ceRNA network and WGCNA analyses of differentially expressed genes in cervical cancer tissues for association with survival of patients

Abstract Objective To identify differential expressed genes (DEGs) in cervical cancer tissues as prognostic biomarkers. Methods We analyzed gene expression profiles from the Cancer Genome Atlas (TCGA) using R software. DEGs were identified in cervical cancer tissues. miRNAs targeted by differentially expressed long non-coding RNAs (lncRNAs) and mRNAs targeted by microRNAs were identified using bioinformatics tools. The ceRNA network and lncRNA expression modules were constructed using weighted gene co-expression network analysis. Kaplan-Meier analysis confirmed DEGs as prognostic markers. Immunohistochemical analysis validated hub gene expression in 10 paired cervical cancer and normal tissues. Results We identified 1914 DEmRNAs, 210 DElncRNAs, and 67 DEmiRNAs in cervical cancer samples. The ceRNA network revealed several lncRNAs, miRNAs, and mRNAs involved. CACNA1C-AS1 and LIFR-AS1 were associated with specific modules. Three hub genes (E2F1, CCNB1, and CCNE1) showed high expression in cervical cancer tissues and correlated with patient prognosis. Conclusion Our study demonstrates the utility of ceRNA network and WGCNA analyses to identify novel DEGs as prognostic markers in cervical cancer. These findings warrant further validation in future studies.