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Computational reconstruction of clonal hierarchies from bulk sequencing data of acute myeloid leukemia samples

View ORCID ProfileThomas Stiehl, Anna Marciniak-Czochra
doi: https://doi.org/10.1101/2021.01.23.427897
Thomas Stiehl
1Institute of Applied Mathematics & Interdisciplinary Center for Scientific Computing, Heidelberg University, Heidelberg, Germany
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Anna Marciniak-Czochra
2Institute of Applied Mathematics, Interdisciplinary Center for Scientific Computing & Bioquant Center, Heidelberg University, Heidelberg, Germany
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  • For correspondence: anna.marciniak@iwr.uni-heidelberg.de
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Abstract

Acute myeloid leukemia is an aggressive cancer of the blood forming system. The malignant cell population is composed of multiple clones that evolve over time. Clonal data reflect the mechanisms governing treatment response and relapse. Single cell sequencing provides most direct insights into the clonal composition of the leukemic cells, however it is still not routinely available in clinical practice. In this work we develop a computational algorithm that allows identifying all clonal hierarchies that are compatible with bulk variant allele frequencies measured in a patient sample. The clonal hierarchies represent descendance relations between the different clones and reveal the order in which mutations have been acquired. The proposed computational approach is tested using single cell sequencing data that allow comparing the outcome of the algorithm with the true structure of the clonal hierarchy. We investigate which problems occur during reconstruction of clonal hierarchies from bulk sequencing data. Our results suggest that in many cases only a small number of possible hierarchies fits the bulk data. This implies that bulk sequencing data can be used to obtain insights in clonal evolution.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • https://ashpublications.org/bloodadvances/article/4/5/943/452671/Single-cell-mutational-profiling-enhances-the

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Posted January 25, 2021.
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Computational reconstruction of clonal hierarchies from bulk sequencing data of acute myeloid leukemia samples
Thomas Stiehl, Anna Marciniak-Czochra
bioRxiv 2021.01.23.427897; doi: https://doi.org/10.1101/2021.01.23.427897
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Computational reconstruction of clonal hierarchies from bulk sequencing data of acute myeloid leukemia samples
Thomas Stiehl, Anna Marciniak-Czochra
bioRxiv 2021.01.23.427897; doi: https://doi.org/10.1101/2021.01.23.427897

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