Bioinformatics analysis of oxidative stress genes in the pathogenesis of ulcerative colitis based on a competing endogenous RNA regulatory network.

Ulcerative colitis (UC) is a common chronic disease associated with inflammation and oxidative stress. This study aimed to construct a long noncoding RNA (lncRNA)-microRNA (miRNA)-messenger RNA (mRNA) network based on bioinformatics analysis and to explore oxidative stress-related genes underlying the pathogenesis of UC. The GSE75214, GSE48959, and GSE114603 datasets were downloaded from the Gene Expression Omnibus database. Following differentially expressed (DE) analysis, the regulatory relationships among these DERNAs were identified through miRDB, miRTarBase, and TargetScan; then, the lncRNA-miRNA-mRNA network was established. The Molecular Signatures Database (MSigDB) was used to search oxidative stress-related genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed for functional annotation and enrichment analyses. Based on the drug gene interaction database DGIdb, drugs that interact with oxidative stress-associated genes were explored. A dextran sulfate sodium (DSS)-induced UC mouse model was used for experimental validation. A total of 30 DE-lncRNAs, 3 DE-miRNAs, and 19 DE-mRNAs were used to construct a lncRNA-miRNA-mRNA network. By comparing these 19 DE-mRNAs with oxidative stress-related genes in MSigDB, three oxidative stress-related genes (CAV1, SLC7A11, and SLC7A5) were found in the 19 DEM sets, which were all negatively associated with miR-194. GO and KEGG analyses showed that CAV1, SLC7A11, and SLC7A5 were associated with immune inflammation and steroid hormone synthesis. In animal experiments, the results showed that dexamethasone, a well-known glucocorticoid drug, could significantly decrease the expression of CAV1, SLC7A11, and SLC7A5 as well as improve UC histology, restore antioxidant activities, inhibit inflammation, and decrease myeloperoxidase activity. SLC7A5 was identified as a representative gene associated with glucocorticoid therapy resistance and thus may be a new therapeutic target for the treatment of UC in the clinic.

Li Q ，Liu Y ，Li B ，Zheng C ，Yu B ，Niu K ，Qiao Y ... -  《PeerJ》

Construction, bioinformatics analysis, and validation of competitive endogenous RNA networks in ulcerative colitis.

Background: Ulcerative colitis (UC) is a common chronic disease of the digestive system. Recently, competitive endogenous RNAs (ceRNAs) have been increasingly used to reveal key mechanisms for the pathogenesis and treatment of UC. However, the role of ceRNA in UC pathogenesis has not been fully clarified. This study aimed to explore the mechanism of the lncRNA-miRNA-mRNA ceRNA network in UC and identify potential biomarkers and therapeutic targets. Materials and Methods: An integrative analysis of mRNA, microRNA (miRNA), and long non-coding RNA (lncRNA) files downloaded from the Gene Expression Omnibus (GEO) was performed. Differentially expressed mRNA (DE-mRNAs), miRNA (DE-miRNAs), and lncRNA (DE-lncRNAs) were investigated between the normal and UC groups by the limma package. A weighted correlation network analysis (WGCNA) was used to identify the relative model for constructing the ceRNA network, and, concurrently, miRWalk and DIANA-LncBase databases were used for target prediction. Consecutively, the Gene Ontology (GO), Kyoto encyclopedia of genes and genomes (KEGG) pathway, and Reactome pathway enrichment analyses, protein-protein interaction (PPI) network, Cytohubba, and ClueGO were performed to identify hub genes. Additionally, we examined the immune infiltration characteristics of UC and the correlation between hub genes and immune cells using the immuCellAI database. Finally, the expression of potential biomarkers of ceRNA was validated via qRT-PCR in an experimental UC model induced by dextran sulfate sodium (DSS). Result: The ceRNA network was constructed by combining four mRNAs, two miRNAs, and two lncRNAs, and the receiver operating characteristic (ROC) analysis showed that two mRNAs (CTLA4 and STAT1) had high diagnostic accuracy (area under the curve [AUC] > 0.9). Furthermore, CTLA4 up-regulation was positively correlated with the infiltration of immune cells. Finally, as a result of this DSS-induced experimental UC model, CTLA4, MIAT, and several associate genes expression were consistent with the results of previous bioinformatics analysis, which proved our hypothesis. Conclusion: The investigation of the ceRNA network in this study could provide insight into UC pathogenesis. CTLA4, which has immune-related properties, can be a potential biomarker in UC, and MIAT/miR-422a/CTLA4 ceRNA networks may play important roles in UC.

Dong L ，Zhang R ，Huang Q ，Shen Y ，Li H ，Yu S ，Wu Q ... -  《Frontiers in Genetics》

Integrative analysis of an lncRNA‑associated competing endogenous RNA network in human trabecular meshwork cells under oxidative stress.

Yao K ，Yu Y ，Li F ，Jin P ，Deng C ，Zhang H ... -  《-》

Excavating novel diagnostic and prognostic long non-coding RNAs (lncRNAs) for head and neck squamous cell carcinoma: an integrated bioinformatics analysis of competing endogenous RNAs (ceRNAs) and gene co-expression networks.

Yang L ，Lu P ，Yang X ，Li K ，Chen X ，Qu S ... -  《-》

Bioinformatic and integrated analysis identifies an lncRNA-miRNA-mRNA interaction mechanism in gastric adenocarcinoma.

Liao Y ，Cao W ，Zhang K ，Zhou Y ，Xu X ，Zhao X ，Yang X ，Wang J ，Zhao S ，Zhang S ，Yang L ，Liu D ，Tian Y ，Wu W ... -  《-》