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.
Contacts: rholt@bcgsc.ca or ksavage@bccancer.bc.ca.
Supplementary information: Supplementary data are available at Bioinformatics online.
© The Author 2016. Published by Oxford University Press.