Identification of an immune-related signature as a prognostic classifier for patients with early-stage head and neck squamous cell carcinoma

被引:1
|
作者
Wang, Le [1 ,2 ]
Zhang, Yulin [1 ,2 ]
Li, Hongmin [1 ]
Peng, Jilin [1 ,2 ]
Gao, Changhui [1 ]
Yu, Qiuning [1 ]
Gao, Pei [1 ]
Li, Ling [1 ]
Chen, Kuisheng [3 ]
Ye, Fanglei [1 ]
机构
[1] Zhengzhou Univ, Dept Otolaryngol Head & Neck Surg, Affiliated Hosp 1, 1 Longhu Zhonghuan Rd, Zhengzhou 450052, Peoples R China
[2] Zhengzhou Univ, Biotherapy Ctr, Affiliated Hosp 1, Zhengzhou, Peoples R China
[3] Zhengzhou Univ, Dept Pathol, Henan Key Lab Tumor Pathol, Affiliated Hosp 1, Zhengzhou, Peoples R China
基金
中国国家自然科学基金;
关键词
Early-stage head and neck squamous cell carcinoma (early-stage HNSCC); immune-related gene (IRG); prognostic evaluation; patient stratification; immune cell infiltration; POOR-PROGNOSIS; CANCER; MECHANISMS; RECURRENT; SURVIVAL; FAMILY;
D O I
10.21037/tcr-23-1791
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Background: Head and neck squamous cell carcinoma (HNSCC) is the most common type and accounts for 90% of all head and neck cancer cases. Despite advances in early diagnosis and treatment strategies-chemotherapy, surgical resection, and radiotherapy-5-year survival remains grim. For patients with early-stage HNSCC, accurately predicting clinical outcomes is challenging. Considering the pivotal role of the immune system in HNSCC, we developed a reliable immune-related gene signature (IRGS) and explored its predictive accuracy in patients with early-stage HNSCC. Methods: We examined immune gene expression profiles and clinical information from 230 early-stage HNSCC specimens, including 100 cases from The Cancer Genome Atlas (TCGA), 49 cases from the Gene Expression Omnibus (GEO; GSE65858), and 81 cases from an independent clinical cohort. The prognostic signature was constructed using Kaplan-Meier analysis and the least absolute shrinkage and selection operator (LASSO) Cox algorithm. We also explored the IRGS-related biological pathways and immune landscape using bioinformatics analysis. Results: A nine-immune-gene signature was generated to significantly stratify patients into high and low-risk groups. High risk patients exhibited shorter survival time [hazard ratio (HR) =13.795, 95% confidence interval (CI): 3.275-58.109, P<0.001]. The signature demonstrated robust prognostic ability in the training and validation sets and could independently predict overall survival (OS) and relapse-free survival (RFS). Subsequently, the receiver operating characteristic (ROC) curve and C-index confirmed the signature's predictive accuracy compared to clinical parameters. Additionally, cases classified as low risk showed more immune cell infiltration than high-risk cases. Conclusions: Our novel IRGS is a reliable and robust classifier for accurate patient stratification and prognostic evaluation. Future studies will attempt to affirm the signature's clinical application to early-stage HNSCC.
引用
收藏
页码:1367 / 1381
页数:20
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