Abstract
BACKGROUND: As the major subtypes of esophageal cancer (EC), esophageal adenocarcinoma (EAC) and esophageal squamous cell carcinoma (ESCC) exhibit distinct etiological mechanism, epidemiology, tumor biology, and prognoses. We performed bioinformatics analysis on specific genes related to pathological subtypes to identify potential biomarkers and therapeutic targets. METHODS: Differentially expressed genes (DEGs) between tumor and normal tissues were identified from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO). Weighted gene co-expression network analysis (WGCNA) was subsequently employed to screen genes associated with pathological subtypes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) annotations, along with gene set enrichment analysis (GSEA), were performed to elucidate the biological roles of these DEGs. A protein‒protein interaction (PPI) network was constructed to explore the hub genes. Furthermore, the prognostic genes were identified via LASSO Cox regression. The differences between EAC and ESCC in terms of immune cell infiltration, somatic mutations, copy number variations (CNVs), and drug sensitivity were subsequently analyzed. RESULTS: A total of 131 genes were identified as EAC-specific DEGs, whereas 49 genes were recognized as ESCC-specific DEGs. Enrichment analysis revealed significant enrichment of the extracellular matrix (ECM)-related pathway, along with the cell cycle, epithelial‒mesenchymal transition (EMT), and hypoxia signaling pathways, in ESCC. Conversely, EAC was associated with alterations in tumor metabolism, particularly glycolysis and gluconeogenesis. For EAC, a prognostic risk model was constructed, including RHOV, SYTL1, MT1X, PRRG4, KCNK5, and CCL20, which demonstrated robust predictive capabilities for patient outcomes. In ESCC, TUSC3 was identified as a prognostic biomarker and was validated in tissue samples. Furthermore, an in-depth analysis revealed distinct patterns in immune cell infiltration, somatic mutations, CNVs, and drug sensitivity between EAC and ESCC. CONCLUSIONS: In this study, pathologically specific genes were identified in EAC and ESCC. These findings might provide valuable insights into the molecular mechanisms and potential therapeutic targets for these two distinct subtypes.