Constructing a prognostic model of immune genes in oral squamous cell carcinoma based on bioinformatics
Wang Jinhang
Peng Shixiong
Yanng Kaicheng
Chen Yanping
Cui Zifeng
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.
Keywords：Oral squamous cell carcinomaImmune-related genesPrognosisRisk prediction modelThe cancer genome atlas database
Publication Date：2024-01-18
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：8( 78-85 )