Background
Many studies focusing on circular RNAs (circRNAs) have recently been published. However, a large number of circRNAs remain to be explored. This study was designed to discover new circRNAs and investigate their potential roles in the pathogenesis of pancreatic ductal adenocarcinoma (PDAC).
Methods
A combination of gene chip analysis and bioinformatic methods was utilized to reveal new circRNAs and their possible mechanisms in PDAC. A circRNA‐miRNA‐mRNA network was established based on the results of differential analyses and interaction predictions. Promising drugs for treating PDAC were determined by connectivity map (CMap) analysis.
Results
Expression profile data were collected from the Gene Expression Omnibus database, and integration of differentially expressed circRNAs (DECs) from two gene chips using the RobustRankAggreg method revealed 10 DECs. The microRNA (miRNA) response elements of these 10 DECs were predicted. The predicted miRNAs and differentially expressed miRNAs were intersected, and 12 overlapping miRNAs were acquired. Next, 2908 miRNA target mRNAs and 1187 differentially expressed genes (DEGs) in PDAC were identified and combined, revealing 118 overlapping mRNAs. A protein‐protein interaction network was constructed with the 118 mRNAs, and four hub genes (CDH1, SERPINE1, IRS1 and FYN) were identified. Using Gene Expression Profiling Interactive Analysis, survival analyses were conducted for the four hub genes, and SERPINE1 and FYN were found to be significantly associated with PDAC patient survival. Functional enrichment analysis indicated that these four hub genes are closely associated with certain cancer‐related biological functions and pathways. In addition, CMap analysis based on the four hub genes was performed to screen potential therapeutic agents for PDAC, and three bioactive chemicals (celastrol, 5109870 and MG‐132) were discovered.
Conclusions
The results of this study further our understanding of the pathogenesis and treatment of PDAC from the perspective of the circRNA‐related competing endogenous RNA network.