dc.contributor.author | Shipman, Joshua T. | |
dc.contributor.author | Nguyen, Hanna T. | |
dc.contributor.author | Desaire, Heather | |
dc.date.accessioned | 2022-09-06T19:14:21Z | |
dc.date.available | 2022-09-06T19:14:21Z | |
dc.date.issued | 2020-03-18 | |
dc.identifier.citation | Joshua T. Shipman, Hanna T. Nguyen, and Heather Desaire. ACS Omega 2020 5 (12), 6270-6276. DOI: 10.1021/acsomega.9b03334 | en_US |
dc.identifier.uri | http://hdl.handle.net/1808/33432 | |
dc.description.abstract | Glycomic-based approaches to discover potential biomarkers have shown great promise in their ability to distinguish between healthy and diseased individuals; these methods can identify when aberrant glycosylation is significant, but they cannot practically be adapted into widely implemented diagnostic assays because they are too complex, expensive, and low-throughput. We have developed a new strategy that addresses challenges associated with sample preparation, sample throughput, instrumentation needs, and data analysis to transfer the valuable knowledge provided by protein glycosylation into a clinical environment. Notably, the detection limits of the assay are in the single-digit picomole range. Proof of principle is demonstrated by quantifying the changes in the sialic acid content in fetuin. As the sialic acid content in proteins varies in a number of disease states, this example demonstrates the utility of the method for biomarker analysis. Furthermore, the developed method can be adapted to other biologically important saccharides, affording a broad array of quantitative glycomic analyses that are accessible in a high-throughput, plate-reader format. These studies enable glycomic-based biomarker discovery efforts to transition through the difficult landscape of developing a potential biomarker into a clinical assay. | en_US |
dc.publisher | American Chemical Society | en_US |
dc.rights | Copyright © 2020 American Chemical Society. This is an open access article published under an ACS AuthorChoice License, which permits copying and redistribution of the article or any adaptations for non-commercial purposes. | en_US |
dc.subject | Assays | en_US |
dc.subject | Carbohydrates | en_US |
dc.subject | Chemical biology | en_US |
dc.subject | Extraction | en_US |
dc.subject | Fluorescence | en_US |
dc.title | So You Discovered a Potential Glycan-Based Biomarker; Now What? We Developed a High-Throughput Method for Quantitative Clinical Glycan Biomarker Validation | en_US |
dc.type | Article | en_US |
kusw.kuauthor | Shipman, Joshua T. | |
kusw.kuauthor | Nguyen, Hanna T. | |
kusw.kuauthor | Desaire, Heather | |
kusw.kudepartment | Chemistry | en_US |
dc.identifier.doi | 10.1021/acsomega.9b03334 | en_US |
dc.identifier.orcid | https://orcid.org/0000-0003-3191-0026 | en_US |
dc.identifier.orcid | https://orcid.org/0000-0002-2181-0112 | en_US |
kusw.oaversion | Scholarly/refereed, publisher version | en_US |
kusw.oapolicy | This item meets KU Open Access policy criteria. | en_US |
dc.rights.accessrights | openAccess | en_US |