Background: Circular RNAs (circRNAs) are involved in the pathogenesis of many diseases through competing endogenous RNA (ceRNA) regulatory mechanisms.
Aim: To investigate a circRNA-related ceRNA regulatory network and a new predictive model by circRNA to understand the diagnostic mechanism of circRNAs in ulcerative colitis (UC).
Methods: We obtained gene expression profiles of circRNAs, miRNAs, and mRNAs in UC from the Gene Expression Omnibus dataset. The circRNA-miRNA-mRNA network was constructed based on circRNA-miRNA and miRNA-mRNA interactions. Functional enrichment analysis was performed to identify the biological mechanisms involved in circRNAs. We identified the most relevant differential circRNAs for diagnosing UC and constructed a new predictive nomogram, whose efficacy was tested with the C-index, receiver operating characteristic curve (ROC), and decision curve analysis (DCA).
Results: A circRNA-miRNA-mRNA regulatory network was obtained, containing 12 circRNAs, three miRNAs, and 38 mRNAs. Two optimal prognostic-related differentially expressed circRNAs, hsa_circ_0085323 and hsa_circ_0036906, were included to construct a predictive nomogram. The model showed good discrimination, with a C-index of 1(> 0.9, high accuracy). ROC and DCA suggested that the nomogram had a beneficial diagnostic ability.
Conclusion: This novel predictive nomogram incorporating hsa_circ_0085323 and hsa_circ_0036906 can be conveniently used to predict the risk of UC. The circRNa-miRNA-mRNA network in UC could be more clinically significant.
Keywords: Bioinformatics; Circular RNAs; Diagnose; New predictive model; RNA regulatory network; Ulcerative colitis.
©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.