The construction of a prognostic model for necroptosis-related lncRNA in glioma and drug prediction
Objective:To construct a prognostic assessment model for glioma patients based on long non-coding RNAs(ln-cRNAs)associated with necroptosis.Through this model,we aim to uncover the correlation between these lncRNAs and the prog-nosis of glioma patients,seeking new therapeutic avenues.Methods:Transcriptomic and clinical data of glioma patients were ex-tracted from the TCGA database.Pearson correlation analysis was employed to identify lncRNAs co-expressed with necroptosis.Single-factor and multi-factor Cox regression analyses,along with Lasso regression,were used to screen lncRNAs closely associ-ated with prognosis,thereby establishing a prognostic assessment model.The model's accuracy was validated through survival analysis,ROC curves,independent prognostic analysis,forest plots,and calibration curves.Additionally,functional enrichment analysis was conducted to identify active metabolic pathways in the high-risk and low-risk groups.Immunological analysis was per-formed to select potential drugs for glioma treatment.Results:The prognostic model categorized patients into the high-risk and low-risk groups based on risk scores.Significant differences were observed between the two groups in terms of survival curves,risk distribution,immune cell infiltration,immune-related functions,immune checkpoints,and immune therapy.The results of ROC curves,independent prognostic analysis,and forest plots supported the high reliability of the model in predicting patient survival.Conclusion:The predictive model,based on 10 necroptosis-related lncRNAs,contributes to the assessment of prognosis and mo-lecular characteristics in glioma patients.
万方数据
维普
