Breast cancer diagnosis and prognosis through quantitative measurements of serum glycan profiles

Recent advances in N-glycan biomarker discovery among human diseases

N-glycans play important roles in a variety of biological processes. In recent years, analytical technologies with high resolution and sensitivity have advanced exponentially, enabling analysts to investigate N-glycomic changes in different states. Specific glycan and glycosylation signatures have been identified in multiple diseases, including cancer, autoimmune diseases, nervous system disorders, and metabolic and cardiovascular diseases. These glycans demonstrate comparable or superior indicating capability in disease diagnosis and prognosis over routine biomarkers. Moreover, synchronous glycan alterations concurrent with disease initiation and progression provide novel insights into pathogenetic mechanisms and potential treatment targets. This review elucidates the biological significance of N-glycans, compares the existing glycomic technologies, and delineates the clinical performance of N-glycans across a range of diseases.

The Human Blood N-Glycome: Unraveling Disease Glycosylation Patterns

Most of the proteins in the circulation are N-glycosylated, shaping together the total blood N-glycome (TBNG). Glycosylation is known to affect protein function, stability, and clearance. The TBNG is influenced by genetic, environmental, and metabolic factors, in part epigenetically imprinted, and responds to a variety of bioactive signals including cytokines and hormones. Accordingly, physiological and pathological events are reflected in distinct TBNG signatures. Here, we assess the specificity of the emerging disease-associated TBNG signatures with respect to a number of key glycosylation motifs including antennarity, linkage-specific sialylation, fucosylation, as well as expression of complex, hybrid-type and oligomannosidic N-glycans, and show perplexing complexity of the glycomic dimension of the studied diseases. Perspectives are given regarding the protein- and site-specific analysis of N-glycosylation, and the dissection of underlying regulatory layers and functional roles of blood protein N-glycosylation.

Noninvasive serum N-glycans associated with ovarian cancer diagnosis and precancerous lesion prediction

BACKGROUND

Ovarian cancer (OC) is one of the most common gynecological tumors with high morbidity and mortality. Altered serum N-glycome has been observed in many diseases, while the association between serum protein N-glycosylation and OC progression remains unclear, particularly for the onset of carcinogenesis from benign neoplasms to cancer.

METHODS

Herein, a mass spectrometry based high-throughput technique was applied to characterize serum N-glycome profile in individuals with healthy controls, benign neoplasms and different stages of OC. To elucidate the alterations of glycan features in OC progression, an orthogonal strategy with lectin-based ELISA was performed.

RESULTS

It was observed that the initiation and development of OC was associated with increased high-mannosylationand agalactosylation, concurrently with decreased total sialylation of serum, each of which gained at least moderately accurate merits. The most important individual N-glycans in each glycan group was H7N2, H3N5 and H5N4S2F1, respectively. Notably, serum N-glycome could be used to accurately discriminate OC patients from benign cohorts, with a comparable or even higher diagnostic score compared to CA125 and HE4. Furthermore, bioinformatics analysis based discriminative model verified the diagnostic performance of serum N-glycome for OC in two independent sets.

CONCLUSIONS

These findings demonstrated the great potential of serum N-glycome for OC diagnosis and precancerous lesion prediction, paving a new way for OC screening and monitoring.

Deep learning enhanced the diagnostic merit of serum glycome for multiple cancers

Protein glycosylation is associated with the pathogenesis of various cancers. The utilization of certain glycans in cancer diagnosis models holds promise, yet their accuracy is not always guaranteed. Here, we investigated the utility of deep learning techniques, specifically random forests combined with transfer learning, in enhancing serum glycome's discriminative power for cancer diagnosis (including ovarian cancer, non-small cell lung cancer, gastric cancer, and esophageal cancer). We started with ovarian cancer and demonstrated that transfer learning can achieve superior performance in data-disadvantaged cohorts (AUROC >0.9), outperforming the approach of PLS-DA. We identified a serum glycan-biomarker panel including 18 serum N-glycans and 4 glycan derived traits, most of which were featured with sialylation. Furthermore, we validated advantage of the transfer learning scheme across other cancer groups. These findings highlighted the superiority of transfer learning in improving the performance of glycans-based cancer diagnosis model and identifying cancer biomarkers, providing a new high-fidelity cancer diagnosis venue.

N-glycan profiling of tissue samples to aid breast cancer subtyping

Breast cancer is a highly heterogeneous disease. Its intrinsic subtype classification for diagnosis and choice of therapy traditionally relies on the presence of characteristic receptors. Unfortunately, this classification is often not sufficient for precise prediction of disease prognosis and treatment efficacy. The N-glycan profiles of 145 tumors and 10 healthy breast tissues were determined using Matrix-Assisted Laser Desorption-Ionization Time-of-Flight Mass Spectrometry. The tumor samples were classified into Mucinous, Lobular, No-Special-Type, Human Epidermal Growth Factor 2 + , and Triple-Negative Breast Cancer subtypes. Statistical analysis was conducted using the reproducibility-optimized test statistic software package in R, and the Wilcoxon rank sum test with continuity correction. In total, 92 N-glycans were detected and quantified, with 59 consistently observed in over half of the samples. Significant variations in N-glycan signals were found among subtypes. Mucinous tumor samples exhibited the most distinct changes, with 28 significantly altered N-glycan signals. Increased levels of tri- and tetra-antennary N-glycans were notably present in this subtype. Triple-Negative Breast Cancer showed more N-glycans with additional mannose units, a factor associated with cancer progression. Individual N-glycans differentiated Human Epidermal Growth Factor 2 + , No-Special-Type, and Lobular cancers, whereas lower fucosylation and branching levels were found in N-glycans significantly increased in Luminal subtypes (Lobular and No-Special-Type tumors). Clinically normal breast tissues featured a higher abundance of signals corresponding to N-glycans with bisecting moiety. This research confirms that histologically distinct breast cancer subtypes have a quantitatively unique set of N-glycans linked to clinical parameters like tumor size, proliferative rate, lymphovascular invasion, and metastases to lymph nodes. The presented results provide novel information that N-glycan profiling could accurately classify human breast cancer samples, offer stratification of patients, and ongoing disease monitoring.

Age-Related Changes in Serum N-Glycome in Men and Women-Clusters Associated with Comorbidity

(1) Aim: To describe, in a general adult population, the serum N-glycome in relation to age in men and women, and investigate the association of N-glycome patterns with age-related comorbidity; (2) Methods: The serum N-glycome was studied by hydrophilic interaction chromatography with ultra-performance liquid chromatography in 1516 randomly selected adults (55.3% women; age range 18-91 years). Covariates included lifestyle factors, metabolic disorders, inflammatory markers, and an index of comorbidity. Principal component analysis was used to define clusters of individuals based on the 46 glycan peaks obtained in chromatograms; (3) Results: The serum N-glycome changed with ageing, with significant differences between men and women, both in individual N-glycan peaks and in groups defined by common features (branching, galactosylation, sialylation, fucosylation, and oligomannose). Through K-means clustering algorithm, the individuals were grouped into a cluster characterized by abundance of simpler N-glycans and a cluster characterized by abundance of higher-order N-glycans. The individuals of the first cluster were older, showed higher concentrations of glucose and glycation markers, higher levels of some inflammatory markers, lower glomerular filtration rate, and greater comorbidity index; (4) Conclusions: The serum N-glycome changes with ageing with sex dimorphism. The N-glycome could be, in line with the inflammaging hypothesis, a marker of unhealthy aging.

TSTA3 overexpression promotes malignant characteristics in LUSC by regulating LAMP2-mediated autophagy and tumor microenvironment

BACKGROUND

TSTA3 gene encoding GDP-L-fucose synthase has recently been proved to be closely related to the prognosis of patients with various tumors. However, its role in lung cancer is still unclear. The purpose of this study is to explore the expression level, prognostic effect, potential function and mechanism of TSTA3 in lung cancer.

METHODS

Based on TCGA database, Kaplan-Meier and COX regression was used to analyze the relationship between TSTA3 expression and prognosis of lung cancer patients. Immunohistochemistry was used to determine the TSTA3 protein expression in lung cancer and normal tissues. The function of TSTA3 in lung squamous cell carcinoma (LUSC) cell was determined by CCK8, colony formation, transwell assay in vitro and subcutaneous xenografts in vivo. Transcriptome analysis, Lyso-Tracker Red staining and rescue experiment were used to explore the possible underlying mechanism.

RESULTS

The expression of TSTA3 was significantly increased in lung cancer, especially in LUSC, and was significantly correlated with the malignant characteristics of LUSC. COX regression analysis showed that the high expression of TSTA3 was an independent prognostic factor in LUSC patients. This was also confirmed by immunohistochemical staining. Compared with the control group, the proliferation, colony formation, invasion and migration ability of LUSC cells with TSTA3 overexpression was enhanced. Similarly, the ability of cell proliferation, colony formation, invasion and migration were weakened after transient knockdown of TSTA3. In vivo experiment showed that compared with control group, TSTA3 overexpression significantly promoted the growth of tumor and shortened survival time. In addition, transcriptome sequencing analysis showed that the differentially expressed genes between TSTA3 overexpression and control group was mainly concentrated in the lysosome pathway. Further study found that TSTA3 might affect the proliferation, invasion and migration of LUSC by regulating the expression of lysosome-associated membrane protein 2 (LAMP2) in LUSC.

CONCLUSION

The expression level of TSTA3 in LUSC is significantly higher than that in normal tissues. High expression of TSTA3 is associated with poor prognosis of LUSC patients. TSTA3 may affect the proliferation, invasion and migration of LUSC by regulating LAMP2.

Comprehensive serum N-glycan profiling identifies a biomarker panel for early diagnosis of non-small-cell lung cancer

Aberrant serum N-glycan profiles have been observed in multiple cancers including non-small-cell lung cancer (NSCLC), yet the potential of N-glycans in the early diagnosis of NSCLC remains to be determined. In this study, serum N-glycan profiles of 275 NSCLC patients and 309 healthy controls were characterized by MALDI-TOF-MS. The levels of serum N-glycans and N-glycosylation patterns were compared between NSCLC and control groups. In addition, a panel of N-glycan biomarkers for NSCLC diagnosis was established and validated using machine learning algorithms. As a result, a total of 54 N-glycan structures were identified in human serum. Compared with healthy controls, 29 serum N-glycans were increased or decreased in NSCLC patients. N-glycan abundance in different histological types or clinical stages of NSCLC presented differentiated changes. Furthermore, an optimal biomarker panel of eight N-glycans was constructed based on logistic regression, with an AUC of 0.86 in the validation set. Notably, this model also showed a desirable capacity in distinguishing early-stage patients from healthy controls (AUC = 0.88). In conclusion, our work highlights the abnormal N-glycan profiles in NSCLC and provides supports potential application of N-glycan biomarker panel in clinical NSCLC detection.

N-glycomic profiling reveals dysregulated N-glycans of peripheral neuropathy in type 2 diabetes

Given the increasing morbidity of diabetes mellitus type 2 (T2DM) with peripheral neuropathy (PN), efficient screening for T2DM-PN is of great significance. Altered N-glycosylation is closely associated with T2DM progression, whereas its association with T2DM-PN remains uncharacterized. In this study, N-glycomic profiling was performed to identify the N-glycan features between T2DM patients with (n = 39, T2DM-PN) and without PN (n = 36, T2DM-C). Another independent set of T2DM patients (n = 29 for both T2DM-C and T2DM-PN) were utilized to validate these N-glycomic features. There were 10 N-glycans varied significantly between T2DM-C and T2DM-PN (p < 0.05 and 0.7 < AUC < 0.9), of which T2DM-PN was associated with increased oligomannose and core-fucosylation of sialylated glycans, and decreased bisected mono-sialylated glycan. Notably, these results were validated by an independent set of T2DM-C and T2DM-PN. This is the first profiling for N-glycan features in T2DM-PN patients, which reliably differentiates them from T2DM controls, thus providing a prospective profile of glyco-biomarkers for the screening and diagnosis of T2DM-PN.

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

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

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

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

MS-based glycomics: An analytical tool to assess nervous system diseases

Neurological diseases affect millions of peopleochemistryorldwide and are continuously increasing due to the globe's aging population. Such diseases affect the nervous system and are characterized by a progressive decline in brain function and progressive cognitive impairment, decreasing the quality of life for those with the disease as well as for their families and loved ones. The increased burden of nervous system diseases demands a deeper insight into the biomolecular mechanisms at work during disease development in order to improve clinical diagnosis and drug design. Recently, evidence has related glycosylation to nervous system diseases. Glycosylation is a vital post-translational modification that mediates many biological functions, and aberrant glycosylation has been associated with a variety of diseases. Thus, the investigation of glycosylation in neurological diseases could provide novel biomarkers and information for disease pathology. During the last decades, many techniques have been developed for facilitation of reliable and efficient glycomic analysis. Among these, mass spectrometry (MS) is considered the most powerful tool for glycan analysis due to its high resolution, high sensitivity, and the ability to acquire adequate structural information for glycan identification. Along with MS, a variety of approaches and strategies are employed to enhance the MS-based identification and quantitation of glycans in neurological samples. Here, we review the advanced glycomic tools used in nervous system disease studies, including separation techniques prior to MS, fragmentation techniques in MS, and corresponding strategies. The glycan markers in common clinical nervous system diseases discovered by utilizing such MS-based glycomic tools are also summarized and discussed.

Quantitative clinical glycomics strategies: A guide for selecting the best analysis approach

Glycans introduce complexity to the proteins to which they are attached. These modifications vary during the progression of many diseases; thus, they serve as potential biomarkers for disease diagnosis and prognosis. The immense structural diversity of glycans makes glycosylation analysis and quantitation difficult. Fortunately, recent advances in analytical techniques provide the opportunity to quantify even low-abundant glycopeptides and glycans derived from complex biological mixtures, allowing for the identification of glycosylation differences between healthy samples and those derived from disease states. Understanding the strengths and weaknesses of different quantitative glycomics analysis methods is important for selecting the best strategy to analyze glycosylation changes in any given set of clinical samples. To provide guidance towards selecting the proper approach, we discuss four widely used quantitative glycomics analysis platforms, including fluorescence-based analysis of released N-linked glycans and three different varieties of MS-based analysis: liquid chromatography (LC)-mass spectrometry (MS) analysis of glycopeptides, matrix-assisted laser desorption ionization-time of flight MS, and LC-ESI-MS analysis of released N-linked glycans. These methods' strengths and weaknesses are compared, particularly associated with the figures of merit that are important for clinical biomarker studies, including: the initial sample requirements, the methods' throughput, sample preparation time, the number of species identified, the methods' utility for isomer separation and structural characterization, method-related challenges associated with quantitation, repeatability, the expertise required, and the cost for each analysis. This review, therefore, provides unique guidance to researchers who endeavor to undertake a clinical glycomics analysis by offering insights on the available analysis technologies.

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

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

An N-glycoproteomic site-mapping analysis reveals glycoprotein alterations in esophageal squamous cell carcinoma

Background

Aberrant glycosylation has been recognized as a hallmark of cancer and N-glycosylation is one of the main types of glycosylation in eukaryotes. Although N-glycoproteomics has made contributions to the discovery of biomarkers in a variety of cancers, less is known about the abnormal glycosylation signatures in esophageal squamous cell carcinoma (ESCC).

Methods

In this study, we reported the proteomics and N-glycoproteomic site-mapping analysis of eight pairs of ESCC tissues and adjacent normal tissues. With zic-HILIC enrichment, TMT-based isobaric labeling, LC–MS/MS analysis, differentially expressed N-glycosylation was quantitatively characterized. Lectin affinity enrichment combined with western blot was used to validate the potential biomarkers in ESCC.

Results

A series of differentially expressed glycoproteins (e.g., LAMP2, PLOD2) and enriched signaling pathways (e.g., metabolism-related pathway, ECM-receptor interaction, focal adhesion) were identified. Besides that, seven significantly enriched motifs were found from the identified N-glycosylation sites. Three clusters were identified after conducting the dynamic profiling analysis of glycoprotein change during lymph node metastasis progression. Further validation found that the elevated fucosylation level of ITGB1, CD276 contributed to the occurrence and development of ESCC, which might be the potential biomarkers in ESCC.

Conclusion

In summary, we characterized the N-glycosylation and N-glycoprotein alterations associated with ESCC. The typical changes in glycoprotein expression and glycosylation occupancy identified in our study will not only be used as ESCC biomarkers but also improve the understanding of ESCC biology.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03489-2.

Changes in Serum N-Glycome for Risk Drinkers: A Comparison with Standard Markers for Alcohol Abuse in Men and Women

Background and aim: Glycomic alterations serve as biomarker tools for different diseases. The present study aims to evaluate the diagnostic capability of serum N-glycosylation to identify alcohol risk drinking in comparison with standard markers. Methods: We included 1516 adult individuals (age range 18–91 years; 55.3% women), randomly selected from a general population. A total of 143 (21.0%) men and 50 (5.9%) women were classified as risk drinkers after quantification of daily alcohol consumption and the Alcohol Use Disorders Identification Test (AUDIT). Hydrophilic interaction ultra-performance liquid chromatography (HILIC-UPLC) was used for the quantification of 46 serum N-glycan peaks. Serum gamma-glutamyltransferase (GGT), carbohydrate-deficient transferrin (CDT), and red blood cell mean corpuscular volume (MCV) were measured by standard clinical laboratory methods. Results: Variations in serum N-glycome associated risk drinking were more prominent in men compared to women. A unique combination of N-glycan peaks selected by the selbal algorithm shows good discrimination between risk-drinkers and non-risk drinkers for men and women. Receiver operating characteristics (ROC) curves show accuracy for the diagnosis of risk drinking, which is comparable to that of the golden standards, GGT, MCV and CDT markers for men and women. Additionally, the inclusion of N-glycan peaks improves the diagnostic accuracy of the standard markers, although it remains relatively low, due to low sensitivity. For men, the area under the ROC curve using N-glycome data is 0.75, 0.76, and 0.77 when combined with GGT, MCV, and CDT, respectively. In women, the areas were 0.76, 0.73, and 0.73, respectively. Conclusion: Risk drinking is associated with significant variations in the serum N-glycome, which highlights its potential diagnostic utility.

Breast cancer glycan biomarkers: their link to tumour cell metabolism and their perspectives in clinical practice

INTRODUCTION

Breast cancer (BCa) is the most common cancer type diagnosed in women and 5^th most common cause of deaths among all cancer deaths despite the fact that screening program is at place. This is why novel diagnostics approaches are needed in order to decrease number of BCa cases and disease mortality.

AREAS COVERED

In this review paper, we aim to cover some basic aspects regarding cellular metabolism and signalling in BCa behind altered glycosylation. We also discuss novel exciting discoveries regarding glycan-based analysis, which can provide useful information for better understanding of the disease. The final part deals with clinical usefulness of glycan-based biomarkers and the clinical performance of such biomarkers is compared to already approved BCa biomarkers and diagnostic tools based on imaging.

EXPERT OPINION

Recent discoveries suggest that glycan-based biomarkers offer high accuracy for possible BCa diagnostics in blood, but also for better monitoring and management of BCa patients. The review article was written using Web of Science search engine to include articles published between 2019 and 2021.

Altered O-glycomes of Renal Brush-Border Membrane in Model Rats with Chronic Kidney Diseases

Chronic kidney disease (CKD) is defined as a decrease in renal function or glomerular filtration rate (GFR), and proteinuria is often present. Proteinuria increases with age and can be caused by glomerular and/or proximal tubule (PT) alterations. PT cells have an apical brush border membrane (BBM), which is a highly dynamic, organized, and specialized membrane region containing multiple glycoproteins required for its functions including regulating uptake, secretion, and signaling dependent upon the physiologic state. PT disorders contribute to the dysfunction observed in CKD. Many glycoprotein functions have been attributed to their N- and O-glycans, which are highly regulated and complex. In this study, the O-glycans present in rat BBMs from animals with different levels of kidney disease and proteinuria were characterized and analyzed using liquid chromatography tandem mass spectrometry (LC–MS/MS). A principal component analysis (PCA) documented that each group has distinct O-glycan distributions. Higher fucosylation levels were observed in the CKD and diabetic groups, which may contribute to PT dysfunction by altering physiologic glycoprotein interactions. Fucosylated O-glycans such as 1-1-1-0 exhibited higher abundance in the severe proteinuric groups. These glycomic results revealed that differential O-glycan expressions in CKD progressions has the potential to define the mechanism of proteinuria in kidney disease and to identify potential therapeutic interventions.

Glycosylation Biomarkers Associated with Age-Related Diseases and Current Methods for Glycan Analysis

Ageing is a complex process which implies the accumulation of molecular, cellular and organ damage, leading to an increased vulnerability to disease. In Western societies, the increase in the elderly population, which is accompanied by ageing-associated pathologies such as cardiovascular and mental diseases, is becoming an increasing economic and social burden for governments. In order to prevent, treat and determine which subjects are more likely to develop these age-related diseases, predictive biomarkers are required. In this sense, some studies suggest that glycans have a potential role as disease biomarkers, as they modify the functions of proteins and take part in intra- and intercellular biological processes. As the glycome reflects the real-time status of these interactions, its characterisation can provide potential diagnostic and prognostic biomarkers for multifactorial diseases. This review gathers the alterations in protein glycosylation profiles that are associated with ageing and age-related diseases, such as cancer, type 2 diabetes mellitus, metabolic syndrome and several chronic inflammatory diseases. Furthermore, the review includes the available techniques for the determination and characterisation of glycans, such as liquid chromatography, electrophoresis, nuclear magnetic resonance and mass spectrometry.

Serum N-glycan profiles differ for various breast cancer subtypes

Breast cancer is the most prevalent cancer in women. Early detection of this disease improves survival and therefore population screenings, based on mammography, are performed. However, the sensitivity of this screening modality is not optimal and new screening methods, such as blood tests, are being explored. Most of the analyses that aim for early detection focus on proteins in the bloodstream. In this study, the biomarker potential of total serum N-glycosylation analysis was explored with regard to detection of breast cancer. In an age-matched case-control setup serum protein N-glycan profiles from 145 breast cancer patients were compared to those from 171 healthy individuals. N-glycans were enzymatically released, chemically derivatized to preserve linkage-specificity of sialic acids and characterized by high resolution mass spectrometry. Logistic regression analysis was used to evaluate associations of specific N-glycan structures as well as N-glycosylation traits with breast cancer. In a case-control comparison three associations were found, namely a lower level of a two triantennary glycans and a higher level of one tetraantennary glycan in cancer patients. Of note, various other N-glycomic signatures that had previously been reported were not replicated in the current cohort. It was further evaluated whether the lack of replication of breast cancer N-glycomic signatures could be partly explained by the heterogenous character of the disease since the studies performed so far were based on cohorts that included diverging subtypes in different numbers. It was found that serum N-glycan profiles differed for the various cancer subtypes that were analyzed in this study.

Glycomic-Based Biomarkers for Ovarian Cancer: Advances and Challenges

Ovarian cancer remains one of the most common causes of death among gynecological malignancies afflicting women worldwide. Among the gynecological cancers, cervical and endometrial cancers confer the greatest burden to the developing and the developed world, respectively; however, the overall survival rates for patients with ovarian cancer are worse than the two aforementioned. The majority of patients with ovarian cancer are diagnosed at an advanced stage when cancer has metastasized to different body sites and the cure rates, including the five-year survival, are significantly diminished. The delay in diagnosis is due to the absence of or unspecific symptoms at the initial stages of cancer as well as a lack of effective screening and diagnostic biomarkers that can detect cancer at the early stages. This, therefore, provides an imperative to prospect for new biomarkers that will provide early diagnostic strategies allowing timely mitigative interventions. Glycosylation is a protein post-translational modification that is modified in cancer patients. In the current review, we document the state-of-the-art of blood-based glycomic biomarkers for early diagnosis of ovarian cancer and the technologies currently used in this endeavor.

Causal link between immunoglobulin G glycosylation and cancer: A potential glycobiomarker for early tumor detection

Changes in immunoglobulin G (IgG) glycan structures are currently believed to closely related to the emergence of cancer. In this review, we summarize the current body of evidence suggesting that differences in serum IgG glycosylation patterns correspond to changes in multiple types of cancer. Modifications include IgG terminal N-link galactosylation, IgG core fucosylation, IgG terminal sialylation, and IgG terminal bisecting N-acetylglucosamine. IgG N-glycomic alterations represent promising novel biomarkers for non-invasive-cancer diagnosis, prognosis, and progression monitoring; they are characterized by high sensitivity and specificity, compensating for previously identified glycobiomarkers.

The Repertoire of Glycan Alterations and Glycoproteins in Human Cancers

Cancer as the leading cause of death worldwide has many issues that still need to be addressed. Since the alterations on the glycan compositions or/and structures (i.e., glycosylation, sialylation, and fucosylation) are common features of tumorigenesis, glycomics becomes an emerging field examining the structure and function of glycans. In the past, cancer studies heavily relied on genomics and transcriptomics with relatively little exploration of the glycan alterations and glycoprotein biomarkers among individuals and populations. Since glycosylation of proteins increases their structural complexity by several orders of magnitude, glycome studies resulted in highly dynamic biomarkers that can be evaluated for cancer diagnosis, prognosis, and therapy. Glycome not only integrates our genetic background with past and present environmental factors but also offers a promise of more efficient patient stratification compared with genetic variations. Therefore, studying glycans holds great potential for better diagnostic markers as well as developing more efficient treatment strategies in human cancers. While recent developments in glycomics and associated technologies now offer new possibilities to achieve a high-throughput profiling of glycan diversity, we aim to give an overview of the current status of glycan research and the potential applications of the glycans in the scope of the personalized medicine strategies for cancer.

Differential N-glycosylation profiling of formalin-fixed paraffin-embedded (FFPE) invasive ductal carcinoma tissues using MALDI-TOF-MS

Invasive ductal carcinoma (IDC) is the most common type of breast cancer. As dynamic changes of the glycome are closely associated with complex diseases, they have become a focal point of cancer research involving predictive and prognostic markers. Formalin-fixed paraffin-embedded (FFPE) clinical specimens are representative of the tumor environment and are thus utilized in studies on cancer related research and biomarker discovery. Further studies on differential N-glycosylation profiling of IDC cancer tissues are necessary in order to understand the biological role of glycans in cancer and to evaluate their predictive ability. In this study, matrix assisted laser desorption ionization-mass spectrometry (MALDI-MS)-based analyses were conducted for determining differential N-glycosylation patterns of IDC. Two different derivatization methods, namely, 2-aminobenzoic acid (2-AA) labeling and linkage-specific sialic acid esterification, were used for the analysis of N-glycans. Forty-seven 2-AA labeled and fifty ethyl esterified N-glycans were identified by MALDI-MS. In statistical analyses conducted for 2-AA-labeled N-glycans, the relative amounts of 32 N-glycans and prevalence of 15 N-glycan traits showed significant (p < 0.05) differences between cancer and normal tissues; and in such analyses for the ethyl-esterified N-glycans, the relative amounts of 27 N-glycans and prevalence of 17 N-glycan traits showed significant (p < 0.05) differences between them. It was found that mainly high mannose N-glycans, including H5N2, H6N2, and H7N2, and two fucosylated compositions (H3N3F1 and H5N5F1) showed strong discrimination between IDC and controls. In addition, compared with the controls, high mannose N-glycans were observed to be up-regulated in IDC whereas bisecting N-glycans were down-regulated.

NF-κB Signaling Is Regulated by Fucosylation in Metastatic Breast Cancer Cells

A growing body of evidence indicates that the levels of fucosylation correlate with breast cancer progression and contribute to metastatic disease. However, very little is known about the signaling and functional outcomes that are driven by fucosylation. We performed a global proteomic analysis of 4T1 metastatic mammary tumor cells in the presence and absence of a fucosylation inhibitor, 2-fluorofucose (2FF). Of significant interest, pathway analysis based on our results revealed a reduction in the NF-κB and TNF signaling pathways, which regulate the inflammatory response. NF-κB is a transcription factor that is pro-tumorigenic and a prime target in human cancer. We validated our results, confirming that treatment of 4T1 cells with 2FF led to a decrease in NF-κB activity through increased IκBα. Based on these observations, we conclude that fucosylation is an important post-translational modification that governs breast cancer cell signaling.

Rapid N-Glycan Profiling of Serum and Plasma by a Novel Slide-Based Imaging Mass Spectrometry Workflow

Changes in the levels and compositions of N-glycans released from serum and plasma glycoproteins have been assessed in many diseases across many large clinical sample cohorts. Assays used for N-glycan profiling in these fluids currently require multiple processing steps and have limited throughput, thus diminishing their potential for use as standard clinical diagnostic assays. A novel slide-based N-glycan profiling method was evaluated for sensitivity and reproducibility using a pooled serum standard. Serum was spotted on to an amine-reactive slide, delipidated and desalted with a series of washes, sprayed with peptide N-glycosidase F and matrix, and analyzed by MALDI-FTICR or MALDI-Q-TOF mass spectrometry. Routinely, over 75 N-glycan species can be detected from one microliter of serum in less than 6.5 h. Additionally, endoglycosidase F3 was applied to this workflow to identify core-fucosylated N-glycans and displayed the adaptability of this method for the determination of structural information. This method was applied to a small pooled serum set from either obese or nonobese patients that had breast cancer or a benign lesion. This study confirms the reproducibility, sensitivity, and adaptability of a novel method for N-glycan profiling of serum and plasma for potential application to clinical diagnostics.

Mass spectrometry in clinical glycomics: The path from biomarker identification to clinical implementation

Over the past decades, the genome and proteome have been widely explored for biomarker discovery and personalized medicine. However, there is still a large need for improved diagnostics and stratification strategies for a wide range of diseases. Post-translational modification of proteins by glycosylation affects protein structure and function, and glycosylation has been implicated in many prevalent human diseases. Numerous proteins for which the plasma levels are nowadays evaluated in clinical practice are glycoproteins. While the glycosylation of these proteins often changes with disease, their glycosylation status is largely ignored in the clinical setting. Hence, the implementation of glycomic markers in the clinic is still in its infancy. This is for a large part caused by the high complexity of protein glycosylation itself and of the analytical techniques required for their robust quantification. Mass spectrometry-based workflows are particularly suitable for the quantification of glycans and glycoproteins, but still require advances for their transformation from a biomedical research setting to a clinical laboratory. In this review, we describe why and how glycomics is expected to find its role in clinical tests and the status of current mass spectrometry-based methods for clinical glycomics.

Bisecting N-Acetylglucosamine on EGFR Inhibits Malignant Phenotype of Breast Cancer via Down-Regulation of EGFR/Erk Signaling

Glycosylation, the most prevalent and diverse post-translational modification of protein, plays crucial biological roles in many physiological and pathological events. Alteration of N-glycan has been detected during breast cancer progression. Among the specific N-glycan structures, bisecting N-Acetylglucosamine (GlcNAc) is a β1,4-linked GlcNAc attached to the core β-mannose residue, and is catalyzed by glycosyltransferase MGAT3. Bisecting GlcNAc levels were commonly dysregulated in different types of cancer. In this study, we utilized mass spectrometry and lectin microarray analysis to investigate aberrant N-glycans in breast cancer cells. Our data showed the decreased levels of bisecting GlcNAc and down-regulated expression of MGAT3 in breast cancer cells than normal epithelial cells. Using PHA-E (a plant lectin recognizing and combining bisecting GlcNAc) based enrichment coupled with nanoLC-MS/MS, we analyzed the glycoproteins bearing bisecting GlcNAc in various breast cancer cells. Among the differentially expressed glycoproteins, levels of bisecting GlcNAc on EGFR were significantly decreased in breast cancer cells, confirmed by immunostaining and immunoprecipitation. We overexpressed MGAT3 in breast cancer MDA-MB-231 cells, and overexpression of MGAT3 significantly enhanced the bisecting N-GlcNAc on EGFR and suppressed the EGFR/Erk signaling, which further resulted in the reduction of migratory ability, cell proliferation, and clonal formation. Taken together, we conclude that bisecting N-GlcNAc on EGFR inhibits malignant phenotype of breast cancer via down-regulation of EGFR/Erk signaling.

Glycoprotein biomarkers and analysis in chronic obstructive pulmonary disease and lung cancer with special focus on serum immunoglobulin G

Chronic obstructive pulmonary disease (COPD) and lung cancer are two major diseases of the lung with high rate of mortality, mostly among tobacco smokers. The glycosylation patterns of various plasma proteins show significant changes in COPD and subsequent hypoxia, inflammation and lung cancer, providing promising opportunities for screening aberrant glycan structures contribute to early detection of both diseases. Glycoproteins associated with COPD and lung cancer consist of highly sialylated N-glycans, which play an important role in inflammation whereby hypoxia leads to accumulation of sialyl Lewis A and X glycans. Although COPD is an inflammatory disease, it is an independent risk factor for lung cancer. Marked decrease in galactosylation of plasma immunoglobulin G (IgG) together with increased presence of sialic acids and more complex highly branched N-glycan structures are characteristic for COPD and lung cancer. Numerous glycan biomarkers have been discovered, and analysis of glycovariants associated with COPD and lung cancer has been carried out. In this paper we review fundamental glycosylation changes in COPD and lung cancer glycoproteins, focusing on IgG to provide an opportunity to distinguish between the two diseases at the glycoprotein level with diagnostic value.

Use of Lectin-based Affinity Techniques in Breast Cancer Glycoproteomics: A Review

Changes in glycoprotein content, altered glycosylations, and aberrant glycan structures are increasingly recognized as cancer hallmarks. Because breast cancer is one of the most common causes of cancer deaths in the world, it is highly urgent to find other reliable biomarkers for its initial diagnosis and to learn as much as possible about this disease. In this Review, the applications of lectins to a screening of potential breast cancer biomarkers published during recent years are overviewed. These data provide a deeper insight into the use of modern strategies, technologies, and scientific knowledge in glycoproteomic breast cancer research. Particular attention is concentrated on the use of lectin-based affinity techniques, applied independently or most frequently in combination with mass spectrometry, as an effective tool for the targeting, separation, and reliable identification of glycoprotein molecules. Individual procedures and lectins used in published glycoproteomic studies of breast-cancer-related glycoproteins are discussed. The summarized approaches have the potential for use in diagnostic and predictive applications. Finally, the use of lectins is briefly discussed from the view of their future applications in the analysis of glycoproteins in cancer.

Mass spectrometry analysis reveals aberrant N-glycans in colorectal cancer tissues

Aberrant glycosylation is strongly correlated with the development of various cancers. Tumor-associated carbohydrate antigens, including N-glycans, are predominantly expressed on the tumor cell surface. Because the incidence of colorectal cancer is high in China, we investigated aberrant N-glycans from colorectal cancer tissues (CRC) in Chinese patients. By Linear ion trap quadrupole-electrospray ionization mass spectrometry, we performed glycomic assays on N-glycans obtained from solid CRC tissues and paired peritumoral tissues. In total, aberrant N-glycans were expressed in the colorectal tumor tissues. Specifically, seven bisecting structures (M/Z 9732+, 10602+, 10752+, 11622+, 11772+, 12642+, 13522+) decreased, M/Z 10552+ (two-antennae complex N-glycan) and M/Z 12792+ (three-antennae complex N-glycan) decreased, M/Z 10132+ and M/Z 11162+ (high-mannose N-glycan) increased, and M/Z 12282+ (bifucosylated N-glycan) increased. To evaluate the MS profile data, several statistical tools were applied, including student's t test, orthogonal partial least squares discriminant analysis and receiver operating characteristic curve. The measurement of the degree of bisecting N-glycans had an area under the curve value of 0.823. Interestingly, we observed that the bisecting N-glycans decreased with the tumor stages. This phenomenon was not found in esophageal squamous cell carcinoma, in which the bisecting N-glycans had no change. Thus, the expression of bisecting N-glycans may be an interesting point in the study of colorectal cancer.

Integrated Transcriptomics, Proteomics, and Glycomics Reveals the Association between Up-regulation of Sialylated N-glycans/Integrin and Breast Cancer Brain Metastasis

Breast cancer brain metastasis has been recognized as one of the central issues in breast cancer research. The elucidation of the processes and pathways that mediate this step will provide important clues for a better understanding of breast cancer metastasis. Increasing evidence suggests that aberrant glycosylation patterns greatly contribute to cell invasion and cancer metastasis. Herein, we combined next-generation RNA sequencing with liquid chromatography-tandem mass spectrometry-based proteomic and N-glycomic analysis from five breast cancer cell lines and one brain cancer cell line to investigate the possible mechanisms of breast cancer brain metastasis. The genes/proteins associated with cell movement were highlighted in breast cancer brain metastasis. The integrin signaling pathway and the up-regulation of α-integrin (ITGA2, ITGA3) were associated with the brain metastatic process. 12 glycogenes showed unique expression in 231BR, which could result in an increase of sialylation during brain metastasis. In agreement with the changes of glycogenes, 60 out of 63 N-glycans that were identified exhibited differential expression among cell lines. The correlation between glycogenes and glycans revealed the importance of sialylation and sialylated glycans in breast cancer brain metastasis. Highly sialylated N-glycans, which were up-regulated in brain-seeking cell line 231BR, likely play a role in brain metastasis.

Altered N-glycan profile of IgG-depleted serum proteins in Hashimoto's thyroiditis

BACKGROUND

Hashimoto's thyroiditis (HT) is an autoimmune disease characterized by chronic inflammation of thyroid gland. Although HT is the most common cause of hypothyroidism, the pathogenesis of this disease is not fully understood. Glycosylation of serum proteins was examined in HT only to a limited extent. The study was designed to determine the glycosylation pattern of IgG-depleted sera from HT patients.

METHODS

Serum N-glycans released by N-glycosidase F (PNGase F) digestion were analyzed by normal-phase high-performance liquid chromatography (NP-HPLC). N-glycan structures in each collected HPLC fraction were determined by liquid chromatography-mass spectrometry (LC-MS) and exoglycosidase digestion. Fucosylation and sialylation was also analyzed by lectin blotting.

RESULTS

The results showed an increase of monosialylated tri-antennary structure (A3G3S1) and disialylated diantennary N-glycan with antennary fucose (FA2G2S2). Subsequently, we analyzed the serum N-glycan profile by lectin blotting using lectins specific for fucose and sialic acid. We found a significant decrease of Lens culinaris agglutinin (LCA) staining in HT samples, which resulted from the reduction of α1,6-linked core fucose in HT serum. We also observed an increase of Maackia amurensis II lectin (MAL-II) reaction in HT due to the elevated level of α2,3-sialylation in HT sera.

CONCLUSIONS

The detected alterations of serum protein sialylation might be caused by chronic inflammation in HT. The obtained results complete our previous IgG N-glycosylation analysis in autoimmune thyroid patients and show that the altered N-glycosylation of serum proteins is characteristic for autoimmunity process in HT. General Significance Thyroid autoimmunity is accompanied by changes of serum protein sialylation.

Highly Efficient Analysis of Glycoprotein Sialylation in Human Serum by Simultaneous Quantification of Glycosites and Site-Specific Glycoforms

Aberrant sialylation of glycoproteins is closely related to many malignant diseases, and analysis of sialylation has great potential to reveal the status of these diseases. However, in-depth analysis of sialylation is still challenging because of the high microheterogeneity of protein glycosylation, as well as the low abundance of sialylated glycopeptides (SGPs). Herein, an integrated strategy was fabricated for the detailed characterization of glycoprotein sialylation on the levels of glycosites and site-specific glycoforms by employing the SGP enrichment method. This strategy enabled the identification of up to 380 glycosites, as well as 414 intact glycopeptides corresponding to 383 site-specific glycoforms from only initial 6 μL serum samples, indicating the high sensitivity of the method for the detailed analysis of glycoprotein sialylation. This strategy was further employed to the differential analysis of glycoprotein sialylation between hepatocellular carcinoma patients and control samples, leading to the quantification of 344 glycosites and 405 site-specific glycoforms, simultaneously. Among these, 43 glycosites and 55 site-specific glycoforms were found to have significant change on the glycosite and site-specific glycoform levels, respectively. Interestingly, several glycoforms attached onto the same glycosite were found with different change tendencies. This strategy was demonstrated to be a powerful tool to reveal subtle differences of the macro- and microheterogeneity of glycoprotein sialylation.

Large-Scale Identification and Fragmentation Pathways Analysis of N-Glycans from Mouse Brain

N-linked glycosylation is one of the most common protein PTMs, and the topological structure (monosaccharide composition and sequence as well as glycosidic linkages) of N-glycans is vital information to understand their biological functions and roles. Tandem mass spectrometry has been widely used for topological structure characterization of N-glycans, where comprehensive understanding of fragmentation pathways and characteristics of product ions are essential to achieve best interpretation of MS/MS data and highest confidence of identification. Here, we report our glycomic study of N-glycome of mouse brain as well as fragmentation pathway analysis of the identified N-glycans. With LC-MS/MS analysis at both the positive and negative ESI modes together with our recently developed N-glycan database search engine GlySeeker, 221 unique N-glycans with putative topological structures were identified with target-decoy searches and number of best hits of 1. Analysis of fragmentation pathways and characteristics of product ions of permethylated N-glycans in the positive mode and native N-glycans in the negative mode were further carried out. The reported N-glycans serve as a basic reference for future glycosylation study of mouse brain; and in general database search of tandem mass spectra of N-glycans, B/Y/Z ions should be preferentially considered for the permethylated form in the positive mode and B/C/Z ions for the native form in the negative mode.

Exploring serum and immunoglobulin G N-glycome as diagnostic biomarkers for early detection of breast cancer in Ethiopian women

Background

Alterations in protein glycosylation patterns have potentially been targeted for biomarker discovery in a wide range of diseases including cancer. Although there have been improvements in patient diagnosis and survival for breast cancer (BC), there is no clinically validated serum biomarker for its early diagnosis. Here, we profiled whole serum and purified Immunoglobulin G (IgG) fraction N-glycome towards identification of non-invasive glycan markers of BC.

Methods

We employed a comprehensive glycomics approach by integrating glycoblotting-based glycan purification with MALDI-TOF/MS based quantitative analysis. Sera of BC patients belonging to stages I-IV and normal controls (NC) were collected from Ethiopian women during 2015–2016. IgG was purified by affinity chromatography using protein G spin plate and further subjected to glycoblotting for glycan release. Mass spectral data were further processed and evaluated rigorously, using various bioinformatics and statistical tools.

Results

Out of 35 N-glycans that were significantly up-regulated in the sera of all BC patients compared to the NC, 17 complex type N-glycans showed profound expression abundance and diagnostic potential (AUC = 0.8–1) for the early stage (I and II) BC patients. Most of these glycans were core-fucosylated, multiply branched and sialylated structures, whose abundance has been strongly associated with greater invasive and metastatic potential of cancer. N-glycans quantified form IgG confirmed their abundance in BC patients, of which two core-fucosylated and agalactosylated glycans (m/z 1591, 1794) could specifically distinguish (AUC = 0.944 and 0.921, p ≤ 0.001) stage II patients from NC. Abundance of such structural features in IgG is associated with a decrease in its immunosuppressive potential towards tumor cells, which in part may correlate with the aggressive nature of BC commonly noticed in black population.

Conclusions

Our comprehensive study has addressed for the first time both whole serum and IgG N-glycosylation signatures of native black women suffering from BC and revealed novel glyco-biomarkers with marked overexpression and distinguishing ability at early stage patients. Further studies on direct identification of the intact glycoproteins using a glycoprteomics approach will provide a deeper understanding of specific biomarkers towards their clinical utility.

Graphical abstract

Electronic supplementary material

The online version of this article (10.1186/s12885-019-5817-8) contains supplementary material, which is available to authorized users.

Core-Fucosylated Tetra-Antennary N-Glycan Containing A Single N-Acetyllactosamine Branch Is Associated with Poor Survival Outcome in Breast Cancer

(1) Glycoproteins account for ~80% of proteins located at the cell surface and in the extracellular matrix. A growing body of evidence indicates that α-L-fucose protein modifications contribute to breast cancer progression and metastatic disease. (2) Using a combination of techniques, including matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI-IMS) based in cell and on tissue imaging and glycan sequencing using exoglycosidase analysis coupled to hydrophilic interaction ultra-high performance liquid chromatography (HILIC UPLC), we establish that a core-fucosylated tetra-antennary glycan containing a single N-acetyllactosamine (F(6)A4G4Lac1) is associated with poor clinical outcomes in breast cancer, including lymph node metastasis, recurrent disease, and reduced survival. (3) This study is the first to identify a single N-glycan, F(6)A4G4Lac1, as having a correlation with poor clinical outcomes in breast cancer.

Stage-associated differences in the serum N- and O-glycan profiles of patients with non-small cell lung cancer

Background

Lung cancer is the leading cause of cancer death in China and around the world. Early detection is key to improving the survival rate of non-small cell lung cancer (NSCLC). Alteration in glycosylation has been observed in cancers, and glycans can be a source for the development of new biomarkers for NSCLC.

Methods

In this glycan biomarker discovery study, we measured serum N- and O-glycan profiles in NSCLC patients with different stages and healthy controls by performing lectin microarray analysis. The alterations of serum glycopatterns were compared between NSCLC patients and controls, and the stage-related changes in serum glycosylation were evaluated.

Results

There were 18 lectins (e.g., AAL, Jacalin, GSL-I and DBA) to give significantly alterations of serum glycopatterns in lung adenocarcinoma compared with control group. Meanwhile, 16 lectins (e.g., Jacalin, HHL, and PHA-E+L) exhibited significantly alterations of serum glycopatterns in squamous cell carcinoma (SCC) compared with control group. Importantly, most of the lectins showing altered signals exhibited significantly increased or decreased NFIs in patients with early stage adenocarcinoma and SCC.

Conclusions

The serum glycan profiles were significantly different between NSCLC and healthy control, and most of the glycosylation changes had occurred at early stage. Further evaluation is needed to examine the diagnostic value of the glycan markers identified in this study.

Sialic Acid Linkage Analysis Refines the Diagnosis of Ovarian Cancer

Epithelial ovarian cancer (EOC) is a rather rare but lethal disease that is usually diagnosed at an advanced stage; this is due to a lack of early diagnostic markers. At the time being, less than a quarter of patients are diagnosed when the tumor has not metastasized yet. In previous work, we demonstrated that antennarity, fucosylation, and sialylation increased in EOC patients and built a glycan-based score that was able to diagnose EOC better than CA125, the routine diagnostic marker, does. To date, little attention had been paid to the sialic acid linkages of N-glycans in the context of blood biomarker research. In this work, the sialic acid linkages of the serum glycome of ovarian cancer patients were investigated for the first time by MALDI-TOF-MS. To this end, we released N-glycans, derivatized sialic acids solely in a linkage-specific way and measured glycome profiles by MALDI-TOF mass spectrometry. A statistically significant decrease was observed between late stage patients and controls or early stage patients for high-mannose, hybrid-type, complex-type asialylated, bi, tri- and tetraantennary sialylated structures. A significant decrease of monosialylated monoantennary N-glycan structures was observed in early and late stage EOC when compared to healthy controls. Statistically significant increases were observed in early and late stage patients compared to controls for tri, tetraantennary fucosylated structures, afucosylated, and fucosylated triantennary structures taken as α-2,3-linked/α-2,6-linked sialic acid ratio. Moreover, all afucosylated and fucosylated structures taken as α-2,3-linked/α-2,6-linked sialic acid ratio and the α-2,3-linked/α-2,6-linked sialic acid ratio of all sialylated structures were increased significantly for early and late stage EOC patients when compared to healthy controls. Finally, ROC curves were built for the most significant glycan combinations and we were able to show that the serum glycome sialic acid ratio could enhance ovarian cancer diagnosis as sialic acid linkage modulations arise even in early stage ovarian cancer.

Comprehensive N-Glycome Profiling of Cells and Tissues for Breast Cancer Diagnosis

Aberrant protein glycosylation is observed in the progression of many types of diseases, including different cancers. In this study, we assess differential N-glycan patterns of human breast cancer cells and tissues by PGC-ESI-MS/MS. Compared with mammary epithelial cells, high-mannose glycans were significantly elevated in breast cancer cells. However, the alteration of N-glycans in tissues was more obvious than that in cells. Sixty-three kinds of different N-glycans were stably identified, and 38 types of them exhibited significant differences between para-carcinoma and breast cancer tissues. High-mannose glycans and core-fucosylated glycans were increased in the breast cancer tissues, while bisected glycans and sialylated glycans were decreased. Moreover, a total of 27 types of N-glycans displayed evident differences between benign breast tumor and breast cancer tissues, and most of them including bisected and sialylated glycans exhibited decreased relative abundances in cancer tissues. Overall, three high-mannose N-glycans (F0H6N2S0, F0H7N2S0, F0H8N2S0) exhibited significant diagnostic accuracy in both breast cancer cells and tissues, suggesting their potential role in biomarkers. Furthermore, a negative correlation between sialylated glycans and age of patients was identified. In conclusion, our results may be beneficial to understand the role that N-glycan plays on the progression of breast cancer and propose potential diagnostic biomarkers.

Hypoxia and serum deprivation induces glycan alterations in triple negative breast cancer cells

Triple negative breast cancer (TNBC) is a major global public health problem. The lack of targeted therapy and the elevated mortality evidence the need for better knowledge of the tumor biology. Hypoxia and aberrant glycosylation are associated with advanced stages of malignancy, tumor progression and treatment resistance. Importantly, serum deprivation regulates the invasive phenotype and favors TNBC cell survival. However, in TNBC, the role of hypoxia and serum deprivation in the regulation of glycosylation remains largely unknown. The effects of hypoxia and serum deprivation on the expression of glycosyltransferases and glycan profile were evaluated in the MDA-MB-231 cell line. We showed that the overexpression of HIF-1α was accompanied by acquisition of epithelial-mesenchimal transition features. Significant upregulation of fucosyl- and sialyltransferases involved in the synthesis of tumor-associated carbohydrate antigens was observed together with changes in fucosylation and sialylation detected by Aleuria aurantia lectin and Sambucus nigra agglutinin lectin blots. Bioinformatic analysis further indicated a mechanism by which HIF-1α can regulate ST3GAL6 expression and the relationship within the intrinsic characteristics of TNBC tumors. In conclusion, our results showed the involvement of hypoxia and serum deprivation in glycosylation profile regulation of TNBC cells triggering breast cancer aggressive features and suggesting glycosylation as a potential diagnostic and therapeutic target.

Death receptor 5 is activated by fucosylation in colon cancer cells

The remarkable pro‐apoptotic properties of tumour necrosis factor (TNF)‐related apoptosis‐inducing ligand (TRAIL) have led to considerable interest in this protein as a potential anticancer therapeutic. However, TRAIL is largely ineffective in inducing apoptosis in certain cancer cells, and the mechanisms underlying this selectivity are unknown. In colon adenocarcinomas, posttranslational modifications including O‐ and N‐ glycosylation of death receptors were found to correlate with TRAIL‐induced apoptosis. Additionally, mRNA levels of fucosyltransferase 3 (FUT3) and 6 (FUT6) were found to be high in the TRAIL‐sensitive colon adenocarcinoma cell line COLO 205. In this study, we use agonistic receptor‐specific TRAIL variants to dissect the contribution of FUT3 and FUT6‐mediated fucosylation to TRAIL‐induced apoptosis via its two death receptors, DR4 and DR5. Triggering of apoptosis by TRAIL revealed that the low FUT3/6‐expressing cells DLD‐1 and HCT 116 are insensitive to DR5 but not to DR4‐mediated apoptosis. By contrast, efficient apoptosis is mediated via both receptors in high FUT3/6‐expressing COLO 205 cells. The reconstitution of FUT3/6 expression in DR5‐resistant cells completely restored TRAIL sensitivity via this receptor, while only marginally enhancing apoptosis via DR4 at lower TRAIL concentrations. Interestingly, we observed that induction of the salvage pathway by external administration of l‐fucose restores DR5‐mediated apoptosis in both DLD‐1 and HCT 116 cells. Finally, we show that fucosylation influences the ligand‐independent receptor association that leads to increased death inducing signalling complex (DISC) formation and caspase‐8 activation. Taken together, these results provide evidence for the differential impact of fucosylation on signalling via DR4 or DR5. These findings provide novel opportunities to enhance TRAIL sensitivity in colon adenocarcinoma cells that are highly resistant to DR5‐mediated apoptosis.

Clinically Relevant Post-Translational Modification Analyses-Maturing Workflows and Bioinformatics Tools

Post-translational modifications (PTMs) can occur soon after translation or at any stage in the lifecycle of a given protein, and they may help regulate protein folding, stability, cellular localisation, activity, or the interactions proteins have with other proteins or biomolecular species. PTMs are crucial to our functional understanding of biology, and new quantitative mass spectrometry (MS) and bioinformatics workflows are maturing both in labelled multiplexed and label-free techniques, offering increasing coverage and new opportunities to study human health and disease. Techniques such as Data Independent Acquisition (DIA) are emerging as promising approaches due to their re-mining capability. Many bioinformatics tools have been developed to support the analysis of PTMs by mass spectrometry, from prediction and identifying PTM site assignment, open searches enabling better mining of unassigned mass spectra-many of which likely harbour PTMs-through to understanding PTM associations and interactions. The remaining challenge lies in extracting functional information from clinically relevant PTM studies. This review focuses on canvassing the options and progress of PTM analysis for large quantitative studies, from choosing the platform, through to data analysis, with an emphasis on clinically relevant samples such as plasma and other body fluids, and well-established tools and options for data interpretation.

Delineation of disease phenotypes associated with esophageal adenocarcinoma by MALDI-IMS-MS analysis of serum N-linked glycans

N-Linked glycans, extracted from patient sera and healthy control individuals, are analyzed by Matrix-assisted laser desorption ionization (MALDI) in combination with ion mobility spectrometry (IMS), mass spectrometry (MS) and pattern recognition methods. MALDI-IMS-MS data were collected in duplicate for 58 serum samples obtained from individuals diagnosed with Barrett's esophagus (BE, 14 patients), high-grade dysplasia (HGD, 7 patients), esophageal adenocarcinoma (EAC, 20 patients) and disease-free control (NC, 17 individuals). A combined mobility distribution of 9 N-linked glycans is established for 90 MALDI-IMS-MS spectra (training set) and analyzed using a genetic algorithm for feature selection and classification. Two models for phenotype delineation are subsequently developed and as a result, the four phenotypes (BE, HGD, EAC and NC) are unequivocally differentiated. Next, the two models are tested against 26 blind measurements. Interestingly, these models allowed for the correct phenotype prediction of as many as 20 blinds. Although applied to a limited number of blind samples, this methodology appears promising as a means of discovering molecules from serum that may have capabilities as markers of disease.

Clinical application of quantitative glycomics

INTRODUCTION

Aberrant glycosylation has been associated with many diseases. Decades of research activities have reported many reliable glycan biomarkers of different diseases which enable effective disease diagnostics and prognostics. However, none of the glycan markers have been approved for clinical diagnosis. Thus, a review of these studies is needed to guide the successful clinical translation. Area covered: In this review, we describe and discuss advances in analytical methods enabling clinical glycan biomarker discovery, focusing only on studies of released glycans. This review also summarizes the different glycobiomarkers identified for cancers, Alzheimer's disease, diabetes, hepatitis B and C, and other diseases. Expert commentary: Along with the development of techniques in quantitative glycomics, more glycans or glycan patterns have been reported as better potential biomarkers of different diseases and proved to have greater diagnostic/diagnostic sensitivity and specificity than existing markers. However, to successfully apply glycan markers in clinical diagnosis, more studies and verifications on large biological cohorts need to be performed. In addition, faster and more efficient glycomic strategies need to be developed to shorten the turnaround time. Thus, glycan biomarkers have an immense chance to be used in clinical prognosis and diagnosis of many diseases in the near future.

The effect of blood sampling and preanalytical processing on human N-glycome

Glycome modulations have been described in the onset and progression of many diseases. Thus, many studies have proposed glycans from blood glycoproteins as disease markers. Astonishingly, little effort has been given unraveling preanalytical conditions potentially influencing glycan analysis prior to blood biomarker studies. In this work, we evaluate for the first time the effect of hemolysis, storage and blood collection, but also influence of various times and temperatures between individual processing steps on the total N-glycome and on a glycan-biomarker score. Venous blood was collected from 10 healthy donors in 11 blood collection tubes with different additives, processed variously to obtain 16 preanalytical variables and N-glycans released from serum or plasma were analyzed by MALDI-TOF-MS and capillary electrophoresis coupled with fluorescence detection (CE-LIF) for the first time. Long time storage of deep frozen samples at -20°C or -80°C exerted only a minor influence on the glycome as demonstrated by CE-LIF. The N-glycome was very stable evidenced by MALDI-TOF when stored at 4°C for at least 48 hours and blood collected in tubes devoid of additives. The glycome was stable upon storage after centrifugation and aliquoting, which is an important information considering future diagnostic applications. Hemolysis, however, negatively correlated with an established glycan score for ovarian cancer, when evaluated by MALDI-TOF-MS measurement by affecting relative intensities of certain glycans, which could lead to false negative / positive results in glycan biomarker studies.