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Biology subjects

Tari, H.

Publications and source records attributed to Tari, H..

2 recordsLinked to original sources

Loss of the H4 lysine methyltransferase KMT5B drives tumorigenic phenotypes by depleting H3K27me3 at loci otherwise retained in H3K27M mutant DIPG cells

DIPG are characterised by histone H3K27M mutations, resulting in global loss of the repressive mark H3K27me3, although certain key loci are retained. We recently identified subclonal loss-of-function mutations in the H4 lysine methyltransferase KMT5B to be associated with enhanced invasion/migration, but the mechanism by which this occurred was unclear. Here we use integrated ChIP-seq, ATAC-seq and RNA-seq on patient-derived, subclonal and CRISPR-Cas9-KD DIPG cells to show that loss of KMT5B/C causes depletion of these retained H3K27me3 loci via changes in chromatin accessibility, causing a raft of transcriptional changes which promote tumorigenesis. De-repression occurred at bivalent loci marked by H3K4me3, driving increased transcriptional heterogeneity and elevated gene expression associated with increased invasion, abrogated DNA repair and mesenchymal transition, along with a markedly altered secretome. These data suggest a previously unrecognised trans-histone (H4/H3) interaction in DIPG cells with a potentially profound effect on their diffusely infiltrating phenotype.

cancer biology↗

Quantification of spatial subclonal interactions enhancing the invasive phenotype of paediatric glioma

Intra-tumour heterogeneity is an intrinsic property of all cancers. In some cases, such variation can be maintained by interactions between tumour subclones with distinct molecular and phenotypic characteristics. In paediatric gliomas, interactions can take the form of enhanced invasive phenotype, a hallmark of these malignancies. However, subclonal interactions are hard to quantify and difficult to distinguish from spatial confounding factors and experimental bias. Here we combine spatial computational modelling of cellular interactions and invasion, with co-evolution experiments of clonally disassembled primary glioma lines derived at autopsy. We design a Bayesian inference framework to quantify spatial subclonal interactions between molecular and phenotypically distinct lineages with different patterns of invasion. We show how this approach could discriminate genuine subclonal interactions where one clone enhanced the invasive phenotype of another, from apparent interactions that were only due to the complex dynamics of subclones growing in space. This study provides a new approach for the identification and quantification of spatial subclonal interactions in cancer.

cancer biology↗