RESUMO
BACKGROUND: Lung adenocarcinoma (LUAD) has a high mortality rate. Ferroptosis is linked to tumor initiation and progression. AIMS: This study aims to develop prognostic models of ferroptosis-related lncRNAs, evaluate the correlation between differentially expressed genes and tumor microenvironment, and identify prospective drugs for managing LUAD. METHODS AND RESULTS: In this study, transcriptomic and clinical data were downloaded from the TCGA database, and ferroptosis-related genes were obtained from the FerrDb database. Through correlation analysis, Cox analysis, and the LASSO algorithm for constructing a prognostic model, we found that ferroptosis-related lncRNA-based gene signatures (FLncSig) had a strong prognostic predicting ability in the LUAD patients. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichments reconfirmed that ferroptosis is related to receptor-ligand activity, enzyme inhibitor activity, and the IL-17 signaling pathway. Next, tumor mutation burden (TMB), tumor immune dysfunction and exclusion (TIDE) algorithms, and pRRophetic were used to predict immunotherapy response and chemotherapy sensitivity. The IMvigor210 cohort was also used to validate the prognostic model. In the tumor microenvironment, Type_II_IFN_Response and HLA were found to be a group of low-risk pathways, while MHC_class_I was a group of high-risk pathways. Patients in the high-risk subgroup had lower TIDE scores. Exclusion, MDSC, CAF, and TAMM2 were significantly and positively correlated with risk scores. In addition, we found 15 potential therapeutic drugs for LUAD. Finally, differential analysis of stemness index based on mRNA expression (mRNAsi) indicated that mRNAsi was correlated with gender, primary tumor (T), distant metastasis (M), and the tumor, node, and metastasis (TNM) stage in LUAD patients. CONCLUSIONS: In conclusion, the prognostic model based on FLncSig can alleviate the difficulty in predicting the prognosis and immunotherapy of LUAD patients. The identified FLncSig and the screened drugs exhibit potential for clinical application and provide references for the treatment of LUAD.
Assuntos
Adenocarcinoma , Ferroptose , RNA Longo não Codificante , Humanos , RNA Longo não Codificante/genética , Estudos Retrospectivos , Ferroptose/genética , Prognóstico , Transformação Celular Neoplásica , Pulmão , Microambiente Tumoral/genéticaRESUMO
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.