ArticleProteomics. Clinical applications2013
Prediction of glycan motifs using quantitative analysis of multi-lectin binding: Motifs on MUC1 produced by cultured pancreatic cancer cells.
Article in Proteomics. Clinical applications, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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Who cites it
8 citing papers in PubMed, 14 citations in OpenAlex.
- Glycan array analysis of Pholiota squarrosa lectin and other fucose-oriented lectins.Glycobiology · 2021Article
- Genomic alterations in mucins across cancers.Oncotarget · 2017Article
- Characterizing Protein Glycosylation through On-Chip Glycan Modification and Probing.Analytical chemistry · 2016Article
- Hijacking the Hexosamine Biosynthetic Pathway to Promote EMT-Mediated Neoplastic Phenotypes.Frontiers in oncology · 2016Review
- Article
- Glycan motif profiling reveals plasma sialyl-lewis x elevations in pancreatic cancers that are negative for sialyl-lewis A.Molecular & cellular proteomics : MCP · 2015Article
- The detection and discovery of glycan motifs in biological samples using lectins and antibodies: new methods and opportunities.Advances in cancer research · 2015Review
- Detection of distinct glycosylation patterns on human γ-glutamyl transpeptidase 1 using antibody-lectin sandwich array (ALSA) technology.BMC biotechnology · 2014Article
Corrections and comments
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Authors and funding
9 authors at 3 institutions in 1 country.
Funding
Abstract
purposeLectins are valuable tools for detecting specific glycans in biological samples, but the interpretation of the measurements can be ambiguous due to the complexities of lectin specificities. Here, we present an approach to improve the accuracy of interpretation by converting lectin measurements into quantitative predictions of the presence of various glycan motifs. EXPERIMENTAL
designThe conversion relies on a database of analyzed glycan array data that provides information on the specificities of the lectins for each of the motifs. We tested the method using measurements of lectin binding to glycans on glycan arrays and then applied the method to predicting motifs on the protein mucin 1 (MUC1) expressed in eight different pancreatic cancer cell lines.
resultsThe combined measurements from several lectins were more accurate than individual measurements for predicting the presence or absence of motifs on arrayed glycans. The analysis of MUC1 revealed that each cell line expressed a unique pattern of glycoforms, and that the glycoforms significantly differed between MUC1 collected from conditioned media and MUC1 collected from cell lysates. CONCLUSIONS AND CLINICAL RELEVANCE: This new method could provide more accurate analyses of glycans in biological sample and make the use of lectins more practical and effective for a broad range of researchers.
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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.