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Cell Rep. 2014 Jun 12;7(5):1740-52. doi: 10.1016/j.celrep.2014.04.055. Epub 2014 May 29.

High-definition reconstruction of clonal composition in cancer.

Author information

1
Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK. Electronic address: af7@sanger.ac.uk.
2
Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK; Department of Applied Mathematics and Theoretical Physics, Centre for Mathematical Sciences, University of Cambridge, Wilberforce Road, Cambridge CB3 0WA, UK.
3
Department of Genetics, University of Cambridge, Downing Street, Cambridge CB2 3EH, UK.
4
Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK. Electronic address: vm5@sanger.ac.uk.

Abstract

The extensive genetic heterogeneity of cancers can greatly affect therapy success due to the existence of subclonal mutations conferring resistance. However, the characterization of subclones in mixed-cell populations is computationally challenging due to the short length of sequence reads that are generated by current sequencing technologies. Here, we report cloneHD, a probabilistic algorithm for the performance of subclone reconstruction from data generated by high-throughput DNA sequencing: read depth, B-allele counts at germline heterozygous loci, and somatic mutation counts. The algorithm can exploit the added information present in correlated longitudinal or multiregion samples and takes into account correlations along genomes caused by events such as copy-number changes. We apply cloneHD to two case studies: a breast cancer sample and time-resolved samples of chronic lymphocytic leukemia, where we demonstrate that monitoring the response of a patient to therapy regimens is feasible. Our work provides new opportunities for tracking cancer development.

PMID:
24882004
PMCID:
PMC4062932
DOI:
10.1016/j.celrep.2014.04.055
[Indexed for MEDLINE]
Free PMC Article
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