Apolipoprotein-CIII O-Glycosylation Is Associated with Micro- and Macrovascular Complications of Type 2 Diabetes.

Apolipoprotein-CIII (apo-CIII) inhibits the clearance of triglycerides from circulation and is associated with an increased risk of diabetes complications. It exists in four main proteoforms: O-glycosylated variants containing either zero, one, or two sialic acids and a non-glycosylated variant. O-glycosylation may affect the metabolic functions of apo-CIII. We investigated the associations of apo-CIII glycosylation in blood plasma, measured by mass spectrometry of the intact protein, and genetic variants with micro- and macrovascular complications (retinopathy, nephropathy, neuropathy, cardiovascular disease) of type 2 diabetes in a DiaGene study (n = 1571) and the Hoorn DCS cohort (n = 5409). Mono-sialylated apolipoprotein-CIII (apo-CIII1) was associated with a reduced risk of retinopathy (ß = -7.215, 95% CI -11.137 to -3.294) whereas disialylated apolipoprotein-CIII (apo-CIII2) was associated with an increased risk (ß = 5.309, 95% CI 2.279 to 8.339). A variant of the GALNT2-gene (rs4846913), previously linked to lower apo-CIII0a, was associated with a decreased prevalence of retinopathy (OR = 0.739, 95% CI 0.575 to 0.951). Higher apo-CIII1 levels were associated with neuropathy (ß = 7.706, 95% CI 2.317 to 13.095) and lower apo-CIII0a with macrovascular complications (ß = -9.195, 95% CI -15.847 to -2.543). In conclusion, apo-CIII glycosylation was associated with the prevalence of micro- and macrovascular complications of diabetes. Moreover, a variant in the GALNT2-gene was associated with apo-CIII glycosylation and retinopathy, suggesting a causal effect. The findings facilitate a molecular understanding of the pathophysiology of diabetes complications and warrant consideration of apo-CIII glycosylation as a potential target in the prevention of diabetes complications.

Autoimmune hepatitis displays distinctively high multi-antennary sialylation on plasma N-glycans compared to other liver diseases.

BACKGROUND: Changes in plasma protein glycosylation are known to functionally affect proteins and to associate with liver diseases, including cirrhosis and hepatocellular carcinoma. Autoimmune hepatitis (AIH) is a liver disease characterized by liver inflammation and raised serum levels of IgG, and is difficult to distinguish from other liver diseases. The aim of this study was to examine plasma and IgG-specific N-glycosylation in AIH and compare it with healthy controls and other liver diseases. METHODS: In this cross-sectional cohort study, total plasma N-glycosylation and IgG Fc glycosylation analysis was performed by mass spectrometry for 66 AIH patients, 60 age- and sex-matched healthy controls, 31 primary biliary cholangitis patients, 10 primary sclerosing cholangitis patients, 30 non-alcoholic fatty liver disease patients and 74 patients with viral or alcoholic hepatitis. A total of 121 glycans were quantified per individual. Associations between glycosylation traits and AIH were investigated as compared to healthy controls and other liver diseases. RESULTS: Glycan traits bisection (OR: 3.78 [1.88-9.35], p-value: 5.88 × 10- 3), tetraantennary sialylation per galactose (A4GS) (OR: 2.88 [1.75-5.16], p-value: 1.63 × 10- 3), IgG1 galactosylation (OR: 0.35 [0.2-0.58], p-value: 3.47 × 10- 5) and hybrid type glycans (OR: 2.73 [1.67-4.89], p-value: 2.31 × 10- 3) were found as discriminators between AIH and healthy controls. High A4GS differentiated AIH from other liver diseases, while bisection associated with cirrhosis severity. CONCLUSIONS: Compared to other liver diseases, AIH shows distinctively high A4GS levels in plasma, with potential implications on glycoprotein function and clearance. Plasma-derived glycosylation has potential to be used as a diagnostic marker for AIH in the future. This may alleviate the need for a liver biopsy at diagnosis. Glycosidic changes should be investigated further in longitudinal studies and may be used for diagnostic and monitoring purposes in the future.

A semi-automated, high throughput approach for O-glycosylation profiling of in vitro established cancer cell lines by MALDI-FT-ICR MS.

The study of protein O-glycosylation is important in biological research as O-glycans have been reported to regulate a multitude of molecular and cell biology processes occurring in cancer. It is known that alterations in O-glycosylation are involved in the development and progression of cancer. Their easy accessibility makes in vitro established cell lines suitable and useful models for studying biological mechanisms in disease. However, the O-glycosylation analysis of large numbers of samples, as required in systems biology and biomarker discovery studies, is often challenging. In the present study, O-glycans from three human colorectal cancer cell lines and two human pancreatic cancer cell lines were released by semi-automated, high throughput reductive ß-elimination and analysed using ultrahigh resolution MALDI-FT-ICR MS. Automated data integration and processing was performed using MassyTools, where the analyte was automatically included for relative quantitation based on a range of selection criteria including signal-to-noise ratio, mass error and isotopic pattern quality scores. A total of 126 O-glycan compositions, ranging from a single monosaccharide to large oligosaccharides exhibiting complex glycan motifs, were detected. The use of ultrahigh resolution MALDI-FTICR MS enabled glycan identification and quantitation in the matrix region of the spectrum. This approach has the potential to be used for O-glycosylation analysis of large numbers of samples, such as patient sample cohorts.

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.

High-throughput glycopeptide profiling of prostate-specific antigen from seminal plasma by MALDI-MS.

An altered total seminal plasma glycosylation has been associated with male infertility, and the highly abundant seminal plasma glycoprotein prostate-specific antigen (PSA) plays an important role in fertilization. However, the exact role of PSA glycosylation in male fertility is not clear. To understand the involvement of PSA glycosylation in the fertilization process, analytical methods are required to study the glycosylation of PSA from seminal plasma with a high glycoform resolution and in a protein-specific manner. In this study, we developed a novel, high-throughput PSA glycopeptide workflow, based on matrix-assisted laser desorption/ionization-mass spectrometry, allowing the discrimination of sialic acid linkage isomers via the derivatization of glycopeptides. The method was successfully applied on a cohort consisting of seminal plasma from infertile and fertile men (N = 102). Forty-four glycopeptides were quantified in all samples, showing mainly complex-type glycans with high levels of fucosylation and sialylation. In addition, N,N-diacetyllactosamine (LacdiNAc) motives were found as well as hybrid-type and high mannose-type structures. Our method showed a high intra- and interday repeatability and revealed no difference in PSA glycosylation between fertile and infertile men. Next to seminal plasma, the method is also expected to be of use for studying PSA glycopeptides derived from other biofluids and/or in other disease contexts.

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.

A Matrix-Assisted Laser Desorption/Ionization-Mass Spectrometry Assay for the Relative Quantitation of Antennary Fucosylated N-Glycans in Human Plasma.

Changes in the abundance of antennary fucosylated glycans in human total plasma N-glycome (TPNG) have been associated with several diseases ranging from diabetes to various forms of cancer. However, it is challenging to address this important part of the human glycome. Most commonly, time-consuming chromatographic separations are performed to differentially quantify core and antenna fucosylation. Obtaining sufficient resolution for larger, more complex glycans can be challenging. We introduce a matrix-assisted laser desorption/ionization-mass spectrometry (MALDI-MS) assay for the relative quantitation of antennary fucosylation in TPNG. N-linked glycans are released from plasma by PNGase F and further treated with a core fucosidase before performing a linkage-informative sialic acid derivatization. The core fucosylated glycans are thus depleted while the remaining antennary fucosylated glycans are quantitated. Simultaneous quantitation of α2,3-linked sialic acids and antennary fucosylation allows an estimation of the sialyl-Lewis x motif. The approach is feasible using either ultrahigh-resolution Fourier-transform ion cyclotron resonance mass spectrometry or time-of-flight mass spectrometry. The assay was used to investigate changes of antennary fucosylation as clinically relevant marker in 14 colorectal cancer patients. In accordance with a previous report, we found elevated levels of antennary fucosylation pre-surgery which decreased after tumor resection. The assay has the potential for revealing antennary fucosylation signatures in various conditions including diabetes and different types of cancer.

Monitoring glycation levels of a bispecific monoclonal antibody at subunit level by ultrahigh-resolution MALDI FT-ICR mass spectrometry.

Bispecific monoclonal antibodies (BsAbs) are engineered proteins with multiple functionalities and properties. The "bi-specificity" of these complex biopharmaceuticals is a key characteristic for the development of novel and more effective therapeutic strategies. The high structural complexity of BsAbs poses a challenge to the analytical methods needed for their characterization. Modifications of the BsAb structure, resulting from enzymatic and non-enzymatic processes, further complicate the analysis. An important example of the latter type of modification is glycation, which can occur in the manufacturing process, during storage in the formulation or in vivo after application of the drug. Glycation affects the structure, function, and stability of monoclonal antibodies, and consequently, a detailed analysis of glycation levels is required. Mass spectrometry (MS) plays a key role in the structural characterization of monoclonal antibodies and top-down, middle-up and middle-down MS approaches are increasingly used for the analysis of modifications. Here, we apply a novel middle-up strategy, based on IdeS digestion and matrix-assisted laser desorption ionization (MALDI) Fourier transform ion cyclotron resonance (FT-ICR) MS, to analyze all six different BsAb subunits in a single high-resolution mass spectrum, namely two light chains, two half fragment crystallizable regions and two Fd' regions, thus avoiding upfront chromatography. This method was used to monitor glycation changes during a 168 h forced-glycation experiment. In addition, hot spot glycation sites were localized using top-down and middle-down MALDI-in-source decay FT-ICR MS, which provided complementary information compared to standard bottom-up MS.

Accounting for isotopic clustering in Fourier transform mass spectrometry data analysis for clinical diagnostic studies.

Mass spectrometry based clinical proteomics has emerged as a powerful tool for high-throughput protein profiling and biomarker discovery. Recent improvements in mass spectrometry technology have boosted the potential of proteomic studies in biomedical research. However, the complexity of the proteomic expression introduces new statistical challenges in summarizing and analyzing the acquired data. Statistical methods for optimally processing proteomic data are currently a growing field of research. In this paper we present simple, yet appropriate methods to preprocess, summarize and analyze high-throughput MALDI-FTICR mass spectrometry data, collected in a case-control fashion, while dealing with the statistical challenges that accompany such data. The known statistical properties of the isotopic distribution of the peptide molecules are used to preprocess the spectra and translate the proteomic expression into a condensed data set. Information on either the intensity level or the shape of the identified isotopic clusters is used to derive summary measures on which diagnostic rules for disease status allocation will be based. Results indicate that both the shape of the identified isotopic clusters and the overall intensity level carry information on the class outcome and can be used to predict the presence or absence of the disease.

Application of a Serum Protein Signature for Pancreatic Cancer to Separate Cases from Controls in a Pancreatic Surveillance Cohort.

BACKGROUND: Pancreatic cancer (PC) surveillance is currently offered to individuals with a genetic predisposition to PC, but routinely used radiological screening modalities are not entirely reliable in detecting early-stage PC or its precursor lesions. We recently identified a discriminating PC biomarker signature in a sporadic patient cohort. In this study, we investigated if protein profiling can accurately distinguish PC from non-PC in a pancreatic surveillance cohort of genetically predisposed individuals. METHODS: Serum samples of 66 individuals with a CDKN2A germline mutation who participated in the pancreatic surveillance program (5 cases, 61 controls) were obtained following a standardized protocol. After sample clean-up, peptide and protein profiles were obtained on an ultrahigh-resolution matrix-assisted laser desorption/ionization-Fourier transform ion cyclotron resonance mass spectrometry platform. A discriminant score for each sample was calculated with a previously designed prediction rule, and the median discriminant scores of cases and controls were compared. Individuals with precursor lesions of PC (n = 4) and individuals with a recent diagnosis of melanoma (n = 4) were also separately considered. RESULTS: Cases had a higher median discriminant score than controls (0.26 vs 0.016; P = .001). The only individual with pathologically confirmed precursor lesions of PC could also be clearly distinguished from controls, and having a (recent) medical history of melanoma did not influence the protein signatures. CONCLUSIONS: Peptide and protein signatures are able to accurately distinguish PC cases from controls in a pancreatic surveillance setting. Mass spectrometry-based protein profiling therefore seems to be a promising candidate for implementation in the pancreatic surveillance program as an additional screening modality.

Developments in FTICR-MS and Its Potential for Body Fluid Signatures.

Fourier transform mass spectrometry (FTMS) is the method of choice for measurements that require ultra-high resolution. The establishment of Fourier transform ion cyclotron resonance (FTICR) MS, the availability of biomolecular ionization techniques and the introduction of the Orbitrap™ mass spectrometer have widened the number of FTMS-applications enormously. One recent example involves clinical proteomics using FTICR-MS to discover and validate protein biomarker signatures in body fluids such as serum or plasma. These biological samples are highly complex in terms of the type and number of components, their concentration range, and the structural identity of each species, and thus require extensive sample cleanup and chromatographic separation procedures. Clearly, such an elaborate and multi-step sample preparation process hampers high-throughput analysis of large clinical cohorts. A final MS read-out at ultra-high resolution enables the analysis of a more complex sample and can thus simplify upfront fractionations. To this end, FTICR-MS offers superior ultra-high resolving power with accurate and precise mass-to-charge ratio (m/z) measurement of a high number of peptides and small proteins (up to 20 kDa) at isotopic resolution over a wide mass range, and furthermore includes a wide variety of fragmentation strategies to characterize protein sequence and structure, including post-translational modifications (PTMs). In our laboratory, we have successfully applied FTICR "next-generation" peptide profiles with the purpose of cancer disease classifications. Here we will review a number of developments and innovations in FTICR-MS that have resulted in robust and routine procedures aiming for ultra-high resolution signatures of clinical samples, exemplified with state-of-the-art examples for serum and saliva.

Structure characterization of unexpected covalent O-sulfonation and ion-pairing on an extremely hydrophilic peptide with CE-MS and FT-ICR-MS.

In this study, we characterized unexpected side-products in a commercially synthesized peptide with the sequence RPRTRLHTHRNR. This so-called peptide D3 was selected by mirror phage display against low molecular weight amyloid-ß-peptide (Aß) associated with Alzheimer's disease. Capillary electrophoresis (CE) was the method of choice for structure analysis because the extreme hydrophilicity of the peptide did not allow reversed-phase liquid chromatography (RPLC) and hydrophilic interaction stationary phases (HILIC). CE-MS analysis, applying a strongly acidic background electrolyte and different statically adsorbed capillary coatings, provided fast and efficient analysis and revealed that D3 unexpectedly showed strong ion-pairing with sulfuric acid. Moreover, covalent O-sulfonation at one or two threonine residues was identified as a result of a side reaction during peptide synthesis, and deamidation was found at either the asparagine residue or at the C-terminus. In total, more than 10 different species with different m/z values were observed. Tandem-MS analysis with collision induced dissociation (CID) using a CE-quadrupole-time-of-flight (QTOF) setup predominantly resulted in sulfate losses and did not yield any further characteristic fragment ions at high collision energies. Therefore, direct infusion Fourier transform ion cyclotron resonance (FT-ICR) MS was employed to identify the covalent modification and discriminate O-sulfonation from possible O-phosphorylation by using an accurate mass analysis. Electron transfer dissociation (ETD) was used for the identification of the threonine O-sulfation sites. In this work, it is shown that the combination of CE-MS and FT-ICR-MS with ETD fragmentation was essential for the full characterization of this extremely basic peptide with labile modifications.

Serum peptide signatures for pancreatic cancer based on mass spectrometry: a comparison to CA19-9 levels and routine imaging techniques.

PURPOSE: The detection of pancreatic tumors lacks a sensitive and specific diagnostic tool. Mass spectrometry (MS)-based profiling of serum proteins is a promising approach for discovery of new clinical biomarkers or biomarker signatures. METHODS: Serum samples from pancreatic cancer (PC) patients and control individuals were collected and processed using a standardized protocol. Samples were divided in a calibration set (n = 49 PC and 110 controls) and a validation set (n = 39 PC and 75 controls). Peptide profiles were obtained using a combination of automated solid-phase extraction with reversed-phase C18 paramagnetic beads and matrix-assisted laser desorption ionization time-of-flight MS. RESULTS: Linear discriminant analysis with double cross-validation resulted in a discriminating peptide signature for PC in the calibration set with a sensitivity of 78 % and a specificity of 91 % [area under the curve (AUC) of 92 %]. Classification was validated with a sensitivity of 93 % and a specificity of 100 % (AUC of 98 %), and the results were compared with carbohydrate antigen 19-9 levels and currently available clinical imaging techniques. The ten most discriminating peptide peaks were identified as fragments of proteins involved in the clotting cascade, acute phase response and immunologic response. CONCLUSIONS: In this study, it is shown that MS-based serum peptide profiles can discriminate between PC and control samples. The approach has great potential for high-throughput analysis in surveillance programs and appears to be most promising for patients with an inherited risk for PC, who benefit from more frequent screening.

Alterations of the serum peptidome in renal cell carcinoma discriminating benign and malignant kidney tumors.

Renal cell carcinoma (RCC) is typically asymptomatic and surgery usually increases patient's life only for early stage tumors. However, some cystic and solid renal lesions cannot be confidently differentiated from clear-cell-RCC. Therefore possible markers for early detection and to distinguish malignant kidney tumors are needed. To this aim, we applied MALDI-TOF and LC-MS/MS analysis to RPC18 MB purified serum of ccRCC, non-ccRCC patients and controls. A cluster of five signals differentiate malignant tumors from benign renal masses and healthy subjects. Moreover, a combination of six ions showed the highest specificity and sensitivity to distinguish ccRCC from controls. Healthy subjects were also differentiated from non-ccRCC by three features. Peptide ratios obtained by MALDI-TOF were compared with those from label-free LC-ESI and no statistical difference was found (p>0.05). ESI-results were linked with MALDI profiles by both TOF/TOF sequencing and MALDI FT-ICR accurate mass measurements. About 200 unique endogenous peptides, originating from 32 proteins, were identified. Among them, SDPR and ZYX were found down-expressed, while SRGN and TMSL3 were up-expressed. In conclusion, our results suggest the possibility to discriminate malignant kidney tumors based on a cluster of serum peptides. Moreover, label-free approach may represent a valid method to verify results obtained by MALDI-TOF. This article is part of a Special Issue entitled: Integrated omics.

Precision profiling and identification of human serum peptides using Fourier transform ion cyclotron resonance mass spectrometry.

Many biomarker discovery studies are based on matrix-assisted laser desorption/ionisation (MALDI) peptide profiles. In this study, 96 human serum samples were analysed on a Bruker solariX(TM) MALDI Fourier transform ion cyclotron resonance (FTICR) system equipped with a 15 tesla magnet. Isotopically resolved peptides were observed in ultrahigh resolution FTICR profiles up to m/z 6500 with mass measurement errors (MMEs) of previously identified peptides at a sub-ppm level. For comparison with our previous platform for peptide profile mass analysis (i.e. Ultraflex II) the corresponding time-of-flight (TOF) spectra were obtained with isotopically resolved peptides up to m/z 3500. The FTICR and TOF systems performed rather similar with respect to the repeatability of the signal intensities. However, the mass measurement precision improved at least 10-fold in ultrahigh resolution data and thus simplified spectral alignment necessary for robust and quantitatively precise comparisons of profiles in large-scale clinical studies. From each single MALDI-FTICR spectrum an m/z-list was obtained with sub-ppm precision for all different species, which is beneficial for identification purposes and interlaboratory comparisons. Furthermore, the FTICR system allowed new peptide identifications from collision-induced dissociation (CID) spectra using direct infusion of reversed-phase (RP) C(18)-fractionated serum samples on an electrospray ionisation (ESI) source.

Quality control based on isotopic distributions for high-throughput MALDI-TOF and MALDI-FTICR serum peptide profiling.

In this study, we have implemented a new quality control (QC) parameter for peptide profiling based on isotopic distributions. This QC parameter is an objective measure and facilitates automatic sorting of large numbers of peptide spectra. Peptides in human serum samples were enriched using reversed-phase C(18)-functionalized magnetic beads using a high-throughput robotic platform. High-resolution MALDI-TOF and ultrahigh resolution MALDI-FTICR mass spectra were obtained and a workflow was developed for automated analysis and evaluation of these profiles. To this end, the isotopic distributions of multiple peptides were quantified from both MALDI-TOF and MALDI-FTICR spectra. Odd peptide isotope distributions in TOF spectra could be rationalized from ultrahigh resolution FTICR spectra that showed overlap of different peptides. The comparison of isotope patterns with estimated polyaveragine distributions was used to calculate a QC value for each single mass spectrum. Sorting these QC values enabled the best MALDI spectrum to be selected from replicate spots. Moreover, using this approach spectra containing high intensities of polymers or other contaminants and lacking peptides of interest can be efficiently removed from a clinical dataset. In general, this method simplifies the exclusion of low quality spectra from further statistical analysis.