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Abstract The mammalian target of rapamycin (mTOR) exists in two complexes, mTORC1 and mTORC2. Most mTOR inhibitors used for hematologic diseases such as rapamycin, everolimus, and temsirolimus are considered mTORC1 inhibitors and do not target mTORC2. The central role of the mTOR kinase in controlling cell growth has sparked interest in discovering mTOR inhibitors that bind to the ATP active site and therefore target both mTORC2 and mTORC1. mTOR also regulates protein synthesis by phosphorylating the P70S6-Kinase and the eIF4E-binding-protein, 4EBP1. The effect of active site dual mTOR inhibitors on cap dependent translation has not been investigated in lymphomas. In this study we moved beyond the effect of the dual mTOR inhibitor CC214-1 (Celgene Pharmceuticals) on the mTORC2/AKT pathway to focus on its effects on cap dependent protein translation. Cap dependent translation is regulated by the translation initiation complex eIF4F (eIF4E-eIF4G-eIF4A). First, we assessed the formation of the active eIF4F (m7GTP-eIF4E-eIF4G) translation complex by a pull down assay using agarose-immobilized m7GTP cap analog to capture eIF4E and its binding partner in lymphoma cell lines (Jeko, Mino, Granta and JVM2, Ly3, Ly1, DHL6) and in primary cells (n=5). Our data demonstrate that the cap bound fraction from normal B cells contain very little eIF4G and eIF4A; however, lymphoma cells were enriched with eIF4G, eIF4E and eIF4A. Increased mRNA of eIF4E and eIF4G was observed in all lymphoma cell lines tested as compared to normal B-cells. 150 untreated diffuse large B cell lymphoma samples were stained for eIF4E by immunohistochemistry and 76% (135/150) were found eIF4E positive. Taken together, these data suggest that lymphoma cells exist in a translational activated state compared to normal B-cells. Next, we examined the effect of the dual mTOR inhibitor CC214-1 on the integrity of the eIF4F complex. In the CC214-1 treated cells the quantity of the eIF4E bound to 4EBP1 was increased whereas the amount of the eIF4E bound to eIF4G was decreased in the CC214-1 treated lymphoma cells but not in those treated with a selective mTORC1 agent (everolimus). We also found that the phosphorylation of 4EBP1 that controls protein synthesis is partially resistant to everolimus/rapamycin but fully suppressed with CC214-1. CC214-1 had a dose-dependent inhibitory effect on lymphoma cell survival; however, everolimus and rapamycin were only cytostatic. Moreover, CC-214 was much more potent than rapamycin and everolimus in blocking protein translation measured by the leucine incorporation assay. To elucidate the role of the eIF4E complex in the response to CC214-1, we transiently expressed WT-eIF4E plasmid in Jeko cells and then treated with CC214-1. Ectopic expression of wt-eIF4E led to a loss in the CC-214-1 dependent decrease in the eIF4E bound eIF4G as compared with the control plasmid. Moreover, overexpression of eIF4E also protected against CC214-1-induced apoptosis. To evaluate the efficiency of cap-dependent translation in the presence of CC214-1 and rapamycin, we used the bicistronic reporter assay where translation initiation of the first cistron is dependent on the 5′ cap, whereas initiation of the second cistron depends on a viral internal ribosome entry site. Transfection of this plasmid in CC214-1 treated cells caused a significant decrease in cap-dependent, but not IRES-dependent, translation. We next looked the effect of CC214-1 on the eIF4E regulated translationally active mRNA targets. We isolated eIF4E known mRNA targets (Myc, Cylin D1, Cyclin D2 and MCL-1) by immunoprecipitation assays using eIF4E antibody (mRNA-IP). CC214-1 treated RNA-IP data showed decreased expression of Myc but not the other mRNA targets. Myc is highly expressed in the DLBCL tumors and would be a good prognostic or predictive biomarker for CC214-1 therapy. Translation deregulation is an important mechanism that causes aberrant cell growth in lymphoma cells. Currently, there is a need to identify additional agents that target this pathway. These studies provide a mechanistic basis of targeting cap dependent translation in lymphoma through next generation dual mTOR inhibitors. This study also suggests eIF4E (indicative of activated eIF4F complex) as a potential biomarker for the selection of patients for next generation mTOR inhibitors clinical trials in lymphoma patients. Disclosures: No relevant conflicts of interest to declare.

Abstract Background The JAK1/JAK2 inhibitor ruxolitinib (RUX) is approved for treatment of myelofibrosis (MF). However, some patients do not respond to RUX, while others lose responsiveness or develop intolerance to RUX over time. Preclinical data also suggest that certain JAK2 mutations (eg the gatekeeper mutation M929I) may confer resistance to RUX (Leukemia 2012;26:708). Options for these RUX resistant/intolerant patients, particularly with regard to further JAK inhibitor therapy, are unclear. Fedratinib (SAR302503) is a JAK2-selective inhibitor which has demonstrated clinically meaningful reductions in splenomegaly and symptom burden in patients with MF, with an acceptable and consistent safety profile (J Clin Oncol 2011;29:789. Haematologica 2013;98:S1113). Fedratinib sensitivity in vitro is unaffected by the M929I mutation. This pre-specified interim analysis of the JAKARTA-2 study (NCT01523171) investigated the efficacy and safety of fedratinib in MF patients previously treated with RUX. Methods JAKARTA-2 is a Phase II, multicenter, open-label, single-arm study of patients who previously received RUX for MF. Patients ≥18 yrs with splenomegaly and platelet count ≥50 ×109/L received fedratinib 400 mg orally, once daily for consecutive 4-wk cycles (permitted dose adjustment to 200–600 mg daily). Eligible patients had received ≥14 d RUX treatment, and had discontinued RUX for ≥14 d prior to starting fedratinib. Although there is no consensus definition of RUX resistance/intolerance, for the purpose of this study patients were classed (investigator assessment) as resistant (lack or loss of response) or intolerant to RUX. Primary endpoint for the interim analysis: spleen response rate (RR) (≥35% reduction in spleen volume from baseline at Wk 12 [MRI/CT blinded central review]) in the per-protocol (PP) population. Secondary endpoints: symptom RR (≥50% reduction in total symptom score [TSS: modified Myelofibrosis Symptom Assessment Form] from baseline to Wk 12) and safety. Results At the cut-off date for this interim analysis, 27 patients had received fedratinib treatment (median RUX exposure 10.7 months [range 1.9–34.4]): median age 69 yrs; 56% male; 67% primary MF; 63% high-risk MF; 67% JAK2V617F positive; 41% platelet count <100 × 109/L; baseline median spleen volume 3190 mL [1072–7815]; baseline median TSS 19.6 [4.9–46.0]. Eighteen patients were considered resistant by the treating physician (8 lack of response, 3 disease progression, 7 loss of response; median RUX exposure 11.1 months [range 1.9–34.4]) and 9 intolerant (6 hematologic, 3 non-hematologic toxicity; median RUX exposure 9.2 months [2.9–33.2]) to RUX. Median fedratinib exposure to cut-off date: 4 cycles (range 1–10); 19 patients remain on treatment. Spleen RRs were 40% (8/20 PP patients) and 43% (3/7) in patients with baseline platelet count <100 ×109/L. Overall, 19% (5/26 evaluable patients) had a symptom response by Wk 12 (Table). The majority of patients had a reduction in TSS at Wk 12 (Figure). The most common non-hematologic treatment-emergent adverse events (AEs) were gastrointestinal (nausea 67%; diarrhea 56%; vomiting 48%). Grade 3/4 diarrhea occurred in 2 patients; no Grade 3/4 vomiting or nausea. Anemia was the most common hematologic AE (all grades, 93%; Grade 3, 41%; Grade 4, 0%). Thrombocytopenia (all grades) occurred in 19 (70%) patients; Grade 3 in 6 patients and Grade 4 in 2 patients. One patient had Grade 3 AST elevations and 1 patient had Grade 3 hyperbilirubinemia. Seven patients (26%) discontinued treatment due to AEs. There were 2 deaths on study, both due to disease progression. Conclusions Interim results from the JAKARTA-2 study indicate that once-daily fedratinib provides clinical benefit, through reduced splenomegaly and symptom burden, in MF patients previously treated with RUX. The safety profile was acceptable and manageable, with safety results to date consistent with those reported in previous trials of fedratinib. Sponsored by Sanofi. Disclosures: Harrison: Novartis: Research Funding; Novartis, Sanofi, YM Bioscience, Celgene, SBio, Gilead: Honoraria; Novartis, Sanofi, Shire: Speakers Bureau; Novartis, Sanofi, YM Bioscience, SBio, Gilead: Membership on an entity’s Board of Directors or advisory committees. Jourdan:Sanofi: Honoraria. Kiladjian:Novartis, Celgene, AOP Orphan: Research Funding; Novartis, Sanofi, AOP Orphan: Honoraria; Novartis, Sanofi, AOP Orphan: Membership on an entity’s Board of Directors or advisory committees. Cervantes:Novartis: Speakers Bureau; Novartis and Sanofi: Membership on an entity’s Board of Directors or advisory committees. Niederwieser:Novartis Pharma: Consultancy. Cortes:Incyte, Sanofi: Consultancy; Incyte, Sanofi: Research Funding. Passamonti:Novartis, Celgene, Incyte, Sanofi, Roche: Honoraria. Reiter:Sanofi: Honoraria. Heidel:Novartis Inc.: Honoraria; Novartis Inc.: Research Funding; Novartis Inc.: Membership on an entity’s Board of Directors or advisory committees. Silver:Sanofi: Consultancy; Sanofi: Research Funding; Sanofi: Honoraria. Winton:Sanofi: Research Funding. Gupta:Incyte, Novartis: Consultancy; Incyte, Novartis: Research Funding; Novartis: Honoraria. Gisslinger:AOP Orphan Pharmaceuticals, Novartis, Sanofi, Shire, Celgene, Janssen: Membership on an entity’s Board of Directors or advisory committees; AOP Orphan Pharmaceuticals, Novartis, Sanofi, Shire, Celgene, Janssen: Honoraria. Vannucchi:Novartis: Membership on an entity’s Board of Directors or advisory committees. Talpaz:Novartis, Bristol-Myers Squibb, Ariad, Deciphera: Research Funding; Novartis, Bristol-Myers Squibb, Ariad, Deciphera: Speakers Bureau. Zhang:Sanofi: Employment. Shi:Sanofi: Employment. Mesa:Incyte, Genentech, Lilly, MS Pharma, Gilead: Research Funding.

Abstract Abstract 897 Recent changes in allogeneic hematopoietic cell transplantation (HCT) including increased use of reduced-intensity conditioning, peripheral blood cells as the graft source (PB) and unrelated donors (URD) warrant re-evaluation of risk factors for acute graft-versus-host disease (aGVHD) and its impact on overall survival (OS). Risk factors for these outcomes were analyzed using more recent data from CIBMTR observational database. Methods: The cohort included adult patients ≥ 20 y transplanted from an HLA-identical sibling (SD) (n=3191) or URD (N=2370) for acute myelogenous leukemia (AML), acute lymphoid leukemia (ALL), chronic myeloid leukemia (CML), or myelodsyplastic syndrome (MDS) using a T-cell replete graft from 1999–2005. Six groups were created to evaluate the impact of conditioning [(myeloablative (MA) and reduced-intensity or non-myeloablative (RIC)], total-body irradiation (TBI) and graft source [(bone marrow (BM) or PB] as follows: MA+TBI+PB (group 1), MA+TBI+BM (group 2) MA+ no TBI+PB (group 3), MA+ no-TBI+BM (group 4), RIC+PB (group 5) and RIC+BM (group 6). Separate analyses were performed for SD and URD. IBMTR grade was used to classify aGVHD. A p-value of ≤ 0.01 was considered significant. Results: Among the SD cohort, the probability of aGVHD grade B-D and grade C-D at 100 days was 39% (95% CI, 37–41%) and 16% (95% CI, 14–17%). In multivariate analyses, non-TBI based MA regimens with a BM graft (group 4), RIC conditioning with PB (group 5) and tacrolimus plus methotrexate aGVHD prophylaxis were associated with lower odds ratio of grade B-D aGVHD (Table 1). The probability of OS was 51% (95% CI: 49–53%) at 3 y and 46% (95% CI: 44–49%) at 5 y. In multivariate analyses, grade B-D aGVHD was associated with a higher risk of death. Other independent risk factors for OS are shown in Table 2. Among the URD cohort, the probability of aGVHD grade B-D and C-D at 100 days was 59% (95%, CI 57–61%) and 32% (30-34%). In multivariate analysis, BM with MA (TBI and no TBI) or RIC conditioning (groups 2, 4 and 6) were significantly associated with lower odds ratio of grade B-D aGVHD (Table 1). Other independent risk factors included a diagnosis of CML. HCT from a 7/8 HLA-mismatched URD showed a trend for higher incidence of aGVHD (p=0.02). The probability of OS was 38% (95% CI: 35–40%) at 3 y and 33% (95% CI: 31–35%) at 5 y. In multivariate analysis, grade B-D aGVHD was associated with a higher mortality. Table 2 shows other independent risk factors for OS. Conclusion: Intensity of the conditioning regimen, TBI and the graft source has a combined effect on the risk of aGVHD. In both SD and URD cohorts, BM with MA, non-TBI regimens were associated with lower risk of aGVHD. In URD cohort, BM after a RIC also was associated with a reduced risk of aGVHD. Modulation of these risk factors is needed to reduce acute GVHD incidence and death after allogeneic transplantation. Disclosures: No relevant conflicts of interest to declare.

Abstract Long noncoding RNAs (lncRNAs) are defined as RNA-like transcripts that are over 200 nucleotides and lack significant open reading frames. Some lncRNAs such as HOTAIR, MALAT1 and H19 have been found to be associated with clinical prognosis and are potential drivers of cancer progression in cancers of the breast, lung, and liver respectively. The role of lncRNAs in lymphoma is unknown. Dysregulation of eIF4E (a key component of the translation initiation complex eIF4F) influences global protein translation, especially the translation of “weak” mRNAs that can be malignancy-related. We and others have found that eIF4E is dysregulated in B-cell lymphoma. The aim of this study is to identify eIF4E-associated lncRNAs through next generation RNA-Sequencing (NGS RNA-Seq) and delineate their role in protein translation in lymphoma. RNA-immunoprecipitation (RNA-IP) was used to pull down eIF4E-bound lncRNA in lymphoma cells. eIF4E-bound lncRNAs were immunoprecipitated with eIF4E antibody or IgG control in Jeko, a mantle cell lymphoma (MCL) cell line and sent for microarray analysis and NGS-RNA-Seq for identification of lncRNAs. The microarray analysis showed that several lncRNAs were enriched with eIF4E antibody compared to IgG control. These included SNHG4 (13.6 fold), SNHG12 (4.8 fold), NCRNA00171 (4.8 fold) and IPW (4.6 fold), GNASAS (3.5 fold), SNHG7 (3.3 fold), NCRNA00182 (2.7 fold), NCRNA00094 (2.6 fold), NCRNA00188 (2.4 fold) and NCRNA00201 (2.1 fold). The binding of these lncRNAs to eIF4E was further confirmed by RT-PCR in Jeko, Mino and Granta MCL cell lines. Next, we looked the expression of these lncRNAs by qRT- PCR in the MCL cell lines and normal controls. We found SNHG4 and IPW to be overexpressed in all the MCL cell lines, while SNHG12 and NCRNA00201 were overexpressed in the selected cell lines. No significant difference was found for the expression of NCRNA00171 and NCRNA00182 in any of the MCL cell lines compared to controls. Overall, these data suggest that several lncRNA have altered expression in malignant B-cells. Considering that the microarray assay only covered a limited number of lncRNAs, we further confirmed eIF4E bound lncRNA by NGS RNA-Seq in Jeko MCL and normal control. The binding of 10/13 lncRNA mentioned above with eIF4E were found upregulated by NGS-RNA-Seq. In addition several novel lncRNAs such as SNHG1 (161.6), AC091814.2 (98.8) and RP11-304L19.5 (64.2) showed up in NGS-RNA-Seq data. These data suggest that lncRNAs, such as SNHG12, SNHG4, and SNHG1 bind to eIF4E with high affinity in malignant B-cells and might play a role in protein translation. We knocked down the expression of SNHG4 through siRNA and demonstrated that cell proliferation and global protein translation was inhibited in lymphoma cells. To further confirm the role of SNHG4 in translation regulation, a plasmid, which contains a renilla luciferase driven by SV40 promoter, was co-transfected with SNHG4 siRNA into Mino cells. The luciferase signal, decreased compared with the cells transfected with nontargeting siRNA. These data suggest that SNHG4 is involved in the regulation of protein translation. In order to clarify the mechanism of lncRNAs bound to eIF4E we searched for RNA binding sites or motifs in eIF4E protein using the web-based tools, BindN and PPRInt. Interestingly two RNA binding motifs, KNKRGGRWLITLNKQQRRS and SHADTATKSGSTTKNR, were found in eIF4E based on the prediction. To examine whether lncRNAs bind with eIF4E through these RNA binding motifs, an eIF4E mutant plasmid with both RNA binding motifs deleted (eIF4EDel), was constructed and transfected transiently into HEK-293T cells along with eIF4EWT plasmid. RNA-IP data showed that the lncRNAs SNHG12, SNHG4 and SNHG1 were not able to bind with eIF4E in eIF4EDel-transfected cells compared with that of eIF4EWT, suggesting that these lncRNAs complex with eIF4E through RNA-binding motifs within the eIF4E. Overall, our results show that the lncRNAs, SNHG1 and SNHG4 are able to bind with eIF4E and regulate protein translation. Since lncRNAs had been found to play roles in the regulation of gene expression, including transcription, splicing and mRNA stability, our results may broaden the view of the functional role of lncRNAs in translation in lymphoma cells and in other cancers. Furthermore, our results also suggested that SNHG4 lncRNAs might be served as potential biomarkers for MCL and other B cell lymphomas for translation therapy. Disclosures: No relevant conflicts of interest to declare.

Abstract Background The presence of circulating plasma cells (PCs) in multiple myeloma (MM) is a known poor prognostic marker. Prior studies have utilized a technically challenging slide-based immunofluorescence technique to detect and quantify the presence of circulating PCs which was not widely adapted in clinical practice. More recently, the routine use of flow cytometry has provided the opportunity to quantitatively assess circulating PCs in MM patients with relative ease. We report the prognostic value of quantifying circulating clonal PCs using multiparametric flow cytometry in MM patients with relapsed disease. Methods We evaluated all MM patients seen at the Mayo Clinic, Rochester from 2009 to 2011 with previous or ongoing relapsed disease and who had their peripheral blood samples evaluated by flow cytometry. Each blood sample had its peripheral blood mononuclear cells isolated by ficoll gradient and stained with antibodies to CD45, CD19, CD38, CD138 and cytoplasmic Kappa and Lambda Ig light chains. A six-color multi-parameter flow cytometer (Becton Dickinson FacsCantos II) was used to examine each sample with a target of detecting 150,000 events (cells) that was then analyzed using the Facs Diva Software. Plasma cells were selectively analyzed through combinatorial gating using light scatter properties and CD38, CD138, CD19, and CD45. Normal PC's were then separated from clonal plasma cells based on the differential expression of CD45, CD19 and polytypic Ig light chains. The clonal plasma cells detected were reported out as the number of clonal events/150,000 collected total events. For those samples where less than 150,000 events were gated or examined, the number of final clonal events was adjusted to 150,000 events. Survival analysis was performed by the Kaplan-Meier method and differences in survival assessed using the log rank test. Results There were 647 consecutive patients with a history of treated MM who had a peripheral blood flow cytometry as part of their routine clinical evaluation. The median patient age was 62 years (29-88) and 55% were male. The median time since diagnosis was 12 months (range: 1-363) and the median number of lines of treatment received was 2 (1-11). There were 81 (13%) patients with clonal circulating PCs with a median of 368 cells (4 – 133,464). The 2-year overall survival (OS) for the 81 (13%) patients with any circulating PCs was 17% compared with 65% for those with none (P<0.001). The presence of circulating clonal PCs was associated with high-risk disease by FISH (P <0.001) as well as higher PCLI (P <0.001). We then correlated the presence of circulating clonal PCs with the disease status at flow cytometry assessment. Among the study patients, only 145 (22%) had actively relapsing disease with the remaining 502 (78%) in a plateau including patients in CR. Circulating clonal PCs were more likely to be detected in patients with actively relapsing disease compared with plateau phase (43% vs. 4%, P < 0.001); none of the CR patients and <5% of the remaining plateau phase patients had any detectable circulating clonal PCs. We then restricted the analysis to the actively relapsing patients; the best cutoff predicting 1-year mortality by ROC analysis was 100 events. Based on this, we defined >=100 events as a cutoff for defining the prognostic role of circulating clonal PCs in actively relapsing patients. The median OS for those with >=100 clonal PC events was 12 months compared with not reached for those with <100 events (p<0.001; Figure 1 ). Among patients with actively relapsing disease, >= 100 circulating PCs was associated with a higher ISS stage, plasma cell labeling index and bone marrow PC% compared with those with <100 circulating PCs. In a multivariable model, only LDH > 222 (HR: 2.08, P = 0.045) and >= 100 circulating PCs (HR: 2.48, P = 0.048) were found to adversely affect OS in actively relapsing patients. Conclusion The utilization of flow cytometry to quantify circulating clonal PCs in patients with relapsed MM appears to have significant prognostic relevance. In patients with actively relapsing disease, >= 100 circulating PCs predicted for worse OS with a median of 12 months. Future studies are needed to determine if this would allow an opportunity to develop a more risk adapted approach for patients with relapsed disease. Disclosures: Kumar: Celgene: Consultancy, Research Funding; Millennium: Consultancy, Research Funding; Onyx: Consultancy, Research Funding.

Abstract Abstract 3678 The JAK/STAT pathway is becoming a relevant target for lymphoma therapy and inhibitors of the pathway are now in clinical trial. It would be ideal to identify patients for trial by assessment of pathway activation. We analyzed the primary tumors from 50 patients with diffuse large B cell lymphoma (DLBCL) using antibody against phosphorylated tyrosine signal transducer and activator of transcription 3 (STAT3) revealed that 52% (21/40) of DLBCL tumors express tyrosine phosphorylated STAT3 (pSTAT3). There are several potential mechanisms of activation of the JAK/STAT pathway. Protein tyrosine phosphatases such as SHP1 are key negative regulators of this pathway. SHP-1 is also considered a tumor suppressor gene because of its ability to antagonize the action of tyrosine kinases. Persistent activation of STAT3 seems to play a critical role in the pathogenesis of several malignancies. In an attempt to determine mechanism of STAT3 phosphorylation, we analyzed SHP1 expression and its correlation to STAT3 phosphorylation in DLBCL tumors. We analyzed SHP1 expression by immunohistochemistry (IHC) in a tissue microarray composed of 27 DLBCL tumor samples. SHP1 was found silenced in 33% (7/27) of DLBCL cases. To confirm our IHC data SHP1 mRNA expression was also analyzed in DLBCL patients (n=7) and CD19+ normal B cells (n=3) using reverse transcriptase polymerase chain reaction (RT-PCR). SHP1 expression was found silenced in 57% (4/7) of cases, however normal B cells expressed a significant amount of SHP1 mRNA transcripts. We next sought to determine the mechanism of SHP1 silencing in these patients. DNA methylation is the most common mechanism of gene silencing and gene inactivation in human cancers and methylation of a cluster of CPG sites near the proximal SHP1 promoter 2 has been shown in myeloma and T cell lymphoma cells. We analyzed the frequency of SHP1 DNA methylation in 40 DLBCL patients and in DLBCL cell lines by analyzing the proximal promoter regions for SHP1 with methylation specific (MSP) and unmethylation specific (UMSP) PCR primers. We found SHP1 methylation in 2.5% (1/40) DLBCL tumors and none of the DLBCL cell lines tested (OCILy3, OCILy10, SUDHL2, SUDHL6, OCILy19 and OCILy1) were positive for methylation. Furthermore, bisulphite sequencing of the MSP product confirmed methylated cytosines in the one MSP-positive DLBCL patient sample and in the positive control (methylated DNA). We next confirmed our MSP methylation results in the 40 DLBCL tumors DNA with a high resolution melting (HRM) methylation array for accurate detection of changes in the CpG methylation. The primers were designed to flank CpG islands, not to specifically amplify (converted) methylated or unmethylated DNA (as in MSP PCR). Data were normalized to an unmethylated control. Based on the melting profile, there was no methylation in the controls but detectable methylation (>5%) in the SHP1 promoter region was found in 10% (4/40) of DLBCL samples. The one sample that was positive with MSP PCR was also >50% methylated by HRM. Next we analyzed whether there is any correlation between SHP1 expression and tyrosine phoshorylated STAT3 (pSTAT3). In the 27 cases of DLBCL studied, 16 were pSTAT3 negative and 11 were pSTAT3 positive by IHC. 50% (8/16) of the pSTAT3 negative cases had very high expression of SHP1. Similarly, 45 % (5/11) of pSTAT3 positive cases were SHP1 negative consistent with loss of SHP1 gene expression. These data suggest that loss of SHP1 expression is one of several potential mechanisms that can contribute to increased tyrosine STAT3 activation in DLBCL. In addition, these data suggest that CPG island promoter hypermethylation in the SHP1 promoter is not associated with SHP1 gene silencing in DLBCL tumors. Disclosures: No relevant conflicts of interest to declare.

Abstract Abstract 3842 Background: Dysregulated JAK-STAT signaling is a key feature in MF, which is characterized by splenomegaly, debilitating symptoms, poor quality of life (QoL), cytopenias, and shortened survival. Ruxolitinib is a selective JAK1 and JAK2 inhibitor with clinical activity in MF. COMFORT-I is a Phase III, double-blinded, placebo-controlled study of ruxolitinib in patients with MF. At wk 24, 41.9% of patients receiving ruxolitinib reached the protocol-defined threshold of a ≥35% reduction in spleen volume (SV) compared to 0.7% in the placebo group (p<0.0001). The objective of this analysis was to evaluate the relationship between SV reduction achieved with ruxolitinib treatment and changes in symptoms and QoL. Methods: 309 patients were randomized to receive ruxolitinib (n=155) or placebo (n=154). Initial dosing was based on baseline platelet counts: 15 mg BID for counts of 100–200 x109/L and 20 mg BID for >200 x109/L. SV was measured by blinded imaging (MRI or CT scan) every 12 wks. Via electronic diary, patients reported MF symptoms daily using the modified Myelofibrosis Symptom Assessment Form (MFSAF) v2.0. The Total Symptom Score (TSS) from the MFSAF represents a combined score for the individual symptoms of abdominal discomfort, pain under ribs on left side, early satiety, itching, night sweats, and bone/muscle pain. The European Organization for Research and Treatment of Cancer Quality-of-Life 30 (EORTC QLQ-C30) and Patient-Reported Outcomes Measurement System (PROMISE) Fatigue questionnaires were administered at each visit; Patient Global Impression of Change (PGIC) was administered at every visit beginning at wk 4. The PGIC rates a patient's overall sense of whether a treatment has been beneficial or not on a 7-point scale, ranging from 1 = very much improved to 7 = very much worse, with 4 = no change. Results: Baseline QoL scores reflected debilitating disease, and were similar to scores for similar-aged patients with other cancers (Scott NW, Fayers PM, Aaronson NK, et al. EORTC QLQ-C30 Reference Values Manual, July 2008). The impact on patients was particularly evident on the PROMIS Fatigue scale and QLC-C30 Global Health, Physical Functioning, Role Functioning, and Social Functioning subscales. Baseline Symptom and QoL Measures* Associations between changes in symptoms and QoL with the objectively measured changes in SV were evaluated. Patients receiving ruxolitinib were grouped according to SV reduction at 24 wks of treatment: ≥35% reduction in SV (n=65), 10-<35% (n=51), and <10% (n=23). Symptom and QoL responses were evaluated among the various subgroups (of the SV reduction percentage strata) and comparisons were made across these and the total placebo group (n=106). Shown in the Figure are mean changes at wk 24 relative to baseline for TSS, QoL indicators, and PGIC scores. Conclusions: Changes in SV as low as 10% in ruxolitinib-treated patients were associated with improvements on EORTC QLQ-C30 Global Health subscale, PROMISE Fatigue scale, and the MFSAF v2.0 diary TSS. Moreover, commensurate improvements in these outcomes were observed as the SV reduction increased. Importantly, the simple PGIC questionnaire allowed patients to characterize a meaningful change in their condition that was consistent with more comprehensive measures of MF symptoms and quality of life, reflecting a doctor-patient assessment easily applied to clinical practice. Disclosures: Mesa: Incyte: Research Funding; Lilly: Research Funding; SBio: Research Funding; Astra Zeneca: Research Funding; NS Pharma: Research Funding; Celgene: Research Funding. Gotlib:Incyte: Consultancy, Research Funding. Gupta:Incyte: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Catalano:Incyte: Honoraria; Novartis: Honoraria. Deininger:BMS: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Ariad: Consultancy, Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; Genzyme: Research Funding. Shields:Incyte: Consultancy. Miller:Incyte: Research Funding; Novartis: Honoraria, Research Funding, Speakers Bureau. Winton:Incyte: Consultancy. Hare:Incyte: Employment. Erickson-Viitanen:Incyte: Employment. Sun:Incyte: Employment. Sandor:Incyte: Employment. Levy:Incyte: Employment, Equity Ownership. Kantarjian:Incyte: Research Funding; Novartis: Consultancy, Research Funding. Verstovsek:Incyte: Research Funding.

Abstract Background In the primary analysis of the phase III COMFORT-I study, the JAK1/JAK2 inhibitor ruxolitinib (RUX) significantly improved splenomegaly, myelofibrosis (MF)-related symptoms, and quality of life (QoL) measures in patients (pts) with MF versus placebo (PBO). An additional analysis (median follow-up 51 weeks [wks)]) showed RUX was associated with a survival advantage versus PBO (Verstovsek et al. N Engl J Med2012). Longer term follow-up (median 102 wks) showed durable SV reductions and QoL improvements. At this time point, RUX continued to be associated with a survival advantage, despite all pts originally randomized to PBO having discontinued or crossed over to ruxolitinib shortly after the primary analysis (Verstovsek et al. ASH 2012. abstract 800). We report additional longer-term follow-up of pts from COMFORT-I. Methods In COMFORT-I, 309 pts were randomized (1:1) to RUX or PBO. RUX starting dose depended on baseline platelet count (100–200´109/L: 15 mg BID; >200´109/L: 20 mg BID). Doses could be titrated for lack of efficacy or excess toxicity as specified in the protocol. Pts receiving PBO could crossover to RUX after the primary analysis (ie, when all pts completed 24 wks and half the pts completed 36 wks of therapy) or at any time if they met protocol-specified criteria for worsening splenomegaly. The primary endpoint was the proportion of pts who achieved a ≥35% reduction in spleen volume (SV) at wk 24. Symptoms were assessed up to wk 24 using the modified MF Symptom Assessment Form v2.0. QoL continued to be evaluated beyond wk 24 using the EORTC QoL Questionnaire-Core 30 (QLQ-C30). Survival was estimated by Kaplan-Meier analysis according to original randomized treatment. To better understand the effect of crossover on the PBO arm, statistical modeling of survival was conducted using a generalized Gamma distribution. Results Median follow-up was 149 wks at the time of this updated analysis. Of 155 pts originally randomized to RUX, 77 remain on therapy. Of 154 pts originally randomized to PBO, 111 crossed over to RUX; the median time to crossover was 41.1 wks (range, 5.1–65.4). At wk 24, pts originally randomized to RUX had a mean SV reduction of −31.6%; this was durable for pts who continued on RUX, where the mean SV reduction at wk 144 was −34.1%. Fifty-nine percent (91/155) of pts originally randomized to RUX achieved a ≥35% SV reduction at any time during study; for these pts, the probability of maintaining this response for >132 weeks from the time of their initial response was 0.53. Pts originally randomized to RUX who continued on therapy experienced durable improvements in the Global Health Status/QoL and functional domains of the EORTC QLQ-C30. Overall survival favored RUX (HR=0.69; 95% CI: 0.46, 1.03; P= 0.067; Fig 1), with 42 and 54 deaths among pts originally randomized to RUX and PBO, respectively. Modeling of the hazard function of death over time to explore the effect of crossover to RUX in pts originally randomized to PBO showed a decrease in hazard for these pts, which corresponded to an increased proportion of pts crossing over to RUX. In pts originally randomized to RUX who continued on therapy, there was no substantial change in the rate, distribution, or severity of nonhematologic adverse events (AEs) with longer-term therapy; most nonhematologic AEs were grade 1 or 2. Mean and median hemoglobin and platelet count remained stable with longer-term therapy. Consistent with this, the incidence of new onset grade 3 or 4 anemia and thrombocytopenia observed after the first 6 months of RUX therapy decreased relative to that seen in the first 6 months of therapy (Fig 2). With approximately 1 year of additional follow up, 4 new cases of acute myeloid leukemia were reported: 2 pts originally randomized to PBO (376 and 666 days after crossover to RUX) and 2 pts originally randomized to RUX (848 and 1143 days after starting RUX). Conclusions After a median follow-up of 149 wks, the hazard ratio for overall survival favored pts originally randomized to RUX over those originally randomized to PBO, the majority of whom crossed over to RUX. The hazard of death for pts originally randomized to PBO decreased as pts crossed over to RUX. SV reductions and QoL improvements were sustained with longer-term therapy. The incidence of new onset grade 3 or 4 anemia and thrombocytopenia decreased with longer-term therapy. Collectively, these data reinforce the durable efficacy and longer-term safety of RUX in pts with MF. Disclosures: Verstovsek: Incyte Corporation: Research Funding. Mesa:Genentech: Research Funding; NS Pharma: Research Funding; Gilead: Research Funding; Incyte Corporation: Research Funding; Lilly: Research Funding. Gotlib:Incyte Corporation: Travel support, Travel support Other; Incyte Corporation: Membership on an entity’s Board of Directors or advisory committees; Incyte Corporation: Research Funding. Levy:Incyte Corporation: Equity Ownership; Incyte Corporation: Employment. Gupta:Incyte Corporation: Consultancy; Novartis: Consultancy; Inctye Corporation: Research Funding; Novartis: Research Funding; Novartis: Speakers Bureau. Deininger:BMS, ARIAD, NOVARTIS: Consultancy; BMS, NOVARTIS, CELGENE, GILEAD: Research Funding; ARIAD, NOVARTIS: Advisory Boards, Advisory Boards Other. Miller:Novartis: Consultancy; Incyte Corporation: Consultancy; Novartis: Research Funding; Incyte Corporation: Research Funding; Novartis: Honoraria; Incyte Corporation: Honoraria. Talpaz:Ariad: Consultancy; Novartis: Consultancy; BMS: Consultancy; Pfizer: Consultancy; Ariad: Membership on an entity’s Board of Directors or advisory committees; Novartis: Membership on an entity’s Board of Directors or advisory committees; BMS: Membership on an entity’s Board of Directors or advisory committees; Pfizer: Membership on an entity’s Board of Directors or advisory committees. Winton:Incyte Corporation: Research Funding; Incyte Corporation: Membership on an entity’s Board of Directors or advisory committees. Arcasoy:Incyte Corporation: Research Funding. Lyons:Lilly: Research Funding; Amgen: Research Funding; Celgene: Research Funding; Incyte Corporation: Research Funding; Gilead: Consultancy; Seattle Genetics: Research Funding; Gilead: Research Funding; Ariad: Research Funding; GlaxoSmithKline: Research Funding; Novartis: Research Funding. Paquette:Incyte Corporation: Consultancy. Raza:Novartis: Speakers Bureau; Onconova Inc: Research Funding. Vaddi:Incyte Corporation: Employment; Incyte Corporation: Equity Ownership. Sun:Incyte: Employment; Incyte: Equity Ownership. Peng:Incyte Corporation: Employment; Incyte Corporation: Equity Ownership. Sandor:Incyte: Employment; Incyte: Equity Ownership. Kantarjian:Ariad: Research Funding; Novartis: Research Funding; BMS: Research Funding; Pfizer: Research Funding.

Abstract Abstract 970 The mammalian target of rapamycin, mTOR, is a highly conserved serine/threonine kinase known to play a role in regulating mRNA translation, cell cycle progression, cell proliferation and apoptosis. As a downstream effector of the phosphatidylinositol 3-kinase (PI3K)/Akt signaling pathway, mTOR is a component of two distinct complexes, TORC1 and TORC2. While TORC1 facilitates cell cycle progression from G1 into S phase by phosphorylating p70S6 kinase and eukaryotic initiation factor 4E binding protein 1 (4E-BP1), TORC2 catalyzes the activating phosphorylation of Akt on Ser473, providing a feedback loop for further activation of mTOR. Phase II trials have shown activity of the TORC1-selective inhibitor rapamycin and its analogs in a wide range of lymphoma subtypes. The purpose of this study was to evaluate the anti-proliferative and pro-apoptotic effects of the dual TORC1/TORC2 inhibitor OSI-027 in human neoplastic lymphoid cells in vitro. MTS assays demonstrated that OSI-027 inhibited proliferation in a wide range of lymphoid lines, including SeAx (Sezary syndrome), DoHH2 (large cell lymphoma), RL (follicular lymphoma) and Jurkat (T cell ALL), as well as clinical lymphoma and T cell ALL samples, with IC50 values ranging from 0.078 to 10 μM. Propidium iodide staining followed by flow cytometry for subdiploid cells revealed induction of apoptosis within 48 h of treatment with OSI-027 (but not rapamycin) in SeAx, DoHH2, and Jurkat cells. Examination of Jurkat variants with alterations in key proteins involved in the death receptor versus mitochondrial pathway revealed diminished apoptotic responses to OSI-027 when Bcl-2 was overexpressed or caspase 9 was silenced, indicating involvement of the mitochondrial pathway. Immunoblotting for Bcl-2 family members revealed upregulation of Bim and Puma after a 48-hour exposure to OSI-027 but not rapamycin. This upregulation was also seen at the mRNA level, with a 12- to 20-fold increase in Puma mRNA and 4- to 12-fold induction of Bim mRNA. Small interfering RNA (siRNA)-mediated knockdown of Bim and Puma significantly diminished the apoptotic response to OSI-027. Because the Foxo3a transcription factor has been implicated in Bim and Puma expression and is known to be activated when Akt is inhibited, we next examined whether Bim and Puma induction was Foxo3a-dependent. Luciferase reporter assays showed that OSI-027 activated the full-length Puma and Bim promoters and that this activation was diminished when the Foxo3a binding sites were deleted or mutated. In addition, OSI-027 induced nuclear translocation of Foxo3a, while Foxo3a siRNA diminished OSI-027-induced apoptosis in Jurkat cells. Collectively, these results indicate that OSI-027 inhibits proliferation and induces apoptosis in a wide range of neoplastic lymphoid cells through a process that involves Foxo3a-mediated upregulation of Bim and Puma. These results also suggest that dual inhibition of TORC1 and TORC2 may be an effective treatment strategy in lymphoid malignancy. Disclosures: Barr: OSI Pharmaceuticals: Employment. Witzig:Novartis and Celgene: Patents & Royalties, Research Funding, Served on advisory boards with Novartis and Celgene – both uncompensated with compensation to Mayo Clinic.

Abstract T cell lymphoma (TCL) is a heterogeneous group of malignant lymphomas and is subdivided in three major subgroups, (i) cutaneous (mycosis fungoides (MF), sezary syndrome (SS) and primary CTCL), (ii) nodal (peripheral T-cell lymphoma, PTCL NOS, anaplastic large cell lymphoma (ALCL), angioimmunoblastic (AITL)) (iii) and extranodal. Because of this broad morphological spectrum and immunophenotypic variation the pathogenesis of most of the TCL is poorly understood. Constitutive STAT3 signaling provides growth-promoting signals in many forms of malignancy; however in-vivo activation of phosphorylated STAT3 and its clinical correlation in subtypes of TCLs has not been extensively studied. In this study we examined constitutive STAT3 activation in various subtypes of TCL tumors and performed pre-clinical testing to determine whether STAT3 inhibitors will be effective. First, we assessed the STAT3 activation (pSTAT3Tyr705) by immunohistochemistry (IHC) on a tissue microarray (TMA) from 169 untreated TCL patient samples. Using a cutoff of ≥30% pSTAT3 nuclear staining, 38% (64/169) of TCL tumors were pSTAT3+. Interestingly, pSTAT3 was differentially expressed among the various TCL subgroups. 27% (16/59) PTCL NOS, 29% (11/38) AITL, 93% (14/15) ALK+ ALCL, 57% (13/28) ALK- ALCL, 50% (6/12) extranodal NK/T cell tumors and 17% (1/6) primary cutaneous showed pSTAT3 positivity. Using either a 30% or 80% cut-off, pSTAT3 positivity was associated with inferior event free survival for AITL, PTCL NOS and ALK neg ALCLs TCLs. Due to small sample size within each group statistical significance (p=0.03) was met only for ALK neg ALCL (80% cutoff). Further analysis in the human TCL cell lines and normal control T-cells also revealed differential expression of pSTATs. ALCL cell lines, Karpas 299 and SR786 were pSTAT3 positive but pSTAT5 negative. Both the CTCL (SS) cell lines HuT78 and SeAx were pSTAT3 negative, however MyLa a cell line of MF origin was strongly pSTAT3+ and pSTAT5+. The normal control CD4 T-cells was pSTAT3- and pSTAT5+. These data clearly suggest that pSTAT3 is differentially expressed among the TCL tumors and is a potential therapeutic target. Potential mechanisms for STAT3 activation could be aberrant secretion of cytokines/chemokines produced by the tumor itself or the tumor microenvironment. We compared the cytokine profile of the culture supernatant from pSTAT3 positive SUDHL1 and pSTAT3 negative HuT78 TCL cell lines using a 30-plex ELISA. The most significantly different cytokines among these 2 cell lines were interleukin -10 (IL-10) and soluble interleukin-2 receptor alpha (sIL-2Ra). The SUDHL1 was found to secrete a very high level (1700 pg/ml) of IL-10, in contrast to only 167 pg/mL in the HuT78 supernatant. Moreover, SUDHL1 secretes 3.5 times more sIL-2Ra (6600 pg/ml) than the pSTAT3 negative cell line HuT78 (1800 pg/ml). In-vitro exposure to IL-10 but not sIL-2Ra was able to further upregulate pSTAT3 in SUDHL1 and Karpas 299. Overall, these data suggest that autocrine secretion of IL-10 but not sIL-2Ra is important for STAT3 activation in ALCL TCLs. Next we compared the cytokine profile of 2 pSTAT3 positive cells from different origin; SUDHL1 (ALCL) and MyLa (MF). In contrast to SUDHL1 (which produce high level of IL-10), MyLa was producing very little IL-10 (18pg/ml). The other most significantly different cytokines between these cells was RANTES with MyLa producing a very high level (28897 pg/ml) and SUDHL1 a very low level (8pg/ml). We also noticed differential level of IL-13 between these cells; MyLa producing 113pg/ml while SUDHL1 only 13 pg/ml. SAR302 (Sanofi, Cambridge, MA), a selective JAK2 inhibitor currently in clinical trial for myeloproliferative neoplasms was able to inhibit autocrine secretion of IL-10 but not sIL-2Ra in a dose-dependent manner followed by STAT3 dephosphorylation and decreased lymphoma cell survival. In summary, our data provide first evidence of in-vivo STAT3 activation in AITL, PTCL NOS, ALK negative ALCL TCLs using TMA from patient samples. Comprehensive cytokine analysis determined IL-10 as an autocrine factor driving STAT3 activation in ALCLTCLs, while RANTES and IL-13 might be important drivers for STAT3 activation in MF TCLs. Finally our data provide a mechanistic basis of selecting and targeting TCL tumor cells with high IL-10 levels and/or constitutive STAT3 activity with potent and novel JAK2 inhibitors such as SAR302 or other STAT3 inhibitors. Disclosures: No relevant conflicts of interest to declare.