Clinical Correlates of Venetoclax-Based Combination Sensitivities to Augment Acute Myeloid Leukemia Therapy

Abstract

The BCL2 inhibitor venetoclax combined with the hypomethylating agent azacytidine shows significant clinical benefit in a subset of patients with acute myeloid leukemia (AML); however, resistance limits response and durability. We prospectively profiled the ex vivo activity of 25 venetoclax-inclusive combinations on primary AML patient samples to identify those with improved potency and synergy compared with venetoclax + azacytidine (Ven + azacytidine). Combination sensitivities correlated with tumor cell state to discern three patterns: primitive selectivity resembling Ven + azacytidine, monocytic selectivity, and broad efficacy independent of cell state. Incorporation of immunophenotype, mutation, and cytogenetic features further stratified combination sensitivity for distinct patient subtypes. We dissect the biology underlying the broad, cell state-independent efficacy for the combination of venetoclax plus the JAK1/2 inhibitor ruxolitinib. Together, these findings support opportunities for expanding the impact of venetoclax-based drug combinations in AML by leveraging clinical and molecular biomarkers associated with ex vivo responses.

Significance: By mapping drug sensitivity data to clinical features and tumor cell state, we identify novel venetoclax combinations targeting patient subtypes who lack sensitivity to Ven + azacytidine. This provides a framework for a taxonomy of AML informed by readily available sets of clinical and genetic features obtained as part of standard care. See related commentary by Becker, p. 437 . This article is featured in Selected Articles from This Issue, p. 419.

Figure 1.

Ex vivo drug-sensitivity recapitulates clinical experience with Ven + azacytidine in AML. A,Ex vivo sensitivities for venetoclax (Ven), azacytidine and Ven + azacytidine on matched AML primary samples (n = 142). Sensitivity is represented as % of the maximum (max) area-under-the-dose response curve (AUC) derived for a 7-point concentration series ranging from 10 μmol/L to 10 nmol/L. B, Distribution of combination ratio (CR) values for patient samples treated with Ven + azacytidine ex vivo. CR is defined as the AUC of the combination divided by the AUC of the most potent single agent, where AUC CR <1 denotes the enhanced efficacy of the combination. C, Differences in Ven + azacytidine ex vivo sensitivity among patient samples with respect to expression of select immunophenotypic markers of primitive (CD117) and monocytic tumor cells (CD14). Neg, negative; Pos, positive. D, Differences in ex vivo sensitivity of Ven + azacytidine among patient samples based on the presence of prognostically relevant mutations in IDH1, NPM1, and either NRAS or KRAS. WT, wild-type. E, For 10 newly diagnosed patients with AML with both ex vivo screening and subsequent clinical treatment with Ven + azacytidine, ex vivo sensitivity collected at baseline prior to treatment is compared based on subsequent clinical response achieved on treatment. P values shown were determined using Mann–Whitney tests.

Figure 2.

Novel partners with venetoclax augment the sensitivity of Ven + azacytidine. A, Comparisons of overall ex vivo potency (as measured by median AUC) and enhanced efficacy [median AUC combination ratio (CR)] for venetoclax (Ven) combined with azacytidine and 30 novel drug partners among primary AML patient specimens. Numbers of evaluable samples and fractions exhibiting the highest single-agent (HSA) synergy for each combination are shown as point size and color, respectively. Note that absolute numbers of samples tested with a particular combination vary as they were added to drug panels over time. Ven + azacytidine is highlighted in red for reference comparison purposes. B, Heat map of matched ex vivo sensitivity data [AUC % of maximum (max)] for 95 AML patient samples tested with Ven + azacytidine, a subset of novel Ven combinations, and their respective single agents. C–E, Comparisons of Ven combination sensitivities with respect to AML type (C), ELN 2017 risk (D), and peripheral blood (PB) monocyte percentage from differential blood counts obtained at the time of sample collection (E). For categorical variables (de novo/secondary diagnosis and ELN 2017 risk) are compared by Mann–Whitney test; points indicate the difference of median AUC and bars indicate the 95% confidence interval around this estimate. Negative and positive differences in median values reflect greater sensitivity and resistance, respectively, in patient samples with secondary AML or adverse risk. Percent monocytes are correlated with combination AUC by Spearman rank test, where negative and positive Spearman r values denote correlation with sensitivity and resistance, respectively. Blue and orange coloring represent statistically significant associations with sensitivity and resistance, respectively; gray color indicates the comparison was not statistically significant. Secondary AML denotes instances in which a patient's AML transformed from one of multiple disease states.

Figure 3.

Varying venetoclax partner drugs alters associations of sensitivity with AML tumor cell state. A, Concordance of drug-sensitivity cell state Pearson correlations for training and test sample cohorts. Colors indicate significant P values [after adjustment for family-wise error rate (FWER)] for both cohorts (purple), training set only (green), and test set only (orange). B, Clustered heat map of Pearson correlation r values for venetoclax (Ven) combination sensitivities (left) and respective single-agent sensitivities (not clustered, right) with respect to tumor cell state gene-expression signatures. Negative (blue) and positive (orange) correlation values correspond to sensitivity and resistance, respectively. C, Sensitivity of Ven + azacytidine and selected Ven combinations with respect to individual patient sample cell state. Dots represent individual patient specimens across the cell state spectrum defined by monocyte-like versus progenitor-like expression scores. Ex vivo drug sensitivity (AUC) is denoted in the color scale hue of each dot. Max, maximum.

Figure 4.

Clinical and genetic features map to associations with combination sensitivity. A, Ridge density plots of venetoclax (Ven) combination sensitivity differences with respect to indicated gene mutations. Color gradients indicate AUC-based ex vivo sensitivity (dark blue/purple) through resistance (orange/yellow). Max, maximum. B and C, Volcano plots showing a comparison of Ven combination sensitivity differences with respect to recurrent cytogenetic rearrangements (B) and immunophenotype surface markers (C). Negative and positive tails of each plot correspond to significantly increased (blue) and decreased sensitivity (orange), respectively, in samples positive for the tested feature. Size of each point represents the number of samples in the comparison that were positive for the tested feature for the given combination. The difference in median AUC was computed by the Hodges–Lehmann; P values were determined by Mann–Whitney tests and corrected for false discovery using the Benjamini–Hochberg method. D, Clustered heat map of multivariate ridge regression coefficient estimates for clinical and genetic feature associations with ex vivo combination sensitivity among newly diagnosed AML patient specimens. Blue and orange shading corresponds to associations of the indicated feature with sensitivity and resistance, respectively, for the corresponding combination. Feature panels and combinations included reflect limitations involving sample numbers and model requirements for minimizing missing data for analysis. E, Bivariate subgroup stratification of ex vivo sensitivity for select Ven combinations for indicated features. Combination AUC was compared across subgroups by the Kruskal–Wallis test; post-hoc pairwise Mann–Whitney tests were performed, with FWER-adjusted P values shown. Abbreviations: mut, mutated; wt, wild-type.

Figure 5.

Patterns of sensitivity and resistance for the type 3 combination Ven + ruxolitinib. A, Patient-derived xenograft evaluation of Ven + ruxolitinib in vivo. Mononuclear cells from a newly diagnosed AML patient were injected into NSGS mice, allowed to engraft to ∼1% human CD33 chimerism, and cohorts (n = 4/group) were treated with venetoclax (Ven; 50 mg/kg), ruxolitinib (30 mg/kg), or Ven + ruxolitinib (30/50 mg/kg) daily for 3 weeks. Animals were sacrificed and splenic disease burdens were compared using one-way ANOVA. *, P < 0.05; **, P < 0.01. B, Volcano plot of differential gene expression (DE) by RNA-seq in OCI-AML2 cells following treatment with Ven alone or in combination with ruxolitinib in triplicate for 24 hours. Genes highlighted in blue and orange indicate those with significantly decreased and increased expression, respectively, in cells treated with the combination compared with single-agent Ven. C, Predicted protein interaction network between drug targets of the combination (highlighted in red) and genes downregulated upon Ven + ruxolitinib treatment compared with Ven alone in OCI-AML2 cells. D, Principal component analysis of CRISPR/Cas9 screen sequencing data obtained from YUSA library-transduced OCI-AML2 cells at days 7, 14, and 21 after treatment with DMSO, Ven, or Ven + ruxolitinib. Clusters representing Ven-treated and Ven + ruxolitinib–treated cells are highlighted in purple and blue, respectively. Duplicate samples were evaluated for each condition. E, Volcano plot of changes in sgRNA expression (log₂ fold change) for Ven-treated cells relative to DMSO control cells at day 21. Select genes highlighted in blue in the left tail showed unique sgRNA-sensitizing effects for Ven treatment but not Ven + ruxolitinib. F, Volcano plot of changes in sgRNA expression (log₂ fold change) for Ven + ruxolitinib-treated cells relative to DMSO control cells at day 21. Select genes highlighted in orange in the right tail showed sgRNA enrichment consistent with unique resistance to Ven + ruxolitinibruxolitinib treatment but not Ven alone. On both CRISPR volcano plots (C–D), sgRNAs for select genes previously identified in Ven resistance CRISPR screens (BAX, PMAIP1, and TP53) are highlighted in red in each plot's resistant (positive) tail. Select unique Ven-sensitizing gene hits (G) and Ven + ruxolitinib resistance gene hits (H) are listed.

Figure 6.

Validation of CRISPR screen hits for resistance to the Ven + ruxolitinib combination. A, Immunoblot analysis of OCI-AML2 cells transduced with two independent guide RNAs for genes identified in the Ven + ruxoltinib CRISPR/Cas9 resistance screen. Cells were lysed, subjected to SDS-PAGE, transferred to PVDF membranes, and probed for levels of MED13L, MDM2, and MEIS2; vinculin was used as a protein loading control. Parental denotes untransduced OCI-AML2 cells; NT, nontargeting control guide. B, TIDE sequencing comparisons of genomic loci for MED13L, MDM2, and MEIS2 relative to parental OCI-AML2 controls following transduction and CRISPR modification. C, Dose-response curves for OCI-AML2 cells transduced as in B with two independent guide RNAs for MED13L, MDM2, and MEIS2 and tested for sensitivity to Ven, ruxolitinib, and Ven + ruxolitinib. Data points represent the mean normalized cell viability ± SEM for three replicates. Parental denotes untransduced OCI-AML2 cells; NT, nontargeting control guide. D, Immunoblot analysis of indicated proteins in OCI-AML2 parental and CRISPR knockout (KO) lines for MED13L, MDM2, or MEIS2. The vertical line denotes the cropping of nonadjacent lanes to juxtapose samples for ease of comparison. E, Quantification by densitometry of protein levels detected by immunoblot analysis in D. Band intensities were first blanked and normalized to loading control vinculin levels within lanes, then normalized to levels in parental OCI-AML2 cells and shown as fold change in expression.

Figure 7.

Prioritizing venetoclax-based combination therapy for AML. A, Categories of venetoclax-inclusive combination selectivity from this study. Select combination partner drugs representing FDA-approved agents and their canonical targets are shown. Complete annotations for all tested combinations in this study, along with their type 1, 2, and 3 designations, are provided in Supplementary Table S1. B, Decision scheme for optimizing therapeutic application of Ven + azacytidine and other venetoclax-combination strategies based on standard clinical immunophenotype/differentiation state and mutation features. Ex vivo combination sensitivity data were expressed as z-scores relative to the mean AUC value for each combination to account for differences in overall potency. Scaled sensitivity data were grouped by combination type and then further aligned based on the presence of the indicated clinical immunophenotype and genomic features to optimize patient sample subgroup activity. Given Ven + azacytidine is the standard of care for patients who are ineligible for 7 + 3 chemotherapy, it may be that alternate type combinations or partner drugs added to a backbone of Ven + azacytidine as a triplet may offer improved responses.