Serum N-Glycome analysis reveals pancreatic cancer disease signatures

Aspects and outcomes of surveillance for individuals at high-risk of pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is a leading cause of cancer-related deaths and is associated with a poor prognosis. The majority of these cancers are detected at a late stage, contributing to the bad prognosis. This underscores the need for novel, enhanced early detection strategies to improve the outcomes. While population-based screening is not recommended due to the relatively low incidence of PDAC, surveillance is recommended for individuals at high risk for PDAC due to their increased incidence of the disease. However, the outcomes of pancreatic cancer surveillance in high-risk individuals are not sorted out yet. In this review, we will address the identification of individuals at high risk for PDAC, discuss the objectives and targets of surveillance, outline how surveillance programs are organized, summarize the outcomes of high-risk individuals undergoing pancreatic cancer surveillance, and conclude with a future perspective on pancreatic cancer surveillance and novel developments.

Medical Relevance, State-of-the-Art and Perspectives of "Sweet Metacode" in Liquid Biopsy Approaches

This review briefly introduces readers to an area where glycomics meets modern oncodiagnostics with a focus on the analysis of sialic acid (Neu5Ac)-terminated structures. We present the biochemical perspective of aberrant sialylation during tumourigenesis and its significance, as well as an analytical perspective on the detection of these structures using different approaches for diagnostic and therapeutic purposes. We also provide a comparison to other established liquid biopsy approaches, and we mathematically define an early-stage cancer based on the overall prognosis and effect of these approaches on the patient's quality of life. Finally, some barriers including regulations and quality of clinical validations data are discussed, and a perspective and major challenges in this area are summarised.

N-glycan biosignatures as a potential diagnostic biomarker for early-stage pancreatic cancer

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) has a poor prognosis, with a 5-year survival rate of less than 10%, owing to its late-stage diagnosis. Early detection of pancreatic cancer (PC) can significantly increase survival rates.

AIM

To identify the serum biomarker signatures associated with early-stage PDAC by serum N-glycan analysis.

METHODS

An extensive patient cohort was used to determine a biomarker signature, including patients with PDAC that was well-defined at an early stage (stages I and II). The biomarker signature was derived from a case-control study using a case-cohort design consisting of 29 patients with stage I, 22 with stage II, 4 with stage III, 16 with stage IV PDAC, and 88 controls. We used multiparametric analysis to identify early-stage PDAC N-glycan signatures and developed an N-glycan signature-based diagnosis model called the "Glyco-model".

RESULTS

The biomarker signature was created to discriminate samples derived from patients with PC from those of controls, with a receiver operating characteristic area under the curve of 0.86. In addition, the biomarker signature combined with cancer antigen 19-9 could discriminate patients with PDAC from controls, with a receiver operating characteristic area under the curve of 0.919. Glyco-model demonstrated favorable diagnostic performance in all stages of PC. The diagnostic sensitivity for stage I PDAC was 89.66%.

CONCLUSION

In a prospective validation study, this serum biomarker signature may offer a viable method for detecting early-stage PDAC.

Mass spectrometry analysis of intact protein N-glycosylation signatures of cells and sera in pancreatic adenocarcinomas

Pancreatic cancer is among the most malignant cancers, and thus early intervention is the key to better survival outcomes. However, no methods have been derived that can reliably identify early precursors of development into malignancy. Therefore, it is urgent to discover early molecular changes during pancreatic tumorigenesis. As aberrant glycosylation is closely associated with cancer progression, numerous efforts have been made to mine glycosylation changes as biomarkers for diagnosis; however, detailed glycoproteomic information, especially site-specific N-glycosylation changes in pancreatic cancer with and without drug treatment, needs to be further explored. Herein, we used comprehensive solid-phase chemoenzymatic glycoproteomics to analyze glycans, glycosites, and intact glycopeptides in pancreatic cancer cells and patient sera. The profiling of N-glycans in cancer cells revealed an increase in the secreted glycoproteins from the primary tumor of MIA PaCa-2 cells, whereas human sera, which contain many secreted glycoproteins, had significant changes of glycans at their specific glycosites. These results indicated the potential role for tumor-specific glycosylation as disease biomarkers. We also found that AMG-510, a small molecule inhibitor against Kirsten rat sarcoma viral oncogene homolog (KRAS) G12C mutation, profoundly reduced the glycosylation level in MIA PaCa-2 cells, suggesting that KRAS plays a role in the cellular glycosylation process, and thus glycosylation inhibition contributes to the anti-tumor effect of AMG-510.

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

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

Pancreatic Cancer and Detection Methods

The pancreas is a vital organ with exocrine and endocrine functions. Pancreatitis is an inflammation of the pancreas caused by alcohol consumption and gallstones. This condition can heighten the risk of pancreatic cancer (PC), a challenging disease with a high mortality rate. Genetic and epigenetic factors contribute significantly to PC development, along with other risk factors. Early detection is crucial for improving PC outcomes. Diagnostic methods, including imagining modalities and tissue biopsy, aid in the detection and analysis of PC. In contrast, liquid biopsy (LB) shows promise in early tumor detection by assessing biomarkers in bodily fluids. Understanding the function of the pancreas, associated diseases, risk factors, and available diagnostic methods is essential for effective management and early PC detection. The current clinical examination of PC is challenging due to its asymptomatic early stages and limitations of highly precise diagnostics. Screening is recommended for high-risk populations and individuals with potential benign tumors. Among various PC screening methods, the N-NOSE plus pancreas test stands out with its high AUC of 0.865. Compared to other commercial products, the N-NOSE plus pancreas test offers a cost-effective solution for early detection. However, additional diagnostic tests are required for confirmation. Further research, validation, and the development of non-invasive screening methods and standardized scoring systems are crucial to enhance PC detection and improve patient outcomes. This review outlines the context of pancreatic cancer and the challenges for early detection.

Serum N-Glycosylation RPLC-FD-MS Assay to Assess Colorectal Cancer Surgical Interventions

A newly developed analytical strategy was applied to profile the total serum N-glycome of 64 colorectal cancer (CRC) patients before and after surgical intervention. In this cohort, it was previously found that serum N-glycome alterations in CRC were associated with patient survival. Here, fluorescent labeling of serum N-glycans was applied using procainamide and followed by sialic acid derivatization specific for α2,6- and α2,3-linkage types via ethyl esterification and amidation, respectively. This strategy allowed efficient separation of specific positional isomers on reversed-phase liquid chromatography-fluorescence detection-mass spectrometry (RPLC-FD-MS) and complemented the previous glycomics data based on matrix-assisted laser desorption/ionization (MALDI)-MS that did not include such separations. The results from comparing pre-operative CRC to post-operative samples were in agreement with studies that identified a decrease in di-antennary structures with core fucosylation and an increase in sialylated tri- and tetra-antennary N-glycans in CRC patient sera. Pre-operative abundances of N-glycans showed good performance for the classification of adenocarcinoma and led to the revisit of the previous MALDI-MS dataset with regard to histological and clinical data. This strategy has the potential to monitor patient profiles before, during, and after clinical events such as treatment, therapy, or surgery and should also be further explored.

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.

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2019-2020

This review is the tenth update of the original article published in 1999 on the application of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2020. Also included are papers that describe methods appropriate to analysis by MALDI, such as sample preparation techniques, even though the ionization method is not MALDI. The review is basically divided into three sections: (1) general aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, fragmentation, quantification and the use of arrays. (2) Applications to various structural types such as oligo- and polysaccharides, glycoproteins, glycolipids, glycosides and biopharmaceuticals, and (3) other areas such as medicine, industrial processes and glycan synthesis where MALDI is extensively used. Much of the material relating to applications is presented in tabular form. The reported work shows increasing use of incorporation of new techniques such as ion mobility and the enormous impact that MALDI imaging is having. MALDI, although invented nearly 40 years ago is still an ideal technique for carbohydrate analysis and advancements in the technique and range of applications show little sign of diminishing.

Toolbox Accelerating Glycomics (TAG): Improving Large-Scale Serum Glycomics and Refinement to Identify SALSA-Modified and Rare Glycans

Glycans are involved in many fundamental cellular processes such as growth, differentiation, and morphogenesis. However, their broad structural diversity makes analysis difficult. Glycomics via mass spectrometry has focused on the composition of glycans, but informatics analysis has not kept pace with the development of instrumentation and measurement techniques. We developed Toolbox Accelerating Glycomics (TAG), in which glycans can be added manually to the glycan list that can be freely designed with labels and sialic acid modifications, and fast processing is possible. In the present work, we improved TAG for large-scale analysis such as cohort analysis of serum samples. The sialic acid linkage-specific alkylamidation (SALSA) method converts differences in linkages such as α2,3- and α2,6-linkages of sialic acids into differences in mass. Glycans modified by SALSA and several structures discovered in recent years were added to the glycan list. A routine to generate calibration curves has been implemented to explore quantitation. These improvements are based on redefinitions of residues and glycans in the TAG List to incorporate information on glycans that could not be attributed because it was not assumed in the previous version of TAG. These functions were verified through analysis of purchased sera and 74 spectra with linearity at the level of R2 > 0.8 with 81 estimated glycan structures obtained including some candidate of rare glycans such as those with the N,N’-diacetyllactosediamine structure, suggesting they can be applied to large-scale analyses.

Role of tumor cell sialylation in pancreatic cancer progression

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest malignancies and is currently the third leading cause of cancer death. The aggressiveness of PDAC stems from late diagnosis, early metastasis, and poor efficacy of current chemotherapies. Thus, there is an urgent need for effective biomarkers for early detection of PDAC and development of new therapeutic strategies. It has long been known that cellular glycosylation is dysregulated in pancreatic cancer cells, however, tumor-associated glycans and their cognate glycosylating enzymes have received insufficient attention as potential clinical targets. Aberrant glycosylation affects a broad range of pathways that underpin tumor initiation, metastatic progression, and resistance to cancer treatment. One of the prevalent alterations in the cancer glycome is an enrichment in a select group of sialylated glycans including sialylated, branched N-glycans, sialyl Lewis antigens, and sialylated forms of truncated O-glycans such as the sialyl Tn antigen. These modifications affect the activity of numerous cell surface receptors, which collectively impart malignant characteristics typified by enhanced cell proliferation, migration, invasion and apoptosis-resistance. Additionally, sialic acids on tumor cells engage inhibitory Siglec receptors on immune cells to dampen anti-tumor immunity, further promoting cancer progression. The goal of this review is to summarize the predominant changes in sialylation occurring in pancreatic cancer, the biological functions of sialylated glycoproteins in cancer pathogenesis, and the emerging strategies for targeting sialoglycans and Siglec receptors in cancer therapeutics.

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.

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.

Validation of diagnostic and predictive biomarkers for hereditary angioedema via plasma N-glycomics

BACKGROUND

Hereditary angioedema (HAE) is a rare disease with heterogeneous clinical symptoms. It is vitally important to predict whether an HAE patient will develop severe symptoms in clinical practice, but there are currently no predictive biomarkers for HAE stratification. Plasma N-glycomes are disease-specific and have great potential for the discovery of non-invasive biomarkers. In this study, we profiled the plasma N-glycome of HAE patients from two independent cohorts to identify candidate biomarkers.

METHODS

Linkage-specific sialylation derivatization combined with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry detection and automated data processing was employed to analyze the plasma N-glycome of two independent type-1 HAE cohorts.

RESULTS

HAE patients had abnormal glycan complexity, galactosylation, and α2,3- and α2,6-linked sialylation compared to healthy controls (HC). The classification models based on dysregulated glycan traits could successfully discriminate between HAE and HC with area under the curves (AUCs) being greater than 0.9. Some of the aberrant glycans showed response to therapy. Moreover, we identified a series of glycan traits with strong associations with the occurrence of laryngeal or gastrointestinal angioedema or disease severity score. Predictive models based on these traits could be used to predict disease severity (AUC > 0.9). These results were replicated in an independent cohort.

CONCLUSIONS

We reported the full plasma N-glycomic signature of HAE for the first time, and identified potential biomarkers. These findings may play a critical role in predicting disease severity and guide the treatment of HAE in clinical practice. Further protein-specific and prospective studies are needed to validate our findings.

Brilliant glycans and glycosylation: Seq and ye shall find

Proteoglycosylation is the addition of monosaccharides or glycans to the protein peptide chain. This is a common post-translational modification of proteins with a variety of biological functions. At present, more than half of all biopharmaceuticals in clinic are modified by glycosylation. Most glycoproteins are potential drug targets and biomarkers for disease diagnosis. Therefore, in-depth study of glycan structure of glycoproteins will ultimately improve the sensitivity and specificity of glycoproteins for clinical disease detection. With the deepening of research, the function and application value of glycans and glycosylation has gradually emerged. This review systematically introduces the latest research progress of glycans and glycosylation. It encompasses six cancers, four viruses, and their latest discoveries in Alzheimer's disease, allergic diseases, congenital diseases, gastrointestinal diseases, inflammation, and aging.

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.

Imidazolium labelling permits the sensitive mass-spectrometric detection of N-glycosides directly from serum

A novel imidazolium derivative (GITag) shows superior ionisation and consequently allows increased mass spectrometric detection capabilities of oligosaccharides and N-glycans. Here we demonstrate that human serum samples can be directly labelled by GITag on a MALDI target plate, abrogating prevalently required sample pretreatment or clean-up steps.

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.

Distinguishing Benign and Malignant Thyroid Nodules and Identifying Lymph Node Metastasis in Papillary Thyroid Cancer by Plasma N-Glycomics

BACKGROUND

Biomarkers are needed for patient stratification between benign thyroid nodules (BTN) and thyroid cancer (TC) and identifying metastasis in TC. Though plasma N-glycome profiling has shown potential in the discovery of biomarkers and can provide new insight into the mechanisms involved, little is known about it in TC and BTN. Besides, several studies have indicated associations between abnormal glycosylation and TC. Here, we aimed to explore plasma protein N-glycome of a TC cohort with regard to their applicability to serve as biomarkers.

METHODS

Plasma protein N-glycomes of TC, BTN, and matched healthy controls (HC) were obtained using a robust quantitative strategy based on MALDI-TOF MS and included linkage-specific sialylation information.

RESULTS

Plasma N-glycans were found to differ between BTN, TC, and HC in main glycosylation features, namely complexity, galactosylation, fucosylation, and sialylation. Four altered glycan traits, which were consecutively decreased in BTN and TC, and classification models based on them showed high potential as biomarkers for discrimination between BTN and TC ("moderately accurate" to "accurate"). Additionally, strong associations were found between plasma N-glycans and lymph node metastasis in TC, which added the accuracy of predicting metastasis before surgery to the existing method.

CONCLUSIONS

We comprehensively evaluated the plasma N-glycomic changes in patients with TC or BTN for the first time. We determined several N-glycan biomarkers, some of them have potential in the differential diagnosis of TC, and the others can help to stratify TC patients to low or high risk of lymph node metastasis. The findings enhanced the understanding of TC.

The tip of the iceberg for diagnostic dilemmas: Performance of current diagnostics and future complementary screening approaches

Genetic testing is currently the leading edge of clinical care when it comes to diagnostics. However, many questions remain unanswered even when employing next-generation sequencing techniques due to our inability to decode genetic variations and our limited repertoire of available diagnoses. Accordingly, diagnostic yields for current genomic screenings are <50% and fail to provide the whole picture, leaving the remaining patients without a definitive diagnosis. Human phenotypic/disease expression is explained by alterations not only at the genome, but also at the transcriptome, proteome and metabolome levels. These "higher" complexity levels represent at wealth of information, and diagnostic screenings tests at these levels have been shown to significantly improve diagnostic yields in specific populations compared to conventional diagnostic workup or gold standards in use (7-30% increase in diagnostic yields, depending on the population, approach and gold standard being compared against). However, these are not yet routinely available to clinicians. Due to their dynamic and modifiable nature, tapping into data from different omics will improve our understanding of the pathophysiological bases underlying (many yet to characterize) human disorders. We herein review how alterations at these levels (e.g. post-transcriptional and post-translational) may be pathogenic, how such tests may be implemented and in which situations they are of significant utility.

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.