Abstract
BACKGROUND: Pancreatic cancer (PC) is an exceedingly malignant ailment that is not only characterized by its insidious onset and rapid progression but also by its poor therapeutic effects. Recently, emerging evidence has shed light on the significant role that non-coding RNAs (ncRNAs), particularly long ncRNAs (lncRNAs) and microRNAs (miRNAs), play in the pathogenesis of PC. This investigation aimed to construct a network of interactions between miRNAs, lncRNAs, and mRNAs, as well as to perform correlation analyses in the context of PC. METHODS: This study carried out in Kerman City, southeastern Iran in 2023. We utilized the GSE119794 dataset from the Gene Expression Omnibus (GEO) to analyze differentially expressed lncRNAs (DE-lncRNAs), miRNAs (DE-miRNAs), and mRNAs (DE-mRNAs). Following the identification of the DE-lncRNAs, DE-mRNAs, and DE-miRNAs, we proceeded to examine differentially expressed epithelialmesenchymal transition (EMT) genes. Subsequently, we utilized the RNAInter database to predict interactions among lncRNAs, miRNAs, and mRNAs. Finally, we employed Cytoscape to visualize and analyze the constructed network. RESULTS: 14 DE-lncRNAs, 14 DE-miRNAs, 545 DE-mRNAs, and 65 DE-EMT from pancreatic cancer and its adjacent tissue RNA-Seq data were identified. 1184 EMT genes from dbEMT were obtained, among which 65 DE-EMT were assigned as EMT genes and correlated with tumor progression. One functional lncRNA (UCA1) was identified as a key functional lncRNA. The area under the ROC curve (AUC) of UCA1 and miR-708-5p were 0.79 and 0.86, respectively. Thus, it is reasonable to believe that this prognostic risk model helps predict PC metastasis. CONCLUSION: UCA1 is a new lncRNA linked with EMT in PC and contributes to a better knowledge of the regulatory mechanisms related to lncRNAs in PC.