Citations

Abstract Waldenström macroglobulinemia (WM) is a monoclonal B cell disorder characterized by a circulating monoclonal IgM protein that may lead to serum hyperviscosity in association with an infiltration of lymphoplasmacytic cells into the bone marrow. Although proinflammatory and chemotactic cytokines can profoundly affect tumor cells and the tumor microenvironment, and many cytokines have been shown to have potent therapeutic efficacy in preclinical cancer models, the role of cytokine networks in WM is not fully understood. In this study, we used a high-throughput xMAP multiplex immunobead assay technology (Luminex Corp., Austin, TX) to simultaneously test 30 cytokines, chemokines, angiogenic factors as well as growth factors and soluble receptors in the sera of WM patients and compared them with other B cell malignancies including IgM monoclonal gammopathy of undetermined significance (MGUS), follicular lymphoma, chronic lymphocytic leukemia (CLL) as well as healthy controls. Using a Mann-Whitney U test to analyze the differences between the groups, 15 of the 30 cytokines tested had significantly different levels in WM compared to healthy controls. Of those 15 cytokines, 11 were elevated in WM patients and 4 were decreased. Cytokines were grouped into 3 groups; those with < 2-fold difference, 2–8 fold difference and those having > 8-fold difference in their cytokine levels compared to healthy donors. There was a greater than 8-fold increase in the serum levels of Rantes, G-CSF and IL-2R (p<0.0001) in WM patients. Furthermore, 3 cytokines had between 2–8-fold increase in WM patients including IL-4 (p<0.0001), IL-6 (p<0.0019) and IP-10 (p<0.0006). Five cytokines had statistically elevated levels in WM patients compared to healthy controls, however the fold increase was < 2 including HGF (p<0.0185), IL-10 (p<0.0002), MIP-1α (P<0.0484), IL-2 (P<0.0130) and IL-12 (P<0.0155). Of the cytokines that had significantly lower levels in the sera of WM patients, IL-8 (p<0.0001) and EGF (p<0.0001) were > 8-fold decreased, MCP-1 (p<0.0001) was 2–8 fold lower and Eotaxin (p<0.0004) was < 2-fold lower in WM patients. All of the cytokines that had the greatest fold difference (> 8-fold) in WM patients compared to healthy donors also differed significantly from the MGUS patients. Rantes, G-CSF, IL-2R and EGF had significantly different levels compared to other B cell malignancies. We tested for a correlation between the cytokines that had > 2-fold difference between the WM group and control group with clinical features of the disease and found the cytokines IL-6 and IL-2R had a significant correlation with β2-microglobulin levels (p<0.01). We analyzed cytokine levels in the bone marrow plasma of the same patients and found that high levels of IL-2R in the bone marrow microenvironment significantly correlated with anemia and elevated serum β2-microglobulin (p<0.01). In conclusion, we have simultaneously analyzed sera from WM patients for 30 cytokines and found the most significantly elevated cytokines are Rantes, G-CSF and IL-2R and the most significantly downregulated cytokines are IL-8 and EGF. Furthermore, we found that elevated serum levels of IL-6 and IL-2R correlated with β2-microglobulin levels, a measure of disease activity. Further analysis of the biological role of these cytokines in WM may offer insight into disease pathogenesis and provide a basis for novel targeted therapies.

Abstract Rituximab is a chimeric murine/human monoclonal antibody that binds to CD20 on B-lymphocytes. Binding of the Fab domain to B-cells directly induces apoptosis, while the Fc domain recruits immune effector functions to mediate cell lysis. Because rituximab therapy alone does not result in durable responses for all patients, combination therapies have been explored. We have previously shown in a phase I study that interleukin-12 (IL-12), which facilitates cytolytic T-cell responses and enhances the lytic activity of NK cells, can be safely combined with rituximab and that IL-12 significantly upregulated gamma interferon, CXCL10 (inducible protein-10) and NK cell activity in the peripheral blood. To confirm whether IL-12 could augment the immune mediated cell lysis induced by rituximab, a subsequent randomized phase II study of the combination was performed in patients with B-cell lymphoma. While the combination of IL-12 and rituximab was well tolerated with acceptable toxicity, only moderate disease activity was seen and the response rate to the combination was similar to that seen with rituximab alone. Additionally, the sequential administration of IL-12 at the time of disease progression after treatment with rituximab did not result in any clinical responses. This study was therefore performed to determine potential biologic reasons for the lack of increased clinical efficacy when IL-12 was added to rituximab therapy in patients with B-cell non-Hodgkin lymphoma. Of the 52 patients treated on the phase II study, 8 patients had matched tumor biopsies and peripheral blood specimens obtained prior to therapy and again 2 weeks after treatment was started. Six of the patients were receiving IL-12 plus rituximab at the time the specimens were obtained while 2 were receiving rituximab alone. Gene expression array analysis using the Affymetrix U133 plus chip was performed on RNA isolated from cells from involved lymph nodes and from peripheral blood mononuclear cells. Specimens from the peripheral blood of patients who received IL-12 in combination with rituximab showed a greater than 5-fold increase in the expression of multiple genes known to be upregulated by IL-12 signaling including interferon gamma, CXCL10, IFIT2 and 4 (interferon-induced protein with tetratricopeptide repeats 2 and 4), IL-8 and CXCL2 (macrophage inflammatory protein-2). These increases in gene expression were not seen in the peripheral blood of patients who received rituximab alone. Furthermore, the significant changes seen in cells obtained from the peripheral blood were not seen in cells obtained from lymph nodes involved by lymphoma, despite the samples being obtained from the same patient on the same day. In the tumor specimens, the changes in gene expression involved none of the genes downstream of IL-12 signaling. Instead, many of the upregulated genes were associated with cell cycle and spindle checkpoint proteins suggesting ongoing tumor cell proliferation. In conclusion, while IL-12 significantly upregulated gene expression in the peripheral blood, the same changes were not seen in the tumor. This would suggest that systemically administered IL-12 may not be effectively delivered to the site of tumor involvement. This finding may explain the lack of additional clinical benefit when IL-12 was added to rituximab as therapy for patients with non-Hodgkin lymphoma.

8538 Background: Follicular lymphoma (FL) is a heterogeneous disease with a variable prognosis. Transformation to an aggressive lymphoma is associated with a poor prognosis. Previous studies have identified tumor microenvironment cells such as CD68+ macrophages, PD-1+ and FOXP3+ cells as prognostic in FL. However, results have been conflicting and infrequently address the risk of transformation. In this study we analyzed various components of the microenvironment and their association with transformation. Methods: Patients with FL that later transformed were identified through Mayo Clinic lymphoma database. Tissue specimens at diagnosis were stained with CD68, CD11c, CD21, CXCL13, FOXP3, PD-1 and CD14 and characterized by pattern of location and semi-quantitative cell content. Time to transformation (TTT) and overall survival (OS) were assessed by Kaplan-Meir analysis. Significant variables were further analyzed by cox proportional hazards model. Results: 58 patients were included with a median TTT of 4.7 years (range, 0.4-20). Presence of CD14+ cells vs absence and their location (follicular vs non-follicular) were associated with shorter TTT (4.5 vs 6.2 yrs., p=0.037 and 3.8 vs 5.9 yrs. p= 0.027, respectively). The quantity of PD-1+ cell content was not associated with TTT or OS. However, localization of PD-1 to the follicle compared to diffuse was associated with a longer TTT (6.1 vs 3.6 yrs. p=0.033) and superior OS (9.7 vs 4.6 yrs. p=0.009). On multivariate analysis, the pattern of CD14 and PD-1 staining remained significantly associated with shorter TTT (Table). Conclusions: In follicular lymphoma, a diffuse pattern of PD-1+ cells is associated with inferior TTT and OS. CD14+ cells localized to the follicle is associated with a shorter TTT. After accounting for FLIPI score, both these factors remained significant. These results identify two independent predictors of the rate of transformation in follicular lymphoma and suggest it is location rather than quantity of CD14+ or PD-1+ cells that influence outcomes. [Table: see text]

Background: DLBCL has traditionally been classified by cell of origin (COO) subcategories based on tumor gene expression profiles which include Activated B-Cell (ABC) and Germinal Center B-Cell (GCB). Recently, using tumor samples from patients treated with RCHOP, new classification models have focused on DNA alterations. However, a comprehensive integrative approach using a large transcriptomic data set across both newly diagnosed (nd) and relapsed/refractory (r/r) DLBCL is yet to be accomplished. A robust clustering of this type will allow for identification of biologically driven DLBCL patient subgroups and may predict patient outcome and inform treatment approaches. Methods: RNAseq was performed on a total of 882 DLBCL tumor FFPE biopsies from 2 ndDLBCL cohorts (cohort 1 and 2) and 2 r/r DLBCL cohorts (cohorts 3 and 4). Cohort 1 (N=267) was commercially sourced and served as the discovery cohort. Cohort 2 (N=340) was from the Mayo/Iowa Lymphoma SPORE Molecular Epidemiology Resource (MER) and served as the replication cohort. Cohort 3 (N=189) was from the CC-122-ST-001 and CC-122-DLBCL-001 clinical trials (NCT01421524 and NCT02031419), and cohort 4 (N=86) was from r/r patients from the MER. Clustering input consisted of gene expression data, gene set variation analysis (GSVA) scores computed from the hallmark gene sets of MSigDB gene sets, as well as immune cell abundance estimates from a DLBCL-specific deconvolution method. An integrative clustering method iClusterPlus was applied to the input data to identify patient subgroups. A multinomial generalized linear model classifier was trained on the discovery dataset and applied to cohorts 2, 3, and 4 to assess patterns of gene expression and clinical features among the subgroups. Results: Integrative clustering identified 8 subgroups of ndDLBCL patients (DLBCL1-8; D1-D8) in cohort 1. Classifiers trained on cohort 1 were applied to cohort 2 and the same 8 clusters were identified. Among RCHOP treated patients in cohort 2, subgroups D4 (p<0.01) and D8 (p<0.0001) had significantly worse survival outcomes than the rest of the population. D4 comprised 21% of the MER ndDLBCL replication cohort (cohort 2) with a median event-free survival (mEFS) of 38.2 months and a median overall survival (mOS) of 80.3 months. D8 comprised 5% of the cohort with a mEFS of 7.5 months and a mOS of 12.1 months. The remaining 6 subgroups were standard risk, with mEFS ranging from 82.1 months to not reached, and none reaching mOS. The subgroups were not uniquely defined by previously known molecular classification methods such as COO or double hit signature (DHITsig), nor by clinical risk factors such as age or international prognostic index (IPI). Within D4, 92% of patients were ABC, representing a high risk subset of ABC patients. The mEFS in D4 ABCs was 38.2 months, while mEFS of non-D4 ABCs was not reached (p<0.005). Transcriptomic analysis revealed a lower abundance of immune infiltration. D4 was associated with high IPI, with 49% of D4 having IPI>2, compared to 33% of non-D4 with IPI>2 (p<0.05). D8 represented a high-risk subset which was 73% GCB. The mEFS of D8 GCBs was 5.4 months, while mEFS of non-D8 GCBs was not reached (p<0.0001). Transcriptomic analysis revealed low expression of immune response and cytokine signaling pathways, consistent with the low abundance of immune cells in D8. This subgroup consisted of 63% DHITsig positive patients. Although only 20% of all DHITsig positive patients were in D8, these D8 DHITsig patients showed significantly worse survival than non-D8 DHITsig patients (mEFS 11.3 months vs. not reached, p<0.0001). In the r/r DLBCL setting, D1-D8 were all present, with an increased prevalence of D4 and D8 in Cohort 3 (30% and 17%, respectively) and Cohort 4 (30% and 14%) compared to the newly diagnosed setting. Mutational data for these cohorts has been collected and is being interpreted in the context of the discovered subgroups. Conclusion: A novel integrative clustering of transformed gene expression data revealed 8 biologically homogeneous groups, two of which had inferior outcomes when treated with RCHOP therapy. Furthermore, these two subgroups were more prevalent in r/r DLBCL. This classification allows for the transcriptomic identification of high-risk patients underserved by RCHOP therapy. *Ortiz, Wenzl and Stokes contributed equally **Gandhi and Novak contributed equally Disclosures Ortiz: Celgene Corporation: Employment, Equity Ownership. Stokes:Celgene Corporation: Employment, Equity Ownership. Huang:Celgene Corporation: Employment, Equity Ownership. Maurer:Celgene: Research Funding; Morphosys: Membership on an entity's Board of Directors or advisory committees; Nanostring: Research Funding. Towfic:Celgene Corporation: Employment, Equity Ownership. Hagner:Celgene Corporation: Employment, Equity Ownership, Patents & Royalties. Ratushny:Celgene Corporation: Employment, Equity Ownership. McConnell:Celgene Corporation: Employment, Equity Ownership. Danziger:Celgene Corporation: Employment, Equity Ownership. Stong:Celgene Corporation: Employment, Equity Ownership. Lata:Celgene Corporation: Employment, Equity Ownership. Kamalakaran:Celgene Corporation: Employment, Equity Ownership. Mavrommatis:Celgene Corporation: Employment, Equity Ownership. Trotter:Celgene Corporation: Employment, Equity Ownership. Czuczman:Celgene Corporation: Employment, Equity Ownership. Ansell:Seattle Genetics: Research Funding; Affimed: Research Funding; Regeneron: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; Trillium: Research Funding; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; LAM Therapeutics: Research Funding; Affimed: Research Funding. Cerhan:NanoString: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding. Nowakowski:Genentech, Inc.: Research Funding; F. Hoffmann-La Roche Ltd: Research Funding; Curis: Research Funding; Bayer: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Selvita: Membership on an entity's Board of Directors or advisory committees; NanoString: Research Funding; MorphoSys: Consultancy, Research Funding. Gandhi:Celgene Corporation: Employment, Equity Ownership, Patents & Royalties. Novak:Celgene Coorperation: Research Funding.

Background: Diffuse large B cell lymphoma (DLBCL) is the most common aggressive lymphoid malignancy in adults. Though standard immunochemotherapy regimens can result in clinical remission and cure in a majority of patients, approximately 30% of patients are primary refractory or eventually relapse, and their prognosis is very poor. Recent progress by large scale genomic and transcriptomic profiling of DLBCL patients has resulted in a deep understanding of disease drivers in newly diagnosed DLBCL (ndDLBCL). However, previous genomic studies of relapsed and/or refractory DLBCL (rrDLBCL) are limited by small sample sizes and much less is known about the genomic landscape or the changes in clonal populations that occur within a patient undergoing R-CHOP therapy. Analysis of a large cohort of rrDLBCL is needed to uncover the importance of known drivers, define clonal shifts that occur in relapsing patients, and discover novel mutations that impact resistance to therapy. Methods: DNA sequencing (whole exome or genome sequencing) was performed on tumor and matching germline samples from two rrDLBCL patient cohorts (N=143). The first rrDLBCL cohort consisted of 68 formalin fixed paraffin embedded (FFPE) tumor samples with matched germline obtained from the Mayo/Iowa Lymphoma SPORE Molecular Epidemiology Resource (MER); including 18 diagnostic/relapse paired samples. The second cohort consisted of 75 FFPE samples from 2 rrDLBCL clinical trials CC-122-ST-001 and CC-122-DLBCL-001 (NCT01421524 and NCT02031419). In addition, a ndDLBCL cohort (n=364) consisting of MER front line samples were also analyzed. CNV and SV calling was performed with Sclust and Manta, respectively. Mutational drivers were identified with cDriver. Cosmic mutational signatures were calculated for all samples. Results: For comparison of overall mutation rates between the ndDLBCL and rrDLBCL we analyzed the frequency of mutations in known driver genes [n=211, Chapuy et al, 2018; Schmitz et al, 2018; Reddy et al 2017]. Of these, the top 5 most mutated genes found in the relapse cohort were KMT2D (34.3%), IGLL5 (25.9%), CREBBP (22.4%), TP53 (21.0%), and HIST1H1E (19.6%) all of which were previously reported as mutated genes in rrDLBCL [Morin et al. 2016; Park et al. 2016;Greenawalt et al. 2017]. None of these frequencies changed significantly from the MER ndDLBCL cohort. However, frequencies of 2 genes NCOR1 and ACTB were increased significantly from 3.3% to 13.3% (p= 5.85 x 10-05) and 0.5% to 6.3% (p=2.56 x 10-04), respectively, in the rrDLBCL cohorts. Analysis of the previously reported driver mutations in 18 paired samples revealed a significant increase in the mean variant allele frequency (VAF) from diagnosis to relapse of mutations in BCL2 and BIRC6 from 18.5% to 28.8%(p=0.016) and 4.3% to 13.7%(p=0.011), respectively. In our analysis of novel drivers in rrDLBCL cohorts, 59 significant driver mutations (FDR 0.1) were identified, 23 were novel driver mutations while the remaining 36 have been previously reported as drivers of newly diagnosed DLBCL. These include novel mutations in genes such as IL4R (8.8%), CDK5R1 (6.7%), LAPTM5 (3.7%) and others whose function in lymphoma are unknown. In a secondary analysis, we performed mutational signature analysis for rrDLBCL and identified groups of patients with COSMIC mutational signatures that are associated with aging, defects in homologous end joining resulting in large insertions/deletions, and with defective mismatch repair often found in microsatellite unstable tumors. Together with the high prevalence of TP53 mutations, these results indicate genetic instability as a hallmark of relapse/refractory DLBCL. Analysis of CNV and SV will also be reported. Conclusion: Here we report to our knowledge the largest genomic dataset in relapsed and /or refractory DLBCL using tumor biopsies. Previously identified mutated genes in rrDLBCL were confirmed and novel drivers identified. Paired samples analysis reveals clonal shifts which occur during treatment and at time of relapse. Whether the novel driver mutations appeared as a function of selection of a rare clone over the course of therapy or a therapy induced mutation will be the focus of ongoing work. Novel variants including SNV, CNV and SV can potentially lead to new insights and deepen our understanding of the mechanisms of resistance in DLBCL. * Wenzl, Ortiz and Stong contributed equally **Novak and Gandhi contributed equally Disclosures Ortiz: Celgene Corporation: Employment, Equity Ownership. Stong:Celgene Corporation: Employment, Equity Ownership. Huang:Celgene Corporation: Employment, Equity Ownership. Maurer:Morphosys: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; Nanostring: Research Funding. Towfic:Celgene Corporation: Employment, Equity Ownership. Hagner:Celgene Corporation: Employment, Equity Ownership, Patents & Royalties. Nikbakht:Celgene Corporation: Employment, Equity Ownership. Stokes:Celgene Corporation: Employment, Equity Ownership. Lata:Celgene Corporation: Employment, Equity Ownership. Kamalakaran:Celgene Corporation: Employment, Equity Ownership. Mavrommatis:Celgene Corporation: Employment, Equity Ownership. Trotter:Celgene Corporation: Employment, Equity Ownership. Czuczman:Celgene Corporation: Employment, Equity Ownership. Ansell:Regeneron: Research Funding; LAM Therapeutics: Research Funding; Trillium: Research Funding; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; Mayo Clinic Rochester: Employment; Affimed: Research Funding; Seattle Genetics: Research Funding; LAM Therapeutics: Research Funding; Mayo Clinic Rochester: Employment; Bristol-Myers Squibb: Research Funding; Trillium: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding. Cerhan:Celgene: Research Funding; NanoString: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees. Nowakowski:Bayer: Consultancy, Research Funding; Curis: Research Funding; Celgene: Consultancy, Research Funding; MorphoSys: Consultancy, Research Funding; Genentech, Inc.: Research Funding; F. Hoffmann-La Roche Ltd: Research Funding; Selvita: Membership on an entity's Board of Directors or advisory committees; NanoString: Research Funding. Novak:Celgene Coorperation: Research Funding. Gandhi:Celgene Corporation: Employment, Equity Ownership, Patents & Royalties.

Background: Follicular lymphoma (FL) is the most frequent indolent lymphoma. While immunochemotherapy (IC) treated FL patients who achieve event-free status at 24 months after diagnosis (EFS24) have the subsequent life expectancy of the general population, those who fail to achieve EFS24 have aggressive disease with poor outcomes. Similarly, in FL patients initially observed or treated with rituximab monotherapy, EFS at 12 months (EFS12) is a strong predictor of subsequent outcome. Thus, an unmet patient need is to predict at diagnosis those at greatest risk of early failure in order to identify better treatments. The lymphoma microenvironment may be a key determinant of early failure. Therefore, we aimed to improve risk stratification of newly diagnosed FL patients by using a discovery and validation study design to identify microenvironment determinants of early failure and then integrate them into the Follicular Lymphoma International Prognostic Index (FLIPI). Patients and Methods: We evaluated 496 patients with FL grade 1-3A who were prospectively enrolled into the Molecular Epidemiology Resource (MER) cohort from 2002-2012. In the discovery set of patients (N=166), we stained tissue microarrays for CD4, CD8, FOXP3, CD32b, CD14, CD68, CD70, SIRPa, TIM3, PD-1 and PDL1. Immunohistochemical staining was determined both within and between malignant follicles. Stains were scored to the nearest decile as the percentages of cells positive. Scores for each stain were dichotomized as 0% vs >0% except for CD32b (<20% vs ≥20%), CD70 (<10% vs ≥10%), and SIRPa (<30% vs ≥30%). EFS was defined as time from diagnosis to progression, relapse, retreatment, or death. Early failure was defined as failing to achieve EFS24 for patients treated with IC at diagnosis and failing to achieve EFS12 for patients who were observed or received other treatments. Risk of early failure was estimated using odds ratios (ORs) and 95% confidence intervals (CI) from logistic regression models. Markers at P≤0.15 were brought forward for validation in a separate set of patients from the MER cohort (N=330), with P<0.005 being declared statistically significant after a Bonferroni correction (0.05/10 tests). In the combined dataset, we also used Cox regression to assess associations with continuous EFS and overall survival (OS). Mass cytometry (CyTOF) was then performed on a subset of patients (N=51) to comprehensively characterize the phenotype of intratumoral immune cells associated with outcome. Results: In the discovery set, CD4, CD8, FOXP3, PD-1, and SIRPα were associated with risk of early failure at P≤0.15 and were subsequently evaluated in the validation set. Only CD4 expression inside the follicle validated. Specifically, lack of CD4 expression inside the follicle was associated with higher risk of early failure in the discovery (OR=1.77, P=0.15) and validation (OR=2.59, P=0.001) sets, with a pooled OR=2.29 (95% CI 1.47-3.58; P<0.001). CyTOF analysis characterized the favorable CD4+ T-cell population associated with achieving EFS12/24 as activated effector memory T cells lacking exhaustion markers (Figure 1A). Adjustment of CD4 expression for FLIPI in the combined dataset did not weaken this association (OR=2.38, 95% CI 1.51-3.79), and lack of CD4 expression was prognostic within each FLIPI group 0-1 (OR=2.65; p=0.036), 2 (OR=2.07; P=0.064) and 3-5 (OR=2.51; P=0.015). We next established a bio-clinical risk model (termed BioFLIPI) that combined CD4 intrafollicular expression and FLIPI into a 1-4 scale, where any expression of intrafollicular CD4 moved a patient up one FLIPI risk group, adding a fourth (high) risk group for FLIPI 3-5 and any CD4 inside expression. The BioFLIPI score was strongly associated with risk of early failure: compared to a BioFLIPI score of 1 (24% of patients), patients with a score of 2 (35% of patients; OR=2.17, 95% CI 1.08-4.69), 3 (31% of patients; OR=3.53, 95% CI 1.78-7.54), and 4 (10% of patients; OR=8.92, 95% CI 4.00-21.1) had increasing risk of early failure. The c-statistic for BioFLIPI was 0.665, which was higher than that for FLIPI alone (0.636). BioFLIPI was also strongly predictive of continuous EFS [Figure 1B], OS [Figure 1C], and for EFS and EFS24 when restricted to IC-treated patients [Figure 1D]. Conclusion: Integration of CD4 expression inside the follicle at diagnosis with FLIPI improves identification of FL patients at risk for early failure. Disclosures Novak: Celgene Coorperation: Research Funding. Nowakowski:Curis: Research Funding; Bayer: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; F. Hoffmann-La Roche Ltd: Research Funding; Selvita: Membership on an entity's Board of Directors or advisory committees; NanoString: Research Funding; Genentech, Inc.: Research Funding; MorphoSys: Consultancy, Research Funding. Cerhan:NanoString: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding. Ansell:LAM Therapeutics: Research Funding; Mayo Clinic Rochester: Employment; Affimed: Research Funding; Affimed: Research Funding; Trillium: Research Funding; Bristol-Myers Squibb: Research Funding; Mayo Clinic Rochester: Employment; Affimed: Research Funding; Trillium: Research Funding; Seattle Genetics: Research Funding; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; Trillium: Research Funding; Trillium: Research Funding; LAM Therapeutics: Research Funding; Regeneron: Research Funding; LAM Therapeutics: Research Funding; LAM Therapeutics: Research Funding; Seattle Genetics: Research Funding; LAM Therapeutics: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; Seattle Genetics: Research Funding; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Seattle Genetics: Research Funding; Seattle Genetics: Research Funding; LAM Therapeutics: Research Funding; Trillium: Research Funding; LAM Therapeutics: Research Funding; Affimed: Research Funding; Regeneron: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; Seattle Genetics: Research Funding; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; Trillium: Research Funding; Regeneron: Research Funding; Mayo Clinic Rochester: Employment; Affimed: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Affimed: Research Funding; Trillium: Research Funding; Regeneron: Research Funding; Affimed: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Mayo Clinic Rochester: Employment.

AbstractHistological transformation in Waldenström macroglobulinemia (WM) is an uncommon complication, with limited data, particularly regarding the impact of MYD88 L265P mutation on transformation. We examined risk factors and outcomes associated with transformation in WM, highlighting the role of MYD88 L265P mutation. Patients with WM seen at Mayo Clinic, Rochester, USA and University Hospital of Reims, France, between 01/01/1996 and December 31, 2017 were included; 50 (4.3%) of 1147 patients transformed to a high‐grade lymphoma, with median time‐to‐transformation of 4.5 (range 0‐21) years in the transformed cohort. The MYD88 L265P mutation status was known in 435/1147 (38%) patients (406 with non‐transformed WM and 29 patients in transformed cohort). On multivariate analysis, MYD88 WT status alone was an independent predictor of transformation (odds ratio, 7[95%CI: 2.1‐23]; P = .003). Additionally, the MYD88 WT status was independently associated with shorter time‐to‐transformation (HR 7.9 [95%CI: 2.3‐27; P = .001]), with a 5‐year transformation rate of 16% for MYD88 WT vs 2.8% with MYD88 L265P mutated patients. Patients with transformation demonstrated a significant increase in risk of death compared to patients who did not transform (HR 5.075; 95%CI: 3.8‐6.8; P < .001). In conclusion, the MYD88 WT status is an independent predictor of transformation and associated with a shorter time‐to‐transformation. Additionally, transformation conferred an inferior overall survival in patients with WM.

Abstract Background - The phenotype and biological role of monocytes in B-cell non-Hodgkin lymphoma (NHL) is not fully understood, however, an increased absolute monocyte count in the peripheral blood of lymphoma patients is associated with a poor prognosis. We have previously reported that monocytes from patients with relapsed B-cell NHL displayed an immunosuppressive CD14+HLA-DRlow/- phenotype that correlated with a poor prognosis. However, the underlying mechanism by which CD14+HLA-DRlow/- monocytes develop in patients with B-cell NHL is unknown. The goal of this study was to determine whether cytokines are responsible for the increased number and phenotype of CD14+HLA-DRlow/-monocytes present in lymphoma patients. Methods – Whole blood from patients with newly diagnosed, untreated B-cell NHL (n=20) and healthy donors (n=20) was stained with a panel of antibodies and analyzed by 10-color flow cytometry. Cytokine levels in serum and culture supernatants were measured by Luminex and ELISA, respectively. Polarization of monocytes from healthy donors was performed by incubating CD14+ cells with specific cytokines or supernatants from B-cell NHL cell lines for 24 hours. Activation and proliferation of CD4+T cells cocultured with IL-10-pretreated monocytes were measured by flow cytometry. Results – By flow cytometry, we observed that the absolute number of peripheral monocytes was increased in newly-diagnosed lymphoma patients compared to healthy donors. A significant proportion of these monocytes displayed an immunosuppressive CD14+HLA-DRlow/- phenotype and the numbers of CD14+HLA-DRlow/- cells were significantly higher in lymphoma patients than in healthy donors. To identify the underlying mechanism by which CD14+HLA-DRlow/- monocytes develop thereby leading to increased numbers of CD14+HLA-DRlow/- monocytes in B-cell NHL, we tested a panel of cytokines and found that IL-10 played a key role in the process. Firstly, treatment of monocytes with IL-10 in vitro resulted in the generation of CD14+HLA-DRlow/- cells. Second, monocytes co-cultured with IL-10 producing lymphoma B-cells, or treated with supernatants from lymphoma cell cultures, developed a CD14+HLA-DRlow/- phenotype. Thirdly, IL-10 levels were increased in the serum of DLBCL (p<0.0001) and FL patients (p=0.010) compared to healthy controls, and serum IL-10 levels correlated with increased numbers of peripheral monocytes (p=0.02). Finally, IL-10-pretreated CD14+HLA-DRlow/- monocytes were significantly immunosuppressive and inhibited the proliferation and activation of CD4+T cells in co-culture assays. Conclusions- Taken together, our results suggest that IL-10 signaling contributes to the increased numbers of CD14+HLA-DRlow/- monocytes in B-cell NHL. Strategies to inhibit IL-10 production may therefore have therapeutic potential in B-cell NHL. Disclosures No relevant conflicts of interest to declare.

Abstract Background: Waldenstršms macroglobulinemia (WM) is an indolent B-lymphoplasmacytic lymphoma, which is highly sensitive to 20S proteasome inhibitors such as bortezomib. However, clinical resistance to the drug can be observed early at onset of therapy (primary or inherent resistance) or develop over time, through repeated exposure to the drug (acquired resistance). Although prior investigations into the biological mechanisms associated with bortezomib resistance (BR) have identified aberrations at the genomic (PSMB5 mutation) and transcriptional level (loss of XPB-1), there is limited data on the epigenetic abnormalities that support resistance to 20S proteasome inhibition. With this in mind, we conducted a comprehensive methylation and mRNA expression analysis in WM cells focusing on the molecular patterns that characterize inherent BR (iBR) as well as acquired BR (aBR). Materials and Methods: Bortezomib sensitive (BS) human WM cell lines, BCWM.1 and MWCL-1, the iBR WM cell line RPCI-WM1 (developed from a bortezomib-refractory WM patient) as well as aBR subclones (BCWM.1/BR, MWCL-1/BR) were used in the study. Methylation status of WM cells was profiled by Illumina Infinium 450k methylation array. Methylation IDAT files were background subtracted using GenomeStudio v1.9. Beta mixture quantile dilation (BMIQ) method in R watermelon package was used to adjust type II probes into distribution characteristic of type I probes. For each gene, probes were partitioned into 6 regions using R IMA package and the ones belonging to the same region were averaged, including transcription start sites (TSS; both 200 bp and 1500 bp upstream), 5' untranslated region (UTR), and 3'UTR, the first exon, and genebody. Gene regions showing a significant adjusted p-value and a beta difference of >0.1 or <-0.1 were selected for differential hypermethylation and hypomethylation, respectively. Correlation with gene expression was conducted only on genes showing >1.5 fold change in expression. Overview of methodology is shown in Figure 1. Results: We first assessed the differential methylation pattern (TSS, 200bp upstream of gene body) of bortezomib-sensitive (BS, BCWM.1, IC50 6nM) and iBR cells, (RPCI-WM1). A total of 3,801 hypermethylated and 1,865 hypomethylated DNA regions were observed in iBR cells relative to BS cells (Figure 2A). In iBR cells, a negative correlation between hypermethylated DNA and corresponding gene expression was found in 1,039 genes (Spearman r = -0.12) (Figure 2B). In parallel, we compared the methylation pattern (TSS 200bp) of BS WM cells (BCWM.1 and MWCL-1) with their aBR derivatives, which display ~20 – 50 fold resistance to bortezomib. aBR subclones showed differential hypermethylation of 1,521 DNA regions and hypomethylation of 651 genomic regions relative to BS WM cells. These findings were not unexpected as aBR cell lines, being derivatives of BS WM cells, are clonally related to the former, whereas iBR cells are derived from a different clone. Meta-analysis of iBR and aBR followed by pathway enrichment (NextBio, Illumina Inc), revealed a significant clustering of commonly hypermethylated genes within the Validated Transcriptional Targets of TP63 isoforms Canonical Pathway (p<1.9-E5, Figure 2C) and the CEBPA binding site Geneset 2 (p<8.2-E9, Figure 2D); pathways whose genes are actively involved in suppression of cell growth and differentiation. Further validation and functional relevance of candidate gene targets from this analysis, which are relevant to WM pathobiology, are currently being investigated. Conclusion: This is the first study to examine and correlate the global methylation and gene expression profiles in WM tumor cells that are inherently wired to resist 20S proteasome inhibition as well as tumor cells, which have acquired resistance through continuous exposure to bortezomib. Although considerable differences were observed in the methylation profiles of WM cells displaying inherent vs. acquired resistance, a number of common genes emerged and pointed towards transcriptional repressors, whose inactivation through methylation has been linked to other cancers. Altogether, these findings uncover cellular systems in WM cells, which are affected by DNA methylation, subsequent mRNA suppression and which may be associated as a whole with both inherent and acquired forms of bortezomib resistance. Disclosures No relevant conflicts of interest to declare.

Abstract Background: Deubiquitinating enzyme (DUB) inhibitors are an emerging class of compounds, which are increasingly being regarded for their anti-cancer activity and therapeutic potential. The 19S regulatory particle of the proteasome contains two DUBs, USP14 and UCHL5, which are critical for the proper unfolding and deubiquitination of proteins prior to their entry into the 20S proteasome β-catalytic core. In B/plasma cell malignancies such as Waldenströms macroglobulinemia (WM) and multiple myeloma (MM), protein homeostasis and optimal proteasome functionality are paramount for tumor survival. This is evidenced by the success of 20S proteasome inhibition with bortezomib and carfilzomib, which have demonstrated remarkable clinical benefit in patients with WM or MM. As such, the proteasome degradation pathway represents a highly attractive and clinically validated, yet still largely unexplored therapeutic target. Here, we provide first evidence of the cytotoxic effects and molecular sequelae associated with a novel 19S proteasome DUB inhibitor, VLX1570, which selectively targets USP14 and UCHL5, in preclinical models of B/plasma cell cancers and their drug resistant tumor subclones. Materials: VLX1570 was obtained from Vivolux AB, Sweden. Bortezomib was purchased from Sellekchem, Houston TX. Human myeloma cell lines (OPM2, U266, KMS11), human WM cell lines (BCWM.1, MWCL-1 and RPCI-WM1), their respective bortezomib-resistant (BR) subclones as well as ibrutinib-resistant (IR) derivatives of BCWM.1 and RPCI-WM1 were used in experiments (total n=12). Peripheral blood mononuclear cells (PBMCs) from healthy donors were used to assess for cytotoxicity of VLX1570 in non-tumor cells. Results: A 72hr MTS assay first established sensitivity of plasma cell cancer models towards VLX1570, including drug resistant subclones (EC50 range, 20 – 90nM). Next we assessed whether loss of viability was due to apoptosis and observed dose-dependent annexin-V staining in ~50 – 70% of wild-type MM and WM cells, ~45 – 55% in corresponding BR models and ~50% in IR subclones when exposed to VLX1570 (100nm – 500nM) for 24hrs. VLX1570 was tested at similar concentrations in PBMCs and induced minimal cell death. To understand if VLX1570-induced apoptosis was mitochondrial mediated, we assessed mitochondrial outer membrane permeability (MOMP) in all plasma cell cancer models treated with the DUB inhibitor (100 – 500nM) and found a dose-dependent increase in MOMP (p<0.00025 – 0.000001). Activation of the mitochondrial/intrinsic apoptotic pathway was also evidenced by cleavage of caspase-9 and 3 on immunoblot analysis. As inhibition of protein deubiquitination results in accumulation of polyubiquitinated protein conjugates, we examined global ubiquitinated protein levels and found increasing amounts of high molecular weight poly-ubiquitinated protein in VLX1570 treated tumor cells in a dose-dependent manner. This prompted us to further delineate the potential cellular response mechanisms that relay the antitumor activity of VLX1570 in malignant plasma cells. Immunoblot analysis of drug sensitive and (bortezomib or ibrutinib) resistant MM and WM cell lines revealed several changes in ER stress response proteins, notably induction of HSP70 and splicing of XBP1; the latter event which was less prominent in BR cell lines treated with bortezomib. This suggested the ability of VLX1570 to overcome resistance through a rapid and potent proteotoxic effect, which overwhelmed the tumor cells stress response mechanisms beyond its capacity for survival. Finally, as abnormalities in the NFkB signaling pathway are implicated in malignant plasma cell survival, we found markedly decreased nuclear translocation of NFkB (p-P65) protein in tumor cells treated with VLX1570. Conclusions: The DUBs of the 19S proteasome cap offer an attractive target within the proteasome degradation system and whose inhibition by VLX1570 is able to circumvent mechanisms that support resistance to b-catalytic PI (bortezomib) or BTK inhibitor (ibrutinib) therapy. The studies undertaken thus far, coupled with more rigorous mechanistic and in vivo efficacy analyses currently underway, provides rational for the clinical development of DUB inhibitors for use in malignant B/plasma cell malignancies. Disclosures Martin: Janssen: Honoraria.