Effector and Regulatory T Cell Subsets in Follicular Lymphoma Tumors: Implications for Pathogenesis and Prognosis.

Abstract 2718

Gene expression profiling of follicular lymphoma (FL) tumors showed that genes attributable to infiltrating T cells were associated with improved survival (Dave et al., NEJM 2004; 351: 2109). However, the precise nature of the protective T cell subsets is unknown. Recent studies suggest that master transcription factors (TFs) such as T-bet, GATA-3, RORgt, and Bcl6 regulate the differentiation of effector T cells (Teffs) into TH1/TC1, TH2/TC2, TH17/TC17, and follicular helper T cell (TFH) subsets, respectively. These dominant TFs along with other TFs imprint specific cytokine and chemokine receptor expression in both CD4+ and CD8+ T-cell subsets. Based on these studies, identification of TH1/TC1, TH2/TC2, TH17/TC17, and TFH subsets using chemokine receptor expression pattern has been described in normal donors (Duhen et al., Blood 2012; 119: 4430). To determine whether this chemokine receptor expression pattern could be used for identification of Teff subsets in FL tumors, we FACSorted T cells from single cell suspensions of FL tumors and performed real-time PCR for master TFs and subset-specific cytokines. We found that T cell subsets in FL tumors have similar chemokine receptor expression pattern as peripheral blood T cells from normal donors: TH1/TC1 are CXCR3+, TH17/TC17 are CXCR3-CCR6+CCR4+, and TFH are CXCR5hiPD-1hi. A similar profile was also observed in tonsils, widely accepted as suitable controls for FL. Recent studies also suggest that the TFs essential for Teff differentiation are also involved in polarization of Foxp3+ regulatory T cells (Tregs) into specialized subsets that regulate the corresponding Teff subsets. Moreover, these Treg subsets express identical chemokine receptors as their target Teffs. Using Foxp3 and chemokine receptor expression pattern we found two major subsets of Tregs in FL and tonsils: Foxp3+CXCR3+ Tregs that regulate TH1/TC1 and Foxp3+CXCR5hiPD-1hi follicular regulatory T cells (TFR) that regulate TFH.

Next, using 10-color, 12-parameter flow cytometry we analyzed single cell suspensions of FL tumors (n=41) and normal tonsils (n=11) and determined the percentages of various Teff and Treg subsets, B cells, NK cells, and macrophages of total live cells. We found that NK cells and macrophages were not significantly different between the two but the percentage of B cells was significantly lower in FL vs tonsils (p<0.01). In contrast, CD3+ and CD4+ T cells were significantly increased in FL vs. tonsils (p<0.01) but CD8+ T cells were not (p=0.4). However, activated T cells (CD45RO+) were significantly increased in both CD4+ (p<0.001) and CD8+ (p=0.016) T cells in FL tumors vs. tonsils with the increase predominantly from central memory T cells rather than effector memory T cells. Among the Teffs (identified by excluding Foxp3+ T cells), TH1 (p<0.000001), TH17 (p<0.01), TC1 (p<0.01), and TC17 (p<0.001) were significantly increased in FL tumors vs tonsils but TFH were not (p=0.8). Among the Foxp3+ Tregs, total Tregs (p<0.0001), CXCR3+ Tregs (p<0.0000001), and TFR (p<0.0001) were significantly increased in FL tumors vs tonsils. Comparison of the ratios of TH1:CXCR3+ Tregs, TC1:CXCR3+ Tregs, and TFH:TFR all showed that the ratios were significantly higher in tonsils vs FL tumors (p<0.001). Taken together, these results suggest that despite the increase in CD4+ and CD8+ Teff subsets in FL, the increase in the corresponding Treg subsets may offset their effects and facilitate immune evasion by the tumor. Based on the known functions, TH1/TC1 and TH17/TC17 are likely to have antitumor effects and TFH may have protumor effects in FL. Among Tregs, CXCR3+ Tregs may have protumor effects by inhibiting TH1/TC1 and TFR may have antitumor effects by inhibiting B cells and TFH. Therefore, the prognostic impact of tumor infiltrating T cells in FL may depend on the relative dominance of these various Teff and Treg subsets. The phenotypic profile described above provides a simple method to enumerate these subsets routinely in clinical flow cytometry laboratories and help us better understand their effect on the pathogenesis and prognosis in FL.