Bioinformatics-based analysis of EMT-related genes in cervical cancer patients

Background: In most cases, patients who are not screened canonically have advanced disease by the time they are first diagnosed. Therefore, invasive metastasis is the main feature and cause of death in patients with advanced cervical cancer. Methods: The GEO database was searched for analytical data on cervical cancer. The GSE9750 dataset was employed to identify differentially expressed genes (DEGs) in tumor samples compared to normal samples, carry out enrichment analysis, build protein-protein interaction (PPI) networks to identify key genes (Hub gene), and perform between diagnostic genes and immune infiltrated cells. Results: A total of 1440 DEGs and 46 differential genes linked to EMT were screened. GO enrichment produced 455 results, and Kyoto Encyclopedia of Genes and Genomes pathway enrichment （KEGG ）yielded a total of 18 pathways. A PPI network was built using 46 differential genes related to EMT, and 9 Hub genes were also validated. Nine hub genes had exactly the same up- and down-regulation trend as before in the external verification set, but only six hub genes were ultimately determined to be diagnostic genes after further validation by the external verification set. The results of the KM (Kaplan-Meier) survival study also revealed five prognostic genes related to survival, namely MMP1, CXCL8, SSP1, MMP3, and VCAM1. Conclusion: The genes MMP1, CXCL8, SSP1, MMP3, and VCAM1are crucial in the development of EMT in patients with cervical cancer and can be employed as both diagnostic and therapeutic targets during the progression of EMT in cervical cancer patients.