Deciphering a Prognostic Signature Based on Soluble Mediators Defines the Immune Landscape and Predicts Prognosis in HNSCC

头颈部鳞状细胞癌 肿瘤科 比例危险模型 免疫疗法 列线图 内科学 医学 免疫系统 Lasso(编程语言) 基因签名 单变量 多元分析 弗雷明翰风险评分 头颈部癌 多元统计 癌症 基因 疾病 生物 免疫学 基因表达 计算机科学 万维网 机器学习 生物化学
作者
Hao Chi,Gaoge Peng,Guobin Song,Jinhao Zhang,Xixi Xie,Jinyan Yang,Jiayu Xu,Jieying Zhang,Ke Xu,Qibiao Wu,Guanhu Yang
出处
期刊:Frontiers in bioscience [Bioscience Research Institute Pte. Ltd.]
卷期号:29 (3) 被引量:4
标识
DOI:10.31083/j.fbl2903130
摘要

Background: The study on Head and Neck Squamous Cell Carcinoma (HNSCC), a prevalent and aggressive form of head and neck cancer, focuses on the often-overlooked role of soluble mediators. The objective is to leverage a transcriptome-based risk analysis utilizing soluble mediator-related genes (SMRGs) to provide novel insights into prognosis and immunotherapy efficacy in HNSCC patients. Methods: We analyzed the expression and prognostic significance of 10,859 SMRGs using 502 HNSCC and 44 normal samples from the TCGA-HNSC cohort in The Cancer Genome Atlas (TCGA). The samples were divided into training and test sets in a 7:3 ratio, with an additional external validation using 40 tumor samples from the International Cancer Genome Consortium (ICGC). Key differentially expressed genes (DEGs) with prognostic significance were identified through univariate and Lasso-Cox regression analyses. A prognostic model based on 20 SMRGs was developed using Lasso and multivariate Cox regression. We assessed the clinical outcomes and immune status in high-risk (HR) and low-risk (LR) HNSCC patients utilizing the BEST databases and single-sample Gene Set Enrichment Analysis (ssGSEA). Results: The 20 SMRGs were crucial in predicting the prognosis of HNSCC, with the SMRG signature emerging as an independent prognostic indicator. Patients classified in the HR group exhibited poorer outcomes compared to those in the LR group. A nomogram, integrating clinical characteristics and risk scores, demonstrated substantial prognostic value. Immunotherapy appeared to be more effective in the LR group, possibly attributed to enhanced immune infiltration and expression of immune checkpoints. Conclusions: The model based on soluble mediator-associated genes offers a fresh perspective for assessing the pre-immune efficacy and showcases robust predictive capabilities. This innovative approach holds significant promise in advancing the field of precision immuno-oncology research, providing valuable insights for personalized treatment strategies in HNSCC.
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