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Fig. 3 | BMC Cancer

Fig. 3

From: Comprehensive analysis of metabolism-related gene biomarkers reveals their impact on the diagnosis and prognosis of triple-negative breast cancer

Fig. 3

Development of a metabolism-related gene-based prognostic risk model in the TCGA cohort. (A) Univariate Cox regression analysis of differentially expressed metabolism-related genes. (Hazard Ratio (HR): Indicates the association between a gene and prognosis. HR > 1 means the gene is a risk factor, associated with worse prognosis; HR < 1 suggests means the gene is a protective factor, associated with better prognosis. P < 0.05 was considered statistically significant.). (B) Coefficient plot from the LASSO regression model (The left and right vertical lines respectively represent the λ value (Lambda Min) corresponding to the minimum cross - validation error and the simplest model (Lambda 1SE) within one standard error of the minimum MSE. Lambda Min was selected for subsequent analyses.). (C) Cross-validation for the selection of tuning parameters in the LASSO regression. (D) Multivariate Cox regression analysis revealed five key genes. (E) Distribution of patient survival status and survival time based on the prognostic model in the TCGA-TNBC cohort. (F) Expression profiles of five key genes in the prognostic model. (G) Survival analysis of TNBC patients of high- and low-risk group. (H) Validation of the predictive efficiency of the risk score via ROC curve analysis

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BMC Cancer

ISSN: 1471-2407

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