Cell lineage analysis of acute leukemia relapse uncovers the role of replication-rate heterogeneity and microsatellite instability

Liran I Shlush, Ilani, Noa Chapal Ilani, Rivka Adar, Neta Pery, Yosef Maruvka, Adam Spiro, Roni Shouval, Jacob M. Rowe, Maty Tzukerman, Dani Bercovich, Shai Izraeli, Guido Marcucci, Clara D. Bloomfield, Tsila Zuckerman, Karl Skorecki, Ehud Shapiro

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60 Citations (Scopus)

Abstract

Human cancers display substantial intratumoral genetic heterogeneity, which facilitates tumor survival under changing microenvironmental conditions. Tumor substructure and its effect on disease progression and relapse are incompletely understood. In the present study, a high-throughput method that uses neutral somatic mutations accumulated in individual cells to reconstruct cell lineage trees was applied to hundreds of cells of human acute leukemia harvested from multiple patients at diagnosis and at relapse. The reconstructed cell lineage trees of patients with acute myeloid leukemia showed that leukemia cells at relapse were shallow (divide rarely) compared with cells at diagnosis and were closely related to their stem cell subpopulation, implying that in these instances relapse might have originated from rarely dividing stem cells. In contrast, among patients with acute lymphoid leukemia, no differences in cell depth were observed between diagnosis and relapse. In one case of chronic myeloid leukemia, at blast crisis, most of the cells at relapse were mismatch-repair deficient. In almost all leukemia cases, > 1 lineage was observed at relapse, indicating that diverse mechanisms can promote relapse in the same patient. In conclusion, diverse relapse mechanisms can be observed by systematic reconstruction of cell lineage trees of patients with leukemia.
Original languageEnglish
Pages (from-to)603-612
Number of pages10
JournalBlood
Volume120
Issue number3
DOIs
Publication statusPublished - 19 Jul 2012

Funding

ISF Converging Technologies [1694/07]; European Union [FP7-ERC-AdG]; Miel de Botton Aynsley Foundation; Paul Sparr Foundation; Arthur and Rosalinde Gilbert Foundation; Soref Foundation (American Technion Society); Slava Smolakovski Fund (Rambam Medical Center); Etai Sharon Atidim grant program of Rambam Medical Center; Israel Cancer Association [20110054-B 2011] The authors thank Shalev Itzkovitz for helpful discussions and the European Union FP7-COSTEuGESMA action. This work was supported by The ISF Converging Technologies (grant 1694/07), The European Union (grant FP7-ERC-AdG), Miel de Botton Aynsley Foundation, Paul Sparr Foundation, the Arthur and Rosalinde Gilbert Foundation (K. S.), the Soref Foundation (American Technion Society; K. S.), Slava Smolakovski Fund (Rambam Medical Center; K. S.), the Etai Sharon Atidim grant program of Rambam Medical Center (L. I. S.), and the Israel Cancer Association (grant 20110054-B 2011; L. I. S.). E. S. is the incumbent of The Harry Weinrebe Professorial Chair of Computer Science and Biology. K. S. is the incumbent of the Annie Chutick Chair in Medicine at the Technion-Israel Institute of Technology. S.I. would like to thank the Israeli Cancer Foundation.

All Science Journal Classification (ASJC) codes

  • Hematology
  • Biochemistry
  • Cell Biology
  • Immunology

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