Construction of endogenous RNA regulatory network for colorectal cancer based on bioinformatics.

OBJECTIVES

The high morbidity and mortality of colorectal cancer (CRC) have posed great threats to human health. Circular RNA (circRNA) and microRNA (miRNA), acting as competing endogenous RNAs (ceRNAs), have been found to play vital roles in carcinogenesis. This paper aims to construct a circRNA/miRNA/mRNA regulatory network so as to explore the molecular mechanism of CRC.

METHODS

The sequencing data of circRNA from CRC were obtained from Gene Expression Omnibus (GEO). The differential circRNA was screened and its structure was identified by Cancer-specific CircRNA Database (CSCD); the sequencing data of miRNA and messenger RNA (mRNAs) were downloaded from The Cancer Genome Atlas (TCGA) database and the differentially expressed genes were screened; the corresponding miRNA of differential circRNAs were predicted by CircInteractome database; DIANA, Miranda, PicTar, and TargetScan databases were used to predict the target genes of different miRNAs; the target genes from Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were enriched by R language; String database combined with Cytoscape 3.7.2 software was used to construct protein-protein interaction (PPI) network and hub genes were screened; the expressions of mRNAs in the Top10 hub genes were verified in CRC. The network diagrams of circRNAs/miRNAs/mRNAs and circRNAs/miRNAs/Top10 hub mRNAs were constructed by Cytoscape3.7.2. Real-time PCR was used to examine the expression levels of hsa_circRNA_0065173, hsa-mir-450b, hsa-mir-582, adenylate cyclase 5 (), muscarinic acetylcholine receptor M2 (), cannabinoid receptor 1 (), and lysophosphatidic acid receptor 1 () in the CRC tissues and the adjacent normal tissues.

RESULTS

A total of 14 differential circRNAs were identified, and 8 were found in CSCD; 34 miRNAs targeted by circRNAs were obtained. The PPI network was constructed, and the Top10 hub genes were identified, which were , melanin concentrating hormone receptor 2 (), G-protein gamma 3 subunit (), neuropeptide Y receptor Y1 (), , , , adenylate cyclase 2 (), gamma 7 () and chemokine 12 (), respectively. The expressions of Top 10 hub genes were also verified, and the results showed that the Top 10 hub genes were down-regulated in CRC; the constructed network diagram showed that hsa_circRNA_0065173 may regulate , , and Hsa-mir-450b by modulating hsa-mir-450b and hsa-mir-582. and genes might serve as potentially relevant targets for the treatment of CRC. Real-time PCR results showed that the expression levels of hsa_circRNA_0065173, , , and in the CRC tissues were significantly reduced compared with the adjacent normal tissues (all <0.05); the expression levels of hsa-mir-450b and hsa-miR-582 were significantly increased (both <0.05).

CONCLUSIONS

In this study, a potential circRNAs/miRNAs/mRNAs network is successfully constructed, which provides a new insight for CRC development mechanism through ceRNA mediated by circRNAs.