Bioinformatics Analysis Highlights Five Differentially Expressed Genes as Prognostic Biomarkers of Cervical Cancer and Novel Option for Anticancer Treatment - Cui, Hongtu; Ma, Ruilin; Hu, Tao; Xiao, Gary Guishan; Wu, Chengjun (Frontiers in Cellular and Infection Microbiology, 2022)
Cervical cancer is one of the most common gynecological malignancies and is related with HPV infection, especially high-risk type HPV16 and HPV18. Aberrantly expressed genes are involved in the development of cervical cancer, which set a genetic basis for patient prognosis. In this study, we identified a set of aberrant expressed key genes from the Cancer Genome Atlas (TCGA) database, which could be used to accurately predict the survival rate of patients with cervical squamous cell carcinoma (CESC). A total of 3570 genes differentially expressed between normal and cancerous samples were analyzed by the algorithm of weighted gene co-expression network analysis (WGCNA), 1606 differentially expressed genes (DEGs) were up-regulated, while 1964 DEGs down-regulated. Analysis of these DEGs divided them in 7 modules including 76 hub genes. KEGG and GO enrichment analysis revealed significantly increasing of genes related to cell cycle, DNA replication, p53 signaling pathway, cGMP-PKG signaling pathway and Fanconi anemia (FA) pathway in CESC. These biological activities are previous reported to associate with cervical cancer or/and HPV infection. Finally, we highlighted 5 key genes (EMEMP2, GIMAP4, DYNC2I2, FGF13-AS1 and GIMAP1) as robust prognostic markers to predict patient’s survival rate (p=3.706e-05) through univariate and multivariate regression analysis. Thus, our study provides a novel option to set up several biomarkers for cervical cancer prognosis and anti-cancer drug targets.