Construction of competitive endogenous RNA network related to circular RNA and prognostic nomogram model in lung adenocarcinoma

Abstract

Early researches have revealed that circular RNA (circRNA) had the potential of biomarkers and could affect tumor progression through regulatory networks. However, few research focused on the function of circRNA in lung adenocarcinoma and the regulation mechanism of competitive endogenous RNA. In present study, through differential expression analysis, 10 circRNAs, 98 miRNAs(microRNA) and 2497 mRNAs were screened. Based on the 10 circRNAs and related databases, a competitive endogenous RNA regulatory network (ceRNA network) containing 7 circRNAs, 13 miRNAs and 147 mRNAs was constructed. KEGG and GO analysis suggested that 147 mRNAs were obviously enriched in biological pathway related to LUAD. By constructing a PPI network, 12 hub genes were identified by MCODE. The result of survival analysis showed that 10 hub genes (BIRC5, MKI67, CENPF, RRM2, BUB1, MELK, CEP55, CDK1, NEK2, TOP2A) were significantly related to the survival of LUAD. We randomly divided 483 clinical data into two parts: train set and validation set. The train set was used for Cox regression analysis, 3 prognostic factors (stage, T, CDK1) were screened. The nomogram model was constructed based on stage, T and CDK1. The model was evaluated by ROC curve, calibration chart, Kaplan-Meier (KM) curve and validation set data. The results indicated that the model has good accuracy. Our study elucidated the regulatory mechanism of circRNA in lung adenocarcinoma, and the nomogram model also provided insight for the clinical analysis of lung adenocarcinoma.

Keywords

• lung adenocarcinoma
• circular rna
• competitive endogenous network
• nomogram model
• bioinformatics