What question did this study set out to answer?

The research aims to understand how the differentiation state of cells and immune interactions affect drug responses in acute myeloid leukemia (AML).

April 5, 2026

Abstract 55: Differentiation state and immune interaction contribute to drug response in AML.

Puntos clave

The research aims to understand how the differentiation state of cells and immune interactions affect drug responses in acute myeloid leukemia (AML).
Profiled 90 AML patient samples using CyTOF to assess cell-surface protein expression.
Utilized matched drug response data from the BeatAML cohort.
Conducted drug treatment on five AML patient samples using CITE-seq across various treatment combinations.
Applied topic modeling with the LDA model to identify relationships among immune and differentiation markers.
Trained single-cell drug response prediction methods on sc-RNA-seq data.
Confirmed existing biomarkers for BCL2 inhibitor venetoclax and menin inhibitor revumenib.
Observed shifts in gene expression and cell populations with treatments, especially combinations with azacytidine.
Noted depletion of primitive and pro-monocyte populations following treatment combinations.
Identified five distinct topics in immune signatures relating to drug efficacy in AML.

Resumen

Abstract Introduction: We and others have linked efficacy of targeted therapies to cellular differentiation state in acute myeloid leukemia (AML). In this study, we refine this link by integrating ex vivo drug response, joint single-cell transcriptomic and proteomic, and cell-surface proteomics data that measures both myeloid differentiation and immune markers. Methods: A total of 90 AML patient samples were profiled by CyTOF (cytometry by time-of flight) with ∼100 immune and myeloid differentiation makers to characterize the landscape of cell-surface protein expression. Matched drug response data was used from the largest assembled AML patient cohort BeatAML. Concurrently, five AML patient samples were profiled following ex vivo drug treatment using CITE-seq (cellular indexing of transcriptomes and epitopes by sequencing) with a total of 6 treatments (3 single agent, 2 pairwise and 1 triple combination treatment) and compared to DMSO treated cells. Custom computational pipelines were developed to enable data analysis. Topic modeling using the latent Dirichlet allocation (LDA) model was used to identify topics emerging in the space of both myeloid differentiation and immune markers. Topics were then stratified by matched drug response. Single-cell drug response prediction methods were trained on sc-RNA-seq to identify cell type-specific drug response signatures. Results: Our results recapitulate known biomarkers of response to single agents BCL2 inhibitor venetoclax (ven) and menin inhibitor revumenib. Further, we observe known and novel gene expression and cell population shifts when combined with hypomethylating azacytidine. For example, venetoclax eliminates primitive and B-cell populations. When ven is used in combination with revumenib, intermediate populations such as pro-monocytes mature into monocytes, yielding predominantly differentiated cells. Adding azacytidine to ven+revumenib further depletes intermediate populations, including pro-monocytes. Our topic modeling identified 5 (out of 10) topics that have a stark opposing pattern in drugs targeting primitive vs differentiated cells. We further identified the most prominent immune markers associated with each of these topics. Conclusion: Our results recapitulate previously established links between myeloid differentiation state and selective efficacy to targeted compounds in AML. Notably, our recent findings informed by topics compromised of immune signatures further deconvolute these trends, pointing to new immune programs associated with cell state driven drug response. Citation Format: Natasha R. Black, Trevor Enright, Mira Rajagopalan, Melissa Stewart, Evan Lind, Elie A. Traer, Jeffrey W. Tyner, Olga H. Nikolova. Differentiation state and immune interaction contribute to drug response in AML abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 55.

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