Identification of circRNA-miRNA-mRNA networks to explore underlying mechanism in lung cancer.

BACKGROUND

Circular RNAs (circRNAs) are involved in the occurrence and development of various tumors. CircRNAs can act as competing endogenous RNAs (ceRNAs), which are important regulatory networks, by regulating microRNAs (miRNAs). However, the effects of ceRNA networks on lung cancer (LC), especially the circRNA-miRNA-mRNA regulatory network, remain incompletely understood. Therefore, the aim of this study was to explore novel ceRNA networks and their function and underlying mechanisms in LC.

METHODS

Six RNA expression datasets were obtained from the Gene Expression Omnibus microarray datasets (circRNA: GSE158695, GSE101684, GSE112214, and GSE101586; miRNA: GSE135918; mRNA: GSE98929). First, we constructed a circRNA-miRNA-mRNA ceRNA network in LC using Cytoscape. Second, we constructed a protein-protein interaction network using STRING and identified hub genes using CytoHubba. Functional analysis was performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) to predict the potential function of the hub genes. Third, expression and survival analysis of the hub genes were performed to identify prognostic genes.

RESULTS

We constructed a ceRNA network including 18 circRNAs, 32 miRNAs, and 135 mRNAs, and identified 10 hub genes (, , , , , , , , , and ). Both GO and KEGG analyses revealed that the 10 hub genes were associated with several cancer‑related biological functions and pathways, including "oxygen levels", "nuclear division", and "HIF-1 signaling pathway". Five genes (, , , , and ) were associated with the prognosis of lung adenocarcinoma (LUAD), the most common histological type of LC.

CONCLUSION

Our study provides novel insights into the pathogenesis and therapy of LC from a ceRNA network perspective.