Resolving inter- and intra-patient heterogeneity in NPM1-mutated AML at single-cell resolution

Journal Article (2025)
Author(s)

E.O. Karakaslar (Leiden University Medical Center, TU Delft - Pattern Recognition and Bioinformatics)

Eva M. Argiro (Leiden University Medical Center)

Nadine E. Struckman (Leiden University Medical Center)

R. Shirali Hossein Zade (Leiden University Medical Center, TU Delft - Pattern Recognition and Bioinformatics)

J.F. Severens (Leiden University Medical Center, TU Delft - Pattern Recognition and Bioinformatics)

M. Willy Honders (Leiden University Medical Center)

M.J.T. Reinders (Leiden University Medical Center, TU Delft - Pattern Recognition and Bioinformatics)

Marieke Griffioen (Leiden University Medical Center)

Erik Ben van den Akker (Leiden University Medical Center, TU Delft - Pattern Recognition and Bioinformatics)

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Research Group
Pattern Recognition and Bioinformatics
DOI related publication
https://doi.org/10.1038/s41375-025-02745-w
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Publication Year
2025
Language
English
Research Group
Pattern Recognition and Bioinformatics
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository as part of the Taverne amendment. More information about this copyright law amendment can be found at https://www.openaccess.nl. Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.@en
Issue number
12
Volume number
39
Pages (from-to)
2916-2925
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Abstract

NPM1-mutated AML is one of the largest entities in international classification systems of myeloid neoplasms, which are based on integrating morphologic and clinical data with genomic data. Previous research, however, indicates that bulk transcriptomics-based subtyping may improve prognostication and therapy guidance. Here, we characterized the heterogeneity in NPM1-mutated AML by performing single-cell RNA-sequencing and spectral flow cytometry on 16 AML belonging to three distinct subtypes previously identified by bulk transcriptomics. Using single-cell expression profiling we generated a comprehensive atlas of NPM1-mutated AML, collectively reconstituting complete myelopoiesis. The three NPM1-mutated transcriptional subtypes showed consistent differences in the proportions of myeloid cell clusters with distinct patterns in lineage commitment and maturational arrest. In all samples, leukemic cells were detected across different myeloid cell clusters, indicating that NPM1-mutated AML are heavily skewed but not fully arrested in myelopoiesis. Same-sample multi-color spectral flow cytometry recapitulated these skewing patterns, indicating that the three NPM1-mutated subtypes can be consistently identified across platforms. Moreover, our analyses highlighted differences in the abundance of rare hematopoietic stem cells suggesting that skewing occurs early in myelopoiesis. To conclude, by harnessing single-cell RNA-sequencing and spectral flow cytometry, we provide a detailed description of three distinct and reproducible patterns in lineage skewing in NPM1-mutated AML that may have potential relevance for prognosis and treatment of patients with NPM1-mutated AML. (Figure presented.)

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