A Neutrophil Extracellular Traps-Related Signature Predicts Clinical Outcomes and Identifies Immune Landscape in Ovarian Cancer.

中性粒细胞胞外陷阱相关特征可预测卵巢癌的临床结果并识别其免疫图谱

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Ovarian cancer (OvCa) is the most lethal gynaecology malignancies worldwide. Neutrophil extracellular traps (NETs), net-like protein structures produced by activated neutrophils and DNA-histone complexes, have a central role in tumours, though haven't been fully explored in OvCa. We obtained transcriptome data from TCGA-OvCa database (n = 376) as training, ICGC-OvCa database (n = 111) as validation and GTEx database (n = 180) as controls. Through LASSO-COX Regression analysis, we identified an eight-gene signature among 87 NETs-related genes, which was significantly related to poor prognosis in both TCGA-OvCa and ICGC-OvCa cohorts (Log-rank p-value = 0.0003 and 0.0014). Next, we constructed and validated a prognostic nomogram, consist of NETs-related signature and clinical features (C-index = 0.82). We evaluated 22 typical immune cell infiltration through CIBERSORT analysis, which implied upregulation of memory CD4 + T cells, follicular helper T cells and neutrophils in high-risk group. Additionally, we predicted therapy sensitivity through TIDE algorithm, indicating that high NETs-riskscore exhibited more sensitivity towards Sorafenib and less sensitivity towards immunotherapy. We initially reported that RAC2 upregulation was associated with NETs formation and poor prognosis (p-value < 0.05) through IHC analysis of tissue microarrays (n = 125). Conclusively, NETs-related signature was reliable for OvCa prognosis prediction and therapy assessment. Especially, RAC2 was predominantly related to NETs formation, thus providing hints towards anti-tumour mechanism of NETs in OvCa.

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