A new ferroptosis-related signature model including messenger RNAs and long non-coding RNAs predicts the prognosis of gastric cancer patients

BACKGROUND AND OBJECTIVES: Gastric cancer (GC) is among the most malignant tumor types, which causes heavy healthy and economic burden to the people and societies all around the world. Establishment of an effective set of prognostic marker will benefit a lot to the treatment of GC patients clinically. Ferroptosis is a newly identified regulated cell death modality, with tight relevance with GC development. However, its application in the prognosis of GC has not been studied in detail. Deregulated messenger RNA (mRNA) and long non-coding RNA (lncRNA) expression profile in tumor can serve as novel prognostic marker for predicting the survival and cancer relapse in patients. METHODS: We downloaded ferroptosis-related gene expression microarray data, clinicopathologic information and a list of 259 ferroptosis-related genes from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and Ferroptosis database, respectively. Then, correlation analysis, univariate and multivariate Cox regression analysis were used to construct a novel prognostic model for GC. Then, we validated the model in the GEO datasets. Finally, we evaluated the differences in immune microenvironment between high- and low-risk groups. RESULTS: We utilized the ferroptosis-related mRNA and lncRNA profile to successfully construct a prognostic model (incorporating 2 mRNAs and 15 lncRNAs) in GC. Our model, integrating diverse clinical traits and critical factors of GC, showed desirable efficacy in the prognosis of GC patients. This model also manifested effectively in validation by using external patients’ data. CONCLUSIONS: Our study developed a novel ferroptosis-related signature to predict the prognosis of gastric cancer patients. The ferroptosis-related signature had a favorable predictive ability. This model may greatly boost the treatment of GC patients in clinical practice.