Observational studyJournal of neuro-oncology2026
Evaluation of NETosis-related biomarkers in glioblastoma multiforme: PAD4 as a potent diagnostic predictor.
Observational study in Journal of neuro-oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundGlioblastoma (GBM) is a primary brain tumor with a poor prognosis, characterized by profound immunosuppression and resistance to therapy. In recent years, neutrophil extracellular trap formation (NETosis) has been identified as a pro-tumoral mechanism in various malignancies; however, data on the concurrent and prospective evaluation of tissue and serum levels of NETosis-related biomarkers in GBM remain limited.
methodsThis prospective observational study included 42 patients with histopathologically confirmed GBM who underwent surgery and 38 patients with intracranial meningioma (WHO grades I–III) as controls. NETosis-related biomarkers, including peptidyl arginine deiminase 4 (PAD4), myeloperoxidase (MPO), neutrophil elastase (NE), and citrullinated histone H3 (citH3), were measured using ELISA in tumor tissue samples obtained intraoperatively and in paired preoperative serum samples. Hemogram parameters, inflammatory indices (NLR, PLR, and SII), tumor localization, preoperative tumor volume, and the Ki-67 proliferation index were prospectively recorded. Diagnostic performance was assessed using receiver operating characteristic (ROC) curve analysis, and independent predictors were identified by logistic regression analysis.
resultsIn tumor tissue, levels of NE, PAD4, MPO, and citH3 were significantly higher in patients with GBM compared to the control group (all p < 0.0001). In serum samples, only NE levels were significantly elevated in the GBM group (p < 0.05). Within the GBM cohort, PAD4, MPO, and citH3 levels were significantly higher in tumor tissue than in serum (p < 0.0001). A moderate negative correlation was observed between tissue NE levels and tumor volume (r = − 0.412, p = 0.007). ROC analysis demonstrated high diagnostic accuracy for tissue biomarkers, with PAD4 showing the highest discriminative performance (AUC = 0.9568). In logistic regression analysis, all tissue biomarkers were significant predictors of GBM, with PAD4 emerging as the strongest determinant.
conclusionsThis prospective study suggests that NETosis-related activity is pronounced within the GBM tumor microenvironment and demonstrates that NETosis-related biomarkers, particularly PAD4 measured in tumor tissue, may provide meaningful biological insights when evaluated together with multiple parameters. These findings support that NETosis pathways may constitute part of a holistic approach contributing to the understanding of glioblastoma microenvironment biology.
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