Abstract
BACKGROUND: Barrett's esophagus (BE) is caused by gastroesophageal reflux with consecutive mucosal inflammation, predisposing patients to the development of esophageal adenocarcinoma (EAC). We investigated changes in T cell-related mucosal combinatorial molecular protein patterns in both diseases using the novel Multi-Epitope-Ligand-Cartography, a unique robotic whole-cell imaging technology that simultaneously visualizes dozens of proteins in structurally intact tissues and correlates cellular localization of proteins with function. RESULTS: Biopsies were taken during endoscopy from BE, EAC, and normal control tissue, and proteomic microscopy was performed on 32 different epitopes. When the significance level was set to p < 0.0005 and the search depth to five antibody combinations, controls and BE can be differentiated by 63, controls and EAC by 3222, and BE from EAC by 1521 distinct protein combinations.For example, the number of activated apoptotic naïve and memory T cells was significantly increased only in BE, whereas the number of activated apoptotic helper and regulatory T cells was significantly elevated in BE and EAC. In contrast, the number of activated apoptotic cytotoxic T cells was significantly elevated only in EAC. Confirming different pathways in BE and EAC, the number of T lymphocytes with p53 expression and downregulation of bcl2 expression (CD3+p53+Bcl2-NfkB-) was significantly increased in EAC compared to BE and controls. Interestingly, the number of precursor T cells (CD7+) was significantly elevated only in EAC. These cells lack Bax and caspase-8, suggesting impaired apoptosis in the early stages of T cell differentiation. CONCLUSION: Proteomic analysis showed for the first time that proteins, which are critically involved in the mucosal immune system of the esophagus, are distinctly expressed in BE and EAC, whereas others are comparably altered in both diseases, suggesting that many pathogenic events might be shared by both diseases. Topological proteomic analysis, therefore, helps us to understand the different pathogenic events in the underlying disease pathways.