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Phylogenetic Quantification of Intra-tumour Heterogeneity

Intra-tumour genetic heterogeneity is the result of ongoing evolutionary change within each cancer. The expansion of genetically distinct sub-clonal populations may explain the emergence of drug resistance, and if so, would have prognostic and predictive utility. However, methods for objectively qua...

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Autores principales: Schwarz, Roland F., Trinh, Anne, Sipos, Botond, Brenton, James D., Goldman, Nick, Markowetz, Florian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3990475/
https://www.ncbi.nlm.nih.gov/pubmed/24743184
http://dx.doi.org/10.1371/journal.pcbi.1003535
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author Schwarz, Roland F.
Trinh, Anne
Sipos, Botond
Brenton, James D.
Goldman, Nick
Markowetz, Florian
author_facet Schwarz, Roland F.
Trinh, Anne
Sipos, Botond
Brenton, James D.
Goldman, Nick
Markowetz, Florian
author_sort Schwarz, Roland F.
collection PubMed
description Intra-tumour genetic heterogeneity is the result of ongoing evolutionary change within each cancer. The expansion of genetically distinct sub-clonal populations may explain the emergence of drug resistance, and if so, would have prognostic and predictive utility. However, methods for objectively quantifying tumour heterogeneity have been missing and are particularly difficult to establish in cancers where predominant copy number variation prevents accurate phylogenetic reconstruction owing to horizontal dependencies caused by long and cascading genomic rearrangements. To address these challenges, we present MEDICC, a method for phylogenetic reconstruction and heterogeneity quantification based on a Minimum Event Distance for Intra-tumour Copy-number Comparisons. Using a transducer-based pairwise comparison function, we determine optimal phasing of major and minor alleles, as well as evolutionary distances between samples, and are able to reconstruct ancestral genomes. Rigorous simulations and an extensive clinical study show the power of our method, which outperforms state-of-the-art competitors in reconstruction accuracy, and additionally allows unbiased numerical quantification of tumour heterogeneity. Accurate quantification and evolutionary inference are essential to understand the functional consequences of tumour heterogeneity. The MEDICC algorithms are independent of the experimental techniques used and are applicable to both next-generation sequencing and array CGH data.
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spelling pubmed-39904752014-04-21 Phylogenetic Quantification of Intra-tumour Heterogeneity Schwarz, Roland F. Trinh, Anne Sipos, Botond Brenton, James D. Goldman, Nick Markowetz, Florian PLoS Comput Biol Research Article Intra-tumour genetic heterogeneity is the result of ongoing evolutionary change within each cancer. The expansion of genetically distinct sub-clonal populations may explain the emergence of drug resistance, and if so, would have prognostic and predictive utility. However, methods for objectively quantifying tumour heterogeneity have been missing and are particularly difficult to establish in cancers where predominant copy number variation prevents accurate phylogenetic reconstruction owing to horizontal dependencies caused by long and cascading genomic rearrangements. To address these challenges, we present MEDICC, a method for phylogenetic reconstruction and heterogeneity quantification based on a Minimum Event Distance for Intra-tumour Copy-number Comparisons. Using a transducer-based pairwise comparison function, we determine optimal phasing of major and minor alleles, as well as evolutionary distances between samples, and are able to reconstruct ancestral genomes. Rigorous simulations and an extensive clinical study show the power of our method, which outperforms state-of-the-art competitors in reconstruction accuracy, and additionally allows unbiased numerical quantification of tumour heterogeneity. Accurate quantification and evolutionary inference are essential to understand the functional consequences of tumour heterogeneity. The MEDICC algorithms are independent of the experimental techniques used and are applicable to both next-generation sequencing and array CGH data. Public Library of Science 2014-04-17 /pmc/articles/PMC3990475/ /pubmed/24743184 http://dx.doi.org/10.1371/journal.pcbi.1003535 Text en © 2014 Schwarz et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Schwarz, Roland F.
Trinh, Anne
Sipos, Botond
Brenton, James D.
Goldman, Nick
Markowetz, Florian
Phylogenetic Quantification of Intra-tumour Heterogeneity
title Phylogenetic Quantification of Intra-tumour Heterogeneity
title_full Phylogenetic Quantification of Intra-tumour Heterogeneity
title_fullStr Phylogenetic Quantification of Intra-tumour Heterogeneity
title_full_unstemmed Phylogenetic Quantification of Intra-tumour Heterogeneity
title_short Phylogenetic Quantification of Intra-tumour Heterogeneity
title_sort phylogenetic quantification of intra-tumour heterogeneity
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3990475/
https://www.ncbi.nlm.nih.gov/pubmed/24743184
http://dx.doi.org/10.1371/journal.pcbi.1003535
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