To identify differential expressed genes (DEGs) in cervical cancer tissues as prognostic biomarkers.
MethodsWe analyzed gene expression pro les from the Cancer Genome Atlas (TCGA) using R software. DEGs were identi ed in cervical cancer tissues. miRNAs targeted by differentially expressed long non-coding RNAs (lncRNAs) and mRNAs targeted by microRNAs were identi ed using bioinformatics tools. The ceRNA network and lncRNA expression modules were constructed using weighted gene co-expression network analysis. Kaplan-Meier analysis con rmed DEGs as prognostic markers. Immunohistochemical analysis validated hub gene expression in 10 paired cervical cancer and normal tissues.
ResultsWe identi ed 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 speci c modules. Three hub genes (E2F1, CCNB1, and CCNE1) showed high expression in cervical cancer tissues and correlated with patient prognosis.
ConclusionOur study demonstrates the utility of ceRNA network and WGCNA analyses to identify novel DEGs as prognostic markers in cervical cancer. These ndings warrant further validation in future studies.