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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. 3 — a Venn diagram of SNVs shows 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 all samples C1 (ploidy: 2.03), C2 (ploidy: 2.06), C3 (ploidy: 2.13), C4 (ploidy: 2.02) and C5 (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 varying fractions for eight immune cell populations across all samples.