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Screening and exploration of key genes and transcription factors in esophageal cancer
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  • Yuanguo Wang,
  • Yujing Shi,
  • Peng Zhang,
  • Peng Zhang
Yuanguo Wang
Tianjin Medical University General Hospital
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Yujing Shi
Tianjin Medical University General Hospital
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Peng Zhang
Tianjin Medical University General Hospital
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Peng Zhang
Tianjin Medical University General Hospital

Corresponding Author:[email protected]

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Abstract

Esophageal cancer is a prevalent malignant tumor in the digestive tract, ranking seventh in terms of incidence among all malignant tumors. Therefore, identifying new targets and prognostic markers is crucial for the successful treatment of this disease. In this study, we analyzed two GEO microarray dataset using the GOE2R tool to find differentially expressed genes. And then used DAVID, KEGG, ChEA, X2K, HMDB, and mirTarBase to analyze the differentially gene-associated gene ontology, signaling pathways, transcription factors, kinases, and miRNAs. The PPI interaction network was constructed by Spring. Hub gene was analyzed by Cytoscape and theirs expression level verified by GEPIA. The results showed that 307 genes were up-regulated, and 295 genes were down-regulated in the two datasets. GO and KEGG analysis revealed that the up-regulated genes were mainly involved in collagen fibril organization, extracellular matrix and cell division, KEGG showed that ECM-receptor interaction, cell cycle, and the IL-17 signaling pathway is the improtant pathway. The top 10 hub genes were CCNA2, CDK1, AURKA, MKI67, CDC6, KIF20A, AURKB, KIF14, BUB1, and ASPM. In addition to the AURKA gene, these genes were up-regulated in esophageal cancer tumor tissues according to the GEPIA database. The top five transcription factors identified were FOXM1, SOX2, E2F4, BACH1, and CEBPD. The most important kinases in esophageal cancer were CDK1, CSNK2A1, and MAPK14. miRNA analysis revealed that hsa-miR-193b-3p, hsa-miR-192-5p and hsa-miR-1-3p could target the most up-regulated genes. In summary, the core genes, transcription factors, and metabolites identified in esophageal cancer tissues could serve as potential biomarkers for the diagnosis and treatment of esophageal cancer in the future.