Molecular subtype and prognostic model of laryngeal squamous cell carcinoma based on neutrophil extracellular trap-related genes

基于中性粒细胞胞外陷阱相关基因的喉鳞状细胞癌分子亚型和预后模型

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Abstract

BACKGROUND: Laryngeal squamous cell carcinoma (LSCC) is a prevalent type of head and neck cancer with a poor prognosis due to late diagnosis and limited biomarkers. Neutrophil extracellular traps (NETs) play a critical role in cancer biology, but their involvement in LSCC is not well understood. This study aimed to explore NET's role in LSCC. METHODS: Differentially expressed NET-related genes (DE-NRGs) were identified using GSE10935 datasets and data from The Cancer Genome Atlas (TCGA) database. Functional enrichment and pathway analyses were conducted to elucidate their roles. Consensus clustering identified LSCC molecular subtypes. Immune landscape analyses revealed the tumor microenvironment of different subtypes. A prognostic model was developed using least absolute shrinkage and selection operator​(LASSO) regression and validated in external datasets. RESULTS: We identified 27 DE-NRGs in LSCC, and these genes were involved in heparin binding, cytokine activity, and leukocyte migration. Three molecular subtypes (C1, C2, and C3) were identified, with C3 showing the worst prognosis. Immune landscape analysis revealed significant differences in immune cell infiltration among subtypes. Higher expression of immune checkpoint genes in C2 suggested better immunotherapy outcomes. The prognostic model, based on seven hub DE-NRGs (ENO1, CD44, PTX3, P2RY14, CCL5, KLF2, MYH9), demonstrated good predictive performance with area under curve (AUC) values >0.61 for 1-, 3-, and 5-year overall survival. External validation confirmed the model's robustness. CONCLUSIONS: The study identified DE-NRGs as potential biomarkers and developed a robust prognostic model for LSCC. These findings offer insights into LSCC's molecular basis and highlight NETs' role in prognosis and immune landscape.

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