疑难病杂志2024，Vol.23Issue(1)：78-85,8.DOI:10.3969/j.issn.1671-6450.2024.01.014
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
摘要
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分类
医药卫生引用本文复制引用
王锦航,彭士雄,杨凯成,陈彦平,崔子峰..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[J].疑难病杂志,2024,23(1):78-85,8.基金项目
河北省自然科学基金项目(H2022206410) （H2022206410）
河北省省级科技计划项目(22377779D) （22377779D）
河北省卫生厅青年科技 Hebei Provincial Natural Science Foundation(H2022206410) （H2022206410）
Hebei Provincial Science and Technology Program(22377779D) （22377779D）
Hebei Provincial Health Department Youth Science and Technology Project(20230147) （20230147）
