The development of prognostic gene markers associated with disulfidptosis in gastric cancer and their application in predicting drug response.

BACKGROUND: Gastric cancer (GC) is a malignancy known for its high fatality rate. Disulfidptosis, a potentially innovative therapeutic strategy for cancer treatment, has been proposed. Nevertheless, the specific involvement of disulfidptosis in the context of GC remains uncertain. METHODS: The mRNA expression profiles were obtained from the TCGA and GEO databases. Univariate and LASSO Cox regression analyses were employed to identify differentially expressed genes and develop a risk model for disulfidptosis-related genes. The performance of the model was evaluated using Kaplan-Meier curve, ROC curve, and nomogram. Univariate and multivariate Cox regression analyses were conducted to determine if the risk model could serve as an independent prognostic factor. The biological function of the identified genes was assessed through GO, KEGG, and GSEA analyses. The prediction of drug response was conducted employing the package "pRRophetic". Furthermore, gene expression was determined using qRT-PCR. RESULTS: An eight-gene signature were identified and utilized to categorize patients into low- and high-risk groups. Survival, receiver operating characteristic (ROC) curve, and Cox analyses provided clarification that these eight hub genes served as a favorable independent prognostic factor for patients with GC. A nomogram was constructed by integrating clinical parameters with the risk signatures, demonstrating high precision in predicting 1-, 3-, and 5-year survival rates. Additionally, drug sensitivity was different in the high-risk and low-risk groups, and the expression of three genes was verified by qRT-PCR. CONCLUSION: The prognostic risk model developed in this study demonstrates the potential to accurately forecast the prognosis of patients with GC.