ArticleHuman genomics2017
Inferring clonal structure in HTLV-1-infected individuals: towards bridging the gap between analysis and visualization.
Article in Human genomics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 7 citations in OpenAlex.
- Host genetic determinants of HTLV-1 infection outcomes.Immunologic research · 2026Review
- Circulating Virus-Host Chimera DNAs in the Clinical Monitoring of Virus-Related Cancers.Cancers · 2022Review
- HTLV-1 infection: An emerging risk. Pathogenesis, epidemiology, diagnosis and associated diseases.Revista espanola de quimioterapia : publicacion oficial de la Sociedad Espanola de Quimioterapia · 2019Review
- RNA sequencing identifies clonal structure of T-cell repertoires in patients with adult T-cell leukemia/lymphoma.NPJ genomic medicine · 2019Article
- Mutational Intratumor Heterogeneity is a Complex and Early Event in the Development of Adult T-cell Leukemia/Lymphoma.Neoplasia (New York, N.Y.) · 2018Article
- VISPA2: a scalable pipeline for high-throughput identification and annotation of vector integration sites.BMC bioinformatics · 2017Article
Corrections and comments
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Authors and funding
8 authors at 5 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundHuman 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.
methodsWe 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.
resultsFrom 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.
conclusionsThis 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.
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