Citations

Abstract Description Signal regulatory protein-α (SIRPα) is a key member of the “do-not-eat-me” signaling pathway and is expressed on intratumoral monocytes/macrophages in lymphoma. In this study, we found that SIRPα is also expressed by a subset of malignant B cells in lymphoma. SIRPα+ B cells have a memory phenotype with germinal center (GC) dark-zone features, and RNA velocity analysis showed that SIRPα+ B cells exhibit higher spliced transcripts confirming a more mature phenotype. SIRPα expression is substantially upregulated by treating lymphoma B cells with LPS or CpG and SIRPα+ B cells showed increased proliferation when compared to SIRPα- B cells, which was associated with reduced cellular autophagy. SIRPα+ B cells exhibited increased expression of BAFF signaling pathway molecules as the likely mechanism of increased proliferation and survival. Furthermore, in co-culture, SIRPα+ lymphoma B cells suppressed T-cell function and blocking SIRPa/CD47 signaling reversed T cell inhibition. Clinically, we found that a greater number of SIRPα+ B cells present in the diagnostic tumor biopsies of FL patients was associated with a significantly poorer overall survival. We conclude that SIRPα+ lymphoma B cells are a proliferative component of indolent lymphomas, are associated with T-cell suppression, and increased prevalence of these cells is associated with a poor prognosis. Targeting SIRPα+ B cells in lymphoma may therefore be a promising therapeutic strategy. Topic Categories Tumor Immunology: Cellular Responses and Tumor Microevironment (TIME)

Abstract Description The efficacy of immunotherapy for splenic marginal zone lymphoma (SMZL) remains limited due to the strong immune suppression present in the tumor microenvironment (TME). Tregs play a key role in maintaining TME homeostasis by suppressing effector T cells and malignant B cells. Previously, we identified two Treg subsets CD26+ and CD161+ in SMZL. CD161+ Tregs were more effective at suppressing both CD8+T cells and malignant B cells, whereas CD26+Tregs primarily inhibited CD8+T cells. Patients with higher levels of CD26+ Tregs and fewer CD161+ Tregs tend to have worse outcomes. In this study, we found that cytokine-inducible SH2-containing protein (CISH), a known negative regulator of immune activation, is highly expressed in CD26+Tregs compared to CD161+ Tregs. Co-culturing B cells enhanced the expression of CISH and CD26 in CD4+CD25- Treg cells, knockdown of CISH in Tregs reduced CD26 expression and their immune suppression activity of CD8+T cells, while CRISPR knockout of CISH in Karpas 299 cells led to higher expression CD70, a molecule associated with less immunesuppression. Our findings suggest that increased CISH expression in Tregs could result in increased immune suppression and unfavorable outcome in SMZL, suggesting CISH is a potential therapeutic tagrget in SMZL by dempening immunosuppressive property of the Treg cells hence boosting the antitumor immunity. Topic Categories Tumor Immunology: Cellular Responses and Tumor Microevironment (TIME)

Despite notable advancements in treating chronic lymphocytic leukemia (CLL) with targeted therapies, a significant clinical challenge arises as a subset of CLL patients progress and develop Richter's transformation (RT), an aggressive form of lymphoma. While immune cell dysfunction and T cell defects are well-known characteristics of CLL, the alterations in immune cell subsets during CLL progression to RT remain largely unexplored. While CLL patients typically fail to respond to anti-PD1 pembrolizumab, a positive response has been observed in 20-40% of RT patients. Previously, our study involving three RT patients (1 responder and 2 progressors) revealed enriched regulatory T cells (Tregs) in the responders compared to progressors after pembrolizumab treatment (Iyer et al, ASH2020). Hence, we propose that dynamic changes in T cell subsets at baseline may be associated with response to pembrolizumab treatment. To this end, we performed single-cell RNA sequencing on sorted T cells (CD3 +) from PBMCs derived from 20 patients (responders (RES), n=5; stable disease (SD), n=5; progressive disease/progressors (PD), n=10). A total of 408,627 cells were captured, and an average of 1,393 genes were detected per cell per patient. Using a graph-based clustering approach (Seurat V4.3), we identified 19 clusters based on marker genes and transcriptional signatures and identified enriched pathways using Enrichr analysis. Our results showed that RES had an increased Th17 subset at baseline compared to PD (15% vs. 5%, p=0.01) and reduced Th2 T cells compared to SD (p=0.004) and PD (p=0.05). The Th17/Th2 ratio was higher in RES at baseline (Th17/Th2 R: 1.24, PD: 0.21, SD: 0.25, p0.05) and post-pembrolizumab (Th17/Th2 RES: 1.31, PD: 0.34, SD: 0.30, p0.05). Furthermore, RES had an increased fraction of proliferating CD4 T cells at baseline (4% RES vs. 0.4% SD and 0.4% PD, p=0.02) and post-treatment (1.9% RES vs. 0.8% PD and 0.34% SD, p=0.02). Although we observed an increasing trend in the fraction of Tregs in the RES at baseline [(7.6% RES vs.6.1% PD and 6.5% SD, p=0.4; ns) and post-treatment (10.3% RES vs. 8.3% PD and 5.8% SD, p= 0.2; ns] compared to PD and SD, the difference was not significant. Similarly, among CD8+ T cells, we observed an increasing trend in CD8+ effector T cell fraction in the responders at baseline (29.8% RES vs. 21% PD and 15.6% SD, p=0.9, ns) and post-treatment (30.1% RES vs. 21.2% PD and 19.9% SD, p=0.44, ns). However, the difference was not statistically significant. These findings highlight the dynamic changes in T cell subsets associated with pembrolizumab response. In terms of transcriptional changes in Tregs following pembrolizumab treatment among RES, PD, and SD, we observed dynamic changes on a few Treg marker genes, including TIGIT and TOX. TIGIT and TOX expression drastically decreased after treatment in RES (p < 0.0001), while expression did not change in PD and SD. There were no significant changes in the expression of FOXP3 or CD27 in RES, PD, and SD before and after the treatment. In CD8 effector T cells, GZMK, GZMA (granzymes), and PRF1 (perforin) are marker genes. We observed higher expression of GZMK and GZMA in RES (p <0.0001) at the baseline compared to SD and PD. In the proliferating CD4 T cells, we observed increased expression of IDH2 (Isocitrate dehydrogenase 2-key enzyme of TCA cycle) in RES at the baseline, as compared to PD and SD, indicating increased TCA cycle activity in the proliferating T cells. Pathway analysis of T cell clusters using the Enrichr database showed TNFA-IFNG-MYC targets are enriched in CD8 + cells, IL2-STAT5 signaling is upregulated in Th17, TREGs, and E2F cell cycle associated pathways enriched in CD4 + proliferation cluster. In conclusion, our study unveils significant baseline differences in CD4 subsets between RES and PD/SD subjects and dynamic changes in T cell subsets and transcriptional signatures. These findings offer potential predictors of pembrolizumab response in RT, such as increased Th17/Th2 ratio, enriched proliferating CD4 + T cells, and elevated TIGIT, TOX gene expression in Tregs, GZMK, and GZMA in CD8 effector cells. This deeper understanding of the immunological landscape in RT patients sheds light on the interplay between T cell subsets and treatment response in RT, paving the way for personalized therapeutic strategies. Further validation and exploration can lead to improved outcomes and tailored interventions for RT.

Abstract T follicular helper (TFH) cells are a subset of CD4+ T cells that reside within the follicles of secondary lymphoid organs and play an essential role in the germinal center (GC) reaction. To examine the role TFH cells in follicular lymphoma (FL), we first characterized TFH cells using single cell analysis with the high-throughput technologies of mass cytometry (CyTOF) and the Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq). Clustering analysis revealed that TFH cells form subsets with unique phenotypes, and the expression of many common markers including CXCR5, ICOS, IL-21, TOX2, CD57, GZMK, XCL1, XCL2, CXCL13 and CD40L varies on TFH subsets. We found that TFH cells are phenotypically more heterogenous in FL than benign tonsil tissues by both proteomic (n=82) and transcriptomic (n=8) profiling. Each FL patient showed different dominant TFH subsets, in contrast to tonsil donors which were highly homogenous. Some TFH subsets were only present in FL and absent in tonsil tissues, suggesting the existence of FL-specific TFH cells. Cytokines (IL-2, IL12, IL-17 and IL-21) and activated B cells upregulated TFH markers including PD-1, CXCR5 and IL-21 to induce the development of TFH subsets such as IL-21+ or IL-21+IFN-g+ TFH cells, which was inhibited by rapamycin, an immunosuppressor. We observed that the TFH cell frequency significantly correlated with the number of lymphoma B cells. Futhermore, while TFH cells as a whole showed no correlation with prognosis, TFH subsets such as CD57+ TFH cells were significantly associated with an inferior patient outcome. Taken together, our results indicate that TFH cells are highly heterogenous with different tumor-specific TFH subsets present in FL and associated with patient outcomes in FL.

Abstract The tumor microenvironment (TME) plays a crucial role in mediating the tumor immune response, thereby affecting patient outcomes in follicular lymphoma (FL). Using CyTOF, we analyzed a cohort of 82 FL patients with biopsy specimens collected before the first treatment regimen was administered. Our results showed that there was a difference in the T-cell phenotype in patients with various TMEs. Patients with TMEs rich in monocyte/macrophages/NK cells had more CD8+ cells and tended to have fewer TN, but more TEMRA and TEXH cells. Patients enriched with T cells exhibited a T-cell phenotype skewed toward to TCM and patients with B cell dominance tended to have significant higher number of TFH cells. T-cell phenotypes with more terminally differentiated, senescent and exhausted cells were highly represented in patients with less T cells when compared to patients with more T cells. We observed that CD57+ TFH cells was significantly more abundant in patients who had disease progression than patients who had complete response to therapy, suggesting a role for CD57+ TFH cells in promoting malignant cell growth in FL. Consistent with this finding, we observed that increased numbers of CD57+ TFH cells correlated with an inferior survival in FL. Using CITE-seq technology, we found that CD57+ TFH cells exhibited a substantially different transcriptome from CD57− TFH cells. Genes that were differentially upregulated in CD57+ TFH cells when compared to CD57− TFH cells included genes involved in cell survival, compromised inflammatory response, and metabolic activation. Taken together, our results indicate different tumor microenvironments among patient groups that is associated with variable T-cell phenotypes.

Abstract T cell Ig and ITIM domain (TIGIT) is an immune checkpoint molecule and its ligation delivers an inhibitory signal to T cells that negatively regulates anti-tumor responses. However, the expression and biological relevance of TIGIT in B-cell non-Hodgkin lymphoma (NHL) is completely unknown. To phenotypically characterize TIGIT+ T cell subsets, we profiled TIGIT-expressing CD4+ and CD8+ T cells from biopsy specimens of B-cell NHL. TIGIT expression was not detectable on T cells from peripheral blood, however, TIGIT is constitutively expressed on CD4+ T cells from biopsy specimens of B-cell NHL with a median of 44.8% (range: 25.9–62.2, n=8) of CD4+ T cells expressing TIGIT. By profiling the CD4+TIGIT+ T cells, we observed that CD25 was highly expressed on intratumoral CD4+TIGIT+ T cells. Intracellular staining revealed that Foxp3 was expressed by intratumoral CD4+TIGIT+ T cells. These intratumoral CD4+TIGIT+ T cells expressed high level of chemokine receptor CCR4 and were absent of IL-7 receptor-α (CD127). Functionally, CD4+TIGIT+ T cells displayed reduced cytokine production, as the number of IFN-γ- and TNF-α-producing cells was lower in the TIGIT+ population than in TIGIT− T cells. While TIGIT expression can be induced by TCR activation, treatment of T cells with IL-2 and TGF-β inhibited TCR-mediated TIGIT induction. Furthermore, lymphoma B cells were involved in TIGIT induction as in vitro depletion of lymphoma B cells altered upregulation of TIGIT on CD4+ T cells in B-cell NHL. Taken together, these results indicated that constitutive expression of TIGIT defines a CD4+ population with similar phenotype to regulatory T cells. Inhibition of TIGIT signaling may be an additional mechanism to prevent T-cell suppression in B-cell NHL