Research on the mechanism of neutrophil extracellular trap-related genes mediating the onset of oral squamous cell carcinoma and their prognostic markers
10.12016/j.issn.2096-1456.202550548
- Author:
YU Haoyang
1
;
ZHANG Rui
2
;
SONG Hongquan
3
Author Information
1. School of Stomatology, Harbin Medical University
2. Department of Stomatology, Nangang Branch of Heilongjiang Province Hospital
3. Department of Oral Maxillofacial, The First Affiliated Hospital of Harbin Medical University
- Publication Type:Journal Article
- Keywords:
oral squamous cell carcinoma;
neutrophil extracellular traps;
prognostic model;
risk score;
bio⁃marker;
cathepsin G;
single-cell analysis;
tumor microenvironment;
prognostic evaluation
- From:
Journal of Prevention and Treatment for Stomatological Diseases
2026;34(4):349-366
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To investigate the prognostic significance and biological functions of neutrophil extracellular traps (NETs) related genes in oral squamous cell carcinoma (OSCC).
Methods:A total of 333 transcriptome datasets and 6 single-cell sequencing datasets of OSCC were retrieved from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Based on 69 NETs related gene sets, univariate Cox and Lasso-Cox regression were used to construct a prognostic risk model for OSCC. The model's efficacy was evaluated through Kaplan-Meier analysis and receiver operating characteristic (ROC) curves, and risk scoring and nomogram analysis were conducted. Further, the relationship between NETs risk scores and angiogenesis, epithelial-mesenchymal transition (EMT), and cell cycle was explored. Enrichment analysis was performed to annotate the functional characteristics of relevant pathways. Kaplan-Meier analysis was employed to screen for prognostic key genes. Candidate targets were validated through drug prediction and molecular docking assays. Single-cell RNA sequencing was utilized to characterize the expression profile of the key gene cathepsin G (CTSG) within the tumor microenvironment (TME). Using pan-cancer and OSCC related data retrieved from the TCGA database, we analyzed the differences in CTSG expression between tumor tissues and normal tissues. Subsequently, immunohistochemical staining experiments were performed on tissue microarrays to validate its expression at the protein level.
Results:A prognostic risk model based on six NETs related genes (F3, AKT1, CTSG, VNN3, MPO, and IL17A) was successfully established. Patients in the high-risk group exhibited significantly shorter overall survival (OS) (P < 0.000 1). The area under the ROC curve (AUC) of the established model for predicting 1-, 3-, and 5-year overall survival (OS) rates was 0.718, 0.820, and 0.805, respectively. The NETs related risk score was identified as an independent prognostic factor (P < 0.001), with the constructed nomogram demonstrating good calibration. The NETs related risk score correlated with angiogenesis (r = ˗0.20,, P < 0.001), EMT (r = 0.17, P < 0.01), G1/S phase transition (r = 0.11, P < 0.05), and G2/M phase transition (r = 0.17, P < 0.01). GSEA（gene set enrichment analysis）revealed that the high-risk group was significantly enriched in pathways including basal cell carcinoma, whereas the low-risk group exhibited significant enrichment in pathways such as alpha-linolenic acid metabolism (P < 0.05). Kaplan-Meier analysis revealed that patients with low expression of CTSG had a poorer prognosis (P < 0.001). Molecular docking assays demonstrated a stable binding interaction between CTSG and glutathione (binding energy: -7.4 kcal/mol). Single-cell RNA sequencing analysis further showed that CTSG was highly expressed in mast cell subsets but weakly expressed in malignant cells (P < 0.001). TCGA pan-cancer analysis revealed that CTSG is underexpressed in multiple cancer tissues, including OSCC (P < 0.05). Immunohistochemical staining confirmed that CTSG protein expression was lower in tumor tissues than in paracancerous tissues (P < 0.01).
Conclusion:The NETs related prognostic model established in this study exhibits robust predictive performance. CTSG was identified as a key prognostic gene, thereby providing a novel biomarker and potential therapeutic target for prognostic evaluation and targeted therapy of OSCC.
