Fiche publication
Date publication
décembre 2006
Auteurs
Membres identifiés du Cancéropôle Est :
Dr FERRAND Christophe
Tous les auteurs :
Long SA, Khalili J, Ashe J, Berenson R, Ferrand C, Bonyhadi M
Lien Pubmed
Résumé
Assessment of the diversity of the T-cell receptor (TCR) repertoire is often determined by measuring the frequency and distribution of individually rearranged TCRs in a population of T cells. Spectratyping is a common method used to measure TCR repertoire diversity, which examines genetic variation in the third complementarity-determining region (CDR3) region of the TCR Vbeta chain using RT-PCR length-distribution analysis. A variety of methods are currently used to analyze spectratype data including subjective visual measures, qualitative counting measures, and semi-quantitative measures that compare the original data to a standard, control data set. Two major limitations exist for most of these approaches: data files become very wieldy and difficult to manage, and current analytic methods generate data which are difficult to compare between laboratories and across different platforms. Here, we introduce a highly efficient method of analysis that is based upon a normal theoretical Gaussian distribution observed in cord blood and recent thymic emigrants. Using this analysis method, we demonstrate that PBMC obtained from patients with various diseases have skewed TCR repertoire profiles. Upon in vitro activation with anti-CD3 and anti-CD28 coated beads (Xcyte Dynabeads) TCR diversity was restored. Moreover, changes in the TCR repertoire were dynamic in vivo. We demonstrate that use of this streamlined method of analysis in concert with a flexible software package makes quantitative assessment of TCR repertoire diversity straightforward and reproducible, enabling reliable comparisons of diversity values between laboratories and over-time to further collaborative efforts. Analysis of TCR repertoire by such an approach may be valuable in the clinical setting, both for prognostic potential and measuring clinical responses to therapy.
Référence
J Immunol Methods. 2006 Dec 20;317(1-2):100-13
