Identification of the Characteristic Genes and their Roles in Lung Adenocarcinoma Lymph Node Metastasis through Machine Learning Algorithm

Figure 4

Clinical correlation of our model. Notes: (a–b) univariate and multivariate analysis showed that the model is a risk factor independent of other clinical features; (c) the expression level of MAS1L, TCP10L2, CRHR2, and riskscore in patients with different age groups, ; (d) The expression level of MAS1L, TCP10L2, CRHR2, and riskscore in patients with different gender groups, , , and ; (e) the expression level of MAS1L, TCP10L2, CRHR2, and riskscore in patients with different stage groups, and ; (f) the expression level of MAS1L, TCP10L2, CRHR2, and riskscore in patients with different T-stage groups, ; (g) the expression level of MAS1L, TCP10L2, CRHR2, and riskscore in patients with different M-stage groups, ; (h) the expression level of MAS1L, TCP10L2, CRHR2, and riskscore in patients with different N-stage groups, , , and .

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