ArticleJournal of proteome research2012
Delineating diseases by IMS-MS profiling of serum N-linked glycans.
Article in Journal of proteome research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- High-Throughput Glycomic Methods.Chemical reviews · 2022Review
- Mass Spectrometry-Based Techniques to Elucidate the Sugar Code.Chemical reviews · 2022Review
- Glycoproteomic markers of hepatocellular carcinoma-mass spectrometry based approaches.Mass spectrometry reviews · 2019Review
- Cryogenic Vibrational Spectroscopy Provides Unique Fingerprints for Glycan Identification.Journal of the American Society for Mass Spectrometry · 2017Article
- Delineation of disease phenotypes associated with esophageal adenocarcinoma by MALDI-IMS-MS analysis of serum N-linked glycans.The Analyst · 2017Article
- Eradicating mass spectrometric glycan rearrangement by utilizing free radicals.Chemical science · 2016Article
- Intact glycopeptide characterization using mass spectrometry.Expert review of proteomics · 2016Review
- Serum glycoprotein-derived N- and O-linked glycans as cancer biomarkers.American journal of cancer research · 2016Review
- Ion Mobility Mass Spectrometry for Ion Recovery and Clean-Up of MS and MS/MS Spectra Obtained from Low Abundance Viral Samples.Journal of the American Society for Mass Spectrometry · 2015Article
- Glycopeptide Site Heterogeneity and Structural Diversity Determined by Combined Lectin Affinity Chromatography/IMS/CID/MS Techniques.Journal of the American Society for Mass Spectrometry · 2015Article
- Targeted methods for quantitative analysis of protein glycosylation.Proteomics. Clinical applications · 2015Review
- Populations of metal-glycan structures influence MS fragmentation patterns.Journal of the American Society for Mass Spectrometry · 2015Article
- High sensitivity combined with extended structural coverage of labile compounds via nanoelectrospray ionization at subambient pressures.Analytical chemistry · 2014Article
- Oligosaccharide analysis by mass spectrometry: a review of recent developments.Analytical chemistry · 2014Review
- High-sensitivity analytical approaches for the structural characterization of glycoproteins.Chemical reviews · 2013Review
- Structural glycomic analyses at high sensitivity: a decade of progress.Annual review of analytical chemistry (Palo Alto, Calif.) · 2013Review
- Ion mobility-mass spectrometry analysis of serum N-linked glycans from esophageal adenocarcinoma phenotypes.Journal of proteome research · 2012Article
- Mannose7 glycan isomer characterization by IMS-MS/MS analysis.Journal of the American Society for Mass Spectrometry · 2012Article
- Improving N-glycan coverage using HPLC-MS with electrospray ionization at subambient pressure.Analytical chemistry · 2012Article
- Defining putative glycan cancer biomarkers by MS.Bioanalysis · 2012Review
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Authors and funding
12 authors.
Funding
Abstract
Altered branching and aberrant expression of N-linked glycans is known to be associated with disease states such as cancer. However, the complexity of determining such variations hinders the development of specific glycomic approaches for assessing disease states. Here, we examine a combination of ion mobility spectrometry (IMS) and mass spectrometry (MS) measurements, with principal component analysis (PCA) for characterizing serum N-linked glycans from 81 individuals: 28 with cirrhosis of the liver, 25 with liver cancer, and 28 apparently healthy. Supervised PCA of combined ion-mobility profiles for several, to as many as 10 different mass-to-charge ratios for glycan ions, improves the delineation of diseased states. This extends an earlier study [J. Proteome Res.2008, 7, 1109-1117] of isomers associated with a single glycan (S(1)H(5)N(4)) in which PCA analysis of the IMS profiles appeared to differentiate the liver cancer group from the other samples. Although performed on a limited number of test subjects, the combination of IMS-MS for different combinations of ions and multivariate PCA analysis shows promise for characterizing disease states.
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