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Results for “glycoproteomics”

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PubMed2026

High-Throughput Proteomic and Glycoproteomic Analyses in Benign Prostatic Hyperplasia.

Benign prostatic hyperplasia (BPH) is a disease affecting the majority of aging men; 90% of men develop histological BPH by the time they reach their eighties. BPH can lead to bothersome lower urinary tract symptoms (LUTS), which may reduce quality of life. Many patients fail current treatment options and may progress to surgical intervention. Furthermore, diagnosis is reliant on symptom questionnaires and the cause of LUTS can be difficult to distinguish. Currently, BPH can only be definitively diagnosed through histological analysis of prostate tissue, which is not the standard of care. The resulting lack of clinical tissue samples is a major limitation in investigating disease pathology. Improved understanding of disease development and progression, along with objective biomarkers of disease, is needed for BPH. This investigation uses mass spectrometry (MS)-based proteomics and glycoproteomics to compare healthy prostate tissue with prostate tissue affected by BPH to address this gap in knowledge. By integrating proteomics and glycoproteomics, we identified 206 proteins and 44 glycopeptides that were significantly altered between BPH and control samples. These findings provide deeper insight into disease-associated pathways and may facilitate the identification of clinically relevant targets for further investigation.

Male↗

PubMed2026

Quantitative N-glycoproteomic analysis reveals glycosylation signatures of plasma immunoglobulin G in sepsis.

INTRODUCTION: Sepsis is a life-threatening condition resulting from organ dysfunction due to a dysregulated immune response to infection. Immunoglobulin G (IgG) plays a role in modulating immune responses. However, the precise IgG subclass-specific N-glycosylation profiles in patients with sepsis remain poorly characterized. METHODS: This study aimed to define the site-specific N-glycosylation signatures of plasma IgG subclasses in sepsis patients with different prognoses using quantitative glycoproteomics. By employing our established GlycoQuant strategy, we quantified the intact N-glycopeptides (IGPs) of IgG subclasses in 40 healthy controls and 40 sepsis patients with a clear prognosis. RESULTS: We identified 12 IGPs with altered abundances between patients with sepsis and healthy controls. After Benjamini-Hochberg (BH) correction of the 31 outcome-stratified IGP comparisons, IGP24 and IGP25 remained significant and met the prespecified fold-change criterion. Global BH correction across 124 IGP-clinical parameter correlations retained positive associations of IGP19, IGP22, and IGP23 with procalcitonin (PCT). In exploratory outcome-stratified ROC analyses, candidates were selected using the original unadjusted P-value and fold-change screen; five IGPs were evaluated, with IGP25 and IGP24 yielding the highest individual AUCs. Collectively, our findings underscore the potential of IgG subclass-specific glycosylation profiling as a novel translational approach for clinical applications in sepsis management. SIGNIFICANCE: Sepsis remains a leading cause of global mortality, with patient outcomes heavily dependent on timely diagnosis and accurate prognosis. The dysregulated host immune response, particularly involving immunoglobulins, is central to its pathophysiology. This study provides a significant advance in the field of clinical glycoproteomics by applying a quantitative, site-specific strategy to delineate the plasma IgG subclass N-glycosylation landscape in sepsis. We report, for the first time, a panel of subclass-specific intact IgG N-glycopeptides (IGPs) that are significantly altered in sepsis patients compared to healthy controls. The identified IGPs not only demonstrate diagnostic and prognostic potential but also show a significant correlation with procalcitonin, a key clinical severity index. These findings bridge a critical knowledge gap by moving beyond bulk IgG glycosylation analysis to subclass-resolved profiling, offering novel molecular insights into sepsis immunopathology. The identified glycosylation signatures hold substantial translational promise as a foundation for developing innovative, glycan-based biomarker panels to improve the precision management of this heterogeneous and life-threatening syndrome.

Humans↗

PubMed2026

Development of a High-Sensitivity Glycoproteomics Approach for Fc-Specific Quantification of IgG Core Fucosylation in Traumatic Brain Injury.

Traumatic brain injury (TBI) triggers complex neuroinflammatory cascades that involve sustained immune activation and dysregulated antibody effector functions. Immunoglobulin G (IgG) Fc N-glycosylation, particularly core fucosylation, critically modulates immune signaling through altered Fcγ receptor (FcγR) interactions; however, its role in TBI remains unexplored. Here, we developed a high-sensitivity, mass spectrometry-based glycoproteomics method for the systematic analysis of IgG Fc core fucosylation dynamics following TBI. The approach integrates Fc-specific enzymatic truncation with GlycINATOR (EndoS2) and tryptic digestion, followed by high-resolution LC-MS/MS profiling, enabling confident identification of truncated Fc glycopeptides. Furthermore, a targeted parallel reaction monitoring (PRM) strategy allowed direct quantification of core fucosylated and afucosylated glycopeptides from 10 μg of crude serum protein, eliminating the need for IgG purification. Our results reveal time-dependent and subclass-specific remodeling of IgG Fc fucosylation postinjury, characterized by an overall reduction in fucosylated species and a relative increase in afucosylation. Collectively, this study establishes a scalable analytical platform for Fc-specific glycosylation profiling and identifies IgG core fucosylation as a candidate molecular indicator of immune dysregulation in TBI, providing new insights into post-traumatic immune regulation.

Brain Injuries, Traumatic↗

PubMed2026

Multi-omic analyses of the same sample using metabolomics, lipidomics, proteomics, phosphoproteomics, and glycoproteomics.

Mass spectrometry (MS)-based multi-omics offers powerful tools to comprehensively characterize proteins, post-translational modifications, metabolites, and lipids. However, these measurements are typically performed using separate sample preparation workflows and modality-specific liquid chromatography mass spectrometry (LC-MS) platforms, limiting integration and constraining applications to small amounts of sample materials, especially scarce clinical specimens. Here, we describe a unified nano-LC-MS framework that enables metabolomic, lipidomic, proteomic, phosphoproteomic, and glycoproteomic analyses from the same starting material using a single nano-LC-MS platform, with only the chromatographic conditions, acquisition methods, and enrichment procedures tailored to each omics. This integrated strategy reduces workflow complexity and sample consumption while improves analytical continuity across molecular layers. By enabling deep multi-omics characterization from the same sample, this platform provides a practical foundation for comprehensive analysis of precious clinical samples.

Proteomics↗

PubMed2024

GRable Version 1.0: A Software Tool for Site-Specific Glycoform Analysis With Improved MS1-Based Glycopeptide Detection With Parallel Clustering and Confidence Evaluation With MS2 Information.

High-throughput intact glycopeptide analysis is crucial for elucidating the physiological and pathological status of the glycans attached to each glycoprotein. Mass spectrometry-based glycoproteomic methods are challenging because of the diversity and heterogeneity of glycan structures. Therefore, we developed an MS1-based site-specific glycoform analysis method named "Glycan heterogeneity-based Relational IDentification of Glycopeptide signals on Elution profile (Glyco-RIDGE)" for a more comprehensive analysis. This method detects glycopeptide signals as a cluster based on the mass and chromatographic properties of glycopeptides and then searches for each combination of core peptides and glycan compositions by matching their mass and retention time differences. Here, we developed a novel browser-based software named GRable for semi-automated Glyco-RIDGE analysis with significant improvements in glycopeptide detection algorithms, including "parallel clustering." This unique function improved the comprehensiveness of glycopeptide detection and allowed the analysis to focus on specific glycan structures, such as pauci-mannose. The other notable improvement is evaluating the "confidence level" of the GRable results, especially using MS2 information. This function facilitated reduced misassignment of the core peptide and glycan composition and improved the interpretation of the results. Additional improved points of the algorithms are "correction function" for accurate monoisotopic peak picking; one-to-one correspondence of clusters and core peptides even for multiply sialylated glycopeptides; and "inter-cluster analysis" function for understanding the reason for detected but unmatched clusters. The significance of these improvements was demonstrated using purified and crude glycoprotein samples, showing that GRable allowed site-specific glycoform analysis of intact sialylated glycoproteins on a large-scale and in-depth. Therefore, this software will help us analyze the status and changes in glycans to obtain biological and clinical insights into protein glycosylation by complementing the comprehensiveness of MS2-based glycoproteomics. GRable can be freely run online using a web browser via the GlyCosmos Portal (https://glycosmos.org/grable).

Glycopeptides↗

PubMed2026

Proteomic Identification of Pig Xenoantigens for Clinical Xenotransplantation.

Xenotransplantation using genetically engineered pig organs offers a promising solution to the shortage of donor organs for life-saving transplantations. However, human-preformed antibodies against unknown pig xenoantigens remain a significant barrier to successful xenotransplantation. Current methods for characterizing these antibodies or xenoantigens are limited to cellular-level cross-match assays. In this study, we developed a novel approach to identify pig xenoantigens, including peptide and glycopeptide epitopes, that react with human-preformed antibodies. First, human-preformed antibodies against xenoantigens were enriched from plasma using immobilized pig kidney proteins. The enriched antibodies were then immobilized and used to isolate pig kidney proteins, peptides, and intact glycopeptides, followed by liquid chromatography-tandem mass spectrometry analysis. This dual-level approach identified 221 peptides corresponding to 153 proteins, with a significant enrichment of plasma membrane and extracellular proteins. Notably, 11 peptides were unique to pig sequences, suggesting their potential role in driving xenogeneic immune responses. Glycoproteomic analysis identified 122 intact glycopeptides, predominantly complex/hybrid glycoforms, and Neu5Gc-containing glycans. Our method effectively identifies peptides and intact glycopeptides reactive to human-preformed antibodies, providing critical insights for discovering xenoantigens. These findings could guide genetic engineering strategies and enhance recipient candidate screening for xenotransplantation, ultimately increasing the feasibility and success of xenogeneic organ transplantation.

Animals↗

PubMed2026

Proteomic and metabolomic profiling reveals dysregulation of immune states, mucin-type glycosylation and steroid metabolism in extramammary Paget's disease.

BACKGROUND: Extramammary Paget's disease is a rare cutaneous adenocarcinoma characterized by mucin-rich Paget cells and chronic inflammation, yet its molecular basis remains unclear. OBJECTIVE: To systematically characterize the proteomic and metabolomic landscape of EMPD, uncover immune heterogeneity, and identify molecular pathways underlying tumor progression and microenvironment remodeling. METHODS: We performed integrated proteomic and metabolomic analyses on 92 male tumor patients and 30 healthy controls, identifying 10,217 proteins and 1466 metabolites. RESULTS: Extramammary Paget's disease lesions exhibited broad activation of inflammatory pathways. Immune profiling further uncovered substantial inflammatory heterogeneity, delineating immune-cold and immune-hot subtypes, with the latter associated with stronger invasive potential. Aberrant mucin-type glycosylation was also prominent, featuring Tn-modified MUC1 and MUC5AC accompanied by elevated GALNT7, GALNT6, GALNT4, and ST6GAL1, which correlated with inflammatory intensity. Metabolomic data demonstrated elevated levels of testosterone, dehydroepiandrosterone, and related intermediates in tumor tissues, indicating an androgen-enriched metabolic profile in extramammary Paget's disease. CONCLUSION: These findings reveal immune, glycoproteomic, and metabolomic pathways in extramammary Paget's disease pathogenesis and provide novel insights for molecular classification and therapeutic targeting.

Humans↗

PubMed2024

ST3GAL1 Promotes Malignant Phenotypes in Intrahepatic Cholangiocarcinoma.

Intrahepatic cholangiocarcinoma (iCCA) has a poor prognosis, and elucidation of the molecular mechanisms underlying iCCA malignancy is of great significance. Glycosylation, an important post-translational modification, is closely associated with tumor progression. Altered glycosylation, including aberrant sialylation resulting from abnormal expression of sialyltransferases (STs) and neuraminidases (NEUs), is a significant feature of cancer cells. However, there is limited information on the roles of STs and NEUs in iCCA malignancy. Here, utilizing our proteogenomic resources from a cohort of 262 patients with iCCA, we identified ST3GAL1 as a prognostically relevant molecule in iCCA. Moreover, overexpression of ST3GAL1 promoted proliferation, migration, and invasion and inhibited apoptosis of iCCA cells in vitro. Through proteomic analyses, we identified the downstream pathway potentially regulated by ST3GAL1, which was the NF-κB signaling pathway, and further demonstrated that this pathway was positively correlated with malignancy in iCCA cells. Notably, glycoproteomics showed that O-glycosylation was changed in iCCA cells with high ST3GAL1 expression. Importantly, the altered O-glycopeptides underscored the potential utility of O-glycosylation profiling as a discriminatory marker for iCCA cells with ST3GAL1 overexpression. Additionally, miR-320b was identified as a post-transcriptional regulator of ST3GAL1, capable of suppressing ST3GAL1 expression and then reducing the proliferation, migration, and invasion abilities of iCCA cell lines. Taken together, these results suggest ST3GAL1 could serve as a promising therapeutic target for iCCA.

Female↗

PubMed2025

Multi-omic profiling of intraductal papillary neoplasms of the pancreas reveals distinct patterns and potential markers of progression.

To enable early detection of pancreatic cancer from precancerous lesions, we analyze proteins and glycoproteins from 64 intraductal papillary mucinous neoplasms (IPMNs), 55 cyst fluid samples, 104 pancreatic ductal adenocarcinomas (PDACs), and various types of normal samples using mass spectrometry. High-grade IPMNs show enrichment of glycosylation level and tumor progression pathways compared to low-grade lesions. High-grade IPMN associated proteins, such as PLOD3, IRS2, LGALS9, and Trop-2, are identified and validated using immunolabeling and laser microdissection. Some high-grade associated proteins are also detected in pancreatic cyst fluids, which allows us to link proteins and glycoproteins expressed in neoplastic cells to clinically accessible biospecimens. Altered glycosylation level of extracellular matrix (ECM) proteins is observed in IPMNs compared to normal ducts. Additionally, we identify a subset of IPMNs with PDAC-like features, including elevated expression of ECM proteins. These findings offer insight into progression-associated proteins and emphasize the diagnostic and therapeutic potential of these proteins in pancreatic tumors.

Humans↗

PubMed2026

Proteogenomic analysis of pediatric and AYA high-grade glioma reveals age-dependent biology, female-male differences, and kinase targets.

High-grade gliomas (HGGs) in children and adolescents and young adults (AYA) exhibit distinct biology across the neurodevelopmental spectrum. To dissect tumor-intrinsic molecular characteristics independent of developmental variation, we perform comprehensive proteogenomic analyses of tumors from 112 HGG patients aged 0-40 years. Our multi-omics analysis identifies two AYA subgroups-adolescents (aged 15-26 years) and young adults (aged 26-40 years)-with distinct molecular profiles and survival outcomes. Tumor-normal comparisons and survival modeling highlight roles of oxidative phosphorylation and neuronal system biology in glioma progression. Causal network analysis and cell line studies provide a rationale for personalized therapies targeting candidate kinases, such as CDK8. Survival modeling, clustering, and immune-landscape analyses identify proteins, post-translational modifications, and immune signatures linked to outcomes and reveal clinically relevant differences between male and female patients.

adolescent and young adult glioma↗