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Prediction of glycan motifs using quantitative analysis of multi-lectin binding: Motifs on MUC1 produced by cultured pancreatic cancer cells
Article first published online: 13 SEP 2013
© 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
PROTEOMICS - Clinical Applications
Special Issue: Glycan Biomarker Discovery
Volume 7, Issue 9-10, pages 632–641, October 2013
How to Cite
McCarter, C., Kletter, D., Tang, H., Partyka, K., Ma, Y., Singh, S., Yadav, J., Bern, M. and Haab, B. B. (2013), Prediction of glycan motifs using quantitative analysis of multi-lectin binding: Motifs on MUC1 produced by cultured pancreatic cancer cells. Prot. Clin. Appl., 7: 632–641. doi: 10.1002/prca.201300069
- Issue published online: 9 OCT 2013
- Article first published online: 13 SEP 2013
- Accepted manuscript online: 19 AUG 2013 02:10AM EST
- Manuscript Accepted: 12 AUG 2013
- Manuscript Revised: 8 AUG 2013
- Manuscript Received: 1 AUG 2013
- NCI (Alliance of Glycobiologists for Cancer Detection. Grant Number: U01CA168896
- Early Detection Research Network. Grant Number: U01CA152653
- Van Andel Research Institute
- Glycan motif;
Lectins 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.
The 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.
The 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.