Dataset Information

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

ABSTRACT:

Background

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.

Aim

To identify the CRC-specific circRNA-miRNA-mRNA regulatory network and uncover the subnetwork associated with its prognosis.

Methods

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.

Results

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.

Conclusion

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.

SUBMITTER: Yin TF

PROVIDER: S-EPMC8223824 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BACKGROUND As all we know, gastric cancer (GC) is a highly aggressive disease. Recently, circular RNA (circRNA) was found to play a vital role in regulation of GC. Some circRNAs could regulate messenger RNA (mRNA) expression by functioning as a microRNA (miRNA) sponge. Nevertheless, the circRNA-miRNA-mRNA regulatory network involved GC rarely has been explored and researched. MATERIAL AND METHODS All the differentially expressed circRNAs, miRNAs, and mRNA were derived from Gene Expression Omnibus (GEO) microarray data (GSE78092, GSE89143, GSE93415, and GSE54129). GC level 3 miRNA-sequencing data and clinical information were downloaded from The Cancer Genome Atlas (TCGA) database. Furthermore, a circRNA-miRNA-mRNA regulatory network was constructed by Cytoscape (version 3.6.1). Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway revealed the functions and signaling pathways associated with these target genes. Hub genes of protein-protein interaction (PPI) network were identified by STRING database and cytoHubba. RESULTS The regulatory network consists of 3 circRNAs, 22 miRNAs, and 128 mRNAs. Only 3 miRNAs of the network were consistent with the expression of TCGA and were associated with some clinical features. The results of the functional analysis of 128 mRNAs showed that GO analysis and KEGG pathways of inclusion criteria were 49 and 24, respectively. PPI network and Cytoscape showed that the top 10 hub genes were MYC, CTGF, TGFBR2, TGFBR1, SERPINE1, KRAS, ZEB1, THBS1, CDK6, and TNS1; 4 of which were verified by GEPIA based on TCGA. Highly expressed SERPINE1 had a poor OS (over survival) and DFS (disease-free survival), and TGFBR1 expression increased along with the increase of clinical stages. CONCLUSIONS This study looked at a circRNA-miRNA-mRNA regulatory network associated with GC and explored the potential functions of mRNA in the network, then identified a new molecular marker for prediction, prognosis, and therapeutic targets for clinical patients.

Project description:Gastric cancer (GC) is one of the most common malignancies in the world, with morbidity and mortality ranking second among all cancers. Accumulating evidences indicate that circular RNAs (circRNAs) are closely correlated with tumorigenesis. However, the mechanisms of circRNAs still remain unclear. This study is aimed at determining hub genes and circRNAs and analyzing their potential biological functions in GC. Expression profiles of mRNAs and circRNAs were downloaded from the Gene Expression Omnibus (GEO) data sets of GC and paracancer tissues. Differentially expressed genes (DEGs) and differentially expressed circRNAs (DE-circRNAs) were identified. The target miRNAs of DE-circRNAs and the bidirectional interaction between target miRNAs and DEGs were predicted. Functional analysis was performed, and the protein-protein interaction (PPI) network and the circRNA-miRNA-mRNA network were established. A total of 456 DEGs and 2 DE-circRNAs were identified with 3 mRNA expression profiles and 2 circRNA expression profiles. GO analysis indicated that DEGs were mainly enriched in extracellular matrix and cell adhesion, and KEGG confirmed that DEGs were mainly associated with focal adhesion, the PI3K-Akt signaling pathway, extracellular matrix- (ECM)- receptor interaction, and gastric acid secretion. 15 hub DEGs (BGN, COL1A1, COL1A2, FBN1, FN1, SPARC, SPP1, TIMP1, UBE2C, CCNB1, CD44, CXCL8, COL3A1, COL5A2, and THBS1) were identified from the PPI network. Furthermore, the survival analysis indicate that GC patients with a high expression of the following 9 hub DEGs, namely, BGN, COL1A1, COL1A2, FBN1, FN1, SPARC, SPP1, TIMP1, and UBE2C, had significantly worse overall survival. The circRNA-miRNA-mRNA network was constructed based on 1 circRNA, 15 miRNAs, and 45 DEGs. In addition, the 45 DEGs included 5 hub DEGs. These results suggested that hub DEGs and circRNAs could be implicated in the pathogenesis and development of GC. Our findings provide novel evidence on the circRNA-miRNA-mRNA network and lay the foundation for future research of circRNAs in GC.