Fig. 6: ScRNA-Seq analyses of patient liver tissue uncover pro-inflammatory liver macrophages as nizatidine target. | Nature Communications

Fig. 6: ScRNA-Seq analyses of patient liver tissue uncover pro-inflammatory liver macrophages as nizatidine target.

From: A human liver cell-based system modeling a clinical prognostic liver signature for therapeutic discovery

Fig. 6

a t-SNE map of single-cell transcriptomes from normal liver tissue of donors without history of chronic liver disease highlighting the main liver cell compartments. Data extracted from ref. 35. Cells sharing similar transcriptome profiles are grouped by clusters and each dot represents one cell. Expression t-SNE map of HRH2, CLEC5A, CD163L1, and MARCO are shown. The color bar indicates Log2-normalized expression. be Perturbation of gene expression by nizatidine in liver tissue from patient with chronic liver disease and HCC identifies liver macrophages as therapeutic target. b Experimental approach. CD45+ leukocytes from patient liver tissue were enriched by flow cytometry and were treated with nizatidine or vehicle control (DMSO). Single cells were sorted and analyzed as described35. c t-SNE map of single-cell transcriptomes showing control (blue) and nizatidine-treated cells (yellow), d the t-SNE map indicating the main cell compartments (MAFB: macrophages, CD8: CD8+ T lymphocytes). e Expression t-SNE map of HRH2, macrophage markers, and Siglec-10 are shown. The color bar indicates log2-normalized expression. fh GSEA for differentially expressed genes between nizatidine-treated and CTRL macrophages depicted in d. f Normalized enrichment score (NES) of genes related to macrophage activation (classical M1 vs alternative M2). g NES of the pathways significantly enriched after nizatidine treatment (FDR ≤ 0.05). h Expression heatmap of differentially expressed genes in individual nizatidine- and control-treated macrophages. Each row representing a single cell. Markers of inflammation, fibrogenesis/cancer, and antigen presentation are shown. All genes are normalized by row from their own min to max (Log2 fold; p value ≤ 0.05). Source data are provided as a Source data file.

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