A Systems Biology Approach to Pathogenesis of Gastric Cancer: Gene Network Modeling and Pathway Analysis

IntroductionGastric cancer (GC) ranks among the most common malignancies worldwide. In our previous study, we found overexpressed genes in GC clinical samples. The goal of the current study was to find critical genes and key pathways involved in the pathogenesis of GC. MethodsGene interactions were analyzed using STRING, and Cytoscape was used to visualize the molecular interaction network. CytoHubba was used for drawing the PPI network and identifying hub proteins. The Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) at STRING were used for the enrichment analysis of the hub genes. Cluster analysis of the network was done using CytoCluster. MEME Suite was used for promoter analysis of the hub genes using Tomtom and GoMo tools. Results and DiscussionOur results showed that the most affected processes in GC are the metabolic processes. The OXPHOS pathway was also considerably enriched in our analyses. These results showed the significant role of mitochondria in GC pathogenesis. Although many investigations have focused on the mitochondrial role in the pathogenesis of various cancers, the characteristics of respiratory and metabolic changes in GC have not been fully elucidated. Our results also showed that most of the affected pathways in GC were the pathways also involved in neurodegenerative diseases. Also, promoter analysis showed that negative regulation of signal transduction might play an important role in GC pathogenesis. The results of this study might open up new insights into GC pathogenesis. The identified genes might be novel diagnostic or prognostic biomarkers or potential therapeutic targets for GC. Nonetheless, these results were obtained by bioinformatics analysis and require further clinical validation.