A structure-based modeling approach identifies effective drug combinations for RAS-mutant acute myeloid leukemia.

Mutations activating RAS/RAF/MEK/ERK signaling confer poor outcomes in acute myeloid leukemia (AML), but targeting this pathway is challenging. We used a structure-based, dynamic RAS pathway model to predict RAF inhibitor (RAFi) combinations that synergistically suppress RAS-mutant AML. In silico models predicted synergy for two iterations of conformation-specific RAFi's which were validated in vitro. Lifirafenib (type II) + encorafenib (type I½) was highly synergistic against NRAS- and KRAS-mutant AML cells, while lifirafenib + SB590885 (type I) synergy was NRAS-mutant-specific. Combination efficacy correlated with measured RAS pathway activity. Leveraging in silico pharmacokinetic predictions, we tested RAFi combinations in an NRAS-mutant AML patient-derived xenograft, finding improved leukemia growth delay and survival compared with single agents. Both combinations showed site-specific efficacy against circulating and spleen-resident blasts. In summary, our integrated modeling approach effectively identified non-obvious RAFi combinations that are effective in vitro and in vivo, thereby suggesting alternative therapeutic strategies for RAS-mutant AML.