Abstract
Cervical cancer is one of the most common malignant tumors in women, and its morbidity and mortality are increasing year by year worldwide. Therefore, an urgent and challenging task is to identify potential biomarkers for cervical cancer. This study aims to identify the hub genes based on the GEO database and then validate their prognostic values in cervical cancer by multiple databases. By analysis, we obtained 83 co-expressed differential genes from the GEO database (GSE63514, GSE67522 and GSE39001). GO and KEGG enrichment analysis showed that these 83 co-expressed it mainly involved differential genes in DNA replication, cell division, cell cycle, etc.. The PPI network was constructed and top 10 genes with protein-protein interaction were selected. Then, we validated ten genes using some databases such as TCGA, GTEx and oncomine. Survival analysis demonstrated significant differences in CDC45, RFC4, TOP2A. Differential expression analysis showed that these genes were highly expressed in cervical cancer tissues. Furthermore, univariate and multivariate cox regression analysis indicated that CDC45 and clinical stage IV were independent prognostic factors for cervical cancer. In addition, the HPA database validated the protein expression level of CDC45 in cervical cancer. Further studies investigated the relationship between CDC45 and tumor-infiltrating immune cells via CIBERSORT. Finally, gene set enrichment analysis (GSEA) showed CDC45 related genes were mainly enriched in cell cycle, chromosome, catalytic activity acting on DNA, etc. These results suggested CDC45 may be a potential biomarker associated with the prognosis of cervical cancer.
Highlights
Cervical cancer (CC) is one of the most prevalent gynecological malignancy in women, and its incidence and mortality are second only to breast cancer
Volcano plot and heatmap analysis showed that gene expression profiles from GSE63514 identified 4,608 differentially expressed genes with 3,053 up-regulated genes and 1,555 down-regulated genes in cervical cancer tissues when compared with normal cervical tissues
Gene Ontology (GO) enrichment analysis showed that changes in the biological processes (BP) of differentially expressed genes (DEGs) were significantly enriched in DNA replication, DNA-dependent DNA replication, and telomere maintenance via semi-conservative replication (Fig. 2B)
Summary
Cervical cancer (CC) is one of the most prevalent gynecological malignancy in women, and its incidence and mortality are second only to breast cancer. It is estimated that 570,000 cases and 311,000 deaths from cervical cancer worldwide occurred in 2018 (Bray et al, 2018). Some studies indicated that over 90% of cases are caused by persistent infection with human papillomavirus (HPV), the main subtypes of which are HPV16 and HPV18 (Schiffman et al, 2011). The genetic sensitivity of CC is caused by HPV infection, which leads to genetic mutations. With the popularization and sharing of biomedical big data, the screening of effective molecular targets related to CC has become possible through bioinformatics methods. The previous studies have reported some targeted molecules regarding CC treatment (Jiao et al, 2019; Wu et al, 2019), but the clinical applications are very limited or even almost none. An urgent and challenging task is to continue to explore early biomarkers in CC
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