ReviewMass spectrometry reviews2022
Quantitative clinical glycomics strategies: A guide for selecting the best analysis approach.
Review in Mass spectrometry reviews, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 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
15 citing papers in PubMed, 27 citations in OpenAlex.
- Glycomic Insights in Gynecological Disease: From Molecular Mechanisms to Precision Diagnostics and Therapeutics.International journal of molecular sciences · 2026Review
- Multi-Omics Alterations in Rat Kidneys upon Chronic Glyphosate Exposure.Biomolecules · 2025Article
- Boosting Quantification of N-Glycans by an Enhanced Isobaric Multiplex Reagents for Carbonyl-Containing Compound (SUGAR) Tagging Strategy.Journal of the American Society for Mass Spectrometry · 2025Article
- Fast NMR-Based Assessment of Cancer-Associated Protein Glycosylations from Serum Samples.Analytical chemistry · 2025Article
- Recent advances in analytical methods and bioinformatic tools for quantitative glycomics.Analytical and bioanalytical chemistry · 2025Review
- Recent Advances in Labeling-Based Quantitative Glycomics: From High-Throughput Quantification to Structural Elucidation.Proteomics · 2025Review
- Probing Blood Plasma Protein Glycosylation with Infrared Spectroscopy.Analytical chemistry · 2024Article
- The Role of Clinical Glyco(proteo)mics in Precision Medicine.Molecular & cellular proteomics : MCP · 2023Article
- Glycan Node Analysis Detects Varying Glycosaminoglycan Levels in Melanoma-Derived Extracellular Vesicles.International journal of molecular sciences · 2023Article
- Methods for quantification of glycopeptides by liquid separation and mass spectrometry.Mass spectrometry reviews · 2023Review
- Analysis of Glycosylation and Disulfide Bonding of Wild-Type SARS-CoV-2 Spike Glycoprotein.Journal of virology · 2022Article
- Comparison of denaturing agent effects in enzymaticTurkish journal of chemistry · 2022Article
- The opportunity cost of automated glycopeptide analysis: case study profiling the SARS-CoV-2 S glycoprotein.Analytical and bioanalytical chemistry · 2021Article
- The Hitchhiker's guide to glycoproteomics.Biochemical Society transactions · 2021Review
- Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2021-2022.Mass spectrometry reviewsReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Glycans introduce complexity to the proteins to which they are attached. These modifications vary during the progression of many diseases; thus, they serve as potential biomarkers for disease diagnosis and prognosis. The immense structural diversity of glycans makes glycosylation analysis and quantitation difficult. Fortunately, recent advances in analytical techniques provide the opportunity to quantify even low-abundant glycopeptides and glycans derived from complex biological mixtures, allowing for the identification of glycosylation differences between healthy samples and those derived from disease states. Understanding the strengths and weaknesses of different quantitative glycomics analysis methods is important for selecting the best strategy to analyze glycosylation changes in any given set of clinical samples. To provide guidance towards selecting the proper approach, we discuss four widely used quantitative glycomics analysis platforms, including fluorescence-based analysis of released N-linked glycans and three different varieties of MS-based analysis: liquid chromatography (LC)-mass spectrometry (MS) analysis of glycopeptides, matrix-assisted laser desorption ionization-time of flight MS, and LC-ESI-MS analysis of released N-linked glycans. These methods' strengths and weaknesses are compared, particularly associated with the figures of merit that are important for clinical biomarker studies, including: the initial sample requirements, the methods' throughput, sample preparation time, the number of species identified, the methods' utility for isomer separation and structural characterization, method-related challenges associated with quantitation, repeatability, the expertise required, and the cost for each analysis. This review, therefore, provides unique guidance to researchers who endeavor to undertake a clinical glycomics analysis by offering insights on the available analysis technologies.
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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.