Figure 5.

Unsupervised cluster analysis of differentially expressed genes related to prognosis, and patients were divided into three different genomic subtypes (gene clusters A–C): (a) consensus matrix, (b) CDF graph, and (c) relative change in the area under the CDF curve when k = 2–9. (d) Principal component analysis showing evident clustering among the three gene clusters. (e) Heat maps showing that these subgroups have different clinicopathological characteristics. (f) Kaplan–Meier was used to analyze the survival curve between different m6A gene clusters. Gene cluster II was associated with better survival outcomes. (g) Expression of m6A regulatory factors in breast cancer in three gene clusters. (h) Abundance of immune-infiltrating cells in three different m6A gene clusters in breast cancer (^∗P < 0.05, ^∗∗P < 0.01, and ^∗∗∗P < 0.001).