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Role of Heterotypic Neutrophil-in-Tumor Structure in the Prognosis of Patients With Buccal Mucosa Squamous Cell Carcinoma

Jie Fan, Jie Fan, Qigen Fang and 9 more

Frontiers in Oncology · 2020

doi:10.3389/fonc.2020.541878 (opens in a new tab)

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Abstract

ObjectiveTo analyze the role of frequency of heterotypic neutrophil-in-tumor structure (FNiT) in the prognosis of patients with buccal mucosa squamous cell carcinoma (BMSCC).MethodsIn vitro, we cocultured BMSCC cell line-H157 with neutrophils to form heterotypic neutrophil-in-tumor structures, which were then subject to fluorescence staining. Clinically, 145 patients were retrospectively enrolled. Associations between FNiT and clinicopathological variables including age, sex, smoking history, drinking history, betel nut chewing, tumor stage, node stage, metastasis, disease stage, lymphovascular invasion, extranodal extension, perineural invasion, and tumor grade were analyzed by chi-square test, and the main endpoints of interest were recurrence-free survival (RFS) and disease-specific survival (DSS) which were analyzed by the Kaplan-Meier method and Cox model.ResultsFluorescent staining results of typical heterotypic neutrophil-in-tumor structure showed that well-differentiated H157 cells had a stronger ability to internalize more neutrophils than poorly-differentiated H157 cells, with the latter often internalizing only one neutrophil or nothing. The mean FNiT was 4.2‰, with a range from 2.3‰ to 7.8‰. A total of 80 patients relapsed and 84 patients died of the disease. The 5-year RFS and DSS rate was 42% and 42%, respectively. Patients with an FNiT≥4.2‰ had a significantly higher risk for locoregional recurrence and cancer-caused death than those with an FNiT<4.2‰ (p=0.001 and p<0.001, respectively). The FNiT alone was independently significant in predicting poor RFS, and the FNiT along with tumor grade was an independent predictor for DSS.ConclusionThe FNiT as a novel predictor is significantly negatively associated with both the RFS and DSS of patients with BMSCC.

Abstract licence: CC BY

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