Identification of EPHX2 and RMI2 as two novel key genes in cervical squamous cell carcinoma by an integrated bioinformatic analysis

• Published in: Journal of cellular physiology 2019-11, Vol.234 (11), p.21260-21273
• Main Authors: Liu, Jinhui, Nie, Sipei, Gao, Mei, Jiang, Yi, Wan, Yicong, Ma, Xiaoling, Zhou, Shulin, Cheng, Wenjun
• Format: Article
• Language: English
• Subjects: Annotations; Bioinformatics; bioinformatics analysis; Camptothecin; Cancer; Cdc45 protein; Cervical cancer; cervical squamous cell carcinoma (CESC); Cervix; differentially expressed genes (DEGs); DNA methylation; Drug development; Drugs; Encyclopedias; Gene expression; Genes; Genomes; Malignancy; Medical prognosis; Methylation; Modules; Network analysis; prognosis; Proteins; Resveratrol; Signature analysis; Squamous cell carcinoma; Survival analysis; Trichostatin A; weighted gene coexpression network analysis (WGCNA)
• ISSN: 0021-9541; 1097-4652
• DOI: 10.1002/jcp.28731

Cervical cancer is the fourth most common malignancy in women worldwide and cervical squamous cell carcinoma (CESC) is the most common histological type of cervical cancer. The dysregulation of genes plays a significant role in cancer. In the present study, we screened out differentially expressed genes (DEGs) of CESC in the GSE63514 data set from the Gene Expression Omnibus database. An integrated bioinformatics analysis was used to select hub genes, as well as to investigate their related prognostic signature, functional annotation, methylation mechanism, and candidate molecular drugs. As a result, a total of 1907 DEGs were identified (944 were upregulated and 963 were downregulated). In the protein–protein interaction network, three hub modules and 30 hub genes were identified. And two hub modules and 116 hub genes were screened out from four CESC‐related modules by the weighted gene coexpression network analysis. The gene ontology term enrichment analysis and Kyoto encyclopedia of genes and genomes pathway analysis were performed to better understand functions and pathways. Genes with a significant prognostic value were found by prognostic signature analysis. And there were five genes (EPHX2, CHAF1B, KIAA1524, CDC45, and RMI2) identified as significant CESC‐associated genes after expression validation and survival analysis. Among them, EPHX2 and RMI2 were noted as two novel key genes for the CESC‐associated methylation and expression. In addition, four candidate small molecule drugs for CESC (camptothecin, resveratrol, vorinostat, and trichostatin A) were defined. Further studies are required to explore these significant CESC‐associated genes for their potentiality in diagnosis, prognosis, and targeted therapy. An integrated bioinformatics analysis was used to select hub genes based on the DEGs obtained from the GSE63514 data set, as well as to investigate their related prognostic signature, functional annotation, methylation mechanism, and candidate molecular drugs in CESC. EPHX2 and RMI2 were identified as two novel key CESC‐associated genes, which deserve further investigation for their potentiality in diagnosis, prognosis, and targeted therapy.