Abstract

BACKGROUND: Esophageal adenocarcinoma is a lethal malignancy whose incidence is rapidly growing in recent years. Previous reports suggested that Barrett’s esophagus (BE), which is represented by metaplasia-dysplasia-carcinoma transition, is regarded as the premalignant lesion of esophageal neoplasm. However, our knowledge about the development of esophageal adenocarcinoma is still very limited.

MATERIAL AND METHODS: In order to acquire better understanding about the pathological mechanisms in this field, we obtained gene profiling data on BE, esophageal adenocarcinoma patients, and normal controls from the Gene Expression Omnibus (GEO) database. Bioinformatics analyses, including Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, were conducted.

RESULTS: Our results revealed that several pathways, such as the wound healing, complement, and coagulation pathways, were closely correlated with cancer development and progression. The mitogen-activated protein kinase (MAPK) pathway was discovered to be responsible for the predisposition stage of cancer; while response to stress, cytokine-cytokine receptor interaction, nod-like receptor signaling pathway, and ECM-receptor interaction were chief contributors of cancer progression. More importantly, we discovered in this study that LYN was a critical gene. It was found to be the key nodule of several significant biological networks, which suggests its close correlation with cancer initiation and progression.

CONCLUSIONS: These results provided more information on the mechanisms of esophageal adenocarcinoma, which enlightened our way to the clinical discovery of novel therapeutic makers for conquering esophageal cancer. Keywords: esophageal adenocarcinoma; LYN; Go analysis; KEGG pathway.

Keywords: Barrett Esophagus - genetics, Adenocarcinoma - genetics, Computational Biology, Databases, Genetic, Disease Progression, Esophageal Neoplasms - genetics, Gene Expression Profiling, Tissue Array Analysis, src-Family Kinases - genetics