Abstract
Lung adenocarcinoma is the most common histological subtype of lung cancer which causes the largest number of deaths worldwide. Exploring reliable prognostic biomarkers based on biological behaviors and molecular mechanisms is essential for predicting prognosis and individualized treatment strategies. Ferroptosis is a recently discovered type of regulated cell death. We downloaded ferroptosis-related genes from the literature and collected transcriptome profiles of lung adenocarcinoma from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) to construct ferroptosis-related gene-pair matrixes. Then, we performed the least absolute shrinkage and selection operator regression to build our prognostic ferroptosis-related gene-pair index (FRGPI) in TCGA training matrix. Our study validated FRGPI through ROC curves, Kaplan-Meier methods, and Cox hazard analyses in TCGA and GEO cohorts. The optimal cut-off 0.081 stratified patients into low- and high-FRGPI groups. Also, the low-FRGPI group had a significantly better prognosis than the high-FRGPI group. For further study, we analyzed differentially expressed ferroptosis-related genes between high- and low-FRGPI groups. Gene set enrichment analysis (GSEA) enrichment maps indicated that "cell cycle," "DNA replication," "proteasome," and "the p53 signaling pathway" were significantly enriched in the high-FRGPI group. The high-FRGPI group also presented higher infiltration of M1 macrophages. Meanwhile, there were few differences in adaptive immune responses between high- and low-FRGPI groups. In conclusion, FRGPI was an independent prognostic biomarker which might be beneficial for guiding individualized tumor therapy.