High-Definition Reconstruction of Clonal Composition in Cancer
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...
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2014-06-01
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doaj-d976cc5fb0104049af074b016efe680b2020-11-25T01:17:03ZengElsevierCell Reports2211-12472014-06-01751740175210.1016/j.celrep.2014.04.055High-Definition Reconstruction of Clonal Composition in CancerAndrej Fischer0Ignacio Vázquez-García1Christopher J.R. Illingworth2Ville Mustonen3Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UKWellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UKDepartment of Genetics, University of Cambridge, Downing Street, Cambridge CB2 3EH, UKWellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UKThe 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.http://www.sciencedirect.com/science/article/pii/S2211124714003738 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Andrej Fischer Ignacio Vázquez-García Christopher J.R. Illingworth Ville Mustonen |
spellingShingle |
Andrej Fischer Ignacio Vázquez-García Christopher J.R. Illingworth Ville Mustonen High-Definition Reconstruction of Clonal Composition in Cancer Cell Reports |
author_facet |
Andrej Fischer Ignacio Vázquez-García Christopher J.R. Illingworth Ville Mustonen |
author_sort |
Andrej Fischer |
title |
High-Definition Reconstruction of Clonal Composition in Cancer |
title_short |
High-Definition Reconstruction of Clonal Composition in Cancer |
title_full |
High-Definition Reconstruction of Clonal Composition in Cancer |
title_fullStr |
High-Definition Reconstruction of Clonal Composition in Cancer |
title_full_unstemmed |
High-Definition Reconstruction of Clonal Composition in Cancer |
title_sort |
high-definition reconstruction of clonal composition in cancer |
publisher |
Elsevier |
series |
Cell Reports |
issn |
2211-1247 |
publishDate |
2014-06-01 |
description |
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. |
url |
http://www.sciencedirect.com/science/article/pii/S2211124714003738 |
work_keys_str_mv |
AT andrejfischer highdefinitionreconstructionofclonalcompositionincancer AT ignaciovazquezgarcia highdefinitionreconstructionofclonalcompositionincancer AT christopherjrillingworth highdefinitionreconstructionofclonalcompositionincancer AT villemustonen highdefinitionreconstructionofclonalcompositionincancer |
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