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基于中性粒细胞胞外诱捕网相关基因的喉鳞状细胞癌分子亚型及预后模型

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

作者信息

Wu Guiqin, Jin Riqun, Liao Jiahua, Zhang Jianhua, Liu Xuemei

机构信息

Otorhinolaryngology, Head and Neck Surgery Department, The First Affiliated Hospital of Gannan Medical University, Ganzhou, China.

Medical Oncology Department, The First Affiliated Hospital of Gannan Medical University, Ganzhou, China.

出版信息

Transl Cancer Res. 2025 Mar 30;14(3):1772-1785. doi: 10.21037/tcr-24-1531. Epub 2025 Mar 14.

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 (, , , , , , ), 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.

摘要

背景

喉鳞状细胞癌(LSCC)是一种常见的头颈癌,由于诊断较晚且生物标志物有限,其预后较差。中性粒细胞胞外陷阱(NETs)在癌症生物学中起着关键作用,但其在LSCC中的作用尚未得到充分了解。本研究旨在探讨NETs在LSCC中的作用。

方法

利用GSE10935数据集和癌症基因组图谱(TCGA)数据库的数据,鉴定差异表达的NET相关基因(DE-NRGs)。进行功能富集和通路分析以阐明其作用。共识聚类确定LSCC分子亚型。免疫景观分析揭示了不同亚型的肿瘤微环境。使用最小绝对收缩和选择算子(LASSO)回归开发了一个预后模型,并在外部数据集中进行了验证。

结果

我们在LSCC中鉴定出27个DE-NRGs,这些基因参与肝素结合、细胞因子活性和白细胞迁移。确定了三种分子亚型(C1、C2和C3),其中C3的预后最差。免疫景观分析显示各亚型之间免疫细胞浸润存在显著差异。C2中免疫检查点基因的高表达表明免疫治疗效果较好。基于七个核心DE-NRGs(,,,,,,)的预后模型在1年、3年和5年总生存的曲线下面积(AUC)值>0.61,显示出良好的预测性能。外部验证证实了该模型的稳健性。

结论

该研究将DE-NRGs鉴定为潜在的生物标志物,并为LSCC开发了一个稳健的预后模型。这些发现为LSCC的分子基础提供了见解,并突出了NETs在预后和免疫景观中的作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc6f/11985177/8f02c2a70646/tcr-14-03-1772-f1.jpg

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