Comprehensive Analysis Based on the Cancer Immunotherapy and Immune Activation of Gastric Cancer Patients.

Abstract

When it comes to aggressiveness and prognosis, immune cells play an important role in the microenvironment of gastric cancer (GC). Currently, there is no well-established evidence that immune status typing is reliable as a prognostic tool for gastric cancer. This study aimed to develop a genetic signature based on immune status typing for the stratification of gastric cancer risk. TCGA data were used for gene expression and clinical characteristics analysis. A ssGSEA algorithm was applied to type the gastric cancer cohorts. A multivariate and univariate Cox regression and a lasso regression were conducted to determine which genes are associated with gastric cancer prognosis. Finally, we were able to produce a 6-gene prognostic prediction model using immune-related genes. Further analysis revealed that the prognostic prediction model is closely related to the prognosis of patients with GC. Nomograms incorporating genetic signatures and risk factors produced better calibration results. The relationship between the risk score and gastric cancer T stage was also significantly correlated with multiple immune markers related to specific immune cell subsets. According to these results, patients' outcomes and tumor immune cell infiltration correlate with risk scores. In addition, immune cellular-based genetic signatures can contribute to improved risk stratification for gastric cancer. Clinical decisions regarding immunotherapy and followup can be guided by these features.