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ClonArch: visualizing the spatial clonal architecture of tumors

MOTIVATION: Cancer is caused by the accumulation of somatic mutations that lead to the formation of distinct populations of cells, called clones. The resulting clonal architecture is the main cause of relapse and resistance to treatment. With decreasing costs in DNA sequencing technology, rich cance...

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Autores principales: Wu, Jiaqi, El-Kebir, Mohammed
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7355227/
https://www.ncbi.nlm.nih.gov/pubmed/32657368
http://dx.doi.org/10.1093/bioinformatics/btaa471
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author Wu, Jiaqi
El-Kebir, Mohammed
author_facet Wu, Jiaqi
El-Kebir, Mohammed
author_sort Wu, Jiaqi
collection PubMed
description MOTIVATION: Cancer is caused by the accumulation of somatic mutations that lead to the formation of distinct populations of cells, called clones. The resulting clonal architecture is the main cause of relapse and resistance to treatment. With decreasing costs in DNA sequencing technology, rich cancer genomics datasets with many spatial sequencing samples are becoming increasingly available, enabling the inference of high-resolution tumor clones and prevalences across different spatial coordinates. While temporal and phylogenetic aspects of tumor evolution, such as clonal evolution over time and clonal response to treatment, are commonly visualized in various clonal evolution diagrams, visual analytics methods that reveal the spatial clonal architecture are missing. RESULTS: This article introduces ClonArch, a web-based tool to interactively visualize the phylogenetic tree and spatial distribution of clones in a single tumor mass. ClonArch uses the marching squares algorithm to draw closed boundaries representing the presence of clones in a real or simulated tumor. ClonArch enables researchers to examine the spatial clonal architecture of a subset of relevant mutations at different prevalence thresholds and across multiple phylogenetic trees. In addition to simulated tumors with varying number of biopsies, we demonstrate the use of ClonArch on a hepatocellular carcinoma tumor with ∼280 sequencing biopsies. ClonArch provides an automated way to interactively examine the spatial clonal architecture of a tumor, facilitating clinical and biological interpretations of the spatial aspects of intra-tumor heterogeneity. AVAILABILITY AND IMPLEMENTATION: https://github.com/elkebir-group/ClonArch.
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spelling pubmed-73552272020-07-16 ClonArch: visualizing the spatial clonal architecture of tumors Wu, Jiaqi El-Kebir, Mohammed Bioinformatics Genomic Variation Analysis MOTIVATION: Cancer is caused by the accumulation of somatic mutations that lead to the formation of distinct populations of cells, called clones. The resulting clonal architecture is the main cause of relapse and resistance to treatment. With decreasing costs in DNA sequencing technology, rich cancer genomics datasets with many spatial sequencing samples are becoming increasingly available, enabling the inference of high-resolution tumor clones and prevalences across different spatial coordinates. While temporal and phylogenetic aspects of tumor evolution, such as clonal evolution over time and clonal response to treatment, are commonly visualized in various clonal evolution diagrams, visual analytics methods that reveal the spatial clonal architecture are missing. RESULTS: This article introduces ClonArch, a web-based tool to interactively visualize the phylogenetic tree and spatial distribution of clones in a single tumor mass. ClonArch uses the marching squares algorithm to draw closed boundaries representing the presence of clones in a real or simulated tumor. ClonArch enables researchers to examine the spatial clonal architecture of a subset of relevant mutations at different prevalence thresholds and across multiple phylogenetic trees. In addition to simulated tumors with varying number of biopsies, we demonstrate the use of ClonArch on a hepatocellular carcinoma tumor with ∼280 sequencing biopsies. ClonArch provides an automated way to interactively examine the spatial clonal architecture of a tumor, facilitating clinical and biological interpretations of the spatial aspects of intra-tumor heterogeneity. AVAILABILITY AND IMPLEMENTATION: https://github.com/elkebir-group/ClonArch. Oxford University Press 2020-07 2020-07-13 /pmc/articles/PMC7355227/ /pubmed/32657368 http://dx.doi.org/10.1093/bioinformatics/btaa471 Text en © The Author(s) 2020. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Genomic Variation Analysis
Wu, Jiaqi
El-Kebir, Mohammed
ClonArch: visualizing the spatial clonal architecture of tumors
title ClonArch: visualizing the spatial clonal architecture of tumors
title_full ClonArch: visualizing the spatial clonal architecture of tumors
title_fullStr ClonArch: visualizing the spatial clonal architecture of tumors
title_full_unstemmed ClonArch: visualizing the spatial clonal architecture of tumors
title_short ClonArch: visualizing the spatial clonal architecture of tumors
title_sort clonarch: visualizing the spatial clonal architecture of tumors
topic Genomic Variation Analysis
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7355227/
https://www.ncbi.nlm.nih.gov/pubmed/32657368
http://dx.doi.org/10.1093/bioinformatics/btaa471
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