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Detecting truly clonal alterations from multi-region profiling of tumours

Modern cancer therapies aim at targeting tumour-specific alterations, such as mutations or neo-antigens, and maximal treatment efficacy requires that targeted alterations are present in all tumour cells. Currently, treatment decisions are based on one or a few samples per tumour, creating uncertaint...

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Autores principales: Werner, Benjamin, Traulsen, Arne, Sottoriva, Andrea, Dingli, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5366809/
https://www.ncbi.nlm.nih.gov/pubmed/28344344
http://dx.doi.org/10.1038/srep44991
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author Werner, Benjamin
Traulsen, Arne
Sottoriva, Andrea
Dingli, David
author_facet Werner, Benjamin
Traulsen, Arne
Sottoriva, Andrea
Dingli, David
author_sort Werner, Benjamin
collection PubMed
description Modern cancer therapies aim at targeting tumour-specific alterations, such as mutations or neo-antigens, and maximal treatment efficacy requires that targeted alterations are present in all tumour cells. Currently, treatment decisions are based on one or a few samples per tumour, creating uncertainty on whether alterations found in those samples are actually present in all tumour cells. The probability of classifying clonal versus sub-clonal alterations from multi-region profiling of tumours depends on the earliest phylogenetic branching event during tumour growth. By analysing 181 samples from 10 renal carcinoma and 11 colorectal cancers we demonstrate that the information gain from additional sampling falls onto a simple universal curve. We found that in colorectal cancers, 30% of alterations identified as clonal with one biopsy proved sub-clonal when 8 samples were considered. The probability to overestimate clonal alterations fell below 1% in 7/11 patients with 8 samples per tumour. In renal cell carcinoma, 8 samples reduced the list of clonal alterations by 40% with respect to a single biopsy. The probability to overestimate clonal alterations remained as high as 92% in 7/10 renal cancer patients. Furthermore, treatment was associated with more unbalanced tumour phylogenetic trees, suggesting the need of denser sampling of tumours at relapse.
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spelling pubmed-53668092017-03-28 Detecting truly clonal alterations from multi-region profiling of tumours Werner, Benjamin Traulsen, Arne Sottoriva, Andrea Dingli, David Sci Rep Article Modern cancer therapies aim at targeting tumour-specific alterations, such as mutations or neo-antigens, and maximal treatment efficacy requires that targeted alterations are present in all tumour cells. Currently, treatment decisions are based on one or a few samples per tumour, creating uncertainty on whether alterations found in those samples are actually present in all tumour cells. The probability of classifying clonal versus sub-clonal alterations from multi-region profiling of tumours depends on the earliest phylogenetic branching event during tumour growth. By analysing 181 samples from 10 renal carcinoma and 11 colorectal cancers we demonstrate that the information gain from additional sampling falls onto a simple universal curve. We found that in colorectal cancers, 30% of alterations identified as clonal with one biopsy proved sub-clonal when 8 samples were considered. The probability to overestimate clonal alterations fell below 1% in 7/11 patients with 8 samples per tumour. In renal cell carcinoma, 8 samples reduced the list of clonal alterations by 40% with respect to a single biopsy. The probability to overestimate clonal alterations remained as high as 92% in 7/10 renal cancer patients. Furthermore, treatment was associated with more unbalanced tumour phylogenetic trees, suggesting the need of denser sampling of tumours at relapse. Nature Publishing Group 2017-03-27 /pmc/articles/PMC5366809/ /pubmed/28344344 http://dx.doi.org/10.1038/srep44991 Text en Copyright © 2017, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Werner, Benjamin
Traulsen, Arne
Sottoriva, Andrea
Dingli, David
Detecting truly clonal alterations from multi-region profiling of tumours
title Detecting truly clonal alterations from multi-region profiling of tumours
title_full Detecting truly clonal alterations from multi-region profiling of tumours
title_fullStr Detecting truly clonal alterations from multi-region profiling of tumours
title_full_unstemmed Detecting truly clonal alterations from multi-region profiling of tumours
title_short Detecting truly clonal alterations from multi-region profiling of tumours
title_sort detecting truly clonal alterations from multi-region profiling of tumours
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5366809/
https://www.ncbi.nlm.nih.gov/pubmed/28344344
http://dx.doi.org/10.1038/srep44991
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