Development and Validation of a Robust Immune-Related Prognostic Signature for Gastric Cancer

Background: An increasing number of reports have found that immune-related genes (IRGs) have a significant impact on the prognosis of a variety of cancers, but the prognostic value of IRGs in gastric cancer (GC) has not been fully elucidated.

Methods: Univariate Cox regression analysis was adopted for the identification of prognostic IRGs in three independent cohorts (GSE62254, = 300; GSE15459, = 191; and GSE26901, = 109). After obtaining the intersecting prognostic genes, the three independent cohorts were merged into a training cohort ( = 600) to establish a prognostic model. The risk score was determined using multivariate Cox and LASSO regression analyses. Patients were classified into low-risk and high-risk groups according to the median risk score. The risk score performance was validated externally in the three independent cohorts (GSE26253, = 432; GSE84437, = 431; and TCGA, = 336). Immune cell infiltration (ICI) was quantified by the CIBERSORT method.

Results: A risk score comprising nine genes showed high accuracy for the prediction of the overall survival (OS) of patients with GC in the training cohort (AUC > 0.7). The risk of death was found to have a positive correlation with the risk score. The univariate and multivariate Cox regression analyses revealed that the risk score was an independent indicator of the prognosis of patients with GC ( < 0.001). External validation confirmed the universal applicability of the risk score. The low-risk group presented a lower infiltration level of M2 macrophages than the high-risk group ( < 0.001), and the prognosis of patients with GC with a higher infiltration level of M2 macrophages was poor ( = 0.011). According to clinical correlation analysis, compared with patients with the diffuse and mixed type of GC, those with the Lauren classification intestinal GC type had a significantly lower risk score ( = 0.00085). The patients' risk score increased with the progression of the clinicopathological stage.

Conclusion: In this study, we constructed and validated a robust prognostic signature for GC, which may help improve the prognostic assessment system and treatment strategy for GC.