Cancer Cell International (Feb 2021)
Identification of four genes and biological characteristics of esophageal squamous cell carcinoma by integrated bioinformatics analysis
Abstract
Abstract Background Esophageal squamous cell carcinoma (ESCC) has become one of the most serious diseases affecting populations worldwide and is the primary subtype of esophageal cancer (EC). However, the molecular mechanisms governing the development of ESCC have not been fully elucidated. Methods The robust rank aggregation method was performed to identify the differentially expressed genes (DEGs) in six datasets (GSE17351, GSE20347, GSE23400, GSE26886, GSE38129 and GSE77861) from the Gene Expression Omnibus (GEO). The Search Tool for the Retrieval of Interacting Genes (STRING) database was utilized to extract four hub genes from the protein–protein interaction (PPI) network. Module analysis and disease free survival analysis of the four hub genes were performed by Cytoscape and GEPIA. The expression of hub genes was analyzed by GEPIA and the Oncomine database and verified by real-time quantitative PCR (qRT-PCR). Results In total, 720 DEGs were identified in the present study; these genes consisted of 302 upregulated genes and 418 downregulated genes that were significantly enriched in the cellular component of the extracellular matrix part followed by the biological process of the cell cycle phase and nuclear division. The primary enriched pathways were hsa04110:Cell cycle and hsa03030:DNA replication. Four hub genes were screened out, namely, SPP1, MMP12, COL10A1 and COL5A2. These hub genes all exhibited notably increased expression in ESCC samples compared with normal samples, and ESCC patients with upregulation of all four hub genes exhibited worse disease free survival. Conclusions SPP1, MMP12, COL10A1 and COL5A2 may participate in the tumorigenesis of ESCC and demonstrate the potential to serve as molecular biomarkers in the early diagnosis of ESCC. This study may help to elucidate the molecular mechanisms governing ESCC and facilitate the selection of targets for early treatment and diagnosis.
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