Prognostic Nomogram Based on an Immune-Related Biomarker Model Based on the circRNA-Associated Regulatory Network for Cervical cancer

Abstract

Cervical cancer (CC) is a common cancer among women with poor prognosis. Circular RNA (circRNA), as a ceRNA, plays an important role in regulating microRNAs (miRNAs) in many cancers. The immune microenvironment of CC and the regulatory mechanisms at the transcriptomic level have not been fully explored. This study integrated the expression data of circRNA, Long non-coding RNA (lncRNA), miRNA and mRNA from TCGA database, GTEx database and GEO database, and mapped the ceRNA network through variation analysis and correlation analysis. Based on ceRNA network and tumor immune cell infiltration, we constructed two nomograms that can predict CC patients. Through co expression analysis and gene function enrichment, we explored the relationship between prognostic genes and immune cells in the model and the overall function of network node genes. In addition, we screened the drug RO-3306 with sensitivity to high-risk patients and predicted potential drugs with anti CC function by CMap. In conclusion, the research provides relevant information about the diagnosis, treatment and prognosis of CC patients, and several related drugs for reference. Prospective studies are necessary to validate the prognostic ability of this model.