Genome-scale analysis identifies SERPINE1 and SPARC as diagnostic and prognostic biomarkers in gastric cancer

Background: Gastric cancer (GC) is one of the most common types of malignancy and is associated with high morbidity and mortality rates around the world. With poor clinical outcomes, potential biomarkers for diagnosis and prognosis are important to investigate. Objective: The aim of this study is to investigate the gene expression module of GC and to identify potential diagnostic and prognostic biomarkers. Method: Microarray data (GSE13911, GSE29272, GSE54129, and GSE79973), including 293 stomach tumor tissues and 196 normal tissues, were analyzed to identify differentially expressed genes (DEGs). DEGs were identified in four profiles by intersecting four overlapping subsets, including 90 downregulated and 45 upregulated DEGs in common. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway analyses have been showed that extracellular matrix was the most enriched signal pathway. Furthermore, hub genes were analyzed by protein-protein interaction network and clinical outcomes were assessed by Kaplan-Meier survival analysis. Two independent datasets were used to validate the differential expression of two hub genes: Serpin Family E Member 1 (SERPINE1) and Secreted Protein Acidic and Cysteine Rich (SPARC). Results: Validation of independent datasets indicated that SERPINE1 and SPARC expression were drastically increased in gastric tumor tissues and associated with poor outcomes in GC patients. The expression of SERPINE1 was related to race (Asian and White) (P < 0.05). Conclusion: SERPINE1 and SPARC were significantly upregulated in gastric tissues and associated with poor outcomes. The investigations of SERPINE1 and SPARC may promote their predictive and prognostic value in GC.