Serum N-glycome alterations in breast cancer during multimodal treatment and follow-up

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.

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

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

Serum glycomic profile as a predictive biomarker of recurrence in patients with differentiated thyroid cancer

PURPOSE

Thyroid cancer recurrence following curative thyroidectomy is associated with increased morbidity and mortality, but current surveillance strategies are inadequate for early detection. Prior studies indicate that tissue glycosylation is altered in thyroid cancer, but the utility of serum glycosylation in thyroid cancer surveillance remains unexplored. We therefore assessed the potential utility of altered serum glycomic profile as a tumor-specific target for disease surveillance in recurrent thyroid cancer.

EXPERIMENTAL DESIGN

We employed banked serum samples from patients with recurrent thyroid cancer post thyroidectomy and healthy controls. N-glycans were enzymatically released from serum glycoproteins, labeled via permethylation, and analyzed by MALDI-TOF mass spectrometry. Global level and specific subtypes of glycan structures were compared between patients and controls.

RESULTS

We evaluated 28 independent samples from 13 patients with cancer recurrence and 15 healthy controls. Global features of glycosylation, including N-glycan class and terminal glycan modifications were similar between groups, but three of 35 individual glycans showed significant differences. The three glycans were biosynthetically related biantennary core fucosylated N-glycans that only varied by the degree of galactosylation (G0F, G1F, and G2F; G: galactose, F: fucose). The ratio of G0F:G1F that captures reduced galactosylation was observed in patients samples but not in healthy controls (p = 0.004) and predicted thyroid cancer recurrence (AUC = 0.82, CI 95% = 0.64-0.99).

CONCLUSIONS

Altered N-glycomic profile was associated with thyroid cancer recurrence. This serum-based biomarker would be useful as an effective surveillance tool to improve the care and prognosis of thyroid cancer after prospective validation.

High-Throughput Glycomic Methods

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

Nomograms Based on Serum N-glycome for Diagnosis of Papillary Thyroid Microcarcinoma and Prediction of Lymph Node Metastasis

Non-invasive biomarkers for the diagnosis and prognosis of papillary thyroid microcarcinoma (PTMC) are still urgently needed. We aimed to characterize the N-glycome of PTMC, and establish nomograms for the diagnosis of PTMC and the prediction of lymph node metastasis (LNM). N-glycome of PTMC (LNM vs. non-LNM, capsular invasion (CI) vs. non-CI (NCI)) and matched healthy controls (HC) were quantitatively analyzed based on mass spectrometry. N-glycan traits associated with PTMC/LNM were used to create binomial logistic regression models and were visualized as nomograms. We found serum N-glycome differed between PTMC and HC in high-mannose, complexity, fucosylation, and bisection, of which, four N-glycan traits (TM, CA1, CA4, and A2Fa) were significantly associated with PTMC. The nomogram based on four traits achieved good performance for the identification of PTMC. Two N-glycan traits (CA4 and A2F0S0G) showed strong associations with LNM. The nomogram based on two traits showed relatively good performance in predicting LNM. We also found differences between CI and NCI in several N-glycan traits, which were not the same as that associated with LNM. This study reported serum N-glycosylation signatures of PTMC for the first time. Nomograms constructed from aberrant glycans could be useful tools for PTMC diagnosis and stratification.

Differentiation of Sialyl Linkages Using a Combination of Alkyl Esterification and Phenylhydrazine Derivatization: Application for N-Glycan Profiling in the Sera of Patients with Lung Cancer

Alterations in oligosaccharides and types of sialic acid (SA) attachments have been associated with different pathological states. Matrix-assisted laser desorption mass spectrometry (MS) is commonly used for glycosylation studies. However, native sialylated glycans are suppressed or not detected during MS experiments. Consequently, different approaches have been employed to neutralize the negative charge of the carboxyl group. In this study, we present the advantage of phenylhydrazine (PHN) labeling for the detection and efficient discrimination of SA linkages when this derivatization follows alkyl esterification. As expected, PHN-labeled sialylated oligosaccharides with the 2,6-linkage type can be easily recognized according to the additional shift in mass corresponding to the presence of a methyl or ethyl group. Surprisingly, oligosaccharides with the 2,3-linked SA residue instead of a lactone were detected carrying the second PHN unit. This was beneficial as no further processing after esterification was needed to stabilize the lactone form. Moreover, during tandem mass experiments, all modified glycans produced favorable fragmentation patterns with a coherent recognition of SA linkages. Although both types of esterification, herein called the EST-PHN approach, provided comparable results, methylation exhibited marginally higher linkage specificity than ethyl esterification. The simplicity and effectiveness of the methodology are demonstrated on the model compound, sialyllactose, and its applicability for biological studies is presented on N-glycan profiling in the sera of lung cancer patients.

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.

Screening and diagnosis of colorectal cancer and advanced adenoma by Bionic Glycome method and machine learning

Colorectal cancer (CRC), one of the major health problems worldwide, mostly develops from colorectal adenomas. Advanced adenomas are generally considered as precancerous lesions and patients are recommended to remove the adenomas. Screening for colorectal cancer is usually performed by fecal tests (FOBT or FIT) and colonoscopy, however, their benefits are limited by uptake and adherence. Most CRC develops from colorectal advanced adenomas, but there is currently a lack of effective noninvasive screening method for advanced adenomas. N-glycans in human serum hold the great potentials as biomarker for diagnosis of human cancers. Our aim was to discover blood-based markers for screening and diagnosis of advanced adenomas and CRC, and to ascertain their efficiency in classifying healthy controls, patients with advanced adenomas and CRC by incorporating machine learning techniques with reliable and simple quantitative method with "Bionic Glycome" as internal standard based on the high-throughput Matrix-assisted Laser Desorption/Ionization Mass Spectrometry (MALDI-MS). The quantitative results showed that there is a positive correlation between multi-antennary, sialylated N-glycans and CRC progress, while bi-antennary core-fucosylated N-glycans are negatively correlated with CRC progress. Machine learning is a powerful classification tool, suitable for mining big data, especially the large amount of data generated by high-throughput technologies. Using the predictive model constructed by machine learning, we obtained the classification accuracy of 75% for classification of 189 samples including CRC, advanced adenomas and healthy controls, and the accuracy of 87% for detection of the disease group that required treatment, including CRC and advanced adenomas. To our delight, the model successfully applied to the prediction of 176 samples collected a few months later, and five samples were wrongly predicted in the disease group. Overall, this diagnostic model we constructed here has valuable potential in the clinical application of detecting advanced adenomas and colorectal cancer and could compensate for the limitations of the current screening methods for detection of CRC and advanced adenomas.

Integrating transcriptomics, proteomics, glycomics and glycoproteomics to characterize paclitaxel resistance in breast cancer cells

Chemoresistance is a major factor driving breast cancer (BC) relapse and the high rates of cancer-related deaths. Aberrant levels of glycans are closely correlated with chemoresistance. The essential functions of glycans in chemoresistance is not systematically studied. In this study, an integrated strategy with a combination of transcriptomics, proteomics, glycomics and glycoproteomics was applied to explore the dysregulation of glycogenes, glycan structures and glycoproteins in chemoresistance of breast cancer cells. In paclitaxel (PTX) resistant MCF7 cells, 19 differentially expressed N-glycan-related proteins were identified, of which MGAT4A was the most significantly down-regulated, consistent with decrease in MGAT4A expression at mRNA level in PTX treated BC cells. Glycomic analysis consistently revealed suppressed levels of multi-antennary branching structures using MALDI-TOF/TOF-MS and lectin microarray. Several target glycoproteins bearing suppressed levels of multi-antennary branching structures were identified, and ERK signaling pathway was strongly suppressed in PTX resistant MCF7 cells. Our findings demonstrated the aberrant levels of multi-antennary branching structures and their target glycoproteins on PTX resistance. Systematically integrative multi-omic analysis is expected to facilitate the discovery of the aberrant glycosyltransferases, N-glycosylation and glycoproteins in tumor progression and chemoresistance. SIGNIFICANCE: An integrated strategy with a combination of transcriptomics, proteomics, glycomics and glycoproteomics is crucial to understand the association between glycans and chemoresistance in BC. In this multi-omic analysis, we identified unique glycan-related protein, glycan and glycoprotein signatures defining PTX chemoresistance in BC. This study might provide valuable information to understand molecular mechanisms underlying chemoresistance in BC.

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.

Clinical Perspective on Proteomic and Glycomic Biomarkers for Diagnosis, Prognosis, and Prediction of Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) is known as a highly aggressive malignant disease. Prognosis for patients is notoriously poor, despite improvements in surgical techniques and new (neo)adjuvant chemotherapy regimens. Early detection of PDAC may increase the overall survival. It is furthermore foreseen that precision medicine will provide improved prognostic stratification and prediction of therapeutic response. In this review, omics-based discovery efforts are presented that aim for novel diagnostic and prognostic biomarkers of PDAC. For this purpose, we systematically evaluated the literature published between 1999 and 2020 with a focus on protein- and protein-glycosylation biomarkers in pancreatic cancer patients. Besides genomic and transcriptomic approaches, mass spectrometry (MS)-based proteomics and glycomics of blood- and tissue-derived samples from PDAC patients have yielded new candidates with biomarker potential. However, for reasons discussed in this review, the validation and clinical translation of these candidate markers has not been successful. Consequently, there has been a change of mindset from initial efforts to identify new unimarkers into the current hypothesis that a combination of biomarkers better suits a diagnostic or prognostic panel. With continuing development of current research methods and available techniques combined with careful study designs, new biomarkers could contribute to improved detection, prognosis, and prediction of pancreatic cancer.

5-AZA-dC induces epigenetic changes associated with modified glycosylation of secreted glycoproteins and increased EMT and migration in chemo-sensitive cancer cells

Background

Glycosylation, one of the most fundamental post-translational modifications, is altered in cancer and is subject in part, to epigenetic regulation. As there are many epigenetic-targeted therapies currently in clinical trials for the treatment of a variety of cancers, it is important to understand the impact epi-therapeutics have on glycosylation.

Results

Ovarian and triple negative breast cancer cells were treated with the DNA methyltransferase inhibitor, 5-AZA-2-deoxycytidine (5-AZA-dC). Branching and sialylation were increased on secreted N-glycans from chemo-sensitive/non-metastatic cell lines following treatment with 5-AZA-dC. These changes correlated with increased mRNA expression levels in MGAT5 and ST3GAL4 transcripts in ovarian cancer cell lines. Using siRNA transient knock down of GATA2 and GATA3 transcription factors, we show that these regulate the glycosyltransferases ST3GAL4 and MGAT5, respectively. Moreover, 5-AZA-dC-treated cells displayed an increase in migration, with a greater effect seen in chemo-sensitive cell lines. Western blots showed an increase in apoptotic and senescence (p21) markers in all 5-AZA-dC-treated cells. The alterations seen in N-glycans from secreted glycoproteins in 5-AZA-dC-treated breast and ovarian cancer cells were similar to the N-glycans previously known to potentiate tumour cell survival.

Conclusions

While the FDA has approved epi-therapeutics for some cancer treatments, their global effect is still not fully understood. This study gives insight into the effects that epigenetic alterations have on cancer cell glycosylation, and how this potentially impacts on the overall fate of those cells.

Graphic abstract

N-Linked glycosylation profiles of therapeutic induced senescent (TIS) triple negative breast cancer cells (TNBC) and their extracellular vesicle (EV) progeny

Triple negative breast cancer (TNBC) has poor clinical outcomes and limited treatment options. Chemotherapy, while killing some cancer cells, can result in therapeutic-induced-senescent (TIS) cells. Senescent cells release significantly more extracellular vesicles (EVs) than non-senescent cells. Recently, N- and O-linked glycosylation alterations have been associated with senescence. We aimed to profile the N-linked glycans of whole cells, membrane, cytoplasm and EVs harvested from TIS TNBC cells and to compare these to results from non-senescent cells. TIS was induced in the Cal51 TNBC cells using the chemotherapeutic agent paclitaxel (PTX). Ultra-performance liquid chromatography (UPLC) analysis of exoglycosidase digested N-linked glycans was carried out on TIS compared to non-treated control cells. LC-Mass spectrometry (MS) analysis of the N-linked glycans and lectin blotting of samples was carried out to confirm the UPLC results. Significant differences were found in the N-glycan profile of the Cal51 membrane, cytoplasm and EV progeny of TIS compared to non-senescent cells. Protein mass spectrometry showed that the TIS cells contain different glycan modifying enzymes. The lectin, calnexin demonstrated a lower kDa size (∼58 kDa) in TIS compared to control cells (∼90 kDa) while Galectin 3 demonstrated potential proteolytic cleavage with 32 kDa and ∼22 kDa bands evident in TIS compared to non-senescent control cells with a major 32 kDa band only. TIS CAL51 cells also demonstrated a reduced adhesion to collagen I compared to control non-senescent cells. This study has shown that therapeutic-induced-senescent TNBC cells and their EV progeny, display differential N-glycan moieties compared to non-senescent Cal51 cells and their resultant EV progeny. For the future, N-glycan moieties on cancer senescent cells and their EV progeny hold potential for (i) the monitoring of treatment response as a liquid biopsy, and (ii) cancer senescent cell targeting with lectin therapies.

Machine Learning Based Analysis of Human Serum N-glycome Alterations to Follow up Lung Tumor Surgery

Simple Summary

Globally, there were around 2.1 million lung cancer cases and 1.8 million deaths in 2018. Hungary—where this study was carried out—had the highest rate of lung cancer in the same year. We developed a new analytical method which can be readily used to follow up the tumor surgery by investigating the glycan (sugar) structures of proteins. As the results of such investigations are very complex, computer-assisted machine learning methods were utilized for data interpretation.

Abstract

The human serum N-glycome is a valuable source of biomarkers for malignant diseases, already utilized in multiple studies. In this paper, the N-glycosylation changes in human serum proteins were analyzed after surgical lung tumor resection. Seventeen lung cancer patients were involved in this study and the N-glycosylation pattern of their serum samples was analyzed before and after the surgery using capillary electrophoresis separation with laser-induced fluorescent detection. The relative peak areas of 21 N-glycans were evaluated from the acquired electropherograms using machine learning-based data analysis. Individual glycans as well as their subclasses were taken into account during the course of evaluation. For the data analysis, both discrete (e.g., smoker or not) and continuous (e.g., age of the patient) clinical parameters were compared against the alterations in these 21 N-linked carbohydrate structures. The classification tree analysis resulted in a panel of N-glycans, which could be used to follow up on the effects of lung tumor surgical resection.

Analysis of Minor Acidic N-Glycans in Human Serum

Prior investigations by our research group focused on the method development for the simultaneous analysis of sulfated and phosphorylated glycans. Herein, the developed method was applied to analyze minor acidic N-glycans including sulfated and phosphorylated N-glycans in human serum. First, 2-aminobenzoic acid-labeled minor acidic N-glycans were enriched from the serum using a serotonin-immobilized column and were then separated into groups using hydrophilic interaction liquid chromatography, and analyzed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. Phosphorylated hybrid-type and sulfated bi-antennary N-glycans were detected in the serum. In addition, we observed that multiple types of glucuronidated N-glycans were present. These results indicate that the developed method is applicable to the analysis of glucuronidated as well as sulfated and phosphorylated N-glycans. It was also applied to the sera obtained from 17 healthy subjects and 15 pancreatic cancer patients, and the profiles of sulfated, phosphorylated, and glucuronidated N-glycans were compared. The expressed amount of glucuronidated N-glycans was significantly decreased in some pancreatic cancer patients. Numerous examples of the N-glycan analysis in human serum were reported, but phosphorylated and glucuronidated glycans were not investigated. The methods described herein allow the analysis of minor acidic glycans that are typically difficult to detect.

Hypoxia Alters Epigenetic and N-Glycosylation Profiles of Ovarian and Breast Cancer Cell Lines in-vitro

Background: Glycosylation is one of the most fundamental post-translational modifications. Importantly, glycosylation is altered in many cancers. These alterations have been proven to impact on tumor progression and to promote tumor cell survival. From the literature, it is known that there is a clear link between chemoresistance and hypoxia, hypoxia and epigenetics and more recently glycosylation and epigenetics. Methods and Results: Our objective was to investigate these differential parameters, in an in vitro model of ovarian and breast cancer. Ovarian (A2780, A2780cis, PEO1, PEO4) and triple negative breast cancer (TNBC) (MDA-MB-231 and MDA-MB-436) cells were exposed to differential hypoxic conditions (0.5-2% O₂) and compared to normoxia (21% O₂). Results demonstrated that in hypoxic conditions some significant changes in glycosylation on the secreted N-glycans from the ovarian and breast cancer cell lines were observed. These included, alterations in oligomannosylated, bisected glycans, glycans with polylactosamine extensions, in branching, galactosylation and sialylation in all cell lines except for PEO1. In general, hypoxia exposed ovarian and TNBC cells also displayed increased epithelial to mesenchymal transition (EMT) and migration, with a greater effect seen in the 0.5% hypoxia exposed samples compared to 1 and 2% hypoxia (p ≤ 0.05). SiRNA transient knock down of GATA2/3 transcription factors resulted in a decrease in the expression of glycosyltransferases ST3GAL4 and MGAT5, which are responsible for sialylation and branching, respectively. Conclusions: These glycan changes are known to be integral to cancer cell survival and metastases, suggesting a possible mechanism of action, linking GATA2 and 3, and invasiveness of both ovarian and TNBC cells in vitro.

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.

Glycan-based biomarkers for diagnosis of cancers and other diseases: Past, present, and future

Glycans are essential biomolecules in regulating human physiology and pathology ranging from signal transduction to microbial infections. Developing complex human diseases, such as cancer, diabetes, and cardiovascular diseases, are a combination of genetic and environmental factors. Genetics dominates embryonic development and the passing of genes to the next generation whereas the information in glycans reflects the impact of internal and external environmental factors, such as diseases, lifestyle, and social factors, on a person's health and disease. The reason behind this is that glycans are not directly encoded in a genetic template. Instead, they are assembled dynamically by hundreds of enzymes organized in more than 10 complex biosynthetic pathways. Any environmental changes affecting enzymatic activities or the availability of high-energy monosaccharide donors in a specific location will disturb the final structure of glycans. The glycan structure-dependent biological activities subsequently enable or disable gene expressions, which partially explain that it is difficult to pinpoint specific genetic defects to aging-associated diseases. Glycan-based biomarkers are currently used for diagnosis of diabetes, cancers, and other complex diseases. We will recapitulate the discovery of glucose, glycated proteins, glycan-, and glycoprotein-based biomarkers followed by summarizing clinically used glycan/glycoprotein-based biomarkers. The potential serum/plasma-derived N- and O-linked glycans as biomarkers will also be discussed.

Serum N-glycome alterations in colorectal cancer associate with survival

Proteins are routinely measured in clinical laboratories for diagnosis, prognosis and therapy monitoring. Nevertheless, both test improvements (performance) and innovations (biomarkers) are needed, and protein N-glycosylation offers a rich source of potential markers. Here, we have analyzed the total serum N-glycome in a matched case-control study (124 cases versus 124 controls) of colorectal cancer patients. The results were validated in an independent sample cohort (both 61 cases versus 61 controls) and further tested in post-operative samples of cured patients. Our results revealed significant differences between patients and controls, with increased size (antennae) and sialylation of the N-glycans in the colorectal cancer patient sera as compared to mainly di-antennary N-glycans in sera from controls. Furthermore, glycan alterations showed strong associations with cancer stage and survival: The five-year survival rate largely varied between patients with an altered serum N-glycome (46%) and an N-glycome similar to controls (87%). Importantly, the total serum N-glycome showed prognostic value beyond age and stage. This clinical glycomics study provides novel serum biomarker candidates and shows the potential of total serum N-glycans as a prognostic panel. Moreover, serum N-glycome changes reverted to a control-like profile after successful treatment as was demonstrated from pre- and post-operative samples.