Defining putative glycan cancer biomarkers by MS

Advancements in protein glycosylation biomarkers for ovarian cancer through mass spectrometry-based approaches

INTRODUCTION

Ovarian cancer, characterized by metastasis and reduced 5-year survival rates, stands as a substantial factor in the mortality of gynecological malignancies worldwide. The challenge of delayed diagnosis originates from vague early symptoms and the absence of efficient screening and diagnostic biomarkers for early cancer detection. Recent studies have explored the intricate interplay between ovarian cancer and protein glycosylation, unveiling the potential significance of glycosylation-oriented biomarkers.

AREAS COVERED

This review examines the progress in glycosylation biomarker research, with particular emphasis on advances driven by mass spectrometry-based technologies. We document milestones achieved, discuss encountered limitations, and also highlight potential areas for future research and development of protein glycosylation biomarkers for ovarian cancer.

EXPERT OPINION

The association of glycosylation in ovarian cancer is well known, but current research lacks desired sensitivity and specificity for early detection. Notably, investigations into protein-specific and site-specific glycoproteomics have the potential to significantly enhance our understanding of ovarian cancer and facilitate the identification of glycosylation-based biomarkers. Furthermore, the integration of advanced mass spectrometry techniques with AI-driven analysis and glycome databases holds the promise for revolutionizing biomarker discovery for ovarian cancer, ultimately transforming diagnosis and improving patient outcomes.

Assessing the hydrophobicity of glycopeptides using reversed-phase liquid chromatography and tandem mass spectrometry

Retention time is one of the most important parameters that has been widely used to demonstrate the separation results obtained from liquid chromatography (LC) platforms. However, retention time can shift when samples are tested with different instruments and laboratories, which hinders the identification process of analytes when comparing data collected from different LC systems. To address this problem, hydrophobicity index was introduced for retention time normalization of the glycopeptides separated by reversed-phase LC (RPLC). Tandem MS was used for the detection and identification of glycopeptides. In addition, the influence of different types of glycans on the hydrophobicity of peptide backbones was studied by comparing the retention time of glycopeptides with their non-glycosylated counterparts. The hydrophobicity of tryptic digested glycopeptides derived from model glycoproteins, including bovine fetuin, α1-acid glycoprotein, and haptoglobin from human plasma, were evaluated based on the hydrophobicity index of the standard peptides from a peptide retention time calibration mixture. The reduction of hydrophobicity of multiple peptide backbones was observed due to the hydrophilic glycan structures. By comparing the hydrophobicity index of glycopeptides collected from different time and instruments, the day-to-day and lab-to-lab comparisons suggested high reliability and reproducibility of this approach. The RSD% of hydrophobicity index from inter-lab experiments was 1.2%, while the RSD% of retention time was 5.1%. Then, the applications of this method were demonstrated on complex glycopeptide samples extracted from human blood serum. The hydrophobicity index can be applied to address the retention time shift when using different instruments, thereby boosting confidence of the characterization of glycopeptides.

MS-based glycomics: An analytical tool to assess nervous system diseases

Neurological diseases affect millions of peopleochemistryorldwide and are continuously increasing due to the globe's aging population. Such diseases affect the nervous system and are characterized by a progressive decline in brain function and progressive cognitive impairment, decreasing the quality of life for those with the disease as well as for their families and loved ones. The increased burden of nervous system diseases demands a deeper insight into the biomolecular mechanisms at work during disease development in order to improve clinical diagnosis and drug design. Recently, evidence has related glycosylation to nervous system diseases. Glycosylation is a vital post-translational modification that mediates many biological functions, and aberrant glycosylation has been associated with a variety of diseases. Thus, the investigation of glycosylation in neurological diseases could provide novel biomarkers and information for disease pathology. During the last decades, many techniques have been developed for facilitation of reliable and efficient glycomic analysis. Among these, mass spectrometry (MS) is considered the most powerful tool for glycan analysis due to its high resolution, high sensitivity, and the ability to acquire adequate structural information for glycan identification. Along with MS, a variety of approaches and strategies are employed to enhance the MS-based identification and quantitation of glycans in neurological samples. Here, we review the advanced glycomic tools used in nervous system disease studies, including separation techniques prior to MS, fragmentation techniques in MS, and corresponding strategies. The glycan markers in common clinical nervous system diseases discovered by utilizing such MS-based glycomic tools are also summarized and discussed.

Glycosylation of a key cubilin Asn residue results in reduced binding to albumin

Kidney disease often manifests with an increase in proteinuria, which can result from both glomerular and/or proximal tubule injury. The proximal tubules are the major site of protein and peptide endocytosis of the glomerular filtrate, and cubilin is the proximal tubule brush border membrane glycoprotein receptor that binds filtered albumin and initiates its processing in proximal tubules. Albumin also undergoes multiple modifications depending upon the physiologic state. We previously documented that carbamylated albumin had reduced cubilin binding, but the effects of cubilin modifications on binding albumin remain unclear. Here, we investigate the cubilin-albumin binding interaction to define the impact of cubilin glycosylation and map the key glycosylation sites while also targeting specific changes in a rat model of proteinuria. We identified a key Asn residue, N1285, that when glycosylated reduced albumin binding. In addition, we found a pH-induced conformation change may contribute to ligand release. To further define the albumin-cubilin binding site, we determined the solution structure of cubilin's albumin-binding domain, CUB7,8, using small-angle X-ray scattering and molecular modeling. We combined this information with mass spectrometry crosslinking experiments of CUB7,8 and albumin that provides a model of the key amino acids required for cubilin-albumin binding. Together, our data supports an important role for glycosylation in regulating the cubilin interaction with albumin, which is altered in proteinuria and provides new insight into the binding interface necessary for the cubilin-albumin interaction.

Isomeric separation of permethylated glycans by extra-long reversed-phase liquid chromatography (RPLC)-MS/MS

Glycosylation is known as a critical biological process that can largely affect the properties and the functions of proteins. Glycan isomers have been shown to be involved in a variety of disease progressions. However, the separation and identification of glycan isomers has been a challenge for years due to the microheterogeneity of glycan isomeric structures. Therefore, effective and stable techniques have been investigated over the last few decades to improve isomeric separations of glycans. RPLC has been widely used in biomolecule analysis because of its extraordinary reproducibility and reliability in retention time and separation resolution. However, so far, no studies have achieved high resolution of glycan isomers using this technique. In this study, we focused on further boosting the isomeric separation of permethylated glycans using a 500 mm reversed-phase LC column. To achieve better resolutions on permethylated glycans, different LC conditions were optimized using glycan standards, including core- and branch-fucosylated N-glycan isomers and sialic acid linked isomers, which were both successfully separated. Then, the optimal separation strategy was applied to achieve separations of N- and O-glycan isomers derived from model glycoproteins, including bovine fetuin, ribonuclease B and κ-casein. Baseline separations were observed on multiple sialylated linkage isomers. However, the separation performance of high-mannose isomers needs further improvement. The reproducibility and stability of this long C18 column was also tested by doing run-to-run, day-to-day and month-to-month comparisons of retention times on multiple glycans and the %RSD was found less than 0.92%. Finally, we applied this approach to separate glycan isomers derived from complex biological samples, including blood serum and cell lines, where baseline separations were attained on several isomeric structures. Compared to the separation efficiency of PGC and MGC columns, the RPLC C18 column provides lower resolution but more robust reproducibility, which makes it a good complementary alternative for isomeric separations of glycans.

Applications of Proteomics in Ovarian Cancer: Dawn of a New Era

The ability to identify ovarian cancer (OC) at its earliest stages remains a challenge. The patients present an advanced stage at diagnosis. This heterogeneous disease has distinguishable etiology and molecular biology. Next-generation sequencing changed clinical diagnostic testing, allowing assessment of multiple genes, simultaneously, in a faster and cheaper manner than sequential single gene analysis. Technologies of proteomics, such as mass spectrometry (MS) and protein array analysis, have advanced the dissection of the underlying molecular signaling events and the proteomic characterization of OC. Proteomics analysis of OC, as well as their adaptive responses to therapy, can uncover new therapeutic choices, which can reduce the emergence of drug resistance and potentially improve patient outcomes. There is an urgent need to better understand how the genomic and epigenomic heterogeneity intrinsic to OC is reflected at the protein level, and how this information could potentially lead to prolonged survival.

Glycine additive enhances sensitivity for N- and O-glycan analysis with hydrophilic interaction chromatography-electrospray ionization-mass spectrometry

Glycosylation is critical for many biological processes and biotherapeutic development. One of the most powerful approaches for analyzing released glycans is hydrophilic interaction chromatography coupled with electrospray ionization mass spectrometry (HILIC-ESI-MS). The high sensitivity of MS is crucial for detecting low-abundance glycans and elucidating their structures. In this study, we presented a simple solution to boost MS response of procainamide (ProcA) labeled glycans for 2- to over 60-fold by including 1 mM glycine in ammonium formate mobile phases for HILIC-ESI-MS. The glycine additive increased charge states, enhanced ion intensities and signal-to-noise ratios, and improved tandem MS spectral quality of various N- and O-glycans without affecting chromatographic performance. Furthermore, more homogeneous ionization among different ProcA labeled glycans was achieved by using the glycine additive, resulting in more comparable quantitative results relative to fluorescence-based quantification. We demonstrated that ammonium formate caused ion suppression to ProcA labeled glycans, which were likely mitigated by glycine with enhanced ESI ionization. Overall, simple addition of glycine to mobile phases during HILIC-ESI-MS analysis significantly improves MS detection sensitivity and will facilitate future profiling and quantitation of glycans released from N- and O-glycoproteins.

Changes in the Expression of Renal Brush Border Membrane N-Glycome in Model Rats with Chronic Kidney Diseases

Chronic kidney disease (CKD) is defined by a reduced renal function i.e., glomerular filtration rate (GFR), and the presence of kidney damage is determined by measurement of proteinuria or albuminuria. Albuminuria increases with age and can result from glomerular and/or proximal tubule (PT) alterations. Brush-border membranes (BBMs) on PT cells play an important role in maintaining the stability of PT functions. The PT BBM, a highly dynamic, organized, specialized membrane, contains a variety of glycoproteins required for the functions of PT. Since protein glycosylation regulates many protein functions, the alteration of glycosylation due to the glycan changes has attracted more interests for a variety of disease studies recently. In this work, liquid chromatography-tandem mass spectrometry was utilized to analyze the abundances of permethylated glycans from rats under control to mild CKD, severe CKD, and diabetic conditions. The most significant differences were observed in sialylation level with the highest present in the severe CKD and diabetic groups. Moreover, high mannose N-glycans was enriched in the CKD BBMs. Characterization of all the BBM N-glycan changes supports that these changes are likely to impact the functional properties of the dynamic PT BBM. Further, these changes may lead to the potential discovery of glycan biomarkers for improved CKD diagnosis and new avenues for therapeutic treatments.

Rapid glycosylation analysis of mouse serum glycoproteins separated by supported molecular matrix electrophoresis

Previously, we developed a novel separation technique, namely, supported molecular matrix electrophoresis (SMME), which separates mucins on a PVDF membrane that impregnated with a hydrophilic polymer (such as polyvinyl alcohol), so it has the characteristics that are compatible with glycan analysis of the separated bands. Here, we describe the first instance of the application of SMME to mouse sera fractionation and demonstrate their differences from the pooled human sera fractionation by SMME. Furthermore, we have developed a fixation method for the lectin blotting of SMME-separated glycoproteins by immersing the SMME membranes into acetone solvent followed by heating. It showed that the amount of protein samples required for SMME were reduced more than 4-fold than that of the process of SDS-PAGE. We applied these techniques for the detection of glycosylation patterns of serum proteins from Fut8^+/+ and Fut8^-/- mice, further analyzed N-linked and O-linked glycans from the separated γ-bands by mass spectrometry, and demonstrated that there are α2,8-sialylated O-glycans contained in mouse sera glycoproteins. SMME can provide simple, rapid sera fractionation, glycan profiling differences between the bands of two samples and a new insight into the underlying mechanism that responsible for related diseases. SIGNIFICANCE: We describe that the first application of SMME can separate mouse serum proteins into six bands and identify the major protein components of each fraction in mouse serum separated by SMME. Furthermore, we successfully developed a fixation method for lectin blotting of SMME-separated glycoproteins and applied to the detection of glycosylation patterns of serum glycoproteins from Fut8^+/+ and Fut8^-/- mice, also, the method is promising for detecting glycan profiling differences between two samples in both research and clinical settings.

A nomogram based on glycomic biomarkers in serum and clinicopathological characteristics for evaluating the risk of peritoneal metastasis in gastric cancer

Background

Peritoneal metastasis (PM) in gastric cancer (GC) remains an untreatable disease, and is difficult to diagnose preoperatively. Here, we aim to establish a novel prediction model.

Methods

The clinicopathologic characteristics of a cohort that included 86 non-metastatic GC patients and 43 PMGC patients from Zhongshan Hospital were retrospectively analysed to identify PM associated variables. Additionally, mass spectrometry and glycomic analysis were applied in the same cohort to find glycomic biomarkers in serum for the diagnosis of PM. A nomogram was established based on the associations between potential risk variables and PM.

Results

Overexpression of 4 N-glycans (H6N5L1E1: m/z 2620.93; H5N5F1E2: m/z 2650.98; H6N5E2, m/z 2666.96; H6N5L1E2, m/z 2940.08); weight loss ≥ 5 kg; tumour size ≥ 3 cm; signet ring cell or mucinous adenocarcinoma histology type; poor differentiation; diffuse or mixed Lauren classification; increased CA19-9, CA125, and CA724 levels; decreased lymphocyte count, haemoglobin, albumin, and pre-albumin levels were identified to be associated with PM. A nomogram that integrated with five independent risk factors (weight loss ≥ 5 kg, CA19-9 ≥ 37 U/mL, CA125 ≥ 35 U/mL, lymphocyte count < 2.0 * 10 ~ 9/L, and H5N5F1E2 expression ≥ 0.0017) achieved a good performance for diagnosis (AUC: 0.892, 95% CI 0.829–0.954). When 160 was set as the cut-off threshold value, the proposed nomogram represented a perfectly discriminating power for both sensitivity (0.97) and specificity (0.88).

Conclusions

The nomogram achieved an individualized assessment of the risk of PM in GC patients; thus, the nomogram could be used to assist clinical decision-making before surgery.

Glycoprotein biomarkers and analysis in chronic obstructive pulmonary disease and lung cancer with special focus on serum immunoglobulin G

Chronic obstructive pulmonary disease (COPD) and lung cancer are two major diseases of the lung with high rate of mortality, mostly among tobacco smokers. The glycosylation patterns of various plasma proteins show significant changes in COPD and subsequent hypoxia, inflammation and lung cancer, providing promising opportunities for screening aberrant glycan structures contribute to early detection of both diseases. Glycoproteins associated with COPD and lung cancer consist of highly sialylated N-glycans, which play an important role in inflammation whereby hypoxia leads to accumulation of sialyl Lewis A and X glycans. Although COPD is an inflammatory disease, it is an independent risk factor for lung cancer. Marked decrease in galactosylation of plasma immunoglobulin G (IgG) together with increased presence of sialic acids and more complex highly branched N-glycan structures are characteristic for COPD and lung cancer. Numerous glycan biomarkers have been discovered, and analysis of glycovariants associated with COPD and lung cancer has been carried out. In this paper we review fundamental glycosylation changes in COPD and lung cancer glycoproteins, focusing on IgG to provide an opportunity to distinguish between the two diseases at the glycoprotein level with diagnostic value.

Comparative Membrane N-Glycomics of Different Breast Cancer Cell Lines To Understand Breast Cancer Brain Metastasis

The mechanism of brain metastatic breast cancer has gained attention because of its increased incidence rate and its low survival rate. Aberrant protein glycosylation is thought to be a contributing factor in this metastatic mechanism, in which metastatic cancer cells can pass through the blood-brain barrier (BBB). The cell membrane is the outermost layer of a cell and in direct contact with the environment and with other cells, making membrane glycans especially important in many biological processes that include mediating cell-cell adhesion, cell signaling, and interactions. Thus, membrane glycomics has attracted more interest for a variety of disease studies in recent years. To reveal the role that membrane N-glycans play in breast cancer brain metastasis, in this study, membrane enrichment was achieved by ultracentrifugation. Liquid chromatography-tandem mass spectrometry was employed to analyze enriched membrane N-glycomes from five breast cancer cell lines and one brain cancer cell line. Relative quantitative glycomic data from each cell line were compared to MDA-MB-231BR, which is the brain-seeking cell line. The higher sialylation level observed in MDA-MB-231BR suggested the importance of sialylation as it might assist with cell invasion and the penetration of the BBB. Some highly sialylated N-glycans, such as HexNAc₅Hex₆DeoxyHex₁NeuAc₃ and HexNAc₆Hex₇DeoxyHex₁NeuAc₃, exhibited higher abundances in 231BR, indicating their possible contributions to breast cancer brain metastasis as well as their potential to be indicators for the breast cancer brain metastasis.

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.

Glycosylation and glycan interactions can serve as extracellular machinery facilitating clathrin-independent endocytosis

In contrast to clathrin-mediated endocytosis (CME) which is well characterized and understood, little is known about the regulation and machinery underlying clathrin-independent endocytosis (CIE). There is also a wide variation in the requirements each individual CIE cargo has for its internalization. Recent studies have shown that CIE is affected by glycosylation and glycan interactions. We briefly review these studies and explore how these studies mesh with one another. We then discuss what this sensitivity to glycan interactions could indicate for the regulation of CIE. We address the spectrum of responses CIE has been shown to have with respect to changes in glycan interactions and attempt to reconcile disparate observations onto a shared conceptual landscape. We focus on the mechanisms by which cells can alter the glycan interactions at the plasma membrane and propose that glycosylation and glycan interactions could provide cells with a tool box with which cells can manipulate CIE. Altered glycosylation is often associated with a number of diseases and we discuss how under different disease settings, glycosylation-based modulation of CIE could play a role in disease progression.

Clinical application of quantitative glycomics

Aberrant glycosylation has been associated with many diseases. Decades of research activities have reported many reliable glycan biomarkers of different diseases which enable effective disease diagnostics and prognostics. However, none of the glycan markers have been approved for clinical diagnosis. Thus, a review of these studies is needed to guide the successful clinical translation. Area covered: In this review, we describe and discuss advances in analytical methods enabling clinical glycan biomarker discovery, focusing only on studies of released glycans. This review also summarizes the different glycobiomarkers identified for cancers, Alzheimer's disease, diabetes, hepatitis B and C, and other diseases. Expert commentary: Along with the development of techniques in quantitative glycomics, more glycans or glycan patterns have been reported as better potential biomarkers of different diseases and proved to have greater diagnostic/diagnostic sensitivity and specificity than existing markers. However, to successfully apply glycan markers in clinical diagnosis, more studies and verifications on large biological cohorts need to be performed. In addition, faster and more efficient glycomic strategies need to be developed to shorten the turnaround time. Thus, glycan biomarkers have an immense chance to be used in clinical prognosis and diagnosis of many diseases in the near future.

Mass spectrometry-based proteomics techniques and their application in ovarian cancer research

Ovarian cancer has emerged as one of the leading cause of gynecological malignancies. So far, the measurement of CA125 and HE4 concentrations in blood and transvaginal ultrasound examination are essential ovarian cancer diagnostic methods. However, their sensitivity and specificity are still not sufficient to detect disease at the early stage. Moreover, applied treatment may appear to be ineffective due to drug-resistance. Because of a high mortality rate of ovarian cancer, there is a pressing need to develop innovative strategies leading to a full understanding of complicated molecular pathways related to cancerogenesis. Recent studies have shown the great potential of clinical proteomics in the characterization of many diseases, including ovarian cancer. Therefore, in this review, we summarized achievements of proteomics in ovarian cancer management. Since the development of mass spectrometry has caused a breakthrough in systems biology, we decided to focus on studies based on this technique. According to PubMed engine, in the years 2008-2010 the number of studies concerning OC proteomics was increasing, and since 2010 it has reached a plateau. Proteomics as a rapidly evolving branch of science may be essential in novel biomarkers discovery, therapy decisions, progression predication, monitoring of drug response or resistance. Despite the fact that proteomics has many to offer, we also discussed some limitations occur in ovarian cancer studies. Main difficulties concern both complexity and heterogeneity of ovarian cancer and drawbacks of the mass spectrometry strategies. This review summarizes challenges, capabilities, and promises of the mass spectrometry-based proteomics techniques in ovarian cancer management.

A carbon nanoparticles-based solid-phase purification method facilitating sensitive MALDI-MS analysis of permethylated N-glycans

In recent decades, MALDI-MS has been extensively used for the analysis of glycans. However, native glycans usually have low ionization efficiency in MS, which hinders the direct analysis. Permethylation of glycans is a solution for this issue, but a significant amount of salt is introduced during this process, which can further suppress the MS signals. Thus, it is necessary to purify the glycans prior to MALDI-MS analysis. In this study, we developed a carbon nanoparticles-based solid-phase purification method to enable direct MALDI-MS analysis of permethylated glycans. Two carbon nanomaterials, carbon nanoparticles (CNPs) and graphene nanosheets (GNs), and two conventional carbon materials, activated charcoal and porous graphitic carbon (PGC), were investigated as sorbents to purify permethylated N-glycans derived from ribonuclease B and fetuin. The results confirmed the superior performance of CNPs over the other carbon materials. Additionally, our method was also employed to purify glycans released from human sera in different esophageal disease stages. The obtained data confirmed 16 and 18 structures in adenocarcinoma and Barret's sera with significantly different relative intensities versus disease-free sera. Comparing the performance of CNPs-based solid-phase purification method employed in this study to online purification suggested more than 97% recovery rate. The results of this study demonstrate that CNPs have the potential to be a better alternative to existing solid-phase purification sorbents.

Carbon Nanoparticles and Graphene Nanosheets as MALDI Matrices in Glycomics: a New Approach to Improve Glycan Profiling in Biological Samples

Glycomics continues to be a highly dynamic and interesting research area due to the need to comprehensively understand the biological attributes of glycosylation in many important biological functions such as the immune response, cell development, cell differentiation/adhesion, and host-pathogen interactions. Although matrix-assisted laser desorption ionization (MALDI) mass spectrometry (MS) has proven to be suitable for glycomic profiling studies, there is a need for improved sensitivity in the detection of native glycans, which ionize inefficiently. In this study, we investigated the efficiencies of graphene nanosheets (GNs) and carbon nanoparticles (CNPs) as MALDI matrices and co-matrices in glycan profiling. Our results indicated an enhancement of signal intensity by several orders of magnitude upon using GNs and CNPs in MALDI analysis of N-glycans derived from a variety of biological samples. Interestingly, increasing the amounts of CNPs and GNs improved not only the signal intensities but also prompted in-source decay (ISD) fragmentations, which produced extensive glycosidic and cross-ring cleavages. Our results indicated that the extent of ISD fragmentation could be modulated by CNP and GN concentrations, to obtain MS² and pseudo-MS³ spectra. The results for glycan profiling in high salt solutions confirmed high salt-tolerance capacities for both CNPs and GNs. Finally, the results showed that by using CNPs and GNs as co-matrices, DHB crystal formation was more homogeneous which improved shot-to-shot reproducibility and sensitivity. Graphical Abstract ᅟ.

Recent advances in mass spectrometry-based glycoproteomics

Protein glycosylation plays fundamental roles in many biological processes as one of the most common, and the most complex, posttranslational modification. Alterations in glycosylation profile are now known to be associated with many diseases. As a result, the discovery and detailed characterization of glycoprotein disease biomarkers is a primary interest of biomedical research. Advances in mass spectrometry (MS)-based glycoproteomics and glycomics are increasingly enabling qualitative and quantitative approaches for site-specific structural analysis of protein glycosylation. While the complexity presented by glycan heterogeneity and the wide dynamic range of clinically relevant samples like plasma, serum, cerebrospinal fluid, and tissue make comprehensive analyses of the glycoproteome a challenging task, the ongoing efforts into the development of glycoprotein enrichment, enzymatic digestion, and separation strategies combined with novel quantitative MS methodologies have greatly improved analytical sensitivity, specificity, and throughput. This review summarizes current MS-based glycoproteomics approaches and highlights recent advances in its application to cancer biomarker and neurodegenerative disease research.

Distinct cargo-specific response landscapes underpin the complex and nuanced role of galectin-glycan interactions in clathrin-independent endocytosis

Clathrin-independent endocytosis (CIE) is a form of endocytosis that lacks a defined cytoplasmic machinery. Here, we asked whether glycan interactions, acting from the outside, could be a part of that endocytic machinery. We show that the perturbation of global cellular patterns of protein glycosylation by modulation of metabolic flux affects CIE. Interestingly, these changes in glycosylation had cargo-specific effects. For example, in HeLa cells, GlcNAc treatment, which increases glycan branching, increased major histocompatibility complex class I (MHCI) internalization but inhibited CIE of the glycoprotein CD59 molecule (CD59). The effects of knocking down the expression of galectin 3, a carbohydrate-binding protein and an important player in galectin-glycan interactions, were also cargo-specific and stimulated CD59 uptake. By contrast, inhibition of all galectin-glycan interactions by lactose inhibited CIE of both MHCI and CD59. None of these treatments affected clathrin-mediated endocytosis, implying that glycosylation changes specifically affect CIE. We also found that the galectin lattice tailors membrane fluidity and cell spreading. Furthermore, changes in membrane dynamics mediated by the galectin lattice affected macropinocytosis, an altered form of CIE, in HT1080 cells. Our results suggest that glycans play an important and nuanced role in CIE, with each cargo being affected uniquely by alterations in galectin and glycan profiles and their interactions. We conclude that galectin-driven effects exist on a continuum from stimulatory to inhibitory, with distinct CIE cargo proteins having unique response landscapes and with different cell types starting at different positions on these conceptual landscapes.

Comparison of the methods for profiling N-glycans—hepatocellular carcinoma serum glycomics study

Monitoring serum glycomics is one of the most important emerging approaches for diagnosis of various cancers, and the majority of previous studies were based on MALDI-MS or HPLC analysis. Considering the difference of these analytical methods employed for serum glycomics, it is necessary to compare the effectiveness of different analytical methods for monitoring the aberrant changes in serum glycomics. In this study, a strategy based on machine learning was firstly applied for comparing the analysis results of MALDI-MS and HPLC on the same serum glycomics of hepatocellular carcinoma (HCC) samples. The capability of these two analytical methods for identifying HCC is demonstrated by the classification results obtained from MALDI-MS and HPLC data. In addition, by comparing glycomics which were significantly correlated with HCC based on MALDI-MS and HPLC, some N-glycans which may be the potential biomarkers for HCC were identified, validating the capability of these two analytical methods for the differentiated identification in the analysis of glycomics. Meanwhile, it is noteworthy that various physiological and environmental factors may cause the aberrant changes in glycosylation, and all these interference factors may be minimized by analyzing the same sample sets of HCC. Overall, these results showed that MALDI-MS and HPLC are complementary in qualitative and quantitative analysis of serum glycomics.

Monitoring serum glycomics is one of the most important emerging approaches for diagnosis of various cancers, and the majority of previous studies were based on MALDI-MS or HPLC analysis.

Discovery of Non-invasive Glycan Biomarkers for Detection and Surveillance of Gastric Cancer

Purpose: Gastric cancer (GC), one of the world's top five most common cancers, is the third leading cause of cancer related death. It is urgent to identify non-invasive biomarkers for GC. The objective of our study was to find out non-invasive biomarkers for early detection and surveillance of GC based on glycomic analysis.

Method: Ethyl esterification derivatization combined with MALDI-TOF MS analysis was employed for the comprehensive serum glycomic analysis in order to investigate glycan markers that would indicate the onset and progression of gastric cancer. Upon the discovery of the candidate biomarkers, those with great potential were further validated in an independent test set. Peaks were acquired by the software of MALDI-MS sample acquisition and processing and analyzed by the software of Progenesis MALDI. 


Results: The differences in glycosylation were found between non-cancer controls and gastric cancer samples: hybrid and multi-branched type (tri-, tetra-antennnary glycans) N-glycans were increased in GC, yet monoantennary, galactose, bisecting type and core fucose N-glycans were decreased. In training set, core fucose (AUC=0.923, 95%CI: 0.8485 to 0.9967) played an excellent diagnostic performance for the early detection of gastric cancer. The diagnostic potential of core fucose was further validated in an independent cohort (AUC=0.854, 95%CI: 0.7592 to 0.9483). Besides, several individual glycan structures reached both statistical criteria (p-values less than 0.05 and AUC scores that were at least moderately accurate) when comparing different stages of GC samples.

Conclusion: We comprehensively evaluate the serum glycan changes in different stages of GC patients including peritoneal metastasis for the first time. We determined several N-glycan biomarkers, some of these have potential in distinguishing the early stage GC from healthy controls, and the others can help to monitor the progression of GC. The findings also enhance understanding of gastric cancer.

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2011-2012

This review is the seventh update of the original article published in 1999 on the application of MALDI mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2012. General aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, and fragmentation are covered in the first part of the review and applications to various structural types constitute the remainder. The main groups of compound are oligo- and poly-saccharides, glycoproteins, glycolipids, glycosides, and biopharmaceuticals. Much of this material is presented in tabular form. Also discussed are medical and industrial applications of the technique, studies of enzyme reactions, and applications to chemical synthesis. © 2015 Wiley Periodicals, Inc. Mass Spec Rev 36:255-422, 2017.

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.

Micronucleus, cell-free DNA, and plasma glycan composition in the newborns of healthy and diabetic mothers

Diabetes is associated with certain environmental exposures, heritable factors, and metabolic conditions of intrauterine development due to diabetes in the mother. We evaluated genomic damage, cell-free DNA, N-glycosylation of umbilical cord plasma proteins (PG), and nuclear division index (NDI) as possible prognostic biomarkers of health risk in the newborns of mothers with treated pregestational diabetes (NBDM; 22 mothers), compared these parameters with those from newborns of healthy mothers (NBHM; 89 mothers), and associated the results with the mothers' lifestyle in both groups, based on a detailed questionnaire. Genomic damage was estimated by the in vitro micronucleus (MN) assay. NDI was detected on MN slides. Glycans were analyzed by ultra-performance liquid chromatography that separates the plasma N-glycome into 46 glycan peaks. Cell-free DNA was analyzed by real-time PCR. For the association between biomarkers and individual characteristics, generalized linear/nonlinear analysis was performed. No significant difference was found between NBHM and NBDM for cell-free DNA levels. There was no association between cell-free DNA levels and lifestyle. MN frequency was significantly higher in NBDM than in NBHM (median, 0.6 vs. 0.3%, p<0.001). MN frequency and NDI were significantly associated with residence (urban vs. rural). PG differed significantly between NBHM and NBDM (p<0.001). A significant association was found between PG and increase of MN frequency (p<0.001). As both MN frequency and altered N-glycosylation are associated with cancer risk, our study indicates need for further investigations.

Validation of N-glycan markers that improve the performance of CA19-9 in pancreatic cancer

Pancreatic cancer (PC) has a high mortality rate because it is usually diagnosed late. Glycosylation of proteins is known to change in tumor cells during the development of PC. The objectives of this study were to identify and validate the diagnostic value of novel biomarkers based on N-glycomic profiling for PC. In total, 217 individuals including subjects with PC, pancreatitis, and healthy controls were divided randomly into a training group (n = 164) and validation groups (n = 53). Serum N-glycomic profiling was analyzed by DSA-FACE. The diagnostic model was constructed based on N-glycan markers with logistic stepwise regression. The diagnostic performance of the model was assessed further in validation cohort. The level of total core fucose residues was increased significantly in PC. Two diagnostic models designated GlycoPCtest and PCmodel (combining GlycoPCtest and CA19-9) were constructed to differentiate PC from normal. The area under the receiver operating characteristic curve (AUC) of PCmodel was higher than that of CA19-9 (0.925 vs. 0.878). The diagnostic models based on N-glycans are new, valuable, noninvasive alternatives for identifying PC. The diagnostic efficacy is improved by combined GlycoPCtest and CA19-9 for the discrimination of patients with PC from healthy controls.

Quantitative Glycomics: A Combined Analytical and Bioinformatics Approach

Glycosylation is one of the most common and essential protein modifications. Glycans conjugated to biomolecules modulate the function of such molecules through both direct recognition of glycan structures and indirect mechanisms that involve the control of protein turnover rates, stability, and conformation. The biological attributes of glycans in numerous biological processes and implications in a number of diseases highlight the necessity for comprehensive characterization of protein glycosylation. This chapter reviews cutting-edge methods and tools developed to facilitate quantitative glycomics. This chapter highlights the different methods employed for the release and purification of glycans from biological samples. The most effective labeling methods developed for sensitive quantitative glycomics are also described and discussed. The chromatographic approaches that have been used effectively in glycomics are also highlighted.

Serum glycoprotein-derived N- and O-linked glycans as cancer biomarkers

Early detection of cancer is the key to improving survival. Since most clinically used serum cancer biomarkers are either glycoproteins or glycan structures that can be recognized by specific monoclonal antibodies, developing glycan structure-based biomarkers from human serum/plasma glycoproteins through mass spectrometry (MS) analysis are active research field during the past decades. Numerous studies have shown that changes in serum/plasma glycan structures occur during cancer initiation, progression, and treatment. This review describes N- and O-linked glycan structures identified from serum/plasma glycoprotein (s) by MS analysis with focus on alterations associated with different types of human cancers. The global changes in serum N- and O-linked glycan structures, especially the glycans that are not made by cancer cells such as B lymphocyte-derived IgG and liver-synthesized haptoglobin and α1 acid glycoprotein, suggest that glycans might be the long sought diagnostic biomarkers associated with system malfunction in the blood circulation of cancer patients. Therefore, N- and O-linked glycan structures have great potential to serve as cancer diagnosis, prognosis, and treatment monitoring biomarkers to facilitate personalized medicine.

Quantitative LC-MS/MS Glycomic Analysis of Biological Samples Using AminoxyTMT

Protein glycosylation plays an important role in various biological processes, such as modification of protein function, regulation of protein-protein interactions, and control of turnover rates of proteins. Moreover, glycans have been considered as potential biomarkers for many mammalian diseases and development of aberrant glycosylation profiles is an important indicator of the pathology of a disease or cancer. Hence, quantitation is an important aspect of a comprehensive glycomics study. Although numerous MS-based quantitation strategies have been developed in the past several decades, some issues affecting sensitivity and accuracy of quantitation still exist, and the development of more effective quantitation strategies is still required. Aminoxy tandem mass tag (aminoxyTMT) reagents are recently commercialized isobaric tags which enable relative quantitation of up to six different glycan samples simultaneously. In this study, liquid chromatography and mass spectrometry conditions have been optimized to achieve reliable LC-MS/MS quantitative glycomic analysis using aminoxyTMT reagents. Samples were resuspended in 0.2 M sodium chloride solution to promote the formation of sodium adduct precursor ions, which leads to higher MS/MS reporter ion yields. This method was first evaluated with glycans from model glycoproteins and pooled human blood serum samples. The observed variation of reporter ion ratios was generally less than 10% relative to the theoretical ratio. Even for the highly complex minor N-glycans, the variation was still below 15%. This strategy was further applied to the glycomic profiling of N-glycans released from blood serum samples of patients with different esophageal diseases. Our results demonstrate the benefits of utilizing aminoxyTMT reagents for reliable quantitation of biological glycomic samples.

High-temperature LC-MS/MS of permethylated glycans derived from glycoproteins

Various glycomic analysis methods have been developed due to the essential roles of glycans in biological processes as well as the potential application of glycomics in biomarker discovery in many diseases. Permethylation is currently considered to be one of the most common derivatization methods in MS-based glycomic analysis. Permethylation not only improves ionization efficiency and stability of sialylated glycans in positive mode but also allows for enhanced separation performance on reversed-phase liquid chromatography (RPLC). Recently, RPLC-MS analysis of permethylated glycans exhibited excellent performance in sensitivity and reproducibility and became a widely-applied comprehensive strategy in glycomics. However, separating permethylated glycans by RPLC always suffers from peak broadening for high-molecular-weight branched glycans, which probably due to the low exchange rate between the stationary phase and mobile phase limited by intermolecular interactions of the methyl groups associated with the branching of the glycan structures. In this study, we employed high separation temperature conditions for RPLC of permethylated glycans, thus achieving enhanced peak capacity, improving peak shape, and enhancing separation efficiency. Additionally, partial isomeric separation were observed in RPLC of permethylated glycans at high-temperature. Mathematical processing of the correlation between retention time and molecular weight also revealed the advantage of high-temperature LC method for both manual and automatic glycan identification.

Disease-specific IgG Fc N-glycosylation as personalized biomarkers to differentiate gastric cancer from benign gastric diseases

Interest in the pathophysiological role of IgG fragment crystallizable (Fc) N-linked glycosylation arose from changes in humoral immune responses. In this study, circulating disease-specific IgG (DSIgG) derived from serum immunoinflammation-related protein complexes was isolated from 846 serum samples of 443 patients with benign gastric diseases (BGDs) and 403 patients with gastric cancer (GC), and DSIgG glycopeptides attached to IgG Fc region at the site of Asn297 were analyzed using matrix-assisted laser desorption/ionization- Fourier transform ion cyclotron resonance mass spectrometry (MALDI-FTICR MS). A total of 22 glycopeptides were detected. Statistical analysis indicated that DSIgG1 G1S, DSIgG2 G0F, G1, G2F, and G2FS as well as DSIgG2 galactosylation and sialylation are significantly associated with sex in BGD patients and that the age-specific glycoforms and glycosylation features from DSIgG between BGD patients and GC patients have similar change trends. In addition, significant changes in galactosylation, sialylation, and bisecting N-acetylglucosamine (GlcNAc) from DSIgG were also observed between two pathophysiological states. Receiver operating characteristic (ROC) analysis indicated that the G2FN/G1FN (from DSIgG2) ratio has an excellent capability to distinguish female BGD patients from female GC patients over the age range of 20-79 years, with the sensitivity of 82.6%, the specificity of 82.6%, and the area under curve (AUC) of 0.872.

Turning-Off Signaling by Siglecs, Selectins, and Galectins: Chemical Inhibition of Glycan-Dependent Interactions in Cancer

Aberrant glycosylation, a common feature associated with malignancy, has been implicated in important events during cancer progression. Our understanding of the role of glycans in cancer has grown exponentially in the last few years, concurrent with important advances in glycomics and glycoproteomic technologies, paving the way for the validation of a number of glycan structures as potential glycobiomarkers. However, the molecular bases underlying cancer-associated glycan modifications are still far from understood. Glycans exhibit a natural heterogeneity, crucial for their diverse functional roles as specific carriers of biologically relevant information. This information is decoded by families of proteins named lectins, including sialic acid-binding immunoglobulin (Ig)-like lectins (siglecs), C-type lectin receptors (CLRs), and galectins. Siglecs are primarily expressed on the surface of immune cells and differentially control innate and adaptive immune responses. Among CLRs, selectins are a family of cell adhesion molecules that mediate interactions between cancer cells and platelets, leukocytes, and endothelial cells, thus facilitating tumor cell invasion and metastasis. Galectins, a family of soluble proteins that bind β-galactoside-containing glycans, have been implicated in diverse events associated with cancer biology such as apoptosis, homotypic cell aggregation, angiogenesis, cell migration, and tumor-immune escape. Consequently, individual members of these lectin families have become promising targets for the design of novel anticancer therapies. During the past decade, a number of inhibitors of lectin–glycan interactions have been developed including small-molecule inhibitors, multivalent saccharide ligands, and more recently peptides and peptidomimetics have offered alternatives for tackling tumor progression. In this article, we review the current status of the discovery and development of chemical lectin inhibitors and discuss novel strategies to limit cancer progression by targeting lectin–glycan interactions.

Parallel data acquisition of in-source fragmented glycopeptides to sequence the glycosylation sites of proteins

Glycosylation plays important roles in maintaining protein stability and controlling biological processes. In recent years, the correlation between aberrant glycoproteins and many diseases has been reported. Hence, qualitative and quantitative analyses of glycoproteins are necessary to understand physiological processes. LC-MS/MS analysis of glycopeptides is faced with the low glycopeptide signal intensities and low peptide sequence identification. In our study, in-source fragmentation (ISF) was used in conjunction with LC-MS/MS to facilitate the parallel acquisition of peptide backbone sequence and glycan composition information. In ISF method, the identification of glycosylation sites depended on the detection of Y1 ion (ion of peptide backbone with an N-acetylglucosamine attached). To attain dominant Y1 ions, a range of source fragmentation voltages was studied using fetuin. A 45 V ISF voltage was found to be the most efficient voltage for the analysis of glycoproteins. ISF was employed to study the glycosylation sites of three model glycoproteins, including fetuin, α1-acid glycoprotein and porcine thyroglobulin. The approach was then used to analyze blood serum samples. Y1 ions of glycopeptides in tryptic digests of samples were detected. Y1 ions of glycopeptides with different sialic acid groups are observed at different retention times, representing the various numbers of sialic acid moieties associated with the same peptide backbone sequence. With ISF facilitating the peptide backbone sequencing of glycopeptides, identified peptide sequence coverage was increased. For example, identified fetuin sequence percentage was improved from 39 to 80% in MASCOT database searching compared to conventional CID method. The formation of Y1 ions and oxonium ions in ISF facilitates glycopeptide sequencing and glycan composition identification.

Methods for the absolute quantification of N-glycan biomarkers

BACKGROUND

Many treatment options especially for cancer show a low efficacy for the majority of patients demanding improved biomarker panels for patient stratification. Changes in glycosylation are a hallmark of many cancers and inflammatory diseases and show great potential as clinical disease markers. The large inter-subject variability in glycosylation due to hereditary and environmental factors can complicate rapid transfer of glycan markers into the clinical practice but also presents an opportunity for personalized medicine.

SCOPE OF REVIEW

This review discusses opportunities of glycan biomarkers in personalized medicine and reviews the methodology for N-glycan analysis with a specific focus on methods for absolute quantification.

MAJOR CONCLUSIONS

The entry into the clinical practice of glycan markers is delayed in large part due to a lack of adequate methodology for the precise and robust quantification of protein glycosylation. Only absolute glycan quantification can provide a complete picture of the disease related changes and will provide the method robustness required by clinical applications.

GENERAL SIGNIFICANCE

Glycan biomarkers have a huge potential as disease markers for personalized medicine. The use of stable isotope labeled glycans as internal standards and heavy-isotope labeling methods will provide the necessary method precision and robustness acceptable for clinical use. This article is part of a Special Issue entitled "Glycans in personalized medicine" Guest Editor: Professor Gordan Lauc.

Rapid Preparation of Released N-Glycans for HILIC Analysis Using a Labeling Reagent that Facilitates Sensitive Fluorescence and ESI-MS Detection

N-glycosylation of proteins is now routinely characterized and monitored because of its significance to the detection of disease states and the manufacturing of biopharmaceuticals. At the same time, hydrophilic interaction chromatography (HILIC) has emerged as a powerful technology for N-glycan profiling. Sample preparation techniques for N-glycan HILIC analyses have however tended to be laborious or require compromises in sensitivity. To address these shortcomings, we have developed an N-glycan labeling reagent that provides enhanced fluorescence response and MS sensitivity for glycan detection and have also simplified the process of preparing a sample for analysis. The developed labeling reagent rapidly reacts with glycosylamines upon their release from glycoproteins. Within a 5 min reaction, enzymatically released N-glycans are labeled with this reagent comprised of an NHS-carbamate reactive group, a quinoline fluorophore, and a tertiary amine for enhancing ESI+ MS ionization. To further expedite the released N-glycan sample preparation, rapid tagging has been integrated with a fast PNGase F deglycosylation procedure that achieves complete deglycosylation of a diverse set of glycoproteins in approximately 10 min. Moreover, a technique for HILIC-SPE of the labeled glycans has been developed to provide quantitative recovery and facilitate immediate HILIC analysis of the prepared samples. The described approach makes it possible to quickly prepare N-glycan samples and to incorporate the use of a fluorescence and MS sensitivity enhancing labeling reagent. In demonstration of these new capabilities, we have combined the developed sample preparation techniques with UHPLC HILIC chromatography and high sensitivity mass spectrometry to thoroughly detail the N-glycan profile of a monoclonal antibody.

N-linked glycan profiling in neuroblastoma cell lines

Although MYCN amplification has been associated with aggressive neuroblastoma, the molecular mechanisms that differentiate low-risk, MYCN-nonamplified neuroblastoma from high-risk, MYCN-amplified disease are largely unknown. Genomic and proteomic studies have been limited in discerning differences in signaling pathways that account for this heterogeneity. N-Linked glycosylation is a common protein modification resulting from the attachment of sugars to protein residues and is important in cell signaling and immune response. Aberrant N-linked glycosylation has been routinely linked to various cancers. In particular, glycomic markers have often proven to be useful in distinguishing cancers from precancerous conditions. Here, we perform a systematic comparison of N-linked glycomic variation between MYCN-nonamplified SY5Y and MYCN-amplified NLF cell lines with the aim of identifying changes in sugar abundance linked to high-risk neuroblastoma. Through a combination of liquid chromatography-mass spectrometry and bioinformatics analysis, we identified 16 glycans that show a statistically significant change in abundance between NLF and SY5Y samples. Closer examination revealed the preference for larger (in terms of total monosaccharide count) and more sialylated glycan structures in the MYCN-amplified samples in comparison to smaller, nonsialylated glycans that are more dominant in the MYCN-nonamplified samples. These results offer clues for deriving marker candidates for accurate neuroblastoma risk diagnosis.

Glycans and galectins in prostate cancer biology, angiogenesis and metastasis

Prostate cancer is the second most common cause of cancer and the sixth leading cause of cancer death among men worldwide. While localized prostate cancer can be cured, advanced and metastatic prostate cancer remains a significant therapeutic challenge. Malignant transformation is associated with important modifications of the cellular glycosylation profile, and it is postulated that these changes have a considerable relevance for tumor biology. Metastasis is a multiphasic process that encompasses angiogenesis, the spread of tumor cells and their growth at distant sites from the primary tumor location. Recognition of glycoconjugates by galectins, among other lectins, plays a fundamental role in the metastatic spread, tumor immune escape and the neovascularization process. Particularly in prostate cancer, both carbohydrates and galectins have been implicated in many cellular processes such as proliferation, apoptosis, migration and invasion. However, a limited number of studies assessed their potential implications in the induction of metastasis in prostate cancer patients or in animal models. Moreover, the role of galectin-glycan interactions in vivo still remains poorly understood; concerted effort should thus be made in order to shed some light on this question. This review summarizes current evidence on both the expression and role of glycans and galectins in prostate cancer, particularly turning our attention to the angiogenic and metastatic processes.

Specific glycosylation of membrane proteins in epithelial ovarian cancer cell lines: glycan structures reflect gene expression and DNA methylation status

Epithelial ovarian cancer is the fifth most common cause of cancer in women worldwide bearing the highest mortality rate among all gynecological cancers. Cell membrane glycans mediate various cellular processes such as cell signaling and become altered during carcinogenesis. The extent to which glycosylation changes are influenced by aberrant regulation of gene expression is nearly unknown for ovarian cancer and remains crucial in understanding the development and progression of this disease. To address this effect, we analyzed the membrane glycosylation of non-cancerous ovarian surface epithelial (HOSE 6.3 and HOSE 17.1) and serous ovarian cancer cell lines (SKOV 3, IGROV1, A2780, and OVCAR 3), the most common histotype among epithelial ovarian cancers. N-glycans were released from membrane glycoproteins by PNGase F and analyzed using nano-liquid chromatography on porous graphitized carbon and negative-ion electrospray ionization mass spectrometry (ESI-MS). Glycan structures were characterized based on their molecular masses and tandem MS fragmentation patterns. We identified characteristic glycan features that were unique to the ovarian cancer membrane proteins, namely the "bisecting N-acetyl-glucosamine" type N-glycans, increased levels of α 2-6 sialylated N-glycans and "N,N'-diacetyl-lactosamine" type N-glycans. These N-glycan changes were verified by examining gene transcript levels of the enzymes specific for their synthesis (MGAT3, ST6GAL1, and B4GALNT3) using qRT-PCR. We further evaluated the potential epigenetic influence on MGAT3 expression by treating the cell lines with 5-azacytidine, a DNA methylation inhibitor. For the first time, we provide evidence that MGAT3 expression may be epigenetically regulated by DNA hypomethylation, leading to the synthesis of the unique "bisecting GlcNAc" type N-glycans on the membrane proteins of ovarian cancer cells. Linking the observation of specific N-glycan substructures and their complex association with epigenetic programming of their associated synthetic enzymes in ovarian cancer could potentially be used for the development of novel anti-glycan drug targets and clinical diagnostic tools.

Computational framework for identification of intact glycopeptides in complex samples

Glycosylation is an important protein modification that involves enzymatic attachment of sugars to amino acid residues. Understanding the structure of these sugars and the effects of glycosylation are vital for developing indicators of disease development and progression. Although computational methods based on mass spectrometric data have proven to be effective in monitoring changes in the glycome, developing such methods for the glycoproteome are challenging, largely due to the inherent complexity in simultaneously studying glycan structures with their corresponding glycosylation sites. This paper introduces a computational framework for identifying intact N-linked glycopeptides, i.e. glycopeptides with N-linked glycans attached to their glycosylation sites, in complex proteome samples. Scoring algorithms are presented for tandem mass spectra of glycopeptides resulting from collision-induced dissociation (CID), higher-energy C-trap dissociation (HCD), and electron transfer dissociation (ETD) fragmentation modes. An empirical false-discovery rate estimation method, based on a target-decoy search approach, is derived for assigning confidence. The power of our method is further enhanced when multiple data sets are pooled together to increase identification confidence. Using this framework, 103 highly confident N-linked glycopeptides from 53 sites across 33 glycoproteins were identified in complex human serum proteome samples using conventional proteomic platforms with standard depletion of the 7-most abundant proteins. These results indicate that our method is ready to be used for characterizing site-specific protein glycosylation in complex samples.

Matrix assisted laser desorption ionization imaging mass spectrometry workflow for spatial profiling analysis of N-linked glycan expression in tissues

A new matrix assisted laser desorption ionization imaging mass spectrometry (MALDI-IMS) method to spatially profile the location and distribution of multiple N-linked glycan species in tissues is described. Application of an endoglycosidase, peptide N-glycosidase F (PNGaseF), directly on tissues followed by incubation releases N-linked glycan species amenable to detection by MALDI-IMS. The method has been designed to simultaneously profile the multiple glycan species released from intracellular organelle and cell surface glycoproteins, while maintaining histopathology compatible preparation workflows. A recombinant PNGaseF enzyme was sprayed uniformly across mouse brain tissue slides, incubated for 2 h, then sprayed with 2,5-dihydroxybenzoic acid matrix for MALDI-IMS analysis. Using this basic approach, global snapshots of major cellular N-linked glycoforms were detected, including their tissue localization and distribution, structure, and relative abundance. Off-tissue extraction and modification of glycans from similarly processed tissues and further mass spectrometry or HPLC analysis was done to assign structural designations. MALDI-IMS has primarily been utilized to spatially profile proteins, lipids, drug, and small molecule metabolites in tissues, but it has not been previously applied to N-linked glycan analysis. The translatable MALDI-IMS glycan profiling workflow described herein can readily be applied to any tissue type of interest. From a clinical diagnostics perspective, the ability to differentially profile N-glycans and correlate their molecular expression to histopathological changes can offer new approaches to identifying novel disease related targets for biomarker and therapeutic applications.

Enrichment strategies in glycomics-based lung cancer biomarker development

PURPOSE

There is a need to identify better glycan biomarkers for diagnosis, early detection, and treatment monitoring in lung cancer using biofluids such as blood. Biofluids are complex mixtures of proteins dominated by a few high abundance proteins that may not have specificity for lung cancer. Therefore, two methods for protein enrichment were evaluated; affinity capturing of IgG and enrichment of medium abundance proteins, thus allowing us to determine which method yields the best candidate glycan biomarkers for lung cancer.

EXPERIMENTAL DESIGN

N-glycans isolated from plasma samples from 20 cases of lung adenocarcinoma and 20 matched controls were analyzed using nLC-PGC-chip-TOF-MS (where PGC is porous-graphitized carbon). N-glycan profiles were obtained for five different fractions: total plasma, isolated IgG, IgG-depleted plasma, and the bound and flow-through fractions of protein enrichment.

RESULTS

Four glycans differed significantly (false discovery rate, FDR < 0.05) between cases and controls in whole unfractionated plasma, while four other glycans differed significantly by cancer status in the IgG fraction. No significant glycan differences were observed in the other fractions.

CONCLUSIONS AND CLINICAL RELEVANCE

These results confirm that the N-glycan profile in plasma of lung cancer patients is different from healthy controls and appears to be dominated by alterations in relatively abundant proteins.

Decreased expression of alpha-L-fucosidase gene FUCA1 in human colorectal tumors

In previous studies we described a decreased alpha-l-fucosidase activity in colorectal tumors, appearing as a prognostic factor of tumoral recurrence. The aim of this work was to extend the knowledge about tissue alpha-l-fucosidase in colorectal cancer by quantifying the expression of its encoding gene FUCA1 in tumors and healthy mucosa. FUCA1 mRNA levels were measured by RT-qPCR in paired tumor and normal mucosa tissues from 31 patients. For the accuracy of the RT-qPCR results, five candidate reference genes were validated in those samples. In addition, activity and expression of alpha-l-fucosidase in selected matched tumor and healthy mucosa samples were analyzed. According to geNorm and NormFinder algorithms, RPLP0 and HPRT1 were the best reference genes in colorectal tissues. These genes were used for normalization of FUCA1 expression levels. A significant decrease of more than 60% in normalized FUCA1 expression was detected in tumors compared to normal mucosa (p = 0.002). Moreover, a gradual decrease in FUCA1 expression was observed with progression of disease from earlier to advanced stages. These findings were confirmed by Western blot analysis of alpha-l-fucosidase expression. Our results demonstrated diminished FUCA1 mRNA levels in tumors, suggesting that expression of tissue alpha-l-fucosidase could be regulated at transcriptional level in colorectal cancer.

Glycomic profiling of tissue sections by LC-MS

Because routine preparation of glycan samples involves multiple reaction and cleaning steps at which sample loss occurs, glycan analysis is typically performed using large tissue samples. This type of analysis yields no detailed molecular spatial information and requires special care to maintain proper storage and shipping conditions. We describe here a new glycan sample preparation protocol using minimized sample preparation steps and optimized procedures. Tissue sections and spotted samples first undergo on-surface enzymatic digestion to release N-glycans. The released glycans are then reduced and permethylated prior to online purification and LC-electrospray ionization (ESI)-MS analysis. The efficiency of this protocol was initially evaluated using model glycoproteins and human blood serum (HBS) spotted on glass or Teflon slides. The new protocol permitted the detection of permethylated N-glycans derived from 10 ng RNase B. On the other hand, 66 N-glycans were identified when injecting the equivalent of permethylated glycans derived from a 0.1-μL aliquot of HBS. On-tissue enzymatic digestion of nude mouse brain tissue permitted the detection of 43 N-glycans. The relative peak areas of these 43 glycans were comparable to those from a C57BL/6 mouse reported by the Consortium for Functional Glycomics (CFG). However, the sample size analyzed in the protocol described here was substantially smaller than for the routine method (submicrogram vs mg). The on-tissue N-glycan profiling method permits high sensitivity and reproducibility and can be widely applied to assess the spatial distribution of glycans associated with tissue sections, and may be correlated with immunoflourescence imaging when adjacent tissue sections are analyzed.

Ovarian cancer: can proteomics give new insights for therapy and diagnosis?

The study of the ovarian proteomic profile represents a new frontier in ovarian cancer research, since this approach is able to enlighten the wide variety of post-translational events (such as glycosylation and phosphorylation). Due to the possibility of analyzing thousands of proteins, which could be simultaneously altered, comparative proteomics represent a promising model of possible biomarker discovery for ovarian cancer detection and monitoring. Moreover, defining signaling pathways in ovarian cancer cells through proteomic analysis offers the opportunity to design novel drugs and to optimize the use of molecularly targeted agents against crucial and biologically active pathways. Proteomic techniques provide more information about different histological types of ovarian cancer, cell growth and progression, genes related to tumor microenvironment and specific molecular targets predictive of response to chemotherapy than sequencing or microarrays. Estimates of specificity with proteomics are less consistent, but suggest a new role for combinations of biomarkers in early ovarian cancer diagnosis, such as the OVA1 test. Finally, the definition of the proteomic profiles in ovarian cancer would be accurate and effective in identifying which pathways are differentially altered, defining the most effective therapeutic regimen and eventually improving health outcomes.