Venetoclax-based therapy can induce responses in approximately 70% of older previously untreated patients with acute myeloid leukemia (AML). However, up-front resistance as well as relapse following initial response demonstrates the need for a deeper understanding of resistance mechanisms. In the present study, we report that responses to venetoclax +azacitidine in patients with AML correlate closely with developmental stage, where phenotypically primitive AML is sensitive, but monocytic AML is more resistant. Mechanistically, resistant monocytic AML has a distinct transcriptomic profile, loses expression of venetoclax target BCL2, and relies on MCL1 to mediate oxidative phosphorylation and survival. This differential sensitivity drives a selective process in patients which favors the outgrowth of monocytic subpopulations at relapse. Based on these findings, we conclude that resistance to venetoclax + azacitidine can arise due to biological properties intrinsic to monocytic differentiation. We propose that optimal AML therapies should be designed so as to independently target AML subclones that may arise at differing stages of pathogenesis. SIGNIFICANCE: Identifying characteristics of patients who respond poorly to venetoclax-based therapy and devising alternative therapeutic strategies for such patients are important topics in AML. We show that venetoclax resistance can arise due to intrinsic molecular/metabolic properties of monocytic AML cells and that such properties can potentially be targeted with alternative strategies.
Acute myeloid leukemia stem cells (LSCs) are uniquely reliant on oxidative phosphorylation (OXPHOS) for survival. Moreover, maintenance of OXPHOS is dependent on BCL-2, creating a therapeutic opportunity to target LSCs using the BCL-2 inhibitor venetoclax. Although venetoclax-based regimens have shown promising clinical activity, the emergence of drug resistance is prevalent. Thus, in the present study, we investigated how mitochondrial properties may influence venetoclax responsiveness. Our data show that utilization of mitochondrial calcium is fundamentally different between drug-responsive and nonresponsive LSCs. By comparison, venetoclax-resistant LSCs demonstrate an active metabolic (i.e., OXPHOS) status with relatively high levels of calcium. Consequently, we tested genetic and pharmacological approaches to target the mitochondrial calcium uniporter. We demonstrate that inhibition of calcium uptake reduces OXPHOS and leads to eradication of venetoclax-resistant LSCs. These findings demonstrate a central role for calcium signaling in LSCs and provide an avenue for clinical management of venetoclax resistance. Significance: We identify increased utilization of mitochondrial calcium as a distinct metabolic requirement of venetoclax-resistant LSCs and demonstrate the potential of targeting mitochondrial calcium uptake as a therapeutic strategy.
<p>Supplementary Fig. 1: Immunophenotyping and WES analysis of primary AML specimens. Supplementary Fig. 2: Immunophenotyping of engrafted cells in PDX. Supplementary Fig. 3: WES analysis and remission duration of VEN/AZA relapsed AML patients. Supplementary Fig. 4: CITE-seq data analysis. Supplementary Fig. 5: Sorting strategies for determining m-LSC immunophenotype and expression of various LSC markers in m-LSCs. Supplementary Fig. 6: Molecular properties and targeting of m-LSCs in vitro and in vivo. Supplementary Fig. 7: M5 but not M4 patients showing significantly higher refractory rate to VEN/AZA therapy.</p>
Background The treatment of acute myeloid leukemia (AML) in older or unfit patients typically involves a regimen of venetoclax plus azacitidine (ven/aza). Toxicity and treatment responses are highly variable following treatment initiation and clinical decision-making continually evolves in response to these as treatment progresses. To improve clinical decision support (CDS) following treatment initiation, predictive models based on evolving and dynamic toxicities, disease responses, and other features should be developed. Objective This study aims to generate machine learning (ML)–based predictive models that incorporate individual predictors of overall survival (OS) for patients with AML, based on clinical events occurring after the initiation of ven/aza or 7+3 regimen. Methods Data from 221 patients with AML, who received either the ven/aza (n=101 patients) or 7+3 regimen (n=120 patients) as their initial induction therapy, were retrospectively analyzed. We performed stratified univariate and multivariate analyses to quantify the association between toxicities, hospital events, and short-term disease responses and OS for the 7+3 and ven/aza subgroups separately. We compared the estimates of confounders to assess potential effect modifications by treatment. 17 ML-based predictive models were developed. The optimal predictive models were selected based on their predictability and discriminability using cross-validation. Uncertainty in the estimation was assessed through bootstrapping. Results The cumulative incidence of posttreatment toxicities varies between the ven/aza and 7+3 regimen. A variety of laboratory features and clinical events during the first 30 days were differentially associated with OS for the two treatments. An initial transfer to intensive care unit (ICU) worsened OS for 7+3 patients (aHR 1.18, 95% CI 1.10-1.28), while ICU readmission adversely affected OS for those on ven/aza (aHR 1.24, 95% CI 1.12-1.37). At the initial follow-up, achieving a morphologic leukemia free state (MLFS) did not affect OS for ven/aza (aHR 0.99, 95% CI 0.94-1.05), but worsened OS following 7+3 (aHR 1.16, 95% CI 1.01-1.31) compared to that of complete remission (CR). Having blasts over 5% at the initial follow-up negatively impacted OS for both 7+3 (P<.001) and ven/aza (P<.001) treated patients. A best response of CR and CR with incomplete recovery (CRi) was superior to MLFS and refractory disease after ven/aza (P<.001), whereas for 7+3, CR was superior to CRi, MLFS, and refractory disease (P<.001), indicating unequal outcomes. Treatment-specific predictive models, trained on 120 7+3 and 101 ven/aza patients using over 114 features, achieved survival AUCs over 0.70. Conclusions Our findings indicate that toxicities, clinical events, and responses evolve differently in patients receiving ven/aza compared with that of 7+3 regimen. ML-based predictive models were shown to be a feasible strategy for CDS in both forms of AML treatment. If validated with larger and more diverse data sets, these findings could offer valuable insights for developing AML-CDS tools that leverage posttreatment clinical data.
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