ArticleNature communications2022
Integrated stem cell signature and cytomolecular risk determination in pediatric acute myeloid leukemia.
Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.
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Who cites it
38 citing papers in PubMed.
- Hematopoietic Stem Cell Transplantation Outcomes for High-Risk AML: A Report From the Children's Oncology Group.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2025Trial
- Imetelstat-mediated alterations in fatty acid metabolism to induce ferroptosis as a therapeutic strategy for acute myeloid leukemia.Nature cancer · 2024Trial
- A parallel-risk framework accurately predicts hematopoietic stem cell transplantation outcomes and identifies benefiting patients in pediatric AML.Genes & diseases · 2026Article
- Disrupting a Convergent Acetylation Circuit Collapses Leukemic Identity Across AML Subtypes.bioRxiv : the preprint server for biology · 2026Article
- Advancing child health: forecasting the next great research achievements.Pediatric research · 2026Article
- An international framework for clinical translation of molecular classifiers in osteosarcoma.NPJ precision oncology · 2026Article
- Pediatric acute myeloid leukemia tumor composition predicts patient outcomes at diagnosis and reveals mechanisms of resistance to chemotherapy.Research square · 2026Article
- Clonal Evolution of Pediatric Acute Myeloid Leukemia and Its Contribution to Disease Relapse.medRxiv : the preprint server for health sciences · 2025Article
- Longitudinal single-cell analysis reveals treatment-resistant stem and mast cells with potential treatments for pediatric AML.Leukemia · 2025Article
- How to drug a leukemic stem cell: deciphering heterogeneity for better specificity.Blood neoplasia · 2025Review
- Characterization of Chemoresistant Cell Populations Improves Risk Stratification and Therapy Prediction in Pediatric AML.bioRxiv : the preprint server for biology · 2025Article
- Image-based drug screening combined with molecular profiling identifies signatures and drivers of therapy resistance in pediatric AML.Cell reports. Medicine · 2025Article
- ST2/IL-33 axis blockade inhibits regulatory T cell cytotoxicity towards CD8 T cells in the leukemic niche.Nature communications · 2025Article
- Dual targeting of tumoral cells and immune microenvironment by blocking the IL-33/IL1RL1 pathway.Nature communications · 2025Article
- Perturbing LSD1 and WNT rewires transcription to synergistically induce AML differentiation.Nature · 2025Article
- Article
- Identification of a novel unfolded protein response related signature for predicting the prognosis of acute myeloid leukemia.Scientific reports · 2025Article
- Investigating the biology of microRNA links to ALDH1A1 reveals candidates for preclinical testing in acute myeloid leukemia.International journal of oncology · 2024Review
- A simplified and robust risk stratification model for stem cell transplantation in pediatric acute myeloid leukemia.Cell reports. Medicine · 2024Article
- Metabolic dependencies of acute myeloid leukemia stem cells.International journal of hematology · 2024Review
Corrections and comments
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Authors and funding
26 authors.
Funding
Abstract
Relapsed or refractory pediatric acute myeloid leukemia (AML) is associated with poor outcomes and relapse risk prediction approaches have not changed significantly in decades. To build a robust transcriptional risk prediction model for pediatric AML, we perform RNA-sequencing on 1503 primary diagnostic samples. While a 17 gene leukemia stem cell signature (LSC17) is predictive in our aggregated pediatric study population, LSC17 is no longer predictive within established cytogenetic and molecular (cytomolecular) risk groups. Therefore, we identify distinct LSC signatures on the basis of AML cytomolecular subtypes (LSC47) that were more predictive than LSC17. Based on these findings, we build a robust relapse prediction model within a training cohort and then validate it within independent cohorts. Here, we show that LSC47 increases the predictive power of conventional risk stratification and that applying biomarkers in a manner that is informed by cytomolecular profiling outperforms a uniform biomarker approach.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.