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Defining the clonality of peripheral T cell lymphomas using RNA-seq

MOTIVATION: In T-cell lymphoma, malignant T cells arising from a founding clone share an identical T cell receptor (TCR) and can be identified by the over-representation of this TCR relative to TCRs from the patient’s repertoire of normal T cells. Here, we demonstrate that TCR information extracted...

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Autores principales: Brown, Scott D, Hapgood, Greg, Steidl, Christian, Weng, Andrew P, Savage, Kerry J, Holt, Robert A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5408843/
https://www.ncbi.nlm.nih.gov/pubmed/28003262
http://dx.doi.org/10.1093/bioinformatics/btw810
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author Brown, Scott D
Hapgood, Greg
Steidl, Christian
Weng, Andrew P
Savage, Kerry J
Holt, Robert A
author_facet Brown, Scott D
Hapgood, Greg
Steidl, Christian
Weng, Andrew P
Savage, Kerry J
Holt, Robert A
author_sort Brown, Scott D
collection PubMed
description MOTIVATION: In T-cell lymphoma, malignant T cells arising from a founding clone share an identical T cell receptor (TCR) and can be identified by the over-representation of this TCR relative to TCRs from the patient’s repertoire of normal T cells. Here, we demonstrate that TCR information extracted from RNA-seq data can provide a higher resolution view of peripheral T cell lymphomas (PTCLs) than that provided by conventional methods. RESULTS: For 60 subjects with PTCL, flow cytometry/FACS was used to identify and sort aberrant T cell populations from diagnostic lymph node cell suspensions. For samples that did not appear to contain aberrant T cell populations, T helper (T(H)), T follicular helper (T(FH)) and cytotoxic T lymphocyte (CTL) subsets were sorted. RNA-seq was performed on sorted T cell populations, and TCR alpha and beta chain sequences were extracted and quantified directly from the RNA-seq data. 96% of the immunophenotypically aberrant samples had a dominant T cell clone readily identifiable by RNA-seq. Of the samples where no aberrant population was found by flow cytometry, 80% had a dominant clone by RNA-seq. This demonstrates the increased sensitivity and diagnostic ability of RNA-seq over flow cytometry and shows that the presence of a normal immunophenotype does not exclude clonality. AVAILABILITY AND IMPLEMENTATION: R scripts used in the processing of the data are available online at https://www.github.com/scottdbrown/RNAseq-TcellClonality SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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spelling pubmed-54088432017-05-03 Defining the clonality of peripheral T cell lymphomas using RNA-seq Brown, Scott D Hapgood, Greg Steidl, Christian Weng, Andrew P Savage, Kerry J Holt, Robert A Bioinformatics Discovery Notes MOTIVATION: In T-cell lymphoma, malignant T cells arising from a founding clone share an identical T cell receptor (TCR) and can be identified by the over-representation of this TCR relative to TCRs from the patient’s repertoire of normal T cells. Here, we demonstrate that TCR information extracted from RNA-seq data can provide a higher resolution view of peripheral T cell lymphomas (PTCLs) than that provided by conventional methods. RESULTS: For 60 subjects with PTCL, flow cytometry/FACS was used to identify and sort aberrant T cell populations from diagnostic lymph node cell suspensions. For samples that did not appear to contain aberrant T cell populations, T helper (T(H)), T follicular helper (T(FH)) and cytotoxic T lymphocyte (CTL) subsets were sorted. RNA-seq was performed on sorted T cell populations, and TCR alpha and beta chain sequences were extracted and quantified directly from the RNA-seq data. 96% of the immunophenotypically aberrant samples had a dominant T cell clone readily identifiable by RNA-seq. Of the samples where no aberrant population was found by flow cytometry, 80% had a dominant clone by RNA-seq. This demonstrates the increased sensitivity and diagnostic ability of RNA-seq over flow cytometry and shows that the presence of a normal immunophenotype does not exclude clonality. AVAILABILITY AND IMPLEMENTATION: R scripts used in the processing of the data are available online at https://www.github.com/scottdbrown/RNAseq-TcellClonality SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2017-04-15 2016-12-21 /pmc/articles/PMC5408843/ /pubmed/28003262 http://dx.doi.org/10.1093/bioinformatics/btw810 Text en © The Author 2016. 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 Discovery Notes
Brown, Scott D
Hapgood, Greg
Steidl, Christian
Weng, Andrew P
Savage, Kerry J
Holt, Robert A
Defining the clonality of peripheral T cell lymphomas using RNA-seq
title Defining the clonality of peripheral T cell lymphomas using RNA-seq
title_full Defining the clonality of peripheral T cell lymphomas using RNA-seq
title_fullStr Defining the clonality of peripheral T cell lymphomas using RNA-seq
title_full_unstemmed Defining the clonality of peripheral T cell lymphomas using RNA-seq
title_short Defining the clonality of peripheral T cell lymphomas using RNA-seq
title_sort defining the clonality of peripheral t cell lymphomas using rna-seq
topic Discovery Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5408843/
https://www.ncbi.nlm.nih.gov/pubmed/28003262
http://dx.doi.org/10.1093/bioinformatics/btw810
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