Abstract 314: Evaluation of effective drug combinations of sonidegib and ribociclib for treatment of Sonic hedgehog medulloblastoma using mathematical models of the cell cycle and Hedgehog pathways

Sonic hedgehog(SHH) tumors account for roughly 25% of all pediatric medulloblastoma. Aberrant signaling of the SHH pathway, typically via Patched-1 (PTCH) mutation, results in cell proliferation and subsequent tumor formation. Smoothened(SMO) inhibitors such as sonidegibhave been used clinically to combat tumor progression and have shown initial promise. However, many tumors acquire resistance to therapy. Combination therapy with an additional agent targeting another node in pathways affecting cell-cycle progression such as ribociclib, a cyclin D-dependent kinase (CDK) 4/6 inhibitor, may improve therapy and reduce tumor burden by delaying or preventing the development of resistance. Identification and evaluation of effective anti-cancer drug combinations, along with their schedule, sequence, and dosage are a major challenge due to the large number of possible combinations in addition to the cost and time involved in experimentally testing each possible permutation. Mathematical models can aid in the discovery of optimal drug combinations. A mathematical model of the SHH and Cyclin D/ CDK / Rb pathways was designed to evaluate effective sequences and schedules of sonidegiband ribociclibfor the treatment of SHH medulloblastoma. The model was parameterized using in vitro data from studies treating the NIH3T3 cell line with sonidegiband ribociclibsingly or in combination. Flow cytometry analysis was used to quantify response to treatment by obtaining cell-cycle phase distributions for each drug as a single agent or in combination. Uncertainty and sensitivity analysis of the model parameters were evaluated via Latin Hypercube Samplingand Partial Rank Correlation Coefficient analysis to interpret the effects of amplification or deletion of nodes in the pathway, evaluate potential targetable nodes, and identify sensitive parameters that need robust quantification. Sensitivity analysis indicated that the formation of Cyclin D/CDK4/6 complexes and the dephosphorylation of Rb were significant nodes that should be included in the model. Uncertainty analysisindicated that the majority of the variability lies in the distribution of cells in G0/G1 and S phase. Simulations of single agent treatment predict a similar response between sonidegiband ribociclib, with co-treatment indicative of an additive effect. Optimal control theory methods are being applied to this model to help determine effective sequence, schedule, and dose of sonidegiband ribociclibto improve efficacy and reduce drug resistance in the treatment of SHH medulloblastoma. Citation Format: Zack Jones, Jessica Roberts, Haley Houke, Martine Roussel, Clinton Stewart, Carl Panetta. Evaluation of effective drug combinations of sonidegiband ribociclibfor treatment of Sonic hedgehog medulloblastomausing mathematical models of the cell cycle and Hedgehogpathways [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 314. doi:10.1158/1538-7445.AM2017-314