Dynamic Chromatin Alteration Induces Oncogenic Hijacking by Nuclear Factor I Family Proteins for Medulloblastoma Progression
The cancer-specific epigenome is the critical scaffold on which genetic programs work to positively promote cancer growth and progression. Understanding and appropriately disrupting this epigenome will lead to the discovery of new, more extensive and effective therapies in addition to conventional personalized medicine that relies on genomic mutations. However, the epigenomic changes during the process from normal cells to cancer formation as well as the molecules involved in the maintenance of the aberrant epigenome are still poorly characterized, and the development of epigenome-based therapeutics is therefore undeniably stagnant. To address this issue, we here focus on SHH-subgroup medulloblastoma, a representative pediatric brain tumor for which we developed a reliable mouse model to capture the epigenomic changes that cerebellar granule cells, the cells of origin, undergo during tumorigenesis. By comparing the epigenomes of the different stages of transforming cells, we identified NFI family of developmental factors as oncogenic regulators in the epigenome of pre-cancerous and cancerous cells, which they also contribute to maintain. Furthermore, we report pharmacological experiments demonstrating that inhibition of NFIB methylation blocks tumor growth and increases sensitivity to molecularly targeted drugs by disrupting the cancer epigenome. Thus, this study is a unique example of how epigenomic studies of cancer have led directly to therapeutic insights, and similar approaches in various cancers would accelerate the establishment of novel therapies. Overall design: To identify the transcriptional targets of NFIA and NFIB in the context of Sonic Hedgehog medulloblastoma (SHH-MB), we performed knockdown of these genes using shRNAs and checked which genes were differentially expressed. The knockdown was performed in two human SHH-MB PDXs and on cultured murine SHH-MB cells derived from a spontaneous SHH-MB mouse model, in order to allow cross-species comparisons. The data from RNA-seq were also crossed and integrated with ATAC-seq and CUT&Tag data to identify direct targets of NFIA and NFIB.