Figure 1.
Landscape of single-cell analysis and interpatient heterogeneity in PCNSL. (A) Schematic of the workflow for single-cell sequencing, spatial transcriptomics, and IHC analyses. (B) Uniform manifold approximation and projection (UMAP) plot of all cells after the integration assay colored according to the cell type. (C) Bar chart shows the proportion of each cell type split by samples. (D) Violin plot of GCB and ABC signature scores based on 2 different gene lists (Scott et al16 and Reddy et al17). (E) Violin plot shows the distribution of the GCB signature score between tumor and reactive samples. (F) Heat map of the top differentially upregulated genes in each sample. (G) Dot plot shows representative biological pathways enriched in each patient using Gene Ontology Biological Process. (H) Heat map of the top differentially downregulated genes in each sample. DC, dendric cell; NK, natural killer cell; Treg, regulatory T cell.

Landscape of single-cell analysis and interpatient heterogeneity in PCNSL. (A) Schematic of the workflow for single-cell sequencing, spatial transcriptomics, and IHC analyses. (B) Uniform manifold approximation and projection (UMAP) plot of all cells after the integration assay colored according to the cell type. (C) Bar chart shows the proportion of each cell type split by samples. (D) Violin plot of GCB and ABC signature scores based on 2 different gene lists (Scott et al16 and Reddy et al17). (E) Violin plot shows the distribution of the GCB signature score between tumor and reactive samples. (F) Heat map of the top differentially upregulated genes in each sample. (G) Dot plot shows representative biological pathways enriched in each patient using Gene Ontology Biological Process. (H) Heat map of the top differentially downregulated genes in each sample. DC, dendric cell; NK, natural killer cell; Treg, regulatory T cell.

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