Research Paper Volume 16, Issue 9 pp 7704—7732
Immune cell senescence and exhaustion promote the occurrence of liver metastasis in colorectal cancer by regulating epithelial-mesenchymal transition
Figure 10. Development of prognostic risk models using machine learning algorithms. (A) Identification of the intersection between differentially expressed genes and genes from the turquoise module within subtypes of SMCs in primary and liver metastasis colorectal cancer tissues. (B, C) Construction of prognostic risk models employing 113 machine learning algorithms. The bar chart illustrates the relevant genes and their correlation coefficients (B), while the heatmap displays the AUC values for training and validation cohorts under various algorithms (C). (D–F) Depiction of Kaplan-Meier survival curves for high- and low-risk groups within all samples (D), training cohorts (E), and validation cohorts (F). (G–K) Display of Kaplan-Meier survival curves representing high- and low-risk groups in validation cohorts from GSE17536 (G), GSE17537 (H), GSE29621 (I), GSE38832 (J), and GSE39582 (K) samples.