Identification of TAP1 as a T-cell related therapeutic target in gastric cancer by mediating oxalipliatin-related synergistic enhancement of immunotherapy.

Background: Given the intricate molecular complexities and heterogeneity inherent in T-cell immunotherapy of gastric cancer (GC), elucidative T-cell-related biomarkers were imperative needed for facilitating the prediction of GC patient prognosis and identify potential synergistic therapeutic targets.

Methods: We conducted COX regression analysis in TISIDB, TCGA-STAD, and GEO databases to identify 19 GC T-cell-mediated sensitivity tumor killing (TTK) genes (key GCTTKs). Based on key GCTTKs, we constructed two TTK patterns and analyzed their metabolic pathways, mutation features, clinical data distribution, immune cell infiltration, and prognosis. LASSO regression was performed to develop a T-cell-mediated GC Prognosis (TGCP) model. We validated the TGCP model in GC patients. TAP1 was further selected for investigation of its biological functions and molecular mechanisms. We assessed the potential of TAP1 as a promising therapeutic target for GC using Patient-derived organoids (PDOs)-derived xenografts (PDOXs) models of GC.

Results: The TTK patterns display notable disparities. The TGCP model showcases its proficiency in predicting immune response efficacy, effectively distinguishes immunotherapy difference GC patients. Our findings find further confirmation in PDOX models, affirming TAP1 can enhance immunotherapy facilitated by PDL1 inhibitors. Furthermore, Oxaliplatin, by promoting TAP1 expression, augments PDL1 expression, thereby enhancing the efficacy of immunotherapy.

Conclusions: We constructed a TGCP model, which demonstrates satisfactory predictive accuracy. Out of 9 prognostic genes, TAP1 was validated as a synergistic target for Oxaliplatin and PDL1 inhibitors, offering a genetic-level explanation for the synergy observed in GC treatment involving Oxaliplatin in combination with PDL1 inhibitors.