Immune biomarkers and predictive signatures in gastric cancer: Optimizing immunotherapy responses

Gastric cancer is a malignant disease with a poor prognosis and few therapeutic options once it has advanced. Immunotherapy using ICIs has emerged as a viable therapeutic method; nevertheless, reliable immunological biomarkers are required to identify who may benefit from these therapies. It focuses on key immune biomarkers and predictive signatures in gastric cancer, such as PD-L1 expression, microsatellite instability (MSI), tumor mutational burden (TMB), and Epstein-Barr virus (EBV) status, to optimize gastric cancer patients' immunotherapy responses. PD-L1 expression is a popular biomarker for ICI effectiveness. Tumors with high MSI-H and TMB are the most susceptible to ICIs because they are highly immunogenic. EBV-positive stomach tumors are highly immunogenic, and immunotherapy has a high response rate. Combining composite biomarker panels with multi-omics-based techniques improved patient selection accuracy. In recent years, machine learning models have been integrated into next-generation sequencing. Dynamic, real-time-monitorable biomarkers for real-time immune response monitoring are also being considered. Thus, enhancing biomarker-driven immunotherapy is critical for improving clinical outcomes with gastric cancer. There is still more work to be done in this field, and verifying developing biomarkers will be an important component in the future of customized cancer therapy.