Development Immune-Related Prognostic Model and LncRNA-miRNA-mRNA ceRNA Network for Cervical Cancer

Abstract

Cervical cancer is a serious threat to women’s health. The aim of this study was to provide new insights into the mechanism of cervical cancer by constructing immune-related prognostic model and ceRNA network. The mRNA and circRNA datasets of cervical cancer were downloaded from NCBI GEO database. Wilcox.test was used to screen the differential immune cells between cervical cancer patients and normal participants. WGCNA was performed for identification immune related genes. A circRNA-lncRNA-mRNA network was constructed and the genes in the network were further screened for genes related to prognosis using survival package in R software. The prognostic risk model was further validated in the TCGA database. Finally, GSEA was performed to investigate the different enrichment pathways between high_risk and low_risk groups. Nine genes (BEX4, CCL14, CCL3, CMPK2, FMOD, GHR, HLF, IGFBP5, PAG1) were selected to construct the prognostic model. Patients in the low_risk group had a significantly better prognosis than those in the high_risk group. hsa_circ_0021727-hsa-miR-133b-PAG1 regulatory axis may participate in the regulatory of cervical cancer. The enrichment pathways to patients in the high-risk group and the low-risk group were different. The results were not validated by in vitro and in vivo experiments. We developed an immune-related prognostic model and lncRNA-miRNA-mRNA ceRNA network, which can predict prognosis and understand the mechanism of cervical cancer.