finding new biomarkers and therapeutic targets for gastric cancer using a system biology approach

Background: gastric cancer is one of the leading causes of cancer-related mortality worldwide, withapproximately one million new cases diagnosed annually. identifying key genes involved in this cancer iscrucial for proposing suitable therapeutic targets and facilitating early diagnosis. this study aims to analyzethe transcriptomic profile of gastric cancer cells to identify these critical genes.methods: gene expression profiles from six gastric cancer datasets (gse13911, gse79973, gse103236,gse116312, gse118916, and gse161533) were analyzed. differentially expressed genes were identified, andtheir protein-protein interaction networks were investigated using graph-based analysis.results: transcriptome analysis of gastric cancer versus normal tissues identified 516 significantly differentiallyexpressed genes. among these, three genes, atp4a, spp1, and gkn1, were prioritized as potential biomarkersbased on their significant expression changes (log2 fold change of 6.76, 3.5, and 6.88, respectively ; p-value=0.01)and central roles in the protein-protein interaction network, with node degrees of 17, 22, and 11.conclusion: the combination of spp1, atp4a, and gkn1 provides a powerful and minimally invasive tool fordiagnosing gastric cancer. this multi-marker approach utilizes the gastric specificity of atp4a and gkn1 forearly detection, alongside the malignant indicator spp1, to effectively distinguish gastric cancer from benignconditions, thereby reducing false positives.