Machine learning algorithm to construct cuproptosis- and immune-related prognosis prediction model for colon cancer

Figure 6 Principal component analysis and the independent predictive value of the risk score. A and B: The principal component analysis plots in The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus, respectively, and both high- and low-risk groups can be obviously distinguished; C and D: Univariate and multivariate Cox regression analyses of the cuproptosis- and immune-related risk score and other clinical features to screen for factors independently associated with prognosis; E: A nomogram helps predict a patient’s prognosis based on the patient’s information; F: Differential expression of CDKN2A, HSPA1A, and UCN3 in the high- and low-risk groups; G: Functional enrichment consequences of differentially expressed genes in the high- and low-risk groups. ^cP < 0.001.