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. 2023 May 1;4(5):608–628. doi: 10.1038/s43018-023-00548-5

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© The Author(s) 2023

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Extended Data Fig. 6 — a, The relative amount of immune cells in each micro-region calculated on the gene list of Danaher et al. using the GeoMx transcriptome data. Z-score distribution of the gene expression comparisons of tumor versus stroma, TLS, and CD45⁺ micro-regions in b, excluded-low (n = 2 and 256 genes) and c, infiltrated-low (n = 1 and 369 genes) samples. Correlation of all genes attributed to stroma, TLS, and CD45⁺ micro-regions (lower quartile) or with tumor micro-regions (upper qurtile) with d, cell type abundance in excluded-low and e, infiltrated-low samples. Sum of sampling score for genes correlating with any immune cell type (Pearson Correlation r > 0.5) per cell type in f, excluded-low (n = 2 patients and n = 62 genes) and g, infiltrated-low samples (n = 1 patient and n = 169 genes).