Influence of AML Differentiation State in Risk Stratification of Frontline Therapy with Hypomethylating Agents + Venetoclax in AML

• Published in: Blood 2024-11, Vol.144 (Supplement 1), p.62-62
• Main Authors: Lachowiez, Curtis A, Zeidner, Joshua F, Eckel, Ashley M., Peters, Daniel T, Fang, Jacob, Ashango, Amenech, Kaempf, Andy, Dai, Fangyan, Eide, Christopher A., Kurtz, Stephen E., Braun, Theodore P, Swords, Ronan T., Saultz, Jennifer N., Tyner, Jeffrey W., Pollyea, Daniel A
• Format: Article
• Language: English
• ISSN: 0006-4971; 1528-0020
• DOI: 10.1182/blood-2024-201532

Background: Acute myeloid leukemia (AML) with monocytic differentiation can be associated with resistance to hypomethylating agents plus venetoclax (HMA+VEN). Using a multi-modal analysis in newly diagnosed patients with AML treated with HMA+VEN, we assessed the influence of AML differentiation on clinical outcomes to determine modifying factors of this key variable. Methods: This retrospective included two cohorts. The Beat AML cohort (N=228) was used to comprehensively establish the influence of genetic mutations and AML differentiation state (using transcriptional phenotype scores based on RNA sequencing) with ex vivo VEN sensitivity (measured using the area under the curve [AUC] where increasing AUC values correspond with decreased drug response). An independent clinical cohort (N=144) was next utilized to clinically confirm associations identified within the Beat AML cohort and assess clinical endpoints, including response and overall survival (OS). The differentiation state for this cohort was assessed using unbiased clustering diagnostic flow cytometry data. Comparisons of categorical and continuous variables utilized the Chi-square or Fisher exact test and Wilcoxon rank-sum or Kruskal-Wallis test as appropriate. Time-to-event endpoints were evaluated utilizing the Kaplan-Meier method with Cox proportional hazards modeling for multivariable analysis (MVA). Allogeneic hematopoietic cell transplant (HCT) was included as a time-dependent covariate. Results In the Beat AML cohort (N=228), variability in VEN AUC was observed based on genetics and differentiation. IDH1 (median AUC: 111) and IDH2-mutated AML samples (median AUC: 120) had the lowest VEN AUC and were significantly lower compared with K/NRAS (median AUC: 194) or PTPN11-mutated samples (median AUC: 231). Increasing monocyte-like gene expression positively correlated with VEN AUC (R=0.72, p < 0.001), while progenitor-like gene expression negatively correlated with VEN AUC (R=-0.58, p < 0.001). In MVA inclusive of clinical factors, genetics, and myeloid cell differentiation state scores, IDH1/2 mutations correlated with increased VEN sensitivity (p: 0.019), while increased monocyte-like gene expression correlated with decreased response to VEN (p < 0.001) ex vivo. Incorporating AML differentiation (specifically, monocyte-like gene expression) in the MVA model of VEN AUC increased the adjusted R2 4-fold (0.54 vs. 0.13) compared to the selected model that considered only clinical and genetic varia