Establishment of a prognostic model of four genes in gastric cancer based on multiple data sets.

Gastric cancer (GC) is a kind of malignancy with a high mortality and recurrence. An effective prediction model based on ideal biomarkers to assess prognosis could benefit patients for optimization of treatment. Bioinformatics has played an increasingly important role in the study of cancer diseases. Therefore, this study started with bioinformatics to establish a reliable prognostic model of gastric cancer. The gene expression data and clinical data of GC tissues and normal tissues were obtained from the Gene Expression Omnibus (GEO), Genotype-Tissue Expression (GTEx), and The Cancer Genome Atlas (TCGA) profile database. We finally identified a four gene signature and constructed a prognostic model. The results of internal and external validation showed that the model is highly reliable. In addition, we also constructed a nomogram based on the model, which was verified by a calibration curve to show its predicted accuracy. Comprehensive analysis indicated that the four genes in the model are related to the occurrence and development of tumors, perhaps they are potential targets for tumor treatment. Generally, this prognostic model can bring potential benefits to patients with gastric cancer.