Objective To construct a prognostic and drug sensitivity model of low grade glioma based on tumor necrosis factor(TNF)signaling pathway related genes.Methods A total of 1023 patients were included in this study,and LASSO-Cox analysis was used to construct a predictive risk score.The receiver operating characteristic(ROC)curve was used to evaluate the effectiveness of the risk score.ESTIMATE and CIBERSORT algorithms were used to analyze the immune environment of LGG,and Oncocredit analysis was used to investigate the correlation between risk score and treatment drug sensitivity.Finally,construct a column chart and evaluate its performance using calibration curves.Results Seven TNF signaling pathway related genes(ACTN4 CARD16,HSPA1B,NKIRAS2,SPPL2A,TNFRSF11A,TRAF5)related to LGG prognosis were selected for a prognostic score.The Kaplan Meier survival curve showed that the overall survival(OS)of patients in the high-risk group is lower than that of the low-risk group.Risk score was associated with immune cells such as macrophages M1 and regulatory T cells.LGG patients in the high-risk group exhibited higher sensitivity to temozolomide.Multivariate Cox regression analysis showed that risk score and chromosome 1p19q combined deletion status were independent risk factors for the prognosis of LGG patients.Conclusion The prediction model based on TNF signaling pathway related genes can be used to predict the prognosis and drug sensitivity of LGG patients.
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