Integrative bioinformatic characterization of driver genes and prognostic features in human gastric carcinoma

Abstract Background: Gastric cancer (GC) is the second most common cause of cancer death worldwide but could be more curable if diagnosed at an earlier stage. At present, the capability to predict the efficaciousness of molecular diagnosis for GC for each patient remains elusive. The purpose of this study was to identify tumor biomarkers through systems analysis of multigene predictors exploiting the available data resource. Results: Our study showed that 61 shared DEGs were significantly involved in functions such as gastric acid secretion. COL1A1, MMP9, and SPP1 were highly connected nodes in the PPI network. Among the 61 common DEGs, 34 driver genes were identified, including CST1 and MMP9. A total of 34 drug-gene interactions were found, which involved 9 common DEGs. Moreover, CTHRC1 and INHBA were related to clinical outcome in gastric cancer patients. Conclusion: The identification of new driver genes, such as MMP9, CTHRC1, and INHBA, may contribute to the understanding of the etiology of gastric cancer and the development of individualized therapies.