Fig. 7: Computational tissue annotation enhances the visualization resolution of spatially identified lymphocyte clones. | npj Precision Oncology

Fig. 7: Computational tissue annotation enhances the visualization resolution of spatially identified lymphocyte clones.

From: Computational pathology annotation enhances the resolution and interpretation of breast cancer spatial transcriptomics data

Fig. 7

a Spatial distribution of BCSA2TumE2 B-cell clone 0 indicated by the yellow dots representing individual Visium spots. Scale bar 1 mm. b Magnified H&E image showing a selected spot enriched with B-cell clone 0. The blue dotted-line circle marked the position of the selected Visium spot, while colors around the nucleus represent the annotation of the cells. Red indicates tumor cells, yellow refers to immune cells, and blue implies stroma cells. Scale bar 50 μm. c Deconvolution outputs of the exact spot showing in (b) with B-cell clone 0 using the Cell2location method. d Spatial distribution of BCSA3TumA1 T-cell clone 61 indicated by the yellow dots representing individual Visium spots. Scale bar 1 mm. e Magnified H&E image showing a selected spot enriched with T-cell clone 61. The blue dotted-line circle marked the position of the selected Visium spot, while colors around the nucleus represent the annotation of the cells. Red indicates tumor cells, yellow refers to immune cells, and blue implies stroma cells. Scale bar 50 μm. f Deconvolution outputs of the exact spot showing in (e) with T-cell clone 61 using the Cell2location method. CAFs cancer-associated fibroblasts, PVLs perivascular-like cells, ILCs innate lymphoid cells.

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