Wu, Hongyan

Abstract The tumor microenvironment plays a crucial role in mediating the tumor immune response, thereby affecting patient outcomes in follicular lymphoma (FL). Using CyTOF, we analyzed single cell suspensions created from pre-treatment biopsies in a cohort of 82 FL patients and retrospectively extracted patient clinical parameters. Hierarchical analysis of the tumor microenvironment composition stratified these patients into 4 groups: group 1 represents patients with high percentage of monocyte/macrophages/NK cells; patients from group 2 and 3 are rich of intratumoral T and B cells, respectively. Patients with intermediate number of T and B cells are classed into group 4. Intratumoral T cells from these 4 groups exhibited distinct phenotypical characteristics. Group 1 was enriched with KLRG1 +CD8 + T cells, while group 4 showed increased number of CXCR3 - T EM and CD4 + T N cells. Patients from group 2 and 3 featured with increased number of ICOS + T reg cells and CD57 + T FH cells, respectively. We observed that higher numbers of T cells significantly correlated with early disease stage, lack of B-symptoms, event-free survival at 24 months (EFS24) and a favorable overall and EFS survival in patients with histological grade 1 and 2. However, this association was not seen in patients with histological grade 3a and b, suggesting that T cell-mediated anti-tumor immunity is preserved in low grade patients, but overridden in higher grade patients. CITRUS analysis revealed that a cluster that is CD57 + and PD-1 high was significantly more abundant in patients who had disease progression than patients who had a complete response to therapy, suggesting a role of CD57 + T FH cells in promoting malignant cell growth in FL. Consistent with this finding, we observed that higher number of CD57 + T FH cells correlated with an inferior survival in FL. Using CITE-seq technology, we found that CD57 + T FH cells exhibited a substantially different transcriptome when compared to CD57 - T FH cells. Genes that were differentially upregulated in CD57 + T FH cells when compared to CD57 - T FH cells included genes involved in cell survival, compromised inflammatory response, and metabolism activation including GZMK, CCL4, CST7, DUSP2, LGALS3, CYTOR, CHI3L2, SYNE2, CXCL13, CD27 and FABP5. Taken together, our results indicate different tumor microenvironments among FL patient groups that is associated with variable T-cell phenotype. We found that CD57 + T FH cells play an important role in predicting disease progression and patient prognosis in FL. Figure 1 Figure 1. Disclosures Novak: Celgene/BMS: Research Funding. Ansell: Bristol Myers Squibb, ADC Therapeutics, Seattle Genetics, Regeneron, Affimed, AI Therapeutics, Pfizer, Trillium and Takeda: Research Funding.

Background CD8+ T-lymphocyte subsets defined by killer lectin-like receptor G1 (KLRG1) and CD127 expression have been reported to have an important role in infection, but their role in the setting of lymphoid malignancies, specifically follicular lymphoma (FL), has not been studied. Methods To characterize the phenotype of KLRG1/CD127-defined CD8+ subsets, surface and intracellular markers were measured by flow cytometry and Cytometry by time of flight (CyTOF), and the transcriptional profile of these cells was determined by CITE-Seq (Cellular Indexing of Transcriptomes and Epitopes by Sequencing). The functional capacity of each subset was determined, as was their impact on overall survival (OS) and event-free survival (EFS) of patients with FL. Results We found that intratumoral CD8+ cells in FL are skewed toward effector cell subsets, particularly KLRG+CD127- and KLRG1-CD127- cells over memory cell subsets, such as KLRG1-CD127+ and KLRG1+CD127+ cells. While effector subsets exhibited increased capacity to produce cytokines/granules when compared with memory subsets, their proliferative capacity and viability were found to be substantially inferior. Clinically, a skewed distribution of intratumoral CD8+ T cells favoring effector subtypes was associated with an inferior outcome in patients with FL. Increased numbers of CD127+KLRG1- and CD127+KLRG1+ were significantly associated with a favorable OS and EFS, while CD127-KLRG1- correlated with a poor EFS and OS in patients with FL. Furthermore, we demonstrated that interleukin (IL)-15 promotes CD127-KLRG1+ cell development in the presence of dendritic cells via a phosphoinositide 3-kinase (PI3K)-dependent mechanism, and treatment of CD8+ T cells with a PI3K inhibitor downregulated the transcription factors responsible for CD127-KLRG1+ differentiation. Conclusions Taken together, these results reveal not only a biological and prognostic role for KLRG1/CD127-defined CD8+ subsets in FL but also a potential role for PI3K inhibitors to manipulate the differentiation of CD8+ T cells, thereby promoting a more effective antitumor immune response.

Abstract Purpose: T-cell immunoglobulin and ITIM domain (TIGIT), a member of the immune checkpoint family, is important in normal T-cell biology. However, the phenotypical profile and clinical relevance of TIGIT in follicular lymphoma is largely unknown. Experimental Design: Biopsy specimens from a cohort of 82 patients with follicular lymphoma were analyzed using mass cytometry to explore the phenotype and biological and clinical significance of TIGIT+ T cells. Results: TIGIT is highly expressed on intratumoral T cells and its expression alters T-cell phenotype in follicular lymphoma. TIGIT is abundantly expressed on Treg cells, resulting in an enhanced suppressive property. TIGIT expression on non-Treg/TFH T cells defines a population that exhibits an exhausted phenotype. Clinically, increased numbers of TIGIT+ T cells are associated with inferior patient outcomes and poor survival. We observe that anti–PD-1 therapy with pembrolizumab alters the phenotype of TIGIT+ T subsets and identifies a role for CD28 expression on TIGIT+ T cells in treatment response. Conclusions: The current study provides a comprehensive analysis of the phenotypic profile of intratumoral TIGIT+ T subsets and their prognostic relevance in follicular lymphoma. Inhibition of TIGIT signaling may be an additional mechanism to prevent T-cell suppression and exhaustion in B-cell lymphoma.

The outcomes of lymphoma patients treated with PD1 inhibitors (PD1i) vary significantly across different histologies with objective responses rates that are around 70% in classical Hodgkin lymphoma, but significantly lower, around 10%, in indolent non-Hodgkin lymphomas (iNHL). This may be due in part to the inability of PD1i to restore the function of exhausted T-cells (Tex) in the tumor microenvironment (TME). PD1 is expressed on various T-cell subsets, including effector cells and Tex. In this study we sought to identify markers of exhaustion beyond PD1 that define T-cell subsets with high reactivation potential in marginal zone lymphoma (MZL). To define different stages of exhaustion in MZL, we developed and validated a mass cytometry (CyTOF) panel which integrates T-cell markers of lineage, differentiation, activation, suppression, cytokine production and transcription factors associated with exhaustion. We analyzed 35 MZL spleens obtained at diagnosis and 6 reactive spleens. We identified a population of CD8 cells in MZL that express TIM3 without PD1, compose 1.5% (range 0.14-4.88%) of total CD8 cells and expand with activation through the TCR (6.2% of CD8, range 0.6-14.2%). Prolonged cytokine exposure has been shown to induce exhaustion in healthy T-cells, and so to determine whether PD1-TIM3+ cells are Tex, we treated healthy donor T-cells with activating beads and IL12 and analyzed them by flow cytometry. We showed that PD1-TIM3+ cells expand with repetitive activation and IL12 treatment suggesting that they are Tex. Since Tex have been shown to have a distinct transcription profile compared to functional effector T-cells, we analyzed the expression of several transcription factors (TFs) that are upregulated in Tex by CyTOF and compared them to other subsets of T-cells. PD1-TIM3+ cells expressed higher levels of Eomes, Tbet, TOX and Helios compared to activated effector cells, confirming that they are Tex, but lower levels levels of the same TFs compared to PD1+TIM3+ cells, consistent with a less severely exhausted phenotype. To characterize the function of PD1-TIM3+ cells, we manually gated on subsets of CD8+ non-naïve cells that were stained with the CyTOF panel and compared the different subsets. We showed that PD1-TIM3+ cells arise from effector cells, maintain their polyfunctionality by producing cytokines and chemokines and have a unique cytokine production profile, including perforin, granzyme B and proinflammatory cytokines, such as IL17A. Importantly, PD1-TIM3+ cells produced higher levels of most cytokines compared to more severely Tex expressing both PD1 and TIM3 (Fig 1). We then performed tSNE analysis where similar objects are modeled by nearby points. We determined that PD1-TIM3+ cells cluster together, suggesting that they are phenotypically homogeneous cells in terms of function and expression of activation markers and are significantly different from PD1+TIM3+ cells (Fig 2). We finally blocked PD1 or TIM3 and analyzed the effect of each antibody blockade on function. We showed that TIM3 blockade was able to restore the production of most cytokines to higher degrees than PD1 blockade. In addition, TIM3 blockade led to upregulation of CD28, which is critical for the rescue of Tex through costimulation, while PD1 blockade did not. We then analyzed the clinical outcomes of all 34 MZL patients. The frequency of PD1-TIM3+ cells was lower among observed patients who failed to achieve an event-free survival (EFS) of 12 months (EFS12) (0.8% vs 1.7%, p=0.02) and among treated patients that failed an EFS of 24 months (EFS24) (0.9 vs 1.7%, p=0.03), when compared to patients that reached these endpoints. Higher levels of PD1-TIM3+ cells were also associated with a trend towards improved overall survival (OS). Five-year OS was 88% vs. 69% in patients with PD1-TIM3+ levels >2% and <2% of total CD8 cells respectively (p=0.1) (Fig 3). Our study provides insights into the mechanisms of failure of PD1i in MZL and identifies a novel population of Tex with high reactivation potential which is clinically relevant and could serve as a target for future immunotherapies in iNHL. Disclosures Anagnostou: American Society of Hematology, Mayo Clinic/Iowa Lymphoma SPORE, Mayo Clinic Immune Monitoring Core, Mayo Clinic Hematology Small Grant: Research Funding. Novak:Celgene Coorperation: Research Funding. Ansell:Mayo Clinic Rochester: Employment; Trillium: Research Funding; Seattle Genetics: Research Funding; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Affimed: Research Funding; LAM Therapeutics: Research Funding; Affimed: Research Funding; Seattle Genetics: Research Funding; LAM Therapeutics: Research Funding; Mayo Clinic Rochester: Employment; Bristol-Myers Squibb: Research Funding; Mayo Clinic Rochester: Employment; Trillium: Research Funding; Seattle Genetics: Research Funding; Bristol-Myers Squibb: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; Regeneron: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; Regeneron: Research Funding; LAM Therapeutics: Research Funding; Affimed: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; Trillium: Research Funding; Regeneron: Research Funding; Affimed: Research Funding; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Regeneron: Research Funding; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; Trillium: Research Funding; Seattle Genetics: Research Funding; Seattle Genetics: Research Funding; Trillium: Research Funding; Regeneron: Research Funding; Affimed: Research Funding; LAM Therapeutics: Research Funding; Affimed: Research Funding; LAM Therapeutics: Research Funding; Regeneron: Research Funding; Affimed: Research Funding; Trillium: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; Affimed: Research Funding; Affimed: Research Funding; Seattle Genetics: Research Funding; LAM Therapeutics: Research Funding; Bristol-Myers Squibb: Research Funding; Trillium: Research Funding; LAM Therapeutics: Research Funding; Bristol-Myers Squibb: Research Funding.

Abstract Effector CD8+ T cells play a crucial role in anti-tumor immunity. Two major subsets of effector CD8+ T cells have been identified based on expression of KLRG1 and CD127: KLRG1+CD127- short-lived effector cells (SLECs) and KLRG1-CD127+ memory precursor effector cells (MPECs). In B-cell non-Hodgkin lymphoma (NHL), the frequency and function of SLECs and MPECs are unknown. Furthermore, the underlying mechanism by which these two CD8+ subsets were regulated and differentiate in B-cell NHL remains poorly understood. The goal of the present study is therefore to phenotypically and functionally characterize SLECs and MPECs in B-cell NHL. Using patient biopsy specimens, we observed that the median percentage of SLECs was greater than MPECs and was 39.9% (range: 22.7%~ 54.7%) and 18% (range: 7.66%~31.6%), respectively. In controls, the median percentage of SLECs was lower than that of MPECs and was 13.71% (range: 5.26%~29.2%) and 51.63% (range: 22.5%~70.1%) in PBMC and 12.14% (range: 4.01%~26%) and 51.62% (range: 29.2%~70.3%) in tonsil, respectively. Using mass cytometry (CyTOF), we observed that SLECs have higher expression levels of TIGIT and PD-1 and lower expression of CCR7, CD26 and CD27 when compared to MPECs. SLECs were functionally superior to MPECs as the numbers of cytokine (IFN-γ and TNF-α) - and granule (granzyme B and perforin)-producing cells were higher in SLECs than MPECs. However, SLECs had a lower proliferative capacity and a higher apoptosis rate when compared to MPECs. We observed that a reciprocal differentiation pathway exists between SLECs and MPECs. Activation and cytokine stimulation (IL-2 and IL-15) promoted the development of SLECs and decreased the number of MPECs. This effect was reversed when cells were treated with neutralizing antibodies to block IL-2 or IL-15 signaling. We also found that these two subsets had a distinct transcription factor profile as SLECs had higher expression of Eomes and T-bet, and lower expression of Tcf-1than MPECs. IL-2 and IL-15 enhanced the expression of T-bet and decreased the expression of Tcf-1. Taken together, our results show that SLECs are more prevalent than MPECs in B-cell NHL when compared to normal control tissue. These two effector cell subsets have distinct phenotypical and function profiles and their development is controlled by cytokines that may be dysregulated in lymphoma. Despite the fact that SLECs produce more granzyme B and IFN-γ, they are less proliferative and more susceptible to apoptosis. This may compromise an effective anti-tumor immune response in B-cell NHL. Disclosures Ansell: Celldex: Research Funding; Takeda: Research Funding; Merck & Co: Research Funding; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; Trillium: Research Funding; Regeneron: Research Funding; LAM Therapeutics: Research Funding; Pfizer: Research Funding; Seattle Genetics: Research Funding.

Abstract T cell Ig and ITIM domain (TIGIT) is an immune checkpoint molecule that is expressed on a variety of cell types including NK cells, effector and memory T cells, and Treg cells. Upon ligation with CD155, TIGIT delivers an inhibitory signal and negatively regulates anti-tumor responses. While important in normal T-cell biology, the pathological significance of TIGIT expression and function in the tumor microenvironment of the patients with follicular lymphoma (FL) is largely unknown. The present study sought to phenotypically and functionally characterize TIGIT+ T cell subsets in FL. While its expression is not detected on resting T cells in peripheral blood, we found that TIGIT is highly expressed on intratumoral T cells from FL. Treatment with cytokines such as IL-4 and TGF-β downregulated TIGIT expression on T cells. We found that TIGIT is predominantly expressed on effector memory T cells (TEM) with an activation/exhausted phenotype, and TIGIT+ T cells have higher expression levels of CD69 and PD-1 when compared to TIGIT- T cells. Functionally, TIGIT+ T cells displayed reduced capacity of cell proliferation and cytokine production (IFN-γ and IL-2). Using mass cytometry (CyTOF), we observed that TIGIT is abundantly expressed on some intratumoral Treg (CD4+CD25+Foxp3+) cells, while other Treg cells lack TIGIT expression in FL, forming two subsets of Treg cells: CD4+CD25+TIGIT+ and CD4+CD25+TIGIT-. These two subsets are phenotypically distinct in that CD25+TIGIT+ cells exhibited increased expression of activation/costimulatory markers such as CD69, CD27 and CD28 compared to CD25+TIGIT-, suggesting an activated Treg subset of CD25+TIGIT+ cells. This CD25+TIGIT+ subset had increased suppressive function and could more effectively inhibit activation and proliferation of CD8+ T cells than CD25+TIGIT- cells. Furthermore, we found that lymphoma B cells promoted the development of TIGIT-expressing T cells as TGF-β-mediated downregulation of TIGIT on T cells was inhibited when CD19+ lymphoma cells were present. Using a cohort of 31 FL patients, we found that intratumoral TIGIT-expressing T cells were associated with a favorable prognosis. Patients with TIGIT+ T cell numbers greater than 50% had better overall survival than patients with TIGIT+ T cell numbers less than 50%. Taken together, our results reveal a role of TIGIT in defining Treg cell subsets with different immune function and TIGIT expression may be useful in predicting patient outcome in FL. Disclosures Ansell: Takeda: Research Funding; Bristol-Myers Squibb: Research Funding; Pfizer: Research Funding; Seattle Genetics: Research Funding; Celldex: Research Funding; Regeneron: Research Funding; LAM Therapeutics: Research Funding; Trillium: Research Funding; Affimed: Research Funding; Merck & Co: Research Funding.