Construction And Validation Of Novel DNA Methylation-related Diagnostic And Prognostic Models In Lung Adenocarcinoma

Background:Lung adenocarcinoma(LUAD)is one of the most common cancers and fatal diseases in the world.The incidence of LUAD has been on the rise in recent years,and it has become a major health burden worldwide.Most patients with LUAD are diagnosed at an advanced stage of the disease and have a poor prognosis.Therefore,early identification and screening of LUAD can help improve the prognosis of LUAD.However,CT scan screening is mainly relied on at present,CT has certain radioactive hazards.It is necessary to find a less harmful and more convenient method for early screening and prediction of LUAD.A growing number of studies have shown that DNA methylation is one of the most common epigenetic abnormalities in LUAD tumorigenesis and development,which may play an important role in LUAD carcinogenesis,diagnosis and prognosis prediction.The purpose of this study was to identify differentially methylated Cp Gs(DMCs)between LUAD tumor tissues and normal samples,and to construct a LUAD-specific DNA methylation-related diagnostic and prognostic model in order to optimize the risk stratification and individualized medical interventions of LUAD.Methods:1.The LUAD methylation profiles and RNA-seq data were download from The Cancer Genome Atlas(TCGA)and GSE85845 datasets.We preliminarily identified DMCs and differentially methylated genes(DEGs)between LUAD tumor tissues and normal samples to analyze the correlation between DMCs methylation and DMGs expression level.2.LUAD-specific hypermethylated Cp Gs were further determined through analyzing the methylation profiles of 469 TCGA-LUAD individuals,184 normal blood samples in GSE69270,and 370TCGA-lung squamous cell carcinoma(LUSC)tissues.3.A diagnostic model based on LUAD-specific methylation biomarkers was constructed by the least absolute shrinkage and selection operator(LASSO)Cox regression analysis.The receiver operating characteristic(ROC)and the corresponding area under the curve(AUC)were used to verify the diagnostic performance of the DNA methylation-related diagnostic model in the GSE56044 and GSE75008 datasets.Kyoto Encyclopedia of Genes And Genomes(KEGG)pathway analysis was used to identify pathways with significant enrichment of genes associated with DNA methylation models.Bisulfite sequencing PCR(BSP)was performed in ten paired fresh LUAD tumor and normal tissues to evaluate model performance.4.Univariate and multivariate Cox regression analysis was used to identify DNA methylation biomarkers significantly associated with overall survival(OS)of LUAD patients,and to construct a DNA methylation-related prognosis model consisting of promoter Cp G sites.The predictive power of the prognostic model was assessed by constructing Kaplan-Meier survival curves and nomogram models.The validation of nomogram was performed using time-dependent ROC curve and decision curve analysis(DCA).Results:1.The DNA methylation-related diagnostic model was composed of four LUAD-specific hypermethylation sites,including cg14625175(HOXA10),cg01664864(DIO3),cg09005679(EDN3),and cg19516515(RUSC1).2.The AUC values of the DNA methylation-related diagnostic model in four independent cohorts,including the TCGA-LUAD,GSE85845,GSE56044 and GSE75008 datasets,were 0.924,0.941,0.952 and 0.835,respectively,which could accurately differentiate LUAD tumors from normal samples.3.BSP experiments showed that the methylation levels of four Cp G sites were significantly up-regulated in LUAD tumor samples compared with para-cancerous samples.4.A prognostic signature incorporating cg12691330(SYTL3),cg02196651(LNX1)and cg26165146(ARNTL2)was constructed based on 458 individuals in the TCGA-LUAD,which classified patients into low or high risk of poor prognosis and was considered as an independent prognostic parameter(HR = 1.55,95% CI: 1.13-2.10,P = 0.006).5.ROC curve and DCA analysis showed that nomogram model consisting of the prognostic signature and TNM stage was characterized with optimal predictive performance and clinical utility.Conclusions:Our study systematically depicted DNA methylation characteristics of LUAD and demonstrated the role of methylation spectrum in the diagnosis and prognosis of LUAD.Our established DNA methylation-related diagnostic model could effectively distinguish LUAD tissues from normal tissues.Meanwhile,the novel DNA methylation-related prognostic model constructed in this study could accurately predict and evaluate the long-term prognosis of LUAD patients.