基于生物信息学构建口腔鳞状细胞癌免疫基因的预后模型
Constructing a prognostic model of immune genes in oral squamous cell carcinoma based on bioinformatics
王锦航 1彭士雄 2杨凯成 2陈彦平 2崔子峰2
作者信息
- 1. 050000 石家庄市第二医院口腔科
- 2. 河北医科大学第四医院口腔科
- 折叠
摘要
目的 旨在构建免疫相关基因(IRGs)的风险预测模型,以预测口腔鳞状细胞癌(OSCC)患者的预后.方法 应用生物信息学技术分析OSCC的转录组测序数据,鉴定出差异表达的IRGs(DEIRGs).通过Cox回归分析构建DEIRGs的风险预测模型,并对其预测能力进行评估.分析该模型与临床病理和免疫细胞浸润的相关性.结果 通过比较OSCC和正常样本共鉴定出3 634 个差异表达基因,其中包括330 个DEIRGs(FDR<0.05,|logFC|>1).单因素Cox回归分析筛选出与预后相关的20 个DEIRGs(P<0.05),多因素Cox回归分析筛选出其中 15 个DEIRGs用于构建风险预测模型.该模型可作为OSCC患者的独立预后因素(P<0.001),预测患者预后的能力具有较高的准确性(AUC =0.732),并与临床分期(t =-3.484,P<0.001)、B细胞(Cor =-0.180,P =0.002)和CD4+ T细胞(Cor =-0.127,P =0.026)密切相关.结论 基于15 个预后相关DEIRGs构建的风险预测模型能够有效地预测OSCC患者的预后,可帮助临床医生为不同风险的OSCC患者选择个性化的治疗策略.
Abstract
Objective To construct a risk prediction model for immune related genes(IRGs)to predict the progno-sis of oral squamous cell carcinoma(OSCC)patients.Methods Applying bioinformatics technology to analyze transcrip-tome sequencing data of OSCC and identify differentially expressed IRGs(DEIRGs).Construct a risk prediction model for DEIRGs through Cox regression analysis and evaluate its predictive ability.Analyze the correlation between the model and clinical pathology and immune cell infiltration.Results By comparing OSCC and normal samples,a total of 3634 differential-ly expressed genes were identified,including 330 DEIRGs(FDR<0.05,| logFC |>1).Univariate Coxregression analysis i-dentified 20 DEIRGs related to prognosis(P<0.05),while multivariate Cox regression analysis identified 15 DEIRGs for con-structing a risk prediction model.This model can serve as an independent prognostic factor for OSCC patients(P<0.001),with high accuracy in predicting patient prognosis(AUC=0.732),and is closely related to clinical staging(t=-3.484,P<0.001),B cells(Cor=-0.180,P=0.002),and CD4+ T cells(Cor =-0.127,P=0.026).Conclusion A risk prediction model based on 15 prognostic related DEIRGs can effectively predict the prognosis of OSCC patients and help clinicians choose personalized treatment strategies for OSCC patients with different risks.
关键词
口腔鳞状细胞癌/免疫相关基因/预后/风险预测模型/癌症基因组图谱数据库Key words
Oral squamous cell carcinoma/Immune-related genes/Prognosis/Risk prediction model/The cancer genome atlas database引用本文复制引用
基金项目
河北省自然科学基金(H2022206410)
河北省省级科技计划(22377779D)
Hebei Provincial Health Department Youth Science and Technology Project(20230147)
出版年
2024
国家科技期刊平台
NSTL
万方数据