Detection of chemotherapy-resistant patient-derived acute lymphoblastic leukemia clones in murine xenografts using cellular barcodes

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Abstract

Clonal heterogeneity fuels leukemia evolution, therapeutic resistance, and relapse. Upfront detection of therapy-res istant leukemia clones at diagnosis may allow adaptation of treatment and prevention of relapse, but this is hampered by a paucity of methods to identify and trace single leukemia-propagating cells and their clonal offspring. Here, we tested methods of cellular barcoding analysis, to trace the in vivo competitive dynamics of hundreds of patient-derived leukemia clones upon chemotherapy-mediated selective pressure. We transplanted Nod/Scid/Il2Rg(-/-) (NSG) mice with barcoded patient-derived or SupB15 acute lymphoblastic leukemia (ALL) cells and assessed clonal responses to dexamethasone, methotrexate, and vincristine, longitudinally and across nine anatomic locations. We illustrate that chemotherapy reduces clonal diversity in a drug-dependent manner. At end-stage disease, methotrexate-treated patientderived xenografts had significantly fewer clones compared with placebo-treated mice (100 +/- 10 vs. 160 +/- 15 clones, p = 0.0005), while clonal complexity in vincristineand dexamethasone-treated xenografts was unaffected (115 +/- 33 and 150 +/- 7 clones, p = NS). Using tools developed to assess differential gene expression, we determined whether these clonal patterns resulted from random clonal drift or selection. We identified 5 clones that were reproducibly enriched in methotrexate-treated patient-derived xenografts, suggestive of pre-existent resistance. Finally, we found that chemotherapymediated selection resulted in a more asymmetric distribution of leukemia clones across anatomic sites. We found that cellular barcoding is a powerful method to trace the clonal dynamics of human patient-derived leukemia cells in response to chemotherapy. In the future, integration of cellular barcoding with single-cell sequencing technology may allow in-depth characterization of therapy-resistant leukemia clones and identify novel targets to prevent relapse. (C) 2020 ISEH - Society for Hematology and Stem Cells. Published by Elsevier Inc.

Original languageEnglish
Pages (from-to)46-54
Number of pages9
JournalExperimental Hematology
Volume91
Early online date15-Sep-2020
DOIs
Publication statusPublished - Nov-2020

Keywords

  • DIFFERENTIAL EXPRESSION ANALYSIS
  • EVOLUTION
  • CELLS

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