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

Li Y ，Yuan F ，Lin Z ，Pan Y ... -  《-》

Identification of the circRNA-miRNA-mRNA regulatory network and its prognostic effect in colorectal cancer.

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. However, the biological function of ceRNAs in CRC pathogenesis and prognosis remains largely unexplored. To identify the CRC-specific circRNA-miRNA-mRNA regulatory network and uncover the subnetwork associated with its prognosis. CircRNAs, miRNAs and mRNAs differentially expressed (DE) in CRC tissues were selected by expression file analysis in the Gene Expression Omnibus (GEO) database, and the downstream target molecules of circRNAs and miRNAs were predicted. Then, the intersection of differentially expressed RNA molecules with the predicted targets was determined to obtain a ceRNA network. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were conducted to elucidate the possible mechanism of pathogenesis. A survival analysis using the gene profiles and clinical information in The Cancer Genome Atlas (TCGA) database was performed to identify the mRNAs associated with the clinical outcome of CRC patients and construct a prognostic subnetwork. We downloaded three datasets (GSE126095, GSE41655 and GSE41657) of large-scale CRC samples from the GEO database. There were 55 DEcircRNAs, 114 DEmiRNAs and 267 DEmRNAs in CRC tissues compared with normal tissues. After intersecting these molecules with predicted targets, 19 circRNAs, 13 miRNAs and 28 mRNAs were chosen to develop a circRNA-miRNA-mRNA network. GO and KEGG functional enrichment analyses indicated that the retinol metabolic process, leukocyte chemotaxis, extracellular matrix remodeling, endoplasmic reticulum stress, alcohol dehydrogenase activity, gastric acid secretion, nitrogen metabolism and NOD-like receptor signaling pathway might participate in the tumorigenesis of CRC. After verifying the identified mRNA effect in the TCGA database, we finally recognized 3 mRNAs (CA2, ITLN1 and LRRC19) that were significantly associated with the overall survival of CRC patients and constructed a ceRNA subnetwork including 5 circRNAs (hsa_circ_0080210, hsa_circ_0007158, hsa_circ_0000375, hsa_circ_0018909 and hsa_circ_0011536) and 3 miRNAs (hsa-miR-601, hsa-miR-671-5p and hsa-miR-765), which could contain innovative and noninvasive indicators for the early screening and prognostic prediction of CRC. We proposed a circRNA-miRNA-mRNA regulatory network closely associated with the progression and clinical outcome of CRC that might include promising biomarkers for carcinogenesis and therapeutic targets.

Yin TF ，Zhao DY ，Zhou YC ，Wang QQ ，Yao SK ... -  《World Journal of Clinical Cases》

Bioinformatics Analysis Predicts hsa_circ_0026337/miR-197-3p as a Potential Oncogenic ceRNA Network for Non-Small Cell Lung Cancers.

Circular RNAs (circRNAs) play an essential role in developing tumors, but their role in Non- Small Cell Lung Cancer (NSCLC) is unclear. Thus, the present study explored the possible molecular mechanism of circRNAs in NSCLC. Three circular RNA (circRNA) microarray datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differential expressions of circRNAs (DECs) were identified in NSCLC tissue and compared to adjacent healthy tissue. The online cancer-specific circRNA database (CSCD) was used for the analysis of the DECs function. Protein-Protein Interaction (PPI) network, Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), Cytoscape and UALCAN were used to predict the critical nodes and perform patient survival analysis, respectively. The interaction between the DECs, the predicted miRNAs, and hub genes was also determined. Finally, the circRNA-miRNA-mRNA network was established. The expression of hsa_circ_0049271, hsa_circ_0026337, hsa_circ_0043256, and hsa_circ_0008234 was decreased in NSCLC tissues. The Encyclopedia of RNA Interactomes (ENCORI) and CSCD database results showed that hsa_circ_0026337 was found to sponge with miR-1193, miR-197-3p, miR-3605-5p, miR-433-3p and miR-652-3p, and hsa_circ_0043256 to sponge with miR-1252-5p, miR-494-3p and miR-558, respectively. Subsequently, 100 mRNAs were predicted to bind with these seven miRNA response elements (MREs). The GO analysis and KEGG pathway revealed that these 100 MREs might be involved in "histone deacetylase binding" and "cellular senescence." PPI network and Cytoscape identified the top ten hub genes. Survival analysis data showed that the low expression of hsa_circ_0026337 was significantly associated with shortened survival time in NSCLC (P = 0.037), which increased the expression level of hsa-miR-197-3p, thereby inhibiting the translation of specific proteins. This study examined the circRNA-miRNA-mRNA regulatory network associated with NSCLC and explored the potential functions of DECs in the network to elucidate the mechanisms underlying disease progression in NSCLC.

Zhang Q ，Kang L ，Li X ，Li Z ，Wen S ，Fu X ... -  《-》

Bioinformatics analysis of the circRNA-miRNA-mRNA network for atrial fibrillation.

Atrial fibrillation (AF) is a chronic and progressive disease, with advancing age, the morbidity of which will increase exponentially. Circular ribonucleic acids (RNAs; circRNAs) have gained a growing attention in the development of AF in recent years. The purpose of this study is to explore the mechanism of circRNA regulation in AF, in particular, the intricate interactions among circRNA, microRNA (miRNA), and messenger RNA (mRNA). Three datasets (GSE129409, GSE68475, and GSE79768) were obtained from the Gene Expression Omnibus database to screen differentially expressed (DE) circRNAs, DE miRNAs, and DE mRNAs in AF, respectively. Based on circRNA-miRNA pairs and miRNA-mRNA pairs, a competing endogenous RNAs (ceRNAs) network was built. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analysis of DE mRNAs in the network were performed and protein-protein interaction (PPI) networks were established to identify hub genes. Finally, a circRNA-miRNA-hub gene subnetwork was constructed. A total of 103 DE circRNAs, 16 DE miRNAs, and 110 DE mRNAs were screened in AF. Next, ceRNAs network in AF was constructed with 3 upregulated circRNAs, 2 downregulated circRNAs, 2 upregulated miRNAs, 2 downregulated miRNAs, 17 upregulated mRNAs, and 24 downregulated mRNAs. Thirty GO terms and 6 KEGG pathways were obtained. Besides, 6 hub genes (C-X-C chemokine receptor type 4 [CXCR4], C-X-C chemokine receptor type 2 [CXCR2], C-X-C motif chemokine 11 [CXCL11], neuromedin-U, B1 bradykinin receptor, and complement C3) were screened from constructing a PPI network. Finally, a circRNA-miRNA-hub gene subnetwork with 10 regulatory axes was constructed to describe the interactions among the differential circRNAs, miRNA, and hub genes. We speculated that hsa_circRNA_0056281/hsa_circRNA_0006665 -hsa-miR-613-CXCR4/CXCR2/CXCL11 regulatory axes and hsa_circRNA_0003638-hsa-miR-1207-3p-CXCR4 regulatory axis may be associated with the pathogenesis of AF.

Liu X ，Zeng Y ，Liu Z ，Li W ，Wang L ，Wu M ... -  《-》

Identification of potentially functional circular RNAs hsa_circ_0070934 and hsa_circ_0004315 as prognostic factors of hepatocellular carcinoma by integrated bioinformatics analysis.

Hepatocellular carcinoma (HCC) is one of the most prevalent cancers worldwide, which has a high mortality rate and poor treatment outcomes with yet unknown molecular basis. It seems that gene expression plays a pivotal role in the pathogenesis of the disease. Circular RNAs (circRNAs) can interact with microRNAs (miRNAs) to regulate gene expression in various malignancies by acting as competitive endogenous RNAs (ceRNAs). However, the potential pathogenesis roles of the ceRNA network among circRNA/miRNA/mRNA in HCC are unclear. In this study, first, the HCC circRNA expression data were obtained from three Gene Expression Omnibus microarray datasets (GSE164803, GSE94508, GSE97332), and the differentially expressed circRNAs (DECs) were identified using R limma package. Also, the liver hepatocellular carcinoma (LIHC) miRNA and mRNA sequence data were retrieved from TCGA and differentially expressed miRNAs (DEMIs) and mRNAs (DEGs) were determined using the R DESeq2 package. Second, CSCD website was used to uncover the binding sites of miRNAs on DECs. The DECs' potential target miRNAs were revealed by conducting an intersection between predicted miRNAs from CSCD and downregulated DEMIs. Third, candidate genes were uncovered by intersecting targeted genes predicted by miRWalk and targetscan online tools with upregulated DEGs. The ceRNA network was then built using the Cytoscape software. The functional enrichment and the overall survival time of these potential targeted genes were analyzed, and a PPI network was constructed in the STRING database. Network visualization was performed by Cytoscape, and ten hub genes were detected using the CytoHubba plugin tool. Four DECs (hsa_circ_0000520, hsa_circ_0008616, hsa_circ_0070934, hsa_circ_0004315) were obtained and six miRNAs (hsa-miR-542-5p, hsa-miR-326, hsa-miR-511-5p, hsa-miR-195-5p, hsa-miR-214-3p, and hsa-miR-424-5p) which are regulated by the above DECs were identified. Then 543 overlapped genes regulated by six miRNAs mentioned above were predicted. Functional enrichment analysis showed that these genes are mostly associated with regulatory pathways in cancer. Ten hub genes (TTK, AURKB, KIF20A, KIF23, CEP55, CDC6, DTL, NCAPG, CENPF, PLK4) have been screened from the PPI network of the 204 survival-related genes. KIF20A, NCAPG, TTK, PLK4, and CDC6 were selected for the highest significance p-values. At the end, a circRNA-miRNA-mRNA regulatory axis was established for five final selected hub genes. This study implies the potential pathogenesis of the obtained network and proposes that the two DECs (has_circ_0070934 and has_circ_0004315) may be important prognostic markers for HCC.

Morovat P ，Morovat S ，Ashrafi AM ，Teimourian S ... -  《Scientific Reports》