基于双硫死亡相关lncRNA构建肺腺癌预后模型及ceRNA网络OA

Objective To screen disulfidptosis-related lncRNAs for prognostic biomarkers for lung adenocarci-noma(LUAD)diagnosis and treatment.Methods RNA-seq data and clinical information were obtained from The Cancer Genome Atlas(TCGA)database.LASSO regression analysis was used to construct a prognostic model based on disulfidptosis-related lncRNA.Patients were divided into high/low risk groups based on their risk-scores.Differences in overall survival,functional enrichment,tumor immune cell infiltration and drug sensitivity were further explored between risk groups.Finally,the ceRNA network was constructed and the ex-pression of three lncRNAs in LUAD was verified by external experiments.Results Developing a prognostic model consisting of three disulfidptosis lncRNA(AL365181.2,AC012615.1,AL606489.1),the survival rate of the low-risk group was significantly better than that of the high-risk group.There were significant differenc-es in OS,immune cell infiltration,immune checkpoint expression and immunotherapy response among pa-tients in different risk groups and in building ceRNA networks with model-associated lncRNA.Experimental validation showed that three lncRNA were expressed higher in LUAD tumor tissues than in normal tissues.Conclusion The present prognostic model was constructed using 3 disulfidptosis-related lncRNA and dem-onstrated that the model can independently predict survival in LUAD patients,providing new biomarkers for disulfidptosis in LUAD therapy.