Reanalysis of the gene expression profile in chronic pancreatitis via bioinformatics methods

BACKGROUND: Diagnosis at an early stage of chronic pancreatitis (CP) is challenging. It has been reported that microRNAs (miRNAs) are increasingly found and applied as targets for the diagnosis and treatment of various cancers. However, to the best of our knowledge, few published papers have described the role of miRNAs in the diagnosis of CP. METHOD: We downloaded gene expression profile data from the Gene Expression Omnibus and identified differentially expressed genes (DEGs) between CP and normal samples of Harlan mice and Jackson Laboratory mice. Common DEGs were filtered out, and the semantic similarities of gene classes were calculated using the GOSemSim software package. The gene class with the highest functional consistency was selected, and then the Lists2Networks web-based system was used to analyse regulatory relationships between miRNAs and gene classes. The functional enrichment of the gene classes was assessed based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway annotation terms. RESULTS: A total of 405 common upregulated DEGs and 7 common downregulated DEGs were extracted from the two kinds of mice. Gene cluster D was selected from the common upregulated DEGs because it had the highest semantic similarity. miRNA 124a (miR-124a) was found to have a significant regulatory relationship with cluster D, and DEGs such as CHSY1 and ABCC4 were found to be regulated by miR-124a. The GO term of response to DNA damage stimulus and the pathway of Escherichia coli infection were significantly enriched in cluster D. CONCLUSION: DNA damage and E. coli infection might play important roles in CP pathogenesis. In addition, miR-124a might be a potential target for the diagnosis and treatment of CP.