AbstractMacrophages played an important role in the progression and treatment of head and neck squamous cell carcinoma (HNSCC). We employed weighted gene co-expression network analysis (WGCNA) to identify macrophage-related genes (MRGs) and classify patients with HNSCC into two distinct subtypes. A macrophage-related risk signature (MRS) model, comprising nine genes: IGF2BP2, PPP1R14C, SLC7A5, KRT9, RAC2, NTN4, CTLA4, APOC1, and CYP27A1, was formulated by integrating 101 machine learning algorithm combinations.

摘要巨噬细胞在头颈部鳞状细胞癌（HNSCC）的进展和治疗中起着重要作用。我们采用加权基因共表达网络分析（WGCNA）来鉴定巨噬细胞相关基因（MRG），并将HNSCC患者分为两种不同的亚型。通过整合101种机器学习算法组合，建立了巨噬细胞相关风险特征（MRS）模型，该模型包含9个基因：IGF2BP2，PPP1R14C，SLC7A5，KRT9，RAC2，NTN4，CTLA4，APOC1和CYP27A1。

We observed lower overall survival (OS) in the high-risk group and the high-risk group showed elevated expression levels in most of the immune checkpoint and human leukocyte antigen (HLA) genes, suggesting a strong immune evasion capacity. Correspondingly, TIDE score positively correlated with risk score, implying that high-risk tumors may resist immunotherapy more effectively.

我们观察到高危组的总生存率（OS）较低，高危组在大多数免疫检查点和人类白细胞抗原（HLA）基因中表达水平升高，表明具有很强的免疫逃避能力。相应地，TIDE评分与风险评分呈正相关，这意味着高危肿瘤可能更有效地抵抗免疫治疗。

At the single-cell level, we noted macrophages in the tumor microenvironment (TME) predominantly stalled in the G2/M phase, potentially hindering epithelial-mesenchymal transition and playing a crucial role in the inhibition of tumor progression. Finally, the proliferation and migration abilities of HNSCC cells significantly decreased after the expression of IGF2BP2 and SLC7A5 reduced.

在单细胞水平上，我们注意到肿瘤微环境（TME）中的巨噬细胞主要停滞在G2/M期，可能阻碍上皮-间质转化，并在抑制肿瘤进展中起关键作用。最后，在IGF2BP2和SLC7A5表达降低后，HNSCC细胞的增殖和迁移能力显着降低。

It also decreased migration ability of macrophages and facilitated their polarization towards the M1 direction. Our study constructed a novel MRS for HNSCC, which could serve as an indicator for predicting the prognosis, immune infiltration and immunotherapy for HNSCC patients..

它还降低了巨噬细胞的迁移能力，并促进了它们向M1方向的极化。我们的研究构建了一种新的HNSCC MRS，可作为预测HNSCC患者预后，免疫浸润和免疫治疗的指标。。

IntroductionHead and neck squamous cell carcinoma (HNSCC) is the sixth most prevalent cancer worldwide, accounting for over 95% of all head and neck tumors1. While the TNM classification system is the standard for prognosis and treatment determination, patient outcomes vary significantly even within the same TNM stages2.

引言头颈部鳞状细胞癌（HNSCC）是全球第六大最常见的癌症，占所有头颈部肿瘤的95%以上1。虽然TNM分类系统是预后和治疗确定的标准，但即使在相同的TNM阶段，患者的预后也有显着差异2。

This variability underscores the need for new biomarkers for an accurate survival prognosis and novel treatment targets to improve patient outcomes.The tumor microenvironment (TME) plays a crucial role in HNSCC progression by influencing recurrence, metastasis, and drug resistance3. Tumor-associated macrophages (TAMs), predominantly in the TME, either promote or hinder tumor growth depending on their M1 or M2 polarization4.

这种变异性强调了需要新的生物标志物来获得准确的生存预后和新的治疗目标以改善患者预后。肿瘤微环境（TME）通过影响复发，转移和耐药性在HNSCC进展中起着至关重要的作用3。主要在TME中的肿瘤相关巨噬细胞（TAM）根据其M1或M2极化促进或阻碍肿瘤生长4。

The dynamic balance between these macrophage types is critical for cancer progression, with a higher M2/M1 ratio often indicating advanced tumor stages5.In this study, we explored macrophage-related genes (MRGs) by clustering HNSCC subtypes based on macrophage infiltration using weighted gene co-expression network analysis (WGCNA)6.

这些巨噬细胞类型之间的动态平衡对于癌症进展至关重要，较高的M2/M1比率通常表明晚期肿瘤阶段5。在本研究中，我们通过使用加权基因共表达网络分析（WGCNA）6聚类基于巨噬细胞浸润的HNSCC亚型来探索巨噬细胞相关基因（MRG）。

We developed a macrophage-related risk-signature (MRS) model to predict patient outcomes and make diagnostic and therapeutic decisions. This study extended the examination of gene mutations, immune infiltration, and drug sensitivity, offering insights into the role of macrophages in HNSCC at the single-cell level.Materials and methodsData collection and collationWe accessed The Cancer Genome Atlas (TCGA), GSE65858 and GSE117973 datasets in the Gene Expression Omnibus (GEO) database to gather clinicopathological information, gene expression, and genomic mutation data of HNSCC patients7.

我们开发了一种巨噬细胞相关风险特征（MRS）模型来预测患者的预后并做出诊断和治疗决策。这项研究扩展了对基因突变，免疫浸润和药物敏感性的检查，为单细胞水平上巨噬细胞在HNSCC中的作用提供了见识。材料与方法数据收集和整理我们在基因表达综合（GEO）数据库中访问了癌症基因组图谱（TCGA），GSE65858和GSE117973数据集，以收集HNSCC患者的临床病理信息，基因表达和基因组突变数据7。

Single-cell RNA sequencing (scRNA-seq) profiles from nine HNSCC samples, comprising of 1,4087 cells, were retrieved from .

从包含14087个细胞的9个HNSCC样品中检索到单细胞RNA测序（scRNA-seq）谱。

Data availability

数据可用性

The data underlying this article are available in the Gene Expression Omnibus (GEO) database at https://www.ncbi.nlm.nih.gov/geo/ and The Cancer Genome Atlas (TCGA) at https://portal.gdc.cancer.gov/, and can be accessed with GSE65858, GSE182227 and GSE117973. Transcriptome data of 40 HNSCC patients analyzed during the current study are not publicly available because the project is still ongoing, but are available from the corresponding author on reasonable request.

本文的基础数据可在Gene Expression Omnibus（GEO）数据库中找到https://www.ncbi.nlm.nih.gov/geo/和癌症基因组图谱（TCGA）https://portal.gdc.cancer.gov/，可以通过GSE65858、GSE182227和GSE117973访问。在本研究期间分析的40名HNSCC患者的转录组数据尚未公开，因为该项目仍在进行中，但可根据合理要求从通讯作者处获得。

The rest of data generated or analyzed during this study are included in this published article (and its Supplementary files)..

本研究中生成或分析的其余数据包含在本文（及其补充文件）中。。

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Download referencesFundingThis work was supported by Taishan Scholar Project (No.ts20190991), the Key R&D Project of Shandong Province (No. 2022CXPT023) and the Open Funds of State Key Laboratory of Oncology in South China (No. HN2022-09).Author informationAuthor notesThese authors contributed equally: Yao Wang, Ya-Kui Mou and Wan-Chen Liu.Authors and AffiliationsDepartment of Otorhinolaryngology, Head and Neck Surgery, Yantai Yuhuangding Hospital, Qingdao University, No.20, East Road, Zhifu District, Yantai, 264000, ChinaYao Wang, Ya-Kui Mou, Wan-Chen Liu, Han-Rui Wang, Xiao-Yu Song, Ting Yang, Chao Ren & Xi-Cheng SongShandong Provincial Clinical Research Center for Otorhinolaryngologic Diseases, Yantai Yuhuangding Hospital, Yantai, ChinaYao Wang, Ya-Kui Mou, Wan-Chen Liu, Han-Rui Wang, Xiao-Yu Song, Ting Yang, Chao Ren & Xi-Cheng SongYantai Key Laboratory of Otorhinolaryngologic Diseases, Yantai, ChinaYao Wang, Ya-Kui Mou, Wan-Chen Liu, Han-Rui Wang, Xiao-Yu Song, Ting Yang, Chao Ren & Xi-Cheng SongShandong Provincial Key Laboratory of Neuroimmune Interaction and Regulation, Yantai Yuhuangding Hospital, Yantai, 264000, ChinaYao Wang, Ya-Kui Mou, Wan-Chen Liu, Han-Rui Wang, Xiao-Yu Song, Ting Yang, Chao Ren & Xi-Cheng SongDepartment of Neurology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, ChinaChao RenAuthorsYao WangView author publicationsYou can also search for this author in.

下载参考文献资助这项工作得到了泰山学者项目（No.ts20190991），山东省重点研发项目（No.2022CXPT023）和华南肿瘤国家重点实验室开放基金（No.HN2022-09）的支持。作者信息作者注意到这些作者做出了同样的贡献：Yao Wang，Ya Kui Mou和Wan Chen Liu。作者和单位青岛大学烟台玉皇顶医院耳鼻咽喉头颈外科，烟台市芝罘区东路20号，264000，中国Yao Wang，Ya Kui Mou，Wan Chen Liu，Han Rui Wang，Xiao Yu Song，Ting Yang，Chao Ren&Xi Cheng Song山东省耳鼻咽喉疾病临床研究中心，烟台玉皇顶医院，中国Yao Wang，Ya Kui Mou，Wan Chen Liu，Han Rui Wang，Xiao Yu Song，Ting Yang，Chao Ren&Xi Cheng Song烟台耳鼻咽喉疾病重点实验室，中国烟台Yao Wang山东省烟台玉皇顶医院神经免疫相互作用与调控重点实验室，烟台，264000，ChinaChao RenAuthorsYao WangView作者出版物您也可以在中搜索这位作者。

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PubMed Google ScholarContributionsY.W., Y.M. and W.L. performed data analysis work and aided in writing the manuscript. X.S., H.W. and T.Y. disposal data. C.R. designed the study, assisted in writing the manuscript. X.S. assisted and guide bioinformatics data analysis. All authors read and approved the final manuscript.Corresponding authorsCorrespondence to.

PubMed谷歌学术贡献。W、 ，Y.M.和W.L.进行了数据分析工作，并协助撰写了手稿。十、 S.，H.W.和T.Y.处置数据。C、 R.设计了这项研究，协助撰写了手稿。十、 美国协助和指导生物信息学数据分析。所有作者都阅读并批准了最终稿件。通讯作者通讯。

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Reprints and permissionsAbout this articleCite this articleWang, Y., Mou, YK., Liu, WC. et al. Machine learning developed a macrophage signature for predicting prognosis, immune infiltration and immunotherapy features in head and neck squamous cell carcinoma.

转载和许可本文引用本文Wang，Y.，Mou，YK。，刘，WC。机器学习开发了一种巨噬细胞特征，用于预测头颈部鳞状细胞癌的预后，免疫浸润和免疫治疗特征。

Sci Rep 14, 19538 (2024). https://doi.org/10.1038/s41598-024-70430-6Download citationReceived: 04 April 2024Accepted: 16 August 2024Published: 22 August 2024DOI: https://doi.org/10.1038/s41598-024-70430-6Share this articleAnyone you share the following link with will be able to read this content:Get shareable linkSorry, a shareable link is not currently available for this article.Copy to clipboard.

Sci Rep 1419538（2024）。https://doi.org/10.1038/s41598-024-70430-6Downloadhttps://doi.org/10.1038/s41598-024-70430-6Share本文与您共享以下链接的任何人都可以阅读此内容：获取可共享链接对不起，本文目前没有可共享的链接。复制到剪贴板。

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KeywordsHNSCCMacrophagePrognostic modelRisk scoreImmunotherapy

关键词HNSCCmacrophageProtocol modelRisk Score免疫疗法

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