Glycosylation profiling with mass spectrometry: method development and application to cancer biomarker studies

Biomarker molecules are analyzed in clinical tests to diagnose a disease, but often these test lack sensitivity or specificity. Also, for many diseases there is not even a blood based test available, while blood collection is relatively low invasive. For breast- and pancreatic cancer, there are several proteins that could potentially serve as biomarkers in blood, but these are not yet specific enough to use for diagnostic testing. Further research on other types of biomarkers may therefore be a valuable addition to eventually be able to develop a blood test. Methods for glycosylation profiling from serum and dried bloodspots with mass spectrometry were developed and applied to pancreatic- and breast cancer biomarker studies. Differences were found between profiles of healthy and sick persons for pancreatic cancer, but no clear differences were seen for breast cancer. This is probably due to the many different forms of breast cancer which result in different profiles. In the future, combining different types of markers from serum might ensure that differences between healthy and sick, between different diseases and between types of disease can be identified. This could lead to the development of a blood test for the early detection of cancer and other diseases.LUMC / Geneeskund

Serum Protein N-Glycosylation Changes with Rheumatoid Arthritis Disease Activity during and after Pregnancy

Proteomic

Serum N-glycan profiles differ for various breast cancer subtypes

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

Automated Plasma Glycomics with Linkage-Specific Sialic Acid Esterification and Ultrahigh Resolution MS

Surgical oncolog

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 proteinN-glycan profiles from PDAC patients with regard to their applicability to serve as a disease biomarker panel. Methods Total serumN-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. ProteinN-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 x 10(-11)) and (antenna)fucosylation (OR 13.27,P-value 2.31 x 10(-9)) ofN-glycans was found. Furthermore, the ratio of alpha 2,6- vs alpha 2,3-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 SerumN-glycome analysis revealed glycosylation differences that allow classification of PDAC patients from healthy controls. It was demonstrated that glycosylation traits rather than singleN-glycan structures obtained in this clinical glycomics study can serve as a basis for further development of a blood-based diagnostic test.Surgical oncolog

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.(c) 2022 The Authors. Published by Elsevier B.V. on behalf of IAP and EPC. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).Cellular mechanisms in basic and clinical gastroenterology and hepatolog

O- and N-glycosylation analysis of cell lines by ultrahigh resolution MALDI-FTICR-MS

Glycosylation analysis from biological samples is often challenging due to the high complexity of the glycan structures found in these samples. In the present study N- and O- glycans from human colorectal cancer cell lines and human plasma were analyzed using ultrahigh resolution MALDI-FTICR-MS. N-glycans were enzymatically released from cell lines and plasma proteins, whereas beta-elimination was used for the release of O-glycans from the cells. The purified samples were mass analyzed using a 15T MALDI-FTICR-MS system, with additional MS/MS (collision-induced dissociation) experiments for O-glycan identifications. A total of 104 O-glycan and 62 N-glycan compositions were observed in the spectra obtained from colorectal cancer cell line samples. In the cell line N-glycan spectra, the highest intensity signals originated from high-mannose glycans, next to the presence of various complex type glycans. Notably, in the O-glycan spectra mono- and disaccharide signals were observed, which are difficult to detect using alternative glycomic platforms such as porous graphitized carbon LC-MS. In the N-glycan spectra from plasma, isobaric species were resolved in MALDI-FTICR-MS spectra using absorption mode whereas these overlapped in magnitude mode. The use of ultrahigh resolution MALDI-FTICR-MS for the analysis of glycans in complex mixtures enables us to confidently analyze glycans in the matrix region of the spectrum and to differentiate isobaric glycan species. (C) 2019 The Authors. Published by Elsevier B.V.Afdeling Klinische Chemie en Laboratoriumgeneeskunde (AKCL

Dried blood spot N-glycome analysis by MALDI mass spectrometry

Surgical oncolog

Automation of High-Throughput Mass Spectrometry-Based Plasma N-Glycome Analysis with Linkage-Specific Sialic Acid Esterification

Glycosylation is a post-translational modification of key importance with heterogeneous structural characteristics. Previously, we have developed a robust, high-throughput MALDI-TOF-MS method for the comprehensive profiling of human plasma N-glycans. In this approach, sialic acid residues are derivatized with linkage-specificity, namely the ethylation of α2,6-linked sialic acid residues with parallel lactone formation of α2,3-linked sialic acids. In the current study, this procedure was used as a starting point for the automation of all steps on a liquid-handling robot system. This resulted in a time-efficient and fully standardized procedure with throughput times of 2.5 h for a first set of 96 samples and approximately 1 h extra for each additional sample plate. The mass analysis of the thus-obtained glycans was highly reproducible in terms of relative quantification, with improved interday repeatability as compared to that of manual processing

Metformin and statin use associate with plasma protein N-glycosylation in people with type 2 diabetes

INTRODUCTION: Recent studies revealed N-glycosylation signatures of type 2 diabetes, inflammation and cardiovascular risk factors. Most people with diabetes use medication to reduce cardiovascular risk. The association of these medications with the plasma N-glycome is largely unknown. We investigated the associations of metformin, statin, ACE inhibitor/angiotensin II receptor blocker (ARB), sulfonylurea (SU) derivatives and insulin use with the total plasma N-glycome in type 2 diabetes. RESEARCH DESIGN AND METHODS: After enzymatic release from glycoproteins, N-glycans were measured by matrix-assisted laser desorption/ionization mass spectrometry in the DiaGene (n=1815) and Hoorn Diabetes Care System (n=1518) cohorts. Multiple linear regression was used to investigate associations with medication, adjusted for clinical characteristics. Results were meta-analyzed and corrected for multiple comparisons. RESULTS: Metformin and statins were associated with decreased fucosylation and increased galactosylation and sialylation in glycans unrelated to immunoglobulin G. Bisection was increased within diantennary fucosylated non-sialylated glycans, but decreased within diantennary fucosylated sialylated glycans. Only few glycans were associated with ACE inhibitor/ARBs, while none associated with insulin and SU derivative use. CONCLUSIONS: We conclude that metformin and statins associate with a total plasma N-glycome signature in type 2 diabetes. Further studies are needed to determine the causality of these relations, and future N-glycomic research should consider medication a potential confounder