Pathway Cross-Talk Analysis in Detecting Significant Pathways in Barrett’s Esophagus Patients

BACKGROUND: The pathological mechanism of Barrett’s esophagus (BE) is still unclear. In the present study, pathway cross-talks were analyzed to identify hub pathways for BE, with the purpose of finding an efficient and cost-effective detection method to discover BE at its early stage and take steps to prevent its progression. MATERIAL/METHODS: We collected and preprocessed gene expression profile data, original pathway data, and protein-protein interaction (PPI) data. Then, we constructed a background pathway cross-talk network (BPCN) based on the original pathway data and PPI data, and a disease pathway cross-talk network (DPCN) based on the differential pathways between the PPI data and the BE and normal control. Finally, a comprehensive analysis was conducted on these 2 networks to identify hub pathway cross-talks for BE, so as to better understand the pathological mechanism of BE from the pathway level. RESULTS: A total of 12 411 genes, 300 pathways (6919 genes), and 787 896 PPI interactions (16 730 genes) were separately obtained from their own databases. Then, we constructed a BPCN with 300 nodes (42 293 interactions) and a DPCN with 296 nodes (15 073 interactions). We identified 4 hub pathways: AMP signaling pathway, cGMP-PKG signaling pathway, natural killer cell-mediated cytotoxicity, and osteoclast differentiation. We found that these pathways might play important roles during the occurrence and development of BE. CONCLUSIONS: We predicted that these pathways (such as AMP signaling pathway and cAMP signaling pathway) could be used as potential biomarkers for early diagnosis and therapy of BE.