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Folia Neuropathologica
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vol. 62
Original paper

The neutrophil extracellular traps-related gene signature predicts the prognosis of glioblastoma multiforme

Guanghui Sun
1, 2
Wei Liu

  1. Weifang Medical University, Weifang, Shandong, China
  2. Brain Intensive Care Unit, Sunshine Union Hospital, Weifang, Shandong, China
  3. Department of Neurosurgery, Affiliated Hospital of Weifang Medical University, Weifang, Shandong, China
Folia Neuropathol 2024; 62 (1): 59-75
Online publish date: 2023/12/20
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This research hoped to explore the molecular mechanism of neutrophil extracellular traps (NETs) on glioblastoma multiforme (GBM) progression, and develop a promising prognostic signature for GBM based on NETs-related genes (NETGs).

Material and methods:
Gene expression data and clinical data of GBM tumour samples were downloaded from TCGA and CGGA databases. NETs-related molecular subtypes were explored by using ConsensusClusterPlus. The NETGs with a prognostic value were identified, and then a prognostic model was constructed using LASSO Cox regression. The predicted performance of the prognostic model was evaluated using TCGA training and CGGA validation cohorts. Moreover, independent prognostic indicators were identified by univariate and multivariate analysis to generate the nomogram model. The sensitivities for antitumor drugs and immunotherapy were predicted. Finally, hub genes in the prognostic model were validated using qPCR analysis.

GBM patients were divided into two molecular subtypes with significant differences in tumour microenvironment (TME) score, survival, and immune infiltration. A NETGs signature was constructed based on seven genes (CPPED1, F3, G0S2, MME, MMP9, MAPK1, and MPO), which had a high value for predicting prognosis. A nomogram was constructed by two independent prognostic factors (age and risk score), which could be used to predict 1-, 2-, and 3-year survival probability of GBM. Patients in the high-risk group were more sensitive to bicalutamide, gefitinib, and dasatinib; patients in the low-risk group were associated with poor response to immunotherapy. The validation of the six genes in the prognostic model was consistent with the results of bioinformatics analysis.

The NETs-based prognostic model and nomogram proposed in this study are promising prognostic prediction tools for GBM, which may provide new ideas for the development of precise tumour targeted therapy.


glioblastoma multiforme, neutrophil extracellular traps, molecular subtypes, prognostic model, bio-markers, survival analysis

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