An Immunosuppressive Status Classifier to Predict Recurrence and Assist in Decision Regarding Postoperative Adjuvant Treatment in Gastric Cancer

Abstract

Background: Suppression of the immune microenvironment is a crucial cause of postoperative tumor recurrence. We constructed an immune in ltration classi er based on immunosuppressive indicators to predict recurrence and guide postoperative treatment for gastric cancer (GC). Methods: Immunohistochemical analysis was performed for 825 GC tissues to evaluate immunosuppressive indicators. An immunosuppressive recurrence score (IRS) based on six immunosuppressive indicators was determined using the Lasso Cox method to predict recurrence outcomes. The association between immune in ltration and IRS was assessed using immunohistochemistry and multiplexed immuno uorescence staining. A nomogram predicting recurrence-free survival (RFS) was constructed by integrating IRS and signi cant clinicopathological features using the Cox regression model.Results: The IRS and IRS-based nomogram showed remarkable accuracy and reliability for predicting the recurrence outcome. Moreover, elevated IRS was associated with locoregional recurrence and failure of postoperative adjuvant chemotherapy. We also identi ed that the increased IRS indicated the inhibition of anti-tumor effect of CD8 + tumor-in ltrating lymphocytes (TILs) in the invasive margin (IM). Conclusion: IRS can predict the recurrence outcome of GC patients by comprehensively distinguishing the