Abstract
Background: Although most malignancies are associated with decreased numbers of circulating T cells, in CLL they are elevated 2 to 4 times normal. Rather than promoting an anti-tumor response, this increased population of T cells may contribute to a tumor microenvironment that fosters progression of the malignant clone. Immunocompetent individuals show a wide repertoire of antigen specificity in both CD4+ and CD8+ T cells, but the T cell repertoire is significantly restricted in CLL. This restriction of the T cell repertoire may be an important cause of infectious morbidity in patients with CLL. To better understand these T cell abnormalities, we enumerated T cell subsets and determined T cell receptor diversity in 18 untreated patients with CLL.
Methods: T cell subsets were enumerated from peripheral blood using highly sensitive 6-color flow cytometry. The T cell repertoire was determined for 23 T cell receptor variable β chain families (TCRvβ) in purified CD4+ and CD8+ T cells. These T cell subsets were considered separately because differential restriction of the CD4+ and CD8+ subsets has been reported previously. A PCR-based spectratype assay was used to analyze the length distribution of the TCR complementarity-determining region 3 (CDR3). A limitation of prior reports using spectratype assays was that adequately complex statistical models did not exist to simultaneously analyze the highly diverse vβ families. We addressed this limitation by using a recently-developed statistical method for spectratype analysis (Bioinformatics. 21:3394–400). Briefly, for each vβ family, the divergence from an expected reference distribution was calculated. A divergence coefficient was determined for each vβ family, and the mean divergence of all 23 vβ families was calculated. This allowed for statistical comparisons among individual patients and specific vβ families. To our knowledge, we are the first group to apply this powerful methodology to the analysis of T cell repertoires in patients with CLL.
Results: We found both the CD4+ and CD8+ subsets to be expanded (mean #/μL ± SD: 1134 ± 646 and 768 ± 716, respectively; reference normal CD4+ range 401–1532, CD8+ 152–838). The absolute number of CD4+ and CD8+ T cells was greater in patients with higher absolute CLL lymphocyte counts (p = 0.018, r2 = 0.30, and p = 0.23, r2 = 0.09, respectively, linear regression). The CD4:CD8 ratio was lower in IgVH unmutated subjects (mutated 2.6, umutated 1.7, p = 0.09, two-tailed t-test assuming unequal variances). Though prior reports have disagreed on whether CD4+ or CD8+ subsets show greater restriction of clonality, we observed striking clonal restriction of CD8+ but not CD4+ T cells (p < 1×10−7, 2 sided t-test assuming unequal variances). There was a trend toward greater restriction of the CD8+ subset among patients with IgVH unmutated and Zap70+ CLL, but there was no correlation with lymphocyte doubling time.
Conclusions: In this cohort of 18 untreated patients with CLL, there was a greater proportional increase compared to reference standards of CD8+ versus CD4+ T cells. However, the increase in CD4+, but not CD8+, T cell numbers was significantly correlated to total CLL lymphocyte count. This observation suggests that expansion of the CD4+ T cell pool observed in CLL is proportional to leukemic burden. The restriction of TCRvβ was limited to CD8+ T cells and that this effect was independent of the size of the abnormal clone. Taken together, these findings suggest different mechanisms of dysregulation of CD4+ and CD8+ T cell subsets in CLL.
Overexpression of Select T Cell Receptor Vβ Gene Families within CD4+ and CD8+ T Cell Subsets of Myasthenia Gravis Patients: A Role for Superantigen(s)?
