Genetic variegation of clonal architecture and propagating cells in leukaemia

K Anderson, C Lutz, FW Van Delft, CM Bateman, Y Guo… - Nature, 2011 - nature.com
K Anderson, C Lutz, FW Van Delft, CM Bateman, Y Guo, SM Colman, H Kempski…
Nature, 2011nature.com
Little is known of the genetic architecture of cancer at the subclonal and single-cell level or
in the cells responsible for cancer clone maintenance and propagation. Here we have
examined this issue in childhood acute lymphoblastic leukaemia in which the ETV6–RUNX1
gene fusion is an early or initiating genetic lesion followed by a modest number of recurrent
or 'driver'copy number alterations. By multiplexing fluorescence in situ hybridization probes
for these mutations, up to eight genetic abnormalities can be detected in single cells, a …
Abstract
Little is known of the genetic architecture of cancer at the subclonal and single-cell level or in the cells responsible for cancer clone maintenance and propagation. Here we have examined this issue in childhood acute lymphoblastic leukaemia in which the ETV6–RUNX1 gene fusion is an early or initiating genetic lesion followed by a modest number of recurrent or ‘driver’ copy number alterations. By multiplexing fluorescence in situ hybridization probes for these mutations, up to eight genetic abnormalities can be detected in single cells, a genetic signature of subclones identified and a composite picture of subclonal architecture and putative ancestral trees assembled. Subclones in acute lymphoblastic leukaemia have variegated genetics and complex, nonlinear or branching evolutionary histories. Copy number alterations are independently and reiteratively acquired in subclones of individual patients, and in no preferential order. Clonal architecture is dynamic and is subject to change in the lead-up to a diagnosis and in relapse. Leukaemia propagating cells, assayed by serial transplantation in NOD/SCID IL2Rγnull mice, are also genetically variegated, mirroring subclonal patterns, and vary in competitive regenerative capacity in vivo. These data have implications for cancer genomics and for the targeted therapy of cancer.
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