Research Paper Volume 15, Issue 14 pp 6848—6864
The integration of machine learning and multi-omics analysis provides a powerful approach to screen aging-related genes and predict prognosis and immunotherapy efficacy in hepatocellular carcinoma
Figure 7. Immunological analysis between high and low risk groups. (A) Correlations between risk scores and different immune cells were calculated by the Cibersort algorithm. (B) Tumor microenvironment analysis to assess the differences between high and low risk groups. (C) Tumor stemness analysis found that risk scores were strongly correlated with tumor stemness. (D) Correlation analysis found that risk scores were strongly correlated with MMR. (E) Correlation analysis revealed that risk scores were strongly correlated with immune checkpoints. (F, G) The immune efficacy of the different risk groups was analyzed by the IMvigor210 dataset.