Dynamic Integrative Immune Profiling Reveals Early Biomarkers of Response and Prognosis in Advanced Gastric Cancer Treated with Nivolumab Plus Chemotherapy

TL;DR

This study identifies early blood-based immune markers that predict response and survival in advanced gastric cancer patients treated with nivolumab and chemotherapy.

Contribution

The study introduces dynamic immune profiling to detect early biomarkers for treatment response and prognosis in gastric cancer immunotherapy.

Findings

Early increases in plasma Granzyme B and CXCL10 correlate with better treatment outcomes.

Changes in CD8+ T-cell subsets and immune checkpoint markers predict progression-free survival.

Serial immune monitoring can guide personalized treatment strategies in gastric cancer.

Abstract

Advanced gastric cancer has limited treatment options and poor prognosis. Nivolumab plus chemotherapy offers clinical benefit, but predictive biomarkers remain unclear. We analyzed blood samples from patients before and after treatment to assess immune activation markers, including cytotoxic molecules and CD8+ T cell subsets. Early increases in plasma Granzyme B and CXCL10, and specific activated CD8+ T cells, were associated with better outcomes. Some immune cell subsets showed marked declines after chemotherapy, indicating both stimulatory and suppressive immune effects. These findings may help identify patients most likely to benefit from immunotherapy, supporting personalized treatment strategies in advanced gastric cancer.

Background: Nivolumab plus chemotherapy is a standard first-line treatment for advanced gastric cancer (GC), but reliable early biomarkers for predicting treatment outcomes remain lacking. This study aimed to identify early immunological predictors through dynamic immune profiling. Methods: Fifty patients with advanced or unresectable GC receiving nivolumab plus XELOX or FOLFOX were enrolled. Peripheral blood was collected at baseline, week 1, and week 6. Plasma biomarkers (Granzyme B, Ki-67, CXCL10, IFN-γ, TGF-β1) were measured by ELISA, and immune cell subsets, including cytotoxic T cells, immune checkpoint–positive populations, and memory T-cell subsets, were analyzed by flow cytometry. Cutoffs were defined by medians, established thresholds for NLR and lymphocyte count, and criteria for long-term response (≥9.5 months). Associations with response and progression-free survival (PFS) were evaluated using Kaplan–Meier analysis, Cox regression, and ROC curves. Results: Early responders exhibited significant increases in Granzyme B and CXCL10, with ΔGranzyme B alone and in combination with ΔKi-67 predicting response with high accuracy. A lower week 1 neutrophil-to-lymphocyte ratio was associated with long-term benefit. Elevated week 1 CD8+ T-cell proportion and greater decreases in PD1+CD69+Ki-67+CD8+ T cells were linked to improved PFS. Higher baseline PD1+LAG-3+Ki-67+CD8+ T-cell levels and combined TIM-3+/LAG-3+ expression enhanced prognostic stratification. Additionally, elevated baseline activated TEMRA cells and declines at week 6 in the same subset correlated with better outcomes. Conclusions: These findings highlight the clinical utility of serial immune monitoring to enable early treatment stratification and guide personalized immunotherapy strategies in advanced GC.

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