Journal article

Evaluation of Serum Glycoprotein Biomarker Candidates for Detection of Esophageal Adenocarcinoma and Surveillance of Barrett's Esophagus

Alok K Shah, Gunter Hartel, Ian Brown, Clay Winterford, Renhua Na, Kim-Anh Le Cao, Bradley A Spicer, Michelle Dunstone, Wayne A Phillips, Reginald V Lord, Andrew P Barbour, David I Watson, Virendra Joshi, David C Whiteman, Michelle M Hill

MOLECULAR & CELLULAR PROTEOMICS | AMER SOC BIOCHEMISTRY MOLECULAR BIOLOGY INC | Published : 2018

Abstract

Esophageal adenocarcinoma (EAC) is thought to develop from asymptomatic Barrett's esophagus (BE) with a low annual rate of conversion. Current endoscopy surveillance of BE patients is probably not cost-effective. Previously, we discovered serum glycoprotein biomarker candidates which could discriminate BE patients from EAC. Here, we aimed to validate candidate serum glycoprotein biomarkers in independent cohorts, and to develop a biomarker candidate panel for BE surveillance. Serum glycoprotein biomarker candidates were measured in 301 serum samples collected from Australia (4 states) and the United States (1 clinic) using previously established lectin magnetic bead array (LeMBA) coupled mul..

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Grants

Awarded by National Health and Medical Research Council (NHMRC) Centre of Research Excellence grant


Awarded by NHMRC Career Development Fellowship


Awarded by NHMRC Research Fellowship


Funding Acknowledgements

This work was supported by The University of Queensland-Ochsner Seed Fund for Collaborative Research Grant 2014, The University of Queensland Faculty of Medicine and Biomedical Science Cancer Bequest Grant 2014, and internal funding support from The University of Queensland Diamantina Institute 2015. PROBE-NET was supported by a National Health and Medical Research Council (NHMRC) Centre of Research Excellence grant (APP1040947). KALC is a recipient of NHMRC Career Development Fellowship (APP1087415). DCW is supported by an NHMRC Research Fellowship (APP1058522). The sponsors had no influence on the study design, collection, analysis, and interpretation of data.