Figure 1.
Schematic overview of the 3 workflows and the digital spatial technology. (A) Biopsies from patients diagnosed with MCL were embedded in formalin-fixed and paraffin-embedded blocks. Duplicate cores were sampled and transferred to a tissue microarray block. The full cohort was divided across 3 recipient blocks. Consecutive tissue sections were taken and used for the subsequent omics and image workflows. (B) For protein profiling, tissue was stained with fluorescent-labeled antibodies that targeted CD163, CD3, and CD20, together with barcoded antibodies that targeted 63 unique proteins. ROIs were selected in tumor-rich regions, and, when available, in tumor-sparse regions. Tumor-rich regions were defined as large carpets of mostly MCL cells, whereas tumor-sparse regions were dominated by T cells. Thresholding of Syto13, CD163, CD3, and CD20 allowed selection of MCL cells, CD163+ M2 macrophages, and T cells separately. Only a subset of the patients was CD163-rich (see “Methods” for definition), and the remaining patients were defined as CD163-sparse. (C) For mRNA profiling, tissue was stained with fluorescent-labeled antibodies targeting CD8, CD3, and CD20 together with barcoded-RNA probes targeting 1811 mRNAs. After technical filtering, 1482 mRNAs remained for biologic explorations. The threshold for Syto13, CD8, CD3, and CD20 allowed selection of MCL cells, cytotoxic T cells, and T-helper cells separately. (D) DSP was performed, and UV light was applied to each cell type segment in each ROI, thereby allowing aspiration of barcodes associated with the bound probes in each separate cell type and ROI. nCounter was used to count probes from the protein analysis, whereas Illumina sequencing was performed after library preparation of probes from the RNA profiling. (E) Image analysis using artificial intelligence–based software (Aiforia) was applied to the CD163/CD3/CD20 stained tissue sections. Tumor-rich and tumor-sparse regions were defined, and cells were segmented, classified according to their phenotype. The x/y coordinates were determined. Based on these data, cell frequencies and spatial metrics were determined. (F) Multiplex IF was used to validate the prognostic value of CD11c and CD163 combined.

Schematic overview of the 3 workflows and the digital spatial technology. (A) Biopsies from patients diagnosed with MCL were embedded in formalin-fixed and paraffin-embedded blocks. Duplicate cores were sampled and transferred to a tissue microarray block. The full cohort was divided across 3 recipient blocks. Consecutive tissue sections were taken and used for the subsequent omics and image workflows. (B) For protein profiling, tissue was stained with fluorescent-labeled antibodies that targeted CD163, CD3, and CD20, together with barcoded antibodies that targeted 63 unique proteins. ROIs were selected in tumor-rich regions, and, when available, in tumor-sparse regions. Tumor-rich regions were defined as large carpets of mostly MCL cells, whereas tumor-sparse regions were dominated by T cells. Thresholding of Syto13, CD163, CD3, and CD20 allowed selection of MCL cells, CD163+ M2 macrophages, and T cells separately. Only a subset of the patients was CD163-rich (see “Methods” for definition), and the remaining patients were defined as CD163-sparse. (C) For mRNA profiling, tissue was stained with fluorescent-labeled antibodies targeting CD8, CD3, and CD20 together with barcoded-RNA probes targeting 1811 mRNAs. After technical filtering, 1482 mRNAs remained for biologic explorations. The threshold for Syto13, CD8, CD3, and CD20 allowed selection of MCL cells, cytotoxic T cells, and T-helper cells separately. (D) DSP was performed, and UV light was applied to each cell type segment in each ROI, thereby allowing aspiration of barcodes associated with the bound probes in each separate cell type and ROI. nCounter was used to count probes from the protein analysis, whereas Illumina sequencing was performed after library preparation of probes from the RNA profiling. (E) Image analysis using artificial intelligence–based software (Aiforia) was applied to the CD163/CD3/CD20 stained tissue sections. Tumor-rich and tumor-sparse regions were defined, and cells were segmented, classified according to their phenotype. The x/y coordinates were determined. Based on these data, cell frequencies and spatial metrics were determined. (F) Multiplex IF was used to validate the prognostic value of CD11c and CD163 combined.

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