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BACKGROUND Esophageal cancer is a malignant tumor with a complex pathogenesis and a poor 5-year survival rate, which encourages researchers to explore its molecular mechanisms deeper to improve the prognosis. MATERIAL AND METHODS DEGs were from 4 Gene Expression Omnibus (GEO) databases (GSE92396, GSE20347, GSE23400, and GSE45168) including 87 esophageal tumor samples and 84 normal samples. We performed Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, Protein-Protein interaction (PPI) analysis, and GeneMANIA to identify the DEGs. Gene set enrichment analysis (GSEA) and Kaplan-Meier survival analyses were performed. RESULTS There was an overlapping subset consisting of 120 DEGs that was present in all esophageal tumor samples. The DEGs were enriched in extracellular matrix (ECM)-receptor interaction, as well as focal adhesion and transcriptional mis-regulation in cancer. The 2 most crucial regulatory pathways in esophageal cancer were the amebiasis pathway and the PI3K-Akt signaling pathway. Secreted phosphoprotein 1 (SPP1) and fibronectin 1 (FN1) were selected and verified in an independent cohort and samples using the TCGA and GTEx projects. Gene set enrichment analysis (GSEA) showed that proteasome and nucleotide excision repair were 2 most differentially enriched pathways in the SPP1 high-expression phenotype, and ECM-receptor interaction and focal adhesion in FN1 high-expression phenotype. Kaplan-Meier survival analysis showed that SPP1 and FN1 were significantly positively related to overall survival and had the potential to predict patient relapse. CONCLUSIONS Our analysis is the first to show that SPP1 and FN1 might work as biological markers of progression and prognosis in esophageal carcinoma (ESCA).

Citation

Menglu Li, Kaige Wang, Yanhua Pang, Hongpan Zhang, Hao Peng, Qi Shi, Zhiyu Zhang, Xiaobin Cui, Feng Li. Secreted Phosphoprotein 1 (SPP1) and Fibronectin 1 (FN1) Are Associated with Progression and Prognosis of Esophageal Cancer as Identified by Integrated Expression Profiles Analysis. Medical science monitor : international medical journal of experimental and clinical research. 2020 Mar 24;26:e920355

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PMID: 32208405

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