Abstract
BackgroundThis study aimed to explore and identify key genes and signaling pathways that contribute to the progression of cervical cancer to improve prognosis.MethodsThree gene expression profiles (GSE63514, GSE64217 and GSE138080) were screened and downloaded from the Gene Expression Omnibus database (GEO). Differentially expressed genes (DEGs) were screened using the GEO2R and Venn diagram tools. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed. Gene set enrichment analysis (GSEA) was performed to analyze the three gene expression profiles. Moreover, a protein–protein interaction (PPI) network of the DEGs was constructed, and functional enrichment analysis was performed. On this basis, hub genes from critical PPI subnetworks were explored with Cytoscape software. The expression of these genes in tumors was verified, and survival analysis of potential prognostic genes from critical subnetworks was conducted. Functional annotation, multiple gene comparison and dimensionality reduction in candidate genes indicated the clinical significance of potential targets.ResultsA total of 476 DEGs were screened: 253 upregulated genes and 223 downregulated genes. DEGs were enriched in 22 biological processes, 16 cellular components and 9 molecular functions in precancerous lesions and cervical cancer. DEGs were mainly enriched in 10 KEGG pathways. Through intersection analysis and data mining, 3 key KEGG pathways and related core genes were revealed by GSEA. Moreover, a PPI network of 476 DEGs was constructed, hub genes from 12 critical subnetworks were explored, and a total of 14 potential molecular targets were obtained.ConclusionsThese findings promote the understanding of the molecular mechanism of and clinically related molecular targets for cervical cancer.
Highlights
This study aimed to explore and identify key genes and signaling pathways that contribute to the progression of cervical cancer to improve prognosis
The gene expression profiles related to Cervical intraepithelial neoplasia (CIN) progression were retrieved and downloaded from the Gene Expression Omnibus (GEO) database of the National Center for Biotechnology Information (NCBI)
The results showed that the hub genes constituted the key network of cervical carcinogenesis, and the genes were scored with the cytoHubba plug-in
Summary
This study aimed to explore and identify key genes and signaling pathways that contribute to the progression of cervical cancer to improve prognosis. Human papillomavirus (HPV) infection is a primary cause of cervical cancer and led to 311,365 deaths in 2018 [1]. Wu and Xi BMC Cancer (2021) 21:733 development of bioinformatics, more studies have focused on the signaling and metabolic pathways of cervical cancer, data mining and validation of related biomolecular targets. The aim of this study was to explore and identify the key genes and signaling pathways contributing to the progression of cervical cancer to improve prognosis. An integrated bioinformatics analysis was performed to select differentially expressed genes (DEGs) and hub genes and to investigate their protein–protein interaction (PPI) networks, related prognostic signatures, functional annotations and potential prognostic value. This study may offer better insight into potential molecular mechanisms to explore preventive and therapeutic strategies
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