A Network Polypharmacological Approach to Combinatorial Drug Repurposing for Diffuse Intrinsic Pontine Glioma

Abstract

Despite five decades of clinical investigations, there is currently no effective treatment for children diagnosed with Diffuse Intrinsic Pontine Glioma (DIPG). We now understand that DIPGs share the same histone 3 mutation and fatal prognosis as other diffuse midline gliomas (DMGs), which led to the introduction of a new entity referred to as DMG, H3 K27M mutant. Indeed, therapeutics indicated for other brain neoplasms have proven ineffective for DIPGs. We posit that by using a polypharmacological approach to determine drug combinations that target distinct mechanistic pathways of DIPG, it is more likely that an efficacious treatment will be developed. Using FDAapproved drugs as an indication for viability of a drug pair for combinatorial use, we developed an embedding-based link-prediction model trained on a drug-disease regulation network, to predict the complementary relationship between a drug pair. To further understand the regulatory mechanisms of these potential drug combinations, we explored the regulatory action of these drugs upon statistically significant biological processes and molecular functions that are in turn misregulated in the disease state of phylogenetically similar gliomas to DIPG. Next, we constructed a regulatory network of these regulators illustrating a negative correlation between network proximity and overlap of direct targets, regulators, pathways and biological processes. We replicate research that finds an optimal distance between drugs in this regulatory network for both FDA-approved and synergistic drugs, although we deem the embedding model more performant. Finally, we highlight the individual importance of all disease-host protein regulators in notable pathways, by constructing protein-protein interaction networks for each pathway and calculating the centrality of each regulatory gene. We believe this newly formed knowledge of drug pairs and their regulatory pathways, will help researchers in identifying an efficacious treatment for this disease.

An Open Access Database of Licensed Cancer Drugs

“…Graph based methods are increasingly being used in the drug discovery process, including for repurposing ( Gramatica et al, 2014 ). One recent example used such methods to search for new therapeutic avenues to explore in diffuse intrinsic pontine glioma ( MacLean et al, 2020 ). Here too the availability of curated data enables rich networks to be developed in which multiple data sources can be used to construct models which embed implicit knowledge and new connections.…”