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SciClone: Inferring Clonal Architecture and Tracking the Spatial and Temporal Patterns of Tumor Evolution
The sensitivity of massively-parallel sequencing has confirmed that most cancers are oligoclonal, with subpopulations of neoplastic cells harboring distinct mutations. A fine resolution view of this clonal architecture provides insight into tumor heterogeneity, evolution, and treatment response, all...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4125065/ https://www.ncbi.nlm.nih.gov/pubmed/25102416 http://dx.doi.org/10.1371/journal.pcbi.1003665 |
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author | Miller, Christopher A. White, Brian S. Dees, Nathan D. Griffith, Malachi Welch, John S. Griffith, Obi L. Vij, Ravi Tomasson, Michael H. Graubert, Timothy A. Walter, Matthew J. Ellis, Matthew J. Schierding, William DiPersio, John F. Ley, Timothy J. Mardis, Elaine R. Wilson, Richard K. Ding, Li |
author_facet | Miller, Christopher A. White, Brian S. Dees, Nathan D. Griffith, Malachi Welch, John S. Griffith, Obi L. Vij, Ravi Tomasson, Michael H. Graubert, Timothy A. Walter, Matthew J. Ellis, Matthew J. Schierding, William DiPersio, John F. Ley, Timothy J. Mardis, Elaine R. Wilson, Richard K. Ding, Li |
author_sort | Miller, Christopher A. |
collection | PubMed |
description | The sensitivity of massively-parallel sequencing has confirmed that most cancers are oligoclonal, with subpopulations of neoplastic cells harboring distinct mutations. A fine resolution view of this clonal architecture provides insight into tumor heterogeneity, evolution, and treatment response, all of which may have clinical implications. Single tumor analysis already contributes to understanding these phenomena. However, cryptic subclones are frequently revealed by additional patient samples (e.g., collected at relapse or following treatment), indicating that accurately characterizing a tumor requires analyzing multiple samples from the same patient. To address this need, we present SciClone, a computational method that identifies the number and genetic composition of subclones by analyzing the variant allele frequencies of somatic mutations. We use it to detect subclones in acute myeloid leukemia and breast cancer samples that, though present at disease onset, are not evident from a single primary tumor sample. By doing so, we can track tumor evolution and identify the spatial origins of cells resisting therapy. |
format | Online Article Text |
id | pubmed-4125065 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-41250652014-08-12 SciClone: Inferring Clonal Architecture and Tracking the Spatial and Temporal Patterns of Tumor Evolution Miller, Christopher A. White, Brian S. Dees, Nathan D. Griffith, Malachi Welch, John S. Griffith, Obi L. Vij, Ravi Tomasson, Michael H. Graubert, Timothy A. Walter, Matthew J. Ellis, Matthew J. Schierding, William DiPersio, John F. Ley, Timothy J. Mardis, Elaine R. Wilson, Richard K. Ding, Li PLoS Comput Biol Research Article The sensitivity of massively-parallel sequencing has confirmed that most cancers are oligoclonal, with subpopulations of neoplastic cells harboring distinct mutations. A fine resolution view of this clonal architecture provides insight into tumor heterogeneity, evolution, and treatment response, all of which may have clinical implications. Single tumor analysis already contributes to understanding these phenomena. However, cryptic subclones are frequently revealed by additional patient samples (e.g., collected at relapse or following treatment), indicating that accurately characterizing a tumor requires analyzing multiple samples from the same patient. To address this need, we present SciClone, a computational method that identifies the number and genetic composition of subclones by analyzing the variant allele frequencies of somatic mutations. We use it to detect subclones in acute myeloid leukemia and breast cancer samples that, though present at disease onset, are not evident from a single primary tumor sample. By doing so, we can track tumor evolution and identify the spatial origins of cells resisting therapy. Public Library of Science 2014-08-07 /pmc/articles/PMC4125065/ /pubmed/25102416 http://dx.doi.org/10.1371/journal.pcbi.1003665 Text en © 2014 Miller 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 Miller, Christopher A. White, Brian S. Dees, Nathan D. Griffith, Malachi Welch, John S. Griffith, Obi L. Vij, Ravi Tomasson, Michael H. Graubert, Timothy A. Walter, Matthew J. Ellis, Matthew J. Schierding, William DiPersio, John F. Ley, Timothy J. Mardis, Elaine R. Wilson, Richard K. Ding, Li SciClone: Inferring Clonal Architecture and Tracking the Spatial and Temporal Patterns of Tumor Evolution |
title | SciClone: Inferring Clonal Architecture and Tracking the Spatial and Temporal Patterns of Tumor Evolution |
title_full | SciClone: Inferring Clonal Architecture and Tracking the Spatial and Temporal Patterns of Tumor Evolution |
title_fullStr | SciClone: Inferring Clonal Architecture and Tracking the Spatial and Temporal Patterns of Tumor Evolution |
title_full_unstemmed | SciClone: Inferring Clonal Architecture and Tracking the Spatial and Temporal Patterns of Tumor Evolution |
title_short | SciClone: Inferring Clonal Architecture and Tracking the Spatial and Temporal Patterns of Tumor Evolution |
title_sort | sciclone: inferring clonal architecture and tracking the spatial and temporal patterns of tumor evolution |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4125065/ https://www.ncbi.nlm.nih.gov/pubmed/25102416 http://dx.doi.org/10.1371/journal.pcbi.1003665 |
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