Published online Oct 21, 2020. doi: 10.3748/wjg.v26.i39.5983
Peer-review started: June 10, 2020
First decision: August 22, 2020
Revised: August 30, 2020
Accepted: September 16, 2020
Article in press: September 16, 2020
Published online: October 21, 2020
Ulcerative colitis (UC) tends to occur in young and middle-aged people. It substantially affects the patient’s quality of life because it is difficult to cure, readily relapses and poses a high risk of colon cancer. However, the pathogenesis of UC is complex and multifaceted, and specific biomarkers for UC are currently unavailable.
In recent years, with the optimization of gene sequencing platforms, differentially expressed genes (DEGs) have been identified through bioinformatics analyses by comparing microarrays. To date, several studies have reported the results of bioinformatics analyses of samples from patients with inflammatory bowel disease using arrays or chips, but the analysis of patients with UC is still lacking. The specific molecules or biomarkers of UC are insufficient. Thus, we will apply bioinformatics methods to more clearly elucidate the underlying biomarkers and mechanisms of UC.
To identify UC-related DEGs by performing a bioinformatics analysis and verify them in vivo and to identify novel biomarkers and the underlying mechanisms of UC.
Two microarray datasets from the National Center for Biotechnology Information-Gene Expression Omnibus database were used, and DEGs were analyzed using GEO2R and Venn diagrams. We annotated these genes based on functions and signaling pathways. Then protein-protein interaction (PPI) were constructed using the Search Tool for the Retrieval of Interacting Genes. The data were further analyzed with Cytoscape software and the Molecular Complex Detection (MCODE) app. The core genes were selected, and the Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis was repeated. Finally, colitis model mice were established by administering dextran sulfate sodium, and the top three core genes were verified in colitis mice using real-time polymerase chain reaction.
One hundred and seventy-seven DEGs (118 upregulated genes and 59 downregulated genes) predominantly participated in inflammation-related pathways. Seventeen core genes were upregulated, and one gene was downregulated in the first cluster according to the PPI and MCODE analyses in Cytoscape. These genes were markedly enriched in the cytokine-cytokine receptor interaction and chemokine signaling pathways. The top three core genes showed increased expression compared with the control mice, but only the difference in C-X-C motif chemokine receptor 2 (CXCR2) expression was statistically significant. CXCR2 may reflect the degree of inflammation in patients with UC and serve as an underlying treatment target.
Core DEGs identified in patients with UC are related to inflammation and immune inflammatory reactions, indicating that these reactions are core features of the pathogenesis of UC. CXCR2 may reflect the degree of inflammation in patients with UC.
CXCR2 may represent a new biomarker to determine the degree of inflammation or a treatment target in UC. In the future, the combination of CXCR2 with other biomarkers will potentially improve the ability to diagnose and dynamically monitor UC.