CELL INTELLIGENCE · 肿瘤细胞治疗研究

Gastric cancer (GC) remains a major global health burden with unsatisfactory overall prognosis, largely attributed to profound heterogeneity, late-stage diagnosis, and therapeutic resistance. Over the past decade, immune checkpoint inhibitors (ICIs) targeting programmed cell death protein 1 (PD-1)/programmed death-ligand 1 (PD-L1) and cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) have reshaped treatment paradigms, yet durable responses remain limited to a subset of patients, underscoring the need for deeper mechanistic understanding and refined therapeutic strategies. In 2025, transformative advances in translational research have reshaped the landscape of GC immuno-oncology, moving toward mechanism-driven precision medicine. This review synthesizes key breakthroughs across interconnected domains, including multidimensional predictive biomarker systems, emerging immunoregulatory targets beyond classical checkpoints, advanced immunotherapeutic technologies such as adoptive cell transfer (ACT) and cancer vaccines, and the intertwined networks of tumor microenvironment (TME) remodeling and metabolic reprogramming. Notably, advances in understanding myeloid cell subset heterogeneity [e.g., myelocyte and metamyelocyte-stage (MC&MM-stage) neutrophils] and the development of major histocompatibility complex class II (MHC-II)-restricted neoantigen vaccines have further deepened mechanistic insights and expanded the therapeutic toolkit. These collective progressions have established a cohesive "mechanism-biomarker-therapy" loop, laying the foundation for personalized combination strategies. Despite significant advances, challenges persist-including tumor heterogeneity, immunosuppressive TME, and the need to balance therapeutic efficacy with toxicity. Future directions should leverage multi-omics and artificial intelligence to optimize personalized combination therapies, advance precise perioperative interventions for early-stage GC, and implement dynamic treatment adjustments, ultimately improving therapeutic efficacy and patient outcomes.