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Inferring clonal structure in HTLV-1-infected individuals: towards bridging the gap between analysis and visualization
BACKGROUND: Human T cell leukemia virus type 1 (HTLV-1) causes adult T cell leukemia (ATL) in a proportion of infected individuals after a long latency period. Development of ATL is a multistep clonal process that can be investigated by monitoring the clonal expansion of HTLV-1-infected cells by iso...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5505134/ https://www.ncbi.nlm.nih.gov/pubmed/28697807 http://dx.doi.org/10.1186/s40246-017-0112-8 |
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author | Farmanbar, Amir Firouzi, Sanaz Makałowski, Wojciech Iwanaga, Masako Uchimaru, Kaoru Utsunomiya, Atae Watanabe, Toshiki Nakai, Kenta |
author_facet | Farmanbar, Amir Firouzi, Sanaz Makałowski, Wojciech Iwanaga, Masako Uchimaru, Kaoru Utsunomiya, Atae Watanabe, Toshiki Nakai, Kenta |
author_sort | Farmanbar, Amir |
collection | PubMed |
description | BACKGROUND: Human T cell leukemia virus type 1 (HTLV-1) causes adult T cell leukemia (ATL) in a proportion of infected individuals after a long latency period. Development of ATL is a multistep clonal process that can be investigated by monitoring the clonal expansion of HTLV-1-infected cells by isolation of provirus integration sites. The clonal composition (size, number, and combinations of clones) during the latency period in a given infected individual has not been clearly elucidated. METHODS: We used high-throughput sequencing technology coupled with a tag system for isolating integration sites and measuring clone sizes from 60 clinical samples. We assessed the role of clonality and clone size dynamics in ATL onset by modeling data from high-throughput monitoring of HTLV-1 integration sites using single- and multiple-time-point samples. RESULTS: From four size categories analyzed, we found that big clones (B; 513–2048 infected cells) and very big clones (VB; >2048 infected cells) had prognostic value. No sample harbored two or more VB clones or three or more B clones. We examined the role of clone size, clone combination, and the number of integration sites in the prognosis of infected individuals. We found a moderate reverse correlation between the total number of clones and the size of the largest clone. We devised a data-driven model that allows intuitive representation of clonal composition. CONCLUSIONS: This integration site-based clonality tree model represents the complexity of clonality and provides a global view of clonality data that facilitates the analysis, interpretation, understanding, and visualization of the behavior of clones on inter- and intra-individual scales. It is fully data-driven, intuitively depicts the clonality patterns of HTLV-1-infected individuals and can assist in early risk assessment of ATL onset by reflecting the prognosis of infected individuals. This model should assist in assimilating information on clonal composition and understanding clonal expansion in HTLV-1-infected individuals. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s40246-017-0112-8) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5505134 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-55051342017-07-12 Inferring clonal structure in HTLV-1-infected individuals: towards bridging the gap between analysis and visualization Farmanbar, Amir Firouzi, Sanaz Makałowski, Wojciech Iwanaga, Masako Uchimaru, Kaoru Utsunomiya, Atae Watanabe, Toshiki Nakai, Kenta Hum Genomics Primary Research BACKGROUND: Human T cell leukemia virus type 1 (HTLV-1) causes adult T cell leukemia (ATL) in a proportion of infected individuals after a long latency period. Development of ATL is a multistep clonal process that can be investigated by monitoring the clonal expansion of HTLV-1-infected cells by isolation of provirus integration sites. The clonal composition (size, number, and combinations of clones) during the latency period in a given infected individual has not been clearly elucidated. METHODS: We used high-throughput sequencing technology coupled with a tag system for isolating integration sites and measuring clone sizes from 60 clinical samples. We assessed the role of clonality and clone size dynamics in ATL onset by modeling data from high-throughput monitoring of HTLV-1 integration sites using single- and multiple-time-point samples. RESULTS: From four size categories analyzed, we found that big clones (B; 513–2048 infected cells) and very big clones (VB; >2048 infected cells) had prognostic value. No sample harbored two or more VB clones or three or more B clones. We examined the role of clone size, clone combination, and the number of integration sites in the prognosis of infected individuals. We found a moderate reverse correlation between the total number of clones and the size of the largest clone. We devised a data-driven model that allows intuitive representation of clonal composition. CONCLUSIONS: This integration site-based clonality tree model represents the complexity of clonality and provides a global view of clonality data that facilitates the analysis, interpretation, understanding, and visualization of the behavior of clones on inter- and intra-individual scales. It is fully data-driven, intuitively depicts the clonality patterns of HTLV-1-infected individuals and can assist in early risk assessment of ATL onset by reflecting the prognosis of infected individuals. This model should assist in assimilating information on clonal composition and understanding clonal expansion in HTLV-1-infected individuals. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s40246-017-0112-8) contains supplementary material, which is available to authorized users. BioMed Central 2017-07-11 /pmc/articles/PMC5505134/ /pubmed/28697807 http://dx.doi.org/10.1186/s40246-017-0112-8 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Primary Research Farmanbar, Amir Firouzi, Sanaz Makałowski, Wojciech Iwanaga, Masako Uchimaru, Kaoru Utsunomiya, Atae Watanabe, Toshiki Nakai, Kenta Inferring clonal structure in HTLV-1-infected individuals: towards bridging the gap between analysis and visualization |
title | Inferring clonal structure in HTLV-1-infected individuals: towards bridging the gap between analysis and visualization |
title_full | Inferring clonal structure in HTLV-1-infected individuals: towards bridging the gap between analysis and visualization |
title_fullStr | Inferring clonal structure in HTLV-1-infected individuals: towards bridging the gap between analysis and visualization |
title_full_unstemmed | Inferring clonal structure in HTLV-1-infected individuals: towards bridging the gap between analysis and visualization |
title_short | Inferring clonal structure in HTLV-1-infected individuals: towards bridging the gap between analysis and visualization |
title_sort | inferring clonal structure in htlv-1-infected individuals: towards bridging the gap between analysis and visualization |
topic | Primary Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5505134/ https://www.ncbi.nlm.nih.gov/pubmed/28697807 http://dx.doi.org/10.1186/s40246-017-0112-8 |
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