Serum protein N-glycosylation changes in multiple myeloma

The oligosaccharyltransferase complex is an essential component of multiple myeloma plasma cells

Multiple myeloma (MM) is an incurable malignancy characterized by mutated plasma cell clonal expansion in the bone marrow, leading to severe clinical symptoms. Thus, identifying new therapeutic targets for MM is crucial. We identified the oligosaccharyltransferase (OST) complex as a novel vulnerability in MM cells. Elevated expression of this complex is associated with relapsed, high-risk MM, and poor prognosis. Disrupting the OST complex suppressed MM cell growth, induced cell-cycle arrest, and apoptosis. Combined inhibition with bortezomib synergistically eliminated MM cells in vitro and in vivo, via suppressing genes related to bortezomib-resistant phenotypes. Mechanistically, OST complex disruption downregulated MM pathological pathways (mTORC1 pathway, glycolysis, MYC targets, and cell cycle) and induced TRAIL-mediated apoptosis. Notably, MYC translation was robustly suppressed upon inhibiting the OST complex. Collectively, the OST complex presents a novel target for MM treatment, and combining its inhibition with bortezomib offers a promising approach for relapsed MM patients.

Deciphering N-Glycosylation Dynamics of Serum Monoclonal Immunoglobulins in Multiple Myeloma via EThcD-sceHCD-MS/MS

Serum glycoprotein glycosylation changes can indicate disease onset and progression. However, the site-specific N-glycosylation of monoclonal immunoglobulins (M-proteins) in multiple myeloma (MM) and its clinical implications are unclear. In this study, we isolated pathogenic micromonoclonal IgA or IgG (approximately 2 μg) from IgA-MM patients (n = 22) and IgG-MM patients (n = 30), and normal polyclonal IgA and IgG from healthy controls (HCs) (n = 16). Using EThcD-sceHCD-MS/MS, the N-glycosylation dynamics of serum M-proteins in MM were determined. Compared with polyclonal IgA1 from HCs, monoclonal IgA1 from IgA-MM patients had higher fucosylation (58.1% vs 32.1%, p < 0.001), sialylation (68.0% vs 50.8%, p = 0.011), and mannosylation (1.5% vs 0.3%, p < 0.001). While, monoclonal IgG1 from IgG-MM patients had higher fucosylation (97.8% vs 95.3%, p < 0.001). In addition, specific N-glycan abundances correlated with MM clinical features: for IgA1, HexNAc5Hex5Fuc1NeuAc1 was associated with hypocomplementemia; for IgG1, HexNAc4Hex3Fuc1 was associated with the serum albumin level (r = -0.363, p = 0.049) and estimated glomerular filtration rate (r = -0.433, p = 0.017); and HexNAc4Hex5 was associated with therapeutic prognosis. In conclusion, monoclonal IgA1 and IgG1 in MM patients and their polyclonal isotypes in HCs have distinct N-glycosylation profiles, and specific N-glycans of M-proteins are associated with MM characteristics and therapeutic prognosis.

Fully Integrated Centrifugal Microfluidics for Rapid Exosome Isolation, Glycan Analysis, and Point-of-Care Diagnosis

Exosomes present in the circulatory system demonstrate considerable promise for the diagnosis and treatment of diseases. Nevertheless, the complex nature of blood samples and the prevalence of highly abundant proteins pose a significant obstacle to prompt and effective isolation and functional evaluation of exosomes from blood. Here, we present a fully integrated lab-on-a-disc equipped with two nanofilters, also termed iExoDisc, which facilitates automated isolation of exosomes from 400 μL blood samples within 45 min. By integrating the plasma separation module, highly abundant protein removal module, and nanopore membrane-based total isolation module, the resulting exosomes exhibited significantly increased purity (∼3-6-fold) compared to conventional ultracentrifugation and polymer precipitation. Additionally, we then successfully performed nontargeted and targeted glycan profiling on exosomes derived from clinical triple-negative breast cancer (TNBC) patients using MALDI-TOF-MS and lectin microarray containing 56 kinds of lectins. The findings from both methodologies indicated that galactosylation and sialylation exhibit potential as diagnostic indicators for TNBC. Finally, by utilizing the exosome-specific glycosylated protein CD63 as a proof-of-concept, we successfully realized the integration of point-of-care on-chip exosome separation and in situ detection with 2 h. Thus, the iExoDisc provides a potential approach to early cancer detection, liquid biopsy, and point-of-care diagnosis.

Prognostic Value of Plasma Immunoglobulin G N-Glycome Traits in Pulmonary Arterial Hypertension

BACKGROUND

B-type natriuretic peptide or N-terminal pro-B-type natriuretic peptide is the only blood biomarker in established risk calculators for pulmonary arterial hypertension (PAH). Profiling systemic-originated plasma immunoglobulin G (IgG) N-glycans, which reflect different components of the pathophysiology of PAH including immune dysregulation and inflammation, may improve PAH risk assessment.

OBJECTIVES

This study sought to identify plasma IgG N-glycan biomarkers that predict survival in PAH to improve risk assessment.

METHODS

This cohort study examined 622 PAH patients from 2 national centers (Beijing [discovery] cohort: n = 273; Shanghai [validation] cohort: n = 349). Plasma IgG N-glycomes were profiled by a robust mass spectrometry-based method. Prognostic IgG N-glycan traits were identified and validated in the 2 cohorts using Cox regression and Kaplan-Meier survival analyses. The added value of IgG N-glycan traits to previously established risk models was assessed using Harrell C-indexes and survival analysis.

RESULTS

Plasma IgG fucosylation was found to predict survival independent of age and sex in the discovery cohort (HR: 0.377; 95% CI: 0.168-0.845; P = 0.018) with confirmation in the validation cohort (HR: 0.445; 95% CI: 0.264-0.751; P = 0.005). IgG fucosylation remained a robust predictor of mortality in combined cohorts after full adjustment and in subgroup analyses. Integrating IgG fucosylation into previously established risk models improved their predictive capacity, marked by an overall elevation in Harrell C-indexes. IgG fucosylation was useful in further stratifying the intermediate-risk patients classified by a previously established model.

CONCLUSIONS

Plasma IgG fucosylation informs PAH prognosis independent of established factors, offering additional value for predicting PAH outcomes.

Exploring serum N-glycome patterns as candidate non-invasive biomarkers in inguinal hernia

Introduction

Although inguinal hernia (IH) is prevalent in elderly males, research on its specific diagnostic biomarkers is limited. Protein N-glycosylation is one of the most important and ubiquitous post-translational modifications and often results in a remarkable heterogeneity of protein glycoforms. Protein N-glycosylation often changes in a disease and holds great potential for discovering non-invasive biomarkers. This study aimed to gain insights into total serum protein N-glycosylation of IH to identify candidate non-invasive biomarkers for diagnosis and subtype classification of IH.

Methods

Linkage-specific sialylation derivatization combined with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry detection was used to analyze serum protein N-glycosylation patterns in IH patients and healthy controls.

Results

IH patients had abnormal glycan fucosylation and sialylation compared to healthy controls (HC), of which two glycan traits representing linkage-specific sialylation within monoantennary glycans showed high potential as diagnostic biomarkers for IH with an area under the curve (AUC) of 0.75. Additionally, serum N-glycans were different between indirect IH and direct IH in glycosylation features, namely complexity, fucosylation, galactosylation, sialylation, and α2,6-linked sialylation. Four distinctive glycans between the two subtypes showed good performance with AUC >0.8, suggesting that these glycan traits have potential as biomarkers for subtype classification.

Conclusions

We first reported the serum N-glycomic features of IH patients. Furthermore, we identified several potential biomarkers for the diagnosis and subtype classification of IH. These findings can deepen the understanding of IH.

The Human Blood N-Glycome: Unraveling Disease Glycosylation Patterns

Most of the proteins in the circulation are N-glycosylated, shaping together the total blood N-glycome (TBNG). Glycosylation is known to affect protein function, stability, and clearance. The TBNG is influenced by genetic, environmental, and metabolic factors, in part epigenetically imprinted, and responds to a variety of bioactive signals including cytokines and hormones. Accordingly, physiological and pathological events are reflected in distinct TBNG signatures. Here, we assess the specificity of the emerging disease-associated TBNG signatures with respect to a number of key glycosylation motifs including antennarity, linkage-specific sialylation, fucosylation, as well as expression of complex, hybrid-type and oligomannosidic N-glycans, and show perplexing complexity of the glycomic dimension of the studied diseases. Perspectives are given regarding the protein- and site-specific analysis of N-glycosylation, and the dissection of underlying regulatory layers and functional roles of blood protein N-glycosylation.

Influence of plasma collection tubes on N-glycome in human blood samples

Background and aims

Quantitative analysis of plasma N-glycome is a promising method for identifying disease biomarkers. This study aimed to investigate the impact of using blood collection tubes with different anticoagulants on plasma N-glycome.

Materials and methods

We used a robust mass spectrometry method to profile plasma N-glycomes in two cohorts of healthy volunteers (cohort 1, n = 16; cohort 2, n = 53). The influence of three commonly used blood collection tubes on fully characterized N-glycomic profiles were explored.

Results

Principal component analysis revealed distinct clustering of blood samples based on the collection tubes. Pairwise comparisons demonstrated significant differences between EDTA and heparin plasma in 55 out of 82 quantified N-glycan traits, and between EDTA and citrate plasma in 62 out of 82 traits. These differences encompassed various N-glycan features, including glycan type, sialylation, galactosylation, fucosylation, and bisection. Trends in N-glycan variations in citrate and heparin plasma were largely consistent compared to EDTA plasma. In correlation analysis (EDTA vs. heparin; EDTA vs. citrate), Pearson's correlation coefficients were consistently higher than 0.7 for the majority of N-glycan traits.

Conclusion

Sample matrix variations impact plasma N-glycome measurements. Caution is crucial when comparing samples from different plasma collection tubes in glycomics projects.

Noninvasive serum N-glycans associated with ovarian cancer diagnosis and precancerous lesion prediction

BACKGROUND

Ovarian cancer (OC) is one of the most common gynecological tumors with high morbidity and mortality. Altered serum N-glycome has been observed in many diseases, while the association between serum protein N-glycosylation and OC progression remains unclear, particularly for the onset of carcinogenesis from benign neoplasms to cancer.

METHODS

Herein, a mass spectrometry based high-throughput technique was applied to characterize serum N-glycome profile in individuals with healthy controls, benign neoplasms and different stages of OC. To elucidate the alterations of glycan features in OC progression, an orthogonal strategy with lectin-based ELISA was performed.

RESULTS

It was observed that the initiation and development of OC was associated with increased high-mannosylationand agalactosylation, concurrently with decreased total sialylation of serum, each of which gained at least moderately accurate merits. The most important individual N-glycans in each glycan group was H7N2, H3N5 and H5N4S2F1, respectively. Notably, serum N-glycome could be used to accurately discriminate OC patients from benign cohorts, with a comparable or even higher diagnostic score compared to CA125 and HE4. Furthermore, bioinformatics analysis based discriminative model verified the diagnostic performance of serum N-glycome for OC in two independent sets.

CONCLUSIONS

These findings demonstrated the great potential of serum N-glycome for OC diagnosis and precancerous lesion prediction, paving a new way for OC screening and monitoring.

Deep learning enhanced the diagnostic merit of serum glycome for multiple cancers

Protein glycosylation is associated with the pathogenesis of various cancers. The utilization of certain glycans in cancer diagnosis models holds promise, yet their accuracy is not always guaranteed. Here, we investigated the utility of deep learning techniques, specifically random forests combined with transfer learning, in enhancing serum glycome's discriminative power for cancer diagnosis (including ovarian cancer, non-small cell lung cancer, gastric cancer, and esophageal cancer). We started with ovarian cancer and demonstrated that transfer learning can achieve superior performance in data-disadvantaged cohorts (AUROC >0.9), outperforming the approach of PLS-DA. We identified a serum glycan-biomarker panel including 18 serum N-glycans and 4 glycan derived traits, most of which were featured with sialylation. Furthermore, we validated advantage of the transfer learning scheme across other cancer groups. These findings highlighted the superiority of transfer learning in improving the performance of glycans-based cancer diagnosis model and identifying cancer biomarkers, providing a new high-fidelity cancer diagnosis venue.

Advances in minimal residual disease monitoring in multiple myeloma

Multiple myeloma (MM) is characterized by the clonal expansion of plasma cells and the excretion of a monoclonal immunoglobulin (M-protein), or fragments thereof. This biomarker plays a key role in the diagnosis and monitoring of MM. Although there is currently no cure for MM, novel treatment modalities such as bispecific antibodies and CAR T-cell therapies have led to substantial improvement in survival. With the introduction of several classes of effective drugs, an increasing percentage of patients achieve a complete response. This poses new challenges to traditional electrophoretic and immunochemical M-protein diagnostics because these methods lack sensitivity to monitor minimal residual disease (MRD). In 2016, the International Myeloma Working Group (IMWG) expanded their disease response criteria with bone marrow-based MRD assessment using flow cytometry or next-generation sequencing in combination with imaging-based disease monitoring of extramedullary disease. MRD status is an important independent prognostic marker and its potential as a surrogate endpoint for progression-free survival is currently being studied. In addition, numerous clinical trials are investigating the added clinical value of MRD-guided therapy decisions in individual patients. Because of these novel clinical applications, repeated MRD evaluation is becoming common practice in clinical trials as well as in the management of patients outside clinical trials. In response to this, novel mass spectrometric methods that have been developed for blood-based MRD monitoring represent attractive minimally invasive alternatives to bone marrow-based MRD evaluation. This paves the way for dynamic MRD monitoring to allow the detection of early disease relapse, which may prove to be a crucial factor in facilitating future clinical implementation of MRD-guided therapy. This review provides an overview of state-of-the-art of MRD monitoring, describes new developments and applications of blood-based MRD monitoring, and suggests future directions for its successful integration into the clinical management of MM patients.

Human Plasma IgG N-Glycome Profiles Reveal a Proinflammatory Phenotype in Chronic Thromboembolic Pulmonary Hypertension

BACKGROUND

The pathological mechanism of chronic thromboembolic pulmonary hypertension (CTEPH) is not fully understood, and inflammation has been reported to be one of its etiological factors. IgG regulates systemic inflammatory homeostasis, primarily through its N-glycans. Little is known about IgG N-glycosylation in CTEPH. We aimed to map the IgG N-glycome of CTEPH to provide new insights into its pathogenesis and discover novel markers and therapies.

METHODS

We characterized the plasma IgG N-glycome of patients with CTEPH in a discovery cohort and validated our results in an independent validation cohort using matrix-assisted laser desorption/ionization time of flight mass spectrometry. Thereafter, we correlated IgG N-glycans with clinical parameters and circulating inflammatory cytokines in patients with CTEPH. Furthermore, we determined IgG N-glycan quantitative trait loci in CTEPH to reveal partial mechanisms underlying glycan changes.

RESULTS

Decreased IgG galactosylation representing a proinflammatory phenotype was found in CTEPH. The distribution of IgG galactosylation showed a strong association with NT-proBNP (N-terminal pro-B-type natriuretic peptide) in CTEPH. In line with the glycomic findings, IgG pro-/anti-inflammatory N-glycans correlated well with a series of inflammatory markers and gene loci that have been reported to be involved in the regulation of these glycans or inflammatory immune responses.

CONCLUSIONS

This is the first study to reveal the full signature of the IgG N-glycome of a proinflammatory phenotype and the genes involved in its regulation in CTEPH. Plasma IgG galactosylation may be useful for evaluating the inflammatory state in patients with CTEPH; however, this requires further validation. This study improves our understanding of the mechanisms underlying CTEPH inflammation from the perspective of glycomics.

An insight on the N-glycome of notochordal cell-rich porcine nucleus pulposus during maturation

Degeneration of the intervertebral disc is an age-related condition. It also accompanies the disappearance of the notochordal cells, which are remnants of the developmental stages of the nucleus pulposus (NP). Molecular changes such as extracellular matrix catabolism, cellular phenotype, and glycosaminoglycan loss in the NP have been extensively studied. However, as one of the most significant co- and posttranslational modifications, glycosylation has been overlooked in cells in degeneration. Here, we aim to characterize the N-glycome of young and mature NP and identify patterns related to aging. Accordingly, we isolated N-glycans from notochordal cell-rich NP from porcine discs, characterized them using a combined approach of exoglycosidase digestions and analysis with hydrophilic interaction ultra-performance liquid chromatography and mass spectrometry. We have assigned over 300 individual N-glycans for each age group. Moreover, we observed a notable abundance of antennary structures, galactosylation, fucosylation, and sialylation in both age groups. In addition, as indicated from our results, increasing outer arm fucosylation and decreasing α(2,3)-linked sialylation with aging suggest that these traits are age-dependent. Lastly, we have focused on an extensive characterization of the N-glycome of the notochordal cell-rich NP in aging without inferred degeneration, describing glycosylation changes specific for aging only. Our findings in combination with those of other studies, suggest that the degeneration of the NP does not involve identical processes as aging.

Serum protein N-glycome patterns reveal alterations associated with endometrial cancer and its phenotypes of differentiation

Background

Aberrant N-glycosylation and its involvement in pathogenesis have been reported in endometrial cancer (EC). Nevertheless, the serum N-glycomic signature of EC remains unknown. Here, we investigated serum N-glycome patterns of EC to identify candidate biomarkers.

Methods

This study enrolled 34 untreated EC patients and 34 matched healthy controls (HC) from Peking Union Medical College Hospital. State-of-the-art MS-based methods were employed for N-glycans profiling. Multivariate and univariate statistical analyses were used to identify discriminative N-glycans driving classification. Receiver operating characteristic analyses were performed to evaluate classification accuracy.

Results

EC patients displayed distinct differences in serum N-glycome and had abnormal high-mannose and hybrid-type N-glycans, fucosylation, galactosylation, and linkage-specific sialylation compared with HC. The glycan panel built with the four most discriminative and biologically important derived N-glycan traits could accurately identify EC (random forest model, the area under the curve [AUC]=0.993 [95%CI 0.955-1]). The performance was validated by two other models. Total hybrid-type N-glycans significantly associated with the differentiation types of EC could effectively stratify EC into well- or poorly-differentiated subgroups (AUC>0.8).

Conclusion

This study provides the initial evidence supporting the utility of serum N-glycomic signature as potential markers for the diagnosis and phenotyping of EC.

Single-Cell Discovery and Multiomic Characterization of Therapeutic Targets in Multiple Myeloma

Multiple myeloma (MM) is a highly refractory hematologic cancer. Targeted immunotherapy has shown promise in MM but remains hindered by the challenge of identifying specific yet broadly representative tumor markers. We analyzed 53 bone marrow (BM) aspirates from 41 MM patients using an unbiased, high-throughput pipeline for therapeutic target discovery via single-cell transcriptomic profiling, yielding 38 MM marker genes encoding cell-surface proteins and 15 encoding intracellular proteins. Of these, 20 candidate genes were highlighted that are not yet under clinical study, 11 of which were previously uncharacterized as therapeutic targets. The findings were cross-validated using bulk RNA sequencing, flow cytometry, and proteomic mass spectrometry of MM cell lines and patient BM, demonstrating high overall concordance across data types. Independent discovery using bulk RNA sequencing reiterated top candidates, further affirming the ability of single-cell transcriptomics to accurately capture marker expression despite limitations in sample size or sequencing depth. Target dynamics and heterogeneity were further examined using both transcriptomic and immuno-imaging methods. In summary, this study presents a robust and broadly applicable strategy for identifying tumor markers to better inform the development of targeted cancer therapy.

SIGNIFICANCE

Single-cell transcriptomic profiling and multiomic cross-validation to uncover therapeutic targets identifies 38 myeloma marker genes, including 11 transcribing surface proteins with previously uncharacterized potential for targeted antitumor therapy.

Analysis of monoclonal immunoglobulins from bone marrow plasma cells using immunopurification and LC-MS

Introduction

Clonal plasma cells secrete immunoglobulins, each with the exact same amino acid sequence, that are referred to as monoclonal immunoglobulins. The monoclonal heavy chain and light chain secreted from clonal plasma cells have the same molecular mass prior to the addition of post-translational modifications (PTMs) since their amino acid sequences are the same.

Objective

To examine the molecular masses of monoclonal light chains and heavy chains isolated directly from the cytoplasm of bone marrow (BM) plasma cells and compare them to the serum derived monoclonal heavy and light chains.

Methods

Using immunopurification and LC-MS we compared the molecular masses of immunoglobulins immunopurified from a patient's serum to those immunopurified from the cytoplasm of their BM plasma cells.

Results

Our findings demonstrate that the light chain molecular masses were identical whether they were obtained from serum or plasma cell cytoplasm. However, the heavy chain molecular masses did not match in bone marrow and serum due to differences in glycosylation, a common post-translational modification (PTM) found on the heavy chain.

Conclusion

The data presented here show that by using LC-MS to analyze monoclonal immunoglobulins (also referred to as miRAMM) additional phenotype information is obtained at the cellular level which is complementary to other more common techniques such as flow cytometry and histopathology.

Increased expression of CEP72 predicts poor prognosis in multiple myeloma

INTRODUCTION

Multiple myeloma (MM) is a fatal hematological malignancy and does not have adequate prognostic indicators. Previous studies indicate that CEP72 is closely related to tumorigenesis and tumor progression. However, the expression and function of CEP72 in multiple myeloma have yet to be elucidated.

METHODS

In this study, we explored the correlation between CEP72 expression and clinicopathological characteristics as well as the impacts of CEP72 expression on the survival of MM patients. In addition, PPI, GSEA and Chemotherapy drug resistance analysis identified the possible mechanism.

RESULTS

CEP72 is overexpressed in both MM patients and MM cell lines. Clinically, patients in the CEP72^high subgroup were significantly older than those in the CEP72^low subgroup (p = 0.003). Up-regulation of CEP72 was related to poor overall survival and event-free survival. PPI network showed that CEP72 was related to PCM1, KIZ, OFD1, etc. GSEA analysis showed that CEP72 was enriched in cell cycle, oocyte meiosis, protein export, lysosome and N-glycan biosynthesis pathways. Drug resistance analysis indicated that there was a positive correlation between the CEP72 expression and the IC50 values of 6-mercaptopurine, 8-chloro-adenosine, clofarabine, fludarabine and allopurinol.

CONCLUSION

High CEP72 expression was a poor prognostic factor in patients diagnosed with multiple myeloma.

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

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

Characterizing M-protein light chain glycosylation via mass spectrometry

OBJECTIVES

Monoclonal gammopathy of undetermined significance (MGUS) patients with M-proteins containing n-glycosylated light chains (GLC) have an increased risk for progression to symptomatic plasma cell disorders (PCD). Large-scale research involving the determination of glycan specific moieties is understudied due to the lack of clinically viable methods. This report documents a proof-of-concept glycan characterization method for patients with M-protein GLCs.

DESIGN AND METHODS

Twenty-three previously characterized MGUS patients with glycosylated light chains identified by MASS-FIX were used for this study. Glycosylated light chains were enriched from patient serum using light chain (LC) specific Sepharose nanobody beads (NB), followed by glycan digestion via PNGase F. Glycan moieties were derivatized on-target using Girard's reagent T for MALDI-TOF analysis and confirmed with top-down GLC LC-ESI-Q-TOF-MS analysis.

RESULTS

Intact GLC LC-ESI-Q-TOF-MS and cleaved glycan MALDI-TOF MS analysis had 100% agreement for the top three intensity glycans between spectra and 88 percent agreement for all reported glycan moieties. GLC moieties among patients were similar with fucosylation being the only notable difference. Additionally, doubly glycosylated light chains were observed in two patients.

CONCLUSIONS

The MALDI-TOF method provides the tools to characterize and evaluate GLCs in a clinical setting as it is adaptable to our clinical MASS-Fix assay, relatively cheap, and accurate in glycan moiety assignments as confirmed by top-down GLC LC-ESI-Q-TOF-MS.

Nomograms Based on Serum N-glycome for Diagnosis of Papillary Thyroid Microcarcinoma and Prediction of Lymph Node Metastasis

Non-invasive biomarkers for the diagnosis and prognosis of papillary thyroid microcarcinoma (PTMC) are still urgently needed. We aimed to characterize the N-glycome of PTMC, and establish nomograms for the diagnosis of PTMC and the prediction of lymph node metastasis (LNM). N-glycome of PTMC (LNM vs. non-LNM, capsular invasion (CI) vs. non-CI (NCI)) and matched healthy controls (HC) were quantitatively analyzed based on mass spectrometry. N-glycan traits associated with PTMC/LNM were used to create binomial logistic regression models and were visualized as nomograms. We found serum N-glycome differed between PTMC and HC in high-mannose, complexity, fucosylation, and bisection, of which, four N-glycan traits (TM, CA1, CA4, and A2Fa) were significantly associated with PTMC. The nomogram based on four traits achieved good performance for the identification of PTMC. Two N-glycan traits (CA4 and A2F0S0G) showed strong associations with LNM. The nomogram based on two traits showed relatively good performance in predicting LNM. We also found differences between CI and NCI in several N-glycan traits, which were not the same as that associated with LNM. This study reported serum N-glycosylation signatures of PTMC for the first time. Nomograms constructed from aberrant glycans could be useful tools for PTMC diagnosis and stratification.

Isomer-specific biomarker discovery in multiple myeloma with dual-derivatized N-glycans

As one of the most important post-translational modifications, protein glycosylation plays vital role in various physiological processes. With multitudinous glycosyltransferases, N-glycans present structural diversity in linkages and branching styles. Structure-specific glycan profiling may provide more potential biological information than compositional profiling. In this work, N-glycans released from human serum samples were derivatized with reduction and methylamination prior to profiling using nanoLC-ESI-MS with PGC as stationary phase. In addition, α 2-3 neuraminidase was also applied for distinguishing the linkage types of sialic acid corresponding to different isomers. Relative abundances of 280 isomeric N-glycans were compared and 20 isomers showed significant difference between multiple myeloma cases and healthy controls. ROC was performed to assess the significantly altered isomeric glycans and 6 AUCs have exceeded 0.80, providing high diagnostic accuracy for MM. PCA is also employed to establish the differences among sample sets. Furthermore, these specific isomers have also been used for early detection of multiple myeloma, presenting important clinical application value. Isomer-specific biomarker discovery in multiple myeloma with dual-derivatized N-glycans.

Comprehensive bioinformatics analysis reveals the hub genes and pathways associated with multiple myeloma

PURPOSE

While the prognosis of multiple myeloma (MM) has significantly improved over the last decade because of new treatment options, it remains incurable. Aetiological explanations and biological targets based on genomics may provide additional help for rational disease intervention.

MATERIALS AND METHODS

Three microarray datasets associated with MM were downloaded from the Gene Expression Omnibus (GEO) database. GSE125364 and GSE39754 were used as the training set, and GSE13591 was used as the verification set. The differentially expressed genes (DEGs) were obtained from the training set, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to annotate their functions. The hub genes were derived from the combined results of a protein-protein interaction (PPI) network and weighted gene coexpression network analysis (WGCNA). The receiver operating characteristic (ROC) curves of hub genes were plotted to evaluate their clinical diagnostic value. Biological processes and signaling pathways associated with hub genes were explained by gene set enrichment analysis (GSEA).

RESULTS

A total of 1759 DEGs were identified. GO and KEGG pathway analyses suggested that the DEGs were related to the process of protein metabolism. RPN1, SEC61A1, SPCS1, SRPR, SRPRB, SSR1 and TRAM1 were proven to have clinical diagnostic value for MM. The GSEA results suggested that the hub genes were widely involved in the N-glycan biosynthesis pathway.

CONCLUSION

The hub genes identified in this study can partially explain the potential molecular mechanisms of MM and serve as candidate biomarkers for disease diagnosis.

Identification of novel combined biomarkers in the diagnosis of multiple myeloma

PURPOSE

Multiple myeloma (MM) is a haematological malignant disease with a clonal proliferation of plasma cells, and timely surveillance is helpful to improve the survival rate of patients with MM. However, there is a lack of simple and effective biomarkers for the diagnosis, prognosis, and residual disease evaluation of MM.

MATERIAL & METHODS

In the detection cohort, we used the samples from six newly diagnosed MM patients and six control subjects. Plasma proteins were labelled with dimethyl reagents and enriched by lectin AANL6, then the deglycosylated peptides were identified by LC-MS/MS. Differentially expressed proteins were used for further exploration. In the validation cohort, we used 90 newly diagnosed patients with MM and 70 cases of unrelated diseases as controls. The diagnosis performance was analysed by ROC analysis using SPSS.

RESULTS

In this study, we show, using lectin blots with AANL6, that glycosylation levels were higher in MM patients than in controls. After AANL6 enrichment, we detected 58 differentially expressed proteins using quantitative proteomics. We further validated one candidate Fibulin-1 (FBLN1). Using an Elisa assay, we showed that FBLN1 expression was increased in plasma of 90 cases of MM, and which was significantly correlated with DKK1 expression. ROC analysis showed that these two markers had a 95.7% specificity for determining the diagnosis of MM.

CONCLUSION

These data suggest that the MM cases display increased glycosylation after AANL6 enrichment and that the combined expression of FBLN1 and DKK1 can be used as an effective diagnostic biomarker.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Diagnostic Potential of Plasma IgG N-glycans in Discriminating Thyroid Cancer from Benign Thyroid Nodules and Healthy Controls

Background

Novel biomarkers are urgently needed to distinguish between benign and malignant thyroid nodules and detect thyroid cancer in the early stage. The associations between serum IgG N-glycosylation and thyroid cancer risk have been revealed. We aimed to explore the potential of IgG N-glycan traits as biomarkers in the differential diagnosis of thyroid cancer.

Methods

Plasma IgG N-glycome analysis was applied to a discovery cohort followed by independent validation. IgG N-glycan profiles were obtained using a robust quantitative strategy based on matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. IgG N-glycans were relatively quantified, and classification performance was evaluated based on directly detected and derived glycan traits.

Results

Four directly detected glycans were significantly changed in thyroid cancer patients compared to that in non-cancer controls. Derived glycan traits and a classification glycol-panel were generated based on the directly detected glycan traits. In the discovery cohort, derived trait BN (bisecting type neutral N-glycans) and the glyco-panel showed potential in distinguishing between thyroid cancer and non-cancer controls with AUCs of 0.920 and 0.917, respectively. The diagnostic potential was further validated. Derived trait BN and the glycol-panel displayed “accurate” performance (AUC>0.8) in discriminating thyroid cancer from benign thyroid nodules and healthy controls in the validation cohort. Meanwhile, derived trait BN and the glycol-panel also showed diagnostic potential in detecting early-stage thyroid cancer.

Conclusions

IgG N-glycome analysis revealed N-glycomic differences that allow classification of thyroid cancer from non-cancer controls. Our results suggested that derived trait BN and the classification glyco-panel rather than single N-glycans may serve as candidate biomarkers for further validation.

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.

Current Methods of Post-Translational Modification Analysis and Their Applications in Blood Cancers

Post-translational modifications (PTMs) add a layer of complexity to the proteome through the addition of biochemical moieties to specific residues of proteins, altering their structure, function and/or localization. Mass spectrometry (MS)-based techniques are at the forefront of PTM analysis due to their ability to detect large numbers of modified proteins with a high level of sensitivity and specificity. The low stoichiometry of modified peptides means fractionation and enrichment techniques are often performed prior to MS to improve detection yields. Immuno-based techniques remain popular, with improvements in the quality of commercially available modification-specific antibodies facilitating the detection of modified proteins with high affinity. PTM-focused studies on blood cancers have provided information on altered cellular processes, including cell signaling, apoptosis and transcriptional regulation, that contribute to the malignant phenotype. Furthermore, the mechanism of action of many blood cancer therapies, such as kinase inhibitors, involves inhibiting or modulating protein modifications. Continued optimization of protocols and techniques for PTM analysis in blood cancer will undoubtedly lead to novel insights into mechanisms of malignant transformation, proliferation, and survival, in addition to the identification of novel biomarkers and therapeutic targets. This review discusses techniques used for PTM analysis and their applications in blood cancer research.

Monoclonal immunoglobulins promote bone loss in multiple myeloma

Most patients with multiple myeloma develop a severe osteolytic bone disease. The myeloma cells secrete immunoglobulins, and the presence of monoclonal immunoglobulins in the patient's sera is an important diagnostic criterion. Here, we show that immunoglobulins isolated from myeloma patients with bone disease promote osteoclast differentiation when added to human preosteoclasts in vitro, whereas immunoglobulins from patients without bone disease do not. This effect was primarily mediated by immune complexes or aggregates. The function and aggregation behavior of immunoglobulins are partly determined by differential glycosylation of the immunoglobulin-Fc part. Glycosylation analyses revealed that patients with bone disease had significantly less galactose on immunoglobulin G (IgG) compared with patients without bone disease and also less sialic acid on IgG compared with healthy persons. Importantly, we also observed a significant reduction of IgG sialylation in serum of patients upon onset of bone disease. In the 5TGM1 mouse myeloma model, we found decreased numbers of lesions and decreased CTX-1 levels, a marker for osteoclast activity, in mice treated with a sialic acid precursor, N-acetylmannosamine (ManNAc). ManNAc treatment increased IgG-Fc sialylation in the mice. Our data support that deglycosylated immunoglobulins promote bone loss in multiple myeloma and that altering IgG glycosylation may be a therapeutic strategy to reduce bone loss.

Serum Protein N-Glycosylation Signatures of Neuroblastoma

Background

Neuroblastoma is the most common extracranial childhood solid tumor which accounts for 10% of the malignancies and 15% of the cancer fatalities in children. N-glycosylation is one of the most frequent post-translation protein modification playing a vital role in numerous cancers. N-glycosylation changes in neuroblastoma patient serum have not been studied in existing reports. The comprehensive analyses of serum N-glycomics in neuroblastoma can provide useful information of potential disease biomarkers and new insights of the pathophysiology in neuroblastoma.

Methods

The total serum protein N-glycosylation was analyzed in 33 neuroblastoma patients and 40 age- and sex-matched non-malignant controls. N-glycans were enzymatically released, derivatized to discriminate linkage-specific sialic acid, purified by HILIC-SPE, and identified by MALDI-TOF-MS. Peak areas were acquired by the software of MALDI-MS sample acquisition, processed and analyzed by the software of Progenesis MALDI.

Results

Three glyco-subclasses and six individual N-glycans were significantly changed in neuroblastoma patients compared with controls. The decreased levels of high mannose N-glycans, hybrid N-glycans, and increased levels of α2,3-sialylated N-glycans, multi-branched sialylated N-glycans were observed in neuroblastoma patients. what is more, a glycan panel combining those six individual N-glycans showed a strong discrimination performance, with an AUC value of 0.8477.

Conclusions

This study provides new insights into N-glycosylation characteristics in neuroblastoma patient serum. The analyses of total serum protein N-glycosylation could discriminate neuroblastoma patients from non-malignant controls. The alterations of the N-glycomics may play a suggestive role for neuroblastoma diagnosis and advance our understanding of the pathophysiology in neuroblastoma.

Serum N-Glycomics Stratifies Bacteremic Patients Infected with Different Pathogens

Bacteremia—i.e., the presence of pathogens in the blood stream—is associated with long-term morbidity and is a potential precursor condition to life-threatening sepsis. Timely detection of bacteremia is therefore critical to reduce patient mortality, but existing methods lack precision, speed, and sensitivity to effectively stratify bacteremic patients. Herein, we tested the potential of quantitative serum N-glycomics performed using porous graphitized carbon liquid chromatography tandem mass spectrometry to stratify bacteremic patients infected with Escherichia coli (n = 11), Staphylococcus aureus (n = 11), Pseudomonas aeruginosa (n = 5), and Streptococcus viridans (n = 5) from healthy donors (n = 39). In total, 62 N-glycan isomers spanning 41 glycan compositions primarily comprising complex-type core fucosylated, bisecting N-acetylglucosamine (GlcNAc), and α2,3-/α2,6-sialylated structures were profiled across all samples using label-free quantitation. Excitingly, unsupervised hierarchical clustering and principal component analysis of the serum N-glycome data accurately separated the patient groups. P. aeruginosa-infected patients displayed prominent N-glycome aberrations involving elevated levels of fucosylation and bisecting GlcNAcylation and reduced sialylation relative to other bacteremic patients. Notably, receiver operating characteristic analyses demonstrated that a single N-glycan isomer could effectively stratify each of the four bacteremic patient groups from the healthy donors (area under the curve 0.93–1.00). Thus, the serum N-glycome represents a new hitherto unexplored class of potential diagnostic markers for bloodstream infections.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Glycomics studies using sialic acid derivatization and mass spectrometry

Proteins can undergo glycosylation during and/or after translation to afford glycoconjugates, which are often secreted by a cell or populate cell surfaces. Changes in the glycan portion can have a strong influence on a glycoconjugate and are associated with a multitude of human pathologies. Of particular interest are sialylated glycoconjugates, which exist as constitutional isomers that differ in their linkages (α2,3, α2,6, α2,8 or α2,9) between sialic acids and their neighbouring monosaccharides. In general, mass spectrometry enables the rapid and sensitive characterization of glycosylation, but there are challenges specific to identifying and (relatively) quantifying sialic acid isomers. These challenges can be addressed using linkage-specific methodologies for sialic acid derivatization, after which mass spectrometry can enable product identification. This Review is concerned with the new and important derivatization approaches reported in the past decade, which have been implemented in various mass-spectrometry-glycomics workflows and have found clinical glycomics applications. The convenience and wide applicability of the approaches make them attractive for studies of sialylation in different types of glycoconjugate.

Targeted Approaches to Inhibit Sialylation of Multiple Myeloma in the Bone Marrow Microenvironment

Aberrant glycosylation modulates different aspects of tumor biology, and it has long been recognized as a hallmark of cancer. Among the different forms of glycosylation, sialylation, the addition of sialic acid to underlying oligosaccharides, is often dysregulated in cancer. Increased expression of sialylated glycans has been observed in many types of cancer, including multiple myeloma, and often correlates with aggressive metastatic behavior. Myeloma, a cancer of plasma cells, develops in the bone marrow, and colonizes multiple sites of the skeleton including the skull. In myeloma, the bone marrow represents an essential niche where the malignant cells are nurtured by the microenvironment and protected from chemotherapy. Here, we discuss the role of hypersialylation in the metastatic process focusing on multiple myeloma. In particular, we examine how increased sialylation modulates homing of malignant plasma cells into the bone marrow by regulating the activity of molecules important in bone marrow cellular trafficking including selectins and integrins. We also propose that inhibiting sialylation may represent a new therapeutic strategy to overcome bone marrow-mediated chemotherapy resistance and describe different targeted approaches to specifically deliver sialylation inhibitors to the bone marrow microenvironment.

Glycosylation products in prostate diseases

Although prostate cancer is notable for its high incidence and mortality in men worldwide, its identification remains a challenge. Biomarkers have been useful tools for the specific detection of prostate cancer. Unfortunately, benign prostate diseases cause similar alterations in screening assays thus reducing the potential for early and specific diagnosis. Changes in glycan and glycoprotein expression have often been associated with the onset and progression of cancer. Abnormal glycans and glycoproteins have been reported as new biomarkers of prostate metabolism that can distinguish benign prostate disease and cancer in non-aggressive and aggressive stages. Carbohydrate-binding proteins known as lectins have been valuable tools to detect these changes, investigate potential biomarkers and improve our understanding aberrant glycosylation in cancer. Here we review progress in elucidating prostate disease and discuss the roles of glycans in the differential detection of benign and cancerous prostate disease. We also summarize the lectin-based tools for detecting glycosylation changes.