Abstract

Nonalcoholic fatty liver disease (NAFLD) is a widespread liver disorder linked to metabolic conditions and an increased risk of extrahepatic cancers while Gallbladder cancer (GBC) is one of the most common biliary tract malignancies which shares key risk factors with NAFLD, including obesity and gallstone disease. However, the molecular association between NAFLD and GBC remains unexplored. Therefore, the present study was undertaken to identify the common molecular signatures underlying NAFLD and GBC using an in silico computational biology-based approach. RNA-seq datasets for NAFLD (GSE126848) and GBC (GSE139682) were retrieved from the GEO database, common DEGs between the two diseases were identified using GEO2R and analysed using various plugins of Cytoscape. The analysis identified 361 common DEGs and the PPI network, constructed using STRING, consisted of 307 nodes and 517 edges. Seven hub genes i.e., CDC20, CCNA2, TOP2A, BIRC5, CDK1, NUSAP1, and CCNB1, that were found to be predominantly involved in the cell cycle pathway. This study demonstrates that the molecular factors and mechanisms driving the onset and progression of liver diseases such as NAFLD and GBC are the dysregulation of the cell cycle and the hub genes identified in the presented study can be further explored for therapeutic intervention of these diseases.

Key words: Nonalcoholic fatty liver disease (NAFLD), Gallbladder cancer (GBC), Differential gene expression (DEG), computational biology, In-silico, Cell cycle