A disease model for Diffuse Intrinsic Pontine Glioma (DIPG) with mutations in TP53 and its application for drug repurposing

Abstract

Brain cancers are ones of most aggressive and difficult to treat cancers. Despite numerous studies of the cellular mechanisms of gliomas, it is difficult to stop tumor growth. A complex genetic and epigenetic nature of many gliomas and poorly known pathways of human neuron precursors maturation suggest turning to big data analysis to find new insights and directions for drug development. We developed in silico molecular models and predicted molecular switches in signaling cascades that maintain multipotency of neuronal precursor cells in diffuse intrinsic pontine glioma (DIPG) driven by the H3K27M mutation and mutations in the TP53 gene. Oncogenes and biomarkers were predicted based on transcriptomics and mutational genomics data from a cohort of 30 patients with DIPG analyzed using Elsevier artificial intelligence methods and a collection of manually curated cancer hallmark pathways. The molecular models of DIPG with mutations in TP53 and histone 3 gene describe the mechanism of oligodendrocyte dedifferentiation due to activation of transcriptional factors OLIG2, SOX2, and POU5F1, epithelial-to-mesenchymal transition via strong EGFR and TGFR signaling, enhanced cell response to hypoxia via HIF1A signaling and enhanced angiogenesis by VEGFA overexpression. Using in silico analysis, we identified drugs capable of inhibiting mutant TP53: vorinostat, cisplatin, paclitaxel, and statins were top-ranked drugs. The predicted drugs and oncogenes had individual patient-level differences that can be visualized with created DIPG model and may be useful for future research in the field of personalized medicine.