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Heterogeneity in refractory acute myeloid leukemia

  1. Author:
    Horibata, Sachi
    Gui, Gege
    Lack,Justin
    DeStefano, Christin B
    Gottesman, Michael M [ORCID]
    Hourigan, Christopher S
  2. Author Address

    Laboratory of Cell Biology, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892; sachi.horibata@nih.gov mgottesman@nih.gov hourigan@nih.gov., Laboratory of Myeloid Malignancies, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20814., NIAID Collaborative Bioinformatics Resource, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892., Advanced Biomedical Computational Science, Frederick National Laboratory for Cancer Research sponsored by the National Cancer Institute, Frederick, MD 21702., Department of Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD 20814., Laboratory of Myeloid Malignancies, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20814; sachi.horibata@nih.gov mgottesman@nih.gov hourigan@nih.gov.,
    1. Year: 2019
    2. Date: MAY 21
    3. Epub Date: 2019 05 07
  1. Journal: Proceedings of the National Academy of Sciences of the United States of America
    1. 116
    2. 21
    3. Pages: 10494-10503
  2. Type of Article: Article
  3. ISSN: 0027-8424
  1. Abstract:

    Successful clinical remission to therapy for acute myeloid leukemia (AML) is required for long-term survival to be achieved. Despite trends in improved survival due to better supportive care, up to 40% of patients will have refractory disease, which has a poorly understood biology and carries a dismal prognosis. The development of effective treatment strategies has been hindered by a general lack of knowledge about mechanisms of chemotherapy resistance. Here, through transcriptomic analysis of 154 cases of treatment-naive AML, three chemorefractory patient groups with distinct expression profiles are identified. A classifier, four key refractory gene signatures (RG4), trained based on the expression profile of the highest risk refractory patients, validated in an independent cohort (n = 131), was prognostic for overall survival (OS) and refined an established 17-gene stemness score. Refractory subpopulations have differential expression in pathways involved in cell cycle, transcription, translation, metabolism, and/or stem cell properties. Ex vivo drug sensitivity to 122 small-molecule inhibitors revealed effective group-specific targeting of pathways among these three refractory groups. Gene expression profiling by RNA sequencing had a suboptimal ability to correctly predict those individuals resistant to conventional cytotoxic induction therapy, but could risk-stratify for OS and identify subjects most likely to have superior responses to a specific alternative therapy. Such personalized therapy may be studied prospectively in clinical trials.

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External Sources

  1. DOI: 10.1073/pnas.1902375116
  2. PMID: 31064876
  3. WOS: 000468403400052
  4. PII : 1902375116

Library Notes

  1. Fiscal Year: FY2018-2019
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