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Abstract Background The role of intratumoral PD-1+ T cells and their contribution to patient outcome in follicular lymphoma (FL) has been controversial. While some studies have found that increased numbers of PD-1+ T cells correlate with an inferior prognosis or have no impact on patient outcomes, other studies observed that the numbers of intratumoral PD-1+ T cells are an indicator of a favorable outcome in FL. In previous work, we observed that PD-1 can be expressed by different subsets of intratumoral T cells in FL including T follicular helper (TFH) cells and exhausted T effector cells. However, the function, prevalence, distribution and clinical importance of the respective intratumoral PD-1+ T subsets in FL patients are largely unknown. Goal To characterize PD-1+ T cell subsets and to determine the biological and clinical relevance of these T cell subsets in FL. Results In an analysis of biopsy specimens from 33 previously untreated FL patients, we found that PD-1 is abundantly expressed on intratumoral T cells. A median of 54.9% (range: 17.2-92.6, n=33) of CD4+ or 45.8% (range: 12.8-81.7, n=33) of CD8+ T cells express PD-1 on the cell surface. We found by flow cytometry that PD-1 is expressed on intratumoral CD4+ T cells with bright or dim intensity that represents two different subpopulations in FL. By immunohistochemistry, we identified that CD4+PD-1bright T cells predominantly reside in the lymph node follicles while PD-1dim T cells are mainly located in an inter-follicular pattern. Intratumoral CD4+PD-1bright T cells have a TFH cell phenotype and express CXCR5, secret IL-21 and are BCL-6 positive with no TIM-3 expression. In contrast, CD4+PD-1dim T cells have an exhausted phenotype, express TIM-3 and do not express BCL-6 and CXCR5. Functionally, CD4+PD-1dim T cells displayed reduced proliferation, cytokine production and cell signal transduction. When the CD8+ T cells were analyzed, we found that intratumoral CD8+ T cells, primarily reside in the inter-follicular regions, express PD-1 with low intensity and exhibit similar phenotypic and functional changes to inter-follicular CD4+PD-1dim T cells. These cells express TIM-3 but lack CXCR5 and BCL-6. They also displayed reduced proliferation and cytokine production. Clinically, we observed that both the numbers of CD4+PD-1dim and CD8+PD-1dim exhausted T cells significantly correlate with a reduced progression-free survival in FL patients treated with single agent rituximab (p=0.007 and p=0.04 respectively; n=31). Although it did not reach statistical significance, CD4+PD-1bright TFH cells appeared to correlate with a favorable survival, suggesting that TFH and exhausted T cells differentially impact patient outcome in FL. Conclusion Taken together, these results indicated that PD-1 expression defines two subpopulations with distinct functions that differentially impact patient outcome in FL. This finding provides not only an explanation for the previously discrepant clinical observations, but is also important in the design of future anti-PD-1 antibody-based therapy in FL. Disclosures: No relevant conflicts of interest to declare.

Abstract Recent studies have shown decreased megakaryocyte expression of the thrombopoietin receptor (c-mpl) in patients with polycythemia vera (PV) but not in those with reactive erythrocytosis. We examined the diagnostic utility of this observation in 22 patients with PV, 7 patients with secondary erythrocytosis (SE), and 10 normal controls. Commercial antibodies against c-mpl were used with standard immunoperoxidase methods. Megakaryocyte c-mpl staining intensity was uniformly moderate-to-strong in the healthy controls and in all the patients with SE. In contrast, staining intensity in 9 patients with PV (41%) was uniformly weak. Furthermore, in 12 of the remaining 13 patients with PV, the c-mpl staining pattern in each case was heterogeneous and was associated with weak staining intensity in more than 20% of the megakaryocyte population. These preliminary data suggest that c-mpl immunostains may complement bone marrow histopathology in distinguishing PV from nonclonal causes of erythrocytosis.

Abstract Gene expression profiling has shown that diffuse large B-cell lymphoma (DLBCL) clusters into three major subtypes based on similarity in expression patterns to their cell of origin (COO): germinal center B-cell-like (GCB-DLBCL), activated B-cell-like DLBCL (ABC-DBLCL) and primary mediastinal B-cell lymphoma (PMBCL). These subtypes of DLBCLs are associated with distinctly different overall survival rates after standard immunochemotherapy. However, clinical and prognostic heterogeneity remains within COO subsets and strategies are needed to further stratify patients to identify and target high-risk subsets. A comprehensive genomic analysis of COO on a clinically defined set of DLBCL cases has not been performed and the aim of this study was to use whole-exome sequencing (WES) data from 58 paired tumor-normal DLBCL samples to assess association of known DLBCL genomic alterations with cell COO as well as for identification of novel and relevant genetic biomarkers. To investigate genomic alterations associated with DLBCL subsets, we analyzed WES and genome wide copy number data from 58 paired tumor-normal DLBCL tumors. Gene expression profiling or Hans classification was performed to determine DLBCL COO subtype; 31 patients were classified as GCB and 27 as non-GCB. The WES data were used to 1) assess the association of known DLBCL genomic alterations with COO, and 2) identify novel alternations associated with COO. Statistical analysis was performed and the data were ranked by significance (p≤ 0.05) within each DLBCL subtype. In total, 45 genomic abnormalities were analyzed for their association with either GCB, non-GCB or both. Mutations in CREBBP, EZH2, MEF2B, FOXO1 and REL have also been reported as GCB driver mutations and we observed GCB patients with these mutations, but the mutation clustering was not wholly associated with GCB. MYC double-hits were exclusively found in the GCB-subtype group. For the non-GCB cases we found that mutations in MAP2K3 and MYD88 were significantly associated with this subtype(p< 0.05). In addition to mutational patterns, we identified several copy number alterations (CNA) across both groups. Chromosomal losses in GCB patients were found at chromosomes 10q11.21-10q24.23, 4q12-4q35.2, 3q12.1-3q29, 4p12-4p16.3, 10p11.21-10p15.3, and 14q11.2-14q24.3 whereas gains were localized to 7q11.1-7q36.3, 7p11.2-7p22.3, and 1q21-1q32.1 (p < 0.05). No CNA was observed to directly associate with non-GCB patients, however, a loss at 9p21 and gains at 9q24.1 and 18q21.33 trended with the non-GCB subtype, supporting previous reports. Loss at 10q23.31 or a gain in 2p13-2p12 have been reported as being specific for GCB and our data confirmed the association of 10q23.31 with GCB while a gain at 2p13-2p12 (REL)was found in both subtypes. To further understand genomic differences between DLBCL subtypes, we evaluated the relative percentage of each genomic feature. 18/45 (40%) were only observed in GCB patients whereas 2/45 (5%) were specific to the non-GCB subtype. The majority (25/45, 55%) overlapped between the two subtypes. Throughout our analysis we noted that 7 non-GCB cases lacked any of the driver mutations analyzed in the study. While all cases carried mutations, they consisted of low frequency mutations that were not specifically associated with COO. 2/7 cases had a gain at 9p24.1 that included CD274 and JAK2. Because 9p24.1 gains have not been fully defined in DLBCL, we reviewed all cases and identified 4 (7%) with a 9p24.1 gain, 3 of which were non-GCB and 1 GCB. One non-GCB case was EBV+ and none of the cases showed evidence of PMBCL. Of the 9p24.1 cases, three had RNAseq data available and we found that PDL1 and JAK2 expression was elevated (12 fold p< 0.01 and 7 fold p< 0.01, respectively) when compared to the 9p24.1 normal cases (n=32). While outcome was not the focus of the study, we did note that 6/7 cases that lacked driver mutations achieved event free survival at 24 months (EFS24). Taken together, this analysis has further characterized the genetic profile of each COO subtype and has identified novel GCB CNAs which require independent replication. Additionally, we identify a subgroup of non-GCB DLBCL patients that do not harbor known driver mutations and require further genomic study to better resolve the biology of these tumors. Together, these data provide insight on the genetic heterogeneity of DLBCL and identify genetic variants that may inform subtype specific therapy. Disclosures Nowakowski: Morphosys: Research Funding; Celgene: Research Funding; Bayer: Consultancy, Research Funding. Rimsza:NCI/NIH: Patents & Royalties: L.M. Rimsza is a co-inventor on a provisional patent, owned by the NCI of the NIH, using Nanostring technology for determining cell of origin in DLBCL..

Abstract Background: Large case-control studies have identified common epidemiologic exposures associated with risk of AML development, including obesity [BMI ≥30 kg/m2] associated with 2-fold increase risk. However it is not known whether individual risk factors are associated with unique AML genetic lesions. We have recently identified a significant association of some common exposures including obesity with unique disease cytogenetic subgroups in a cohort of n=295 consecutive AML patients diagnosed and treated at Mayo Clinic [Cancer Epidemiol 39:1084, 2015]. Aberrant DNA methylation is a hallmark of cancer and has been reported in AML, and we therefore performed an analysis of global DNA methylation in patients in this cohort to determine whether specific epidemiologic exposures are associated with a unique pattern of DNA methylation. Methods: Patients in the initial cohort were previously reported. An available baseline AML bone marrow cytogenetic pellet from diagnosis was identified for n=148 patients (50.2%). Following IRB approval and using previously reported techniques [Leukemia 24:1283, 2010], leukemia DNA was isolated from the remnant diagnostic cytogenetic samples and processed on the HumanMethylation450 BeadChip array (Illumina). Individual CpG dinucleotides were assigned a Beta value (i.e. methylation value) ranging from 0 (unmethylated) to 1 (methylated). We excluded those with minor methylation changes (<0.2 between any two samples), resulting in 383,524 CpG's. For the purposes of this first analysis we have focused only on CpG's with an inter-quartile range (IQR, i.e. difference between 75th and 25th percentiles) of greater than 0.25, comprising a total of 39,657 CpG's. An unsupervised cluster analysis of differential methylation was generated ("Heatmap", Figure). Univariate and multivariable analyses were performed adjusting for age as a continuous variable to determine the association of individual exposures with unique methylation clusters (primary endpoint), and we also evaluated the association of clinical characteristics and clinical outcomes after therapy (secondary endpoint). The median age of patients was 69 yrs (range 19-89), male 65%, and Caucasian 89%. The median BMI was 27.2 (range 16.9-59.9), and n=47 patients (32%) had BMI ≥30. Standard cytogenetic risk groups were applied [favorable (n=8), normal (n=61), intermediate abnormal (n=32) and poor (n=47)]. Results: We identified 4 distinct methylation clusters (Figure: Cluster #1, Black horizontal bar; Cluster #2, Green; Cluster #3, Blue; and Cluster #4, Red). Multivariate analysis of select variables is shown in Table. Patients in cluster #1 were significantly more likely to have a BMI ≥30 [Odds Ratio (OR) 2.49, p=0.017] and more likely to have favorable risk cytogenetics although this was not statistically significant [OR 6.71, p=0.088], while those in cluster #2 were significantly more likely to be have a history of regular NSAID use [OR 3.26, p=0.03] and less likely to have normal [OR 0.40, p=0.044] and possibly intermediate abnormal cytogenetics [OR 0.34, p=0.051]. Those in cluster #3 were significantly younger [median age 48 yrs, p<0.001] and were also more likely to have prior history MDS although this was not statistically significant [OR 3.7, p=0.082]. Cluster #4 was not correlated with any distinct exposure apart from possible decreased alcohol use [OR 0.3, p=0.079]. History of past or current tobacco use, regular acetaminophen use, documented myelotoxin exposure, family history, and secondary AML did not correlate with a unique methylation cluster. There was no independent association of methylation cluster with overall survival (p=0.46), although among patients receiving intensive therapy cluster #2 was associated with lower complete remission rate [OR 0.28 (95% CI 0.09-0.86), p=0.026]. Conclusion: This first analysis of AML molecular epidemiology and clinical outcome suggests that specific disease risk factors (esp. obesity and age) are associated with unique leukemia DNA methylation clusters. In addition, aberrant methylation is associated with some clinical features and with outcome after therapy, suggesting that epidemiologic risk factors may have a prognostic impact. This provides novel insight into leukemogenesis, and will guide prospective studies of AML epidemiology and outcome. Figure. Figure. Disclosures Foran: medscape: Honoraria; pfizer: Honoraria; Millennium Pharmaceuticals, Inc.: Research Funding; novartis: Honoraria; karyopharm: Honoraria; boehringer ingelheim: Research Funding; agios: Research Funding; Cellerant: Research Funding.

Abstract Abstract 1586 Transformation growth factor (TGF-β) is a highly pleiotropic cytokine critical to a variety of cellular events such as cell differentiation and apoptosis. TGF-β is synthesized as a prepro-TGF-β precursor and secreted after being processed in Golgi apparatus as a latent form that non-covalently combines both TGF-β and latency-associated protein (LAP). Our previous work in B-cell NHL has shown that the intratumoral T cell composition results in the establishment of a profoundly inhibitory tumor microenvironment. However, the underlying mechanism is only partially understood. In this study, using patient specimens and lymphoma cell lines, we evaluated the role of TGF-β in the tumor microenvironment and determined the effect of TGF-β on the generation of intratumoral TH1, TH17 and Treg cells in B-cell NHL. First, we determined expression of TGF-β and found that a latent form of TGF-β was specifically expressed on the surface of CD19+ B cells, but not on other types of cells from B-cell lymphoma biopsy specimens. By screening cell lines, we found that latent TGF-β was also expressed on the surface of lymphoma cell lines, confirming the finding. Second, we tested whether surface expression by lymphoma cells led to the secretion of TGF-β in culture medium. Using an ELISA assay, we detected variable levels of latent TGF-β in the culture medium of primary malignant B cells (median 100 pg/ml per million cells, range: undetectable −229 pg/ml, n=7). Similarly, lymphoma cell lines secreted variable amounts of TGF-β from undetectable to 200 pg/ml per million cells. Next, we determined the effect of TGF-b on intratumoral T cell proliferation and differentiation. As expected, exogenous addition of TGF-β inhibited the proliferation of T cells. Notably, the proliferation of intratumoral T cells was significantly reduced when co-cultured with lymphoma cells bearing an active form of TGF-β compared to that with lymphoma cells without TGF-β. Using flow cytometry, we showed that the addition of exogenous TGF-β enhanced Foxp3 expression in activated CD4+, CD4+CD45RA+ or CD4+CD45RO+ intratumoral T cells, suggesting that TGF-β promotes the generation of Treg cells in tumor microenvironment. In contrast, TGF-β suppressed the expression of IFN-γ in activated CD4+ T cells and inhibited the up-regulation of IL-12 and IL-23-induced IFN-γ expression in CD4+ cells, indicating that TGF-β suppresses the generation of TH1 cells. TGF-β alone slightly inhibited IL-17 expression in CD4+ T cells; however, TGF-β, in the presence of IL-6 and IL-23, up-regulated IL-17 expression in CD4+ T cells, suggesting proinflammatory cytokines are able to reverse the suppression induced by TGF-β. These results suggest that TGF-β controls the generation of TH1, TH17 and Treg cells contributing to the imbalance of effector TH cells and inhibitory Treg cells in the tumor microenvironment of B-cell NHL. Since malignant B-cells produce TGF-β, these results further support the important role of malignant B cells in the regulation of intratumoral T cell differentiation and the host immune response. Disclosures: No relevant conflicts of interest to declare.

Abstract Abstract 2700 Background: Follicular lymphoma is a heterogeneous disease in terms of disease course and prognosis. Clinical risk factors, including age, presence of B symptoms and bulky disease have been shown to have prognostic value. More recently, elements of the tumor microenvironment, including CD68 positive macrophages as well as programmed death-1 (PD-1) expressing lymphocytes, have been shown to be associated with a worse prognosis. However, there is a paucity of data in terms of microenvironment changes that take place in the setting of transformation into diffuse large B cell lymphoma (DLBCL). CD14 is a monocytic marker, and increased numbers of CD14+ cells in the peripheral blood have been associated with a poor prognosis in non-Hodgkin's lymphoma and CLL. It has also been shown that CD14+ cells are present in biopsy specimens in DLBCL and that these cells may support malignant cell growth. This study was designed to examine the presence of CD14+ cells in follicular lymphoma that transformed to DLBCL and to determine the prognostic value of CD14 expression in terms of time to transformation. Methods: Patients with follicular lymphoma who underwent transformation into DLBCL were identified from the Mayo Clinic Lymphoma Database. Controls were follicular lymphoma patients who did not undergo transformation, and were matched 2:1 (control:transformed) on age at diagnosis, year of diagnosis, sex, stage, and length of follow-up time. Tissue specimens at the time of diagnosis were stained for CD14 and CD68, and characterized semiquantitatively based on the presence and distribution of positive cells. Time to transformation (TTT) was assessed using the Kaplan-Meier method. Results: 159 patients were included in the study: 58 patients transformed and 101 did not transform into DLBCL. Median age at diagnosis was 64 years. 150 specimens were sufficient for immunohistochemical analysis. When patients with transformed disease were compared to those who did not transform, those who transformed had greater numbers of CD14+ cells present in their initial diagnostic biopsy (p=0.0415). When only patients who transformed were considered, CD14+ cells in a follicular pattern was associated with a median time to transformation of 3.9 years, CD14+ cells in an interfollicular pattern had a median TTT of 4.9 years and CD14- specimens were associated with a median TTT of 6.2 years (p = 0.0322). The staining pattern for CD68 differed from that of CD14 and was not significantly associated with time to transformation. Conclusions: The presence of intratumoral CD14+ cells at diagnosis in follicular lymphoma is associated with subsequent disease transformation. Our results suggest that when CD14+ cells organize in the follicle, follicular lymphoma patients are likely to transform into DLBCL sooner. Further studies are therefore warranted to define the role of these cells in the tumor microenvironment during transformation to DLBCL. Disclosures: No relevant conflicts of interest to declare.

Abstract T-cell exhaustion plays an important role in attenuating the function of immune cells in B-cell non-Hodgkin's lymphoma (NHL) and PD-1 expression is typically used to identify exhausted T-cells. We have however previously shown that not all PD-1+ cells are exhausted and that PD-1 is differentially expressed on two distinct T-cell subpopulations, with high expression on T follicular helper cells and dim expression on exhausted T cells. Other markers are therefore needed to more clearly identify exhausted intratumoral T cells. To further define exhaustion of intratumoral T cells, we determined the co-expression, regulation and function of PD-1, TIM-3 and LAG-3 on CD4+ or CD8+ T cells by flow cytometry. Using biopsy specimens from follicular B-cell NHL, we found that the percentages of PD-1+ and TIM-3+ T cells were 53.1% (range: 17.2-81.2%, n=32) and 34.5% (range: 14.9-62.6%, n=34) in CD4+ T cells and 46.8% (range: 12.8-81.7%, n=32) and 40.4% (range: 15.0-78.4%, n=34) in CD8+ T cells, respectively. We observed that TIM-3 was predominantly expressed on PD-1dim T cells and TIM-3+ cells accounted for 40% of CD4+ PD-1dim or 45% of CD8+ PD-1dim T cells. Similarly, LAG-3 was variably expressed on intratumoral T cells from B-cell NHL. A median of 9.54% (range: 3.01-15.46, n=6) of CD4+ or 20.48% (7.93-33.9, n=8) of CD8+ T cells express LAG-3. We found that LAG-3+ T cells almost exclusively came from PD-1+ TIM-3+ cells, forming a defined population of intratumoral PD-1+ TIM-3+ LAG-3+ CD4+ or CD8+ T cells. While the majority of LAG-3+ T cells were effector memory T cells (CD45RA- CCR7-), some LAG-3-expressing T cells displayed a phenotype of terminally-differentiated T cells (CD45RA+ CCR7-). Functionally, the intratumoral TIM-3+ LAG-3+ T cells exhibited reduced capacity to produce cytokines (IL-2, IFN-γ) and granules (perforin, granzyme B). Similar to TIM-3, LAG-3 expression was strongly up-regulated on CD4+ or CD8+ T cells by IL-12, a cytokine that has been shown to induce T-cell exhaustion. Interestingly, we observed that while expression of TIM-3 on CD8+ T cells was upregulated by IL-12 at an early time point (day 1), LAG-3 was only induced after TIM-3 up-regulation (day 3) and almost exclusively on TIM-3+ T cells. Furthermore, we found that blockade of both TIM-3 and LAG-3 signaling was able to reverse the exhausted phenotype of CD8+ T cells resulting in increased IFN-γ and IL-2 production. This effect was further enhanced when CD8+ T cells were treated with both anti-TIM-3 and anti-LAG-3 Abs. Taken together, these results suggest that PD-1, TIM-3 and LAG-3 were involved in the induction of exhaustion of T cells in B-cell NHL. We find that PD-1, TIM-3 and LAG-3 are expressed on the same T cells and that blocking TIM-3 and LAG-3 can reverse T-cell exhaustion signaling. These results suggest that PD-1, TIM-3 and LAG-3 play a synergistic role in the development of T cell exhaustion in NHL. Disclosures No relevant conflicts of interest to declare.

Background:T cell Ig and ITIM domain (TIGIT) is an immune checkpoint molecule and a novel member of CD28 family. TIGIT is expressed on 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 expression and function of TIGIT in the blood and tumor microenvironment of patients with B-cell non-Hodgkin lymphoma (NHL) is completely unknown. Goal: To phenotypically and functionally characterize TIGIT+T cell subsets in B-cell NHL and compare expression of TIGIT on intratumoral T cells to normal controls. Results: In peripheral blood, TIGIT expression was not detected on resting T cells. In contrast, when we analyzed biopsy specimens from B-cell NHL patients, we observed that TIGIT is variably but highly expressed on a subset of intratumoral T cells. A median of 41.1% (range: 24.9-56.1, n=5) of CD4+ or 22.2% (range: 13.4-33.3, n=5) of CD8+ T cells from tumor specimens expressed TIGIT on the cell surface. In normal tonsil tissue, expression level of TIGIT was modest or negligible. A median of 12.0% (range: 9.1-15.8, n=5) of CD4+ or 3.9% (range: 1.3-5.7, n=5) of CD8+ T cells express TIGIT on the cell surface, which is significantly lower than that in B-cell NHL (p=0.005 and p=0.003 for CD4+ and CD8+, respectively). We observed that both CD45RA+ and CD45RA- T cells express TIGIT with the greatest expression on the CD45RA- population in B-cell NHL specimens. Furthermore, we found that TIGIT+ T cells coexpressed other immune checkpoint molecules including PD-1 and TIM-3. Functionally, TIGIT+ T cells displayed reduced cytokine production, as the number of IFN-γ- and IL-2-producing cells was lower in the TIGIT+ population than in TIGIT-T cells. Unlike TIM-3 that is coexpressed with PD-1 and whose expression is upregulated by IL-12, TIGIT expression is not upregulated by IL-12, suggesting that a different mechanism is involved in TIGIT upregulation in B-cell NHL. Conclusion: Taken together, these results indicated that TIGIT is highly expressed on intratumoral T cells in B-cell NHL and is expressed on a population of T-cells with suppressed immune function. TIGIT, while co-expressed with PD-1 and TIM-3, is not upregulated by cytokines such as IL-12, suggesting that it is regulated by an alternate pathway. Inhibition of TIGIT signaling may be an additional mechanism to prevent T-cell suppression and exhaustion in B-cell NHL. Disclosures No relevant conflicts of interest to declare.

Abstract Abstract 2688 Members of the signal transducers and activators of transcription (STAT) family of proteins function as secondary messengers mediating cellular responses to various cytokines. Aberrant activation of STAT5 protein has been implicated in the pathogenesis of hematologic malignancies due to the ability of these transcription factors to regulate genes involved in cellular proliferation and survival. The two highly homologous transcription factors collectively known as STAT5, namely STAT5A and STAT5B, display both redundant and distinct physiologic functions in non-malignant B cells. Yet, despite evidence suggesting independent functions for STAT5A and STAT5B in the pathophysiology of solid tumors, the precise roles of these isoforms in hematologic malignancies such as Waldenstrom's macroglobulinemia (WM) are not known. Initial immunohistochemical staining of WM bone marrow biopsies (n=6) revealed higher levels of STAT5 phosphorylation compared to bone marrows from normal controls (n=6). Additionally, phosphorylated STAT5 was highly expressed in CD19/CD138+ sorted cells obtained from the bone marrow of patients with WM (average ΔMFI compared to isotype control, 4.64 +/− 1.7, n=6) as determined by FACS analysis. Furthermore, western blotting demonstrated baseline STAT5 phosphorylation in both WM and IgM-secreting cell lines (MWCL-1 and BCWM-1, respectfully). The expression of other phosphorylated STAT proteins (1, 3, 4, and 6) was not detected. To better understand the overall role of STAT5 biologically in WM, MWCL-1 and BCWM.1 cells were treated with a specific inhibitor of STAT5, N′-((4-Oxo-4H-chromen-3-yl)methylene) nicotinohydrazide. Following 72 hours in culture, this inhibitor significantly decreased IgM secretion at lower doses when compared to controls (10 μM, MWCL-1: 9413 +/− 511 ng/mL vs. 6166 +/− 160 ng/mL, p<0.001; BCWM.1: 13,380 +/− 393 ng/mL +/− 10970 +/− 240 ng/mL, p<0.001) and nearly abolished IgM secretion at higher doses. Significant effects on proliferation and viability were also observed, but only at higher concentrations of drug where the specificity toward STAT5 may have diminished. To characterize the roles of the individual STAT5 isoforms in WM, we have developed doxycycline-inducible STAT5A-shRNA and STAT5B-shRNA and used these to create stable knockdowns in the MWCL-1 cell line. Addition of doxycycline to these cell lines for 72h nearly abolishes STAT5A or STAT5B protein expression, respectively, without affecting expression of the other isoform, while no change in STAT5 expression is detected in cells transduced with the empty vector (EV) control. The functional effects of isoform-specific STAT5 inhibition on WM tumor biology were assessed through proliferation assays and ELISA to determine the utility of therapeutically targeting a single STAT5 isoform. No difference in proliferation was observed in the STAT5A- or STAT5B-shRNA cells following 72h induction with doxycycline as compared to the EV control cells. However, specific knockdown of STAT5A following doxycycline induction significantly decreased IgM secretion as compared to the EV control (EV, 91.8 +/− 10.2% of baseline secretion, STAT5A, 66.7 +/− 15.1% of baseline, p<0.05), whereas IgM secretion was decreased by knockdown of STAT5B but not significantly. Similarly, IL-6 secretion was only diminished in cells lacking STAT5A as compared to EV cells (EV, 94 +/− 14.16% of baseline secretion; STAT5A, 64% +/− 7.6% of baseline, p<0.001). Overall these initial data indicate a role for isoform-specific STAT5 activation in the maintenance of WM tumors, and future studies will further our understanding of the specific roles of STAT5A and STAT5B in WM tumors. Disclosures: Ansell: Seattle Genetics, Inc.: Research Funding.

Abstract Introduction: Myelofibrosis (MF) is a life-threatening hematologic malignancy characterized by splenomegaly and debilitating symptoms including fatigue, abdominal pain, night sweats, bone pain, pruritus, and unintentional weight loss. The myeloproliferative neoplasm symptom assessment form (MPN-SAF) is a PRO tool designed to measure MF-related symptom burden and was developed and validated at Mayo Clinic. It was modified (MPN-SAF total symptom score [TSS] and TSS 2.0) for use in the PERSIST-1 and PERSIST-2 phase 3 trials. For PERSIST-1, when examining the 6 common symptoms in both TSS versions (tiredness, night sweats, early satiety, itchiness, bone pain, and abdominal pain), pacritinib-treated patients (pts) had significant improvements in TSS overall and in individual symptoms vs BAT; Pt Global Impression of Change (PGIC) was also significantly improved for pts receiving pacritinib. Improvements in EORTC-QLQ-C30 scales were noted in the pacritinib arm (Mesa, EHA 2015). The proportion of pts achieving spleen volume reduction (SVR) ≥35% at Week 24 was significantly greater with pacritinib vs BAT (ITT: 19.1% vs 4.7%, p=0.0003; evaluable at baseline and Week 24: 25.0% vs 5.9%; p=0.0001). This analysis examines relationships between TSS improvement and changes in splenomegaly and HRQoL outcomes. Methods: Pts who received no prior JAK inhibitor therapy were randomized 2:1 to oral pacritinib 400 mg once daily or BAT. Pts were stratified by DIPSS risk (Int-1/Int-2 vs High) and platelet count (<50,000/μL vs 50,000/μL to <100,000/μL vs ≥100,000/μL). Pts must have had a baseline total TSS ≥13 using MPN-SAF TSS 2.0. Each symptom is rated on a scale from 0 (absent) to 10 (worst imaginable) using MPN-SAF TSS and TSS 2.0. Results for the 6 symptoms common to both TSS versions are reported. Additional PROs used for assessment of HRQoL included EORTC QLQ-C30 and EQ-5D-5L. In multivariate logistic regressions, odds of TSS reduction ≥50% at Week 24 were modeled as a function of Week 24 SVR ≥35%, spleen length reduction (SLR) ≥ 50%, PGIC, improvement in each EORTC scale, and improvement in EQ-5D-5L Overall Health State (OHS) and in each dimension individually while adjusting for treatment (pacritinib vs BAT). Correlations were examined in all pts and by baseline platelet counts (<50,000/μL, <100,000/μL, and ≥100,000/μL). Results: A total of 327 pts were enrolled (PAC: 220, BAT: 107). 62% of pts had primary MF, 32% had baseline platelets <100,000/μL, and 16% had baseline platelets <50,000/μL. TSS reduction ≥50% was found to be associated with SVR ≥35% and improvement in splenomegaly (SLR ≥50%). In the total pt population, there was a significant association between TSS reduction and SVR (odds ratio [OR]=2.60, p=0.016). In all pts, there was a significant association between TSS reduction and improvements in OHS as measured by EQ-5D-5L (OR=2.30, p=0.013). TSS reductions were also marginally associated with improvements in the QLQ-C30 Global Health Scale (GHS)/QoL Scale (OR=1.92, p=0.050) and, though not statistically significant, there was a trend of improvement in perceived overall health as measured by PGIC (OR=2.16, p=0.118). TSS reductions were further examined in pts grouped by baseline platelet count. Improvement in EQ-5D-5L OHS was marginally associated with TSS reductions in pts with platelets <50,000/μL (OR=6.03, p=0.057). For pts with platelets <100,000/μL, reductions in TSS were significantly associated with reductions in splenomegaly (SLR ≥50%; OR=9.53, p=0.004), and improvements in the QLQ-C30 GHS/QoL domain (OR=4.03, p=0.022) as well as the EQ-5D-5L OHS (OR=5.49, p=0.008). A significant association between TSS reductions and SVR ≥35% was observed in pts with platelets ≥100,000/μL (OR=3.99, p=0.005). In all pts, improvements in Fatigue as measured by QLQ-C30 were significantly associated with TSS reductions (OR=2.20, p=0.019) as well as in pts with baseline platelets <50,000/μL (OR=17.88, p=0.008) and <100,000/μL (OR=10.18, p<0.001). Conclusions: In the total pt population, TSS reduction was associated with improvements in spleen response and perceived overall health. This trend was also observed in pts with low baseline platelet counts. Additionally, TSS reduction was significantly associated with improvements in fatigue, a major contributor to poor HRQoL in pts with MF. This reinforces the clinical relevance of measuring TSS using a validated instrument as an endpoint in MF trials. Disclosures Mesa: NS Pharma: Research Funding; Pfizer: Research Funding; Gilead: Research Funding; Incyte Corporation: Research Funding; CTI Biopharma: Research Funding; Novartis Pharmaceuticals Corporation: Consultancy; Genentech: Research Funding; Promedior: Research Funding. Off Label Use: This abstract discusses off-label use of pacritinib. Harrison:Shire: Speakers Bureau; Novartis: Honoraria, Research Funding, Speakers Bureau; Gilead: Honoraria; CTI Biopharma: Consultancy, Honoraria, Speakers Bureau; Sanofi: Honoraria, Speakers Bureau. Cervantes:Novartis: Consultancy, Speakers Bureau; Sanofi-Aventis: Consultancy; CTI-Baxter: Consultancy, Speakers Bureau. Dean:CTI Biopharma: Employment, Equity Ownership. Wang:CTI Biopharma: Employment, Equity Ownership. Yang:Baxalta: Employment, Other: Stock. Vannucchi:Shire: Speakers Bureau; Novartis Pharmaceuticals Corporation: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Baxalta: Membership on an entity's Board of Directors or advisory committees.