A novel ferroptosis- and endoplasmic reticulum stress-related gene signature for predicting prognosis, immune features and drug sensitivity in gastric cancer

While ferroptosis and endoplasmic reticulum stress (ERS) are implicated in gastric cancer (GC), their integrated prognostic value remains unclear. Our research aimed to construct a novel prediction model based on ferroptosis- and ERS-related genes (F&ERSRGs) to assess prognosis and identify potential therapeutic strategies for GC. We analyzed the transcriptome and clinical data of GC cohort (n = 378) from The Cancer Genome Atlas (TCGA) database as a training set and data of three independent cohorts from the Gene Expression Omnibus (GEO) database as validation sets. Differential expression analysis for the ferroptosis- and ERS-related genes (F&ERSRGs) between tumor and normal tissues was performed. Among the differentially expressed F&ERSRGs, prognostic F&ERSRGs screened by univariate Cox regression were included in Least Absolute Shrinkage and Selection Operator (LASSO) analysis to develop a risk model. Kaplan-Meier survival analysis and receiver operating characteristic (ROC) analysis were performed to assess the performance of the model. A nomogram was developed by integrating the risk score and clinicopathological characteristics. Functional enrichment analysis and evaluation of tumor microenvironment (TME) were also conducted. In addition, drug sensitivity was predicted using data from the Genomics of Drug Sensitivity in Cancer (GDSC) database. Finally, the expression of seven signature genes was validated by quantitative real-time PCR (qRT-PCR) in clinical samples. A seven-gene (NOX4, CHAC1, MYB, SNCA, ALB, CAV1, and FABP4) predictive risk model was finally constructed. Patients were categorized as high- or low-risk using median risk score as the threshold. The area under the ROC curve (AUC) values for the 1-, 3-, and 5-year overall survival (OS) in the training cohort were 0.619, 0.680, and 0.709, respectively. Survival analysis showed a better OS in low-risk patients in the training and validation cohorts. The AUC values of the nomogram for predicting 1-, 3-, and 5-year OS were 0.709, 0.711, and 0.723, respectively. TME analyses revealed a higher M2 macrophage infiltration and an immunosuppressive TME in the high-risk group. Furthermore, High-risk patients tended to be more sensitive to sepantronium bromide. A novel F&ERSRGs based signature was built for prognosis and treatment prediction of GC patients.