Research Paper Volume 15, Issue 22 pp 13504—13541

Figure 3. Two CoCu-DEG clusters identified. (A) The development process of CoCu-DEG clusters, and its KM and PCA performance. 72 CoCu-DEGs were applied for the clusters’ generation. Consensus plot (top left) showing the consensus value at specific k value. Clustering diagrams for k = 2 displaying at the top right. KM curves for k = 2 is at the lower left and PCA plot is at the lower right for k = 2. (B) The heatmap depicts the correlation between CoCu-DEG clusters, clinical parameters, and 72 CoCu-DEGs. The asterisks indicate statistical differences between CoCu clusters. In the heatmap, each row corresponds to a specific gene, while each column corresponds to a particular sample. (C) The box plots illustrate variations in the distribution of 23 immune cell types across the two CoCu-DEG clusters. The asterisks indicate distribution statistical differences between clusters. (D) A heatmap was used to visualize the enrichment of KEGG pathways that were present between the CoCu-DEG clusters, which was carried out utilizing the R package “GSVA.” (E) Box plots show the distribution of 21 copper homeostasis/cuproptosis-regulated genes across CoCu-DEG clusters. CoCu clusters: clusters identified by copper homeostasis and cuproptosis correlated genes; CoCu-DEGs: differentially expressed genes identified among CoCu clusters; CoCu-DEG clusters: clusters identified by CoCu-DEGs; DEGs: differentially expressed genes; KM: Kaplan–Meier estimator; PCA: Principal component analysis; KEGG: Kyoto Encyclopedia of Genes and Genomes; In Figure 3, statistical significance was defined as a P-value < 0.05; Results with P-values greater than or equal to 0.05 were considered not significant (ns), while those with P-values less than 0.05, 0.01, and 0.001 were denoted by ^*, ^**, and ^***, respectively.