Using Structure-Based Modeling to Identify Effective Drug Combinations in RAS-Mutant Acute Myeloid Leukemia

Introduction Mutations activating RAS signaling, typically in NRAS or KRAS, are common in acute myeloid leukemia (AML). These alterations hyperactivate downstream RAF/MEK/ERK kinases and are typically associated with poor outcome, especially in children. We recently developed a structure-based dynamic RAS pathway model that successfully predicted RAF inhibitor combinations which synergistically reduced downstream signaling and effectively killed RAS- and RAF-mutant solid tumor models. This approach leverages RAF dimer asymmetry and the affinity of different inhibitor types (Type 1/1.5/2) for alternative conformations of RAF monomers upon dimerization. Here, we apply our computational modeling approach to RAS-mutant AML in vitro and in preclinical in vivo models to assess novel RAF inhibitor combinations as potential treatments for this high-risk patient group. Methods Phospho-proteomics and drug response data for RAS-mutant cell lines (3 NRAS-mut, 2 KRAS-mut) were incorporated into our established rule-based RAS signaling model. Combination synergy was determined using the Loewe Additivity model (>10 = synergy). To generate AML patient-derived xenografts (PDXs), patient samples were injected into NSGS mice via the lateral tail vein. Engraftment was assessed by flow cytometry to measure human CD45+ cells in peripheral blood (PB). For efficacy studies, treatment began when mice reached a median of > 1% huCD45+ cells in PB. Mice were then treated with vehicle, lifirafenib (LIF; 10 mg/kg, p.o.), encorafenib (ENCO; 20 mg/kg, p.o.), SB590885 (SB; 25 mg/kg, IP), or either drug combination (LIF + ENCO or LIF + SB). The study concluded when mice reached event (>25% huCD45+ cells in PB). Results Phospho-proteomic profiling and in silico modeling predicted two RAF inhibitor combinations as being most synergistic against RAS-mutant AML; i) Type 1/2, and ii) Type 1.5/2. Combined LIF (Type 2) + ENCO (Type 1.5) was highly synergistic against all cell lines (Loewe additivity scores 7.9-31.1), while synergy observed for LIF + SB (Type 1) was specific to NRAS-mutant lines (Loewe additivity scores 21.4-27.9). Immunoblotting confirmed that combination efficacy correlated strongly with measured RAS pathway activation. For instance, in one NRAS-mutant cell line LIF + ENCO treatment led to a 2.9-fold decrease in phosphorylated ERK (pERK) compared with vehicle control, while single agent LIF and ENCO caused a 1.5-fold and 1.3-fold increase in pERK respectively. Combined LIF + SB led to a 14-fold reduction in pERK compared with vehicle control, while single agent SB caused a 1.5-fold reduction. To further validate these combinations in a pre-clinical model, we established a PDX from a pediatric AML harboring an activating NRAS G12A mutation and a KMT2A-MLLT4 fusion. Combined LIF + ENCO achieved a leukemia growth delay (LGD) of 6.83 days compared with vehicle control, which was significantly greater than either LIF (LGD = 4.39 days) or ENCO (LGD = -0.25 days). Notably, 2/6 combination-treated mice had leukemia regression, which was not observed in either single-agent group. Combined LIF + SB achieved a LGD of 8.91 days compared with vehicle control, which was significantly greater than LIF (LGD = 4.39 days) but was not significant compared with single agent SB (LGD = 8.71). Representative mice were harvested on Day 10 of treatment to assess leukemia burden in the spleen and bone marrow (BM). While there were no significant differences in the percentage of huCD45+ cells in the BM or spleen between cohorts for either combination, gross spleen weight was significantly reduced in both combination groups compared with respective single agent and vehicle control groups. Most strikingly, median spleen weight for LIF + SB treated mice (80 mg) was markedly lower than single agent LIF (median = 237 mg), SB (median = 519 mg) and vehicle control (median = 361 mg) groups. Immunoblotting confirmed that decreased spleen weight in combination-treated mice correlated with reduced RAS pathway activation as compared with single agent and vehicle groups. Conclusions We used a structural biology and in silico computational modelling approach to identify novel, non-obvious kinase inhibitor combinations. Computational approaches were notably validated by the high efficacy of well-tolerated treatments in a pre-clinical mouse model, suggesting potential translatability for treating RAS-mutant AML.