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So You Discovered a Potential Glycan-Based Biomarker; Now What? We Developed a High-Throughput Method for Quantitative Clinical Glycan Biomarker Validation.
Shipman, Joshua T; Nguyen, Hanna T; Desaire, Heather.
Afiliação
  • Shipman JT; Department of Chemistry, University of Kansas, Lawrence, Kansas 66045, United States.
  • Nguyen HT; Department of Chemistry, University of Kansas, Lawrence, Kansas 66045, United States.
  • Desaire H; Department of Chemistry, University of Kansas, Lawrence, Kansas 66045, United States.
ACS Omega ; 5(12): 6270-6276, 2020 Mar 31.
Article em En | MEDLINE | ID: mdl-32258861
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.

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2020 Tipo de documento: Article