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

**Authors:** Hyunho Kim, Kabsoo Shin, Se Jun Park, Myung Ah Lee, Juyeon Park, Okran Kim, Nahyeon Kang, In-Ho Kim

PMC · DOI: 10.3390/cancers17193131 · 2025-09-26

## 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.

## Key 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.

## Linked entities

- **Proteins:** CXCL10 (C-X-C motif chemokine ligand 10), Mki67 (antigen identified by monoclonal antibody Ki 67), IFNG (interferon gamma), TGFB1 (transforming growth factor beta 1), PDCD1 (programmed cell death 1), LAG3 (lymphocyte activating 3), HAVCR2 (hepatitis A virus cellular receptor 2), CD8A (CD8 subunit alpha), CD69 (CD69 molecule), Mki67 (antigen identified by monoclonal antibody Ki 67)
- **Diseases:** gastric cancer (MONDO:0001056)

## Full-text entities

- **Genes:** GZMB (granzyme B) [NCBI Gene 3002] {aka C11, CCPI, CGL-1, CGL1, CSP-B, CSPB}, HAVCR2 (hepatitis A virus cellular receptor 2) [NCBI Gene 84868] {aka CD366, HAVcr-2, KIM-3, SPTCL, TIM3, TIMD-3}, CXCL10 (C-X-C motif chemokine ligand 10) [NCBI Gene 3627] {aka C7, IFI10, INP10, IP-10, SCYB10, crg-2}, LAG3 (lymphocyte activating 3) [NCBI Gene 3902] {aka CD223}, CD8A (CD8 subunit alpha) [NCBI Gene 925] {aka CD8, CD8alpha, IMD116, Leu2, p32}, IFNG (interferon gamma) [NCBI Gene 3458] {aka IFG, IFI, IMD69}, CD69 (CD69 molecule) [NCBI Gene 969] {aka AIM, BL-AC/P26, CLEC2C, EA1, GP32/28, MLR-3}, TGFB1 (transforming growth factor beta 1) [NCBI Gene 7040] {aka CAEND1, CED, DPD1, IBDIMDE, LAP, TGF-beta1}
- **Diseases:** GC (MESH:D013274)
- **Chemicals:** FOLFOX (MESH:C410216), XELOX (MESH:C519688), Nivolumab (MESH:D000077594)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Figures

8 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12523374/full.md

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Source: https://tomesphere.com/paper/PMC12523374