Modeling and integration of N-glycan biomarkers in a comprehensive biomarker data model.

Molecular biomarkers measure discrete components of biological processes that can contribute to disorders when impaired. Great interest exists in discovering early cancer biomarkers to improve outcomes. Biomarkers represented in a standardized data model, integrated with multi-omics data, may improve the understanding and use of novel biomarkers such as glycans and glycoconjugates. Among altered components in tumorigenesis, N-glycans exhibit substantial biomarker potential, when analyzed with their protein carriers. However, such data are distributed across publications and databases of diverse formats, which hamper their use in research and clinical application. Mass spectrometry measures of 50 N-glycans on 7 serum proteins in liver disease were integrated (as a panel) into a cancer biomarker data model, providing a unique identifier, standard nomenclature, links to glycan resources, and accession and ontology annotations to standard protein, gene, disease, and biomarker information. Data provenance was documented with a standardized United States Food and Drug Administration-supported BioCompute Object. Using the biomarker data model allows the capture of granular information, such as glycans with different levels of abundance in cirrhosis, hepatocellular carcinoma, and transplant groups. Such representation in a standardized data model harmonizes glycomics data in a unified framework, making glycan-protein biomarker data exploration more available to investigators and to other data resources. The biomarker data model we describe can be used by researchers to describe their novel glycan and glycoconjugate biomarkers; it can integrate N-glycan biomarker data with multi-source biomedical data and can foster discovery and insight within a unified data framework for glycan biomarker representation, thereby making the data FAIR (Findable, Accessible, Interoperable, Reusable) (https://www.go-fair.org/fair-principles/).

A Novel Mass Spectrometry Platform for Multiplexed N-Glycoprotein Biomarker Discovery from Patient Biofluids by Antibody Panel Based N-Glycan Imaging.

A new platform for N-glycoprotein analysis from serum that combines matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) workflows with antibody slide arrays is described. Antibody panel based (APB) N-glycan imaging allows for the specific capture of N-glycoproteins by antibodies on glass slides and N-glycan analysis in a protein-specific and multiplexed manner. Development of this technique has focused on characterizing two abundant and well-studied human serum glycoproteins, alpha-1-antitrypsin and immunoglobulin G. Using purified standard solutions and 1 µL samples of human serum, both glycoproteins can be immunocaptured and followed by enzymatic release of N-glycans. N-Glycans are detected with a MALDI FT-ICR mass spectrometer in a concentration-dependent manner while maintaining specificity of capture. Importantly, the N-glycans detected via slide-based antibody capture were identical to that of direct analysis of the spotted standards. As a proof of concept, this workflow was applied to patient serum samples from individuals with liver cirrhosis to accurately detect a characteristic increase in an IgG N-glycan. This novel approach to protein-specific N-glycan analysis from an antibody panel can be further expanded to include any glycoprotein for which a validated antibody exists. Additionally, this platform can be adapted for analysis of any biofluid or biological sample that can be analyzed by antibody arrays.

N-Linked Glycan Branching and Fucosylation Are Increased Directly in Hcc Tissue As Determined through in Situ Glycan Imaging.

Hepatocellular carcinoma (HCC) remains as the fifth most common cancer in the world and accounts for more than 700,000 deaths annually. Changes in serum glycosylation have long been associated with this cancer but the source of that material is unknown and direct glycan analysis of HCC tissues has been limited. Our laboratory previously developed a method of in situ tissue based N-linked glycan imaging that bypasses the need for microdissection and solubilization of tissue prior to analysis. We used this methodology in the analysis of 138 HCC tissue samples and compared the N-linked glycans in cancer tissue with either adjacent untransformed or tissue from patients with liver cirrhosis but no cancer. Ten glycans were found significantly elevated in HCC tissues as compared to cirrhotic or adjacent tissue. These glycans fell into two major classes, those with increased levels of fucosylation and those with increased levels of branching with or without any fucose modifications. In addition, increased levels of fucosylated glycoforms were associated with a reduction in survival time. This work supports the hypothesis that the increased levels of fucosylated N-linked glycans in HCC serum are produced directly from the cancer tissue.

GlycoFibroTyper: A Novel Method for the Glycan Analysis of IgG and the Development of a Biomarker Signature of Liver Fibrosis.

Our group has recently developed the GlycoTyper assay which is a streamlined antibody capture slide array approach to directly profile N-glycans of captured serum glycoproteins including immunoglobulin G (IgG). This method needs only a few microliters of serum and utilizes a simplified processing protocol that requires no purification or sugar modifications prior to analysis. In this method, antibody captured glycoproteins are treated with peptide N-glycosidase F (PNGase F) to release N-glycans for detection by MALDI imaging mass spectrometry (IMS). As alterations in N-linked glycans have been reported for IgG from large patient cohorts with fibrosis and cirrhosis, we utilized this novel method to examine the glycosylation of total IgG, as well as IgG1, IgG2, IgG3 and IgG4, which have never been examined before, in a cohort of 106 patients with biopsy confirmed liver fibrosis. Patients were classified as either having no evidence of fibrosis (41 patients with no liver disease or stage 0 fibrosis), early stage fibrosis (10 METAVIR stage 1 and 18 METAVIR stage 2) or late stage fibrosis (6 patients with METAVIR stage 3 fibrosis and 37 patients with METAVIR stage 4 fibrosis (cirrhosis)). Several major alterations in glycosylation were observed that classify patients as having no fibrosis (sensitivity of 92% and a specificity of 90%), early fibrosis (sensitivity of 84% with 90% specificity) or significant fibrosis (sensitivity of 94% with 90% specificity).

Glycan Imaging Mass Spectrometry: Progress in Developing Clinical Diagnostic Assays for Tissues, Biofluids, and Cells.

N-glycan imaging mass spectrometry (IMS) can rapidly and reproducibly identify changes in disease-associated N-linked glycosylation that are linked with histopathology features in standard formalin-fixed paraffin-embedded tissue samples. It can detect multiple N-glycans simultaneously and has been used to identify specific N-glycans and carbohydrate structural motifs as possible cancer biomarkers. Recent advancements in instrumentation and sample preparation are also discussed. The tissue N-glycan IMS workflow has been adapted to new glass slide-based assays for effective and rapid analysis of clinical biofluids, cultured cells, and immunoarray-captured glycoproteins for detection of changes in glycosylation associated with disease.

N-Glycosylation Patterns Correlate with Hepatocellular Carcinoma Genetic Subtypes.

Hepatocellular carcinoma (HCC) is the second leading cause of cancer deaths globally, and the incidence rate in the United States is increasing. Studies have identified inter- and intratumor heterogeneity as histologic and/or molecular subtypes/variants associated with response to certain molecular targeted therapies. Spatial HCC tissue profiling of N-linked glycosylation by matrix-assisted laser desorption ionization imaging mass spectrometry (MALDI-IMS) may serve as a new method to evaluate the tumor heterogeneity. Previous work has identified significant changes in the N-linked glycosylation of HCC tumors but has not accounted for the heterogeneous genetic and molecular nature of HCC. To determine the correlation between HCC-specific N-glycosylation changes and genetic/molecular tumor features, we profiled HCC tissue samples with MALDI-IMS and correlated the spatial N-glycosylation with a widely used HCC molecular classification (Hoshida subtypes). MALDI-IMS data displayed trends that could approximately distinguish between subtypes, with subtype 1 demonstrating significantly dysregulated N-glycosylation versus adjacent nontumor tissue. Although there were no individual N-glycan structures that could identify specific subtypes, trends emerged regarding the correlation of branched glycan expression to HCC as a whole and fucosylated glycan expression to subtype 1 tumors specifically. IMPLICATIONS: Correlating N-glycosylation to specific subtypes offers the specific detection of subtypes of HCC, which could both enhance early HCC sensitivity and guide targeted clinical therapies.

Rapid N-Glycan Profiling of Serum and Plasma by a Novel Slide-Based Imaging Mass Spectrometry Workflow.

Changes in the levels and compositions of N-glycans released from serum and plasma glycoproteins have been assessed in many diseases across many large clinical sample cohorts. Assays used for N-glycan profiling in these fluids currently require multiple processing steps and have limited throughput, thus diminishing their potential for use as standard clinical diagnostic assays. A novel slide-based N-glycan profiling method was evaluated for sensitivity and reproducibility using a pooled serum standard. Serum was spotted on to an amine-reactive slide, delipidated and desalted with a series of washes, sprayed with peptide N-glycosidase F and matrix, and analyzed by MALDI-FTICR or MALDI-Q-TOF mass spectrometry. Routinely, over 75 N-glycan species can be detected from one microliter of serum in less than 6.5 h. Additionally, endoglycosidase F3 was applied to this workflow to identify core-fucosylated N-glycans and displayed the adaptability of this method for the determination of structural information. This method was applied to a small pooled serum set from either obese or nonobese patients that had breast cancer or a benign lesion. This study confirms the reproducibility, sensitivity, and adaptability of a novel method for N-glycan profiling of serum and plasma for potential application to clinical diagnostics.

Antibody Panel Based N-Glycan Imaging for N-Glycoprotein Biomarker Discovery.

Antibody panel based N-glycan imaging is a novel platform for N-glycan analysis of immunocaptured proteins. N-glycosylation is a post-translational modification of pathophysiological importance and is often studied in the context of disease biomarkers. Determination of protein-specific N-glycosylation changes in patient samples has traditionally been laborious or limited to study of a single protein per analysis. This novel technique allows for the multiplexed analysis of N-glycoproteins from biofluids. Briefly, this platform consists of antibodies spotted in an array panel to a microscope slide, specific capture of glycoproteins from a biological sample, and then enzymatic release of N-glycans for analysis by matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS). N-glycans are detected at each individual spot, allowing N-glycan information to easily be linked back to its protein carrier. Using this protocol, multiplexed analysis of N-glycosylation on serum glycoproteins can be performed. Human serum is discussed here, but this method has potential to be applied to other biofluids and to any glycoprotein that can be captured by a validated antibody. © 2019 by John Wiley & Sons, Inc. Basic Protocol: Antibody panel based N-glycan imaging by MALDI MS Support Protocol: Confirmation of antibody capture by IR-labeled proteins.

The search for biomarkers of hepatocellular carcinoma and the impact on patient outcome.

Hepatocellular carcinoma (HCC) is the 5th most common cancer, but the 3rd leading cause of cancer death globally with approximately 700,000 fatalities annually. The severity of this cancer arises from its difficulty to detect and treat. The major etiologies of HCC are liver fibrosis or cirrhosis from chronic viral infections, as well as metabolic conditions. Since most cases arise from prior pathologies, biomarker surveillance in high-risk individuals is an essential approach for early detection and improved patient outcome. While many molecular biomarkers have been associated with HCC, there are few that have made clinical impact for this disease. Here we review some major approaches used for HCC biomarker discovery-proteomics and glycomics-and describe new methodologies being tested for biomarker development.