Dataset Information

Serum N-glycomics with nanoLC-QToF LC-MS/MS reveals N-glycan biomarkers for glioblastoma, meningioma, and high-grade meningioma

ABSTRACT: Alteration of glycosylation in cancer cells leaded to the expression of tumor-associated glycans that could be used as a biomarker for diagnosis and prognostic prediction of the diseases. In this study, we used nanoLC-QToF LC-MS/MS for the identification of serum N-glycan biomarkers for detection of brain tumors. We identified the increase of sialylated N-glycans and decrease of fucosylated N-glycans in serum of patients with glioblastoma (GBM) and meningioma (MG) compared with healthy persons.

INSTRUMENT(S): 6520A Quadrupole Time-of-Flight LC/MS

ORGANISM(S): Homo Sapiens (ncbitaxon:9606)

SUBMITTER: Carlito B. Lebrilla

PROVIDER: MSV000096282 | MassIVE | Sun Nov 03 21:53:00 GMT 2024

REPOSITORIES: MassIVE

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Publications

Serum N-Glycomics with Nano-LC-QToF LC-MS/MS Reveals N-Glycan Biomarkers for Glioblastoma, Meningioma, and High-Grade Meningioma.

Silsirivanit Atit A Alvarez Michael Russelle S MRS Grijaldo-Alvarez Sheryl Joyce SJ Gogte Riya R Kitkhuandee Amnat A Piyawattanametha Nontaphon N Seubwai Wunchana W Luang Sukanya S Panawan Orasa O Mahalapbutr Panupong P Vaeteewoottacharn Kulthida K Sawanyawisuth Kanlayanee K Let-Itthiporn Worachart W Saengboonmee Charupong C Duangthongphon Pichayen P Jingjit Kritsakorn K Pankongsap Anuchit A Waraasawapati Sakda S Aphivatanasiri Chaiwat C Lebrilla Carlito B CB

Journal of proteome research 20250205 3

Alteration of glycosylation in cancer cells leads to the expression of tumor-associated glycans, which can be used as biomarkers for diagnosis and prognostic prediction of diseases. In this study, we used nano-LC-QToF to identify serum N-glycan biomarkers for the detection of brain tumors. We observed an increase in sialylated N-glycans and a decrease in fucosylated N-glycans in the serum of patients with glioblastoma (GBM) and meningioma (MG) compared to healthy individuals. In GBM, a combinati ...[more]

PMID: 39905713

Similar Datasets

Project description:The intrinsic nature of glycosylation, namely nontemplate encoded, stepwise elongation and termination with a diverse range of isomeric glyco-epitopes (glycotopes), translates into ambiguity in most cases of mass spectrometry (MS)-based glycomic mapping. It is arguable that whether one needs to delineate every single glycomic entity, which may be counterproductive. Instead, one should focus on identifying as many structural features as possible that would collectively define the glycomic characteristics of a cell or tissue, and how these may change in response to self-programmed development, immuno-activation, and malignant transformation. We have been pursuing this line of analytical strategy that homes in on identifying the terminal sulfo-, sialyl, and/or fucosylated glycotopes by comprehensive nanoLC-MS2-product dependent MS3 analysis of permethylated glycans, in conjunction with development of a data mining computational tool, GlyPick, to enable an automated, high throughput, semi-quantitative glycotope-centric glycomic mapping amenable to even nonexperts. We demonstrate in this work that diagnostic MS2 ions can be relied on to inform the presence of specific glycotopes, whereas their possible isomeric identities can be resolved at MS3 level. Both MS2 and associated MS3 data can be acquired exhaustively and processed automatically by GlyPick. The high acquisition speed, resolution, and mass accuracy afforded by top-notch Orbitrap Fusion MS system now allow a sensible spectral count and/or summed ion intensity-based glycome-wide glycotope quantification. We report here the technical aspects, reproducibility and optimization of such an analytical approach that uses the same acidic reverse phase C18 nanoLC conditions fully compatible with proteomic analysis to allow rapid hassle-free switching. We further show how this workflow is particularly effective when applied to larger, multiply sialylated and fucosylated N-glycans derived from mouse brain. The complexity of their terminal glycotopes including variants of fucosylated and disialylated type 1 and 2 chains would otherwise not be adequately delineated by any conventional LC-MS/MS analysis.

Project description:Glycobiology plays a central role in prostate cancer (PCa), as evidenced by the aberrant glycosylation in PCa-derived glycoproteins. Understanding the protein glycosylation changes underling PCa onset and progression may open opportunities for the discovery of novel biomarkers for PCa detection and stratification as well as targets for PCa metastasis. Advances in mass spectrometry-based glycomics and glycoproteomics have opened up exciting avenues for deep characterisation of the immensely, yet poorly understood complex glycoproteome. In this study, we have used integrated glycomics and glycoproteomics to explore the protein, cell and tumour-grade specific N- and O- glycosylation signatures in surgically-removed fresh PCa tissues grouped into five PCa disease grades and tissues from benign prostatic hyperplasia patients (BPH). Porous graphitised carbon–liquid chromatography (PGC–LC)-MS/MS analysis was used to profile the N-and O-glycome, revealing PCa grade specific N and O glycosylation changes, including oligomannosidic and paucimannosidic, bisecting-GlcNAc and highly branched tri- and tetra-antennary fucosylated and sialylated N-glycans as well as sialylated core 1 and 2 type O-glycans. High resolution LC-MS/MS was then employed to capture the micro and macroheterogeneity of 1,085 N-glycosites (>7,400 unique N-glycopeptides) from 540 N-glycoproteins and 360 O-glycosites (>500 unique O-glycopeptides) from 178 O-glycoproteins and reveal protein and cell specific N- and O- glycosylation changes associated with PCa progression. We also showed PCa grade-specific increase in the expression of oligosaccharyltransferase (OST) subunits that correlate with changes in the site occupancy of N-glycoproteins. In conclusion, this study shows that integrated glycomics and glycoproteomics can provide unprecedented insight into key molecular features and site-specific glycan heterogeneity contributing to the highly diverse tumour-microenvironment and allow us to deconstruct the regulation of the protein, cell and tumour-grade-specific glycosylation associated with PCa onset and development.