Development and validation of a combined ferroptosis and immune prognostic signature for lung adenocarcinoma.

Abstract

Studies have shown that the regulation of ferroptosis could be a new approach to cancer treatment and abnormal ferroptosis is closely associated with a dysregulated immune response. However, a combined signature with ferroptosis-related genes (FRGs) and immune-related genes (IRGs) is necessary to be constructed for predicting prognoses and guiding individualized precision therapy of lung adenocarcinoma (LUAD) patients. In this study, based on the Cancer Genome Atlas (TCGA) cohort, prognosis-related FRGs and IRGs were first identified and incorporated into the Least Absolute Shrinkage and Selection Operator (LASSO)-Cox regression model to generate a combined signature of ferroptosis- and immune-related genes (CSFI) values to predict the overall survivals (OSs) of LUAD patients. And patients with LUAD from the Gene Expression Omnibus (GEO) database were applied for the validation set. Nomogram was constructed based on multivariate Cox regression analysis. Subsequently, ferroptosis, immunity, and gene mutation status of patients between the CSFI-high and -low groups were compared. Additionally, the enrichment pathways in CSFI-high and -low groups were explored by Gene Ontology (GO), Kyoto Gene and Genome Encyclopedia (KEGG) and Gene Set Enrichment Analysis (GSEA) analyses. As a result, the CSFI-low group showed a good prognosis instead of the CSFI-high group. CSFI was identified to be an independent prognosis factor for LUAD. In general, there were ferroptosis- and immune-suppressive states in CSFI-high patients. Notably, the mutation frequencies of TP53 were higher in CSFI-high patients. In LUAD, CSFI which served as a novel classifier was offered for predicting the prognoses of patients and contributing to guiding personalized targeted therapy of patients. Therefore, based on these findings, it was believed that a synergistic treatment of ferroptosis and immunity would be more effective on LUAD patients with low CSFI values.