ArticlemAbs2018
Data-independent oxonium ion profiling of multi-glycosylated biotherapeutics.
Article in mAbs, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed.
- Article
- Mass Spectrometry Analysis of Biotherapeutic Monoclonal Antibody Glycosylation.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Extracting informative glycan-specific ions from glycopeptide MS/MS spectra with GlyCounter.bioRxiv : the preprint server for biology · 2025Article
- Autonomous Dissociation-type Selection for Glycoproteomics Using a Real-Time Library Search.Journal of proteome research · 2024Article
- Oxonium ion scanning mass spectrometry for large-scale plasma glycoproteomics.Nature biomedical engineering · 2024Article
- Mass Spectrometry Strategies forCells · 2024Review
- Highly sensitive characterization of non-human glycan structures of monoclonal antibody drugs utilizing tandem mass spectrometry.Scientific reports · 2022Article
- Developing mass spectrometry for the quantitative analysis of neuropeptides.Expert review of proteomics · 2021Review
- The Role of Data-Independent Acquisition for Glycoproteomics.Molecular & cellular proteomics : MCP · 2021Review
- Glycosaminoglycans.Advances in experimental medicine and biology · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The characterization of glycosylation is required for many protein therapeutics. The emergence of antibody and antibody-like molecules with multiple glycan attachment sites has rendered glycan analysis increasingly more complicated. Reliance on site-specific glycopeptide analysis is therefore necessary to fully analyze multi-glycosylated biotherapeutics. Established glycopeptide methodologies have generally utilized a priori knowledge of the glycosylation states of the investigated protein(s), database searching of results generated from data-dependent liquid chromatography-tandem mass spectrometry workflows, and extracted ion quantitation of the individual identified species. However, the inherent complexity of glycosylation makes predicting all glycoforms on all glycosylation sites extremely challenging, if not impossible. That is, only the "knowns" are assessed. Here, we describe an agnostic methodology to qualitatively and quantitatively assess both "known" and "unknown" site-specific glycosylation for biotherapeutics that contain multiple glycosylation sites. The workflow uses data-independent, all ion fragmentation to generate glycan oxonium ions, which are then extracted across the entirety of the chromatographic timeline to produce a glycan-specific "fingerprint" of the glycoprotein sample. We utilized both HexNAc and sialic acid oxonium ion profiles to quickly assess the presence of Fab glycosylation in a therapeutic monoclonal antibody, as well as for high-throughput comparisons of multi-glycosylated protein drugs derived from different clones to a reference product. An automated method was created to rapidly assess oxonium profiles between samples, and to provide a quantitative assessment of similarity.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.