Back to Search Start Over

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

Authors :
Scott D. Brown
Christian Steidl
Robert A. Holt
Andrew P. Weng
Greg Hapgood
Kerry J. Savage
Source :
Bioinformatics
Publication Year :
2016
Publisher :
Oxford University Press (OUP), 2016.

Abstract

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 (TH), T follicular helper (TFH) 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.

Details

ISSN :
13674811 and 13674803
Volume :
33
Database :
OpenAIRE
Journal :
Bioinformatics
Accession number :
edsair.doi.dedup.....b880726308c77bd58b20eb0498331519