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. 2020 Jul 3;5:27. doi: 10.1038/s41525-020-0134-3

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© The Author(s) 2020

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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Fig. 2 — a Venn diagrams of SNVs for all lesions B1–B5 (left) and for MSI lesions B1–B4 (right) show low overlap between tumours. b Putative phylogenetic tree based on driver mutations. c VAFs of putative driver mutations. d Mutational signature analysis. e Transcript counts of the MLH1 detected by RNA-seq analysis. f Genomic landscape of CNAs shows low CIN for MSI samples B1 (ploidy: 2), B2 (ploidy: 1.95), B3 (ploidy: 2) and B4 (ploidy: 1.98), and higher CIN for MSS sample B5 (ploidy: 2.13). g Median log-ratio of putative driver CNAs highlights heterogeneity of tumourigenic events between all lesions. h Microbial analysis of DNA data shows microbial abundance at the phylum level. i Quantification of tumour immune infiltration reveals distinct profiles for eight immune cell populations across B1–B5.