Abstract
Esophageal squamous cell carcinoma (ESCC) accounts for over 90% of all esophageal tumors. However, the molecular mechanism underlying ESCC development and prognosis remains unclear, and there are still no effective molecular biomarkers for diagnosing or predicting the clinical outcome of patients with ESCC. Here, using bioinformatics analyses, we attempted to identify potential biomarkers and therapeutic targets for ESCC. Differentially expressed genes (DEGs) between ESCC and normal esophageal tissue samples were obtained through comprehensive analysis of three publicly available gene expression profile datasets from the Gene Expression Omnibus database. The biological roles of the DEGs were identified by Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Moreover, the Cytoscape 3.7.1 platform and subsidiary tools such as Molecular Complex Detection (MCODE) and CytoHubba were used to visualize the protein-protein interaction (PPI) network of the DEGs and identify hub genes. A total of 345 DEGs were identified between normal esophageal and ESCC samples, which were enriched in the KEGG pathways of the cell cycle, endocytosis, pancreatic secretion, and fatty acid metabolism. Two of the highest scoring models were selected from the PPI network using Molecular Complex Detection. Moreover, CytoHubba revealed 21 hub genes with a valuable influence on the progression of ESCC in these patients. Among these, the high expression levels of five genes—SPP1, SPARC, BGN, POSTN, and COL1A2—were associated with poor disease-free survival of ESCC patients, as indicated by survival analysis. Taken together, we identified that elevated expression of five hub genes, including SPP1, is associated with poor prognosis in ESCC patients, which may serve as potential prognostic biomarkers or therapeutic target for ESCC.
Highlights
Esophageal carcinoma (EC) ranks seventh in incidence and sixth in mortality worldwide, with approximately 572,000 new cases and 50,900 deaths due to EC estimated in 2018 alone [1]
Gene Ontology (GO) annotation showed that the 345 Differentially expressed genes (DEGs) were mostly enriched in the Submodules and hub genes analysis with CytoHubba
345 DEGs between esophageal squamous cell carcinoma (ESCC) and normal esophageal samples were identified from three microarray datasets in the Gene Expression Omnibus (GEO) database, which were mainly significantly enriched in neutrophil-mediated immunity and cell cycle processes
Summary
Esophageal carcinoma (EC) ranks seventh in incidence and sixth in mortality worldwide, with approximately 572,000 new cases and 50,900 deaths due to EC estimated in 2018 alone [1]. The incidence rate of EC greatly differs depending on sex and population, with about 70% of cases occurring in men, and their mortality rate is 2-3-fold higher than that reported for women with EC. Based on the histological type, EC is classified as esophageal adenocarcinoma (EAC) and esophageal squamous cell carcinoma (ESCC), with the latter accounting for over 90% of all esophageal tumors [1]. Successful surgery, radiation therapy, and chemotherapy all contribute to a better prognosis for patients with EC. There are still numerous challenges to achieving an early diagnosis and accurate prognosis of individual EC patients based on current clinical indicators
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