Noninvasive imaging-based assessment of tumor-associated neutrophils for prognosis and immunotherapy response in gastric cancer: a multicenter study.

[INTRODUCTION] Tumor-associated neutrophils (TAN) critically promote gastric cancer progression. However, current assessment relies on invasive biopsies that preclude serial monitoring. Noninvasive tools to quantify TAN infiltration are urgently required.

[OBJECTIVES] To develop and validate a noninvasive, CT-based ensemble machine learning radiomic biomarker for mapping TAN infiltration in gastric cancer, and to assess its utility for prognosis stratification and the prediction of response to anti-PD-1 immunotherapy.

[METHODS] In this multicenter study of 2,170 gastric cancer patients across eight cohorts, we developed EnmlbaRB, an ensemble machine-learning-based CT radiomic biomarker. Portal venous-phase scans were processed to extract features, with mRMR-Boruta algorithms identifying 11 radiomic signatures (six peritumoral and five intratumoral signatures). These were integrated via a five-tier heterogeneous stacking architecture supervised by the immunohistochemistry-derived CD66b + TAN status (High/Mix/Low). The validation spanned six independent cohorts, including 177 anti-PD-1-treated patients.

[RESULTS] External validation demonstrated robust performance: EnmlbaRB predicted TAN status with an AUC of 0.71 (95%CI: 0.65-0.78) and 80.74% specificity. Critically, TAN-Low patients exhibited significantly superior 5-year overall survival compared to TAN-High across all cohorts (e.g., SYSUCC cohort: 64.12% vs. 46.78%, p < 0.05). In the anti-PD-1 cohorts, the TAN-Low subgroups achieved 1.9-fold higher disease control rates (83.9% vs 44.1%; p < 0.001) and significantly prolonged median progression-free survival (>41.9 vs 6.2 months; HR = 0.162, p < 0.001), establishing clear clinical utility for immunotherapy stratification.

[CONCLUSIONS] This study is the first clinically validated noninvasive solution for mapping the TAN infiltration status in gastric cancer. EnmlbaRB effectively stratified the patients based on survival outcomes and immunotherapy responsiveness. This paradigm empowers clinicians to personalize therapeutic sequencing based on evolving TAN biology, thereby addressing the critical need for adaptive treatment strategies for advanced gastric cancer management.