Stage Dependence, Cell-Origin Independence, and Prognostic Capacity of Serum Glycan Fucosylation, β1-4 Branching, β1-6 Branching, and α2-6 Sialylation in Cancer

Golgi apparatus targeted therapy in cancer: Are we there yet?

Membrane trafficking within the Golgi apparatus plays a pivotal role in the intracellular transportation of lipids and proteins. Dysregulation of this process can give rise to various pathological manifestations, including cancer. Exploiting Golgi defects, cancer cells capitalise on aberrant membrane trafficking to facilitate signal transduction, proliferation, invasion, immune modulation, angiogenesis, and metastasis. Despite the identification of several molecular signalling pathways associated with Golgi abnormalities, there remains a lack of approved drugs specifically targeting cancer cells through the manipulation of the Golgi apparatus. In the initial section of this comprehensive review, the focus is directed towards delineating the abnormal Golgi genes and proteins implicated in carcinogenesis. Subsequently, a thorough examination is conducted on the impact of these variations on Golgi function, encompassing aspects such as vesicular trafficking, glycosylation, autophagy, oxidative mechanisms, and pH alterations. Lastly, the review provides a current update on promising Golgi apparatus-targeted inhibitors undergoing preclinical and/or clinical trials, offering insights into their potential as therapeutic interventions. Significantly more effort is required to advance these potential inhibitors to benefit patients in clinical settings.

High-throughput analysis of glycan sorting into extracellular vesicles

Extracellular vesicles (EVs) are cell-released vesicles that mediate intercellular communication by transferring bioactive cargo. Protein and RNA sorting into EVs has been extensively assessed, while selective enrichment of glycans in EVs remains less explored. In this study, a mass spectrometry-based approach, glycan node analysis (GNA), was applied to broadly assess the sorting of glycan features into EVs. Two metastatic variants (lung and bone) generated in mouse modes from the MDA-MB-231 human breast cancer cell line were assessed, as these EVs are known to contain distinct organotropic biomolecules. EVs were isolated from conditioned cell culture medium by tangential flow filtration and authenticated by standard techniques. GNA analysis revealed selective enrichment of several glycan features in EVs compared to the originating cells, particularly those associated with binding to the extracellular matrix, which was also observed in EVs from the parental MDA-MB-231 cell line (human pleural metastases). The bone-tropic variant displayed enrichment of distinct EV glycan features compared to the lung-tropic one. Additionally, the metastatic variants generated in mouse models displayed reduced EV glycan sorting compared to the parental metastatic cell line. This study represents the first comprehensive assessment of differences in glycan features between EVs and originating cells and provides evidence that the diversity of EV glycan sorting is reduced upon generation of variant cell lines in mouse models. Future research is likely to uncover novel mechanisms of EV glycan sorting, shed light on glycan features for EV authentication or biomarker purposes, and assess functional roles of the EV glycocode in (patho)physiology.

Glycan node profiling of soluble and membrane glycoproteins in whole cell lysates

Glycan node analysis (GNA) is a molecularly bottom-up glycomics technique based on the relative quantification of glycan linkage-specific monosaccharide units ("glycan nodes"). It was originally applied to blood plasma/serum, where it detected and predicted progression, reoccurrence, and survival in different types of cancer. Here, we have adapted this technology to previously inaccessible membrane glycoproteins from cultured cells. The approach is facilitated by methanol/chloroform precipitation of cell lysates and a "liquid phase permethylation" (LPP) procedure. LPP gave better signal-to-noise, yield and precision for most of the glycan nodes from membrane glycoproteins/glycolipids than the conventional solid phase permethylation approach. This GNA approach in cell lysates revealed that specific glycan features such as antennary fucosylation, N-glycan branching, and α2,6-sialylation were elevated in hepatocellular carcinoma (HepG2) cells relative to leukemia cells (THP-1 and K562) and normal donor PBMCs. Additional nodes commonly associated with glycolipids were elevated in the leukemia cells relative to HepG2 cells and PBMCs. Exposure of HepG2 cells to a fucosyltransferase inhibitor resulted in a significant reduction in the relative abundance of 3,4-substituted GlcNAc, which represents antennary fucosylation-providing further proof-of-concept that downregulation of glycosyltransferase activity is detected by shifts in glycan node expression-now detectable in membrane glycoproteins.

Targeting protein glycosylation to regulate inflammation in the respiratory tract: novel diagnostic and therapeutic candidates for chronic respiratory diseases

Protein glycosylation is a widespread posttranslational modification that can impact the function of proteins. Dysregulated protein glycosylation has been linked to several diseases, including chronic respiratory diseases (CRDs). CRDs pose a significant public health threat globally, affecting the airways and other lung structures. Emerging researches suggest that glycosylation plays a significant role in regulating inflammation associated with CRDs. This review offers an overview of the abnormal glycoenzyme activity and corresponding glycosylation changes involved in various CRDs, including chronic obstructive pulmonary disease, asthma, cystic fibrosis, idiopathic pulmonary fibrosis, pulmonary arterial hypertension, non-cystic fibrosis bronchiectasis, and lung cancer. Additionally, this review summarizes recent advances in glycomics and glycoproteomics-based protein glycosylation analysis of CRDs. The potential of glycoenzymes and glycoproteins for clinical use in the diagnosis and treatment of CRDs is also discussed.

Glycan Node Analysis Detects Varying Glycosaminoglycan Levels in Melanoma-Derived Extracellular Vesicles

Extracellular vesicles (EVs) play important roles in (patho)physiological processes by mediating cell communication. Although EVs contain glycans and glycosaminoglycans (GAGs), these biomolecules have been overlooked due to technical challenges in comprehensive glycome analysis coupled with EV isolation. Conventional mass spectrometry (MS)-based methods are restricted to the assessment of N-linked glycans. Therefore, methods to comprehensively analyze all glyco-polymer classes on EVs are urgently needed. In this study, tangential flow filtration-based EV isolation was coupled with glycan node analysis (GNA) as an innovative and robust approach to characterize most major glyco-polymer features of EVs. GNA is a molecularly bottom-up gas chromatography-MS technique that provides unique information that is unobtainable with conventional methods. The results indicate that GNA can identify EV-associated glyco-polymers that would remain undetected with conventional MS methods. Specifically, predictions based on GNA identified a GAG (hyaluronan) with varying abundance on EVs from two different melanoma cell lines. Enzyme-linked immunosorbent assays and enzymatic stripping protocols confirmed the differential abundance of EV-associated hyaluronan. These results lay the framework to explore GNA as a tool to assess major glycan classes on EVs, unveiling the EV glycocode and its biological functions.

Fractionation and characterization of sialyl linkage isomers of serum N-glycans by CE-MS

Structural isomers of sialylated N-glycans contribute to the diversity of the N-glycome and to a range of biological functions. Sialyl linkage isomers can be readily distinguished by mass spectrometry with mass differences between α2,3- and α2,6-linkages generated by a two-step sialic acid linkage-specific alkylamidation. To improve the identification of N-glycans from complex mixtures, we added a delactonization step after the first alkylamidation step, which regenerates negatively charged carboxylic acids on α2,3-sialic acids. N-glycan isomers with α2,3-sialic acids are then fractionated by ion-exchange chromatography prior to the second alkylamidation step. With this modified alkylamidation method, sialylated N-glycans were enriched and stabilized for structural characterization by capillary electrophoresis-mass spectrometry and tandem mass spectrometry. We identified 52 sialylated N-glycan structures, including 107 linkage isomers, in human serum and confirmed the presence of positional isomers of specific sialyl linkage isomers. Due to the reduced sample complexity after ion-exchange fractionation and CE separation, substructural features of N-glycans were rapidly evaluated and included core- and antenna-fucosylation and poly-lactosamine.

Oxidized-Desialylated Low-Density Lipoprotein Inhibits the Antitumor Functions of Lymphokine Activated Killer Cells

Elevated concentrations of circulating low density lipoprotein (LDL) that is abnormally oxidized and desialylated is both a precursor to and a hallmark of atherosclerosis. Peripheral blood mononuclear cells (PBMCs) treated in vitro with interleukin-2 (IL-2) become lymphokine activated killer (LAK) cells, the primary effectors of which are NK cells and NKT cells. LAK cells display antitumor functions such as increased cytotoxicity and IFN-γ production, and they have been evaluated as a potential cancer therapeutic. Atherosclerotic processes may influence innate immunity against cancer. Because prior studies have shown that low density lipoprotein (LDL) reduces T-cell and NK cell antitumor functions, we asked whether oxidized-desialylated LDL affects the functionality of LAK cells in vitro. We show here that LAK cells take up oxidized-desialylated LDL to a significantly greater extent than native LDL over a period of 72 hours. This resulted in a significant downregulation of LAK cell cytotoxicity against K562 cells. In particular, the expression of IFN-γ, CD56, and NKG2D were reduced upon oxidized-desialylated LDL treatment of LAK cells and, conversely, their expression was enhanced with native LDL. It was also observed that as the number of CD56 and NKG2D positive cells decreased upon treatment with oxidized-desialylated LDL, the number of CD3 positive cells increased in proportion. Additionally, only a slight inhibition of LAK cell cytotoxicity was observed with desialylation alone of LDL, and no significant inhibition was observed with oxidation alone of LDL. Thus, this study describes a new role of oxidized-desialylated LDL as an inhibitor of the antitumor functions of LAK cells. These observations have implications for how atherosclerosis processes, namely oxidation and desialylation of LDL, may influence LAK cell antitumor activity.

Glycosylation Profiling of Glycoproteins Secreted from Cultured Cells Using Glycan Node Analysis and GC-MS

Glycan "node" analysis is the process by which pooled glycans within complex biological samples are chemically deconstructed in a way that facilitates the analytical quantification of uniquely linked monosaccharide units (glycan "nodes"). It is based on glycan methylation analysis (a.k.a. linkage analysis) that has historically been applied to pre-isolated glycans. Thus, when using glycan node analysis, unique glycan features within whole biospecimens such as "core fucosylation," "α2-6 sialylation," "β1-6 branching," "β1-4 branching," and "bisecting GlcNAc," are captured as single analytical signals by GC-MS. Here we describe the use of this methodology in cell culture supernatant and in the analysis of IgG (alpha-1 antitrypsin) glycans. The effect of IL-6 and IL-1β cytokines on secreted hepatocyte protein glycan features is demonstrated; likewise, the impact of neuraminidase treatment of IgG is illustrated. For the majority of glycan nodes, the assay is consistent and reproducible on a day-to-day basis; because of this, relatively subtle shifts in the relative abundance of glycan features can be captured using this approach.

Quantitation of sex-specific serum N-glycome changes in expression level during mouse aging based on Bionic Glycome method

Studying the changes of serum N-glycome during mouse aging is beneficial to explore the molecular basis behind the alterations reported in human. However, such studies remainscarce and lack some information such as sialylation due to the method limitation. Here, we introduced Bionic Glycome method to quantify the serum N-glycome changes during C57BL/6 mouse aging (from the pubertal period to the old age stage). This technique enabled reliable and comprehensive quantitation of the expression level changes of more than 20 N-glycans in mouse serum at 12 time points in both genders for the first time, involving the analysis of sialic acid and its different linkages. The results demonstrated that the expression level of total glycans increased from middle age to old age. Interestingly, sex-specific N-glycome profiles and alterations were observed. Female mice showed higher level of serum fucosylation and lower level of serum afucosylation than male mice (fucosylation: p < 1.0E-6; afucosylation: p < 1.0E-6). Obviously, higher increase of serum fucosylation level was found in female mice than in male mice from middle age to old age. In addition, the opposite alterations of the afucosylated glycans with α2,3-linked sialic acid and those only with α2,6-linked sialic acid were observed at old age in male mice. These findings suggested that N-glycome could be a valuable target for investigating aging and possible contributors to aging.

Extracellular Vesicles in Cancer Detection: Hopes and Hypes

Early cancer diagnosis is critical for improving patient survival and mortality rates, but most diagnostics on solid tumors rely on imaging tests with limited sensitivity and specificity to identify potential cases, which are then confirmed by tissue biopsies. However, this process is usually not suitable for cancer screening or evaluation of tumor responses to treatment. Liquid biopsies have the potential to bridge this gap, but few such assays have been approved for cancer applications. Extracellular vesicles hold particular promise for liquid biopsy diagnostics but are currently limited by the lack of robust methods for isolation and analysis. New isolation and analysis techniques, however, show promise to improve the clinical utility of extracellular vesicle-based cancer diagnosis.

Glycan Node Analysis of Plasma-Derived Extracellular Vesicles

Blood plasma is a readily accessible source of extracellular vesicles (EVs), i.e., cell-secreted nanosized carriers that contain various biomolecules, including glycans. Previous studies have demonstrated that glycans play a major role in physiological and pathological processes, and certain plasma glycans have been associated with disease conditions. However, glycome studies have been limited by a lack of analytical techniques with the throughput capacity necessary to study hundreds of clinical samples. This study is the first to characterize the EV plasma glycome based on all major glycan classes. The results based on glycan node analysis revealed, as expected, that plasma-derived EVs have distinct glycan features from donor-matched whole plasma. Specifically, glycan nodes corresponding to those observed in chondroitin sulfate, dermatan sulfate, type I keratan sulfate, and type II keratan sulfate were enriched on EVs. The identification of specific differences in glycan features in plasma vs. plasma-derived EVs is relevant for understanding the physiological role of EVs and as a reference for future diagnostic studies. Additionally, the results indicate that EV glycan nodes do not substantially differ among a small set of healthy donors. These results lay the framework for the further evaluation of all EV glycan classes as diagnostic markers, therapeutic targets, and biologically active components in health and disease.

So You Discovered a Potential Glycan-Based Biomarker; Now What? We Developed a High-Throughput Method for Quantitative Clinical Glycan Biomarker Validation

Glycomic-based approaches to discover potential biomarkers have shown great promise in their ability to distinguish between healthy and diseased individuals; these methods can identify when aberrant glycosylation is significant, but they cannot practically be adapted into widely implemented diagnostic assays because they are too complex, expensive, and low-throughput. We have developed a new strategy that addresses challenges associated with sample preparation, sample throughput, instrumentation needs, and data analysis to transfer the valuable knowledge provided by protein glycosylation into a clinical environment. Notably, the detection limits of the assay are in the single-digit picomole range. Proof of principle is demonstrated by quantifying the changes in the sialic acid content in fetuin. As the sialic acid content in proteins varies in a number of disease states, this example demonstrates the utility of the method for biomarker analysis. Furthermore, the developed method can be adapted to other biologically important saccharides, affording a broad array of quantitative glycomic analyses that are accessible in a high-throughput, plate-reader format. These studies enable glycomic-based biomarker discovery efforts to transition through the difficult landscape of developing a potential biomarker into a clinical assay.

High Throughput Multiplex SNP-analysis in Chronic Obstructive Pulmonary Disease and Lung Cancer

Background:

A number of human inflammatory diseases and tumors have been shown to cause alterations in the glycosylation pattern of plasma proteins in a specific manner. These highly variable and versatile post-translational modifications finetune protein functions by influencing sorting, folding, enzyme activity and subcellular localization. However, relatively little is known about regulatory factors of this procedure and about the accurate causative connection between glycosylation and disease.

Objective:

The aim of the present study was to investigate whether certain single nucleotide polymorphisms (SNPs) in genes encoding glycosyltransferases and glycosidases could be associated with elevated risk for chronic obstructive pulmonary disease (COPD) and lung adenocarcinoma.

Methods:

A total of 32 SNPs localized in genes related to N-glycosylation were selected for the association analysis. Polymorphisms with putative biological functions (missense or regulatory variants) were recruited. SNPs were genotyped by a TaqMan OpenArray platform. A single base extension-based method in combination with capillary gel electrophoresis was used for verification.

Results:

The TaqMan OpenArray approach provided accurate and reliable genotype data (global call rate: 94.9%, accuracy: 99.6%). No significant discrepancy was detected between the obtained and expected genotype frequency values (Hardy–Weinberg equilibrium) in the healthy control sample group in case of any SNP confirming reliable sampling and genotyping. Allele frequencies of the rs3944508 polymorphism localized in the 3’ UTR of the MGAT5 gene significantly differed between the sample groups compared.

Conclusion:

Our results suggest that the rs34944508 SNP might modulate the risk for lung cancer by influencing the expression of MGAT5. This enzyme catalyzes the addition of N-acetylglucosamine (GlcNAc) in beta 1-6 linkage to the alpha-linked mannose of biantennary N-linked oligosaccharides, thus, increasing branching that is the characteristic of invasive malignancies.

Quantification of the α2-6 Sialic Acid Linkage in Branched N-Glycan Structures with Capillary Nanogel Electrophoresis

Sialylation and sialic acid linkage in N-glycans are markers of disease but are analytically challenging to quantify. A capillary electrophoresis method is reported that integrates a unique combination of enzymes and lectins to modify sialylated N-glycans in real time in the capillary so that N-glycan structures containing α2-6-linked sialic acid are easily separated, detected, and quantified. In this study, N-glycans were sequentially cleaved by enzymes at the head of the separation capillary so that the presence of α2-6-linked sialic acids corresponded to a shift in the analyte migration time in a manner that enabled interpretation of the N-glycan structure. Following injection, only afucosylated N-glycan structures were passed through enzyme zones that contained α2-3 sialidase, followed by β1-3,4 galactosidase, which cleaved any terminal α2-3-linked sialic acid and underlying galactose yielding a terminal N-acetyl glucosamine. With this treatment complete, a third zone of α2-3,6,8 sialidase converted the remaining α2-6-linked sialic acid to terminal galactose. With these enzyme processing steps the α2-6-linked sialic acid residues on an N-glycan correlated directly to the number of terminal galactose residues that remained. The number of terminal galactose residues could be interpreted as a stepwise decrease in the migration time. Complex N-glycans from α-1-acid glycoprotein were analyzed using this approach, revealing that a limited number of α2-6-linked sialic acids were present with biantennary, triantennary, and tetraantennary N-glycans of α-1-acid glycoprotein generally containing 0 or 1 α2-6-linked sialic acid.

Diagnostic and Prognostic Performance of Blood Plasma Glycan Features in the Women Epidemiology Lung Cancer (WELCA) Study

Lung cancer is the leading cause of cancer death in women living in the United States, which accounts for approximately the same percentage of cancer deaths in women as breast, ovary, and uterine cancers combined. Targeted blood plasma glycomics represents a promising source of noninvasive diagnostic and prognostic biomarkers for lung cancer. Here, 208 samples from lung cancer patients and 207 age-matched controls enrolled in the Women Epidemiology Lung Cancer (WELCA) study were analyzed by a bottom-up glycan "node" analysis approach. Glycan features, quantified as single analytical signals, including 2-linked mannose, α2-6 sialylation, β1-4 branching, β1-6 branching, 4-linked GlcNAc, and antennary fucosylation, exhibited abilities to distinguish cases from controls (ROC AUCs: 0.68-0.92) and predict survival in patients (hazard ratios: 1.99-2.75) at all stages. Notable alterations of glycan features were observed in stages I-II. Diagnostic and prognostic glycan features were mostly independent of smoking status, age, gender, and histological subtypes of lung cancer.

Delta-S-Cys-Albumin: A Lab Test that Quantifies Cumulative Exposure of Archived Human Blood Plasma and Serum Samples to Thawed Conditions

Exposure of blood plasma/serum (P/S) to thawed conditions (> -30 °C) can produce biomolecular changes that skew measurements of biomarkers within archived patient samples, potentially rendering them unfit for molecular analysis. Because freeze-thaw histories are often poorly documented, objective methods for assessing molecular fitness before analysis are needed. We report a 10-μl, dilute-and-shoot, intact-protein mass spectrometric assay of albumin proteoforms called "ΔS-Cys-Albumin" that quantifies cumulative exposure of archived P/S samples to thawed conditions. The relative abundance of S-cysteinylated (oxidized) albumin in P/S increases inexorably but to a maximum value under 100% when samples are exposed to temperatures > -30 °C. The difference in the relative abundance of S-cysteinylated albumin (S-Cys-Alb) before and after an intentional incubation period that drives this proteoform to its maximum level is denoted as ΔS-Cys-Albumin. ΔS-Cys-Albumin in fully expired samples is zero. The range (mean ± 95% CI) observed for ΔS-Cys-Albumin in fresh cardiac patient P/S (n = 97) was, for plasma 12-29% (20.9 ± 0.75%) and for serum 10-24% (15.5 ± 0.64%). The multireaction rate law that governs S-Cys-Alb formation in P/S was determined and shown to predict the rate of formation of S-Cys-Alb in plasma and serum samples-a step that enables back-calculation of the time at which unknown P/S specimens have been exposed to room temperature. A blind challenge demonstrated that ΔS-Cys-Albumin can detect exposure of groups (n = 6 each) of P/S samples to 23 °C for 2 h, 4 °C for 16 h, or -20 °C for 24 h-and exposure of individual specimens for modestly increased times. An unplanned case study of nominally pristine serum samples collected under NIH-sponsorship demonstrated that empirical evidence is required to ensure accurate knowledge of archived P/S biospecimen storage history.

The Aristotle Classifier: Using the Whole Glycomic Profile To Indicate a Disease State

"The totality is not, as it were, a mere heap, but the whole is something besides the parts."-Aristotle. We built a classifier that uses the totality of the glycomic profile, not restricted to a few glycoforms, to differentiate samples from two different sources. This approach, which relies on using thousands of features, is a radical departure from current strategies, where most of the glycomic profile is ignored in favor of selecting a few features, or even a single feature, meant to capture the differences in sample types. The classifier can be used to differentiate the source of the material; applicable sources may be different species of animals, different protein production methods, or, most importantly, different biological states (disease vs healthy). The classifier can be used on glycomic data in any form, including derivatized monosaccharides, intact glycans, or glycopeptides. It takes advantage of the fact that changing the source material can cause a change in the glycomic profile in many subtle ways: some glycoforms can be upregulated, some downregulated, some may appear unchanged, yet their proportion-with respect to other forms present-can be altered to a detectable degree. By classifying samples using the entirety of their glycan abundances, along with the glycans' relative proportions to each other, the "Aristotle Classifier" is more effective at capturing the underlying trends than standard classification procedures used in glycomics, including PCA (principal components analysis). It also outperforms workflows where a single, representative glycomic-based biomarker is used to classify samples. We describe the Aristotle Classifier and provide several examples of its utility for biomarker studies and other classification problems using glycomic data from several sources.

Optimized Fragmentation for Quantitative Analysis of Fucosylated N-Glycoproteins by LC-MS-MRM

Quantitative analysis of site specific glycoforms of proteins is technically challenging but highly desirable; resolution of the fucosylated glycoforms is of particular interest due to their biological importance. In this study, we developed a sensitive and specific LC-MS-MRM quantification method that distinguishes the outer arm and core fucosylated configurations of the N-glycopeptides. We take advantage of limited fragmentation of the glycopeptides at low collision energy CID to produce linkage-specific Y-ions. We select these informative ions as MRM transitions for the quantification of the outer arm and total fucosylation of 12 fucosylated glycoforms of 9 glycopeptides in 7 plasma proteins. Our workflow showed improved sensitivity and specificity of quantification of the glycopeptides compared to oxonium ion transitions which allowed us to quantify the glycoforms directly in plasma or serum without fractionation of the samples or glycopeptide enrichment. A pilot study of fucosylation in liver cirrhosis of the HCV and NASH etiologies confirms the quantitative capabilities of the method and shows that liver cirrhosis is consistently associated with increased outer arm fucosylation of majority of the analyzed proteins. The results show that the outer arm fucosylation of the A2G2F1 glycoform of the VDKDLQSLEDILHQVENK peptide of fibrinogen increases greater than 10-fold in the HCV and NASH patients compared to healthy controls.

Behavior of blood plasma glycan features in bladder cancer

Despite systemic therapy and cystectomy, bladder cancer is characterized by a high recurrence rate. Serum glycomics represents a promising source of prognostic markers for monitoring patients. Our approach, which we refer to as "glycan node analysis", constitutes the first example of molecularly "bottom-up" glycomics. It is based on a global glycan methylation analysis procedure that is applied to whole blood plasma/serum. The approach detects and quantifies partially methylated alditol acetates arising from unique glycan features such as α2-6 sialylation, β1-4 branching, and core fucosylation that have been pooled together from across all intact glycans within a sample into a single GC-MS chromatographic peak. We applied this method to 122 plasma samples from former and current bladder cancer patients (n = 72 former cancer patients with currently no evidence of disease (NED); n = 38 non-muscle invasive bladder cancer (NMIBC) patients; and n = 12 muscle invasive bladder cancer (MIBC) patients) along with plasma from 30 certifiably healthy living kidney donors. Markers for α2-6 sialylation, β1-4 branching, β1-6 branching, and outer-arm fucosylation were able to separate current and former (NED) cases from certifiably healthy controls (ROC curve c-statistics ~ 0.80); but NED, NMIBC, and MIBC were not distinguished from one another. Based on the unexpectedly high levels of these glycan nodes in the NED patients, we hypothesized that recurrence of this disease could be predicted by some of the elevated glycan features. Indeed, α2-6 sialylation and β1-6 branching were able to predict recurrence from the NED state using a Cox proportional hazards regression model adjusted for age, gender, and time from cancer. The levels of these two glycan features were correlated to C-reactive protein concentration, an inflammation marker and known prognostic indicator for bladder cancer, further strengthening the link between inflammation and abnormal plasma protein glycosylation.