Development and validation of neutrophil extracellular traps-derived signature to predict the prognosis for osteosarcoma patients

Abstract

Neutrophil extracellular traps (NETs) have been reported to be crucial in tumorigenesis and malignant progression. However, their prognostic significance, association with tumor immune microenvironment (TIME), and therapeutic response in osteosarcoma (OS) stills remain unclear. Hence, TARGET and GSE21257 cohorts were included for analysis. Single-sample gene set enrichment analysis (ssGSEA) and weighted gene co-expression network analysis (WGCNA) were conducted to extract NETs-derived genes. Subsequently, the NETs score (NETScore) model, consisting of 4 signature genes, was established and validated with the least absolute shrinkage and selection operator (LASSO) and Cox regression analysis. Our results indicated that NETScore has satisfactory predictability of the patient's overall survival, with AUC values at 1-, 3- and 5-year in the training cohort of 0.798, 0.792 and 0.804, respectively; similar prominent prediction performance was obtained in three validation cohorts. Further, real-time quantitative PCR (RT-qPCR) assay was conducted to determine the expression of signature genes in human osteoblasts and OS cells. Besides, NETScore and clinical factors (age, gender, metastatic status) were integrated to construct a nomogram. C-index and AUC values at 1-, 3-, and 5-year were above 0.800, displaying robust predictive performance. Patients with high and low NETScore had different immune statuses and drug sensitivity. Meanwhile, several positive regulatory immune function pathways, including T cell proliferation, activation and migration, were significantly suppressed among patients with high NETScore. Summarily, we established a novel NETScore that can accurately predict OS patients' prognosis, which correlated closely with the immune landscape and therapeutic response and might help to guide clinical decision-making.