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

Author:

Li Qifang1,Liu Yuan2,Li Bingbing2,Zheng Canlei2,Yu Bin2,Niu Kai2ORCID,Qiao Yi3

Affiliation:

1. Department of Traditional Chinese Medicine, Affiliated Hospital of Jining Medical University, Jining, Shandong, China

2. College of Integrated Chinese and Western Medicine, Jining Medical University, Jining, Shandong, China

3. School of Public Health, Jining Medical University, Jining, Shandong, China

Abstract

Background 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. Methods 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. Results 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. Conclusion 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.

Funder

National Natural Science Foundation of China

Natural Science Foundation of Shandong Province

Key Research and Development Plan of Jining

Publisher

PeerJ

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