4.7 Article

A risk signature with inflammatory and immune cells infiltration predicts survival and efficiency of chemotherapy in gastric cancer

Journal

INTERNATIONAL IMMUNOPHARMACOLOGY
Volume 96, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.intimp.2021.107589

Keywords

Risk signature; Neutrophil; Lymphocyte; Survival; Chemotherapy; Gastric cancer

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By integrating neutrophils into T lymphocytes, more accurate prognostic information can be provided in gastric cancer, guiding clinical treatment strategies.
Objective: Tumor immune microenvironment biomarkers might add predictive value for outcomes. This study aimed to construct a risk signature with tumor infiltration immune and inflammatory cells to improve the prediction of survival. Methods: A risk signature model in combination with CD66b + neutrophils, CD3+ T, CD8+ T lymphocytes, and FOXP3 + regulatory T cells was developed in a training cohort of 327 GC patients undergoing surgical resection between 2011 and 2012, and validated in a validation cohort of 285 patients from 2012 to 2013. Results: The high CD66b expression predicted the poor disease special survival (DSS) and inversely correlated with the CD8 (P < 0.05) and FOXP3 expression (P < 0.05) in the training cohort. This was comparable to the disease-free survival (DFS) findings observed in the validation cohort. Furthermore, a risk stratification was developed from the integration of CD66b + neutrophils and T immune cells. For DFS and DSS, both demonstrated the worse prognosis in the high-risk group, when compared to the low-risk group in both the training cohort and validation cohort (all P < 0.05). In addition, the high-risk group was associated with post-operative relapses, and this risk signature model increased the predictive accuracy and efficiency for post-operative relapses. Moreover, the high-risk group identified a subgroup of GC patients who tended not to benefit from the adjuvant chemotherapy. Conclusions: The incorporation of neutrophils into T lymphocytes could provide more accurate prognostic information in GC and this risk stratification has potential for identifying the subgroup of GC patients who could benefit from adjuvant chemotherapy.

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