be conducted on human Tg protein. BIOLOGICAL SIGNIFICANCE: N-glycans of human thyroglobulin modulate thyroid hormone synthesis both in vivo and in vitro. Therefore, a comprehensive analysis of the N-glycosylation sites of human thyroglobulin is essential to improve our understanding of the function of its N-glycans. The present research significantly expanded the knowledge regarding N-glycosylation profiles of human thyroid thyroglobulin protein. For instance, as highlighted here, sulfated N-glycan structures were characterized using comprehensive glyco-analytical strategies. N-glycan patterns for the sites Asn110, Asn1869, and Asn2122 were described for the first time in this current work. In addition, N-glycan structures containing core-fucosylation and bisecting types were confirmed for all determined glycosylation sites.

Mass Spectrometry-Based Techniques to Elucidate the Sugar Code

Cells encode information in the sequence of biopolymers, such as nucleic acids, proteins, and glycans. Although glycans are essential to all living organisms, surprisingly little is known about the "sugar code" and the biological roles of these molecules. The reason glycobiology lags behind its counterparts dealing with nucleic acids and proteins lies in the complexity of carbohydrate structures, which renders their analysis extremely challenging. Building blocks that may differ only in the configuration of a single stereocenter, combined with the vast possibilities to connect monosaccharide units, lead to an immense variety of isomers, which poses a formidable challenge to conventional mass spectrometry. In recent years, however, a combination of innovative ion activation methods, commercialization of ion mobility-mass spectrometry, progress in gas-phase ion spectroscopy, and advances in computational chemistry have led to a revolution in mass spectrometry-based glycan analysis. The present review focuses on the above techniques that expanded the traditional glycomics toolkit and provided spectacular insight into the structure of these fascinating biomolecules. To emphasize the specific challenges associated with them, major classes of mammalian glycans are discussed in separate sections. By doing so, we aim to put the spotlight on the most important element of glycobiology: the glycans themselves.

Cancer glycomics offers potential biomarkers and therapeutic targets in the framework of 3P medicine

Glycosylation is one of the most important post-translational modifications (PTMs) in a protein, and is the most abundant and diverse biopolymer in nature. Glycans are involved in multiple biological processes of cancer initiation and progression, including cell-cell interactions, cell-extracellular matrix interactions, tumor invasion and metastasis, tumor angiogenesis, and immune regulation. As an important biomarker, tumor-associated glycosylation changes have been extensively studied. This article reviews recent advances in glycosylation-based biomarker research, which is useful for cancer diagnosis and prognostic assessment. Truncated O-glycans, sialylation, fucosylation, and complex branched structures have been found to be the most common structural patterns in malignant tumors. In recent years, immunochemical methods, lectin recognition-based methods, mass spectrometry (MS)-related methods, and fluorescence imaging-based in situ methods have greatly promoted the discovery and application potentials of glycomic and glycoprotein biomarkers in various cancers. In particular, MS-based proteomics has significantly facilitated the comprehensive research of extracellular glycoproteins, increasing our understanding of their critical roles in regulating cellular activities. Predictive, preventive and personalized medicine (PPPM; 3P medicine) is an effective approach of early prediction, prevention and personalized treatment for different patients, and it is known as the new direction of medical development in the 21st century and represents the ultimate goal and highest stage of medical development. Glycosylation has been revealed to have new diagnostic, prognostic, and even therapeutic potentials. The purpose of glycosylation analysis and utilization of biology is to make a fundamental change in health care and medical practice, so as to lead medical research and practice into a new era of 3P medicine.

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.