Objective: To identify ferroptosis-related genes associated with gastric cancer prognosis and investigate their potential molecular functions. Methods: Gene expression profiles and clinical information of gastric cancer tissues and adjacent normal tissues were obtained from TCGA database. Differential expression analysis of ferroptosis-related genes was performed using the "DESeq2" package in R software. Key genes were identified and a prognostic model for gastric cancer was constructed through Cox regression analysis based on the LASSO algorithm. Patients were stratified into high-risk and low-risk groups according to the median risk score. The accuracy of the model was evaluated using Kaplan-Meier survival analysis and ROC curve analysis. Immune cell infiltration in gastric cancer patients was assessed with the "CIBERSORT" package. The mRNA expression of differentially expressed genes(DEGs) with prognostic significance was examined in both gastric cancer and adjacent normal tissue samples. In vitro experiments were conducted to validate the impact of hydroxycarboxylic acid receptor 1(HCAR1) on the malignant biological behavior of gastric cancer. Results: Based on ferroptosis-related genes from the TCGA database, a novel prognostic model was constructed. It demonstrated robust predictive power for survival in both training and validation cohorts. RT-qPCR analysis of 8 pairs of gastric cancer and normal tissues revealed that the expression patterns of 6 prognostic DEGs in cancer tissues were consistent with those predicted by the model. In vitro experiments confirmed that downregulation of the key gene HCAR1 could inhibit the proliferation, invasion, and metastasis of gastric cancer cells. Conclusion The ferroptosis-related gene based prognostic model exhibits robust predictive capability, allowing for accurate determination of prognosis and survival in individuals with gastric cancer.