ArticleCell reports. Medicine2025
Image-based drug screening combined with molecular profiling identifies signatures and drivers of therapy resistance in pediatric AML.
Article in Cell reports. Medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Clinical profiling of AML1::ETO and KIT exon 17 mutation in pediatric AML by high-throughput drug sensitivity.BMC cancer · 2026Article
- Pediatric leukemia: origins, pathogenesis, the role of microenvironment and immunological modulation.Frontiers in immunology · 2026Review
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Authors and funding
14 authors.
Funding
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Abstract
Despite recent advances in the understanding of the genomic landscape of pediatric acute myeloid leukemia (pedAML), targeted treatments are only available for selected genomic alterations, and the functional link between genotype and outcome remains partially elusive. Functional precision medicine approaches to investigate treatment resistance and patient risk have not been applied systematically for pedAML. Here, we describe an advanced functional screening platform combining high-content imaging and deep learning-based phenotyping. In 45 patients with pedAML, we identify BCL2 and FLT3 inhibitors and standard chemotherapy as major drivers of the chemosensitivity landscape, reveal substantial differential sensitivities between risk groups, and may effectively predict individual measurable residual disease and patient risk. Integration with genomic and epigenomic data uncovers a chemotherapy-resistant primitive state vulnerable to combined BCL2 and MDM2 inhibition and HDAC inhibition. Overall, we identify early signatures of therapy resistance across genetic subgroups and prioritize targeted treatments for these functionally and epigenetically defined patient subsets.
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