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Neutrophil Extracellular Traps Predict Prognosis and Neoadjuvant Immunotherapy Response in Gastric Cancer.

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Journal of inflammation research 2026 Vol.19() p. 564892
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PICO 자동 추출 (휴리스틱, conf 2/4)

유사 논문
P · Population 대상 환자/모집단
49 patients receiving neoadjuvant chemotherapy combined with immunotherapy were collected.
I · Intervention 중재 / 시술
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C · Comparison 대조 / 비교
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O · Outcome 결과 / 결론
[CONCLUSION] Low NET density is linked to better prognosis and may identify patients with GC who could benefit from immunotherapy. These findings highlight the important role of NET in GC.

Zhong W, Wang Q, Sun L, Zhu H, Cai H, Dong J, Chen G, Liu A, Du J

📝 환자 설명용 한 줄

[PURPOSE] To determine whether neutrophil extracellular trap (NET) predicts prognosis and response to neoadjuvant immunotherapy in gastric cancer (GC) and explore the associated mechanisms.

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BibTeX ↓ RIS ↓
APA Zhong W, Wang Q, et al. (2026). Neutrophil Extracellular Traps Predict Prognosis and Neoadjuvant Immunotherapy Response in Gastric Cancer.. Journal of inflammation research, 19, 564892. https://doi.org/10.2147/JIR.S564892
MLA Zhong W, et al.. "Neutrophil Extracellular Traps Predict Prognosis and Neoadjuvant Immunotherapy Response in Gastric Cancer.." Journal of inflammation research, vol. 19, 2026, pp. 564892.
PMID 41847426
DOI 10.2147/JIR.S564892

Abstract

[PURPOSE] To determine whether neutrophil extracellular trap (NET) predicts prognosis and response to neoadjuvant immunotherapy in gastric cancer (GC) and explore the associated mechanisms.

[PATIENTS AND METHODS] Transcriptomic data from a GEO dataset (GSE62254) comprising 300 GC patients were analyzed. Patients were clustered based on 69 predefined NET-related genes (NRGs) summarized in previous studies, and clinical characteristics and immune cell infiltration between clusters were compared. An NRG signature was constructed. Retrospective clinical data and tissue samples from 243 surgically resected GC patients without neoadjuvant therapy and 49 patients receiving neoadjuvant chemotherapy combined with immunotherapy were collected. RNA sequencing, immunohistochemistry, and immunofluorescence were performed to assess NET density and its clinical relevance.

[RESULTS] Two NET-related subtypes in GC (NT1 and NT2) with distinct clinical features and survival time were identified. A risk model based on five NRGs demonstrated that NT2 had lower risk scores, correlating with favorable outcomes. High NET density was associated with advanced TNM stage and short recurrence-free survival time in the surgery cohort. In the immunotherapy cohort, low pre-treatment NET density correlated with more T cells predicted superior response rates (45.8% vs. 16.0%,  = 0.032) and pathological complete response (29.2% vs. 4.0%,  = 0.023).

[CONCLUSION] Low NET density is linked to better prognosis and may identify patients with GC who could benefit from immunotherapy. These findings highlight the important role of NET in GC.

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