Characterization of chemoresistant cell populations improves risk stratification and therapy prediction in pediatric acute myeloid leukemia
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.
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BibTeX
@article{najafpanah2026characterization,
title = {{Characterization of chemoresistant cell populations improves risk stratification and therapy prediction in pediatric acute myeloid leukemia}},
author = {Mohammad Javad NajafPanah and Alexandra M. Stevens and Michael J. Krueger and Max Rochette and Sohani Sandhu and Lana Kim and Hua-Sheng Chiu and Jessica Epps and Sonal Somvanshi and Barry Zorman and Maria Rodriguez Martinez and Marianna Rapsomaniki and Susanne Unger and Burkhard Becher and Joanna S. Yi and Tsz-Kwong Man and Michele S. Redell and Pavel Sumazin},
journal = {Nature Communications},
year = {2026},
month = oct,
doi = {10.1038/s41467-026-78283-5},
url = {https://www.nature.com/articles/s41467-026-78283-5},
note = {CC BY-NC-ND 4.0},
}
RIS
TY - JOUR
TI - Characterization of chemoresistant cell populations improves risk stratification and therapy prediction in pediatric acute myeloid leukemia
AU - Mohammad Javad NajafPanah
AU - Alexandra M. Stevens
AU - Michael J. Krueger
AU - Max Rochette
AU - Sohani Sandhu
AU - Lana Kim
AU - Hua-Sheng Chiu
AU - Jessica Epps
AU - Sonal Somvanshi
AU - Barry Zorman
AU - Maria Rodriguez Martinez
AU - Marianna Rapsomaniki
AU - Susanne Unger
AU - Burkhard Becher
AU - Joanna S. Yi
AU - Tsz-Kwong Man
AU - Michele S. Redell
AU - Pavel Sumazin
PY - 2026
DA - 2026/10/02
JO - Nature Communications
DO - 10.1038/s41467-026-78283-5
UR - https://www.nature.com/articles/s41467-026-78283-5
AB - 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.
SN - 2041-1723
ER -