Identification of core genes and clinical outcomes in tumors originated from endoderm (gastric cancer and lung carcinoma) via bioinformatics analysis

Abstract

During last decade, bioinformatics analysis has provided an effective way to study the relationship between various genes and biological processes. In this study, we aimed to identify potential core candidate genes and underlying mechanisms of progression of lung and gastric carcinomas which both originated from endoderm. The expression profiles, GSE54129 (gastric carcinoma) and GSE27262 (lung carcinoma), were collected from GEO database. One hundred eleven patients with gastric carcinoma and 21 health people were included in this research. Meanwhile, there were 25 lung carcinoma patients. Then, 75 differentially expressed genes were selected via GEO2R online tool and Venn software, including 31 up-regulated genes and 44 down-regulated genes. Next, we used Database for Annotation, Visualization, and Integrated Discovery and Metascpe software to analyze Kyoto Encyclopedia of Gene and Genome pathway and gene ontology. Furthermore, Cytoscape software and MCODE App were performed to construct complex of these differentially expressed genes . Twenty core genes were identified, which mainly enriched in extracellular matrix-receptor interaction, focal adhesion, and PI3K-Akt pathway (P < .01). Finally, the significant difference of gene expression between cancer tissues and normal tissues in both lung and gastric carcinomas was examined by Gene Expression Profiling Interactive Analysis database. Twelve candidate genes with positive statistical significance (P < .01), COMP CTHRC1 COL1A1 SPP1 COL11A1 COL10A1 CXCL13 CLDN3 CLDN1 matrix metalloproteinases 7 ADAM12 PLAU, were picked out to further analysis. The Kaplan-Meier plotter website was applied to examine relationship among these genes and clinical outcomes. We found 4 genes (ADAM12, SPP1, COL1A1, COL11A1) were significantly associated with poor prognosis in both lung and gastric carcinoma patients (P < .05). In conclusion, these candidate genes may be potential therapeutic targets for cancer treatment.