基于TCGA数据库肺腺癌自噬相关基因预后模型的建立与验证OA

Objective To explore autophagy-related genes(ARGs)in lung adenocarcinoma and con-struct a prognostic model for lung adenocarcinoma based on ARGs.Methods RNA high-throughput tran-scriptome data of lung adenocarcinoma were obtained from The Cancer Genome Atlas(TCGA)database and HADb database to acquire ARGs.A prognostic model for lung adenocarcinoma was constructed and validated based on differentially expressed ARGs,followed by the construction of column line graphs and calibration curves to explore the clinical application value of the model.Gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed on differentially expressed ARGs.Lasso regression analysis was conducted on differentially expressed ARGs with prognostic significance to construct the prognostic model for lung adenocarcinoma.Kaplan-Meier survival curves were plotted.Results A total of 31 differentially expressed ARGs were obtained,and 10 differentially expressed ARGs with prognostic signifi-cance were selected.Patients in the high-risk group were significantly associated with poorer overall survival,with statistical significance(P<0.05).T stage,N stage and risk score was an independent prognostic factor for patients with lung adenocarcinoma.The global consistency of the calibration curve column line graph was 0.710,indi-cating a high level of agreement between the model's predicted results and actual outcomes.Conclusion The risk model constructed based on differentially expressed ARGs can serve as a prognostic feature for patients with lung ade-nocarcinoma or provide a reference for individualized treatment for patients with lung adenocarcinoma.