Abstract
Gastric cancer (GC) is a serious malignant disorder with a mortality rate of approximately 10%. It is therefore necessary to identify prognostic biomarkers and drug targets to improve the clinical outcome of patients with GC. The present research aims to distinguish the key genes and the relevant pathways using a microarray gene expression dataset that facilitates the understanding of molecular mechanisms. The identified genes may be used as the therapeutic biomarker of GC. Seven important pathways, like, ECM-receptor interaction, Gastric acid secretion, PI3K-Akt signaling pathway, Focal adhesion, Amoebiasis, Gastric acid secretion, and Collecting duct acid secretion, linked with gastric cancer are identified. The 11 genes associated with these pathways are considered as the potential targets for gastric cancer drug discovery. Finally, survival analysis based on the expression of these genes generates 7 key genes (COL1A1, COL1A2, THBS2, FN1, SPP1, ATP4A, and ATP4B) having poor overall survival. We have also constructed a protein-protein interaction (PPI) network of the differentially expressed genes (DEGs) using STRING and 57 hub genes are identified using Cytoscape. Survival analysis of these hub genes yields 16 genes that are highly correlated with the poor survival of GC patients. The current study would help understand the disease mechanisms and accelerate its diagnosis.
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