Glycans as cancer biomarkers

Unveiling the crucial role of glycosylation modification in lung adenocarcinoma metastasis through artificial neural network-based spatial multi-omics single-cell analysis and Mendelian randomization

BACKGROUND

Investigations into the intricacies of glycosylation modifications, a prevalent post-translational alteration observed in neoplasms, especially remain elusive in the context of lung adenocarcinoma. Through the integration of multiple omics approaches, the investigation aimed to delineate the significance of glycosylation in lung adenocarcinoma, with an objective to pinpoint viable biological targets.

METHODS

Initial steps involved the identification of genes differentially expressed in relation to glycosylation at the aggregate transcriptome level within lung adenocarcinoma tissues. This was followed by analyses of localization and function employing both single-cell and spatial transcriptomics to provide a more nuanced understanding. In pursuit of elucidating functional disparities in glycosylation patterns, a predictive framework employing artificial neural networks was constructed. To ascertain causal relationships between specific genes and lung adenocarcinoma, Mendelian randomization was applied, culminating in the experimental validation of these genes' roles.

RESULTS

Analysis at the single-cell level uncovered marked glycosylation modification expressions in metastatic tissues of lung adenocarcinoma. Moreover, tissues of lung adenocarcinoma with elevated expression of genes associated with glycosylation displayed enhanced differentiation and activation across signaling pathways including TGF-β, oxidative stress, and WNT. Through spatial transcriptomics, zones of intense glycosylation modification were pinpointed within tumor nests and proximate to tumor-associated blood vessels. An artificial neural network-derived prognostic model demonstrated outstanding predictive capability, with AUC scores achieving 0.84, 0.83, and 0.89 for 1, 3, and 5-year forecasts, respectively. The group identified as high-risk was characterized by pronounced immunosuppression and diminished responsiveness to immunotherapy. Mendelian randomization analysis pinpointed GLANT2 (OR = 1.3654, p < 0.05) and GYS1 (OR = 1.2668, p < 0.05) as genes contributing to the pathogenesis of lung adenocarcinoma. Cell assays have reaffirmed that the inhibition of GYS1 significantly reduces proliferation and invasion in lung adenocarcinoma cell lines, while also decreasing glycogen storage and the formation of glycosylation end products, indicating suppression of glycosylation processes. These findings identify GYS1 as a prospective glycosylation-linked biological target for lung adenocarcinoma therapy.

Site-specific immunoglobulin G N-glycosylation is associated with gastric cancer progression

BACKGROUND

The relationship between cancer development and alterations in IgG N-glycosylation has been well-established. However, comprehensive profiling of the N-glycome and N-glycoproteome in gastric cancer (GC) remains limited. Furthermore, the prognostic potential of IgG N-glycan patterns in identifying precursors to GC has yet to be fully elucidated.

METHODS

The IgG N-glycome in GC was characterized using a custom high-throughput orthogonal mass spectrometry approach. Multivariate analysis was employed to identify and assess glycomic alterations. A comprehensive bioinformatics analysis was also conducted to investigate the differential expression of N-glycosylation-related genes and their potential roles in GC pathogenesis. Additionally, interleukin-11 (IL-11) levels were quantified using a standardized enzyme-linked immunosorbent assay (ELISA).

RESULTS

Galactosylation and sialylation of IgG decreased mainly in the IgG1 and IgG2 subclasses in GC, with subclass-specific changes in IgG3 and IgG4 galactosylation. These glycan modifications were represented by unique glycopeptides (IgG1_H5N5, IgG2_H4N3F1, IgG2_H4N4, IgG2_H4N4F1S1, IgG3/4_H4N4F1, IgG3/4_H4N4F1S1), which outperformed CA72-4 for GC diagnosis. Analysis of key glycogenes revealed differential expression patterns, implicating a functional role for IgG N-glycosylation in GC. Notably, the abundance of specific IgG glycosylation exhibited a significant correlation with serum level of IL-11.

CONCLUSIONS

Alterations in subclass-specific IgG N-glycosylation represent promising biomarkers for the detection and monitoring of GC progression, potentially influenced by cytokine-driven inflammation. Understanding these changes could improve our knowledge of molecular mechanisms, aiding in diagnostic improvements and therapeutic development.

C,N-Diaryl Glycosyl Imidates for Catalytic Glycosylation

We report the development of a novel class of glycosyl donors, C,N-diaryl imidates, distinguished by the presence of two identical aryl groups. These DAIs are efficiently synthesized from imidoyl fluorides, which are derived from symmetrical benzophenone precursors. Among the DAIs evaluated, the donor featuring two para-fluorophenyl groups exhibits exceptional versatility and efficiency, enabling high-yield glycosylation reactions across a wide range of acceptors. Key intermediates, including imidoyl fluorides and DAI donors, strike an ideal balance between storage stability and reactivity, underscoring their promise for the streamlined synthesis of complex saccharides.

Recent Advances in Labeling-Based Quantitative Glycomics: From High-Throughput Quantification to Structural Elucidation

Glycosylation, a crucial posttranslational modification (PTM), plays important roles in numerous biological processes and is linked to various diseases. Despite its significance, the structural complexity and diversity of glycans present significant challenges for mass spectrometry (MS)-based quantitative analysis. This review aims to provide an in-depth overview of recent advancements in labeling strategies for N-glycomics and O-glycomics, with a specific focus on enhancing the sensitivity, specificity, and throughput of MS analyses. We categorize these advancements into three major areas: (1) the development of isotopic/isobaric labeling techniques that significantly improve multiplexing capacity and throughput for glycan quantification; (2) novel methods that aid in the structural elucidation of complex glycans, particularly sialylated and fucosylated glycans; and (3) labeling techniques that enhance detection ionization efficiency, separation, and sensitivity for matrix-assisted laser desorption/ionization (MALDI)-MS and capillary electrophoresis (CE)-based glycan analysis. In addition, we highlight emerging trends in single-cell glycomics and bioinformatics tools that have the potential to revolutionize glycan quantification. These developments not only expand our understanding of glycan structures and functions but also open new avenues for biomarker discovery and therapeutic applications. Through detailed discussions of methodological advancements, this review underscores the critical role of derivatization methods in advancing glycan identification and quantification.

Optimization of glycopeptide enrichment techniques for the identification of clinical biomarkers

INTRODUCTION

The identification and characterization of glycopeptides through LC-MS/MS and advanced enrichment techniques are crucial for advancing clinical glycoproteomics, significantly impacting the discovery of disease biomarkers and therapeutic targets. Despite progress in enrichment methods like Lectin Affinity Chromatography (LAC), Hydrophilic Interaction Liquid Chromatography (HILIC), and Electrostatic Repulsion Hydrophilic Interaction Chromatography (ERLIC), issues with specificity, efficiency, and scalability remain, impeding thorough analysis of complex glycosylation patterns crucial for disease understanding.

AREAS COVERED

This review explores the current challenges and innovative solutions in glycopeptide enrichment and mass spectrometry analysis, highlighting the importance of novel materials and computational advances for improving sensitivity and specificity. It outlines the potential future directions of these technologies in clinical glycoproteomics, emphasizing their transformative impact on medical diagnostics and therapeutic strategies.

EXPERT OPINION

The application of innovative materials such as Metal-Organic Frameworks (MOFs), Covalent Organic Frameworks (COFs), functional nanomaterials, and online enrichment shows promise in addressing challenges associated with glycoproteomics analysis by providing more selective and robust enrichment platforms. Moreover, the integration of artificial intelligence and machine learning is revolutionizing glycoproteomics by enhancing the processing and interpretation of extensive data from LC-MS/MS, boosting biomarker discovery, and improving predictive accuracy, thus supporting personalized medicine.

Unraveling Clinical Glycoproteome by Integrating Affinity Enrichment with Nanopore Sequencing

This prospect explores the integration of enrichment strategies with nanopore detection to advance clinical glycoproteomics. Glycoproteins, crucial for understanding biological processes, pose challenges due to their low abundance and structural diversity. Enrichment techniques using lectin affinity, boronate affinity, and hydrazide chemistry and especially molecular imprinted polymers may selectively and specifically isolate glycoproteins from complex samples, while nanopore technology enables label-free, real-time, and single-molecule analysis. This approach holds promise for disease-related glycosylation studies, biomarker discovery, personalized medicine, and streamlined clinical analysis. Standardization, optimization, and data analysis remain challenges, requiring interdisciplinary collaborations and technological advancements. Overall, this integration may offer transformative potential for clinical glycoproteomics and innovative diagnostic and therapeutic strategies.

Detection of Tn-antigen in breast and prostate cancer models by VVL-labeled red dye-doped nanoparticles

Aim: Fluorescence detection of breast and prostate cancer cells expressing Tn-antigen, a tumor marker, with Vicia villosa lectin (VVL)-labeled nanoparticles.Materials & methods: Breast and prostate cancer cells engineered to express high levels of Tn-antigen and non-engineered controls were incubated with VVL-labeled or unlabeled red dye-doped silica-coated polystyrene nanoparticles. The binding to cells was studied with flow cytometry, confocal microscopy, and electron microscopy.Results: Flow cytometry showed that the binding of VVL-labeled nanoparticles was significantly higher to Tn-antigen-expressing cancer cells than controls. Confocal microscopy demonstrated that particles bound to the cell surface. According to the correlative light and electron microscopy the particles bound mostly as aggregates.Conclusion: VVL-labeled nanoparticles could provide a new tool for the detection of Tn-antigen-expressing breast and prostate cancer cells.

Increased α2,3-sialyl N-glycosylated prostate-specific membrane antigen (PSMA) in post-DRE urine is associated with high grade group prostate cancer

INTRODUCTION

Aberrant glycosylation of proteins is an important hallmark in multiple cancers. Prostate-specific membrane antigen (PSMA), a highly glycosylated protein with 10 N-linked glycosylation sites, is an Food and Drug Administration approved theranostic for prostate cancer. However, glycosylation changes in PSMA that are associated with prostate cancer disease progression have not been fully characterized.

METHODS

We investigated whether urinary PSMA sialylation correlate with high-grade prostate cancer. Urine samples were collected from men after digital rectal examination (DRE) before prostate biopsy. Lectin-antibody enzyme-linked immunoassay was used to quantify α2,3-sialyl PSMA in post-DRE urine samples from subjects with benign prostate tumors, Grade Group 1 prostate cancer and those with Grade Group ≥2 disease.

RESULTS

There are significant increases in α2,3-sialylated PSMA in patients with Grade Group ≥2 disease compared to benign (p = 0.0009) and those with Grade Group 1 disease (p = 0.0063). There were no significant differences in α2,3-sialyl PSMA levels between Grade Group 1 and benign prostate tumors (p = 0.7947).

CONCLUSIONS

Our study shows that there are significant differences in the abundance of α2,3-sialylated PSMA in post-DRE urines from disease stratified prostate cancer patients, and the increase is correlated with progression and disease severity. The detection of increased PSMA sialyation in post-DRE urines from patients with higher Grade Group ≥2 disease states provides novel untapped potential for the development of prognostic biomarkers for prostate cancer. Specifically, quantitation of α2,3-sialylated PSMA shows potential for discriminating between benign to intermediate grade disease, which is a significant clinical challenge in staging and risk stratification of prostate cancer.

Serum N-Glycan Profiling of Patients with Narcolepsy Type 1 Using LC-MS/MS

The neurological condition known as narcolepsy type 1 (NT1) is an uncommon condition marked by extreme daytime sleepiness, cataplexy, sleep paralysis, hallucinations, disrupted nocturnal sleep, and low or undetectable levels of orexin in the CSF fluid. NT1 has been hypothesized to be an immunological disorder; its treatment is currently only symptomatic, and misdiagnosis is not uncommon. This study compares the N-glycome of NT1 patients with healthy controls in search of potential glycan biomarkers using LC-MS/MS. A total of 121 candidate N-glycans were identified, 55 of which were isomeric N-glycan structures and 65 were not. Seventeen N-glycan biomarker candidates showed significant differences between the NT1 and control cohorts. All of the candidate glycan biomarkers were isomeric except HexNAc6Hex7Fuc0NeuAc1 (6701) and HexNAc6Hex7Fuc1NeuAc2 (6712). Therefore, with isomeric and nonisomeric structures, a total of 20 candidate N-glycan biomarkers are reported in this study, and interestingly, all are either sialylated or sialylated-fucosylated and upregulated in NT1 relative to the control. The distribution levels of all the identified N-glycans show that the sialylated glycan type is the most abundant in NT1 and is majorly disialylated, although the trisialylated subtype is three-fold higher in NT1 compared to the healthy control. The first isomers of HexNAc5Hex6Fuc0NeuAc3 (5603), HexNAc6Hex7Fuc0NeuAc2 (6702), and HexNAc6Hex7Fuc1NeuAc4 (6714) expressed a high level of fold changes (FC) of 1.62, 2.19, and 2.98, respectively. These results suggest a different N-glycome profile of NT1 and a relationship between sialylated glycan isomers in NT1 disease development or progression. The revelation of N-glycan expression alterations in this study may improve NT1 diagnostic methods, understanding of NT1 pathology, and the development of new targeted therapeutics.

Growing Glycans in Rosetta: Accurate de novo glycan modeling, density fitting, and rational sequon design

Carbohydrates and glycoproteins modulate key biological functions. However, experimental structure determination of sugar polymers is notoriously difficult. Computational approaches can aid in carbohydrate structure prediction, structure determination, and design. In this work, we developed a glycan-modeling algorithm, GlycanTreeModeler, that computationally builds glycans layer-by-layer, using adaptive kernel density estimates (KDE) of common glycan conformations derived from data in the Protein Data Bank (PDB) and from quantum mechanics (QM) calculations. GlycanTreeModeler was benchmarked on a test set of glycan structures of varying lengths, or "trees". Structures predicted by GlycanTreeModeler agreed with native structures at high accuracy for both de novo modeling and experimental density-guided building. We employed these tools to design de novo glycan trees into a protein nanoparticle vaccine to shield regions of the scaffold from antibody recognition, and experimentally verified shielding. This work will inform glycoprotein model prediction, glycan masking, and further aid computational methods in experimental structure determination and refinement.

Surface plasmon resonance microscopy identifies glycan heterogeneity in pancreatic cancer cells that influences mucin-4 binding interactions

Membrane proteins are the main targets of therapeutic drugs and most of them are glycosylated. Glycans play pivotal roles in several biological processes, and glycosylation changes are a well-established hallmark of several types of cancer, including pancreatic cancer, that contribute to tumor growth. Mucin-4 (MUC-4) is a membrane glycoprotein which is associated with pancreatic cancer and metastasis, and it has been targeted as a promising vaccine candidate. In this study, Surface Plasmon Resonance Microscopy (SPRM) was implemented to study complex influences of the native N-glycan cellular environment on binding interactions to the MUC-4 receptor as this is currently the only commercially available label-free technique with high enough sensitivity and resolution to measure binding kinetics and heterogeneity on single cells. Such unique capability enables for a more accurate understanding of the "true" binding interactions on human cancer cells without disrupting the native environment of the target MUC-4 receptor. Removal of N-linked glycans in pancreatic cancer cells using PNGase F exposed heterogeneity in Concanavalin (Con A) binding by revealing three new binding populations with higher affinities than the glycosylated control cells. Anti-MUC-4 binding interactions of enzymatically N-linked deglycosylated pancreatic cancer cells produced a 25x faster association and 37x higher affinity relative to the glycosylated control cells. Lastly, four interaction modes were observed for Helix Pomatia Agglutinin (HPA) binding to the glycosylated control cells, but shifted and increased in activity upon removal of N-linked glycans. These results identified predominant interaction modes of glycan and MUC-4 in pancreatic cancer cells, the kinetics of their binding interactions were quantified, and the influence of N-linked glycans in MUC-4 binding interactions was revealed.

O-Glycome Profiling of Breast Cancer Cell Lines to Understand Breast Cancer Brain Metastasis

Breast cancer is the second leading cause of cancer-related death among women and a major source of brain metastases. Despite the increasing incidence of brain metastasis from breast cancer, the underlying mechanisms remain poorly understood. Altered glycosylation is known to play a role in various diseases including cancer metastasis. However, profiling studies of O-glycans and their isomers in breast cancer brain metastasis (BCBM) are scarce. This study analyzed the expression of O-glycans and their isomers in human breast cancer cell lines (MDA-MB-231, MDA-MB-361, HTB131, and HTB22), a brain cancer cell line (CRL-1620), and a brain metastatic breast cancer cell line (MDA-MB-231BR) using nanoLC-MS/MS, identifying 27 O-glycan compositions. We observed significant upregulation in the expression of HexNAc1Hex1NeuAc2 and HexNAc2Hex3, whereas the expression of HexNAc1Hex1NeuAc1 was downregulated in MDA-MB-231BR compared to other cell lines. In our isomeric analysis, we observed notable alterations in the isomeric forms of the O-glycan structure HexNAc1Hex1NeuAc1 in a comparison of different cell lines. Our analysis of O-glycans and their isomers in cancer cells demonstrated that changes in their distribution can be related to the metastatic process. We believe that our investigation will contribute to an enhanced comprehension of the significance of O-glycans and their isomers in BCBM.

Biomarkers for Early Cancer Detection: A Landscape View of Recent Advancements, Spotlighting Pancreatic and Liver Cancers

Cancer is one of the leading causes of death worldwide. Early cancer detection is critical because it can significantly improve treatment outcomes, thus saving lives, reducing suffering, and lessening psychological and economic burdens. Cancer biomarkers provide varied information about cancer, from early detection of malignancy to decisions on treatment and subsequent monitoring. A large variety of molecular, histologic, radiographic, or physiological entities or features are among the common types of cancer biomarkers. Sizeable recent methodological progress and insights have promoted significant developments in the field of early cancer detection biomarkers. Here we provide an overview of recent advances in the knowledge related to biomolecules and cellular entities used for early cancer detection. We examine data from the CAS Content Collection, the largest human-curated collection of published scientific information, as well as from the biomarker datasets at Excelra, and analyze the publication landscape of recent research. We also discuss the evolution of key concepts and cancer biomarkers development pipelines, with a particular focus on pancreatic and liver cancers, which are known to be remarkably difficult to detect early and to have particularly high morbidity and mortality. The objective of the paper is to provide a broad overview of the evolving landscape of current knowledge on cancer biomarkers and to outline challenges and evaluate growth opportunities, in order to further efforts in solving the problems that remain. The merit of this review stems from the extensive, wide-ranging coverage of the most up-to-date scientific information, allowing unique, unmatched breadth of landscape analysis and in-depth insights.

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.

The use of multicomponent reactions in the development of bis-boronic acids for the detection of β-sialic acid

Sialic acid (SA) is a naturally occurring monosaccharide found in glycoproteins and glycolipids. Changes in the expression of SA are associated with several diseases; thus, the detection of SA is of great significance for biological research, cancer diagnosis, and treatment. Boronic acid analogs have emerged as a promising tool for detecting sugars such as SA due to its reversible covalent bonding ability. In this study, 11 bis-boronic acid compounds and 2 mono-boronic acid compounds were synthesized via a highly efficient Ugi-4CR strategy. The synthesized compounds were subjected to affinity fluorescence binding experiments to evaluate their binding capability to SA. Compound A1 was shown to have a promising binding constant of 2602 ± 100 M-1 at pH = 6.0. Density Functional Theory (DFT) calculations examining the binding modes between A1 and SA indicated that the position of the boronic acid functional group was strongly correlated with its interaction with SA's α-hydroxy acid unit. The DFT calculations were consistent with the observations from the fluorescence experiments, demonstrating that the number and relative positions of the boronic acid functional groups are critical factors in enhancing the binding affinity to SA. DFT calculations of both S and R configuration of A1 indicated that the effect of the S/R configuration of A1 on its binding with β-sialic acid was insignificant as the Ugi-4CR generated racemic products. A fluorine atom was incorporated into the R2 substituent of A1 as an electron-withdrawing group to produce A5, which possessed a significantly higher capability to bind to SA (Keq = 7015 ± 5 M-1 at pH = 6.0). Finally, A1 and A5 were shown to possess exceptional binding selectivity toward β-sialic acid under pH of 6.0 and 6.5 while preferring to bind with glucose, fructose, and galactose under pH of 7.0 and 7.5.

Anastrozole and Tamoxifen Impact on IgG Glycome Composition Dynamics in Luminal A and Luminal B Breast Cancers

This study examines the intricate relationship between protein glycosylation dynamics and therapeutic responses in Luminal A and Luminal B breast cancer subtypes, focusing on anastrozole and tamoxifen impacts. The present methods inadequately monitor and forecast patient reactions to these treatments, leaving individuals vulnerable to the potential adverse effects of these medications. This research investigated glycan structural changes by following patients for up to 9 months. The protocol involved a series of automated steps including IgG isolation, protein denaturation, glycan labelling, purification, and final analysis using capillary gel electrophoresis with laser-induced fluorescence. The results suggested the significant role of glycan modifications in breast cancer progression, revealing distinctive trends in how anastrozole and tamoxifen elicit varied responses. The findings indicate anastrozole's association with reduced sialylation and increased core fucosylation, while tamoxifen correlated with increased sialylation and decreased core fucosylation. These observations suggest potential immunomodulatory effects: anastrozole possibly reducing inflammation and tamoxifen impacting immune-mediated cytotoxicity. This study strongly emphasizes the importance of considering specific glycan traits to comprehend the dynamic mechanisms driving breast cancer progression and the effects of targeted therapies. The nuanced differences observed in glycan modifications between these two treatments underscore the necessity for further comprehensive research aimed at thoroughly evaluating the long-term implications and therapeutic efficacy for breast cancer patients.

FUT4 promotes the progression of Cholangiocarcinoma by modulating epithelial-mesenchymal transition

Cholangiocarcinoma (CCA) is a common gastrointestinal malignancy characterized by a poor prognosis. Considering its prevalence, exploring its underlying molecular biological mechanisms is of paramount clinical importance. In this study, bioinformatics techniques were utilized to analyze CCA sample data obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The analysis revealed a notable upregulation in FUT4 expression in CCA samples. To further investigate the functional implications of FUT4, in vivo and in vitro experiments were conducted, which demonstrated that FUT4 overexpression significantly enhances the proliferative and migratory capabilities of tumor cells. Subsequent sequencing analysis unveiled a correlation between FUT4 and epithelial-mesenchymal transition (EMT). Indeed, the pioneering discovery of elevated FUT4 expression in CCA was highlighted in this study. Further investigations into the function of FUT4 in CCA provided initial insights into its role in driving cancer progression via EMT. These findings present promising avenues for the diagnosis and treatment of CCA.[Figure: see text].

Targeted Analysis of Permethylated N-Glycans Using MRM/PRM Approaches

Targeted mass spectrometric analysis is widely employed across various omics fields as a validation strategy due to its high sensitivity and accuracy. The approach has been successfully employed for the structural analysis of proteins, glycans, lipids, and metabolites. Multiple reaction monitoring (MRM) and parallel reaction monitoring (PRM) have been the methods of choice for targeted structural studies of biomolecules. These target analyses simplify the analytical workflow, reduce background interference, and increase selectivity/specificity, allowing for a reliable quantification of permethylated N-glycans in complex biological matrices.

Multiomics insights on the onset, progression, and metastatic evolution of breast cancer

Breast cancer is the most common malignant neoplasm in women. Despite progress to date, 700,000 women worldwide died of this disease in 2020. Apparently, the prognostic markers currently used in the clinic are not sufficient to determine the most appropriate treatment. For this reason, great efforts have been made in recent years to identify new molecular biomarkers that will allow more precise and personalized therapeutic decisions in both primary and recurrent breast cancers. These molecular biomarkers include genetic and post-transcriptional alterations, changes in protein expression, as well as metabolic, immunological or microbial changes identified by multiple omics technologies (e.g., genomics, epigenomics, transcriptomics, proteomics, glycomics, metabolomics, lipidomics, immunomics and microbiomics). This review summarizes studies based on omics analysis that have identified new biomarkers for diagnosis, patient stratification, differentiation between stages of tumor development (initiation, progression, and metastasis/recurrence), and their relevance for treatment selection. Furthermore, this review highlights the importance of clinical trials based on multiomics studies and the need to advance in this direction in order to establish personalized therapies and prolong disease-free survival of these patients in the future.

Differential Protein and Glycan Packaging into Extracellular Vesicles in Response to 3D Gastric Cancer Cellular Organization

Alterations of the glycosylation machinery are common events in cancer, leading to the synthesis of aberrant glycan structures by tumor cells. Extracellular vesicles (EVs) play a modulatory role in cancer communication and progression, and interestingly, several tumor-associated glycans have already been identified in cancer EVs. Nevertheless, the impact of 3D tumor architecture in the selective packaging of cellular glycans into EVs has never been addressed. In this work, the capacity of gastric cancer cell lines with differential glycosylation is evaluated in producing and releasing EVs when cultured under conventional 2D monolayer or in 3D culture conditions. Furthermore, the proteomic content is identified and specific glycans are studied in the EVs produced by these cells, upon differential spatial organization. Here, it is observed that although the proteome of the analyzed EVs is mostly conserved, an EV differential packaging of specific proteins and glycans is found. In addition, protein-protein interaction and pathway analysis reveal individual signatures on the EVs released by 2D- and 3D-cultured cells, suggesting distinct biological functions. These protein signatures also show a correlation with clinical data. Overall, this data highlight the importance of tumor cellular architecture when assessing the cancer-EV cargo and its biological role.

Absolute Affinities from Quantitative Shotgun Glycomics Using Concentration-Independent (COIN) Native Mass Spectrometry

Native mass spectrometry (nMS) screening of natural glycan libraries against glycan-binding proteins (GBPs) is a powerful tool for ligand discovery. However, as the glycan concentrations are unknown, affinities cannot be measured directly from natural libraries. Here, we introduce Concentration-Independent (COIN)-nMS, which enables quantitative screening of natural glycan libraries by exploiting slow mixing of solutions inside a nanoflow electrospray ionization emitter. The affinities (K_d) of detected GBP-glycan interactions are determined, simultaneously, from nMS analysis of their time-dependent relative abundance changes. We establish the reliability of COIN-nMS using interactions between purified glycans and GBPs with known K_d values. We also demonstrate the implementation of COIN-nMS using the catch-and-release (CaR)-nMS assay for glycosylated GBPs. The COIN-CaR-nMS results obtained for plant, fungal, viral, and human lectins with natural libraries containing hundreds of N-glycans and glycopeptides highlight the assay's versatility for discovering new ligands, precisely measuring their affinities, and uncovering "fine" specificities. Notably, the COIN-CaR-nMS results clarify the sialoglycan binding properties of the SARS-CoV-2 receptor binding domain and establish the recognition of monosialylated hybrid and biantennary N-glycans. Moreover, pharmacological depletion of host complex N-glycans reduces both pseudotyped virions and SARS-CoV-2 cell entry, suggesting that complex N-glycans may serve as attachment factors.

Total serum N-glycans mark visceral leishmaniasis in human infections with Leishmania infantum

Visceral leishmaniasis (VL) is a clinical form of leishmaniasis with high mortality rates when not treated. Diagnosis suffers from invasive techniques and sub-optimal sensitivities. The current (affordable) treatment with pentavalent antimony as advised by the WHO is possibly harmful to the patient. There is need for an improved diagnosis to prevent possibly unnecessary treatment. N-glycan analysis may aid in diagnosis. We evaluated the N-glycan profiles from active VL, asymptomatic infections (ASYMP) and controls from non-endemic (NC) and endemic (EC) areas. Active VL has a distinct N-glycome profile that associates with disease severity. Our study suggests that the observed glycan signatures could be a valuable additive to diagnosis and assist in identifying possible markers of disease and understanding the pathogenesis of VL. Further studies are warranted to assess a possible future role of blood glycome analysis in active VL diagnosis and should aim at disease specificity.

Bioactives Promiscuity of Mucin: Insight from Multi-Spectroscopic, Thermodynamic, and Molecular Dynamic Simulation Analyses

Mucosal drug delivery plays an increasing role in the clinical setting owing to mucin's advantageous biochemical and pharmacological properties. However, how this transport system recognizes different substrates remains unclear. In this study, we explore the mechanism of bioactive (quercetin and berberine) promiscuity of mucin using various spectroscopic techniques and molecular dynamics simulations. The UV-visible spectroscopy results and the decreased fluorescence intensity of mucin in the presence of the bioactive compounds via a static quenching mechanism confirmed ground-state complex formation between the bioactives and mucin. The binding constants (K_b) were evaluated at different temperatures to afford K_b values of ∼10⁴ Lmol^-1, demonstrating the moderate and reasonable affinity of the bioactives for mucin, yielding greater diffusion into the tissues. Thermodynamic analysis and molecular dynamics (MD) simulations demonstrate that mucin-bioactive complex formation occurs primarily because of electrostatic/ionic interactions, while hydrophobic interactions were also crucial in stabilizing the complex. Far-UV circular dichroism spectroscopy showed that bioactive binding induced secondary structural changes in mucin. Sitemap and MD simulation indicated the principal binding site of mucin for the bioactives. This study also provides insight into the bioactives promiscuity of mucin in the presence of a crowded environment, which is relevant to the biological activity of mucin in vivo. An in vitro drug release study revealed that crowding assisted drug release in an enhanced burst manner compared with that in a dilute buffer system. This work thus provides fresh insight into drug absorption and distribution in the native cellular environment and helps direct new drug design and use in pharmaceutical and pharmacological fields.

Applications and continued evolution of glycan imaging mass spectrometry

Glycosylation is an important posttranslational modifier of proteins and lipid conjugates critical for the stability and function of these macromolecules. Particularly important are N-linked glycans attached to asparagine residues in proteins. N-glycans have well-defined roles in protein folding, cellular trafficking and signal transduction, and alterations to them are implicated in a variety of diseases. However, the non-template driven biosynthesis of these N-glycans leads to significant structural diversity, making it challenging to identify the most biologically and clinically relevant species using conventional analyses. Advances in mass spectrometry instrumentation and data acquisition, as well as in enzymatic and chemical sample preparation strategies, have positioned mass spectrometry approaches as powerful analytical tools for the characterization of glycosylation in health and disease. Imaging mass spectrometry expands upon these strategies by capturing the spatial component of a glycan's distribution in-situ, lending additional insight into the organization and function of these molecules. Herein we review the ongoing evolution of glycan imaging mass spectrometry beginning with widely adopted tissue imaging approaches and expanding to other matrices and sample types with potential research and clinical implications. Adaptations of these techniques, along with their applications to various states of disease, are discussed. Collectively, glycan imaging mass spectrometry analyses broaden our understanding of the biological and clinical relevance of N-glycosylation to human disease.

How to choose proper magnetic particles for bioaffinity interactions? The case for immobilised glyconanoconjugate

In this study, an assay for detection of the cancer biomarker Thomsen-nouvelle (Tn) antigen on the ELISA plates format was designed and developed. The effects of size and the interfacial density of the negative charge of magnetic beads (MBs) on the specific sensitivity of the bioaffinity interaction were studied. In particular, glyconanoconjugate, i.e. glycan Tn antigen conjugated to bovine serum albumin (BSA) was covalently immobilised on MBs for the bioaffinity detection of anti-Tn antibodies as cancer biomarkers. Six different MBs were used in the study, i.e. carboxy-modified MBs of 250 nm, 500 nm, 1000 nm and 2800 nm and epoxy-modified MBs of 2800 nm and 4500 nm. In order to evaluate which MBs are the best suited for detection of the analyte anti-Tn antibodies, sensitivities of detection (slopes from calibration curves) were calculated. Next, specific sensitivities were calculated for each type of MBs as a ratio of sensitivity of detection to the mass of MBs. From zeta potential ζ for each type of MBs, the interfacial charge density on MBs was calculated, expressed as the density of zeta potential ζ_d (ratio of zeta potential to surface area of MBs, i.e. ζ_d = ζ/A). Then, we evaluated the effect of size and ζ_d on the specific sensitivity of detection of anti-Tn antibodies in order to understand the immobilisation process on nanoscale. We also identified an optimal value of ζ_d on MBs; this was essential to achieve highly sensitive detection of the analyte, which made it possible to attain limit of detection (LOD) of (0.31 ± 0.01) ng mL^-1 or (2.10 ± 0.04) pM for analyte detection. In addition, the optimal assay configuration was highly selective and enabled reliable detection of the analyte in human serum with a recovery index in the range of 102-104%.

Lectin Histochemistry: Historical Perspectives, State of the Art, and Future Directions

Lectins, discovered more than 100 years ago and defined by their ability to selectively recognize specific carbohydrate structures, are ubiquitous in living organisms. Their precise functions are as yet under-explored and incompletely understood but they are clearly involved, through recognition of their binding partners, in a myriad of biological mechanisms involved in cell identity, adhesion, signaling, and growth regulation in health and disease. Understanding the complex "sugar code" represented by the "glycome" is a major challenge and at the forefront of current biological research. Lectins have been widely employed in histochemical studies to map glycosylation in cells and tissues. Here, a brief history of the discovery of lectins and early developments in their use is presented along with a selection of some of the most interesting and significant discoveries to emerge from the use of lectin histochemistry. Further, an evaluation of the next generation of lectin-based technologies is presented, including the potential for designing recombinant lectins with more precisely defined binding characteristics, linking lectin-based studies with other technologies to answer fundamental questions in glycobiology and approaches to exploring the interactions of lectins with their binding partners in more detail.

Lectin Affinity Chromatography

Glycosylation is a non-template-driven posttranslational modification during which linked-sugars and glycans are added to the nascent polypeptide. Over 70% of the eukaryotic proteome is thought to be glycosylated. It is now known that correct glycosylation is essential for the correct folding, solubility, stability, and immunogenicity of proteins. In this chapter, we describe the technique of lectin affinity chromatography (LAC), a procedure that has the ability to distinguish different glycans, which are attached to proteins or lipids, termed glycoproteins or glycolipids, respectively. This method utilizes different immobilized lectins that have affinity for specific sugar substrates, to separate a wide range of glycan-attached complexes (Ambrosi et al., Org Biomol Chem 3:1593-1608, 2005). To further enhance the specificity of LAC, a corresponding free sugar may be used to produce a specific elution. In general, the conditions under which lectin affinity chromatography operates are relatively mild resulting in good biological recoveries of the glycoproteins.

High-throughput screening of glycosynthases using azido sugars for oligosaccharides synthesis

Glycosynthases are mutant glycosyl hydrolases that can synthesize glycosidic bonds between acceptor glycone/aglycone groups and activated donor sugars with suitable leaving groups (e.g., azido, fluoro). However, it has been challenging to rapidly detect glycosynthase reaction products involving azido sugars as donor sugars. This has limited our ability to apply rational engineering and directed evolution methods to rapidly screen for improved glycosynthases that are capable of synthesizing bespoke glycans. Here, we outline our recently developed screening methodologies for rapidly detecting glycosynthase activity using a model fucosynthase enzyme engineered to be active on fucosyl azide as donor sugar. We created a diverse library of fucosynthase mutants using semi-random and random error prone mutagenesis and then identified improved fucosynthase mutants with desired activity using two distinct screening methods developed by our group to detect glycosynthase activity (i.e., by detecting azide formed upon completion of fucosynthase reaction); (a) pCyn-GFP regulon method, and (b) Click chemistry method. Finally, we provide some proof-of-concept results illustrating the utility of both these screening methods to rapidly detect products of glycosynthase reactions involving azido sugars as donor groups.

On-capillary fluorescent labeling of saccharides for capillary electrophoresis

The feasibility of on-capillary derivatization of saccharides by aromatic amine-based fluorescent labeling agents was tested. To avoid the problematic evolution of gaseous hydrogen cyanide, the Schiff base reduction by sodium cyanoborohydride, as the second step of the standard reductive amination protocol, was omitted. Glucose was used as a model analyte and 7-amino-1,3-naphthalenedisulfonic acid as the labeling agent. Our experiments showed that the direct reaction of the saccharide with the labeling agent in 2.5-M acetic acid yields a labeled product that is sufficiently stable to be separated from the labeling agent in 20-mM phosphate buffer, pH 3.5, and detected using UV detection. The glucose and label zones were introduced separately into the capillary and mixed using a negative voltage. Mixing voltage, its duration, the concentration of acetic acid in the reaction zone, and the waiting time between mixing and separation were optimized. To show the applicability of the procedure to a broader range of analytes, a mixture of different types of saccharides, that is, xylose (pentose), fucose (hexose), glucose (hexose), N-acetylglucosamine (N-acetylaminosaccharide), and lactose (disaccharide), was subjected to derivatization and analysis under the optimal conditions. The linearity and repeatability of the process were evaluated as critical parameters for its analytical applications. Six-point calibration dependences in the 1-50 mM range showed excellent determination coefficients of 0.9992 or higher for all five saccharides tested. The repeatability of the labeled saccharide peak areas was between 2.2% and 4.3%.

Integrating age, BMI, and serum N-glycans detected by MALDI mass spectrometry to classify suspicious mammogram findings as benign lesions or breast cancer

While mammograms are the standard tool for breast cancer screening, there remains challenges for mammography to effectively distinguish benign lesions from breast cancers, leading to many unnecessary biopsy procedures. A blood-based biomarker could provide a minimally invasive supplemental assay to increase the specificity of breast cancer screening. Serum N-glycosylation alterations have associations with many cancers and several of the clinical characteristics of breast cancer. The current study utilized a high-throughput mass spectrometry workflow to identify serum N-glycans with differences in intensities between patients that had a benign lesion from patients with breast cancer. The overall N-glycan profiles of the two patient groups had no differences, but there were several individual N-glycans with significant differences in intensities between patients with benign lesions and ductal carcinoma in situ (DCIS). Many N-glycans had strong associations with age and/or body mass index, but there were several of these associations that differed between the patients with benign lesions and breast cancer. Accordingly, the samples were stratified by the patient's age and body mass index, and N-glycans with significant differences between these subsets were identified. For women aged 50-74 with a body mass index of 18.5-24.9, a model including the intensities of two N-glycans, 1850.666 m/z and 2163.743 m/z, age, and BMI were able to clearly distinguish the breast cancer patients from the patients with benign lesions with an AUROC of 0.899 and an optimal cutoff with 82% sensitivity and 84% specificity. This study indicates that serum N-glycan profiling is a promising approach for providing clarity for breast cancer screening, especially within the subset of healthy weight women in the age group recommended for mammograms.

The Effect of Sample Glucose Content on PNGase F-Mediated N-Glycan Release Analyzed by Capillary Electrophoresis

Protein therapeutics have recently gained high importance in general health care along with applied clinical research. Therefore, it is important to understand the structure-function relationship of these new generation drugs. Asparagine-bound carbohydrates represent an important critical quality attribute of therapeutic glycoproteins, reportedly impacting the efficacy, immunogenicity, clearance rate, stability, solubility, pharmacokinetics and mode of action of the product. In most instances, these linked N-glycans are analyzed in their unconjugated form after endoglycosidase-mediated release, e.g., PNGase F-mediated liberation. In this paper, first, N-glycan release kinetics were evaluated using our previously reported in-house produced 6His-PNGase F enzyme. The resulting deglycosylation products were quantified by sodium dodecyl sulfate capillary gel electrophoresis to determine the optimal digestion time. Next, the effect of sample glucose content was investigated as a potential endoglycosidase activity modifier. A comparative Michaelis-Menten kinetics study was performed between the 6His-PNGase F and a frequently employed commercial PNGase F product with and without the presence of glucose in the digestion reaction mixture. It was found that 1 mg/mL glucose in the sample activated the 6His-PNGase F enzyme, while did not affect the release efficiency of the commercial PNGase F. Capillary isoelectric focusing revealed subtle charge heterogeneity differences between the two endoglycosidases, manifested by the lack of extra acidic charge variants in the cIEF trace of the 6His-PNGase F enzyme, which might have possibly influenced the glucose-mediated enzyme activity differences.

Direct discrimination of cell surface glycosylation signatures using a single pH-responsive boronic acid-functionalized polymer

Cell surface glycans serve fundamental roles in many biological processes, including cell-cell interaction, pathogen infection, and cancer metastasis. Cancer cell surface have alternative glycosylation to healthy cells, making these changes useful hallmarks of cancer. However, the diversity of glycan structures makes glycosylation profiling very challenging, with glycan 'fingerprints' providing an important tool for assessing cell state. In this work, we utilized the pH-responsive differential binding of boronic acid (BA) moieties with cell surface glycans to generate a high-content six-channel BA-based sensor array that uses a single polymer to distinguish mammalian cell types. This sensing platform provided efficient discrimination of cancer cells and readily discriminated between Chinese hamster ovary (CHO) glycomutants, providing evidence that discrimination is glycan-driven. The BA-functionalized polymer sensor array is readily scalable, providing access to new diagnostic and therapeutic strategies for cell surface glycosylation-associated diseases.

High-Throughput Glycomic Methods

Glycomics aims to identify the structure and function of the glycome, the complete set of oligosaccharides (glycans), produced in a given cell or organism, as well as to identify genes and other factors that govern glycosylation. This challenging endeavor requires highly robust, sensitive, and potentially automatable analytical technologies for the analysis of hundreds or thousands of glycomes in a timely manner (termed high-throughput glycomics). This review provides a historic overview as well as highlights recent developments and challenges of glycomic profiling by the most prominent high-throughput glycomic approaches, with N-glycosylation analysis as the focal point. It describes the current state-of-the-art regarding levels of characterization and most widely used technologies, selected applications of high-throughput glycomics in deciphering glycosylation process in healthy and disease states, as well as future perspectives.

Recent applications of ionic liquid-based tags in glycoscience

The functionalization of glycosides with ionic compounds such as ionic liquids provides enhanced polarity for the labelled glycans thanks to the presence of a permanent positive charge. The chemical derivatisation of glycans with ionic liquids constitutes an emerging strategy to boost the detection sensitivity in MS applications. This allows the straightforward monitoring and detection of the presence of labelled glycans in complex matrices and in those cases where very limited amounts of material were available such as in biological samples and chemoenzymatic reactions. The use of ionic liquid based derivatisation agents can be further exploited for the labelling of live cells via metabolic oligosaccharide engineering for the detection of cancer biomarkers and for the tuning of live cells-surface properties with implications in cancer prognosis and progression. In this mini-review we summarise the latest development of the ionic liquid based derivatisation agents in glycoscience focussing on their use for sensitive MS applications.

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.

Modeling and integration of N-glycan biomarkers in a comprehensive biomarker data model

Molecular biomarkers measure discrete components of biological processes that can contribute to disorders when impaired. Great interest exists in discovering early cancer biomarkers to improve outcomes. Biomarkers represented in a standardized data model, integrated with multi-omics data, may improve understanding and use of novel biomarkers such as glycans and glycoconjugates. Among altered components in tumorigenesis, N-glycans exhibit substantial biomarker potential, when analyzed with their protein carriers. However, such data are distributed across publications and databases of diverse formats, which hampers their use in research and clinical application. Mass spectrometry measures of fifty N-glycans, on seven serum proteins in liver disease, were integrated (as a panel) into a cancer biomarker data model, providing a unique identifier, standard nomenclature, links to glycan resources, and accession and ontology annotations to standard protein, gene, disease, and biomarker information. Data provenance was documented with a standardized FDA-supported BioCompute Object. Using the biomarker data model allows capture of granular information, such as glycans with different levels of abundance in cirrhosis, hepatocellular carcinoma, and transplant groups. Such representation in a standardized data model harmonizes glycomics data in a unified framework, making glycan-protein biomarker data exploration more available to investigators and to other data resources. The biomarker data model we describe can be used by researchers to describe their novel glycan and glycoconjugate biomarkers, can integrate N-glycan biomarker data with multi-source biomedical data, and can foster discovery and insight within a unified data framework for glycan biomarker representation thereby making the data FAIR (Findable, Accessible, Interoperable, Reusable) (https://www.go-fair.org/fair-principles/).

Identification of Mobility-Resolved N-Glycan Isomers

Glycan analysis has evolved considerably during the last decade. The advent of high-resolution ion-mobility spectrometry has enabled the separation of isomers with only the slightest of structural differences. However, the ability to separate such species raises the problem of identifying all the mobility-resolved peaks that are observed, especially when analytical standards are not available. In this work, we report an approach based on the combination of IMSⁿ with cryogenic vibrational spectroscopy to identify N-glycan reducing-end anomers. By identifying the reducing-end α and β anomers of diacetyl-chitobiose, which is a disaccharide that forms part of the common core of all N-glycans, we are able to assign mobility peaks to reducing anomers of a selection of N-glycans of different sizes, starting from trisaccharides such as Man-1 up to glycans containing nine monosaccharide units, such as G2. By building an infrared fingerprint database of the identified N-glycans, our approach allows unambiguous identification of mobility peaks corresponding to reducing-end anomers and distinguishes them from positional isomers that might be present in a complex mixture.

Multi-block data integration analysis for identifying and validating targeted N-glycans as biomarkers for type II diabetes mellitus

Plasma N-glycan profiles have been shown to be defective in type II diabetes Mellitus (T2DM) and holds a promise to discovering biomarkers. The study comprised 232 T2DM patients and 219 healthy individuals. N-glycans were analysed by high-performance liquid chromatography. The multivariate integrative framework, DIABLO was employed for the statistical analysis. N-glycan groups (GPs 34, 32, 26, 31, 36 and 30) were significantly expressed in T2DM in component 1 and GPs 38 and 20 were related to T2DM in component 2. Four clusters were observed based on the correlation of the expressive signatures of the 39 N-glycans across T2DM and controls. Cluster A, B, C and D had 16, 16, 4 and 3 N-glycans respectively, of which 11, 8, 1 and 1 were found to express differently between controls and T2DM in a univariate analysis [Formula: see text]. Multi-block analysis revealed that trigalactosylated (G3), triantennary (TRIA), high branching (HB) and trisialylated (S3) expressed significantly highly in T2DM than healthy controls. A bipartite relevance network revealed that HB, monogalactosylated (G1) and G3 were central in the network and observed more connections, highlighting their importance in discriminating between T2DM and healthy controls. Investigation of these N-glycans can enhance the understanding of T2DM.

Metabolic Links to Socioeconomic Stresses Uniquely Affecting Ancestry in Normal Breast Tissue at Risk for Breast Cancer

A primary difference between black women (BW) and white women (WW) diagnosed with breast cancer is aggressiveness of the tumor. Black women have higher mortalities with similar incidence of breast cancer compared to other race/ethnicities, and they are diagnosed at a younger age with more advanced tumors with double the rate of lethal, triple negative breast cancers. One hypothesis is that chronic social and economic stressors result in ancestry-dependent molecular responses that create a tumor permissive tissue microenvironment in normal breast tissue. Altered regulation of N-glycosylation of proteins, a glucose metabolism-linked post-translational modification attached to an asparagine (N) residue, has been associated with two strong independent risk factors for breast cancer: increased breast density and body mass index (BMI). Interestingly, high body mass index (BMI) levels have been reported to associate with increases of cancer-associated N-glycan signatures. In this study, we used matrix assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) to investigate molecular pattern changes of N-glycosylation in ancestry defined normal breast tissue from BW and WW with significant 5-year risk of breast cancer by Gail score. N-glycosylation was tested against social stressors including marital status, single, education, economic status (income), personal reproductive history, the risk factors BMI and age. Normal breast tissue microarrays from the Susan G. Komen tissue bank (BW=43; WW= 43) were used to evaluate glycosylation against socioeconomic stress and risk factors. One specific N-glycan (2158 m/z) appeared dependent on ancestry with high sensitivity and specificity (AUC 0.77, Brown/Wilson p-value<0.0001). Application of a linear regression model with ancestry as group variable and socioeconomic covariates as predictors identified a specific N-glycan signature associated with different socioeconomic stresses. For WW, household income was strongly associated to certain N-glycans, while for BW, marital status (married and single) was strongly associated with the same N-glycan signature. Current work focuses on understanding if combined N-glycan biosignatures can further help understand normal breast tissue at risk. This study lays the foundation for understanding the complexities linking socioeconomic stresses and molecular factors to their role in ancestry dependent breast cancer risk.

Generation of glycan-specific nanobodies

The development of antibodies that target specific glycan structures on cancer cells or human pathogens poses a significant challenge due to the immense complexity of naturally occurring glycans. Automated glycan assembly enables the production of structurally homogeneous glycans in amounts that are difficult to derive from natural sources. Nanobodies (Nbs) are the smallest antigen-binding domains of heavy-chain-only antibodies (hcAbs) found in camelids. To date, the development of glycan-specific Nbs using synthetic glycans has not been reported. Here, we use defined synthetic glycans for alpaca immunization to elicit glycan-specific hcAbs, and describe the identification, isolation, and production of a Nb specific for the tumor-associated carbohydrate antigen Globo-H. The Nb binds the terminal fucose of Globo-H and recognizes synthetic Globo-H in solution and native Globo-H on breast cancer cells with high specificity. These results demonstrate the potential of our approach for generating glycan-targeting Nbs to be used in biomedical and biotechnological applications.

KIT Mutations Correlate with Higher Galectin Levels and Brain Metastasis in Breast and Non-Small Cell Lung Cancer

To investigate a potential role for galectins as biomarkers that enable diagnosis or prognostication of breast or non-small cell lung cancer, the serum levels of galectins -1, -3, -7, -8, and -9 of cancer patients determined by ELISA assays were compared to the mutation status of 50 known cancer-critical genes, which were determined using multiplex PCR in tumors of the same patients. Mutations in the KIT proto-oncogene, which codes for the c-Kit protein, a receptor tyrosine kinase, correlated with higher levels of galectins -1, -3, -8, and -9 in breast cancer patients and galectin-1 in non-small cell lung cancer patients. Mutations in the KIT gene were more likely found in brain metastases from both of these primary cancers. The most common KIT mutation in our panel was p.M541L, a missense mutation in the transmembrane domain of the c-Kit protein. These results demonstrate an association between KIT oncogenic signaling and elevated serum galectins in patients with metastatic disease. Changes in protein trafficking and the glycocalyx composition of cancer cells may explain the observed alterations in galectin expression. This study can be useful for the targeted selection of receptor tyrosine kinase and galectin inhibitor anti-cancer treatments.

Imaging Mass Spectrometry Reveals Alterations in N-Linked Glycosylation That Are Associated With Histopathological Changes in Nonalcoholic Steatohepatitis in Mouse and Human

Nonalcoholic steatohepatitis (NASH) is the progressive form of nonalcoholic fatty liver disease (NAFLD) and is characterized by inflammation, hepatocyte injury, and fibrosis. Further, NASH is a risk factor for cirrhosis and hepatocellular carcinoma. Previous research demonstrated that serum N-glycan profiles can be altered in NASH patients. Here, we hypothesized that these N-glycan modifications may be associated with specific liver damage in NAFLD and NASH. To investigate the N-glycome profile in tissue, imaging mass spectrometry was used for a qualitative and quantitative in situ N-linked glycan analysis of mouse and human NAFLD/NASH tissue. A murine model was used to induce NAFLD and NASH through ad libitum feeding with either a high-fat diet or a Western diet, respectively. Mice fed a high-fat diet or Western diet developed inflammation, steatosis, and fibrosis, consistent with NAFLD/NASH phenotypes. Induction of NAFLD/NASH for 18 months using high caloric diets resulted in increased expression of mannose, complex/fucosylated, and hybrid N-glycan structures compared to control mouse livers. To validate the animal results, liver biopsy specimens from 51 human NAFLD/NASH patients representing the full range of NASH Clinical Research Network fibrosis stages were analyzed. Importantly, the same glycan alterations observed in mouse models were observed in human NASH biopsies and correlated with the degree of fibrosis. In addition, spatial glycan alterations were localized specifically to histopathological changes in tissue like fibrotic and fatty areas. We demonstrate that the use of standard staining's combined with imaging mass spectrometry provide a full profile of the origin of N-glycan modifications within the tissue. These results indicate that the spatial distribution of abundances of released N-glycans correlate with regions of tissue steatosis associated with NAFLD/NASH.