Fig. 5: Immune subtyping and regulatory factors in ATC/PDTC.

A The immune subtypes of ATC and PDTC patients were divided into three based on immune cell scores calculated using xCell. The bottom heatmap shows the abundance of immune cell markers and the activity of pathways (estimated by the GSEA method based on protein abundance) in patients with three immune subtypes. B Heatmap of immune score and stromal score in three immune subtypes. C Kaplan–Meier curves (Log-rank test) showing differences in patient overall survival among three immune subtypes (Cluster1: n = 46 samples, Cluster2: n = 9 samples, Cluster3: n = 46 samples). D Sanky plot showing the composition of ATC and PDTC samples in immune subtypes and proteomic subtype. E Boxplot of the immune score in three immune subtypes (Cluster1: n = 74 samples, Cluster2: n = 11 samples, Cluster3: n = 74 samples). F The survival risk scores (Cox proportional hazards models) of 343 transcription factors (TFs) collected from the ENCODE Project Consortium database based on protein abundance. G Bubble plot of transcription factors in terms of patient survival risk scores and differentially changed in Cluster 3 compared to Cluster 1. Two-sided Kruskal–Wallis test is used to estimate statistical significance. H Boxplot showed the differences in protein abundance of transcription factor STAT1 in three immune subtypes (Cluster1: n = 74 samples, Cluster2: n = 11 samples, Cluster3: n = 74 samples). In boxplot (E, H), two-sided Kruskal–Wallis test is used, the central line represents median, the bounds of boxes represent the first and third quantiles and the upper and lower whiskers extend to the highest or the smallest values with 1.5 interquartile range. Source data are provided as a Source Data file.