Serum immunoglobulin G N-glycome: a potential biomarker in endometrial cancer

Exploring glycans as vital biological macromolecules: A comprehensive review of advancements in biomedical frontiers

This comprehensive review delves into the intricate landscape of glycans and glycoconjugates, unraveling their multifaceted roles across diverse biological dimensions. From influencing fundamental cellular processes such as signaling, recognition, and adhesion to exerting profound effects at the molecular and genetic levels, these complex carbohydrate structures emerge as linchpins in cellular functions and interactions. The structural diversity of glycoconjugates, which can be specifically classified into glycoproteins, glycolipids, and proteoglycans, underscores their importance in shaping the architecture of cells. Beyond their structural roles, these molecules also play key functions in facilitating cellular communication and modulating recognition mechanisms. Further, glycans and glycoconjugates prove invaluable as biomarkers in disease diagnostics, particularly in cancer, where aberrant glycosylation patterns offer critical diagnostic cues. Furthermore, the review explores their promising therapeutic applications, ranging from the development of glycan-based nanomaterials for precise drug delivery to innovative interventions in cancer treatment. This review endeavors to comprehensively explore the intricate functions of glycans and glycoconjugates, with the primary goal of offering valuable insights into their extensive implications in both health and disease. Encompassing a broad spectrum of biological processes, the focus of the review aims to provide a comprehensive understanding of the significant roles played by glycans and glycoconjugates.

Serum protein N-glycome patterns reveal alterations associated with endometrial cancer and its phenotypes of differentiation

Background

Aberrant N-glycosylation and its involvement in pathogenesis have been reported in endometrial cancer (EC). Nevertheless, the serum N-glycomic signature of EC remains unknown. Here, we investigated serum N-glycome patterns of EC to identify candidate biomarkers.

Methods

This study enrolled 34 untreated EC patients and 34 matched healthy controls (HC) from Peking Union Medical College Hospital. State-of-the-art MS-based methods were employed for N-glycans profiling. Multivariate and univariate statistical analyses were used to identify discriminative N-glycans driving classification. Receiver operating characteristic analyses were performed to evaluate classification accuracy.

Results

EC patients displayed distinct differences in serum N-glycome and had abnormal high-mannose and hybrid-type N-glycans, fucosylation, galactosylation, and linkage-specific sialylation compared with HC. The glycan panel built with the four most discriminative and biologically important derived N-glycan traits could accurately identify EC (random forest model, the area under the curve [AUC]=0.993 [95%CI 0.955-1]). The performance was validated by two other models. Total hybrid-type N-glycans significantly associated with the differentiation types of EC could effectively stratify EC into well- or poorly-differentiated subgroups (AUC>0.8).

Conclusion

This study provides the initial evidence supporting the utility of serum N-glycomic signature as potential markers for the diagnosis and phenotyping of EC.

Nutritional and immune-related indicators-based Nomogram for predicting overall survival of surgical oral tongue squamous cell carcinoma

Oral tongue squamous cell carcinoma (OTSCC) is one of the most aggressive oral tumors. The aim of this study was to establish a nomogram to predict overall survival (OS) of TSCC patients after surgery. 169 TSCC patients who underwent surgical treatments in the Cancer Hospital of Shantou University Medical College were included. A nomogram based on Cox regression analysis results was established and internally validated using bootstrap resampling method. pTNM stage, age and total protein, immunoglobulin G, factor B and red blood cell count were identified as independent prognostic factors to create the nomogram. The Akaike Information Criterion and Bayesian Information Criterion of the nomogram were lower than those of pTNM stage, indicating a better goodness-of-fit of the nomogram for predicting OS. The bootstrap-corrected concordance index of nomogram was higher than that of pTNM stage (0.794 vs. 0.665, p = 0.0008). The nomogram also had a good calibration and improved overall net benefit. Based on the cutoff value obtained from the nomogram, the proposed high-risk group had poorer OS than low-risk group (p < 0.0001). The nomogram based on nutritional and immune-related indicators represents a promising tool for outcome prediction of surgical OTSCC.

IgG N-glycan Signatures as Potential Diagnostic and Prognostic Biomarkers

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

Total serum N-glycans associate with response to immune checkpoint inhibition therapy and survival in patients with advanced melanoma

BACKGROUND

Immune checkpoint inhibitors (ICIs) have revolutionized the treatment of melanoma and other cancers. However, no reliable biomarker of survival or response has entered the clinic to identify those patients with melanoma who are most likely to benefit from ICIs. Glycosylation affects proteins and lipids' structure and functions. Tumours are characterized by aberrant glycosylation which may contribute to their progression and hinder an effective antitumour immune response.

METHODS

We aim at identifying novel glyco-markers of response and survival by leveraging the N-glycome of total serum proteins collected in 88 ICI-naive patients with advanced melanoma from two European countries. Samples were collected before and during ICI treatment.

RESULTS

We observe that responders to ICIs present with a pre-treatment N-glycome profile significantly shifted towards higher abundancy of low-branched structures containing lower abundances of antennary fucose, and that this profile is positively associated with survival and a better predictor of response than clinical variables alone.

CONCLUSION

While changes in serum protein glycosylation have been previously implicated in a pro-metastatic melanoma behaviour, we show here that they are also associated with response to ICI, opening new avenues for the stratification of patients and the design of adjunct therapies aiming at improving immune response.

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.

Diagnostic Accuracy of Liquid Biomarkers for the Non-Invasive Diagnosis of Endometrial Cancer: A Systematic Review and Meta-Analysis

Endometrial cancer rates are increasing annually due to an aging population and rising rates of obesity. Currently there is no widely available, accurate, non-invasive test that can be used to triage women for diagnostic biopsy whilst safely reassuring healthy women without the need for invasive assessment. The aim of this systematic review and meta-analysis is to evaluate studies assessing blood and urine-based biomarkers as a replacement test for endometrial biopsy or as a triage test in symptomatic women. For each primary study, the diagnostic accuracy of different biomarkers was assessed by sensitivity, specificity, likelihood ratio and area under ROC curve. Forest plots of summary statistics were constructed for biomarkers which were assessed by multiple studies using data from a random-effect models. All but one study was of blood-based biomarkers. In total, 15 studies reported 29 different exosomal biomarkers; 34 studies reported 47 different proteomic biomarkers. Summary statistic meta-analysis was reported for micro-RNAs, cancer antigens, hormones, and other proteomic markers. Metabolites and circulating tumor materials were also summarized. For the majority of biomarkers, no meta-analysis was possible. There was a low number of small, heterogeneous studies for the majority of evaluated index tests. This may undermine the reliability of summary estimates from the meta-analyses. At present there is no liquid biopsy that is ready to be used as a replacement test for endometrial biopsy. However, to the best of our knowledge this is the first study to report and meta-analyze the diagnostic accuracy of different classes of blood and urine biomarkers for detection of endometrial cancer. This review may thus provide a reference guide for those wishing to explore candidate biomarkers for further research.

Glycosylation of immunoglobin G in tumors: Function, regulation and clinical implications

Immunoglobulin G (IgG) is the predominant component in humoral immunity and the major effector of neutralizing heterogeneous antigens. Glycosylation, as excessive posttranscriptional modification, can modulate IgG immune function. Glycosylated IgG has been reported to correlate with tumor progression, presenting several characteristic modifications, including the core fucose, galactose, sialic acid, and the bisect N-acetylglucosamine (GlcNAc). Meanwhile, IgG glycosylation regulates tumor immunity involved in tumor progression and is thus a potential target. Herein, we summarized the research progression to provide novel insight into the application of IgG glycosylation in tumor diagnosis and treatment.

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

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

Glycosylation and its research progress in endometrial cancer

Endometrial cancer (EC) is one of the most common tumors in the female reproductive system, which seriously threatens women's health, particularly in developed countries. 13% of the patients with EC have a poor prognosis due to recurrence and metastasis. Therefore, identifying good predictive biomarkers and therapeutic targets is critical to enable the early detection of metastasis and improve the prognosis. For decades, extensive studies had focused on glycans and glycoproteins in the progression of cancer. The types of glycans that are covalently attached to the polypeptide backbone, usually via nitrogen or oxygen linkages, are known as N‑glycans or O‑glycans, respectively. The degree of protein glycosylation and the aberrant changes in the carbohydrate structures have been implicated in the extent of tumorigenesis and reported to play a critical role in regulating tumor invasion, metabolism, and immunity. This review summarizes the essential biological role of glycosylation in EC, with a focus on the recent advances in glycomics and glycosylation markers, highlighting their implications in the diagnosis and treatment of EC.

Nomogram based on clinical characteristics and serological inflammation markers to predict overall survival of oral tongue squamous cell carcinoma patient after surgery

BACKGROUND

Oral tongue squamous cell carcinoma (OTSCC) is a prevalent malignant disease that is characterized by high rates of metastasis and postoperative recurrence. The aim of this study was to establish a nomogram to predict the outcome of OTSCC patients after surgery.

METHODS

We retrospectively analyzed 169 OTSCC patients who underwent treatments in the Cancer Hospital of Shantou University Medical College from 2008 to 2019. The Cox regression analysis was performed to determine the independent prognostic factors associated with patient's overall survival (OS). A nomogram based on these prognostic factors was established and internally validated using a bootstrap resampling method.

RESULTS

Multivariate Cox regression analysis revealed the independent prognostic factors for OS were TNM stage, age, lymphocyte-to-monocyte ratio and immunoglobulin G, all of which were identified to create the nomogram. The Akaike Information Criterion and Bayesian Information Criterion of the nomogram were lower than those of TNM stage (292.222 vs. 305.480; 298.444 vs. 307.036, respectively), indicating a better goodness-of-fit of the nomogram for predicting OS. The bootstrap-corrected of concordance index (C-index) of nomogram was 0.784 (95% CI 0.708-0.860), which was higher than that of TNM stage (0.685, 95% CI 0.603-0.767, P = 0.017). The results of time-dependent C-index for OS also showed that the nomogram had a better discriminative ability than that of TNM stage. The calibration curves of the nomogram showed good consistency between the probabilities and observed values. The decision curve analysis also revealed the potential clinical usefulness of the nomogram. Based on the cutoff value obtained from the nomogram, the proposed high-risk group had poorer OS than low-risk group (P < 0.0001).

CONCLUSIONS

The nomogram based on clinical characteristics and serological inflammation markers might be useful for outcome prediction of OTSCC patient.

IgG N-glycans

Glycosylation, one of the most common post-translational modifications in mammalian cells, impacts many biological processes such as cell adhesion, proliferation and differentiation. As the most abundant glycoprotein in human serum, immunoglobulin G (IgG) plays a vital role in immune response and protection. There is a growing body of evidence suggests that IgG structure and function are modulated by attached glycans, especially N-glycans, and aberrant glycosylation is associated with disease states. In this chapter, we review IgG glycan repertoire and function, strategies for profiling IgG N-glycome and recent studies. Mass spectrometry (MS) based techniques are the most powerful tools for profiling IgG glycome. IgG glycans can be divided into high-mannose, biantennary complex and hybrid types, modified with mannosylation, core-fucosylation, galactosylation, bisecting GlcNAcylation, or sialylation. Glycosylation of IgG affects antibody half-life and their affinity and avidity for antigens, regulates crystallizable fragment (Fc) structure and Fcγ receptor signaling, as well as antibody effector function. Because of their critical roles, IgG N-glycans appear to be promising biomarkers for various disease states. Specific IgG glycosylation can convert a pro-inflammatory response to an anti-inflammatory activity. Accordingly, IgG glycoengineering provides a powerful approach to potentially develop effective drugs and treat disease. Based on the understanding of the functional role of IgG glycans, the development of vaccines with enhanced capacity and long-term protection are possible in the near future.

Sialic acids in gynecological cancer development and progression: Impact on diagnosis and treatment

Gynecological cancers are in the top 10 of most common cancers in women. Survival and outcome are strongly related to the stage at diagnosis. Therefore, early diagnosis is essential in reducing morbidity and mortality. The high mortality rate of gynecological cancers can mainly be attributed to ovarian cancer (OC). OC is commonly diagnosed at an advanced stage due to a lack of proper screening tools allowing early detection. Endometrial cancer (EC) on the contrary, is mostly diagnosed at an early stage and has, in general, better outcomes. The incidence of nonendometrioid EC has increased in the last decade, displaying a shared tumor biology with OC and consequently significantly worse outcome. New approaches allowing detection of gynecological cancers in an early stage are therefore desired. Recent studies on cancer biology have shown the relevance of altered glycosylation in the occurrence and progression of cancer. The aberrant expression of sialic acid, a specific carbohydrate terminating glycoproteins and glycolipids on the cell‐surface, is frequently correlated with malignancy. We aimed to determine the current understanding of sialic acid function in different gynecological cancers to identify the gaps in knowledge and its potential use for new diagnostic and therapeutic avenues. Therefore we performed a review on current literature focusing on studies where sialylation was linked to gynecological cancers. The identified studies showed elevated levels of sialic acid in serum, tissue and sialylated antigens in most patients with gynecological cancers, underlining its potential for diagnosis.

What's new?

Recent studies have shown the relevance of altered glycosylation in the occurrence and progression of cancer. In this review, the authors found elevated levels of sialic acid in serum and tissue and high levels of sialylated antigens in most patients with gynaecological cancers, underlining the potential of sialic acid for diagnosis. Elevated levels of sialylation were related with tumour growth, poor differentiation, inhibition of apoptosis, and chemoresistance. Taken together, the studies suggest that sialylation levels could be used to discriminate healthy and benign samples from cancer samples and even early and advanced stages in ovarian, cervical, and endometrial cancer.

Serum and Plasma Immunoglobulin G Fc N-Glycosylation Is Stable during Storage

Immunoglobulin G (IgG) glycosylation is studied in biological samples to develop clinical markers for precision medicine, for example, in autoimmune diseases and oncology. Inappropriate storage of proteins, lipids, or metabolites can lead to degradation or modification of biomolecular features, which can have a strong negative impact on accuracy and precision of clinical omics studies. Regarding the preservation of IgG glycosylation, the range of appropriate storage conditions and time frame is understudied. Therefore, we investigated the effect of storage on IgG Fc N-glycosylation in the commonly analyzed biofluids, serum and plasma. Short-term storage and accelerated storage stability were tested by incubating samples from three healthy donors under stress conditions of up to 50 °C for 2 weeks using −80 °C for 2 weeks as the reference condition. All tested IgG glycosylation features—sialylation, galactosylation, bisection, and fucosylation—remained unchanged up to room temperature as well as during multiple freeze–thaw cycles and exposure to light. Only when subjected to 37 °C or 50 °C for 2 weeks, galactosylation and sialylation subtly changed. Therefore, clinical IgG glycosylation analysis does not rely as heavily on mild serum and plasma storage conditions and timely analysis as many other omics analyses.

Association of IgG Glycosylation and Esophageal Precancerosis Beyond Inflammation

This study aimed to investigate the association of IgG glycosylation and esophageal precancerosis for squamous cell carcinoma and determine its role in inflammation. Primary glycans selected by the least absolute shrinkage and selection operator (LASSO) algorithm were validated using univariate and multivariate logistics models plus restricted cubic spline functions. In total, 24 direct glycans and 27 derived traits were detected, among which four glycans and three derived traits were primarily selected. Then, GP5 (adjusted OR: 0.805), GP17 (adjusted OR: 1.305), G12n (adjusted OR: 1.271), Gal_1 (adjusted OR: 0.776) and Fuc (adjusted OR: 0.737) were validated and significantly associated with esophageal precancerosis. In addition, there was a consistent positive association in GP17 and G12n and a negative association in GP5, Gal_1, and Fuc by restricted cubic spline function. Compared with esophageal inflammation, GP17, G12n, and Fuc were still independently associated with precancerosis. In brief, the IgG glycosylation profile was independently associated with esophageal precancerosis beyond inflammation, which could be an early biomarker for esophageal cancer.Prevention Relevance: IgG glycosylation profile is associated with esophageal precancerosis and specific IgG glycans involves in the early stage of esophageal cancer, which is independent of inflammation.