Biomarker-Oriented Contextual Analysis of First-Line Zolbetuximab and Immunotherapy-Based Strategies in HER2-Negative...

Purpose In HER2-negative metastatic gastric cancer, immune checkpoint inhibitors (ICIs) and CLDN18.2-targeted antibody zolbetuximab, combined with chemotherapy (CT), have emerged as first line options. Treatment selection is relatively straightforward in microsatellite instability-high (MSI-H), PD-L1 combined positive score (CPS)-high/negative disease, but uncertainty persists in overlapping biomarkers-particularly CLDN18.2-positive tumors with low-to-intermediate PD-L1 CPS-where direct comparative evidence is lacking. Methods Individual patient data were reconstructed from published Kaplan-Meier curves of pivotal phase III trials (SPOTLIGHT/GLOW, CheckMate-649, KEYNOTE-859). Descriptive, unadjusted indirect comparisons of progression-free survival (PFS) and overall survival (OS) were performed using pooled CT as common reference. Findings were interpreted within a biomarker-oriented framework incorporating PD-L1 CPS, CLDN18.2 expression, MSI status and treatment mechanisms. Results PFS benefit versus pooled CT was marked with zolbetuximab plus CT (hazard ratio [HR] 0.60, 95% confidence interval [CI] 0.53-0.68), but more modest with pooled ICI-based regimens (HR 0.81, 95% CI 0.75-0.88). Both strategies improved OS. CLDN18.2-positive tumors are predominantly PD-L1 CPS-low, a biological context where ICI benefit may be heterogeneous. Conversely, zolbetuximab demonstrated consistent efficacy in this selected population; leveraging its established mechanism of direct CLDN18.2-targeting and innate immune activation, it provides a biomarker-directed therapeutic option that addresses the clinical gap in PD-L1 CPS-low disease. Conclusions Population-level efficacy estimates should not be interpreted as therapeutic interchangeability between ICIs and CLDN18.2-targeted therapy. Without direct comparative data, treatment selection in CLDN18.2-positive, PD-L1 CPS-low disease requires integration of biomarker biology and clinical context. This biomarker-informed framework supports clinical decision-making under uncertainty.