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. 2022 Apr 18;4(4):458–475. doi: 10.1038/s42255-022-00558-0

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© The Author(s) 2022, corrected publication 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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Fig. 1 — a, Differential abundance of bacterial genera in CRC stool samples. Clustered heatmap (Pearson correlation) shows the significant differentially abundant bacterial genera in an in-house cohort of samples from patients with CRC (n = 52 independent biological samples) in comparison with healthy donor (n = 63 independent biological samples) (P < 0.05; negative binomial Wald Benjamini–Hochberg testing) as identified by 16S rRNA gene sequencing. Top CRC-enriched bacteria⁷ are marked in red and separately plotted as abundance (baseMean) of a bacterium per patient (right). Heatmap intensities (blue colour scale) represent log₁₀ base mean values. b, Differential abundance of bacterial genera in CRC-tissue samples, following a PathSeq analysis on whole-exome sequencing (WXS) data (TCGA). Clustered heatmap (Pearson correlation) showing the significant differentially abundant bacterial genera in tumour tissue samples from patients with CRC (n = 50) in comparison with adjacent healthy mucosal samples (n = 50, P < 0.05; negative binomial Wald Benjamini–Hochberg testing). Top CRC-enriched bacteria are marked in red and separately plotted as abundance (score) of a bacterium per sample (right). Heatmap intensities (blue colour scale) represent log₁₀ scores. c, Fusobacterium abundance in tissue samples from patients with CRC (n = 595 independent biological samples, TCGA). WXS data were analysed for the logarithmic score abundance of Fusobacterium across all samples via quantile-based classification (colour code). d, Fusobacterium abundance across CMS subtypes. The cohort (c) was subjected to gene expression analysis and CMS classification of matching RNA-seq⁶⁷. Coloured, segregated bars show the proportion of patients with fusobacterial loads per CMS. Significant differences were observed for CMS1 versus CMS2 (P = 0.003103733) or CMS4 (P = 0.006062911) and CMS3 versus CMS2 (P = 0.038151361) or CMS4 (P = 0.035902419) Chi-squared tests. n^CMS1 = 62, n^CMS2 = 207, n^CMS3 = 69, n^CMS4 = 139 biologically independent samples.

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