Characterization of a ferroptosis and iron-metabolism related lncRNA signature in lung adenocarcinoma

Abstract

Abstract Background Long non-coding RNAs (lncRNAs) are increasingly recognized as the crucial mediators in the regulation of ferroptosis and iron metabolism. A systematic understanding of ferroptosis and iron-metabolism related lncRNAs (FIRLs) in lung adenocarcinoma (LUAD) is essential for new diagnostic and therapeutic strategies. Methods FIRLs were obtained through Pearson correlation analysis between ferroptosis and iron-metabolism related genes and all lncRNAs. Univariate and multivariate Cox regression analysis were used to identify optimal prognostic lncRNAs. Next, a novel signature was constructed and risk score of each patient was calculated. Survival analysis and ROC analysis were performed to evaluate the predictive performance using The Cancer Genome Atlas Lung Adenocarcinoma (TCGA-LUAD) and Gene Expression Omnibus (GEO) datasets, respectively. Furthermore, multivariate Cox and stratification analysis were used to assess prognostic value of this signature in whole cohort and various subgroups. The correlation of risk signature with immune infiltration and gene mutation was also discussed. The expression of lncRNAs was verified by quantitative real-time PCR (qRT-PCR). Results A 7-FIRLs signature including ARHGEF26-AS1, LINC01137, C20orf197, MGC32805, TMPO-AS1, LINC00324, and LINC01116 was established in the present study to assess the overall survival (OS) of LUAD. The survival analysis and ROC curve indicated good predictive performance of the signature in both the TCGA training set and the GEO validation set. Multivariate Cox and stratification analysis indicated that the 7‐FIRLs signature was an independent prognostic factor for OS. Nomogram exhibited robust validity in prognostic prediction. Differences in immune cells, immune functions and gene mutation were also found between high-risk and low-risk groups. Conclusions This risk signature based on the FIRLs may be promising for the clinical prediction of prognosis and immunotherapeutic responses in LUAD patients.