ArticleNPJ precision oncology2024
Integrated drug resistance and leukemic stemness gene-expression scores predict outcomes in large cohort of over 3500 AML patients from 10 trials.
Article in NPJ precision oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT00136084 (A Collaborative Trial for the Treatment of Patients With Newly Diagnosed Acute Myeloid Leukemia or Myelodysplasia), which is not on this map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
A Collaborative Trial for the Treatment of Patients With Newly Diagnosed Acute Myeloid Leukemia or Myelodysplasia
Who cites it
3 citing papers in PubMed.
- How to drug a leukemic stem cell: deciphering heterogeneity for better specificity.Blood neoplasia · 2025Review
- Epigenomic diagnosis and prognosis of Acute Myeloid Leukemia.Nature communications · 2025Article
- The joint role of the immune microenvironment and NFrontiers in genetics · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
21 authors.
Funding
Abstract
In this study, we leveraged machine-learning tools by evaluating expression of genes of pharmacological relevance to standard-AML chemotherapy (ara-C/daunorubicin/etoposide) in a discovery-cohort of pediatric AML patients (N = 163; NCT00136084 ) and defined a 5-gene-drug resistance score (ADE-RS5) that was predictive of outcome (high MRD1 positivity p = 0.013; lower EFS p < 0.0001 and OS p < 0.0001). ADE-RS5 was integrated with a previously defined leukemic-stemness signature (pLSC6) to classify patients into four groups. ADE-RS5, pLSC6 and integrated-score was evaluated for association with outcome in one of the largest assembly of ~3600 AML patients from 10 independent cohorts (1861 pediatric and 1773 adult AML). Patients with high ADE-RS5 had poor outcome in validation cohorts and the previously reported pLSC6 maintained strong significant association in all validation cohorts. For pLSC6/ADE-RS5-integrated-score analysis, using Group-1 (low-scores for ADE-RS5 and pLSC6) as reference, Group-4 (high-scores for ADE-RS5 and pLSC6) showed worst outcome (EFS: p < 0.0001 and OS: p < 0.0001). Groups-2/3 (one high and one low-score) showed intermediate outcome (p < 0.001). Integrated score groups remained an independent predictor of outcome in multivariable-analysis after adjusting for established prognostic factors (EFS: Group 2 vs. 1, HR = 4.68, p < 0.001, Group 3 vs. 1, HR = 3.22, p = 0.01, and Group 4 vs. 1, HR = 7.26, p < 0.001). These results highlight the significant prognostic value of transcriptomics-based scores capturing disease aggressiveness through pLSC6 and drug resistance via ADE-RS5. The pLSC6 stemness score is a significant predictor of outcome and associates with high-risk group features, the ADE-RS5 drug resistance score adds further value, reflecting the clinical utility of simultaneous testing of both for optimizing treatment strategies.
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Registered trials
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