Citations

Cancer cells have altered energy demand due to their increased proliferative capacity. In Waldenstrom Macroglobulinemia (WM), an indolent yet incurable B-cell lymphoma, the homeostasis of the bone marrow (BM) environment is disturbed due to the infiltration of the lymphoplamacytic cells that continuously produce monoclonal IgM. An alteration in energy demand could skew the balance of key proteins and metabolites towards a permissive niche for WM tumor cells growth, and unfavorably effect on the immune response against tumor cells. Therefore, the aim of our study was to identify how changes in certain metabolites and/or proteins could contribute to the pathobiology of WM and whether the cytokine and chemokine composition of the BM microenvironment play a role in such changes. WM patient's samples including BM plasma, peripheral blood serum and BM cells (n=101) as well as equivalent normal counterparts (n=86) were collected and used for metabolomics analysis. Comprehensive targeted metabolomics analysis was performed using Capillary Electrophoresis Time-of-Flight Mass spectrometry (CE-TOFMS), CE-triple quadrupole mass spectrometry (CE-qQqMS) and Liquid Chromatography (LC-TOFMS). Normal and WM peripheral blood serums samples were also used for untargeted proteomics analysis using a fully automated proteomic technology platform that includes an Agilent 1200 Series Quaternary HPLC system connected to a Q Exactive Plus mass spectrometer. Real-time PCR analysis was performed to detect the gene expression of the relevant metabolite transporters located on the cell membrane. BM cells from control and WM patients' samples were used for flow cytometry analysis. IHC was used to detect the proteins on the BM tissues. Principal Component Analysis (PCA) and Hierarchal Clustering Analysis (HCA) on both metabolomics and proteomics data identified two distinct clusters for disease and normal samples, indicating that there are differentially expressed proteins and metabolites in WM versus normal samples. Furthermore, pathway analysis showed that the majority of the altered metabolites were the members of the glutathione (GSH) metabolism pathway. This finding was further validated not only by data obtained from metabolomics analysis of BM cells and BM plasma, but also by proteomic data WM patients serum, implying that GSH metabolism is key to the biology of WM. Moreover, stimulation of WM cell lines by IL-6 and IL-21, cytokines involved in inducing WM cell proliferation and IgM secretion, resulted in increased gene expression of the transporters mediating uptake of metabolites required for GSH synthesis, including SLC7A11, 4F2HC and LAT1, indicating that cytokines in the WM BM could modulate GSH metabolism. In addition, IHC staining of the BM tissues as well as flow cytometry analysis of patients' lymphoplasmacytic cells identified glutathione peroxidase as one of the major proteins modulating GSH metabolism in WM. In summary, our data highlight a central role for GSH metabolism in WM disease biology and indicate that intervening with the metabolic processes could be a potential therapeutic strategy for patients with WM. Disclosures Ansell: AI Therapeutics: Other: research funding for clinical trials; Seattle Genetics: Other: research funding for clinical trials; Regeneron: Other: research funding for clinical trials; Affimed: Other: research funding for clinical trials; Bristol Myers Squibb: Other: research funding for clinical trials; Pfizer: Other: research funding for clinical trials; Merck: Other: research funding for clinical trials; Takeda: Other: research funding for clinical trials.

Myeloid derived suppressor cells (MDSC) are a heterogeneous population of undifferentiated myeloid cells that are expanded and activated in pathological conditions and have the ability to potently suppress T-cell function and thereby contribute to immunosuppression and tumor progression. While there have been studies showing a role for MDSC in a variety of hematological malignancies, no data is available indicating that MDSCs contribute to the tumor progression in Waldenstrom's Macroglobulinemia (WM), an indolent lymphoma characterized by bone marrow (BM) infiltration of lymphoplasmacytic (LPL) cells and increased secretion of monoclonal IgM. In previous work, we have found increased GM-CSF and reduced arginine and cysteine in the BM microenvironment in WM. We hypothesized that this was due to the presence and activity of MDSCs in WM. BM aspirates from WM patients (n=17) were therefore processed to isolate LPL (CD19+/CD138+) cells from the rest of the BM cells (CD19-/CD138-). Sorted (CD19-/CD138-) cells from BM of patients with WM were studied with flow cytometry. Using a sequential gating strategy (lack of lineage markers, low levels of HLADR, CD33+, CD11b+) we identified a population of MDSCs that were then subdivided using CD14 and CD15 expression into total-, monocytic-, or granulocytic- MDSCs (m-MDSC, g-MDSC). We also analyzed unsorted BM cells using cytometry by time-of-flight (CyTOF) in order to further identify and phenotypically characterize the BM MDSC population in a group of WM patients with smoldering (asymptomatic) disease, symptomatic disease, or in remission post-treatment. BM samples from normal subjects were used as a control. Flow cytometry data showed significant higher numbers of MDSC subsets expressing PD-L1 and Arginase1 in WM patients when compared to the normal samples. BM cells from WM patients (n=18) then were compared to controls (n=11), and the absolute number of the total MDSC (p=0.05), m-MDSC (p=0.002), g-MDSC (p=0.02) was increased in WM specimens. When MDSCs from WM or normal monocytes from healthy controls were co-cultured with activated T-cells, the proliferation of activated T-cells in the presence of MDSCs from WM patients was impaired compared to controls, confirming the suppressive role of MDSCs. We then performed high dimensional analysis of the total BM MDSC cells using t-SNEand identified phenotypically distinct MDSC cell populations in the BM that were differentially present when healthy controls were compared to patients with smoldering WM or those with WM needing treatment. Specifically, WM patients needing treatment had increased numbers of a distinct MDSC population that was highly positive for CD163, and CD138. Moreover, conventional markers denoting m-MDSC and g-MDSC, such as CD14 and CD15, were highly expressed in all populations and their pattern of expression did not specifically define the MDSC subtypes, indicating that high dimensional phenotyping further details the MDSC sub-compartments beyond the conventional categorization of MDSC using conventional cytometry. In summary, we find that MDSCs are increased in the BM of WM patients compared to controls. MDSCs expressing CD163 and CD138 increase when WM patients become symptomatic and require therapy. Furthermore, MDSCs in the BM of WM patients suppress T-cell function and likely contribute to progression of the disease. MDSCs in the BM therefore present a therapeutic target that should be explored in WM patients. Disclosures Ansell: Bristol Myers Squibb: Other: research funding for clinical trials; Merck: Other: research funding for clinical trials; AI Therapeutics: Other: research funding for clinical trials; Affimed: Other: research funding for clinical trials; Takeda: Other: research funding for clinical trials; Pfizer: Other: research funding for clinical trials; Regeneron: Other: research funding for clinical trials; Seattle Genetics: Other: research funding for clinical trials.

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.

Introduction: New Diffuse Large B-cell (DLBCL) treatments remain a clinical need despite the success of rituximab combined with CHOP chemotherapy (RCHOP), which results in durable responses in 60-70% of patients. Those refractory to, or who relapse following, first-line therapy have a very poor outcome, with only 20% surviving beyond 5 years. Rationally-targeted frontline strategies are needed, especially for those with high-risk disease. Significant advances have been made in the genomic classification of DLBCL, but none have impacted the design of phase III trials for untreated DLBCL patients. Building on new genetic profiling studies to personalize clinical treatment, an NCI initiative, could allow clinicians to add targeted therapies to the RCHOP backbone based on individual tumor signatures. The phase II ECOG-ACRIN1412 trial, which compared RCHOP combined with lenalidomide (R2CHOP) versus RCHOP showed significantly superior event free survival (EFS) and overall survival benefits for those treated with R2CHOP. Herein, we report the profile of a high-risk ABC/non-GCB subset of DLBCL driven by genomic alterations in inflammatory genes that are susceptible to front-line R2CHOP, but continue to experience poor outcome with RCHOP alone. Methods: We studied a total of 196 DLBCL patients. 47 were treated with R2CHOP from an investigator-initiated, open-label, single-arm phase II study (NCT00670358). 149 were newly diagnosed DLBCL cases treated with RCHOP, or R-immunochemotherapy (herein called RCHOP), and followed prospectively through the Molecular Epidemiology Resource (MER) of the University of Iowa/Mayo Clinic SPORE that served as a contemporary cohort. Patients from each treatment group were divided based on their event free survival at 24 months (EFS24). DNA alterations within these populations were identified through whole exome sequencing (WES). Variants were analyzed for their presence in EFS24 achievement or failure groups in both RCHOP and R2CHOP. Both tumor and germline sequencing was performed for 47/47 R2CHOP cases and 49/149 RCHOP cases. Gene expression data from the PanCan panel of 730 B-cell-related genes was analyzed to determine gene expression profiles characteristic of the high-risk/R2CHOP-profile on 59 available non-GCB DLBCL cases (45 RCHOP; 14 R2CHOP). A two-sided comparative marker analysis T statistic test was applied to assess what genes displayed differential expression based on achieving EFS24 in both R2CHOP and RCHOP populations. Positive values represented associations with achieving EFS24 and negative values were associated with cases of EFS24 failure. Results: Three genes were enriched in the RCHOP cases that failed EFS24 but achieved EFS24 with R2CHOP among non-GCB patients: PIM1, SPEN, and MYD88 (L265P), herein referred to as Responder Alterations. In R2CHOP cases, patients with a Responder Alteration had a better overall EFS (P = 0.051) compared to wild type patients. In contrast, RCHOP treated patients with a Responder Alteration in their tumor had a significantly worse overall EFS (P = 0.0004) compared to patients without a mutation. Together, PIM1, SPEN, or MYD88 (L265P) mutations were present in 38.0% (30/79) of all non-GCB cases. Collective R2CHOP and RCHOP EFS24 differential gene expression T values were significantly different for 18 previously-defined signatures. The R2CHOP cases that achieved EFS24 were enriched for genes involved in cell cycle, JAK-STAT, cytokine signaling, and NF-κB pathways based on these signatures and ontology analyses. Lastly, cases with WES and PanCan data were analyzed together to observe differential gene expression patterns between cases with and without signature mutations. These data suggest that R2CHOP disrupts tumors reliant on IRF4, NF-κB, and STAT transcription factors, leading to a loss of proliferative feedback systems. Conclusions: Our combined analysis of DNA and RNA across R2CHOP and RCHOP treatment cohorts identifies a high-risk non-GCB phenotype that encompasses approximately 38% of non-GCB patients, is capable of sustaining JAK-STAT and NF-κB signaling, and is sensitive to R2CHOP. Our study lays the groundwork for a precision therapy approach in DLBCL in which DNA or RNA profiles can be used to identify patients early in treatment who may not benefit from the current standard of care, RCHOP, and who would benefit from the addition of lenalidomide or other targeted agents. Disclosures Gandhi: Celgene Corporation: Employment, Equity Ownership, Patents & Royalties. Ansell:LAM Therapeutics: Research Funding; Seattle Genetics: Research Funding; LAM Therapeutics: Research Funding; Seattle Genetics: Research Funding; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; Affimed: Research Funding; Trillium: Research Funding; Trillium: Research Funding; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; Trillium: Research Funding; Affimed: Research Funding; LAM Therapeutics: Research Funding; Bristol-Myers Squibb: Research Funding; Trillium: Research Funding; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; Trillium: Research Funding; LAM Therapeutics: Research Funding; Bristol-Myers Squibb: Research Funding; Regeneron: Research Funding; Affimed: Research Funding; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; LAM Therapeutics: Research Funding; LAM Therapeutics: Research Funding; LAM Therapeutics: Research Funding; Regeneron: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding; Seattle Genetics: Research Funding; Trillium: Research Funding; Trillium: Research Funding; Affimed: Research Funding; Affimed: Research Funding; Mayo Clinic Rochester: Employment; Mayo Clinic Rochester: Employment; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Affimed: Research Funding; Regeneron: Research Funding; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Mayo Clinic Rochester: Employment; Trillium: Research Funding; Affimed: Research Funding; Mayo Clinic Rochester: Employment; Bristol-Myers Squibb: Research Funding; Affimed: Research Funding; LAM Therapeutics: Research Funding. Cerhan:Celgene: Research Funding; NanoString: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees. Nowakowski:Curis: Research Funding; Bayer: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; F. Hoffmann-La Roche Ltd: Research Funding; Genentech, Inc.: Research Funding; MorphoSys: Consultancy, Research Funding; NanoString: Research Funding; Selvita: Membership on an entity's Board of Directors or advisory committees. Novak:Celgene Coorperation: 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.

Abstract Background: B-cell non-Hodgkin lymphomas (NHL) are common lymphoid malignancies in which malignant B-cells arrested at various stages of differentiation proliferate within lymph nodes and occasionally other tissues. The microenvironment that supports the growth and survival of NHL B cells consists of a complex network of immune cells and cytokines and its specific composition has been shown to have significant clinical implications. The intratumoral immune cells include effector and regulatory T (Treg) lymphocytes that are more than simple residual elements from the normal lymph node structure. We previously explored whether the extent of T cell infiltration played a role in the clinical outcome of patients with B-cell NHL and found that an increased percentage of CD4+ T cells in the diagnostic biopsy of lymphoma patients significantly correlated with an improved 5-year overall survival. We have also shown that intratumoral Treg cells significantly suppress the anti-tumor response. Based on the fact that intratumoral T-cells are important in B-cell NHL, we evaluated whether genetic variation in genes that regulate the T-cell response may be associated with lymphoma risk. Methods: We genotyped 257 single nucleotide polymorphisms (SNPs) from 50 candidate genes related to T-cell differentiation and function in a clinic-based study of 441 Caucasian NHL cases and 475 frequency matched Caucasian controls seen at the Mayo Clinic from 2002–2005. Tagging and nsSNPs were selected from HapMap. The most prevalent homozygous genotype was used as the reference group and each SNP was modeled individually as having a log-additive effect, expressed as ordinal odds ratios (OR) per variant allele and 95% confidence intervals, in an age- and sex-adjusted logistic regression analysis. We also evaluated the consistency of the findings for the most common types of B-cell NHL - diffuse large B-cell lymphoma (DLBCL), follicular lymphoma (FL), and CLL/SLL. For gene-level analyses, we used principal components (PC) analysis using all SNPs from a gene; those PCs that explained > 90% of the variability were then modeled in a logistic regression analysis and significance was determined using a likelihood ratio test. We also evaluated the association of haplotypes from each gene with risk of NHL using the score test implemented from HAPLO.SCORE. Results. The mean age at diagnosis was 60.1 years for cases and 58% were male; among controls, the mean age at enrollment was 61.7 years and 55% were men. In the PC gene analyses, PRF1 (perforin gene - involved in cytotoxicity; p=0.004), CD276 (B7-H3 gene - involved in co-stimulation; p=0.01), TBX21 (T-bet gene – regulates Th1 cell development; p=0.02), and IL6 (p=0.02) were significant at p<0.05; haplotype analysis showed similar results, with the addition of CARD15 (NOD2 gene – regulates Th1 responses; p=0.02). There were 2 SNPs in PRF1, and both the intronic SNP rs3758562 (OR=1.38; 1.13–1.69) and the synonymous coding SNP rs885821 (OR=0.80; 0.63–1.02) were associated with NHL risk overall and for each subtype. There were 2 SNPs in CD276, and both the intronic SNP rs7176654 (OR=1.29; 1.07–1.56) and the mrna-utr SNP rs3816661 (OR=0.82; 0.68–0.99) were associated with NHL risk overall and with the CLL/SLL and follicular NHL subtypes specifically. There were 2 SNPs in TBX21, and only the mrna-utr SNP rs7502875 (OR=0.73; 0.59–0.92) was associated with NHL risk overall and for each subtype. There were 11 SNPs in IL6, and the intronic SNP rs2069835 (OR=1.88; 1.24–2.84) and the locus-region SNP rs2069824 (OR=1.73; 1.20–2.50) were each associated with NHL risk overall and each subtype. Finally, there were 9 SNPs in CARD15, with only the nonsynonymous coding SNP rs5743291 (OR=1.43; 1.02–1.98) being associated with overall NHL risk, and risk was specific to FL. Conclusions. Genetic variation in several genes that play critical roles in T-cell maturation and function was associated with lymphoma risk. These genes appeared to be associated with the differentiation and function of effector T-cells particularly Th1 and Th17 cells. These results provide potentially important insights into the role of T-cells in lymphomagenesis.

Abstract Background: Cutaneous T-cell lymphoma (CTCL) is an incurable lymphoproliferative disorder characterized by the clonal expansion of malignant CD4+ T cells. Currently there is a poor understanding of the underlying mechanisms in the development and progression of this disease. Members of the TNF superfamily have been shown to be important mediators in the formation and regulation of normal T cell responses. A proliferation-inducing ligand (APRIL), a newly identified member of the TNF superfamily, has been shown to stimulate tumor cell growth as well as proliferation of primary B and T lymphocytes. APRIL transcript levels are reported to be low in normal tissues with the highest levels found in peripheral blood leucocytes. In contrast, higher mRNA levels have been detected in tumor cell lines and primary tumor tissues and various tumor cell lines have been shown to respond to APRIL with increased tumor cell proliferation and decreased apoptosis. The striking effects of APRIL on tumor cell growth and survival raise the possibility that the APRIL and its receptors-TACI and BCMA may be involved in the pathogenesis and maintenance of T cell malignancies. Goal: To explore the involvement of APRIL on normal and malignant T cell growth and survival. Results: Under resting conditions, there was minimal APRIL binding to normal T-cells and no TACI or BCMA expression. However, stimulation of resting T cells with OKT3 (anti-CD3) or a combination of PMA and ionomycin resulted in an increase in APRIL binding and TACI expression on a subset of activated T-cells. When CD3+ resting human T cells were cultured in the presence of APRIL, IL-2, or OKT3 alone or a combination, normal T cells had greater viability compared to the nil control and APRIL mediated-T cell survival was similar level to that seen with IL-2 or OKT3 alone. CSFE labeled T cells were activated with suboptimal dose of OKT3 and incubated in the presence of APRIL and /or IL-2. Both APRIL and IL-2 alone induced cell proliferation, while treatment with the combination of APRIL and IL-2 had a synergistic effect on T cell proliferation. Malignant T cells isolated from the blood of patients with Sezary Syndrome exhibited a similar pattern of APRIL binding and APRIL also enhanced their survival. Gene array experiments were performed to identify genes involved in APRIL-mediated survival. In normal and primary malignant T cells the anti-apoptotic genes BCL2A1, BIRC6, CHK1, MCL-1, and MDM2 were upregulated and the pro-apoptotic genes CASP5, DR5, and TNFR2 were downregulated in response to APRIL. Conclusion: APRIL promotes the survival of normal and malignant T cells and co-stimulates CD3-mediated T cell proliferation. The gene array experiments suggest that APRIL regulates the expression of anti-apoptotic and pro-apoptotic genes in both normal and malignant T cells. Taken together, these data indicate an important role for APRIL in the biology of normal T cells and in the pathophysiology of T cell lymphoma.

Abstract Background: Patients with newly diagnosed, advanced-stage, follicular B-cell non-Hodgkin’s lymphomas (NHL) commonly receive rituximab as initial therapy. While antibody dependent cytotoxicity (ADCC) is felt to be the predominant mechanism of action for rituximab, the immunologic effects of rituximab are largely unknown. We have previously shown that genetic polymorphisms in IL-8, IL-2, IL-12 and IL-1 receptor antagonist (IL-1RN) have prognostic significance in follicular lymphoma. The goal of this study was to measure changes in the abovementioned and other serum cytokine levels in patients receiving single agent rituximab as initial therapy for follicular NHL and to identify cytokines that are associated with an increased risk of disease relapse. Methods: Patients with untreated follicular grade 1 NHL, and measurable stage III/IV disease were treated with rituximab 375 mg/m2 intravenous weekly for 4 doses and were then followed for response and time to progression (TTP); no maintenance therapy was provided. Thirty-seven patients were enrolled in this clinical trial between July 1999 and May 2001. As previously reported, the overall response rate in the 36 eligible patients was 72%, with 36% complete remissions. Now, with a median follow up of 5.1 years, the median TTP is 2.2 years (95% CI, 1.2–3.3 years) and the 5-year overall survival is 77% (95% CI: 64–92%). We measured the serum levels of a variety of inflammatory cytokines by ELISA at baseline and 1 month after completing treatment. Serum specimens were available in 30 patients. Thirty two cytokines or receptors including IL-1β, IL-1RN, IL-2, IL-2R, IL-4, IL-5, IL-6, IL-7, IL-8, IL-10, IL-12 p40/p70, IL-13, IL-15, IL-17, TNF-α, IFN-α, IFN-γ, GM-CSF, MIP-1α, MIP-1β, IP-10, MIG, Eotaxin, RANTES, MCP-1, VEGF, GCSF, EGF, FGF-basic, HGF, BLyS and APRIL were analyzed. Results: A significant increase was seen in the serum levels of BLyS (p=0.0001) after rituximab therapy, while IL-12 (p=0.0002), IL-1RN (p=0.0001), IL-2R (p=0.0001), IL-1β (p=0.02), IL-7 (p=0.02), IL-10 (p=0.02), and MIG (p=0.05) all significantly decreased. All other cytokines/receptors remained unchanged. Higher pretreatment serum levels of IL-2R (p=0.008) and IL-12 (p=0.001) correlated with a shorter TTP. Furthermore, elevated serum IL-2R levels pretreatment correlated with a lack of response to rituximab (p=0.03). Differences in overall survival could not be determined due to the fact that only 8 patients enrolled in the study have died. Because serum IL-2R levels correlated with response and TTP, we measured the cell surface expression of IL-2R in the tumor by flow cytometry. IL-2R was detected on a subpopulation of CD4+ T-cells in all specimens tested (n=14), and on malignant B-cells in 5 cases (36%). Conclusions: Pretreatment serum levels of IL-2R and IL-12 are important prognostic factors for response to therapy or TTP in follicular lymphoma patients treated with rituximab. Furthermore, serum levels of BLyS, IL-1RN, IL-7, IL-10, IL-1β and MIG also change after rituximab treatment. Targeting these cytokines may therefore provide additional clinical benefit to patients treated with rituximab.

Abstract Numerous clinical therapies have attempted to modulate tumor cell immunity, but for the most part, have proven unsuccessful. The inability to produce or augment an effective immune response is due in part to regulatory T (Treg) cells, which inhibit CD4 and CD8 T cell function. Our group has recently shown that Treg cell numbers are elevated in NHL tumors and that NHL B cells induce the development of Treg cells thereby inhibiting anti-tumor responses. The ability of NHL B cells to direct the cellular composition of their microenvironment is critical to our understanding of tumor immunity and we therefore wanted to determine if NHL B cells also directed the expansion or reduction of other T cell populations. IL-17-secreting CD4+ T cells (TH17), a newly characterized CD4+ T helper cell lineage, promote inflammation and play an important role in autoimmune disease. IL-17 has been shown to inhibit tumor cell growth suggesting a potential role for TH17 cells in anti-tumor immunity. We therefore set out to determine if TH17 cells were present in NHL tumors and whether or not their numbers were regulated by NHL B cells. Using unsorted mononuclear cells from malignant lymph nodes, we were unable to detect IL-17 expression in resting CD4+ T cells or CD4+ T cells activated with PMA/Ionomycin stimulation (less than 1%). However, IL-17-secreting CD4+ T cells could be detected in significant numbers in inflammatory tonsil and normal PBMCs. Interestingly, depletion of CD19+ NHL B cells from mononuclear cells obtained from patient biopsies resulted in detection of a clear population of IL-17-secreting CD4+ T cells (5%). These results suggest that NHL B cells suppress TH17 cell differentiation. The frequency of IL-17-secreting CD4+ T cells could not be further enhanced by the addition of exogenous TGF-b and IL-6, a cytokine combination favoring for TH17 differentiation, suggesting a further impairment of TH17 cell differentiation in the tumor microenvironment. In contrast, Foxp3 expression could be detected in resting CD4+ T cells (30%) and could be induced in CD4+CD25−Foxp3− T cells activated with TCR stimulation (28%). Contrary to the inhibition of TGF-b-mediated TH17 differentiation, Foxp3 expression could be dramatically upregulated by TGF-b in intratumoral CD4+ T cells (35%). In addition, lymphoma B cells strongly enhanced Foxp3 expression in intratumoral CD4+CD25−Foxp3−. Furthermore, when added together, the frequency of Foxp3+ T cells and Foxp3-inducible cells reached up to 60% of CD4+ T cells in tumor microenvironment of B-cell NHL. These findings suggest that the balance of effector TH17 cells and inhibitory Treg cells is disrupted in B-cell NHL and significantly favors the development of inhibitory Treg cells. Our data indicate that lymphoma B cells are key factor in regulating differentiation of intratumoral CD4+ T cells toward inhibitory CD4+ T cells.