Background: This study aimed to assess the differential gene expression of aquaporin (AQP) gene family interactome in pancreatic ductal adenocarcinoma (PDAC) using data mining techniques to identify novel candidate genes intervening in the pathogenicity of PDAC.
Method: Transcriptome data mining techniques were used in order to construct the interactome of the AQP gene family and to determine which genes members are differentially expressed in PDAC as compared to controls. The same techniques were used in order to evaluate the potential prognostic role of the differentially expressed genes.
Results: Transcriptome microarray data of four GEO datasets were incorporated, including 142 primary tumor samples and 104 normal pancreatic tissue samples. Twenty differentially expressed genes were identified, of which nineteen were downregulated and one up-regulated. A molecular panel of four genes (Aquaporin 7 - AQP7; Archain 1 - ARCN1; Exocyst Complex Component 3 - EXOC3; Coatomer Protein Complex Subunit Epsilon - COPE) were identified as potential prognostic markers associated with overall survival.
Conclusion: These outcomes should be further assessed in vitro in order to fully understand the role of these genes in the pathophysiological mechanism of PDAC.
Keywords: AQP7; ARCN1; Aquaporin; Biomarker; PDAC.
Copyright © 2019 IAP and EPC. Published by Elsevier B.V. All rights reserved.