GlycoFibroTyper: A Novel Method for the Glycan Analysis of IgG and the Development of a Biomarker Signature of Liver Fibrosis

Machine Learning-Enhanced Cerebrospinal Fluid N-Glycome for the Diagnosis and Prognosis of Primary Central Nervous System Lymphoma

The diagnosis and prognosis of Primary Central Nervous System Lymphoma (PCNSL) present significant challenges. In this study, the potential use of machine learning algorithms in diagnosing and predicting the prognosis for PCNSL based on cerebrospinal fluid (CSF) N-glycomics was investigated. First, CSF samples obtained from a cohort of 60 PCNSL patients and 30 controls were analyzed by hydrophilic interaction-based ultra performance liquid chromatography (HILIC-UPLC)-fluorescence mass spectrometry. Subsequently, nine machine learning models were established to diagnose PCNSL based on the changes of CSF N-glycome, with the Random Forest algorithm proving to be the most effective, achieving an accuracy of 100% in the training set and 89.3% in the test set. Moreover, a COX proportional-hazard model and a nomogram incorporating CSF N-glycome (GP6 and GP27) along with clinical data (age) were crafted. This nomogram's discrimination capacity was considered satisfactory, as evidenced by a C-index of 0.804 (95% CI: 0.68, 0.927). The study reveals that machine learning models based on CSF N-glycome offer a valuable approach for diagnosing and prognosticating PCNSL, demonstrating high accuracy and sensitivity in both classification and survival analysis. These findings may offer new insights into the molecular mechanisms underlying PCNSL and contribute to the advancement of personalized medicine for patients with this disease.

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2021-2022

The use of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry for the analysis of carbohydrates and glycoconjugates is a well-established technique and this review is the 12th update of the original article published in 1999 and brings coverage of the literature to the end of 2022. As with previous review, this review also includes a few papers that describe methods appropriate to analysis by MALDI, such as sample preparation, even though the ionization method is not MALDI. The review follows the same format as previous reviews. It is divided into three sections: (1) general aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, fragmentation, quantification and the use of computer software for structural identification. (2) Applications to various structural types such as oligo- and polysaccharides, glycoproteins, glycolipids, glycosides and biopharmaceuticals, and (3) other general areas such as medicine, industrial processes, natural products and glycan synthesis where MALDI is extensively used. Much of the material relating to applications is presented in tabular form. MALDI is still an ideal technique for carbohydrate analysis, particularly in its ability to produce single ions from each analyte and advancements in the technique and range of applications show little sign of diminishing.

Autoimmune hepatitis displays distinctively high multi-antennary sialylation on plasma N-glycans compared to other liver diseases

BACKGROUND

Changes in plasma protein glycosylation are known to functionally affect proteins and to associate with liver diseases, including cirrhosis and hepatocellular carcinoma. Autoimmune hepatitis (AIH) is a liver disease characterized by liver inflammation and raised serum levels of IgG, and is difficult to distinguish from other liver diseases. The aim of this study was to examine plasma and IgG-specific N-glycosylation in AIH and compare it with healthy controls and other liver diseases.

METHODS

In this cross-sectional cohort study, total plasma N-glycosylation and IgG Fc glycosylation analysis was performed by mass spectrometry for 66 AIH patients, 60 age- and sex-matched healthy controls, 31 primary biliary cholangitis patients, 10 primary sclerosing cholangitis patients, 30 non-alcoholic fatty liver disease patients and 74 patients with viral or alcoholic hepatitis. A total of 121 glycans were quantified per individual. Associations between glycosylation traits and AIH were investigated as compared to healthy controls and other liver diseases.

RESULTS

Glycan traits bisection (OR: 3.78 [1.88-9.35], p-value: 5.88 × 10- 3), tetraantennary sialylation per galactose (A4GS) (OR: 2.88 [1.75-5.16], p-value: 1.63 × 10- 3), IgG1 galactosylation (OR: 0.35 [0.2-0.58], p-value: 3.47 × 10- 5) and hybrid type glycans (OR: 2.73 [1.67-4.89], p-value: 2.31 × 10- 3) were found as discriminators between AIH and healthy controls. High A4GS differentiated AIH from other liver diseases, while bisection associated with cirrhosis severity.

CONCLUSIONS

Compared to other liver diseases, AIH shows distinctively high A4GS levels in plasma, with potential implications on glycoprotein function and clearance. Plasma-derived glycosylation has potential to be used as a diagnostic marker for AIH in the future. This may alleviate the need for a liver biopsy at diagnosis. Glycosidic changes should be investigated further in longitudinal studies and may be used for diagnostic and monitoring purposes in the future.

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

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

A Guide to MALDI Imaging Mass Spectrometry for Tissues

Imaging mass spectrometry is a well-established technology that can easily and succinctly communicate the spatial localization of molecules within samples. This review communicates the recent advances in the field, with a specific focus on matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) applied on tissues. The general sample preparation strategies for different analyte classes are explored, including special considerations for sample types (fresh frozen or formalin-fixed,) strategies for various analytes (lipids, metabolites, proteins, peptides, and glycans) and how multimodal imaging strategies can leverage the strengths of each approach is mentioned. This work explores appropriate experimental design approaches and standardization of processes needed for successful studies, as well as the various data analysis platforms available to analyze data and their strengths. The review concludes with applications of imaging mass spectrometry in various fields, with a focus on medical research, and some examples from plant biology and microbe metabolism are mentioned, to illustrate the breadth and depth of MALDI IMS.

Prospective on Imaging Mass Spectrometry in Clinical Diagnostics

Imaging mass spectrometry (IMS) is a molecular technology utilized for spatially driven research, providing molecular maps from tissue sections. This article reviews matrix-assisted laser desorption ionization (MALDI) IMS and its progress as a primary tool in the clinical laboratory. MALDI mass spectrometry has been used to classify bacteria and perform other bulk analyses for plate-based assays for many years. However, the clinical application of spatial data within a tissue biopsy for diagnoses and prognoses is still an emerging opportunity in molecular diagnostics. This work considers spatially driven mass spectrometry approaches for clinical diagnostics and addresses aspects of new imaging-based assays that include analyte selection, quality control/assurance metrics, data reproducibility, data classification, and data scoring. It is necessary to implement these tasks for the rigorous translation of IMS to the clinical laboratory; however, this requires detailed standardized protocols for introducing IMS into the clinical laboratory to deliver reliable and reproducible results that inform and guide patient care.

IgG N-glycan Signatures as Potential Diagnostic and Prognostic Biomarkers

IgG N-glycans are an emerging source of disease-specific biomarkers. Over the last decade, the continued development of glycomic databases and the evolution of glyco-analytic methods have resulted in increased throughput, resolution, and sensitivity. IgG N-glycans promote adaptive immune responses through antibody-dependent cellular cytotoxicity (ADCC) and complement activation to combat infection or cancer and promote autoimmunity. In addition to the functional assays, researchers are examining the ability of protein-specific glycosylation to serve as biomarkers of disease. This literature review demonstrates that IgG N-glycans can discriminate between healthy controls, autoimmune disease, infectious disease, and cancer with high sensitivity. The literature also indicates that the IgG glycosylation patterns vary across disease state, thereby supporting their role as specific biomarkers. In addition, IgG N-glycans can be collected longitudinally from patients to track treatment responses or predict disease reoccurrence. This review focuses on IgG N-glycan profiles applied as diagnostics, cohort discriminators, and prognostics. Recent successes, remaining challenges, and upcoming approaches are critically discussed.

High-Throughput Quantitative Glycomics Enabled by 12-plex Isobaric Multiplex Labeling Reagents for Carbonyl-Containing Compound (SUGAR) Tags

Glycans, which are widely distributed on most proteins and cell surfaces, are a class of important biomolecules playing crucial roles in various biological processes such as immune response and cellular communication. Modern mass spectrometry (MS) coupled with novel chemical probes greatly facilitates routine analysis of glycans. However, the requirement of high-throughput analysis still calls for advanced tools to be developed. Recently, we devised isobaric multiplex reagents for carbonyl-containing compound (SUGAR) tags for 4-plex N-glycan analysis. To further improve the throughput, we utilized the subtle mass differences among different isotopologues and expanded the multiplexing capacity to 12 channels, a 3-fold throughput improvement for the original SUGAR tag design and achieved high-throughput N-glycan analysis in a single LC-MS/MS injection. We then applied 12-plex SUGAR tags to profile the N-glycans in four subtypes of human Immunoglobulin G (IgG) and to investigate the N-glycan changes in the endometrial cancer cells (ECC1) treated with Atovaquone, a quinone antimicrobial medication, and a dihydroorotate dehydrogenase (DHODH) inhibitor. Data are available via ProteomeXchange with the identifier PXD038501.

A multiplexed microflow LC-MS/MS-PRM assay for serologic quantification of IgG N- and HPX O- glycoforms in liver fibrosis

Targeted quantification of glycoproteins has not reached its full potential because of limitations of the existing analytical workflows. In this study, we introduce a targeted microflow LC-MS/MS-PRM method for the quantification of multiple glycopeptides in unfractionated serum samples. The entire preparation of 16 samples in a batch is completed within 3 h, and the LC-MS quantification of all the glycoforms in a sample is completed in 15 min in triplicate, including online capture and desalting. We demonstrate applicability of the workflow on a multiplexed quantification of eight N-glycoforms of immunoglobulin G (IgG) together with two O-glycoforms of hemopexin (HPX). We applied the assay to a serologic study of fibrotic liver disease in patients of HCV etiology. The results document that specific IgG- and HPX-glycoforms detect efficiently fibrotic disease of different degree, and suggest that the LC-MS/MS-PRM assays may provide rapid and reproducible biomarker assay targeting simultaneously the N- and O-glycoforms of the peptides. We propose that such high throughput multiplexed methods may advance the clinical use of the LC-MS/MS assays.

Mass Spectrometry-Based Glycoproteomic Workflows for Cancer Biomarker Discovery

Glycosylation has a clear role in cancer initiation and progression, with numerous studies identifying distinct glycan features or specific glycoproteoforms associated with cancer. Common findings include that aggressive cancers tend to have higher expression levels of enzymes that regulate glycosylation as well as glycoproteins with greater levels of complexity, increased branching, and enhanced chain length1. Research in cancer glycoproteomics over the last 50-plus years has mainly focused on technology development used to observe global changes in glycosylation. Efforts have also been made to connect glycans to their protein carriers as well as to delineate the role of these modifications in intracellular signaling and subsequent cell function. This review discusses currently available techniques utilizing mass spectrometry-based technologies used to study glycosylation and highlights areas for future advancement.

Acute lyme disease IgG N-linked glycans contrast the canonical inflammatory signature

Lyme disease (LD) infection is caused by Borrelia burgdorferi sensu lato (Bb). Due to the limited presence of this pathogen in the bloodstream in humans, diagnosis of LD relies on seroconversion. Immunoglobulins produced in response to infection are differentially glycosylated to promote or inhibit downstream inflammatory responses by the immune system. Immunoglobulin G (IgG) N-glycan responses to LD have not been characterized. In this study, we analyzed IgG N-glycans from cohorts of healthy controls, acute LD patient serum, and serum collected after acute LD patients completed a 2- to 3-week course of antibiotics and convalesced for 70-90 days. Results indicate that during the acute phase of Bb infection, IgG shifts its glycosylation profile to include structures that are not associated with the classic proinflammatory IgG N-glycan signature. This unexpected result is in direct contrast to what is reported for other inflammatory diseases. Furthermore, IgG N-glycans detected during acute LD infection discriminated between control, acute, and treated cohorts with a sensitivity of 75-100% and specificity of 94.7-100%.