Immunosuppressive molecules are extremely valuable prognostic biomarkers across different cancer types. However, the diversity of different immunosuppressive molecules makes it very difficult to accurately predict clinical outcomes based only on a single immunosuppressive molecule. Here, we establish a comprehensive immune scoring system (ISSGC) based on 6 immunosuppressive ligands (NECTIN2, CEACAM1, HMGB1, SIGLEC6, CD44, and CD155) using the LASSO method to improve prognostic accuracy and provide an additional selection strategy for adjuvant chemotherapy of gastric cancer (GC). The results show that ISSGC is an independent prognostic factor and a supplement of TNM stage for GC patients, and it can improve their prognosis prediction accuracy; in addition, it can distinguish GC patients with better prognosis from those with high prognostic nutritional index score; furthermore, ISSGC can also be used as a tool to select GC patients who would benefit from adjuvant chemotherapy independent of their TNM stages, MSI status and EBV status.