Scientific Reports · 2023 · 11 citations · 24 references
MedicineBioinformaticsOncologyCarcinogenesisGene ExpressionNeoplasiaCancer BiomarkersCancer GenomicsEsophageal CancerEsophageal DiseasesGene Co-expression AnalysisGene Expression ProfilingBiomarkersCancer BioinformaticsEnrichment AnalysisEsophageal PathologyGene Co-expression Network AnalysisGene Expression Network AnalysisGene Network AnalysisPrognostic Biomarkers
Almost 50% of esophageal adenocarcinoma (EAC) patients progressed from Barrett's esophagus (BE). EAC is often diagnosed at late stages and is related to dismal prognosis. However, there are still no effective methods for stratification and therapy in BE and EAC. Two public datasets (GSE26886 and GSE37200) were analyzed to identify differentially expressed genes (DEGs) between BE and EAC. Then, a series of bioinformatics analyses were performed to explore potential biomarkers associated with BE-EAC. 27 up- and 104 down-regulated genes were observed between GSE26886 and GSE37200. The GO and KEGG enrichment analysis indicated that the DEGs were highly involved in tumorigenesis. Subsequently, Weighted Gene Co-Expression Network Analysis (WGCNA) were performed to explore the potential genes related to BE-EAC, which were validated in The Cancer Genome Atlas (TCGA) database, and 5 up-regulated genes (MYO1A, ACE2, COL1A1, LGALS4, and ADRA2A) and 3 down-regulated genes (AADAC, RAB27A, and P2RY14) were found in EAC. Meanwhile, ADRA2A and AADAC could contribute to EAC pathogenesis and progression. MYO1A, ACE2, COL1A1, LGALS4, ADRA2A, AADAC, RAB27A, and P2RY14 could be potential novel diagnostic and prognostic biomarkers in BE-EAC.
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