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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 (ISS
GC
) 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 ISS
GC
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, ISS
GC
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.
Expression patterns of immune checkpoints in patients with gastric cancer remain poorly characterized. Here the authors propose an immune scoring system based on the expression of six immunosuppressive ligands to improve the prognostic accuracy in gastric cancer patients and drive the selection of candidates for adjuvant chemotherapy.