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一种结合手术状态的新型免疫相关预后模型,用于预测头颈部鳞状细胞癌中的肿瘤免疫细胞浸润和药物敏感性。

A novel immune-related prognostic model with surgical status to predict tumor immune cell infiltration and drug sensitivity in head and neck squamous cell carcinoma.

作者信息

Wang Lang, Yu Xianchao, Li Hongwei, Wang Chenglong

机构信息

Department of Radiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan Province, 610041, PR China.

School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan Province, 611731, PR China.

出版信息

Biochem Biophys Rep. 2023 Oct 14;36:101557. doi: 10.1016/j.bbrep.2023.101557. eCollection 2023 Dec.

Abstract

Tumor-infiltrating immune cells (TICs) affect tumorigenesis and tumor development in head and neck squamous cell carcinoma (HNSCC). We constructed a novel predictive model for HNSCC based on immune-related genes (IRGs) from The Cancer Genome Atlas and the Immunology Database and Analysis Portal. After identifying the IRGs, a predictive model involving 13 IRGs with high stratification value of overall survival (OS) was constructed by multiple support vector machine recursive feature elimination and least absolute shrinkage and selection operator regression. We explored the relationship between the risk score (RS) and clinical characteristics. The nomogram showed high concordance and good agreement in OS. Four TICs affected the OS and were in agreement with the abundance analysis of the RS levels. Furthermore, the low-risk HNSCC group showed higher expression of PD-1, CTLA4, and TIGIT, while the high-risk group showed higher expression of EGFR. The high-risk HNSCC showed high sensitivity to eight drugs.

摘要

肿瘤浸润免疫细胞(TICs)影响头颈部鳞状细胞癌(HNSCC)的肿瘤发生和发展。我们基于来自癌症基因组图谱以及免疫学数据库和分析门户的免疫相关基因(IRGs)构建了一种新的HNSCC预测模型。在鉴定出IRGs后,通过多支持向量机递归特征消除以及最小绝对收缩和选择算子回归,构建了一个包含13个对总生存期(OS)具有高分层价值的IRGs的预测模型。我们探讨了风险评分(RS)与临床特征之间的关系。列线图在OS方面显示出高度一致性和良好的吻合度。四种TICs影响OS,并且与RS水平的丰度分析结果一致。此外,低风险HNSCC组显示出较高的PD-1、CTLA4和TIGIT表达,而高风险组显示出较高的EGFR表达。高风险HNSCC对八种药物表现出高敏感性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/448a/10585349/b49eaece2c2e/gr1.jpg

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