Abstract
Doxorubicin is the most effective anthracycline chemotherapy drug in the treatment of cancer, and it is an effective single agent in the treatment of non-small cell lung cancer (NSCLC). There is a lack of studies on the differentially expressed doxorubicin metabolism-related lncRNAs in NSCLC. In this study, we extracted related genes from the TCGA database and matched them with lncRNAs. Doxorubicin metabolism-related lncRNA-based gene signatures (DMLncSig) were gradually screened from univariate regression, LASSO regression, and multivariate regression analysis, and the risk score model was constructed. These DMLncSig were subjected to a GO/KEGG analysis. We then used the risk model to construct the TME model and analyze drug sensitivity. The IMvigor 210 immunotherapy model was cited for validation. Eventually, we performed tumor stemness index differences, survival, and clinical correlation analyses.