Fig. 7: VEGFA and mtCTNNB1 confer epistasis control of CCA development within heterogeneous tumour ecosystems.
a, Spatially resolved co-occurence of VEGFA and mutual exclusivity of mtCtnnb1 for the CCA tumour subtype as revealed by C-G2P. Magnified views of three representative nodules ((i)–(iii)) identified as CCA. Nodules identified as CCA (left; the area covered by the tumour nodule is indicated as 10X Visium spots in yellow) as well as the mtCtnnb1 (middle; as in Fig. 3c) and VEGFA (as in Fig. 3c) perturbation probabilities are shown. Bayesian modelling of perturbation probabilities is used to infer the occurrence of individual perturbations per nodule (Methods). Data are derived from 324 nodules across six topographically separated regions used for 10X Visium from a single RUBIX experiment with two animals. Perturbation probabilities for all samples can be explored through the interactive web browser https://chocolat-g2p.dkfz.de/. b, Experimental design. Parallel RUBIX mouse models were performed using the leave-one-out experimental design. c, Time to tumour occurrence. Animals were palpated twice weekly to monitor tumour development. d, Histological quantification of liver tumour subtypes. H&E images were analysed, and tumour nodules were counted and classified as either HCC (top) or CCA (bottom); two independent liver-tissue sections per animal. The median ± s.d. alongside individual tumour counts are indicated. Group comparisons used a two-sided Kruskal–Wallis test with Dunn’s post-hoc test (Holm–Bonferroni correction). Exact adjusted P values are shown. e, Abundance of CCA. CK19 IHC was used as a cholangiocyte marker. Representative samples from a total of two separate sections per animal are depicted. b–e, n = 4 animals per group.
