Objective: The aim of this study was to evaluate the feasibility of using novel autoantibody and cancer-related protein arrays to identify potential biomarkers for the early detection of esophageal adenocarcinoma in serum.
Methods: Sera from 18 patients with esophageal adenocarcinoma and 14 with gastroesophageal reflux disease were added to microarrays designed to detect circulating autoantibodies to 51 tumor-associated antigens. Sera from the same patients were also added to a 53-plex assay for various cancer-related proteins. Cutoff values at 3 standard deviations above the mean expression of gastroesophageal reflux disease were used as a boundary for positivity.
Results: Nine proteins and 11 autoantibodies were able to individually segregate at least 1 esophageal adenocarcinoma sample from gastroesophageal reflux disease by means of cutoff values. The most discriminative marker was Fas ligand in the protein array, which was associated with 83.3% sensitivity and 100% specificity. The best performing autoantibody, NY-ESO-1, detected 3 esophageal adenocarcinoma samples. When both of these markers were combined, a sensitivity of 88.9% and specificity of 100% were attained.
Conclusions: Cancer-related protein and autoantibody arrays provide a technically simple and rapid method of identifying potential biomarkers for the detection of esophageal adenocarcinoma in serum. Furthermore, combining these platforms improves the diagnostic power of either platform alone. Integrating technologies that detect the expression of multiple proteins and autoantibodies in serum may provide a noninvasive and accurate method of detecting early esophageal adenocarcinoma.
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