Identified metabolic related genes to construct a prognostic model of Breast cancer patients

Abstract Background: More and more evidence confirms that there are many metabolic disorders in the tumor. The occurrence and development of breast cancer (BC) is closely related to metabolism. Methods: A metabolic related genes table was obtained by the Kyoto Encyclopedia of Genes and Genomes (KEGG) related metabolic pathway. The edgeR package was used to identify differentially expressed genes (DEGs) of The Cancer Genome Atlas (TCGA) breast cancer. We established a prognostic model by univariate Cox regression analysis and lasso-penalized Cox regression. The validation prognostic model was built through the Group on Earth Observations (GEO) database. Use the nomogram and Receiver Operating Characteristic (ROC) curve to verify the accuracy of models. Result: We identified 178 DEGs and 14 prognostic-related genes to construct a prognostic model. In the TCGA prognostic model and the GEO validation prognostic model, patients were divided into high riskscore group and low riskscore group, the high riskscore group had worse prognosis.Conclusion: We constructed a prognostic model of metabolic related genes and verified the feasibility and accuracy of the model. It is hoped that the model can provide a basis and biomarker for breast cancer related metabolic therapy and prognosis.