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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| Format: | Online |
| Language: | English |
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Cell Press
2014
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| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4062932/ |
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pubmed-4062932 |
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oai_dc |
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pubmed-40629322014-06-20 High-Definition Reconstruction of Clonal Composition in Cancer Fischer, Andrej Vázquez-García, Ignacio Illingworth, Christopher J.R. Mustonen, Ville Resource 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. Cell Press 2014-05-29 /pmc/articles/PMC4062932/ /pubmed/24882004 http://dx.doi.org/10.1016/j.celrep.2014.04.055 Text en © 2014 The Authors http://creativecommons.org/licenses/by-nc-nd/3.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/). |
| repository_type |
Open Access Journal |
| institution_category |
Foreign Institution |
| institution |
US National Center for Biotechnology Information |
| building |
NCBI PubMed |
| collection |
Online Access |
| language |
English |
| format |
Online |
| author |
Fischer, Andrej Vázquez-García, Ignacio Illingworth, Christopher J.R. Mustonen, Ville |
| spellingShingle |
Fischer, Andrej Vázquez-García, Ignacio Illingworth, Christopher J.R. Mustonen, Ville High-Definition Reconstruction of Clonal Composition in Cancer |
| author_facet |
Fischer, Andrej Vázquez-García, Ignacio Illingworth, Christopher J.R. Mustonen, Ville |
| author_sort |
Fischer, Andrej |
| 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 |
| 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. |
| publisher |
Cell Press |
| publishDate |
2014 |
| url |
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4062932/ |
| _version_ |
1612103347308855296 |