Advancing human epidermal growth factor receptor 2-positive gastric cancer therapy: Toward targeted immunotherapy and antibody-drug conjugates

Figure 1 A dynamic, biomarker-informed decision model for overcoming resistance in human epidermal growth factor receptor 2-positive gastric cancer. This flowchart outlines a proposed dynamic decision-model for overcoming therapy resistance. The model shifts the paradigm from a reactive, standardized sequence to a proactive, adaptive process of precision medicine. It operates through three core, iterative steps: (1) Initial multi-omics stratification: A comprehensive molecular profile at diagnosis (e.g., via next-generation sequencing) identifies high-risk features (e.g., PIK3CA mutations, PTEN loss) to guide first-line therapy intensity; (2) Longitudinal liquid biopsy surveillance: Periodic circulating tumor DNA analysis enables the early detection of emerging resistant clones and their mechanisms, often prior to radiographic progression; and (3) Mechanism-directed therapeutic rechallenge: Upon resistance detection, therapy is adaptively switched to a matched, mechanism-specific regimen (e.g., a tyrosine kinase inhibitor for an acquired human epidermal growth factor receptor 2 mutation), bypassing empirical chemotherapy. The model emphasizes continuous adaptation and highly individualized treatment. HER2: Human epidermal growth factor receptor 2; PI3K: Phosphatidylinositol 3-kinase; AKT: Protein kinase B; mTOR: Mammalian target of rapamycin; MET: Mesenchymal-epithelial transition factor; ER: Estrogen receptor; FGFR: Fibroblast growth factor receptor; EMT: Epithelial-mesenchymal transition; CDK: Cyclin-dependent kinase; CAV-1: Caveolin-1; ECM: Extracellular matrix; CD: Cluster of differentiation; TIL: Tumor-infiltrating lymphocyte; CTL: Cytotoxic T lymphocyte; TCR: T cell receptor; MHC: Major histocompatibility complex; PD-1: Programmed cell death 1; PD-L1: Programmed cell death ligand 1; PH: Potential of hydrogen.