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Rethinking biomarker strategy in gastric cancer immunotherapy: from tumor to host
Nabil Ismaili1,2,3
1Department of Medical Oncology, Mohammed VI Faculty of Medicine, Mohammed VI University of Sciences and Health (UM6SS), Casablanca, Morocco.
Immune checkpoint inhibitors (ICIs) have transformed advanced gastric cancer (GC) treatment, but durable responses remain rare, highlighting the need for better patient selection. Recent studies suggest that host-derived autoantibodies (e.g., ANA, ENA) may serve as prognostic markers in GC patients receiving immunotherapy. These hypothesis-generating observations indicate that pre-existing humoral immunity could reflect a clinically relevant axis of immune fitness. This review critically appraises these findings alongside established and emerging predictive biomarkers. We examine the strengths and limitations of PD-L1, MSI, TMB, and EBV status, and explore the clinical potential of dynamic tools like ctDNA and computational models. We also discuss emerging evidence on intrinsic resistance to PD-1 blockade in MSI-H GC, including PTEN mutations, low TMB within MSI-H tumors, and antigen presentation defects. Murine models have provided key insights into these resistance mechanisms and the immunomodulatory role of the gut microbiome. Collectively, the data support a shift from single-analyte biomarkers toward integrative, dynamic, systems-level models for patient selection, heralding a new era of precision immune-oncology in GC. However, most emerging biomarkers remain investigational and require prospective validation.
Immune checkpoint inhibitors (ICIs) have transformed advanced gastric cancer (GC) treatment, but durable responses remain rare, highlighting the need for better patient selection. Recent studies suggest that host-derived autoantibodies (e.g., ANA, ENA) may serve as prognostic markers in GC patients receiving immunotherapy. These hypothesis-generating observations indicate that pre-existing humoral immunity could reflect a clinically relevant axis of immune fitness. This review critically appraises these findings alongside established and emerging predictive biomarkers. We examine the strengths and limitations of PD-L1, MSI, TMB, and EBV status, and explore the clinical potential of dynamic tools like ctDNA and computational models. We also discuss emerging evidence on intrinsic resistance to PD-1 blockade in MSI-H GC, including PTEN mutations, low TMB within MSI-H tumors, and antigen presentation defects. Murine models have provided key insights into these resistance mechanisms and the immunomodulatory role of the gut microbiome. Collectively, the data support a shift from single-analyte biomarkers toward integrative, dynamic, systems-level models for patient selection, heralding a new era of precision immune-oncology in GC. However, most emerging biomarkers remain investigational and require prospective validation.
