| Objective:In this study,prognostic related molecules of glioma with different pathological grades were investigated,and it was expected that they could be used to evaluate the prognosis of patients with diffuse glioma and find biomarkers with clinical value.Methods:The TCGA glioma sequencing expression data and GEO-differential expression combined data sets,WGCNA was used to mine genes related to malignant progression of diffuse glioma,and Lasso regression was conducted to construct a risk assessment model.Then,IDI and C_INDEX were applied to select the best model.Finally,the optimal risk assessment model was used to evaluate the overall prognostic ability of the evaluated candidate molecules in combination with the multi-omics data including CNV,methylation,clinical characteristics and mutation conditions.Results:1.The results of differential analysis showed that there were 705 differentially expressed genes in TCGA database and 254 differentially expressed genes in GSE database,and a total of 67 differentially expressed genes were obtained from the intersection of the two genes(P<0.05).2.Univariate regression analysis excluded 30 genes and found that 37 genes were statistically significant,in glioma of all levels(P<0.05).Four different genes were screened out through multivariate COX regression analysis,and a prediction model was established.The risk values of all the samples were calculated,and the patients were divided into high risk group and low risk group based on the optimal cut-off value.The K-M survival curve showed that the average survival time of the low risk group was higher than that of the high risk group(P<0.05),while the 1-10 year survival prediction ROC curve showed that the area under the curve was all higher than 0.75.The AUC(area under ROC curve)of 1-3 years was 0.878,0.903,0.903,and the C index was 0.838.3.Combined with IDH1 mutations(isocitrate dehydrogenase 1)or not and ATRX(alpha thalassaemia chain genes associated with mental retardation syndrome Ⅹ)state would be low risk group(low-risk group)was divided into three subtypes,survival time between different subtypes had obvious difference(P<0.05),further analysis found that 4 gene prognosis model hadas the characteristics of multiple omics.4.Enrichment analysis showed that the four genes were involved in the formation of extracellular matrix,coagulation and hemostasis,as well as the activation of various immune signals such as macrophages and dendritic cells,and also played a role in metabolic pathways such as cytokine receptor adhesion plaques.Conclusions:1.Four genes closely related to the prognosis of patients with diffuse glioma were screened out:KDELR2,EMP3,TIMP1 and TAGLN2.The prognosis model based on the four genes had good predictive ability for the overall survival status of patients with diffuse glioma,and was not related to the pathological grading of diffuse glioma.2.Four molecular markers were associated with the clinical and genetic background of diffuse glioma,including clinical features,gene mutations,methylation,CNV,and signaling pathways. |