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《天津医科大学学报》[ISSN:1006-8147/CN:12-1259/R]

卷:

29卷

期数:

2023年04期

页码:

379-386

栏目:

基础医学

出版日期:

2023-07-10

文章信息/Info

Title:

Pyroptosis-related gene signature predicts the tumor microenvironment and prognosis in neuroblastoma

文章编号:

1006-8147（2023）04-0379-08

作者:

高伟靖; 李龙

天津医科大学基础医学院免疫学系，天津300070

Author(s):

GAO Wei-jing; LI Long

Department of Immunology，School of Basic Medical Sciences，Tianjin Medical University，Tianjin 300070，China

关键词:

焦亡; 神经母细胞瘤; 肿瘤微环境; 预后

Keywords:

pyroptosis; neuroblastoma; tumor microenvironment; prognosis

分类号:

R739.4

DOI:

-

文献标志码:

A

摘要:

目的：研究焦亡相关基因的特征与神经母细胞瘤的肿瘤免疫微环境（TME）的关系以及神经母细胞瘤患者的预后。方法：基因表达数据来自于TCGA、NCBI-GEO和TARGET数据库。ESTIMATE和ssGSEA用于分析TME。LASSO-COX方法用于建立预后模型以量化神经母细胞瘤中焦亡的水平。同时构建了一种名为Risk的新评分方法，并全面地评价Risk评分的有效性。结果：焦亡相关基因在神经母细胞瘤中突变负荷较低（3.35%突变率）。同时，焦亡相关基因的高表达与患者良好的预后相关（HR=0.4036；95%CI：0.2915~0.5587；Log-ranktest，P<0.001）。免疫细胞的浸润程度在焦亡相关基因高表达的患者中更为丰富。多因素Cox分析表明，Risk评分是一种独立的预后因素，可以提高临床预测模型的准确性（曲线下面积均大于0.8）。结合常见的患者临床特征构建的诺模图具有很好的临床预测价值（P<0.001）。低风险患者的免疫细胞浸润也更为丰富，与预后良好相关。结论：焦亡相关基因的特征可以预测神经母细胞瘤患者的免疫微环境，基于焦亡相关基因的表达特征构建的预后模型可很好的预测患者的预后情况。

Abstract:

Objective：The relationship between pyroptosis-related gene signature and the tumor microenvironment（ TME） and the prognosis of patients withneuroblastoma. Methods：Gene expression data were obtained from TCGA，NCBI-GEO and TARGET databases. ESTIMATE and ssGSEA were used to analyze TME. The LASSO-COX method was used to develop a prognostic model to quantify the level of pyroptosis in neuroblastoma. At the same time，a new scoring method called Risk was constructed and the effectiveness of Risk scoring was comprehensively evaluated. Results：Pyroptosis-related genes had low mutational burden in neuroblastoma （ 3.35% mutation rate）. High expression of pyroptosis-related genes indicated good prognosis of patients（ HR=0.403 6；95%CI：0.291 5-0.558 7；Log-rank test， P<0.001）. The infiltration of immune cells was more abundant in patients with high expression of pyroptosis-related genes. Multivariate Cox analysis showed that Risk scoring was an independent prognostic factor that could improve the accuracy of clinical prediction models （ area under curve>0.8）.The Nomograms constructed by combining common clinical characteristics of patients have good clinical predictive value（ P<0.001）. Immune cell infiltration was also more abundant in low-risk patients，which correlated with favorable prognosis. Conclusion：The immune microenvironment of patients with neuroblastoma can be predicted according to the characteristics of pyroptosis-related genes，and the prognostic model constructed based on the expression characteristics of pyroptosis-related genes has good accuracy in predicting the prognosis of patients.

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备注/Memo

备注/Memo:

基金项目: 国家重点研发计划（2018YFC1313000，2018YFC1313002）
作者简介: 高伟靖（1996-），男，硕士在读，研究方向：肿瘤免疫；
通信作者：李龙，E-mail：Long.Li@tmu.edu.cn。

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更新日期/Last Update: 2023-07-10