Cuproptosis of endothelial cells in a hypoxic environment: from molecular classification to PMAIP1-targeted intervention

Figures

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  Fig. 1. Flowchart illustrating the study design and analysis workflow. PPI, protein-protein interaction; ROC, receiver operating characteristic; WGCNA, weighted gene co-expression network analysis

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  Fig. 2. Differential expression and correlation analysis of cuproptosis-related genes (CRGs). (A) Boxplot showing the distribution of gene expression levels; (B) Heatmap depicting expression patterns of CRGs; (C) Chromosomal locations of genes associated with cuproptosis; (D) Correlation analysis of differentially expressed CRGs. *p < 0.05, **p < 0.01, ***p < 0.001. AMI, acute myocardial infarction

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  Fig. 3. Identification of characteristic cuproptosis-related genes (CRGs) in acute myocardial infarction and construction of a diagnostic classification model. (A-B) LASSO regression for identifying characteristic CRGs; (C) Nomogram of the diagnostic classification model; (D) Receiver operating characteristic curve illustrating model performance; (E) Calibration curve demonstrating model accuracy; (F) Clinical decision curve analysis

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  Fig. 4. Molecular subtypes in acute myocardial infarction. (A) Consensus matrix for k = 2; (B) Cumulative distribution function (CDF) curves for k = 2–6; (C) Relative change in the area under the CDF curves for k = 2–6; (D) Principal component analysis of the two clusters; (E) Differences in cuproptosis-related genes (CRGs) between subtypes; (F) Heatmap of differentially expressed CRGs. *p < 0.05, ***p < 0.001

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  Fig. 5. Disease and classification weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) analysis. (A) Disease-related WGCNA; (B) Correlation of different modules with disease; (C) Classification-related WGCNA; (D) Correlation of different modules with classification; (E) Venn diagram of genes within key modules; (F) PPI analysis results

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  Fig. 6. Identification, validation, and functional characterization of key disease genes. (A) Boxplot of residuals; (B) Reverse cumulative distribution of residuals; (C) Receiver operating characteristic curves for key gene screening; (D) Importance scoring of genes identified by Support Vector Machines (SVM). (E-G) Expression levels of key genes in disease versus control groups; (H-J) Receiver operating characteristic curves demonstrating the ability of key genes to differentiate between disease and healthy controls; (K) Expression levels of HIF-1α in hypoxia-induced HUVECs (exposed to 1% O₂ for 4 h) measured by RT-qPCR; (L) Expression levels of PMAIP1 in hypoxia-induced HUVECs measured by RT-qPCR; (M) Copper (Cu2+) levels assessed using the Cell Copper Colorimetric Assay Kit. ***p < 0.001. AMI, acute myocardial infarction; GLM, Generalized Linear Model; RF, Random Forest