Characterization of chemoresistant cell populations improves risk stratification and therapy prediction in pediatric acute myeloid leukemia
Year: 2026
Type: article
Study design: Observational Study
Abstract: Most pediatric acute myeloid leukemia (pAML) patients achieve complete remission after chemotherapy, yet nearly 40% ultimately relapse and die from their disease. High risk cases are typically referred for stem cell transplantation (SCT) in first remission, but because SCT is associated with substantial toxicity and cures after relapse are rare, accurate risk prediction is critical. Here, we show that combining the detection of chemoresistant cell populations, inferred from single-cell transcriptomic profiles of paired diagnosis–relapse samples, and cytogenetic biomarkers at diagnosis with measurable residual disease after induction chemotherapy, substantially improves risk prediction. This approach identifies a patient subgroup comprising 20% of the patients who do not undergo SCT, with a 5-year event-free survival below 40%, and accounting for nearly half of all deaths in this population. Molecular characterization of these cell populations reveals therapeutic vulnerabilities and potential targeted treatment strategies for high-risk pAML, providing a framework for precision oncology diagnosis and intervention. Early risk prediction is essential to decide the treatment procedure for pediatric acute myeloid leukemia. Here, the authors show that rare chemoresistant cell populations, detectable at diagnosis, improve risk stratification and reveal potential targets for more effective, personalized therapies.
Source: Nature Communications
Authors: Mohammad Javad NajafPanah, Alexandra M. Stevens, Michael J. Krueger, Max Rochette, Sohani Sandhu, Lana Kim, Hua-Sheng Chiu, Jessica Epps, Sonal Somvanshi, Barry Zorman, Maria Rodriguez Martinez, Marianna Rapsomaniki, Susanne Unger, Burkhard Becher, Joanna S. Yi, Tsz-Kwong Man, Michele S. Redell, Pavel Sumazin
Language: English
Subfield: Hematology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $6,990
Funders: CURE Childhood Cancer, Cancer Prevention and Research Institute of Texas, Leukemia and Lymphoma Society, Texas Children's Hospital, Children’s Oncology Group, European Commission, National Institutes of Health, National Eye Institute, National Cancer Institute, Center for Information Technology
Awards: G1158621185, Comprehensive Cancer Epigenomics Core Facility, G1466887737, G1504112592, G1788796038, Clonal evolution and chemoresistance of Hepatoblastomas with hepatocellular carcinoma features, G2408992657, Diagnostic biomarkers for hepatoblastomas with hepatocellular carcinoma features, G3124189783, G3343343458, G3574825479, G3956826231, G4065300843, G418187648, G421865639, Children's Oncology Group Statistics and Data Center, Patient-derived Xenograft and Advanced In Vivo Models (PDX-AIM) Core Facility of Texas, individualizedPaediatricCure: Cloud-based virtual-patient models for precision paediatric oncology, G5465708471, P30 - Core Grant for Vision Research, G5628162970, G5750893613, G6239702407, Advanced Multiparameter Cytometry and Cell Sorting Core, G699606022, G7022586960, Predictive Biomarkers and Novel Therapies for High-Risk Pediatric Liver Cancers, G7326920056, G7514240623, Advanced Multiparameter Cytometry and Cell Sorting Core, G7804230802, G7837447426, G8153776008, Patient-Derived Xenograft and Advanced in Vivo Models (PDX-AIM) Core Facility, G8594780166, G9000035374, G9000036102, G9000065690, G9000102191, G9000115110, G9000198215, G9000240210, G9000849526, Baylor College of Medicine Cancer Center - Cancer Center Support Grant, COG Biospecimen Bank to Support NCI NCTN (U24), BD FACSDiscover S8 Spectral and Imaging Cell Sorter, G931214414, G960470524
OpenAlex ID: W7215808798
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