Glycans and cancer: role of N-glycans in cancer biomarker, progression and metastasis, and therapeutics

A combined immune and exosome-related risk signature as prognostic biomakers in acute myeloid leukemia

OBJECTIVES

Acute myeloid leukemia (AML) is one of the common hematological diseases with low survival rates. Studies have highlighted the dysregulated expression of immune-related and exosome-related genes (ERGs) in cancers. Nevertheless, it remains to be determined whether combining these genes have a prognostic significance in AML.

METHODS

Immune-ERG profiles for 151 AML patients from TCGA were analyzed. A risk model was constructed and optimized through the combination of univariate Cox regression and LASSO regression analysis. GEO datasets were utilized as the external validation for the robustness of the risk model. In addition, we performed KEGG and GO enrichment analyses to investigate the role played by these genes in AML. The variations in immune cell infiltrations among risk groups were assessed through four algorithms. Expression of hub gene in specific cell was analyzed by single-cell RNA seq.

RESULTS

A total of 85 immune-ERGs associated with prognosis were identified, enabling the construction of a risk model for AML. The risk model based on five immune-ERGs (CD37, NUCB2, LSP1, MGST1, and PLXNB1) demonstrated a correlation with the clinical outcomes. Additionally, age, FAB classification, cytogenetics risk, and risk score were identified as independent prognostic factors. The five immune-ERGs exhibited correlations with cytokine-cytokine receptor interaction, and antigen processing and presentation. Notably, the risk model demonstrated significant associations with immune responses and the expression of immune checkpoints.

CONCLUSIONS

An immune-ERG-based risk model was developed to effectively predict prognostic outcomes for AML patients. There is potential for immune therapy in AML targeting the five hub genes.

FUT11 expression in gastric cancer: its prognostic significance and role in immune regulation

BACKGROUND

Gastric cancer (GC) is a malignant digestive tract tumor with a high recurrence rate and poor prognosis. Fucosylation is important in tumor glycosylation, in which the key enzyme is fucosyltransferase (FUT). FUT11 is a member of the fucosyltransferase family and has been closely associated with the development of multiple cancers. However, the specific relationship between FUT11 and GC prognosis and its molecular mechanism has not been fully studied. This study explored FUT11 expression, clinical correlation, and its role in GC occurrence and development to deepen understanding of its function.

METHODS

FUT11 expression in 33 cancers was preliminarily analyzed using the Tumor Immunoassay Resource (TIMER2.0) database. FUT11 expression in GC was evaluated using The Cancer Genome Atlas stomach adenocarcinoma (TCGA-STAD) and Gene Expression Profiling Interactive Analysis (GEPIA2) data and verified using the Gene Expression Omnibus (GEO) GSE65801 dataset. Furthermore, we studied the survival prognosis of FUT11 in GC and analyzed its effect on the survival rate of patients with GC using the KM-plotter. We also performed COX regression analysis on TCGA GC clinical data and analyzed FUT11 expression in the pathway using the STRING and LinkedOmics databases. Moreover, the relationship between FUT11 and GC immune infiltration level was examined, and the Kaplan-Meier survival analysis diagram was constructed. The FUT11 genetic variation information was retrieved using cBioPortal, and its drug sensitivity was analyzed using CellMiner. Finally, differential FUT11 expression in GC tissues was verified using immunohistochemistry.

RESULTS

The data mining and analysis demonstrated that FUT11 expression was abnormally elevated in GC tissues and correlated with poor patient prognosis. The FUT11 expression level was an independent prognostic factor for GC. The difference in FUT11 expression level resulted in different degrees of immune cell infiltration in the patients with GC, which might regulate the tumor microenvironment. FUT11 affected GC development by participating in cancer pathways such as PI3K-AKT, neuroactive ligand-receptor, and MAPK. Immunohistochemical staining revealed that FUT11 was highly expressed in GC.

CONCLUSIONS

This study revealed that FUT11 expression is significantly increased in GC tissues. This increase is associated with poor prognosis and might affect immune regulation. FUT11 might have immunological and targeted therapeutic value, providing a new approach to GC treatment.

Mass spectrometry imaging of N-linked glycans: Fundamentals and recent advances

With implications in several medical conditions, N-linked glycosylation is one of the most important posttranslation modifications present in all living organisms. Due to their nontemplate synthesis, glycan structures are extraordinarily complex and require multiple analytical techniques for complete structural elucidation. Mass spectrometry is the most common way to investigate N-linked glycans; however, with techniques such as liquid-chromatography mass spectrometry, there is complete loss of spatial information. Mass spectrometry imaging is a transformative analytical technique that can visualize the spatial distribution of ions within a biological sample and has been shown to be a powerful tool to investigate N-linked glycosylation. This review covers the fundamentals of mass spectrometry imaging and N-linked glycosylation and highlights important findings of recent key studies aimed at expanding and improving the glycomics imaging field.

Golgi apparatus targeted therapy in cancer: Are we there yet?

Membrane trafficking within the Golgi apparatus plays a pivotal role in the intracellular transportation of lipids and proteins. Dysregulation of this process can give rise to various pathological manifestations, including cancer. Exploiting Golgi defects, cancer cells capitalise on aberrant membrane trafficking to facilitate signal transduction, proliferation, invasion, immune modulation, angiogenesis, and metastasis. Despite the identification of several molecular signalling pathways associated with Golgi abnormalities, there remains a lack of approved drugs specifically targeting cancer cells through the manipulation of the Golgi apparatus. In the initial section of this comprehensive review, the focus is directed towards delineating the abnormal Golgi genes and proteins implicated in carcinogenesis. Subsequently, a thorough examination is conducted on the impact of these variations on Golgi function, encompassing aspects such as vesicular trafficking, glycosylation, autophagy, oxidative mechanisms, and pH alterations. Lastly, the review provides a current update on promising Golgi apparatus-targeted inhibitors undergoing preclinical and/or clinical trials, offering insights into their potential as therapeutic interventions. Significantly more effort is required to advance these potential inhibitors to benefit patients in clinical settings.

Regulation of intracellular activity of N-glycan branching enzymes in mammals

Most proteins in the secretory pathway are glycosylated, and N-glycans are estimated to be attached to over 7000 proteins in humans. As structural variation of N-glycans critically regulates the functions of a particular glycoprotein, it is pivotal to understand how structural diversity of N-glycans is generated in cells. One of the major factors conferring structural variation of N-glycans is the variable number of N-acetylglucosamine branches. These branch structures are biosynthesized by dedicated glycosyltransferases, including GnT-III (MGAT3), GnT-IVa (MGAT4A), GnT-IVb (MGAT4B), GnT-V (MGAT5), and GnT-IX (GnT-Vb, MGAT5B). In addition, the presence or absence of core modification of N-glycans, namely, core fucose (included as an N-glycan branch in this manuscript), synthesized by FUT8, also confers large structural variation on N-glycans, thereby crucially regulating many protein-protein interactions. Numerous biochemical and medical studies have revealed that these branch structures are involved in a wide range of physiological and pathological processes. However, the mechanisms regulating the activity of the biosynthetic glycosyltransferases are yet to be fully elucidated. In this review, we summarize the previous findings and recent updates regarding regulation of the activity of these N-glycan branching enzymes. We hope that such information will help readers to develop a comprehensive overview of the complex system regulating mammalian N-glycan maturation.

Multi Omics Applications in Biological Systems

Traditional methodologies often fall short in addressing the complexity of biological systems. In this regard, system biology omics have brought invaluable tools for conducting comprehensive analysis. Current sequencing capabilities have revolutionized genetics and genomics studies, as well as the characterization of transcriptional profiling and dynamics of several species and sample types. Biological systems experience complex biochemical processes involving thousands of molecules. These processes occur at different levels that can be studied using mass spectrometry-based (MS-based) analysis, enabling high-throughput proteomics, glycoproteomics, glycomics, metabolomics, and lipidomics analysis. Here, we present the most up-to-date techniques utilized in the completion of omics analysis. Additionally, we include some interesting examples of the applicability of multi omics to a variety of biological systems.

Fucosylation inhibitor 6-alkynylfucose enhances the ATRA-induced differentiation effect on acute promyelocytic leukemia cells

For acute promyelocytic leukemia (APL), differentiation therapy with all-trans retinoic acid (ATRA) is well established. However, the narrow application and tolerance development of ATRA remain to be improved. In this study, we investigated the effects of combinations of glycosylation inhibitors with ATRA to achieve better efficiency than ATRA alone. We found that the combination of fucosylation inhibitor 6-alkynylfucose (6AF) and ATRA had an additional effect on cell differentiation, as revealed by expression changes in two differentiation markers, CD11b and CD11c, and significant morphological changes in NB4 APL and HL-60 acute myeloid leukemia (AML) cells. In AAL lectin blot analyses, ATRA or 6AF alone could decrease fucosylation, while their combination decreased fucosylation more efficiently. To clarify the molecular mechanism for the 6AF effect on ATRA-induced differentiation, we performed microarray analyses using NB4 cells. In a pathway analysis using DAVID software, we found that the C-type lectin receptor (CLR) signaling pathway was enriched with high significance. In real-time PCR analyses using NB4 and HL-60 cells, FcεRIγ, CLEC6A, CLEC7A, CASP1, IL-1β, and EGR3, as components of the CLR pathway, as well as CD45 and AKT3 were upregulated by 6AF in ATRA-induced differentiation. Taken together, the present findings suggest that the CLR signaling pathway is involved in the 6AF effect on ATRA-induced differentiation.

Nanopore-based glycan sequencing: state of the art and future prospects

Sequencing of biomacromolecules is a crucial cornerstone in life sciences. Glycans, one of the fundamental biomolecules, derive their physiological and pathological functions from their structures. Glycan sequencing faces challenges due to its structural complexity and current detection technology limitations. As a highly sensitive sensor, nanopores can directly convert nucleic acid sequence information into electrical signals, spearheading the revolution of third-generation nucleic acid sequencing technologies. However, their potential for deciphering complex glycans remains untapped. Initial attempts demonstrated the significant sensitivity of nanopores in glycan sensing, which provided the theoretical basis and insights for the realization of nanopore-based glycan sequencing. Here, we present three potential technical routes to employ nanopore technology in glycan sequencing for the first time. The three novel technical routes include: strand sequencing, capturing glycan chains as they translocate through nanopores; sequential hydrolysis sequencing, capturing released monosaccharides one by one; splicing sequencing, mapping signals from hydrolyzed glycan fragments to an oligosaccharide database/library. Designing suitable nanopores, enzymes, and motors, and extracting characteristic signals pose major challenges, potentially aided by artificial intelligence. It would be highly desirable to design an all-in-one high-throughput glycan sequencer instrument by integrating a sample processing unit, nanopore array, and signal acquisition system into a microfluidic device. The nanopore sequencer invention calls for intensive multidisciplinary cooperation including electrochemistry, glycochemistry, engineering, materials, enzymology, etc. Advancing glycan sequencing will promote the development of basic research and facilitate the discovery of glycan-based drugs and disease markers, fostering progress in glycoscience and even life sciences.

Functional genomics identifies N-acetyllactosamine extension of complex N-glycans as a mechanism to evade lysis by natural killer cells

Natural killer (NK) cells are primary defenders against cancer precursors, but cancer cells can persist by evading immune surveillance. To investigate the genetic mechanisms underlying this evasion, we perform a genome-wide CRISPR screen using B lymphoblastoid cells. SPPL3, a peptidase that cleaves glycosyltransferases in the Golgi, emerges as a top hit facilitating evasion from NK cytotoxicity. SPPL3-deleted cells accumulate glycosyltransferases and complex N-glycans, disrupting not only binding of ligands to NK receptors but also binding of rituximab, a CD20 antibody approved for treating B cell cancers. Notably, inhibiting N-glycan maturation restores receptor binding and sensitivity to NK cells. A secondary CRISPR screen in SPPL3-deficient cells identifies B3GNT2, a transferase-mediating poly-LacNAc extension, as crucial for resistance. Mass spectrometry confirms enrichment of N-glycans bearing poly-LacNAc upon SPPL3 loss. Collectively, our study shows the essential role of SPPL3 and poly-LacNAc in cancer immune evasion, suggesting a promising target for cancer treatment.

IgE and anaphylaxis specific to the carbohydrate alpha-gal depend on IL-4

BACKGROUND

Alpha-gal (Galα1-3Galβ1-4GlcNAc) is a carbohydrate with the potential to elicit fatal allergic reactions to mammalian meat and drugs of mammalian origin. This type of allergy is induced by tick bites, and therapeutic options for this skin-driven food allergy are limited to the avoidance of the allergen and treatment of symptoms. Thus, a better understanding of the immune mechanisms resulting in sensitization through the skin is crucial, especially in the case of a carbohydrate allergen for which underlying immune responses are poorly understood.

OBJECTIVE

We aimed to establish a mouse model of alpha-gal allergy for in-depth immunologic analyses.

METHODS

Alpha-galactosyltransferase 1-deficient mice devoid of alpha-gal glycosylations were sensitized with the alpha-gal-carrying self-protein mouse serum albumin by repetitive intracutaneous injections in combination with the adjuvant aluminum hydroxide. The role of basophils and IL-4 in sensitization was investigated by antibody-mediated depletion.

RESULTS

Alpha-gal-sensitized mice displayed increased levels of alpha-gal-specific IgE and IgG1 and developed systemic anaphylaxis on challenge with both alpha-gal-containing glycoproteins and glycolipids. In accordance with alpha-gal-allergic patients, we detected elevated numbers of basophils at the site of sensitization as well as increased numbers of alpha-gal-specific B cells, germinal center B cells, and B cells of IgE and IgG1 isotypes in skin-draining lymph nodes. By depleting IL-4 during sensitization, we demonstrated for the first time that sensitization and elicitation of allergy to alpha-gal and correspondingly to a carbohydrate allergen is dependent on IL-4.

CONCLUSION

These findings establish IL-4 as a potential target to interfere with alpha-gal allergy elicited by tick bites.

Impacts of β-1, 3-N-acetylglucosaminyltransferases (B3GNTs) in human diseases

Glycosylation modification of proteins is a common post-translational modification that exists in various organisms and has rich biological functions. It is usually catalyzed by multiple glycosyltransferases located in the Golgi apparatus. β-1,3-N-acetylglucosaminyltransferases (B3GNTs) are members of the glycosyltransferases and have been found to be involved in the occurrence and development of a variety of diseases including autoimmunity diseases, cancers, neurodevelopment, musculoskeletal system, and metabolic diseases. The functions of B3GNTs represent the glycosylation of proteins is a crucial and frequently life-threatening step in progression of most diseases. In this review, we give an overview about the roles of B3GNTs in tumor, nervous system, musculoskeletal and metabolic diseases, describing the recent results about B3GNTs, in order to provide a research direction and exploration value for the prevention, diagnosis and treatment of these diseases.

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.

Cancer cells and viruses share common glycoepitopes: exciting opportunities toward combined treatments

Aberrant glycosylation patterns of glycoproteins and glycolipids have long been recognized as one the major hallmarks of cancer cells that has led to numerous glycoconjugate vaccine attempts. These abnormal glycosylation profiles mostly originate from the lack of key glycosyltransferases activities, mutations, over expressions, or modifications of the requisite chaperone for functional folding. Due to their relative structural simplicity, O-linked glycans of the altered mucin family of glycoproteins have been particularly attractive in the design of tumor associated carbohydrate-based vaccines. Several such glycoconjugate vaccine formulations have generated potent monoclonal anti-carbohydrate antibodies useful as diagnostic and immunotherapies in the fight against cancer. Paradoxically, glycoproteins related to enveloped viruses also express analogous N- and O-linked glycosylation patterns. However, due to the fact that viruses are not equipped with the appropriate glycosyl enzyme machinery, they need to hijack that of the infected host cells. Although the resulting N-linked glycans are very similar to those of normal cells, some of their O-linked glycan patterns often share the common structural simplicity to those identified on tumor cells. Consequently, given that both cancer cells and viral glycoproteins share both common N- and O-linked glycoepitopes, glycoconjugate vaccines could be highly attractive to generate potent immune responses to target both conditions.

Development of mass spectrometric glycan characterization tags using acid-base chemistry and/or free radical chemistry

Despite recent advances in glycomics, glycan characterization still remains an analytical challenge. Accordingly, numerous glycan-tagging reagents with different chemistries were developed, including those involving acid-base chemistry and/or free radical chemistry. Acid-base chemistry excels at dissociating glycans into their constituent components in a systematic and predictable manner to generate cleavages at glycosidic bonds. Glycans are also highly susceptible to depolymerization by free radical processes, which is supported by results observed from electron-activated dissociation techniques. Therefore, the free radical activated glycan sequencing (FRAGS) reagent was developed so as to possess the characteristics of both acid-base and free radical chemistry, thus generating information-rich glycosidic bond and cross-ring cleavages. Alternatively, the free radical processes can be induced via photodissociation of the specific carbon-iodine bond which gives birth to similar fragmentation patterns as the FRAGS reagent. Furthermore, the methylated-FRAGS (Me-FRAGS) reagent was developed to eliminate glycan rearrangements by way of a fixed charged as opposed to a labile proton, which would otherwise yield additional, yet unpredictable, fragmentations including internal residue losses or multiple external residue losses. Lastly, to further enhance glycan enrichment and characterization, solid-support FRAGS was developed.

N-Glycosylation as a Modulator of Protein Conformation and Assembly in Disease

Glycosylation, a prevalent post-translational modification, plays a pivotal role in regulating intricate cellular processes by covalently attaching glycans to macromolecules. Dysregulated glycosylation is linked to a spectrum of diseases, encompassing cancer, neurodegenerative disorders, congenital disorders, infections, and inflammation. This review delves into the intricate interplay between glycosylation and protein conformation, with a specific focus on the profound impact of N-glycans on the selection of distinct protein conformations characterized by distinct interactomes-namely, protein assemblies-under normal and pathological conditions across various diseases. We begin by examining the spike protein of the SARS virus, illustrating how N-glycans regulate the infectivity of pathogenic agents. Subsequently, we utilize the prion protein and the chaperone glucose-regulated protein 94 as examples, exploring instances where N-glycosylation transforms physiological protein structures into disease-associated forms. Unraveling these connections provides valuable insights into potential therapeutic avenues and a deeper comprehension of the molecular intricacies that underlie disease conditions. This exploration of glycosylation's influence on protein conformation effectively bridges the gap between the glycome and disease, offering a comprehensive perspective on the therapeutic implications of targeting conformational mutants and their pathologic assemblies in various diseases. The goal is to unravel the nuances of these post-translational modifications, shedding light on how they contribute to the intricate interplay between protein conformation, assembly, and disease.

Integrative proteomics and n-glycoproteomics reveal the synergistic anti-tumor effects of aspirin- and gemcitabine-based chemotherapy on pancreatic cancer cells

OBJECTIVE AND DESIGN

Pancreatic cancer is a highly malignant tumor that is well known for its poor prognosis. Based on glycosylation, we performed integrated quantitative N-glycoproteomics to investigate the synergistic anti-tumor effects of aspirin and gemcitabine on pancreatic cancer cells and explore the potential molecular mechanisms of chemotherapy in pancreatic cancer.

METHODS AND RESULTS

Two pancreatic cancer cell lines (PANC-1 and BxPC-3) were treated with gemcitabine, aspirin, and a combination (gemcitabine + aspirin). We found that the addition of aspirin enhanced the inhibitory effect of gemcitabine on the activity of PANC-1 and BxPC-3 cells. Quantitative N-glycoproteome, proteome, phosphorylation, and transcriptome data were obtained from integrated multi-omics analysis to evaluate the anti-tumor effects of aspirin and gemcitabine on pancreatic cancer cells. Mfuzz analysis of intact N-glycopeptide profiles revealed two consistent trends associated with the addition of aspirin, which showed a strong relationship between N-glycosylation and the synergistic effect of aspirin. Further analysis demonstrated that the dynamic regulation of sialylation and high-mannose glycoforms on ECM-related proteins (LAMP1, LAMP2, ITGA3, etc.) was a significant factor for the ability of aspirin to promote the anti-tumor activity of gemcitabine and the drug resistance of pancreatic cancer cells.

CONCLUSIONS

In-depth analysis of N-glycosylation-related processes and pathways in pancreatic cancer cells can provide new insight for future studies regarding pancreatic cancer therapeutic targets and drug resistance mechanisms.

Combining Liquid Chromatography and Cryogenic IR Spectroscopy in Real Time for the Analysis of Oligosaccharides

While the combination of liquid chromatography (LC) and mass spectrometry (MS) serves as a robust approach for oligosaccharide analysis, it has difficulty distinguishing the smallest differences between isomers. The integration of infrared (IR) spectroscopy within a mass spectrometer as an additional analytical dimension can effectively address this limitation by providing a molecular fingerprint that is unique to each isomer. However, the direct interfacing of LC-MS with IR spectroscopy presents a technical challenge arising from the mismatch in the operational time scale of each method. In previous studies, this temporal incompatibility was mitigated by employing strategies designed to slow down or broaden the LC elution peaks of interest, but this workaround is applicable only for a few species at a time, necessitating multiple LC runs for comprehensive analysis. In the current work, we directly couple LC with cryogenic IR spectroscopy by acquiring a spectrum in as little as 10 s. This allows us to generate an orthogonal data dimension for molecular identification in the same amount of time that it normally takes for LC analysis. We successfully demonstrate this approach on a commercially available human milk oligosaccharide product, acquiring spectral information on the eluting peaks in real time and using it to identify both the specified constituents and nonspecified product impurities.

Identification of molecular characteristics of FUT8 and alteration of core fucosylation in kidney renal clear cell cancer

BACKGROUND

Kidney renal clear cell cancer (KIRC) is a type of urological cancer that occurs worldwide. Core fucosylation (CF), as the most common post-translational modification, is involved in the tumorigenesis.

METHODS

The alterations of CF-related genes were summarized in pan-cancer. The "ConsensusClusterPlus" package was utilized to identify two CF-related KIRC subtypes. The "ssgsea" function was chosen to estimate the CF score, signaling pathways and cell deaths. Multiple algorithms were applied to assess immune responses. The "oncoPredict" was utilized to estimate the drug sensitivity. The IHC and subgroup analysis was performed to reveal the molecular features of FUT8. Single-cell RNA sequencing (scRNA-seq) data were scrutinized to evaluate the CF state.

RESULTS

In pan-cancer, there was a noticeable alteration in the expression of CF-related genes. In KIRC, two CF-related subtypes (i.e., C1, C2) were obtained. In comparison to C2, C1 exhibited a higher CF score and correlated with poorer overall survival. Additionally, the TME of C2 demonstrated increased activity in neutrophils, macrophages, myeloid dendritic cells, and B cells, alongside a higher presence of silent mast cells, NK cells, and endothelial cells. Compared to normal samples, higher expression of FUT8 is observed in KIRC. The mutation of SETD2 was more frequent in low-FUT8 samples while the mutation of DNAH9 was more frequent in high-FUT8 samples. scRNA-seq analyses revealed that the CF score was predominantly higher in endothelial cells and fibroblast cells.

CONCLUSIONS

Two CF-related subtypes with distinct prognosis and TME were identified in KIRC. FUT8 exhibited elevated expression in KIRC samples.

ELF4 contributes to esophageal squamous cell carcinoma growth and metastasis by augmenting cancer stemness via FUT9

Esophageal squamous cell carcinoma (ESCC) commonly has aggressive properties and a poor prognosis. Investigating the molecular mechanisms underlying the progression of ESCC is crucial for developing effective therapeutic strategies. Here, by performing transcriptome sequencing in ESCC and adjacent normal tissues, we find that E74-like transcription factor 4 (ELF4) is the main upregulated transcription factor in ESCC. The results of the immunohistochemistry show that ELF4 is overexpressed in ESCC tissues and is significantly correlated with cancer staging and prognosis. Furthermore, we demonstrate that ELF4 could promote cancer cell proliferation, migration, invasion, and stemness by in vivo assays. Through RNA-seq and ChIP assays, we find that the stemness-related gene fucosyltransferase 9 ( FUT9) is transcriptionally activated by ELF4. Meanwhile, ELF4 is verified to affect ESCC cancer stemness by regulating FUT9 expression. Overall, we first discover that the transcription factor ELF4 is overexpressed in ESCC and can promote ESCC progression by transcriptionally upregulating the stemness-related gene FUT9.

Tolerable glycometabolic stress boosts cancer cell resilience through altered N-glycosylation and Notch signaling activation

Chronic metabolic stress paradoxically elicits pro-tumorigenic signals that facilitate cancer stem cell (CSC) development. Therefore, elucidating the metabolic sensing and signaling mechanisms governing cancer cell stemness can provide insights into ameliorating cancer relapse and therapeutic resistance. Here, we provide convincing evidence that chronic metabolic stress triggered by hyaluronan production augments CSC-like traits and chemoresistance by partially impairing nucleotide sugar metabolism, dolichol lipid-linked oligosaccharide (LLO) biosynthesis and N-glycan assembly. Notably, preconditioning with either low-dose tunicamycin or 2-deoxy-D-glucose, which partially interferes with LLO biosynthesis, reproduced the promoting effects of hyaluronan production on CSCs. Multi-omics revealed characteristic changes in N-glycan profiles and Notch signaling activation in cancer cells exposed to mild glycometabolic stress. Restoration of N-glycan assembly with glucosamine and mannose supplementation and Notch signaling blockade attenuated CSC-like properties and further enhanced the therapeutic efficacy of cisplatin. Therefore, our findings uncover a novel mechanism by which tolerable glycometabolic stress boosts cancer cell resilience through altered N-glycosylation and Notch signaling activation.

Targeting Breast Cancer with N-Acetyl-D-Glucosamine: Integrating Machine Learning and Cellular Assays for Promising Results

BACKGROUND

Breast cancer is a common cancer with high mortality rates. Early diagnosis is crucial for reducing the prognosis and mortality rates. Therefore, the development of alternative treatment options is necessary.

OBJECTIVE

This study aimed to investigate the inhibitory effect of N-acetyl-D-glucosamine (D-GlcNAc) on breast cancer using a machine learning method. The findings were further confirmed through assays on breast cancer cell lines.

METHODS

MCF-7 and 4T1 cell lines (ATCC) were cultured in the presence and absence of varying concentrations of D-GlcNAc (0.5 mM, 1 mM, 2 mM, and 4 mM) for 72 hours. A xenograft mouse model for breast cancer was established by injecting 4T1 cells into mammary glands. D-GlcNAc (2 mM) was administered intraperitoneally to mice daily for 28 days, and histopathological effects were evaluated at pre-tumoral and post-tumoral stages.

RESULTS

Treatment with 2 mM and 4 mM D-GlcNAc significantly decreased cell proliferation rates in MCF-7 and 4T1 cell lines and increased Fas expression. The number of apoptotic cells was significantly higher than untreated cell cultures (p < 0.01 - p < 0.0001). D-GlcNAc administration also considerably reduced tumour size, mitosis, and angiogenesis in the post-treatment group compared to the control breast cancer group (p < 0.01 - p < 0.0001). Additionally, molecular docking/dynamic analysis revealed a high binding affinity of D-GlcNAc to the marker protein HER2, which is involved in tumour progression and cell signalling.

CONCLUSION

Our study demonstrated the positive effect of D-GlcNAc administration on breast cancer cells, leading to increased apoptosis and Fas expression in the malignant phenotype. The binding affinity of D-GlcNAc to HER2 suggests a potential mechanism of action. These findings contribute to understanding D-GlcNAc as a potential anti-tumour agent for breast cancer treatment.

A highly specific antibody against the core fucose of the N-glycan in IgG identifies the pulmonary diseases and its regulation by CCL2

Glycan structure is often modulated in disease or predisease states, suggesting that such changes might serve as biomarkers. Here, we generated a monoclonal antibody (mAb) against the core fucose of the N-glycan in human IgG. Notably, this mAb can be used in Western blotting and ELISA. ELISA using this mAb revealed a low level of the core fucose of the N-glycan in IgG, suggesting that the level of acore fucosylated (noncore fucosylated) IgG was increased in the sera of the patients with lung cancer, chronic obstructive pulmonary disease, and interstitial pneumonia compared to healthy subjects. In a coculture analysis using human lung adenocarcinoma A549 cells and antibody-secreting B cells, the downregulation of the FUT8 (α1,6 fucosyltransferase) gene and a low level of core fucose of the N-glycan in IgG in antibody-secreting B cells were observed after coculture. A dramatic alteration in gene expression profiles for cytokines, chemokines, and their receptors were also observed after coculturing, and we found that the identified C-C motif chemokine 2 was partially involved in the downregulation of the FUT8 gene and the low level of core fucose of the N-glycan in IgG in antibody-secreting B cells. We also developed a latex turbidimetric immunoassay using this mAb. These results suggest that communication with C-C motif chemokine 2 between lung cells and antibody-secreting B cells downregulate the level of core fucose of the N-glycan in IgG, i.e., the increased level of acore fucosylated (noncore fucosylated) IgG, which would be a novel biomarker for the diagnosis of patients with pulmonary diseases.

Exploration of glycosyltransferases mutation status in cervical cancer reveals PARP14 as a potential prognostic marker

This study investigates the potential role of Glycosyltransferases (GTs) in the glycosylation process and their association with malignant tumors. Specifically, the study focuses on PARP14, a member of GTs, and its potential as a target for tumors in the diagnosis and treatment of cervical cancer. To gather data, the study used somatic mutation data, gene expression data and clinical information from TCGA-CESE dataset as well as tissue samples from cervical cancer patients. Further verification was conducted through RT-qPCR and immunohistochemistry staining on cervical cancer tissues to confirm the expression of PARP14. The study utilized Kaplan-Meier for survival analysis of cervical cancer patient and found significant mutational abnormalities in GTs. The high frequency mutated gene was identified as PARP14. RT-qPCR revealed significantly higher mRNA expression of PARP14 compared to precancerous tissue. Using IHC combined with Kaplan-Meier,patients in the PARP14 high expression group had a better prognosis than the low expression group. The study identified PARP14 as a frequently mutated gene in cervical cancer and proposed its potential role in diagnosis and treatment.

High serum mannose in colorectal cancer: a novel biomarker of lymph node metastasis and poor prognosis

Background

Lymph node status is an important prognostic indicator and it significantly influences treatment decisions for colorectal cancer (CRC). The objective of this study was to evaluate the ability of serum monosaccharides in predicting lymph node metastasis (LNM) and prognosis.

Methods

High performance anion exchange chromatography coupled with pulsed amperometric detector (HPAEC-PAD) was used to quantify serum monosaccharides from 252 CRC patients. Receiver operating characteristic (ROC) curves were used to evaluate predictive performance of parameters. Predictors of LNM were evaluated by univariate and multivariate analyses. The prognostic role of the factors was evaluated by survival analysis.

Results

The levels of serum mannose (Man) and galactose (Gal) were significantly increased in patients with LNM (p <0.0001, p =0.0017, respectively). The area under the curves (AUCs) of Man was 0.8140, which was higher than carcinoembryonic antigen (CEA) (AUC =0.6523). Univariate and multivariate analyses demonstrated histologic grade (G3) (odds ratio [OR] =2.60, p =0.043), histologic grade (mucin-producing subtype) (odds ratio [OR] =3.38, p =0.032), lymphovascular invasion (LVI) (OR =2.42, p <0.01), CEA (>5ng/ml) (OR =1.85, p =0.042) and high Man (OR =2.65, p =0.006) to be independent risk factors of LNM. The survival analysis showed that the high serum Man was independent risk factor for poor prognosis in CRC patients (HR=1.75, p =0.004).

Conclusions

The Man is superior to CEA in prediction of LNM for CRC patients. Man is expected to be a predictor for LNM in CRC. High serum Man is associated with poor prognosis of CRC patients.

Ti3C2 and Ti2C MXene materials for high-performance isolation of extracellular vesicles via coprecipitation

Two-dimensional (2D) materials such as MXenes, are usually well utilized in the field of catalysts and battery due to their good hydrophilicity and diversified surface terminals. However, their potential applications in the treatment of biological samples have not been widely concerned. Extracellular vesicles (EVs) contain unique molecular signatures and could be used as biomarkers for the detection of severe diseases such as cancer, as well as monitoring the therapeutic response. In this work, two kinds of MXene materials (Ti₃C₂ and Ti₂C) were successfully synthesized and employed in the isolation of EVs from the biological samples by taking advantage of the affinity interaction between the titanium (Ti) in MXenes and the phospholipid membrane of EVs. Compared with Ti₂C MXene materials, TiO₂ beads and the other EVs isolation methods, Ti₃C₂ MXene materials exhibited excellent isolation performance via the coprecipitation with EVs due to the abundant unsaturated coordination of Ti²⁺/Ti³⁺, and the dosage of materials was the lowest. Meanwhile, the whole isolation process could be done within 30 min and integrated well with the following analysis of proteins and ribonucleic acids (RNAs), which was also convenient and economic. Furthermore, the Ti₃C₂ MXene materials were used to isolate the EVs from the blood plasma of colorectal cancer (CRC) patients and healthy donors. Proteomics analysis of EVs showed that 67 proteins were up-regulated, in which most of them were closely related to CRC progression. These findings indicate that the MXene material-based EVs isolation method via coprecipitation provides an efficient tool for early diagnosis of diseases.

Linking aberrant glycosylation of plasma glycoproteins with progression of myelodysplastic syndromes: a study based on plasmonic biosensor and lectin array

Aberrant glycosylation of glycoproteins has been linked with various pathologies. Therefore, understanding the relationship between aberrant glycosylation patterns and the onset and progression of the disease is an important research goal that may provide insights into cancer diagnosis and new therapy development. In this study, we use a surface plasmon resonance imaging biosensor and a lectin array to investigate aberrant glycosylation patterns associated with oncohematological disease-myelodysplastic syndromes (MDS). In particular, we detected the interaction between the lectins and glycoproteins present in the blood plasma of patients (three MDS subgroups with different risks of progression to acute myeloid leukemia (AML) and AML patients) and healthy controls. The interaction with lectins from Aleuria aurantia (AAL) and Erythrina cristagalli was more pronounced for plasma samples of the MDS and AML patients, and there was a significant difference between the sensor response to the interaction of AAL with blood plasma from low and medium-risk MDS patients and healthy controls. Our data also suggest that progression from MDS to AML is accompanied by sialylation of glycoproteins and increased levels of truncated O-glycans and that the number of lectins that allow discriminating different stages of disease increases as the disease progresses.

Galectin-4 Is Involved in the Structural Changes of Glycosphingolipid Glycans in Poorly Differentiated Gastric Cancer Cells with High Metastatic Potential

Gastric cancer with peritoneal dissemination is difficult to treat surgically, and frequently recurs and metastasizes. Currently, there is no effective treatment for this disease, and there is an urgent need to elucidate the molecular mechanisms underlying peritoneal dissemination and metastasis. Our previous study demonstrated that galectin-4 participates in the peritoneal dissemination of poorly differentiated gastric cancer cells. In this study, the glycan profiles of cell surface proteins and glycosphingolipids (GSLs) of the original (wild), galectin-4 knockout (KO), and rescue cells were investigated to understand the precise mechanisms involved in the galectin-4-mediated regulation of associated molecules, especially with respect to glycosylation. Glycan analysis of the NUGC4 wild type and galectin-4 KO clones with and without peritoneal metastasis revealed a marked structural change in the glycans of neutral GSLs, but not in N-glycan. Furthermore, mass spectrometry (MS) combined with glycosidase digestion revealed that this structural change was due to the presence of the lacto-type (β1-3Galactosyl) glycan of GSL, in addition to the neolacto-type (β1-4Galactosyl) glycan of GSL. Our results demonstrate that galectin-4 is an important regulator of glycosylation in cancer cells and galectin-4 expression affects the glycan profile of GSLs in malignant cancer cells with a high potential for peritoneal dissemination.

AB Toxins as High-Affinity Ligands for Cell Targeting in Cancer Therapy

Conventional targeted therapies for the treatment of cancer have limitations, including the development of acquired resistance. However, novel alternatives have emerged in the form of targeted therapies based on AB toxins. These biotoxins are a diverse group of highly poisonous molecules that show a nanomolar affinity for their target cell receptors, making them an invaluable source of ligands for biomedical applications. Bacterial AB toxins, in particular, are modular proteins that can be genetically engineered to develop high-affinity therapeutic compounds. These toxins consist of two distinct domains: a catalytically active domain and an innocuous domain that acts as a ligand, directing the catalytic domain to the target cells. Interestingly, many tumor cells show receptors on the surface that are recognized by AB toxins, making these high-affinity proteins promising tools for developing new methods for targeting anticancer therapies. Here we describe the structure and mechanisms of action of Diphtheria (Dtx), Anthrax (Atx), Shiga (Stx), and Cholera (Ctx) toxins, and review the potential uses of AB toxins in cancer therapy. We also discuss the main advances in this field, some successful results, and, finally, the possible development of innovative and precise applications in oncology based on engineered recombinant AB toxins.

Genetic control of N-glycosylation of human blood plasma proteins

Glycosylation is an important protein modification, which influences the physical and chemical properties as well as biological function of these proteins. Large-scale population studies have shown that the levels of various plasma protein N-glycans are associated with many multifactorial human diseases. Observed associations between protein glycosylation levels and human diseases have led to the conclusion that N-glycans can be considered a potential source of biomarkers and therapeutic targets. Although biochemical pathways of glycosylation are well studied, the understanding of the mechanisms underlying general and tissue-specific regulation of these biochemical reactions in vivo is limited. This complicates both the interpretation of the observed associations between protein glycosylation levels and human diseases, and the development of glycan-based biomarkers and therapeutics. By the beginning of the 2010s, high-throughput methods of N-glycome profiling had become available, allowing research into the genetic control of N-glycosylation using quantitative genetics methods, including genome-wide association studies (GWAS). Application of these methods has made it possible to find previously unknown regulators of N-glycosylation and expanded the understanding of the role of N-glycans in the control of multifactorial diseases and human complex traits. The present review considers the current knowledge of the genetic control of variability in the levels of N-glycosylation of plasma proteins in human populations. It briefly describes the most popular physical-chemical methods of N-glycome profiling and the databases that contain genes involved in the biosynthesis of N-glycans. It also reviews the results of studies of environmental and genetic factors contributing to the variability of N-glycans as well as the mapping results of the genomic loci of N-glycans by GWAS. The results of functional in vitro and in silico studies are described. The review summarizes the current progress in human glycogenomics and suggests possible directions for further research.

AANL6 is a new efficient tool to probe non-reducing N-acetylglucosamine of N-linked glycans

Terminal N-acetylglucosamine (GlcNAc) N-linked glycosylation is a truncated N-glycosylated modification that has been reported to be involved in various diseases, such as autoimmune diseases, cancers, and neurodegenerative diseases. New and simple tools will be always valuable for further characterization of the functions of this kind of glycosylation. Our previous paper proved that an optimized lectin created from Agrocybe aegerita GlcNAc selective lectin (AANL) named AANL6, can effectively identify O-GlcNAcylation, which is terminal GlcNAc O-linked glycosylation. We speculated that AANL6 could also be used to identify terminal GlcNAc N-linked glycosylation. Using therapeutic monoclonal antibodies as a model of terminal GlcNAc N-glycosylated proteins, we proved that AANL6 could selectively identify terminal GlcNAc N-linked glycosylation. The ratio of terminal GlcNAc N-linked glycosylation was increased by enrichment with AANL6 in human serum. Using cell membrane proteins as a complex sample, we found that AANL6 bound to the sperm surface, which expresses abundant terminal GlcNAc N-glycans, but did not bind to some tumor cell surfaces such A549 and MCF-7 cells, which is rich in high mannose glycoforms. In conclusion, AANL6 was identified as a powerful tool to probe terminal GlcNAc N-linked glycosylation and would be valuable for uncovering the function of this glycosylation.

PPIGCF: A Protein-Protein Interaction-Based Gene Correlation Filter for Optimal Gene Selection

Biological data at the omics level are highly complex, requiring powerful computational approaches to identifying significant intrinsic characteristics to further search for informative markers involved in the studied phenotype. In this paper, we propose a novel dimension reduction technique, protein-protein interaction-based gene correlation filtration (PPIGCF), which builds on gene ontology (GO) and protein-protein interaction (PPI) structures to analyze microarray gene expression data. PPIGCF first extracts the gene symbols with their expression from the experimental dataset, and then, classifies them based on GO biological process (BP) and cellular component (CC) annotations. Every classification group inherits all the information on its CCs, corresponding to the BPs, to establish a PPI network. Then, the gene correlation filter (regarding gene rank and the proposed correlation coefficient) is computed on every network and eradicates a few weakly correlated genes connected with their corresponding networks. PPIGCF finds the information content (IC) of the other genes related to the PPI network and takes only the genes with the highest IC values. The satisfactory results of PPIGCF are used to prioritize significant genes. We performed a comparison with current methods to demonstrate our technique's efficiency. From the experiment, it can be concluded that PPIGCF needs fewer genes to reach reasonable accuracy (~99%) for cancer classification. This paper reduces the computational complexity and enhances the time complexity of biomarker discovery from datasets.

Bladder Cancer Cells Interaction with Lectin-Coated Surfaces under Static and Flow Conditions

Aberrant expression of glycans, i.e., oligosaccharide moiety covalently attached to proteins or lipids, is characteristic of various cancers, including urothelial ones. The binding of lectins to glycans is classified as molecular recognition, which makes lectins a strong tool for understanding their role in developing diseases. Here, we present a quantitative approach to tracing glycan-lectin interactions in cells, from the initial to the steady phase of adhesion. The cell adhesion was measured between urothelial cell lines (non-malignant HCV29 and carcinoma HT1376 and T24 cells) and lectin-coated surfaces. Depending on the timescale, single-cell force spectroscopy, and adhesion assays conducted in static and flow conditions were applied. The obtained results reveal that the adhesion of urothelial cells to two specific lectins, i.e., phytohemagglutinin-L and wheat germ agglutinin, was specific and selective. Thus, these lectins can be applied to selectively capture, identify, and differentiate between cancer types in a label-free manner. These results open up the possibility of designing lectin-based biosensors for diagnostic or prognostic purposes and developing strategies for drug delivery that could target cancer-associated glycans.

Altered Glycosylation in Progression and Management of Bladder Cancer

Bladder cancer (BC) is the 10th most common malignancy worldwide, with an estimated 573,000 new cases and 213,000 deaths in 2020. Available therapeutic approaches are still unable to reduce the incidence of BC metastasis and the high mortality rates of BC patients. Therefore, there is a need to deepen our understanding of the molecular mechanisms underlying BC progression to develop new diagnostic and therapeutic tools. One such mechanism is protein glycosylation. Numerous studies reported changes in glycan biosynthesis during neoplastic transformation, resulting in the appearance of the so-called tumor-associated carbohydrate antigens (TACAs) on the cell surface. TACAs affect a wide range of key biological processes, including tumor cell survival and proliferation, invasion and metastasis, induction of chronic inflammation, angiogenesis, immune evasion, and insensitivity to apoptosis. The purpose of this review is to summarize the current information on how altered glycosylation of bladder cancer cells promotes disease progression and to present the potential use of glycans for diagnostic and therapeutic purposes.

Integrated glycomics and genetics analyses reveal a potential role for N-glycosylation of plasma proteins and IgGs, as well as the complement system, in the development of type 1 diabetes

AIMS/HYPOTHESIS

We previously demonstrated that N-glycosylation of plasma proteins and IgGs is different in children with recent-onset type 1 diabetes compared with their healthy siblings. To search for genetic variants contributing to these changes, we undertook a genetic association study of the plasma protein and IgG N-glycome in type 1 diabetes.

METHODS

A total of 1105 recent-onset type 1 diabetes patients from the Danish Registry of Childhood and Adolescent Diabetes were genotyped at 183,546 genetic markers, testing these for genetic association with variable levels of 24 IgG and 39 plasma protein N-glycan traits. In the follow-up study, significant associations were validated in 455 samples.

RESULTS

This study confirmed previously known plasma protein and/or IgG N-glycosylation loci (candidate genes MGAT3, MGAT5 and ST6GAL1, encoding beta-1,4-mannosyl-glycoprotein 4-beta-N-acetylglucosaminyltransferase, alpha-1,6-mannosylglycoprotein 6-beta-N-acetylglucosaminyltransferase and ST6 beta-galactoside alpha-2,6-sialyltransferase 1 gene, respectively) and identified novel associations that were not previously reported for the general European population. First, novel genetic associations of IgG-bound glycans were found with SNPs on chromosome 22 residing in two genomic intervals close to candidate gene MGAT3; these include core fucosylated digalactosylated disialylated IgG N-glycan with bisecting N-acetylglucosamine (GlcNAc) (p_discovery=7.65 × 10^-12, p_replication=8.33 × 10^-6 for the top associated SNP rs5757680) and core fucosylated digalactosylated glycan with bisecting GlcNAc (p_discovery=2.88 × 10^-10, p_replication=3.03 × 10^-3 for the top associated SNP rs137702). The most significant genetic associations of IgG-bound glycans were those with MGAT3. Second, two SNPs in high linkage disequilibrium (missense rs1047286 and synonymous rs2230203) located on chromosome 19 within the protein coding region of the complement C3 gene (C3) showed association with the oligomannose plasma protein N-glycan (p_discovery=2.43 × 10^-11, p_replication=8.66 × 10^-4 for the top associated SNP rs1047286).

CONCLUSIONS/INTERPRETATION

This study identified novel genetic associations driving the distinct N-glycosylation of plasma proteins and IgGs identified previously at type 1 diabetes onset. Our results highlight the importance of further exploring the potential role of N-glycosylation and its influence on complement activation and type 1 diabetes susceptibility.

Single-cell transcriptomic analysis deciphers key transitional signatures associated with oncogenic evolution in human intramucosal oesophageal squamous cell carcinoma

BACKGROUND AND AIMS

The early diagnosis and intervention of oesophageal squamous cell carcinoma (ESCC) are particularly important because of the lack of effective therapies and poor prognosis. Comprehensive research on early ESCC at the single-cell level is rare due to the need for fresh and high-quality specimens obtained from ESD. This study aims to systematically describe the cellular atlas of human intramucosal ESCC.

METHODS

Five paired samples of intramucosal ESCC, para-ESCC oesophageal tissues from endoscopically resected specimens and peripheral blood mononuclear cells were adopted for scRNA-seq analysis. Computational pipeline scMetabolism was applied to quantify the metabolic diversity of single cells.

RESULTS

A total of 164 715 cells were profiled. Epithelial cells exhibited high intra-tumoural heterogeneity and two evolutionary trajectories during ESCC tumorigenesis initiated from proliferative cells, and then through an intermediate state, to two different terminal states of normally differentiated epithelial cells or malignant cells, respectively. The abundance of CD8+ TEX s, Tregs and PD1+ CD4+ T cells suggested an exhausted and suppressive immune microenvironment. Several genes in immune cells, such as CXCL13, CXCR5 and PADI4, were identified as new biomarkers for poor prognosis. A new subcluster of malignant cells associated with metastasis and angiogenesis that appeared at an early stage compared with progressive ESCC was also identified in this study. Intercellular interaction analysis based on ligand-receptor pairs revealed the subcluster of malignant cells interacting with CAFs via the MDK-NCL pathway, which was verified by cell proliferation assay and IHC. This indicates that the interaction may be an important hallmark in the early change of tumour microenvironment and serves as a sign of CAF activation to stimulate downstream pathways for facilitating tumour invasion.

CONCLUSION

This study demonstrates the changes of cell subsets and transcriptional levels in human intramucosal ESCC, which may provide unique insights into the development of novel biomarkers and potential intervention strategies.

Glycosylated proteins with abnormal glycosylation changes are potential biomarkers for early diagnosis of breast cancer

Conventional cancer management relies on tumor type and stage for diagnosis and treatment, which leads to recurrence and metastasis and death in young women. Early detection of proteins in the serum aids diagnosis, progression, and clinical outcomes, possibly improving survival rate of breast cancer patients. In this review, we provided an insight into the influence of aberrant glycosylation on breast cancer development and progression. Examined literatures revealed that mechanisms underlying glycosylation moieties alteration could enhance early detection, monitoring, and therapeutic efficacy in breast cancer patients. This would serve as a guide for the development of new serum biomarkers with higher sensitivity and specificity, providing possible serological biomarkers for breast cancer diagnosis, progression, and treatment.

In-depth investigation of altered glycosylation in human haptoglobin associated cancer by mass spectrometry

Serum haptoglobin (Hp), a highly sialylated biomolecule with four N-glycosylation sites, is a positive acute-phase response glycoprotein that acts as an immunomodulator. Hp has gained considerable attention due to its potential as a signature molecule that exhibits aberrant glycosylation in inflammatory disorders and malignancies. Its glycosylation can be analyzed qualitatively and quantitatively by various methods using mass spectrometry. In this review, we have provided a brief overview of Hp structure and biological function and described mass spectrometry-based techniques for analyzing glycosylation ranging from macroheterogeneity to microheterogeneity of Hp in diseases and cancer. The sugars on haptoglobin can be a sweet bridge to link the potential of cancer-specific biomarkers to clinically relevant applications.

Limited N-Glycan Processing Impacts Chaperone Expression Patterns, Cell Growth and Cell Invasiveness in Neuroblastoma

Enhanced N-glycan branching is associated with cancer, but recent investigations supported the involvement of less processed N-glycans. Herein, we investigated how changes in N-glycosylation influence cellular properties in neuroblastoma (NB) using rat N-glycan mutant cell lines, NB_1(-Mgat1), NB_1(-Mgat2) and NB_1(-Mgat3), as well as the parental cell line NB_1. The two earlier mutant cells have compromised N-acetylglucosaminyltransferase-I (GnT-I) and GnT-II activities. Lectin blotting showed that NB_1(-Mgat3) cells had decreased activity of GnT-III compared to NB_1. ESI-MS profiles identified N-glycan structures in NB cells, supporting genetic edits. NB_1(-Mgat1) had the most oligomannose N-glycans and the greatest cell invasiveness, while NB_1(-Mgat2) had the fewest and least cell invasiveness. The proliferation rate of NB_1 was slightly slower than NB_1(-Mgat3), but faster than NB_1(-Mgat1) and NB_1(-Mgat2). Faster proliferation rates were due to the faster progression of those cells through the G1 phase of the cell cycle. Further higher levels of oligomannose with 6-9 Man residues indicated faster proliferating cells. Human NB cells with higher oligomannose N-glycans were more invasive and had slower proliferation rates. Both rat and human NB cells revealed modified levels of ER chaperones. Thus, our results support a role of oligomannose N-glycans in NB progression; furthermore, perturbations in the N-glycosylation pathway can impact chaperone systems.

Mechanistic Study into Free Radical-Activated Glycan Dissociations through Isotope-Labeled Cellobioses

Inspired by the electron-activated dissociation technique, the most potent tool for glycan characterization, we recently developed free radical reagents for glycan structural elucidation. However, the underlying mechanisms of free radical-induced glycan dissociation remain unclear and, therefore, hinder the rational optimization of the free radical reagents and the interpretation of tandem mass spectra, especially the accurate assignment of the relatively low-abundant but information-rich ions. In this work, we selectively incorporate the ¹³C and/or ¹⁸O isotopes into cellobiose to study the mechanisms for free radical-induced dissociation of glycans. The eight isotope-labeled cellobioses include 1-¹³C, 3-¹³C, 1'-¹³C, 2'-¹³C, 3'-¹³C, 4'-¹³C, 5'-¹³C, and 1'-¹³C-4-¹⁸O-cellobioses. Upon one-step collisional activation, cross-ring (X ions), glycosidic bond (Y-, Z-, and B-related ions), and combinational (Y₁ + ^0,4X₀ ion) cleavages are generated. These fragment ions can be unambiguously assigned and confirmed by the mass difference of isotope labeling. Importantly, the relatively low-abundant but information-rich ions, such as ^1,5X₀ + H, ^1,4X₀ + H, ^2,4X₀ + H-OH, Y₁ + ^0,4X₀, ^2,5X₁-H, ^3,5X₀-H, ^0,3X₀-H, ^1,4X₀-H, and B₂-3H, are confidently assigned. The mechanisms for the formations of these ions are investigated and supported by quantum chemical calculations. These ions are generally initiated by hydrogen abstraction followed by sequential β-elimination and/or radical migration. Here, the mechanistic study for free radical-induced glycan dissociation allows us to interpret all of the free radical-induced fragment ions accurately and, therefore, enables the differentiation of stereochemical isomers. Moreover, it provides fundamental knowledge for the subsequent development of bioinformatics tools to interpret the complex free radical-induced glycan spectra.

Beyond glyco-proteomics-Understanding the role of genetics in cancer biomarkers

The development of robust cancer biomarkers is the most effective way to improve overall survival, as early detection and treatment leads to significantly better clinical outcomes. Many of the cancer biomarkers that have been identified and are clinically utilized are glycoproteins, oftentimes a specific glycoform. Aberrant glycosylation is a common theme in cancer, with dysregulated glycosylation driving tumor initiation and metastasis, and abnormal glycosylation can be detection both on the tissue surface and in serum. However, most cancer types are heterogeneous in regard to tumor genomics, and this heterogeneity extends to cancer glycomics. This limits the sensitivity of standalone glycan-based biomarkers, which has slowed their implementation clinically. However, if targeted biomarker development can take into account genomic tumor information, the development of complementary biomarkers that target unique cancer subgroups can be accomplished. This idea suggests the need for algorithm-based cancer biomarkers, which can utilize multiple biomarkers along with relevant demographic information. This concept has already been established in the detection of hepatocellular carcinoma with the GALAD score, and an algorithm-based approach would likely be effective in improving biomarker sensitivity for additional cancer types. In order to increase cancer diagnostic biomarker sensitivity, there must be more targeted biomarker development that considers tumor genomic, proteomic, metabolomic, and clinical data while identifying tumor biomarkers.

Glycans as shapers of tumour microenvironment: A sweet driver of T-cell-mediated anti-tumour immune response

Essentially all cells are covered with a dense coat of different glycan structures/sugar chains, giving rise to the so-called glycocalyx. Changes in cellular glycosylation are a hallmark of cancer, affecting most of the pathophysiological processes associated with malignant transformation, including tumour immune responses. Glycans are chief macromolecules that define T-cell development, differentiation, fate, activation and signalling. Thus, the diversity of glycans expressed at the surface of T cells constitutes a fundamental molecular interface with the microenvironment by regulating the bilateral interactions between T-cells and cancer cells, fine-tuning the anti-tumour immune response. In this review, we will introduce the power of glycans as orchestrators of T-cell-mediated immune response in physiological conditions and in cancer. We discuss how glycans modulate the glyco-metabolic landscape in the tumour microenvironment, and whether glycans can synergize with immunotherapy as a way of rewiring T-cell effector functions against cancer cells.

The Blessed Union of Glycobiology and Immunology: A Marriage That Worked

In this article, we discuss the main aspects regarding the recognition of cell surface glycoconjugates and the immunomodulation of responses against the progression of certain pathologies, such as cancer and infectious diseases. In the first part, we talk about different aspects of glycoconjugates and delve deeper into the importance of N-glycans in cancer immunotherapy. Then, we describe two important lectin families that have been very well studied in the last 20 years. Examples include the sialic acid-binding immunoglobulin (Ig)-like lectins (siglecs), and galectins. Finally, we discuss a topic that needs to be better addressed in the field of glycoimmunology: the impact of oncofetal antigens on the cells of the immune system. New findings in this area are of great importance for advancement, especially in the field of oncology, since it is already known that cellular interactions mediated by carbohydrate-carbohydrate and/or carbohydrate proteins are able to modulate the progression of different types of cancer in events that compromise the functionality of the immune responses.

Intra-Individual Variation in Disease-Specific IgG Fc Glycoform Ratios to Monitor the Disease Progression of Lung Cancer

Aberrant protein glycosylation is an active pathological alteration related to the progression of cancers. The speed of progression varies among individuals, increasing the difficulties of prognosis assessment. Hence, evaluating variation in glycosylation using patients themselves as their own controls is a potential way to reduce the impact of individual differences on progression monitoring. Here, following a longitudinal follow-up study involving 125 lung cancer (LC) patients with progressive disease, we isolated disease-specific IgG from serum using polyacrylamide gel electrophoresis, obtained IgG glycoform ratios using mass spectrometry, and then set a fold-change cutoff of 1.5 to utilize the intra-individual variation in IgG glycosylation to monitor PD. We found that the serial monitoring of 15 types of glycoform ratios provided an effective way for monitoring LC progression. Over 1.5-fold changes in glycoform ratios relative to the first observed value were detected in 117 of 125 LC patients (93.6%). Our established method predicted LC progression 55.8 (IQR 31.1-90.1) weeks earlier than imaging examination did. In summary, intra-individual variation in IgG glycoform ratios is useful to monitor LC progression, expanding our knowledge about the relationship between IgG glycosylation and cancer prognosis. The raw data files are available via the ProteomeXchange Consortium with the identifier PXD037541.

Biomimetic Tweezers for N-Glycans: Selective Recognition of the Core GlcNAc2 Disaccharide of the Sialylglycopeptide SGP

In recent years, glycomics have shown how pervasive the role of carbohydrates in biological systems is and how chemical tools are essential to investigate glycan function and modulate carbohydrate-mediated processes. Biomimetic receptors for carbohydrates can carry out this task but, although significant affinities and selectivities toward simple saccharides have been achieved, targeting complex glycoconjugates remains a goal yet unattained. In this work we report the unprecedented recognition of a complex biantennary sialylglycopeptide (SGP) by a tweezers-shaped biomimetic receptor, which selectively binds to the core GlcNAc₂ disaccharide of the N-glycan with an affinity of 170 μM. Because of the simple structure and the remarkable binding ability, this biomimetic receptor can represent a versatile tool for glycoscience, opening the way to useful applications.

Dysregulation of hexosamine biosynthetic pathway wiring metabolic signaling circuits in cancer

Metabolite sensing, a fundamental biological process, plays a key role in metabolic signaling circuit rewiring. Hexosamine biosynthetic pathway (HBP) is a glucose metabolic pathway essential for the synthesis of uridine diphosphate N-acetylglucosamine (UDP-GlcNAc), which senses key nutrients and integrally maintains cellular homeostasis. UDP-GlcNAc dynamically regulates protein N-glycosylation and O-linked-N-acetylglucosamine modification (O-GlcNAcylation). Dysregulated HBP flux leads to abnormal protein glycosylation, and contributes to cancer development and progression by affecting protein function and cellular signaling. Furthermore, O-GlcNAcylation regulates cellular signaling pathways, and its alteration is linked to various cancer characteristics. Additionally, recent findings have suggested a close association between HBP stimulation and cancer stemness; an elevated HBP flux promotes cancer cell conversion to cancer stem cells and enhances chemotherapy resistance via downstream signal activation. In this review, we highlight the prominent roles of HBP in metabolic signaling and summarize the recent advances in HBP and its downstream signaling, relevant to cancer.

Vesicle-mediated transport-related genes are prognostic predictors and are associated with tumor immunity in lung adenocarcinoma

Background

Globally, lung adenocarcinoma (LUAD) is the leading cause of cancer-related deaths. It is a progressive disorder that arises from multiple genetic and environmental factors. Dysregulated expression of vesicle-mediated transport-related genes (VMTRGs) have been reported in several cancers. However, the prognostic significance of VMTRGs in LUAD has yet to be established.

Methods

The VMTRG profiling data for 482 LUAD patients and 59 normal controls were downloaded from The Cancer Genome Altas (TCGA). Univariate Cox regression and Least Absolute Shrinkage and Selection Operator (LASSO) regression analyses were performed to construct and optimize the risk model. Several GEO datasets were used to validate the risk model. The roles of these genes were investigated via the Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene ontology (GO) enrichment analyses. Differences in immune cell infiltrations between risk groups were evaluated using five algorithms. "pRRophetic" was used to investigate anti-cancer drug sensitivities in two groups. Expression of these five genes in LUAD samples and adjacent normal tissues were evaluated by qRT-PCR. Colony formation and wound healing assays were performed to assess the significance of CNIH1 and AP3S1 in LUAD cells.

Results

We identified 85 prognosis-associated VMTRGs that could be constructed a risk model for LUAD patients, indicating their potential importance in LUAD development. The risk model including the five VMTRGs (CNIH1, KIF20A, GALNT2, GRIA1, and AP3S1) was associated with clinical outcomes. Tumor stage and risk score were found to be independent prognostic factors for LUAD patients. The five VMTRGs were also correlated with activation of the Notch and p53 signaling pathways. The risk model was significantly associated with immune responses and with high-level expression of immune checkpoints. High-risk group patients were more sensitive to several chemotherapeutic drugs and Lapatinib. Furthermore, CNIH1 and AP3S1 promoted LUAD cell growth and migration in vitro.

Conclusion

We constructed a VMTRG-based risk model for effective prediction of prognostic outcomes for LUAD patients. The risk model was associated with immune infiltration levels. These five hub genes are potential targets for immune therapy combined with chemotherapy in LUAD.

Determination of monosaccharide composition in human serum by an improved HPLC method and its application as candidate biomarkers for endometrial cancer

Altered glycan levels in serum have been associated with increased risk of cancer. In this study, we have developed and validated a HPLC-based method to analyze monosaccharide composition (D-mannose, Glucosamine, Galactosamine, Glucuronic acid, D-glucose, D-galactose, D-xylose, L-fucose) in human serum, with L-rhamnose, being used as internal standard. Monosaccharides obtained from hydrolyzed serum samples were derivatized by 1-Phenyl-3-methyl-5-pyrazolone. A ZORBAX XDB-C18 column(150×4.6mm) was used for chromatographic separation with 100 mM ammonium acetate buffer (NH4Ac-HAc, PH=5.5, solvent A), acetonitrile (ACN, solvent B) as a mobile phase. The calibration standard curves for the eight monosaccharides showed good linearity over the range of 2.5-500μg/mL with R² > 0.995. The relative standard deviation values for intra-day and inter-day precision were ≤ 5.49%. Recovery was 69.01-108.96%. We observed that this column exhibited high specificity and selectivity to separate monosaccharides from serum. This method was then applied to quantitatively analyze the serum monosaccharide levels in 30 patients with endometrial cancer and 30 matched healthy controls. Statistical analysis indicated that the serum monosaccharide levels were significantly higher in patients compared with healthy controls (P value< 0.0001). Overall, we report here a simple, reliable, low-cost, and reproducible HPLC method for the separation and quantification monosaccharides in the human serum, which has potential value to serve as a screening marker for endometrial cancer.

Identification of a prognostic risk-scoring model and risk signatures based on glycosylation-associated cluster in breast cancer

Breast cancer is a heterogeneous disease whose subtypes represent different histological origins, prognoses, and therapeutic sensitivity. But there remains a strong need for more specific biomarkers and broader alternatives for personalized treatment. Our study classified breast cancer samples from The Cancer Genome Atlas (TCGA) into three groups based on glycosylation-associated genes and then identified differentially expressed genes under different glycosylation patterns to construct a prognostic model. The final prognostic model containing 23 key molecules achieved exciting performance both in the TCGA training set and testing set GSE42568 and GSE58812. The risk score also showed a significant difference in predicting overall clinical survival and immune infiltration analysis. This work helped us to understand the heterogeneity of breast cancer from another perspective and indicated that the identification of risk scores based on glycosylation patterns has potential clinical implications and immune-related value for breast cancer.

Diagnosis of hepatocellular carcinoma based on salivary protein glycopatterns and machine learning algorithms

Objectives

Hepatocellular carcinoma (HCC) is difficult to diagnose early and progresses rapidly, making it one of the most deadly malignancies worldwide. This study aimed to evaluate whether salivary glycopattern changes combined with machine learning algorithms could help in the accurate diagnosis of HCC.

Methods

Firstly, we detected the alteration of salivary glycopatterns by lectin microarrays in 118 saliva samples. Subsequently, we constructed diagnostic models for hepatic cirrhosis (HC) and HCC using three machine learning algorithms: Least Absolute Shrinkage and Selector Operation, Support Vector Machine (SVM), and Random Forest (RF). Finally, the performance of the diagnostic models was assessed in an independent validation cohort of 85 saliva samples by a series of evaluation metrics, including area under the receiver operator curve (AUC), accuracy, specificity, and sensitivity.

Results

We identified alterations in the expression levels of salivary glycopatterns in patients with HC and HCC. The results revealed that the glycopatterns recognized by 22 lectins showed significant differences in the saliva of HC and HCC patients and healthy volunteers. In addition, after Boruta feature selection, the best predictive performance was obtained with the RF algorithm for the construction of models for HC and HCC. The AUCs of the RF-HC model and RF-HCC model in the validation cohort were 0.857 (95% confidence interval [CI]: 0.780–0.935) and 0.886 (95% CI: 0.814–0.957), respectively.

Conclusions

Detecting alterations in salivary protein glycopatterns with lectin microarrays combined with machine learning algorithms could be an effective strategy for diagnosing HCC in the future.