Elucidating the molecular basis of ATP-induced cell death in breast cancer: Construction of a robust prognostic model

Figure 1 Illustrates the results obtained from the analyses. A: Four ATP-induced cell death-related mRNAs are presented with P < 0.05 along with their corresponding risk ratios derived from the univariate Cox proportional hazard regression analysis; B: The process of tuning parameter (λ) selection for overall survival-related mRNAs in the Least Absolute Shrinkage and Selection Operator (LASSO) model is shown; C: The four chosen mRNAs' LASSO coefficient spectra, and the vertical line shows the coefficient values that the LASSO algorithm chose. HR: Hazard ratio.

Figure 2 Illustrates the Cancer Genome Atlas Breast Cancer dataset entire dataset's risk score distribution and expression heat map. A1-A3: Total risk score; B1-B3: Training set risk score; C1-C3: Test set risk score; D1-D3: External validation cohort risk score; A1, B1, C1 and D1: The risk score distribution is illustrated, with pink dots representing the low-risk group and red dots representing the high-risk group. The vertical dotted line represents the median risk score cut-off point; A2, B2, C2 and D2: Displays the survival time and survival status of all patients; A3, B3, C3 and D3: Shows the expression patterns of the four selected genes from the ATP-induced cell death signature.

Figure 3 Displays time-varying receiver operating characteristic curves and Kaplan-Meier survival analyses. A: In the complete dataset, the Kaplan-Meier survival analysis curve revealed a substantial difference in overall survival (OS) among the low-risk and high-risk groups; B: As well as in the training; C: Validation cohorts; D: The time-varying receiver operating characteristic curve area under the curve values for the total dataset; E: Training group; F: Validation group at 5 yr of OS were 0.67, 0.64, and 0.72, respectively; G: Kaplan-Meier survival analysis; H: Receiver operating characteristic curve over time.

Figure 4 Displays the results of the analysis on ATP-induced cell death-related microRNAs. A: Four microRNAs with P < 0.05 are provided, along with the risk ratios calculated using univariate Cox proportional hazard regression; B: Shows the selection process of tuning parameters (λ) for the overall survival-related miRNA using the Least Absolute Shrinkage and Selection Operator (LASSO) model; C: The four miRNAs' LASSO coefficient spectra are illustrated, with the vertical line reflecting the coefficient chosen using LASSO. HR: Hazard ratio.

Figure 5 Risk score distribution and expression heat map for the entire Cancer Genome Atlas Breast Cancer dataset. A1-A3: Total risk score; B1-B3: Training set risk score; C1-C3: Test set risk score; D1-D3: External validation cohort risk score; A1, B1, C1 and D1: The risk score distribution is illustrated, with pink dots representing the low-risk group and red dots representing the high-risk group. The vertical dotted line represents the median risk score cut-off point; A2, B2, C2 and D2: Shows the patient's survival time and status; A3, B3, C3 and D3: Presents the heat maps depicting the expression levels of four selected ATP-induced cell death signature microRNAs.

Figure 6 Displays the Kaplan-Meier survival analysis as well as the receiver operating characteristic curve over time. A: In the total data set; B: Training cohort; C: Validation cohort, the Kaplan-Meier curve shows that the low-risk group had longer overall survival (OS) than the high-risk group; D: Time-varying receiver operating characteristic curve area under the curve for 5-yr OS was 0.70 for the total data set; E: 0.69 for the training group; F: 0.75 for the validation group. These findings illustrate the prognostic model's power in predicting patient outcomes.

Figure 7 Displays time-varying receiver operating characteristic curves and Kaplan-Meier survival analyses. A: Kaplan-Meier survival analysis; B: Receiver operating characteristic curve over time.

Figure 8 Correlation between mRNA and immune-infiltrated population.

Figure 9 Volcano map of differential gene expression. A: Analysis of high-low risk difference in gene prognosis model; B: Analysis of high-low risk difference in the microRNA prognosis model.

Figure 10  Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis. A and E: Biological process (BP) enrichment results; B and F: Cell component (CC) enrichment results; C and G: Molecular function (MF) enrichment results; D and H: Kyoto Encyclopedia of Genes and Genomes enrichment results.

Figure 11  Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis. A and E: Biological process (BP) enrichment results; B and F: Cell component (CC) enrichment results; C and G: Molecular function (MF) enrichment results; D and H: Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment results.

Figure 12  Immune infiltration analysis of risk scores in different breast cancer types. A: Human epidermal growth factor receptor 2-positive (HER2+); B: HER2-; C: Estrogen receptor-positive (ER+); D: ER-; E: progesterone receptor-positive (PR+); F: PR-; G: Luminal A; H: Luminal B; I: HER2-enriched; J: Basal-like; K: Normal-like.