Identifying the molecular association between diabetic nephropathy and hepatocellular carcinoma: an in-silico network biology approach

Diabetic nephropathy (DN) and hepatocellular carcinoma (HCC) pose significant global health burdens. DN is the leading cause of end-stage renal disease and is closely associated with metabolic dysregulation, whereas HCC is the most common primary liver cancer, often arising from chronic liver conditions, including non-alcoholic fatty liver disease and cirrhosis. Although studies have indicated a clinical association between DN and HCC, the underlying molecular association remains unexplored; therefore, the present <i>in-silico</i> network biology study was conducted. Microarray datasets for DN and HCC were retrieved from the Gene Expression Omnibus and processed using Bioconductor Packages to identify differentially expressed genes (DEGs). For the common DEGs between DN and HCC, a protein-protein interaction (PPI) network was constructed using STRING. Topological analysis of the PPI network was performed using Cytoscape and its plug-ins, MCODE, CytoHubba, and CytoCluster, to identify hub genes, and their functional enrichment was performed using Enrichr Knowledge Graph. From the 67 common DEGs, five hub genes were identified, namely, <i>APOA2</i>, <i>APOA5</i>, <i>APOC1</i>, <i>APOC3</i>, and <i>APOH</i>, which belong to the apolipoprotein family. Kyoto Encyclopedia of Genes and Genomes enrichment analysis identified their involvement in cholesterol metabolism and proliferator-activated receptors (PPAR) signaling pathway, emphasizing their potential significance in lipid and other metabolic processes. Dysregulation of apolipoproteins results in altered lipid metabolism and oxidative stress in both diabetic complications and cancer progression. In conclusion, the hub genes identified in the present study can be further explored as promising biomarkers for prognosis and diagnosis in DN and HCC, as well as therapeutic interventions.