A novel ferroptosis-related gene signature associated with Helicobacter pylori for prognosis prediction in patients with gastric cancer

BackgroundGastric Cancer (GC) is a seriously heterogeneous disease, making the prognostic prediction challenging. The causal relationship between helicobacter pylori (Hp) infection and GC has been tightly entrenched by numerous epidemiological and clinical studies. Ferroptosis, a novel form of regulated cell death, is closely related to the increase and development of malignant tumors. ROS plays a key role in ferroptosis, whereas ROS produced by HP in some patients with GC also plays an important role in tumor progression. Whether the induction of ferroptosis can play a better role in the clinical treatment of GC caused by HP infection remains to be further studied. Therefore, the mRNA expression profiles and corresponding clinical data of patients with GC were downloaded from public databases. Methods Univariate Cox regression and LASSO regression were used to construct a multigene signature in the TCGA cohort. Patients with GC from the Gene Expression Omnibus (GEO) cohort were used for validation. The results showed that six differentially expressed genes (DEGs) were correlated with prognosis. Then, GSVA algorithm was used to calculate the enrichment score of each sample based on the six genes. Patients were divided into two risk groups (low and high) by the median risk score evaluated with the enrichment score and found statistically significant differences in their survival rates. ResultsA novel prognostic model integrating six ferroptosis-related and HP-related genes were firstly constructed, and a nomogram combining DEG signature with clinical features was constructed to confirm the robustness of the model for speculating about RFS in patients with GC. The receiver operating characteristic (ROC) curve, independent GEO datasets, and our experiments at the cellular level and with RNA extracted from patient tissues indicated that the signature endows a good predictive performance. The functions of this gene signature were assessed by gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) analysis. Additionally, immune infiltration analysis, gene mutation analysis, and molecular docking were used to explore the potential mechanism of this gene signature.ConclusionsConclusively, a novel gene signature can be used for the prognostic prediction of GC. Targeting ferroptosis and HP may be a therapeutic alternative for patients with GC.