Construction Of A Novel Ferroptosis-Related Gene Signature For Predicting Survival Of Patients With Gastric Cncer

Objective: Gastric cancer is one of the most common gastrointestinal malignancies in China,and it has high mortality.Although the popularization of gastroscopy has brought the possibility of early gastric cancer screening,the detection rate of early gastric cancer in China is less than 10%,and the mortality rate of gastric cancer is still high.Ferroptosis is a new type of programmed cell death,different from apoptosis,necrosis and autophagy.At present,many studies have confirmed that ferroptosis can kill gastric cancer cells and is closely related to the occurrence and development of gastric cancer.Material and Methods: We obtained the m RNA expression data,clinicopathological data and survival information of gastric adenocarcinoma(TCGA-STAD)dataset from The Cancer Genome Atlas(TCGA)as a training set.The m RNA expression data and clinical information of GSE15459 dataset were downloaded from Gene Expression Omnibus(GEO)database.A total of 144 genes associated with ferroptosis were retrieved from Ferr DB.The expression data of 144 ferroptosis-related genes in the TCGA-STAD cohort were extracted,the differential genes were analyzed,and gene pathway enrichment analysis was performed.LASSO analysis and Cox regression analysis were used to further screen out the key genes significantly associated with prognosis and construct a prognosis model.The TCGA-STAD cohort was divided into high and low risk groups according to the prognostic model.The accuracy of the model was evaluated by Kaplan-Meier curve and ROC curve.The reliability of the model was verified by GSE15459 data set.Additionally,we used ESTIMATE and Cibersort algorithms to estimate immune invasion and proportion of immune cells in the high-low risk group to further explore the relationship between the model and tumor immune status and tumor microenvironment.Finally,51 pairs of gastric cancer/paracancer tissue clinical samples were used for IHC staining of key genes to verify the abnormal expression of them.Results: The global microarray m RNA expression dataset of 301 cases of gastric adenocarcinoma and 30 cases of paracancer tissues were screened from the TCGA database,and 34 out of 144 ferroptosis-related genes were found to be differentially expressed,the differentially expressed genes were highly enriched in oxidative stress and inflammatory response related pathways.After LASSO and Cox regression analysis,a risk scoring model consisting of key genes CHAC1,NOX4 and HIF1 A was constructed.Verified by GSE15459 dataset,this model can effectively distinguish high and low risk gastric cancer patients,and the rosette constructed by the patients has good survival prediction ability.ESTIMATE analysis showed a significant positive correlation between risk score and degree of immune cell infiltration.Cibeisort results also showed differences in the composition of immune cells in the high and low risk groups.Next,IHC experiments were used to verify the expression of the three key genes in clinical samples.Experimental results confirmed that CHAC1 expression was down-regulated and NOX4 expression was up-regulated in gastric cancer tissues.Conclusions: By bioinformatics analysis,this study constructed and verified a prognostic model of gastric cancer composed of ferroptosis-related genes CHAC1,NOX4 and HIF1 A,which can accurately predict the prognosis of gastric cancer patients and provide valuable guidance for personalized treatment.The model found a significant positive correlation between risk score and tumor immune invasion,suggesting a potential link between ferroptosis-related and tumor immune microenvironment.