Prognostic value of tumor-associated N1/N2 neutrophil plasticity in patients following radical resection of pancreas ductal adenocarcinoma

Abstract

Background As an integral part of the tumor microenvironment (TME), tumor-associated neutrophils play a crucial role in tumor development. The objective of this study was to investigate the plasticity of tumor-associated N1 and N2 neutrophils in the TME of pancreatic ductal adenocarcinoma (PDAC), along with its impact on survival and association with immune infiltrations.Methods The primary and validation cohorts including 90 radical resection patients from September 2012 to May 2016 and 29 radical resection patients from September 2018 to October 2019, respectively, with complete survival data, were enrolled. Immunofluorescence staining was used to identify tumor-associated N1 and N2 neutrophils, and the N1/N2 ratio was used to evaluate N1 and N2 plasticity. Thereafter, the association between tumor-associated N1/N2 neutrophil plasticity, clinical features, and immune infiltrations was investigated.Results There was a significant increase in tumor-associated N2 neutrophils compared with tumor-associated N1 neutrophils. Low N1/N2 ratios were associated with the poorer differentiation of tumors, easier lymph node metastases, and a higher TNM stage. The median overall survival (OS) and recurrence-free survival (RFS) of the high tumor-associated N1 neutrophil group were significantly longer than those of the low group, while the tumor-associated N2 neutrophils played an opposite role. The multivariable analysis revealed that a high N1/N2 ratio was a significant prognostic indicator for OS and RFS. In addition, tumor-associated N1/N2 neutrophils showed an opposite correlation with tumor-infiltrating CD8+ T cells and Tregs.Conclusion The plasticity of tumor-associated N1/N2 neutrophils was identified as a crucial prognostic indicator that might reflect the TME and immune escape in patients with PDAC. On further investigation and validation, our findings may be used to further stratify patients with varying prognoses to optimize treatment.