Increased α1-3 fucosylation of α-1-acid glycoprotein (AGP) in pancreatic cancer

Blood-Based Multiomics-Guided Detection of a Precancerous Pancreatic Tumor

Over a decade ago, longitudinal multiomics analysis was pioneered for early disease detection and individually tailored precision health interventions. However, high sample processing costs, expansive multiomics measurements along with complex data analysis have made this approach to precision/personalized medicine impractical. Here we describe in a case report, a more practical approach that uses fewer measurements, annual sampling, and faster decision making. We also show how this approach offers promise to detect an exceedingly rare and potentially fatal condition before it fully manifests. Specifically, we describe in the present case report how longitudinal multiomics monitoring (LMOM) helped detect a precancerous pancreatic tumor and led to a successful surgical intervention. The patient, enrolled in an annual blood-based LMOM since 2018, had dramatic changes in the June 2021 and 2022 annual metabolomics and proteomics results that prompted further clinical diagnostic testing for pancreatic cancer. Using abdominal magnetic resonance imaging, a 2.6 cm lesion in the tail of the patient's pancreas was detected. The tumor fluid from an aspiration biopsy had 10,000 times that of normal carcinoembryonic antigen levels. After the tumor was surgically resected, histopathological findings confirmed it was a precancerous pancreatic tumor. Postoperative omics testing indicated that most metabolite and protein levels returned to patient's 2018 levels. This case report illustrates the potentials of blood LMOM for precision/personalized medicine, and new ways of thinking medical innovation for a potentially life-saving early diagnosis of pancreatic cancer. Blood LMOM warrants future programmatic translational research with the goals of precision medicine, and individually tailored cancer diagnoses and treatments.

The role of clinical glyco(proteo)mics in precision medicine

Glycoproteomics reveals site-specific O- and N-glycosylation that may influence protein properties including binding, activity and half-life. The increasingly mature toolbox with glycomic- and glycoproteomic strategies is applied for the development of biopharmaceuticals and discovery and clinical evaluation of glycobiomarkers in various disease fields. Notwithstanding the contributions of glycoscience in identifying new drug targets, the current report is focused on the biomarker modality that is of interest for diagnostic and monitoring purposes. To this end it is noted that the identification of biomarkers has received more attention than corresponding quantification. Most analytical methods are very efficient in detecting large numbers of analytes but developments to accurately quantify these have so far been limited. In this perspective a parallel is made with earlier proposed tiers for protein quantification using mass spectrometry. Moreover, the foreseen reporting of multimarker readouts is discussed to describe an individual's health or disease state and their role in clinical decision-making. The potential of longitudinal sampling and monitoring of glycomic features for diagnosis and treatment monitoring is emphasized. Finally, different strategies that address quantification of a multimarker panel will be discussed.

The hidden potential of glycomarkers: Glycosylation studies in the service of cancer diagnosis and treatment

Changes in the glycosylation process appear early in carcinogenesis and evolve with the growth and spread of cancer. The correlation of the characteristic glycosylation signature with the tumor stage and the appropriate therapy choice is an important issue in translational medicine. Oncologists also pay attention to extracellular vesicles as reservoirs of new cancer glycomarkers that can be potent for cancer diagnosis/prognosis. In this review, we recall glycomarkers used in oncology and show their new glycoforms of improved clinical relevance. We summarize current knowledge on the biological functions of glycoepitopes in cancer-derived extracellular vesicles and their potential use in clinical practice. Is glycomics a future of cancer diagnosis? It may be, but in combination with other omics analyses than alone.

Comprehensive characterization of complex glycosphingolipids in human pancreatic cancer tissues

Pancreatic ductal adenocarcinoma (PDAC) is one of the most common causes of cancer-related deaths worldwide, accounting for 90% of primary pancreatic tumors with an average 5-year survival rate of less than 10%. PDAC exhibits aggressive biology, which, together with late detection, results in most PDAC patients presenting with unresectable, locally advanced, or metastatic disease. In-depth lipid profiling and screening of potential biomarkers currently appear to be a promising approach for early detection of PDAC or other cancers. Here, we isolated and characterized complex glycosphingolipids (GSL) from normal and tumor pancreatic tissues of patients with PDAC using a combination of TLC, chemical staining, carbohydrate-recognized ligand-binding assay, and LC/ESI-MS². The major neutral GSL identified were GSL with the terminal blood groups A, B, H, Le^a, Le^b, Le^x, Le^y, P1, and PX2 determinants together with globo- (Gb₃ and Gb₄) and neolacto-series GSL (nLc₄ and nLc₆). We also revealed that the neutral GSL profiles and their relative amounts differ between normal and tumor tissues. Additionally, the normal and tumor pancreatic tissues differ in type 1/2 core chains. Sulfatides and GM₃ gangliosides were the predominant acidic GSL along with the minor sialyl-nLc₄/nLc₆ and sialyl-Le^a/Le^x. The comprehensive analysis of GSL in human PDAC tissues extends the GSL coverage and provides an important platform for further studies of GSL alterations; therefore, it could contribute to the development of new biomarkers and therapeutic approaches.

Screening and verification of genes related to polycystic ovary syndrome

OBJECTIVE

To identify key genes involved in occurrence and development of polycystic ovary syndrome (PCOS).

METHODS

By downloading the GSE85932 dataset from the GEO database, we used bioinformatical analysis to analyse differentially expressed genes (DEGs) from blood samples of eight women with PCOS and eight matched controls. Following bioinformatic analysis, we performed a cross-sectional study of serum samples taken from 79 women with PCOS and 36 healthy controls.

RESULTS

From the 178 DEGs identified by bioinformatical analysis, 15 genes were identified as significant, and of these, ORM1 and ORM2 were selected for further verification as potential biomarkers for PCOS. Serum ORM1 and ORM2 levels were significantly increased in women with PCOS, and had a high diagnostic value. ORM1 and ORM2 were positively correlated with testosterone, cholesterol, and triglycerides. ORM1 levels were negatively correlated with high density lipoprotein (HDL) while ORM2 levels showed no significant correlation.

CONCLUSIONS

ORM may be an effective biomarker for the diagnosis of PCOS and its monitoring may be a useful therapeutic strategy.

Construction of 2DE Patterns of Plasma Proteins: Aspect of Potential Tumor Markers

The use of tumor markers aids in the early detection of cancer recurrence and prognosis. There is a hope that they might also be useful in screening tests for the early detection of cancer. Here, the question of finding ideal tumor markers, which should be sensitive, specific, and reliable, is an acute issue. Human plasma is one of the most popular samples as it is commonly collected in the clinic and provides noninvasive, rapid analysis for any type of disease including cancer. Many efforts have been applied in searching for “ideal” tumor markers, digging very deep into plasma proteomes. The situation in this area can be improved in two ways—by attempting to find an ideal single tumor marker or by generating panels of different markers. In both cases, proteomics certainly plays a major role. There is a line of evidence that the most abundant, so-called “classical plasma proteins”, may be used to generate a tumor biomarker profile. To be comprehensive these profiles should have information not only about protein levels but also proteoform distribution for each protein. Initially, the profile of these proteins in norm should be generated. In our work, we collected bibliographic information about the connection of cancers with levels of “classical plasma proteins”. Additionally, we presented the proteoform profiles (2DE patterns) of these proteins in norm generated by two-dimensional electrophoresis with mass spectrometry and immunodetection. As a next step, similar profiles representing protein perturbations in plasma produced in the case of different cancers will be generated. Additionally, based on this information, different test systems can be developed.

Characterization of Mesothelin Glycosylation in Pancreatic Cancer: Decreased Core Fucosylated Glycoforms in Pancreatic Cancer Patients’ Sera

Currently, there are no reliable biomarkers for the diagnosis of pancreatic cancer (PaC). Glycoproteomic approaches that analyze the glycan determinants on specific glycoproteins have proven useful to develop more specific cancer biomarkers than the corresponding protein levels. In PaC, mesothelin (MSLN) is a neo-expressed glycoprotein. MSLN glycosylation has not been described and could be altered in PaC. In this work, we aimed to characterize MSLN glycans from PaC cells and serum samples to assess their potential usefulness as PaC biomarkers. First, we analyzed MSLN glycans from PaC cell lines and then we developed an enzyme-linked lectin assay to measure core fucosylated-MSLN (Cf-MSLN) glycoforms. MSLN glycans from PaC cells were analyzed by glycan sequencing and through Western blotting with lectins. All of the cell lines secreted MSLN, with its three N-glycosylation sites occupied by complex-type N-glycans, which were mainly α2,3-sialylated, core fucosylated and highly branched. The Cf-MSLN glycoforms were quantified on PaC serum samples, and compared with MSLN protein levels. The Cf-MSLN was significantly decreased in PaC patients compared to control sera, while no differences were detected by using MSLN protein levels. In conclusion, Cf-MSLN glycoforms were differently expressed in PaC, which opens the way to further investigate their usefulness as PaC biomarkers.

Longitudinal changes of serum protein N-Glycan levels for earlier detection of pancreatic cancer in high-risk individuals

BACKGROUND

Surveillance of individuals at risk of developing pancreatic ductal adenocarcinoma (PDAC) has the potential to improve survival, yet early detection based on solely imaging modalities is challenging. We aimed to identify changes in serum glycosylation levels over time to earlier detect PDAC in high-risk individuals.

METHODS

Individuals with a hereditary predisposition to develop PDAC were followed in two surveillance programs. Those, of which at least two consecutive serum samples were available, were included. Mass spectrometry analysis was performed to determine the total N-glycome for each consecutive sample. Potentially discriminating N-glycans were selected based on our previous cross-sectional analysis and relative abundances were calculated for each glycosylation feature.

RESULTS

165 individuals ("FPC-cohort" N = 119; Leiden cohort N = 46) were included. In total, 97 (59%) individuals had a genetic predisposition (77 CDKN2A, 15 BRCA1/2, 5 STK11) and 68 (41%) a family history of PDAC without a known genetic predisposition (>10-fold increased risk of developing PDAC). From each individual, a median number of 3 serum samples (IQR 3) was collected. Ten individuals (6%) developed PDAC during 35 months of follow-up; nine (90%) of these patients carried a CDKN2A germline mutation. In PDAC cases, compared to all controls, glycosylation characteristics were increased (fucosylation, tri- and tetra-antennary structures, specific sialic linkage types), others decreased (complex-type diantennary and bisected glycans). The largest change over time was observed for tri-antennary fucosylated glycans, which were able to differentiate cases from controls with a specificity of 92%, sensitivity of 49% and accuracy of 90%.

CONCLUSION

Serum N-glycan monitoring may support early detection in a pancreas surveillance program.

Application of Proteomics in Pancreatic Ductal Adenocarcinoma Biomarker Investigations: A Review

Pancreatic ductal adenocarcinoma (PDAC), a highly aggressive malignancy with a poor prognosis is usually detected at the advanced stage of the disease. The only US Food and Drug Administration-approved biomarker that is available for PDAC, CA 19-9, is most useful in monitoring treatment response among PDAC patients rather than for early detection. Moreover, when CA 19-9 is solely used for diagnostic purposes, it has only a recorded sensitivity of 79% and specificity of 82% in symptomatic individuals. Therefore, there is an urgent need to identify reliable biomarkers for diagnosis (specifically for the early diagnosis), ascertain prognosis as well as to monitor treatment response and tumour recurrence of PDAC. In recent years, proteomic technologies are growing exponentially at an accelerated rate for a wide range of applications in cancer research. In this review, we discussed the current status of biomarker research for PDAC using various proteomic technologies. This review will explore the potential perspective for understanding and identifying the unique alterations in protein expressions that could prove beneficial in discovering new robust biomarkers to detect PDAC at an early stage, ascertain prognosis of patients with the disease in addition to monitoring treatment response and tumour recurrence of patients.

Recent Advances in Mass Spectrometry-Based Glycomic and Glycoproteomic Studies of Pancreatic Diseases

Modification of proteins by glycans plays a crucial role in mediating biological functions in both healthy and diseased states. Mass spectrometry (MS) has emerged as the most powerful tool for glycomic and glycoproteomic analyses advancing knowledge of many diseases. Such diseases include those of the pancreas which affect millions of people each year. In this review, recent advances in pancreatic disease research facilitated by MS-based glycomic and glycoproteomic studies will be examined with a focus on diabetes and pancreatic cancer. The last decade, and especially the last five years, has witnessed developments in both discovering new glycan or glycoprotein biomarkers and analyzing the links between glycans and disease pathology through MS-based studies. The strength of MS lies in the specificity and sensitivity of liquid chromatography-electrospray ionization MS for measuring a wide range of biomolecules from limited sample amounts from many sample types, greatly enhancing and accelerating the biomarker discovery process. Furthermore, imaging MS of glycans enabled by matrix-assisted laser desorption/ionization has proven useful in complementing histology and immunohistochemistry to monitor pancreatic disease progression. Advances in biological understanding and analytical techniques, as well as challenges and future directions for the field, will be discussed.

Glycoprotein analysis using lectin microcolumns and capillary electrophoresis: Characterization of alpha1-acid glycoprotein by combined separation methods

Separations based on combinations of 2.1 mm I.D. high-performance affinity microcolumns and capillary electrophoresis were developed and used to characterize the glycoforms of an intact glycoprotein. Human alpha₁-acid glycoprotein (AGP) was used as a model analyte due to its heterogeneous glycosylation resulting from variations in its degree of branching, fucosylation, and number of sialic acids. Three separation formats were examined based on microcolumns that contained the lectins concanavalin A (Con A) or Aleuria aurantia lectin (AAL). These microcolumns were used with one another or in combination with capillary electrophoresis. N-Glycan analysis of the non-retained and retained AGP fractions was carried out by using PNGase F digestion and nanoflow electrospray ionization mass spectrometry. Con A microcolumns were found to selectively enrich AGP that contained bi-antennary N-glycans, while AAL microcolumns retained AGP with fucose-containing N-glycans. Results from these separation methods indicated that fucosylation of the N-linked glycans was more abundant when a high degree of branching was present in AGP. Sialic acid residues were more abundant when higher degrees of branching and more fucose residues were present in AGP. The separation and analysis methods that were developed could be used with relatively small amounts of AGP and can be adapted for use with other intact glycoproteins.

Current State of "Omics" Biomarkers in Pancreatic Cancer

Pancreatic cancer is one of the most fatal malignancies and the seventh leading cause of cancer-related deaths related to late diagnosis, poor survival rates, and high incidence of metastasis. Unfortunately, pancreatic cancer is predicted to become the third leading cause of cancer deaths in the future. Therefore, diagnosis at the early stages of pancreatic cancer for initial diagnosis or postoperative recurrence is a great challenge, as well as predicting prognosis precisely in the context of biomarker discovery. From the personalized medicine perspective, the lack of molecular biomarkers for patient selection confines tailored therapy options, including selecting drugs and their doses or even diet. Currently, there is no standardized pancreatic cancer screening strategy using molecular biomarkers, but CA19-9 is the most well known marker for the detection of pancreatic cancer. In contrast, recent innovations in high-throughput techniques have enabled the discovery of specific biomarkers of cancers using genomics, transcriptomics, proteomics, metabolomics, glycomics, and metagenomics. Panels combining CA19-9 with other novel biomarkers from different "omics" levels might represent an ideal strategy for the early detection of pancreatic cancer. The systems biology approach may shed a light on biomarker identification of pancreatic cancer by integrating multi-omics approaches. In this review, we provide background information on the current state of pancreatic cancer biomarkers from multi-omics stages. Furthermore, we conclude this review on how multi-omics data may reveal new biomarkers to be used for personalized medicine in the future.

High-Throughput and Site-Specific N-Glycosylation Analysis of Human Alpha-1-Acid Glycoprotein Offers a Great Potential for New Biomarker Discovery

Alpha-1-acid glycoprotein (AGP) is an acute phase glycoprotein in blood, which is primarily synthetized in the liver and whose biological role is not completely understood. It consists of 45% carbohydrates that are present in the form of five N-linked complex glycans. AGP N-glycosylation was shown to be changed in many different diseases, and some changes appear to be disease-specific; thus, it has a great diagnostic and prognostic potential. However, AGP glycosylation was mainly analyzed in small cohorts and without detailed site-specific glycan information. Here, we developed a cost-effective method for a high-throughput and site-specific N-glycosylation LC-MS analysis of AGP which can be applied on large cohorts, aid in search for novel disease biomarkers, and enable better understanding of AGP's role and function in health and disease. The method does not require isolation of AGP with antibodies and affinity chromatography, but AGP is enriched by acid precipitation from 5 μl of bloodplasma in a 96-well format. After trypsinization, AGP glycopeptides are purified using a hydrophilic interaction chromatography-based solid-phase extraction and analyzed by reversed-phase-liquid chromatography-electrospray ionization-MS. We used our method to show for the first time that AGP N-glycan profile is stable in healthy individuals (14 individuals in three time points), which is a requirement for evaluation of its diagnostic potential. Furthermore, we tested our method on a population including individuals with registered hyperglycemia in critical illness (59 cases and 49 controls), which represents a significantly increased risk of developing type 2 diabetes. Individuals at higher risk of diabetes presented increased N-glycan branching on AGP's second glycosylation site and lower sialylation of N-glycans on AGP's third and AGP1's fourth glycosylation site. Although this should be confirmed on a larger prospective cohort, it indicates that site-specific AGP N-glycan profile could help distinguish individuals who are at risk of type 2 diabetes.

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.

Serum Levels and Glycosylation Changes of Alpha-1-Acid Glycoprotein According to Severity of Breast Cancer in Korean Women

Elevated serum levels of alpha-1-acid glycoprotein (AGP) are known to be associated with several types of cancer. In addition, some reports have indicated that changes in glycosylation of AGP are associated with cancer progression. However, changes in AGP levels of serum and changes in glycosylation of AGPs in breast cancer have not been specifically studied. In the present study, serum AGP levels in benign (BN) cancer and breast cancer stage I (BC I), BC IIA, BC IIB, and BC III in Korean women were measured using an enzyme-linked immunosorbent assay (ELISA). AGP was purified from individual sera by hot phenol extraction and then subjected to AGP glycosylation analysis. Three types of AGP glycosylation (fucosylation, high-mannose-type and sialylation) were detected using enzyme-linked lectin assays (ELLAs). Serum AGP levels were higher in BC I, BC IIA, BC IIB, and BC III, than in the BN group, and the level in BC I and BC IIA was high enough to be distinguished from BN. Meanwhile, terminal fucosylation and high-mannose-type glycans appeared to be lowest in BC I. The glycosylation levels of BC I provide sensitivity and specificity that make BC I clearly distinguishable from BC IIA, BC IIB, and BC III as well as BN. Therefore, determination of serum AGP or AGP glycosylation level could be useful for detecting the early stages of breast cancer.

Serum N-Glycome analysis reveals pancreatic cancer disease signatures

Background &Aims

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive cancer type with loco‐regional spread that makes the tumor surgically unresectable. Novel diagnostic tools are needed to improve detection of PDAC and increase patient survival. In this study we explore serum protein N‐glycan profiles from PDAC patients with regard to their applicability to serve as a disease biomarker panel.

Methods

Total serum N‐glycome analysis was applied to a discovery set (86 PDAC cases/84 controls) followed by independent validation (26 cases/26 controls) using in‐house collected serum specimens. Protein N‐glycan profiles were obtained using ultrahigh resolution mass spectrometry and included linkage‐specific sialic acid information. N‐glycans were relatively quantified and case‐control classification performance was evaluated based on glycosylation traits such as branching, fucosylation, and sialylation.

Results

In PDAC patients a higher level of branching (OR 6.19, P‐value 9.21 × 10⁻¹¹) and (antenna)fucosylation (OR 13.27, P‐value 2.31 × 10⁻⁹) of N‐glycans was found. Furthermore, the ratio of α2,6‐ vs α2,3‐linked sialylation was higher in patients compared to healthy controls. A classification model built with three glycosylation traits was used for discovery (AUC 0.88) and independent validation (AUC 0.81), with sensitivity and specificity values of 0.85 and 0.71 for the discovery set and 0.75 and 0.72 for the validation set.

Conclusion

Serum N‐glycome analysis revealed glycosylation differences that allow classification of PDAC patients from healthy controls. It was demonstrated that glycosylation traits rather than single N‐glycan structures obtained in this clinical glycomics study can serve as a basis for further development of a blood‐based diagnostic test.

Proteomic analysis of pancreatic ductal adenocarcinoma

INTRODUCTION

Pancreatic ductal adenocarcinoma (PDAC), which represents approximately 80% of all pancreatic cancers, is a highly aggressive malignant disease and one of the most lethal among all cancers. Overall, the 5-year survival rate among all pancreatic cancer patients is less than 9%; these rates have shown little change over the past 30 years. A more comprehensive understanding of the molecular mechanisms underlying this complex disease is crucial to the development of new diagnostic tools for early detection and disease monitoring, as well as to identify new and more effective therapeutics to improve patient outcomes.

AREA COVERED

We summarize recent advances in proteomic strategies and mass spectrometry to identify new biomarkers for early detection and monitoring of disease progression, predict response to therapy, and to identify novel proteins that have the potential to be 'druggable' therapeutic targets. An overview of proteomic studies that have been conducted to further our mechanistic understanding of metastasis and chemotherapy resistance in PDAC disease progression will also be discussed.

EXPERT COMMENTARY

The results from these PDAC proteomic studies on a variety of PDAC sample types (e.g., blood, tissue, cell lines, exosomes, etc.) provide great promise of having a significant clinical impact and improving patient outcomes.

Isomeric Separation of N-Glycopeptides Derived from Glycoproteins by Porous Graphitic Carbon (PGC) LC-MS/MS

Protein glycosylation is involved in many biological processes and physiological functions. Despite the recent advances in LC-MS/MS methodologies, the profiling of site-specific glycosylation is one of the major analytical challenges of glycoprotein analysis. Herein, we report that the separation of glycopeptide isomers on porous graphitic carbon (PGC)-LC was significantly improved by elevating the separation temperature under basic mobile phases. These findings permitted the isomeric separation of glycopeptides resulting from highly specific enzymatic digestions. The selectivity for different glycan types was studied using bovine fetuin, asialofetuin, IgG, ribonuclease B, and alpha-1 acid glycoprotein (AGP) by PGC-LC-MS. Comprehensive structural isomeric separation of glycopeptides was observed by high-resolution MS and confirmed by MS/MS. The specific structures of the glycopeptide isomers were identified and confirmed through exoglycosidase digestions. Glycosylation analysis of human AGP revealed the potential use of PGC-LC-MS for extensive glycoprotein analysis for biomarker discovery. This newly developed separation technique was shown as a reproducible and useful analytical method to study site-specific isomeric glycosylation.

Differential O- and Glycosphingolipid Glycosylation in Human Pancreatic Adenocarcinoma Cells With Opposite Morphology and Metastatic Behavior

Changes in the glycosylation profile of cancer cells have been strongly associated with cancer progression. To increase our insights into the role of glycosylation in human pancreatic ductal adenocarcinoma (PDAC), we performed a study on O-glycans and glycosphingolipid (GSL) glycans of the PDAC cell lines Pa-Tu-8988T (PaTu-T) and Pa-Tu-8988S (PaTu-S). These cell lines are derived from the same patient, but show an almost opposite phenotype, morphology and capacity to metastasize, and may thus provide an attractive model to study the role of glycosylation in progression of PDAC. Gene-array analysis revealed that 24% of the glycosylation-related genes showed a ≥ 1.5-fold difference in expression level between the two cell lines. Subsequent validation of the data by porous graphitized carbon nano-liquid chromatography coupled to a tandem ion trap mass spectrometry and flow cytometry established major differences in O-glycans and GSL-glycans between the cell lines, including lower levels of T and sialylated Tn (sTn) antigens, neoexpression of globosides (Gb3 and Gb4), and higher levels of gangliosides in the mesenchymal-like PaTu-T cells compared to the epithelial-like PaTu-S. In addition, PaTu-S cells demonstrated a significantly higher binding of the immune-lectins macrophage galactose-type lectin and galectin-4 compared to PaTu-T. In summary, our data provide a comprehensive and differential glycan profile of two PDAC cell lines with disparate phenotypes and metastatic behavior. This will allow approaches to modulate and monitor the glycosylation of these PDAC cell lines, which opens up avenues to study the biology and metastatic behavior of PDAC.

Urine α-fetoprotein and orosomucoid 1 as biomarkers of hepatitis B virus-associated hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the sixth common malignant tumor worldwide, but current efficient and convenient screening methods remain lacking. This study aimed to discover a diagnostic or a screening biomarker from the urine of hepatitis B virus (HBV)-related HCC patients. We used iTRAQ coupled with mass spectrometry to identify candidate urinary proteins in a discovery cohort (n = 40). The selected proteins were confirmed using ELISA in a validation cohort (n = 140). Diagnostic performance of the selected proteins was assessed using receiver operating characteristic (ROC) and qualitative diagnostic analysis. A total of 96 differentially expressed proteins were identified. Urinary α-fetoprotein (u-AFP) and orosomucoid 1 (u-ORM1) were selected as target proteins by bioinformatics analysis and were significantly higher in HCC than in non-HCC patients, as validated by Western blot analysis and ELISA. u-AFP had a strong correlation with serum AFP-L3 (Pearson's r = 0.944, P < 0.0001), indicating that u-AFP may be derived from circulating blood. The area under the curve (AUC) of u-AFP was 0.795 with a sensitivity of 62.5% and a specificity of 95.4%, which showed no significantly difference with serum AFP (se-AFP). The AUC was 0.864 as u-AFP and u-ORM1 were combined, and they performed much better than u-AFP or u-ORM1 alone. Qualitative diagnostic analysis showed that the positive predictive value of u-AFP was 90.1% and the diagnostic sensitivity of parallel combination of u-AFP and u-ORM1 was 85.1%. Taken together, AFP and ORM1 in the urine may be used as a diagnostic or screening biomarker of HCC, and studies on large samples are needed to validate the result.NEW & NOTEWORTHY This study provides a novel way to find biomarkers of hepatocellular carcinoma (HCC) and a new perspective of α-fetoprotein clinical application. The urine reagent strips may be helpful in high epidemic areas of HCC and in low-resource settings.

Machine Learning Classifies Core and Outer Fucosylation of N-Glycoproteins Using Mass Spectrometry

Protein glycosylation is known to be involved in biological progresses such as cell recognition, growth, differentiation, and apoptosis. Fucosylation of glycoproteins plays an important role for structural stability and function of N-linked glycoproteins. Although many of biological and clinical studies of protein fucosylation by fucosyltransferases has been reported, structural classification of fucosylated N-glycoproteins such as core or outer isoforms remains a challenge. Here, we report for the first time the classification of N-glycopeptides as core- and outer-fucosylated types using tandem mass spectrometry (MS/MS) and machine learning algorithms such as the deep neural network (DNN) and support vector machine (SVM). Training and test sets of more than 800 MS/MS spectra of N-glycopeptides from the immunoglobulin gamma and alpha 1-acid-glycoprotein standards were selected for classification of the fucosylation types using supervised learning models. The best-performing model had an accuracy of more than 99% against manual characterization and area under the curve values greater than 0.99, which were calculated by probability scores from target and decoy datasets. Finally, this model was applied to classify fucosylated N-glycoproteins from human plasma. A total of 82N-glycopeptides, with 54 core-, 24 outer-, and 4 dual-fucosylation types derived from 54 glycoproteins, were commonly classified as the same type in both the DNN and SVM. Specifically, outer fucosylation was dominant in tri- and tetra-antennary N-glycopeptides, while core fucosylation was dominant in the mono-, bi-antennary and hybrid types of N-glycoproteins in human plasma. Thus, the machine learning methods can be combined with MS/MS to distinguish between different isoforms of fucosylated N-glycopeptides.

Aberrant glycosylation and cancer biomarker discovery: a promising and thorny journey

Glycosylation is among the most important post-translational modifications for proteins and is of intrinsic complex character compared with DNAs and naked proteins. Indeed, over 50%-70% of proteins in circulation are glycosylated, and the "sweet attachments" have versatile structural and functional implications. Both the configuration and composition of the attached glycans affect the biological activities of consensus proteins significantly. Glycosylation is generated by complex biosynthetic pathways comprising hundreds of glycosyltransferases, glycosidases, transcriptional factors, transporters and the protein backbone. In addition, lack of direct genetic templates and glyco-specific antibodies such as those commonly used in DNA amplification and protein capture makes research on glycans and glycoproteins even more difficult, thus resulting in sparse knowledge on the pathophysiological implications of glycosylation. Fortunately, cutting-edge technologies have afforded new opportunities and approaches for investigating cancer-related glycosylation. Thus, glycans as well as aberrantly glycosylated protein-based cancer biomarkers have been increasingly recognized. This mini-review highlights the most recent developments in glyco-biomarker studies in an effort to discover clinically relevant cancer biomarkers using advanced analytical methodologies such as mass spectrometry, high-performance liquid chromatographic/ultra-performance liquid chromatography, capillary electrophoresis, and lectin-based technologies. Recent clinical-centered glycobiological studies focused on determining the regulatory mechanisms and the relation with diagnostics, prognostics and even therapeutics are also summarized. These studies indicate that glycomics is a treasure waiting to be mined where the growth of cancer-related glycomics and glycoproteomics is the next great challenge after genomics and proteomics.

Alpha-1-acid glycoprotein 1 is upregulated in pancreatic ductal adenocarcinoma and confers a poor prognosis

Pancreatic cancer is an aggressive malignancy that carries a high mortality rate. A major contributor to the poor outcome is the lack of effective molecular markers. The purpose of this study was to develop protein markers for improved prognostication and noninvasive diagnosis. A mass spectrometry (MS)-based discovery approach was applied to pancreatic cancer tissues and healthy pancreas. In the verification phase, extracellular proteins with differential expression were further quantified in targeted mode using parallel reaction monitoring (PRM). Next, a tissue microarray (TMA) cohort including 140 pancreatic cancer resection specimens was constructed, in order to validate protein expression status and investigate potential prognostic implications. The levels of protein candidates were finally assessed in a prospective series of 110 serum samples in an accredited clinical laboratory using the automated Cobas system. Protein sequencing with nanoliquid chromatography tandem MS (nano-LC-MS/MS) and targeted PRM identified alpha-1-acid glycoprotein 1 (AGP1) as an upregulated protein in pancreatic cancer tissue. Using TMA and immunohistochemistry, AGP1 expression was significantly associated with shorter overall survival (HR = 2.22; 95% CI 1.30-3.79, P =  0.004). Multivariable analysis confirmed the results (HR = 1.87; 95% CI 1.08-3.24, P  =  0.026). Circulating levels of AGP1 yielded an area under the curve (AUC) of 0.837 for the discrimination of resectable pancreatic cancer from healthy controls. Combining AGP1 with CA 19-9 enhanced the diagnostic performance, with an AUC of 0.963. This study suggests that AGP1 is a novel prognostic biomarker in pancreatic cancer tissue. Serum AGP1 levels may be useful as part of a biomarker panel for early detection of pancreatic cancer but further studies are needed.

Identification of bifucosylated glycoforms using low-energy CID spectra

We have used tandem mass spectrometry (MS/MS)-based analysis of glycopeptides in order to identify the composition and structure of rare glycoforms. The results illustrate utility of low-energy MS/MS for structure identification. We have shown the presence of bifucosylated and trifucosylated glycoforms in human α-1-acid glycoprotein (AGP), a major plasma glycoprotein. Fucosylation in the case of AGP always occurs on the antennae; core fucosylation was not observed.

Development and evaluation of silica-based lectin microcolumns for glycoform analysis of alpha1-acid glycoprotein

Silica-based lectin microcolumns were developed and optimized for the separation and analysis of glycoform fractions in alpha₁-acid glycoprotein (AGP) based on both the degree of branching and level of fucosylation. Concanavalin A (Con A) and Aleuria Aurantia lectin (AAL) were immobilized onto HPLC-grade silica by reductive amination and packed into 2.1 mm i.d. × 5.0 cm microcolumns. Factors examined for these microcolumns include their protein content, binding capacity, binding strength and band-broadening under isocratic conditions (Con A) or step elution conditions (AAL) and in the presence of various flow rates or temperatures. These factors were examined by using experiments based on frontal analysis, zonal elution, peak profiling and peak decay analysis. Up to 200 μg AGP could be loaded onto a Con A microcolumn and provide linear elution conditions, and 100 μg AGP could be applied to an AAL microcolumn. The final conditions for separating retained and non-retained AGP glycoform fractions on a Con A microcolumn used a flow rate of 50 μL min^-1 and a temperature of 50 °C, which gave a separation of these fractions within 20 min or less. The final conditions for an AAL microcolumn included a flow rate of 0.75 mL min^-1, a temperature of 50 °C, and the use of 2.0 mM l-fucose as a competing agent for elution, giving a separation of non-retained and retained AGP glycoforms in 6 min or less. The inter-day precisions were ±0.7-4.0% or less for the retention times of the AGP glycoforms and ±2.2-3.0% or less for their peak areas.

Multivariate data analysis for the detection of human alpha-acid glycoprotein aberrant glycosylation in pancreatic ductal adenocarcinoma

Relative quantification of human alpha-acid glycoprotein (hAGP) glycan isomers using [12C6]/[13C6]-aniline in combination with multivariate data analysis is proposed as an efficient method for the identification of pancreatic ductal adenocarcinoma (PDAC) glycan biomarkers in serum samples. Intact and desialylated glycans from hAGP, purified from serum samples of patients with PDAC and chronic pancreatitis (ChrP), were labeled with aniline and analyzed by μZIC-HILIC-MS. Afterwards, partial least squares discriminant analysis (PLS-DA) was applied to the relative areas obtained for all glycan isomers in the different samples: pathological (ChrP or PDAC) versus healthy samples. Seven intact glycan isomers with α2-6 linked sialic acids, five of them also fucosylated, were the most meaningful to distinguish between PDAC and ChrP patients. The desialylated glycan isomers also identified by PLS-DA as potential biomarker candidates confirmed that antenna but also core fucosylation could be involved in PDAC. The analysis of intact and desialylated glycan isomers in combination with the multivariate data analysis revealed that the triantennary glycan with two fucoses of hAGP could have in the future a relevant role in the differentiation of patients with PDAC from those with ChrP. SIGNIFICANCE: Multivariate data analysis is currently being used in many omics fields for biomarker discovery. However, to date, no glycomics studies have applied chemometric tools combined with mass spectrometry in a preclinical research. In this work, this methodology has been used to identify altered glycosylation of human alpha-acid glycoprotein in pancreatic ductal adenocarcinoma (PDAC). The obtained results reveal that the triantennary glycan with two fucoses could have a great biomarker potential as it was relevant to differentiate PDAC and chronic pancreatitis (ChrP) patients.

Fucosylation in cancer biology and its clinical applications

Fucosylation is the process of transferring fucose from GDP-fucose to their substrates, which includes certain proteins, N- and O-linked glycans in glycoprotein or glycolipids, by fucosyltransferases in all mammalian cells. Fucosylated glycans play vital role in selectin-mediated leukocyte extravasation, lymphocyte homing, and pathogen-host interactions, whereas fucosylated proteins are essential for signaling transduction in numerous ontogenic events. Aberrant fucosylation due to the availability of high energy donor GDP-fucose, abnormal expression of FUTs and/or α-fucosidase, and the availability of their substrates leads to different fucosylated glycan or protein structures. Accumulating evidence demonstrates that aberrant fucosylation plays important role in all aspects of cancer biology. In this review, we will summarize the current knowledge about fucosylation in different physiological and pathological processes with a focus on their roles not only in cancer cell proliferation, invasion, and metastasis but also in tumor immune surveillance. Furthermore, the clinical potential and applications of fucosylation in cancer diagnosis and treatment will also be discussed.

Microchip gel electrophoretic analysis of perchloric acid-soluble serum proteins in systemic inflammatory disorders

Perchloric acid (PCA) precipitation is a well-known method for the separation of heavily glycosylated proteins and for reducing the masking effect of major serum proteins. The aim of this study is to characterize PCA-soluble serum proteins in healthy individuals and in patients with systemic inflammatory diseases, such as Crohn's disease and sepsis. A PCA precipitation protocol was prepared and adapted to the analytical methods. After PCA treatment of the serum, the soluble proteins in the supernatant were analyzed by SDS-PAGE and by microchip gel electrophoresis (MGE). Characteristic changes of the electrophoretic patterns of the PCA-soluble fractions were observed. Four characteristic bands (at ∼11, ∼65, ∼85, and ∼120 kDa) with varying intensity were detected by MGE. The proportion of the ∼65, ∼85, and ∼120 kDa bands were significantly higher in systemic inflammatory conditions than in healthy individuals (p < 0.001), and characteristic patterns were observed in patients with acute inflammation. The marked differences in the acid-soluble protein patterns, which were observed in patients with ongoing systemic inflammation, might be a good indicator of inflammation. The MGE analysis is a fast screening and quantification method for the detection of characteristic changes among acid-soluble serum proteins.

Capillary Electrophoresis Separations of Glycans

Capillary electrophoresis has emerged as a powerful approach for carbohydrate analyses since 2014. The method provides high resolution capable of separating carbohydrates by charge-to-size ratio. Principle applications are heavily focused on N-glycans, which are highly relevant to biological therapeutics and biomarker research. Advances in techniques used for N-glycan structural identification include migration time indexing and exoglycosidase and lectin profiling, as well as mass spectrometry. Capillary electrophoresis methods have been developed that are capable of separating glycans with the same monosaccharide sequence but different positional isomers, as well as determining whether monosaccharides composing a glycan are alpha or beta linked. Significant applications of capillary electrophoresis to the analyses of N-glycans in biomarker discovery and biological therapeutics are emphasized with a brief discussion included on carbohydrate analyses of glycosaminoglycans and mono-, di-, and oligosaccharides relevant to food and plant products. Innovative, emerging techniques in the field are highlighted and the future direction of the technology is projected based on the significant contributions of capillary electrophoresis to glycoscience from 2014 to the present as discussed in this review.

Glycoprotein biomarkers for the detection of pancreatic ductal adenocarcinoma

Pancreatic cancer (PaC) shows a clear tendency to increase in the next years and therefore represents an important health and social challenge. Currently, there is an important need to find biomarkers for PaC early detection because the existing ones are not useful for that purpose. Recent studies have indicated that there is a large window of time for PaC early detection, which opens the possibility to find early biomarkers that could greatly improve the dismal prognosis of this tumor. The present manuscript reviews the state of the art of the existing PaC biomarkers. It focuses on the anomalous glycosylation process and its role in PaC. Glycan structures of glycoconjugates such as glycoproteins are modified in tumors and these modifications can be detected in biological fluids of the cancer patients. Several studies have found serum glycoproteins with altered glycan chains in PaC patients, but they have not shown enough specificity for PaC. To find more specific cancer glycoproteins we propose to analyze the glycan moieties of a battery of glycoproteins that have been reported to increase in PaC tissues and that can also be found in serum. The combination of these new candidate glycoproteins with their aberrant glycosylation together with the existing biomarkers could result in a panel, which would expect to give better results as a new tool for early diagnosis of PaC and to monitor the disease.

Site-Specific Glycan Heterogeneity Characterization by Hydrophilic Interaction Liquid Chromatography Solid-Phase Extraction, Reversed-Phase Liquid Chromatography Fractionation, and Capillary Zone Electrophoresis-Electrospray Ionization-Tandem Mass Spectrometry

Reversed-phase chromatographic separation of glycopeptides tends to be dominated by the peptide composition. In contrast, capillary zone electrophoresis separation of glycopeptides is particularly sensitive to the sialic acid composition of the glycan. In this paper, we combine the two techniques to achieve superior N-glycopeptide analysis. Glycopeptides were first isolated from a tryptic digest using hydrophilic interaction liquid chromatography (HILIC) solid-phase extraction. The glycopeptides were separated using reversed-phase ultra high-performance liquid chromatography (UHPLC) to generate four fractions corresponding to different peptide backbones. Capillary zone electrophoresis-electrospray ionization-tandem mass spectrometry (CZE-ESI-MS/MS) was used to analyze the fractions. We applied this method for the analysis of alpha-1-acid glycoprotein (AGP). A total of 268 site-specific N-glycopeptides were detected, representing eight different glycosylation sites from two isomers of AGP. Glycans included tetra-sialic acids with multi N-acetyllactosamine (LacNAc) repeats and unusual pentasialylated terminal sialic acids. Reversed-phase UHPLC coupled with CZE generated ∼35% more N-glycopeptides than direct reversed-phase UHPLC-ESI-MS/MS analysis and ∼70% more N-glycopeptides than direct CZE-ESI-MS/MS analysis. This approach is a promising tool for global, site-specific glycosylation analysis of highly heterogeneous glycoproteins with mass-limited samples.

Glycoform analysis of alpha1-acid glycoprotein based on capillary electrophoresis and electrophoretic injection

A method based on capillary electrophoresis (CE) with electrophoretic injection and absorbance detection was developed for the direct analysis of AGP glycoforms in human serum. Electrophoretic injection of AGP was performed in the reversed-polarity mode of CE with a capillary coated with poly(ethylene oxide) and that had minimal electroosmotic flow. This situation created an essentially stationary interface between the sample and running buffer during injection and sample stacking. This approach allowed an 11,000-fold increase in sample loading for a 5min injection versus hydrodynamic injection and without introducing any significant levels of extra band-broadening. This method was used with sample pretreatment methods based on acid precipitation and desalting to examine AGP glycoforms in only 65μL of serum. A limit of detection of 2.1-11.3nM was obtained for the major AGP glycoform bands in serum, and the sample pretreatment method gave a recovery of 72.3-80.9% for these glycoforms. The precision for the migration times was ±0.08-0.13% and the precision for the peak areas was ±0.34-1.18% when using serum samples and an internal standard. This method was used for both normal pooled serum and serum from individuals with systemic lupus erythematosus. Results were obtained in a separation time of 25min and allowed the comparison of up to eleven glycoform bands in these samples. A similar approach may be useful in examining additional glycoproteins in serum or other types of biological samples.

Zwitterionic-hydrophilic interaction capillary liquid chromatography coupled to tandem mass spectrometry for the characterization of human alpha-acid-glycoprotein N-glycan isomers

In this work, a μZIC-HILIC-MS/MS methodology was established in negative ion mode for the characterization of glycan isomers. The possibility to separate the glycan isomers by the μZIC-HILIC strategy coupled to a high resolution tandem mass spectrometry detection permitted us to obtain valuable information about each glycan structure. The most important diagnostic ion fragments previously described to characterize structural features of glycans, were evaluated in this study using hAGP as model glycoprotein. The assignation of hAGP glycan isomers performed in our previous work using the GRIL strategy in combination with exoglycosidase digestion [1] was used in this paper to confirm or discard some ion fragments reported in the literature and delve into the structural characterization of glycan isomers. Sialic acid as well as fucose linkage-type glycan isomers were assigned using this approach and daughter ions with higher diagnostic value were determined. The location of α2-3/α2-6 sialic acids on antennas and a deeper characterization of several highly sialylated tri- and tetraantennary glycans was also possible using the established MS/MS method. Moreover, relying on the characterization performed in Ref. [1], core and antenna fucosylation were differentiated in this work using specific ion fragments obtained in the tandem mass spectra. This methodology was also applied to hAGP purified from control and pathological serum samples, which corroborated its robustness and its potential for finding novel glycan-based biomarkers in patho-glycomic studies.

Glycosylation Changes in Serum Proteins Identify Patients with Pancreatic Cancer

After more than a decade of biomarker discovery using advanced proteomic and genomic approaches, very few biomarkers have been involved in clinical diagnostics. Most candidate biomarkers are focused on the protein component. Targeting post-translational modifications (PTMs) in combination with protein sequences will provide superior diagnostic information with regards to sensitivity and specificity. Glycosylation is one of the most common and functionally important PTMs. It plays a central role in many biological processes, including protein folding, host-pathogen interactions, immune response, and inflammation. Cancer-associated aberrant glycosylation has been identified in various types of cancer. Expression of cancer-specific glycan epitopes represents an excellent opportunity for diagnostics and potentially specific detection of tumors. Here, we report four proteins (LIFR, CE350, VP13A, HPT) found in sera from pancreatic cancer patients carrying aberrant glycan structures as compared to those of controls.

Selectin Ligands Sialyl-Lewis a and Sialyl-Lewis x in Gastrointestinal Cancers

The tetrasaccharide structures Siaα2,3Galβ1,3(Fucα1,4)GlcNAc and Siaα2,3Galβ1,4(Fucα1,3)GlcNAc constitute the epitopes of the carbohydrate antigens sialyl-Lewis a (sLe^a) and sialyl-Lewis x (sLe^x), respectively, and are the minimal requirement for selectin binding to their counter-receptors. Interaction of sLe^x expressed on the cell surface of leucocytes with E-selectin on endothelial cells allows their arrest and promotes their extravasation. Similarly, the rolling of cancer cells ectopically expressing the selectin ligands on endothelial cells is potentially a crucial step favoring the metastatic process. In this review, we focus on the biosynthetic steps giving rise to selectin ligand expression in cell lines and native tissues of gastrointestinal origin, trying to understand whether and how they are deregulated in cancer. We also discuss the use of such molecules in the diagnosis of gastrointestinal cancers, particularly in light of recent data questioning the ability of colon cancers to express sLe^a and the possible use of circulating sLe^x in the early detection of pancreatic cancer. Finally, we reviewed the data dealing with the mechanisms that link selectin ligand expression in gastrointestinal cells to cancer malignancy. This promising research field seems to require additional data on native patient tissues to reach more definitive conclusions.

Alteration of N-glycan expression profile and glycan pattern of glycoproteins in human hepatoma cells after HCV infection

BACKGROUND

Hepatitis C virus (HCV) infection causes chronic liver diseases, liver fibrosis and even hepatocellular carcinoma (HCC). However little is known about any information of N-glycan pattern in human liver cell after HCV infection.

METHODS

The altered profiles of N-glycans in HCV-infected Huh7.5.1 cell were analyzed by using mass spectrometry. Then, lectin microarray, lectin pull-down assay, reverse transcription-quantitative real time PCR (RT-qPCR) and western-blotting were used to identify the altered N-glycosylated proteins and glycosyltransferases.

RESULTS

Compared to uninfected cells, significantly elevated levels of fucosylated, sialylated and complex N-glycans were found in HCV infected cells. Furthermore, Lens culinaris agglutinin (LCA)-binding glycoconjugates were increased most. Then, the LCA-agarose was used to precipitate the specific glycosylated proteins and identify that fucosylated modified annexin A2 (ANXA2) and heat shock protein 90 beta family member 1 (HSP90B1) was greatly increased in HCV-infected cells. However, the total ANXA2 and HSP90B1 protein levels remained unchanged. Additionally, we screened the mRNA expressions of 47 types of different glycosyltransferases and found that α1,6-fucosyltransferase 8 (FUT8) was the most up-regulated and contributed to strengthen the LCA binding capability to fucosylated modified ANXA2 and HSP90B1 after HCV infection.

CONCLUSIONS

HCV infection caused the altered N-glycans profiles, increased expressions of FUT8, fucosylated ANXA2 and HSP90B1 as well as enhanced LCA binding to Huh7.5.1.

GENERAL SIGNIFICANCE

Our results may lay the foundation for clarifying the role of N-glycans and facilitate the development of novel diagnostic biomarkers and therapeutic targets based on the increased FUT8, fucosylated ANXA2 and HSP90B1 after HCV infection.

Glycomic Approaches for the Discovery of Targets in Gastrointestinal Cancer

Gastrointestinal (GI) cancer is the most common group of malignancies and many of its types are among the most deadly. Various glycoconjugates have been used in clinical practice as serum biomarker for several GI tumors, however, with limited diagnose application. Despite the good accessibility by endoscopy of many GI organs, the lack of reliable serum biomarkers often leads to late diagnosis of malignancy and consequently low 5-year survival rates. Recent advances in analytical techniques have provided novel glycoproteomic and glycomic data and generated functional information and putative biomarker targets in oncology. Glycosylation alterations have been demonstrated in a series of glycoconjugates (glycoproteins, proteoglycans, and glycosphingolipids) that are involved in cancer cell adhesion, signaling, invasion, and metastasis formation. In this review, we present an overview on the major glycosylation alterations in GI cancer and the current serological biomarkers used in the clinical oncology setting. We further describe recent glycomic studies in GI cancer, namely gastric, colorectal, and pancreatic cancer. Moreover, we discuss the role of glycosylation as a modulator of the function of several key players in cancer cell biology. Finally, we address several state-of-the-art techniques currently applied in this field, such as glycomic and glycoproteomic analyses, the application of glycoengineered cell line models, microarray and proximity ligation assay, and imaging mass spectrometry, and provide an outlook to future perspectives and clinical applications.