DIPG-57. TESTING FOR SYNERGY AMONG RADIATION AND HIGHLY CLINICALLY RELEVANT CHEMOTHERAPEUTIC AGENTS IN PATIENT-DERIVED MODELS OF DIFFUSE MIDLINE GLIOMA

Abstract

Abstract Diffuse midline gliomas (DMG) are aggressive pediatric brain tumors with minimal long-term survival. Radiation is currently the only standard-of-care treatment and is non-curative. Several chemotherapy agents have shown preclinical and/or early clinical promise, and we hypothesize that finding effective chemoradiotherapeutic combinations is likely to be necessary to achieve long-term survival, based on experience from other previously incurable childhood cancers. We treated 8 DMG/DIPG cell lines with one, two, or three treatments among the HDAC inhibitor panobinostat, the CDK4/6 inhibitor ribociclib, the DRD2 inhibitor ONC201, the XPO1 inhibitor selinexor, the PI3K inhibitor paxalisib, and radiation. We then measured the cell survival with MTS assays. Cells were treated with drug concentrations ranging from 1 nM to 100 uM. To assess for synergy among our combinations, we used the Combination Index (CI) model, in which a score of <1 implies synergy. Of the 15 2-treatment combinations, ONC201 + radiation, ONC201 + paxalisib, ribociclib + ONC201, selinexor + paxalisib, and ribociclib + paxalisib met our criteria as successful, synergistic combinations: at least three cell lines with at least 90% cell death achieved, a CI value of 0.5 or lower at doses with at least 50% cell death, and at least 66% of dose levels with a CI value of 0.5 or lower. Early analysis suggests that ribociclib + ONC201 + paxalisib, ONC201 + paxalisib + radiation, and ONC201 + selinexor + paxalisib are the most effective three-treatment combinations. Patient-derived cell culture data in a heterogeneous pool of DMG/DIPG cell lines demonstrate synergy using several combinations of clinically relevant treatments, especially those including paxalisib. We are now optimizing treatment sequencing in synergistic combinations and testing in orthotopic xenograft models. Our goal is to find combinations that can become cycles of therapy in a multimodality clinical trial.