Clinically, almost 50% of esophageal adenocarcinoma (EAC) originates from the progression of Barrett’s esophagus (BE). EAC is often diagnosed at late stages and is related to dismal prognosis. However, there are still no effective strategies for stratification and therapy in BE derived EAC (BE-EAC). Two public datasets (GSE26886 and GSE37200) are analyzed to identify differentially expressed genes (DEGs) between BE and EAC. A series of bioinformatics analyses are performed to explore potential biomarkers associated with BE-EAC. 27 up- and 104 down-regulated genes are identified between GSE26886 and GSE37200. The GO and KEGG enrichment analysis indicate that the DEGs are highly involved in tumorigenesis. Subsequently, Weighted Gene Co-Expression Network Analysis (WGCNA) is performed to explore the potential genes related to BE-EAC, which are further validated in The Cancer Genome Atlas (TCGA) database. 5 up-regulated genes (MYO1A, ACE2, COL1A1, LGALS4, and ADRA2A) and 3 down-regulated genes (AADAC, RAB27A, and P2RY14) were found in BE-EAC. Among them, the expression level of AADAC, ACE2 and ADRA2A show a significant correlation with patients’ survival probability. In conclusion, MYO1A, ACE2, COL1A1, LGALS4, ADRA2A, AADAC, RAB27A, and P2RY14 are potential diagnostic and prognostic biomarkers in BE-EAC.

BackgroundClinically, almost 50% of esophageal adenocarcinoma (EAC) originates from the progression of Barrett’s esophagus (BE). EAC is often diagnosed at late stages and is related to dismal prognosis. However, there are still no effective strategies for stratification and therapy in BE derived EAC (BE-EAC).MethodsTwo public datasets (GSE26886 and GSE37200) are analyzed to identify differentially expressed genes (DEGs) between BE and EAC. A series of bioinformatics analyses are performed to explore potential biomarkers associated with BE-EAC.Results27 up- and 104 down-regulated genes are identified between GSE26886 and GSE37200. The GO and KEGG enrichment analysis indicate that the DEGs are highly involved in tumorigenesis. Subsequently, Weighted Gene Co-Expression Network Analysis (WGCNA) is performed to explore the potential genes related to BE-EAC, which are further validated in The Cancer Genome Atlas (TCGA) database. 5 up-regulated genes (MYO1A, ACE2, COL1A1, LGALS4, and ADRA2A) and 3 down-regulated genes (AADAC, RAB27A, and P2RY14) were found in BE-EAC. Among them, the expression level of AADAC, ACE2 and ADRA2A show a significant correlation with patients’ survival probability .Conclusion MYO1A, ACE2, COL1A1, LGALS4, ADRA2A, AADAC, RAB27A, and P2RY14 are potential diagnostic and prognostic biomarkers in BE-EAC.