Construction of a Cuprotosis-Related Gene-Based Model to Improve the Prognostic Evaluation of Patients with Gastric Cancer

Background: Gastric cancer (GC) is one of the most serious gastrointestinal malignancies with bad prognosis. The association between GC and cuprotosis-related genes has not been reported.

Methods: The clinical and RNA expression of patients with GC were downloaded from TCGA database. The CIBERSORT package was used to quantify the abundance of specific cell types. Using the Cox regression analysis, we conducted a prognostic nomogram model based on cuprotosis-related differential genes in GC. We evaluated the prognostic power of this model using the Kaplan-Meier (K-M) survival curve analysis, decision curve analysis (DCA), and receiver operating characteristic (ROC) curve analysis.

Results: The plasma cells, monocytes, and mast cells in GC tissue were significantly less than those in adjacent tissue ( < 0.05), while T cell CD4 memory activated macrophage M0, macrophage M1, and macrophages in GC tissue. The number of M2 was significantly more than that in the adjacent tissue ( < 0.05). Additionally, GC patients in the test group, the training group, and all the sample groups had shorter survival time with the increase of the risk factor ( < 0.05). The nomogram of GC based on cuprotosis prognosis-related genes was conducted. The AUC of the nomogram to predict 1-, 3-, and 5-year survival rate was 0.618, 0.618, and 0.625, respectively.

Conclusion: A novel cuprotosis-related gene signature impacts on the prognosis of GC. Our research provides new insights and potential targets for studying the link between GC and cuprotosis point, thereby providing new insights into understanding the molecular mechanism of GC.