Identification of hub genes associated with esophageal cancer progression using bioinformatics analysis

Li,Jiangfen; Xie,Yufang; Wang,Xueli; Jiang,Chenhao; Yuan,Xin; Zhang,Anzhi; Yang,Lan; Liu,Chunxia; Zou,Hong; Li,Feng; Hu,Jianming

doi:10.3892/ol.2020.12077

Identification of hub genes associated with esophageal cancer progression using bioinformatics analysis

Authors:
- Jiangfen Li
- Yufang Xie
- Xueli Wang
- Chenhao Jiang
- Xin Yuan
- Anzhi Zhang
- Lan Yang
- Chunxia Liu
- Hong Zou
- Feng Li
- Jianming Hu
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Affiliations: Department of Pathology and Key Laboratory for Xinjiang Endemic and Ethnic Diseases (Ministry of Education), The First Affiliated Hospital, Shihezi University School of Medicine, Shihezi, Xinjiang 832000, P.R. China
Published online on: September 9, 2020 https://doi.org/10.3892/ol.2020.12077
Article Number: 214
Copyright : © Li et al. This is an open access article distributed under the terms of Creative Commons Attribution License [CC BY 4.0].

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Abstract

The underlying causes of esophageal cancer (EC) are unknown. To explore the molecular mechanisms that lead to EC, gene expression profiles of large cohorts of patients with EC were obtained from The Cancer Genome Atlas and the Gene Expression Omnibus (GEO) databases (GSE5364, GSE20347 and GSE23400). The present study identified 83 upregulated and 22 downregulated genes between EC and normal tissue using R statistical software and the GEO2R web tool. The Database for Annotation, Visualization and Integrated Discovery was used to identify the associated pathways, and for functional annotation of the differentially expressed genes (DEGs). Protein‑protein interactions of these DEGs were analyzed based on the Search Tool for the Retrieval of Interacting Genes database, and hub genes were visualized using Cytoscape software. An online Kaplan‑Meier plotter survival analysis tool was utilized to evaluate the prognostic value of hub gene expression in patients with EC. Further analysis of an additional dataset from GEO (GSE21293) revealed that these genes were associated with infiltration and metastasis in EC. In addition, the Gene Expression Profiling Interactive Analysis tool was used to evaluate expression levels of hub genes in patients with EC for different pathological stages. The Ualcan analysis tool was used to evaluate the expression levels of hub genes for different histological types. Overall, ubiquitin conjugating enzyme E2 C, cyclin dependent kinase inhibitor 3, CDC28 protein kinase regulatory subunit 2, kinesin family member 20A (KIF20A) and RAD51 associated protein 1 (RAD51AP1) were upregulated in EC tissues compared with normal tissues, and upregulation of these genes was a poor prognostic factor for patients with EC, indicating that these genes may mediate EC cell infiltration and metastasis. Among the hub genes, KIF‑20A had potential value for predicting the pathological stage of EC. KIF20A and RAD51AP1 were more informative biomarkers of esophageal squamous cell carcinoma. Further studies are required to explore the value of these genes in the treatment of EC.

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