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鉴定和验证 M2 巨噬细胞相关基因特征作为头颈部鳞状细胞癌的新型预后模型。

Identification and validation of M2 macrophage-related gene signature as a novel prognostic model for head and neck squamous cell carcinoma.

机构信息

Department of Otorhinolaryngology Head and Neck Surgery, The Affiliated Hospital of Guizhou Medical University, Guiyang, 550004, Guizhou, P.R. China.

School of clinical medicine, Guizhou Medical University, Guiyang, 550004, Guizhou, P.R. China.

出版信息

Sci Rep. 2024 Oct 25;14(1):25338. doi: 10.1038/s41598-024-76866-0.

Abstract

Head and neck squamous cell carcinoma (HNSCC) is a highly heterogeneous tumor. Commonly used tumor staging don't sufficiently and accurately assess the prognosis of HNSCC patients, resulting in a lack of guidance for clinical treatment decisions. M2 macrophage infiltration has been shown to be strongly associated with the tumor prognosis. In this study, we used the Cancer Genome Atlas (TCGA) data to screen for genes co-expressed with M2 macrophages in HNSCC. We used univariate Cox regression to screen out the genes associated with HNSCC prognosis, and constructed a HNSCC prognosis model by Lasso regression analysis. The results confirmed that the model had good predictive value and accuracy for the prognosis of HNSCC patients by survival analysis, ROC curve and nomogram. We divided the HNSCC samples into high-risk and low-risk groups according to the risk score, and the results showed that patients in the high-risk group were more prone to genetic mutations and had a higher tumor mutational burden. In addition, there were significant differences between risk groups in terms of immune cell infiltration and drug sensitivity. The HNSCC prognostic model established in this study may provide guidance for clinical therapeutic decision-making and provide a theoretical foundation for the development of new immunotherapy methods.

摘要

头颈部鳞状细胞癌(HNSCC)是一种高度异质性的肿瘤。常用的肿瘤分期方法不能充分、准确地评估 HNSCC 患者的预后,导致临床治疗决策缺乏指导。M2 巨噬细胞浸润已被证明与肿瘤预后密切相关。在本研究中,我们使用癌症基因组图谱(TCGA)数据筛选 HNSCC 中与 M2 巨噬细胞共表达的基因。我们使用单因素 Cox 回归筛选出与 HNSCC 预后相关的基因,并通过 Lasso 回归分析构建了 HNSCC 预后模型。生存分析、ROC 曲线和列线图的结果证实,该模型对 HNSCC 患者的预后具有良好的预测价值和准确性。我们根据风险评分将 HNSCC 样本分为高风险组和低风险组,结果表明高风险组患者更容易发生基因突变,肿瘤突变负担更高。此外,风险组之间在免疫细胞浸润和药物敏感性方面存在显著差异。本研究建立的 HNSCC 预后模型可为临床治疗决策提供指导,并为新的免疫治疗方法的发展提供理论基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/deda/11512021/bedfaec64117/41598_2024_76866_Fig1_HTML.jpg

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