An Overview of Predictive Biomarkers and Detection Approaches for Immunotherapy Response in GI Malignancies
Xinyu Chai, Yiwen Zhang, Zhihui Shi, Ruiling Yang, Xumin Liu, Yueting Zhou, Caiyang Li, Zhenhui Li
Abstract
This review provides an in-depth exploration of the evolving role of immunotherapy in gastrointestinal (GI) cancers, with a particular focus on immune checkpoint inhibitors (ICIs) and their associated predictive biomarkers. We present a detailed analysis of established biomarkers, such as PD-L1, microsatellite instability (MSI), tumor mutational burden (TMB), and the tumor microenvironment (TME), as well as emerging biomarkers, including gut microbiota and Epstein-Barr virus (EBV). The predictive value of these biomarkers in guiding clinical decision-making and optimizing immunotherapy outcomes is thoroughly discussed. Additionally, we highlight recent advancements in biomarker evaluation technologies, including next-generation sequencing (NGS), multiplex immunohistochemistry, and artificial intelligence (AI)-driven models. These technologies are instrumental in advancing precision medicine by enhancing the accuracy and efficiency of biomarker detection and facilitating personalized treatment approaches. The integration of these predictive biomarkers with advanced detection technologies has significantly improved the clinical efficacy of immunotherapy in GI cancers by addressing challenges such as tumor heterogeneity, immune evasion, and variable patient responses. By providing a deeper understanding of tumor biology and patient-specific factors, these tools offer the potential to optimize patient selection, treatment regimens, and, ultimately, clinical outcomes. This review underscores the transformative impact of combining predictive biomarkers with cutting-edge technologies, marking a significant step forward in the field of precision oncology for GI cancer treatment.