Fig. 3

Profiling immune cell populations in PitNET. A Uniform Manifold Approximation and Projection (UMAP) map displaying 12,079 immune cells, with color-coding indicating individual cell types. B Dot plot illustrating the specific marker genes associated with the 10 major immune cell types. C–F The unsupervised clustering of PitNET RNA-seq cohorts based on the abundance of immune cells revealed three distinct TIME subtypes. The plot shows the abundance of immune cells in each subtype (C). Expression levels of immune checkpoint genes in the PitNET TIME subtypes (D). The pathways are enriched based on the DEGs (E, F). P-values were calculated using ANOVA and adjusted using FDR. G The composition of immune classification in samples from groups G1 to G6. H Bar plot indicating the proportion of positive cells stained for CD45, CD68, and CD8 in PitNET Tissue Microarray (TMA) using IHC with G1 (n = 6) and G6 (n = 52). P-values were calculated using the Wilcoxon rank-sum test. Results are presented as mean ± standard error of the mean in bar plots. I–J. Bar plot displaying the proportion of CD68/CD45 positive cells stained in PitNETs TMA using IHC with PIT1 (n = 21) and SF1 (n = 45) (I) and flow cytometry with PIT1 (n = 12) and SF1 (n = 19) (J). P-values were calculated using the Wilcoxon rank-sum test. Results are presented as mean ± standard error of the mean in bar plots