The Construction of Disulfide-related LncRNA Prognostic Model and Exploration of Its Functional Mechanisms in Hepatocellular Carcinoma
Objective This study aimed to investigate long non-coding RNAs(LncRNAs)associated with disulfidptosis and to construct a risk prognostic model using identified LncRNAs,and to further identify novel biomarkers for prognostic assessment and individualized therapy in hepatocellular carcinoma(HCC).Methods Transcriptome and clinical data of HCC were downloaded from TCGA database.We used Pearson correlation analysis to identify LncRNAs linked to disulfidptosis.A risk prognostic model was developed employing multiple algorithmic approaches.Univariate Cox proportional hazards(Cox),multifactorial Cox,Kaplan-Meier(KM)analysis,ROC curves,DCA decision curve analysis,and nomogram method were employed to demonstrate its efficacy.Patients were stratified into low-and high-risk groups based on their risk scores.Subsequently,we conducted TIDE analysis,immune checkpoints analysis,m6A analysis,and drug sensitivity analysis.We then performed Gene Set Enrichment Analysis(GSEA)and gene mutation analysis to evaluate biological characteristics.Results Our study identified five disulfidptosis-associated LncRNAs to develop a prognostic model.Survival analysis indicated a markedly reduced overall survival period in the high-risk group compared to their low-risk counterparts(P＜0.001).The model yielded robust AUC values of 0.773,0.725,and 0.679 for predicting one-year,three-year,and five-year survival,respectively.Both univariate and multivariate Cox regression analyses reinforced the model's independent prognostic validity(P＜0.001).The nomogram demonstrated notable predictive reliability.Significant disparities were observed between the high and low-risk groups,particularly in immune escape,expression levels of immune checkpoint genes and m6A modification genes,and their drug sensitivity.Conclusion The prognostic model based on disulfidptosis-associated LncRNAs exhibits strong predictive accuracy.It offers critical insights into the survival outcomes and immune evasion in HCC,aiding in clinical decision-making.
Hepatocellular carcinomaDisulfidptosisLong non-coding RNARisk prognostic model
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