BMC Gastroenterology · 2023 · 23 citations · 50 references
Life SciencesMolecular BiologySystems BiologyCancer Systems BiologyMolecular OncologyNetwork BiologyCancer Cell SignalingCancer GenomicsCancer MetabolismDisease Network BiologyMetabolic Pathway AnalysisMolecular Interaction NetworksCancer BioinformaticsCancer Pathway ModelingCancer Signaling PathwaysEnrichment AnalysisGene Network AnalysisGene Network ModelingProtein-protein Interaction Network AnalysisSignal Transduction Network Modeling
BACKGROUND: Gastric cancer (GC) ranks among the most common malignancies worldwide. This study aimed to find critical genes/pathways in GC pathogenesis. METHODS: Gene interactions were analyzed, and the protein-protein interaction network was drawn. Then enrichment analysis of the hub genes was performed and network cluster analysis and promoter analysis of the hub genes were done. Age/sex analysis was done on the identified genes. RESULTS: Eleven hub genes in GC were identified in the current study (ATP5A1, ATP5B, ATP5D, MT-ATP8, COX7A2, COX6C, ND4, ND6, NDUFS3, RPL8, and RPS16), mostly involved in mitochondrial functions. There was no report on the ATP5D, ND6, NDUFS3, RPL8, and RPS16 in GC. Our results showed that the most affected processes in GC are the metabolic processes, and the oxidative phosphorylation pathway was considerably enriched which showed the significance of mitochondria in GC pathogenesis. Most of the affected pathways in GC were also involved in neurodegenerative diseases. Promoter analysis showed that negative regulation of signal transduction might play an important role in GC pathogenesis. In the analysis of the basal expression pattern of the selected genes whose basal expression presented a change during the age, we found that a change in age may be an indicator of changes in disease insurgence and/or progression at different ages. CONCLUSIONS: These results might open up new insights into GC pathogenesis. The identified genes might be novel diagnostic/prognostic biomarkers or potential therapeutic targets for GC. This work, being based on bioinformatics analysis act as a hypothesis generator that requires further clinical validation.
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KEGG: Kyoto Encyclopedia of Genes and Genomes
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