Fig. 3: Cellular states of CNS SFTs by snRNA-seq.

A Uniform Manifold Approximation and Projection (UMAP) diagram of the different SFT states and cell types of the tumor microenvironment identified by snRNA-seq. SFT_Classical, SFT_Inflamed, SFT_Neural, SFT_Migratory, SFT_Angiogenic: SFT cells with different cellular states; Endo: Endothelial cell; Peri: Pericyte; Macro: Macrophage; Fibro: Fibroblast. B Proportion of different SFT cellular states in seven samples subjected to snRNA-seq sequencing (n = 7). Data are presented as mean ± SEM. *, p < 0.05; **, p < 0.01. (Student’s t-test, two-sided). C Projection of CD34, CD44, ALDH1A1 and ENG expression on the UMAP plot of the major cell types identified in SFT snRNA-seq. D Heatmap of SCENIC binary regulon activities in different SFT states. E RNA velocity plot embedded in UMAP space showing the putative near-transcriptional state of the different CNS SFT cellular states. F Pseudotime trajectory analysis of CNS SFT cell states. G Gene set variation analysis (GSVA) of gene sets or pathways enriched in different SFT cellular states. H Projection of the average expression of 200 genes from the HALLMARK_HYPOXIA gene set onto the UMAP plot of SFT snRNA-seq. I Proportion of different cell types deconvoluted from the bulk transcriptomic data (n = 88). Only cell types with a proportion >5% in the sample are shown. J Proportion of SFT-specific cell types in the four molecular subtypes (total sample n = 88). *p < 0.05; **p < 0.01; ***p < 0.001. (two-sided Wilcoxon Rank Sum and Signed Rank tests). Boxplots display the median (center line), interquartile range (box), and whiskers extending to the smallest and largest values within 1.5 × IQR from the lower (Q1) and upper (Q3) quartiles, respectively. Source data are provided as a Source Data file.