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Abstract Activating mutations in colony stimulating factor 3 receptor gene (CSF3R) have recently been identified as specific driver mutations in chronic neutrophilic leukemia (CNL)(NEJM 2013;368:1781). We sought to outline the clinical and laboratory characteristics and natural history of this molecularly defined entity. Methods : An IRB- approved retrospective analysis of all cases of CSF3R-mutated WHO-defined CNL was undertaken. Methods of mutation analysis have been previously published. (Leukemia 2013; 27: 1870) Results : From 10/1995 to 3/2013, fourteen patients (median age 67 years; 57% male) with CSF3R-mutated CNL were evaluated at the Mayo Clinic. Most of the CSF3R mutations identified occurred in isolation: T618I (n=11), M696T (n=2) and I598I SYN (n=1), although one T618I mutant patient also carried a cytoplasmic domain mutation (2341_2342insC ). All patients were BCR/ABL negative. Five carried a SETBP1 mutation: G870D (n=2), D868N (n=2) and G872R (n=1), all of whom carried the T618I mutation. Only one of 10 tested carried a CALR mutation (E398D) and none of 13 the JAK2 V617F mutation. Apart from fatigue, most patients were asymptomatic at diagnosis and leukocytosis had been mostly an incidental laboratory finding. Ten (71%) patients had preceding chronic leukocytosis, median duration 12.5 months (range 5-84), 5 reported weight loss, which was accompanied by fevers/ sweats in 3. Five (36%) patients had prior exposures to adjuvant chest wall irradiation for breast cancer (n=2), radioiodine for thyroid disease (n=2) and methotrexate/cyclophosphamide for autoimmune disease (n=2). Five (36%) patients had palpable splenomegaly. Peripheral blood (PB) parameters, median (range) at diagnosis were: Hb 10.8 g/dl (8.5-16.0), WBC: 54 x 10(9)/L (21.7-176.2), platelets: 201 x 10(9)/L (25-476), neutrophils: 85% (78-94), immature cells (myelocytes + metamyelocytes): 6% (0-11) and monocytes: 3% (0-10). Neutrophils had toxic granulation and Dohle Bodies in 71% of cases. LDH was elevated in all patients: 354 U/L (225-496). None had a monoclonal protein. The bone marrow (BM) was hypercellular in all patients: 95% (80-100%) and granulocytic precursors were markedly increased with left-shifted (n=11) or normal maturation. BM blasts were < 5%. Reticulin fibrosis was absent (n=5), 1+ (n=5) or 1-2+ (n=1) in those with staining. Cytogenetics were normal in all but one at diagnosis. One patient was lost to follow up after diagnosis. Hydroxyurea (HU) was the most frequently used therapy (initial therapy in 10 patients) and was ultimately received by all. Although initially effective at controlling leukocytosis, clinical course of most was defined by progressive refractory mature neutrophilia with the development of red cell (n=6) and platelet transfusion (n=3) dependancy. Other therapies included IFN or PEG/IFN (n=4), hypomethylating agents (n=4), ruxolitinib (n=2), thalidomide (n=2), cladribine (n=2) and imatinib (n=1). None of these additional drugs, induced remission and they provided primarily palliative and transient benefit. One patient transformed into AML at 17 months, one received induction chemotherapy for suspected AML (PB and BM blasts at 11-13%) at 19 months and two evolved into WHO-defined CMML, at 20 and 27 months, respectively. Both patients with documented/suspected AML were both T618I and SETBP1 positive. Of the cases progressing to CMML (one with T618I, one with M696T) neither was SETBP1 positive. At last follow up, eight patients had died and median survival was 22.5 months. Progressive refractory neutrophilic leukocytosis often preceded and contributed to death. Four (29%) patients are currently alive after a median follow-up of 61 months (14.3- 69.4). Conclusion : CSF3R-mutated CNL is an aggressive disease (median survival <2 years) characterized by progressive neutrophilic leukocytosis which is only partially controlled with current drugs, including the putative targeted therapy ruxolitinib (both ruxolitinib-treated patients progressed on treatment). Patients with CNL could progress into AML or CMML; however, most succumb from complications associated with progressive treatment-refractory leukocytosis. The observation that both patients with documented/suspected AML were SETBP1-mutation positive suggests potential pathogenetic link. Disclosures Off Label Use: Ruxolitinib, cladribine, thalidomideand inteferon. These drugs were used in a historical account of CNL and I report on these in a retrospective chart review only..

Abstract Primary myelofibrosis (PMF) is a clonal hematologic malignancy resulting from the transformation of a pluripotent hematopoietic progenitor cell leading to increased hematopoiesis and overproduction of abnormal blood cells. PMF is characterized by bone marrow (BM) fibrosis, extramedullary hematopoiesis, increased numbers of circulating CD34+ cells, splenomegaly, and a propensity to evolve to AML. Patients also display anemia and thrombocytopenia and harbor abnormal, immature megakaryocytes (Mks) in their BM and spleen. Numerous mutations are associated with PMF including JAK2, CALR, MPL, TET2, CBL, ASXL1, and IDH. The presence of abnormal Mks in the BM of PMF patients is an important characteristic of the disease, as these cells are believed to contribute to the fibrosis.Here, we performed an analysis of Mk differentiation from individuals with PMF compared to healthy individuals as a way to better understand the mechanism leading to their defects. CD34+ cells obtained from PMF and healthy donors were cultivated in presence of thrombopoietin to induce Mks differentiation. Under these conditions, we observed that the proliferative capacity of CD34+ cells from PMF patients was increased as compared to normal CD34+ cells. At the same time, the percentage of mature Mks obtained was reduced. Semi-solid culture conditions confirmed the proliferative advantage of the PMF CD34+ cells. To investigate the mechanism responsible for this phenotype, we performed genome wide expression analysis of sorted Mks from patients versus controls. Nine PMF patients with different mutations (5 JAK2V617F, 1 MPLW515L, 2 CALR and 1 triple negative) and 4 healthy donors were included in the study. Gene Set Enrichment Analysis (GSEA) analysis revealed that the top scoring pathways included the RPS14 signature, ribosome biogenesis, rRNA metabolic process, and rRNA processing. We first studied the RPS14 geneset, which consists of a group of genes that were up-regulated in CD34+ cells after knock-down of RPS14, a component of the small ribosome subunit. Using shRNA against RPS14, we discovered that its knock down leads to a significant reduction in the development of mature Mks from normal CD34+ cells. The microarray data also revealed changes in the expression of several myeloid genes. CEBPa and GFI-1 were over-expressed in PMF Mks, whereas GFI-1b and PF4, which are associated with Mk differentiation, were down-regulated. Surprisingly the expression of GATA1, a master regulator of megakaryopoiesis, was not changed. However, consistent with previous report, we discovered that GATA1 protein level was reduced in PMF Mks. GATA1 deficient Mks are impaired in their maturation, so we reasoned that the reduction in GATA1 contributes to the defects in PMF. Indeed, we found that overexpression of GATA1 in PMF CD34+ cells rescued Mk differentiation. To understand how GATA1 protein but not mRNA, is reduced, we knocked down RPS14 in the JAK2 mutant SET2 megakaryoblastic cell line. As predicted, we observed a reduction in GATA1 protein, but not mRNA. By ribosomal profiling, we saw that the shRPS14 led to an abnormal ribosomal profile with a reduction of the 40s peak. Finally, by RT-PCR analysis of the ribosomal and polysomal fractions, we found that GATA1 mRNA was less abundant in the polysomal fraction in cells expressing the shRPS14. This finding is consistent with recent data showing that alterations in ribosomal genes cause a decrease in GATA1 protein in Diamond-Blackfan Anemia. Although we identified the RPS14 gene signature, we did not observe changes in RPS14 expression or in any of the ribosomal subunits. Since our GSEA analysis also identified deficiencies in three ribosomal biogenesis pathways, we looked for genes present in all three signatures. NOP58, a ribonucleoprotein required for ribosome biogenesis, was significantly reduced in all samples of PMF Mks. To link the reduction in NOP58 expression with PMF associated mutations, we expressed MPLW515L or the CALR type II mutant in hematopoietic progenitor cells and detected a reduction in NOP58 expression. Our findings suggest that the activation of JAK/STAT signaling leads to a reduction in NOP58, which contributes to defects in ribosome assembly, decreased GATA1 expression and subsequent impairment in Mk differentiation. This work reveals, for the first time, that defective ribosomes contribute to the pathogenesis of PMF and suggests new avenues for therapeutic intervention. Disclosures Stein: Incyte Corporation: Honoraria, Speakers Bureau; Sanofi Oncology: Honoraria.

Abstract Background : Controversy persists regarding diagnostic accuracy as well as added value for quantitative assessment of neutrophil PRV-1 expression in polycythemia vera (Klippel et al. Blood2003;102:3569; Tefferi et al. Blood2004;103:3547). This is partly because of limited data regarding the relationship between neutrophil PRV-1 transcript level and other laboratory parameters in polycythemia vera (PV). More information is also needed on the PRV-1 expression profile in other myeloproliferative disorders (MPD), including essential thrombocythemia (ET) and agnogenic (AMM), post-polycythemic (PPMM), and post-thrombocythemic (PTMM) myeloid metaplasia. Methods : The current prospective study involves 141 subjects, including 49 with PV, 40 with secondary or spurious polycythemia (SP), 23 with ET, 11 with AMM, 4 with PPMM, 3 with PTMM, and 11 normal controls. Peripheral blood neutrophil PRV-1 expression was quantified by real-time PCR according to published methods (Klippel et al. Blood 2003). The results were first compared among the different disease categories and controls. Subsequently, within the specific disease categories of both PV and ET, PRV-1 expression was correlated with several laboratory [leukocyte count, absolute neutrophil count (ANC), leukocyte alkaline phosphatase score (LAP) score, CD34 count, platelet count, hematocrit, serum EPO level, MCV, serum ferritin, reticulin fibrosis] and clinical (age, sex, disease duration, spleen size, thrombosis history, and presence of treatment with cytoreductive agent, aspirin, or phlebotomy) parameters. Results : The incidence of increased neutrophil PRV-1 expression was the highest in PV and PPMM (p<0.0001) while the results in the other disease categories (ET, SP, AMM, PTMM) were similar among each other and controls ( p=0.89). Table 1 Parameters Cont. (n=11) SP (n=40) PV ( n=49) ET (n=23) AMM (n=11) PPMM (n=4) PTMM (n=3) Age in years median NA 51 58 46 60 63 47 range NA 19–78 18–83 18–81 41–80 56–71 47–72 Females NA 20% 55% 65% 18% 25% 33% PRV-1/GAPDH median 1.25 1.25 1.01 1.24 1.26 1.04 1.25 range 1.14–1.43 0.99–1.41 0.83–1.28 0.9–1.44 1.08–1.43 0.93–1.11 1.23–1.27 PRV-1 ↑ 9% 15% 76% 17% 18% 100% 0% In both PV and ET, neutrophil PRV-1 expression strongly correlated with LAP score (p=0.003 and 0.04, respectively). In addition, in PV, univariate analysis revealed significant correlations between PRV-1 expression and leukocyte count, ANC, and reticulin fibrosis. On multivariate analysis, only LAP score retained its significance. Figure Figure Conclusion :The current study confirms the previously recognized close association between increased neutrophil PRV-1 expression and PV as well as suggests a similarly strong association with PPMM but not with ET, MMM, or PTMM. The study also underscores the suboptimal diagnostic accuracy of the neutophil PRV-1 assay in distinguishing PV from SP. Most importantly, the demonstrated tight correlation between PRV-1 transcript level and LAP score raises the issue of added value to currently available diagnostic tests.

Abstract Background : Neutrophil PRV-1 over-expression has been strongly associated with polycythemia vera (PV) and its quantitative measurement might complement the diagnostic distinction between PV and secondary polycythemia (Klippel et al. Blood2003;102:3569). Furthermore, the PV-specificity of the particular abnormality had been suggested by studies that demonstrated increased PRV-1 expression in post-polycythemic but not agnogenic myeloid metaplasia (Tefferi et al. Blood2003;103:3547) as well as by other studies that suggested the inevitable progression into PV of essential thrombocythemia (ET) associated with PRV-1 over-expression (Griesshammer et al. Ann Hematol2004;83:364). Still others have suggested the possibile utility of the particular assay in differentiating clonal from reactive myeloproliferation (Cilloni et al. Blood2004;103:2428). Methods : The purpose of the current study was two-fold; i) to further evaluate the specificity of neutrophil PRV-1 over expression to either PV or clonal myeloproliferation by testing the assay in atypical myeloproliferative disorders (AMPD) and ii) to evaluate eosinophil PRV-1 expression in AMPD associated with eosinophilia. In a prospective study, 13 patients with AMPD and 2 with reactive eosinophilia were evaluated for neutrophil PRV-1 expression (table 1). PRV-1 transcript quantitation was performed according to published methods (Klippel et al. Blood2003;102:3569). PRV-1 gene expression was considered elevated in the presence of a PRV-1/GAPDH ratio of 1.17 or lower. Table 1 Patient Diagnosis Neutrophil PRV-1/GAPDH ratio Neutrophil PRV-1 expression 1 Chronic myelomonocytic leukemia associated with myelofibrosis 1.05 Increased 2 FIP1L1/PDGFRA-positive eosinophilic disorder 1.39 Normal 3 FIP1L1/PDGFRA-positive eosinophilic disorder 1.19 Normal 4 FIP1L1/PDGFRA-positive eosinophilic disorder 1.10 Increased 5 Biphenotypic acute leukemia with prominent blood eosinophilia 0.99 Increased 6 Hypereosinophilic syndrome with cardiac involvement 1.15 Increased 7 Hypereosinophilic syndrome with cardiac involvement 1.13 Increased 8 Hypereosinophilic syndrome with sinus involvement 1.29 Normal 9 Reactive eosinophilia associated with atopic dermatitis 1.09 Increased 10 Reactive eosinophilia associated with T cell skin lymphoma 1.22 Normal 11 Aggressive systemic mastocytosis associated with chronic myelomonocytic leukemia 1.08 Increased 12 Aggressive systemic mastocytosis associated with myelofibrosis 1.09 Increased 13 Aggressive systemic mastocytosis with circulating mast cells 1.29 Normal 14 Indolent systemic mastocytosis 1.20 Normal 15 Indolent systemic mastocytosis 1.18 Normal In addition, eosinophil PRV-1 expression was measured in 2 patients from the above cohort (patients 3 and 8) and 3 additional patients with hypereosinophilic syndrome (HES). Results : Table 1 outlines specific diagnoses as well as the corresponding neutrophil PRV-1 expression levels in all 15 patients tested (median age 54 years, range 20–74; 11 males). Eosinophil PRV-1 expression was normal in all 5 patients tested (range of PRV-1/GAPDH ratio between 1.20–1.39). Conclusion : The current study suggests that neutrophil PRV-1 over-expression is a non-specific marker of clonal myeloproliferation that is seen in a broad spectrum of both typical and atypical myeloid disorders. As has been the case in ET, only a subset of AMPD patients display the specific abnormality, thus undermining its diagnostic utility. The preliminary information from the current study does not suggest increased eosinophil PRV-1 expression in either HES or clonal eosinophilia.

Abstract Background : Polycythemia Vera (PV) is associated with JAK2 mutations. In essential thrombocythemia (ET), ̴ 85% of patients harbor one of 3 "driver" mutations, with frequencies of ̴ 58%, 23% and 4%, for JAK2, CALR and MPL, respectively; ̴ 15% are wild type for all three mutations and are referred to as "triple negative". We applied next-generation sequencing (NGS) with a 27-gene panel of myeloid malignancy-relevant genes, in order to describe the prevalence of "non-driver" mutations and their prognostic relevance in PV and ET. Methods: Targeted capture assays were carried out on bone marrow or whole blood DNA for the following genes: TET2, DNMT3A, IDH1, IDH2, ASXL1, EZH2, SUZ12, SRSF2, SF3B1, ZRSR2, U2AF1, PTPN11, Tp53, SH2B3, RUNX1, CBL, NRAS, JAK2, CSF3R, FLT3, KIT, CALR, MPL, NPM1, CEBPA, IKZF, and SETBP1.Paired-end indexed libraries were prepared using the NEBNext Ultra Library prep protocol (NEB, Ipswich, MA /Agilent Technologies Inc, Santa Clara, CA). Capture libraries were assembled according to Nimblegen standard library protocol (Roche Nimblegen, Inc, Basel, Switzerland). Base-calling was performed using Illumina's RTA version 1.17.21.3. Genesifter® software (PerkinElmer, Danvers, Massachusetts) was utilized to analyze targeted sequence data. Nucleotide variants were called using the Genome Analysis Toolkit (GATK -Broad Institute, Cambridge, MA). Specific variants were deemed as mutations if they are associated with a hematologic malignancy (COSMIC database), or if they have not been associated with a dbSNP. Results: 314 patients with PV (n =133; median age 64 years, 53% females) or ET (n =181; median age 58 years, 59% females) were evaluated. Median follow-up was 9.8 years for PV and 9.2 years for ET. During this time 59 (44%) deaths, 15 (11%) fibrotic and 5 (4%) leukemic transformations were documented for PV and the corresponding percentages for ET were approximately 33%, 8% and 2%. Driver mutation distribution was 98% JAK2 for PV and 52% JAK2, 24% CALR, 20% triple-negative and 4% MPL for ET. Polycythemia Vera Mutations other than JAK2, CALR or MPL were seen in 58 (44%) patients; 29% harbored one, 14% two and one 3 mutations. None of 3 JAK2 -unmutated cases expressed non-driver mutations. Mutational frequencies were 18% TET2, 11% ASXL1, 5% SH2B3, 3% SF3B1 and ≤2% SETBP1, IDH2, DNMT3A, CEBPA, CSF3R and SUZ12, SRSF2, ZRSR2, TP53, CBL, NRAS, RUNX1, KIT, PTPN11 and FLT3. "Number of mutations" significantly affected overall (OS; Figure 1) and myelofibrosis-free (MFS) survival; respective HR (95% CI) were 2.6 (1.3-5.2) and 1.7 (0.97-3.1) and 13.7 (2.9-63.4) and 5.1 (1.5-17.6) for ≥2 mutations and one mutation, respectively. OS was also adversely affected by SRSF2 (p=0.006) and RUNX1 (p=0.04) and borderline affected by TET2 (p=0.06), IDH2 (p=0.08), ASXL1 (p=0.19) and SF3B1 (p=0.19) mutations. In multivariable analysis, SRSF2 and RUNX1 retained significance whereas the others remained borderline significant. In both univariate and multivariable analyses, leukemia-free survival (LFS) was adversely affected by IDH2 and RUNX1 mutations. In univariate analysis, ASXL1, IDH2, RUNX1 and KIT mutations predicted fibrotic progression, whereas SETBP1 was of borderline significance (p=0.07); all, including SETBP1, were significant during multivariable analysis. Essential thrombocythemia Mutations other than JAK2, CALR or MPL were seen in 83 (46%) patients; 35% harbored one, 7% two and 4% three mutations; prevalence in JAK2, CALR, MPL mutated and triple-negative cases was 52%, 43%, 43% and 35%, respectively (p=0.52). Mutational frequencies were: 13% TET2, 11% ASXL1, 6% DNMT3A, 5% SF3B1, 4% CEBPA, 2% TP53, SH2B3, EZH2 and CSF3R and <2% for SETBP1, IDH2, SRSF2, ZRSR2, CBL, NRAS, RUNX1, U2AF1, KIT, PTPN11 and FLT3. "Number of mutations" significantly affected OS (Figure 2) but not MFS or LFS; HR (95% CI) for OS were 6.6 (2.5-17.8) for 3 mutations and 2.2 (1.3-3.9) for one or two mutations. In univariate analysis, survival was adversely affected by CBL, EZH2, SF3B1, SRSF2 and IDH2 mutations. In multivariable analysis, EZH2 and SF3B1 remained significant. Univariate analysis identified SETBP1 and SF3B1 mutations as risk factors for fibrotic progression and EZH2, TP53 and CSF3R mutations for leukemic transformation. Conclusions: "Non-driver" mutations occur in more than 40% of patients with PV or ET; the number of such mutations and presence of certain specific ones likely predict OS, MFS or LFS. Figure 1. Figure 1. Figure 2. Figure 2. Disclosures Pardanani: Stemline: Research Funding.

Abstract Background : In primary myelofibrosis (PMF), ̴ 88% of patients harbor one of three "driver" mutations, with mutational frequencies of approximately 60%, 22% and 6% for JAK2, CALR and MPL, respectively. Other "non-driver" mutations have also been described in PMF and some of them and their number have been associated with inferior survival (Leukemia. 2014;28:1804). We applied next generation sequencing (NGS) with a broader panel of MPN-relevant genes, in order to identify additional mutations of prognostic relevance as well as obtain additional information regarding the prognostic value of 'number of mutations'. Methods: Targeted capture assays were carried out on bone marrow or whole blood DNA specimens obtained at time of referral for the following genes: TET2, DNMT3A, IDH1, IDH2, ASXL1, EZH2, SUZ12, SRSF2, SF3B1, ZRSR2, U2AF1, PTPN11, Tp53, SH2B3, RUNX1, CBL, NRAS, JAK2, CSF3R, FLT3, KIT, CALR, MPL, NPM1, CEBPA, IKZF, and SETBP1. Paired-end indexed libraries were prepared from individual patient DNA using the NEB Next Ultra Library prep protocol on the Agilent Bravo liquid handler (NEB, Ipswich, MA/Agilent Technologies Inc, Santa Clara, CA). Capture libraries were assembled according to Nimblegen standard library protocol (Roche Nimblegen, Inc, Basel, Switzerland). Base-calling was performed using Illumina's RTA version 1.17.21.3. Genesifter® software was utilized (PerkinElmer, Danvers, Massachusetts) to analyze targeted sequence data. Nucleotide variants were called using the Genome Analysis Toolkit (GATK-Broad Institute, Cambridge, MA). Specific variants were deemed as mutations if they are associated with a hematologic malignancy (as identified by COSMIC database), or if they have not been associated with a dbSNP. Results: 180 PMF patients were evaluated (median age 63 years; 65% males). DIPSS-plus risk distribution was 32% high, 38% intermediate-2, 17% intermediate-1 and 13% low. Driver mutation distribution was 62% JAK2, 22% CALR, 9% triple-negative and 7% MPL. Karyotype was abnormal in 41% of patients and unfavorable in 12%. Mutations other than JAK2, CALR or MPL (i.e. "non-driver" mutations) were seen in 150 (83%) patients including 88% of "triple-negative" cases. 62 (34%) patients harbored one, 55 (31%) two, 16 (9%) three and 17 (10%) four or more. Mutational frequencies were: ASXL1 36%, TET2 18%, SRSF2 17%, U2AF1 17%, ZRSR2 11%, SF3B1 10%, DNMT3A 9%, CEBPA (9%), Tp53 7%, SETBP1 6%, CBL 5%, IDH1/2 5%, SH2B3 4%, CSF3R 4%, NRAS 4%, RUNX1 3% and ≤2% for SUZ12, KIT, PTPN11, NPM1 and EZH2. DIPSS-plus high/intermediate-2 risk patients displayed higher number of mutations (p=0.0004) and higher mutational frequencies for ASXL1 (p=0.02), SRSF2 (p=0.004) and CBL (p=0.02). Associations noted included JAK2 with U2AF1 (p=0.03), unfavorable karyotype with CBL (p=0.01) and normal karyotype with ZRSR2 mutations (p=0.04). At a median follow-up of 4 years, 111 (62%) deaths were documented. For examination of impact on survival, we considered 'number of mutations' and specific mutations with >2% frequency. Accordingly, in univariate analysis, survival was adversely affected by 'number of mutations' (Figure 1) and presence of ASXL1, SRSF2, IDH1/2, U2AF1, RUNX1 and CBL mutations. For multivariable analysis, we considered three categories (zero, 1-3 and ≥4) for number of mutations based on the results from univariate analysis (Figure 1); the results showed ≥4 mutations, 1-3 mutations, RUNX1, CBL, ASXL1 and SRSF2 mutations were independently associated with shortened survival; the respective HR (95% CI) were 4 (1.4-11.1), 3 (1.3-6.8), 2.9 (1.1-8.1), 2.8 (1.3-6.3), 1.8 (1.2-2.7) AND 1.7 (1.03-2.7). When the multivariable analysis was repeated including only the 150 patients with at least one non-driver mutation, the 'number of mutations' was no longer significant (p=0.35) but ASXL1, CBL, RUNX1 and SRSF2 mutations retained their significance. The prognostic relevance of ASXL1 and CBL continued to be apparent even after the addition of DIPSS-plus and driver mutation profile to the multivariable model. Conclusions: Mutations other than JAK2, CALR or MPL occur in more than 80% of patients with PMF, including those with "triple-negative" driver mutational status. The absence of such mutations is independently favorable for survival while the prognostic effect of their presence is influenced by ASXL1, CBL, RUNX1 and SRSF2 mutations. Figure 1. Figure 1. Disclosures Pardanani: Stemline: Research Funding.

Abstract Background : Prognosis in chronic myelomonocytic leukemia (CMML) is dire and blast transformation (BT) is a main cause of death. Current risk factors and prognostic models are mostly designed to predict overall (OS) and not leukemia-free (LFS) survival. Established risk factors for OS in CMML include anemia, thrombocytopenia, leukocytosis, monocytosis, presence of circulating immature myeloid cells (IMC), peripheral blood (PB) and bone marrow (BM) blasts, lymphocytosis, ASXL1 mutations, high risk abnormal karyotype and advanced age. In the current study, we examined risk factors for BT in CMML and survival outcome after BT. Methods : All CMML patients seen at our institution and with complete presentation data were considered. Clinical and laboratory variables, including cytogenetic information, at time of CMML diagnosis and also at time of BT were collected. DNA analysis for SRSF2, SF3B1, U2AF1, ASXL1 and SETBP1 mutations was carried out on specimens obtained at time of CMML diagnosis. We used both conventional and revised (see accompanying ASH 2014 abstract) cytogenetic risk models to query their influence in the current study population. Results: Clinical and laboratory features at time of CMML diagnosis: 277 consecutive patients (median age 71 years, range 18-91; 67% males) with WHO-defined CMML were considered. 236 (85%) patients had CMML-1 and the remainder CMML-2. According to the molecular Mayo risk model, 86 (33%) were high, 77 (29%) were intermediate-2, 77 (29%) were intermediate-1 and 24 (9%) were low risk. Mutational frequencies were 40% for ASXL1 (n evaluable =264), 44% for SRSF2 (n evaluable =263), 5% for SETBP1 (n evaluable =263). According to the revised Mayo-French consortium cytogenetic risk model, karyotype was high risk in 5%, intermediate in 21% and low risk in 74%. Risk factors for blast transformation (BT) : At a median follow-up of 16.2 months for all 277 patients from time of CMML diagnosis, 204 (74%) deaths and 38 (14%) BTs were documented. Median time from CMML diagnosis to BT was 13.3 months. In univariate analysis, female sex, younger age, lower hemoglobin, higher leukocyte count, higher absolute monocyte count, higher lymphocyte count, presence of circulating immature myeloid cells (IMC), increased peripheral blood (PB) blast %, increased bone marrow (BM) blast %, BM blasts ≥10%, CMML-2, abnormal karyotype, high risk karyotype per the Spanish or Mayo-French consortium, and higher risk disease per Mayo, MDACC or Dusseldorf models were all associated with higher risk of BT. In contrast, ASXL1 (p=0.84), SRSF2 (p=0.28) or SETBP1 (p=0.97) mutations were not found to be significant. In multivariable analysis, only PB blast % (p<0.0001), presence of PB IMC (p=0.004) and younger age (p=0.03) remained significant. Outcome of blast transformation : At time of BT, karyotype was abnormal in 58% and clonal evolution from time of CMML diagnosis was documented in 13 (36%) of 36 evaluable patients. Among the 38 patients with BT, induction chemotherapy was documented in 12 patients and allogeneic stem cell transplant (ASCT) in 6. At a median follow-up of 4.2 months from time of BT, 34 (89%) of the 38 patients with BT had died. Among the four patients who were alive at the time of this writing, 3 had received induction chemotherapy and two ASCT. Median survival of patients with BT, from time of disease transformation, was 4.5 months with 1, 2 and 3 year survival rates of approximately 30%, 16% and 3%, respectively. In univariate analysis, higher leukocyte count (p=0.01) and not receiving induction chemotherapy (p=0.03) were associated with shortened survival. Neither ASXL1 nor SRSF2 mutations affected survival after BT. Conclusions : Blast transformation in CMML occurs in approximately 14% of patients followed for a median of less than 1.5 years. Presence of circulating immature cells and percentage of peripheral blood blasts are the major determinants of BT in CMML. Genetic risk factors for overall survival did not appear to influence leukemia-free survival. Prognosis of post-CMML BT is dismal with median survival of less than 6 months and a 3-year survival of less than 5%. Outcome was better in patients receiving induction chemotherapy followed by ASCT. Disclosures No relevant conflicts of interest to declare.

Abstract Abstract 430 Background: The Dynamic International Prognostic Scoring System (DIPSS-plus) uses eight risk factors to predict overall survival (OS) in primary myelofibrosis (PMF): unfavorable karyotype, peripheral blood (PB) blast count ≥1%, platelet count <100 × 109/L, white blood cell count (WBC) >25 × 109/L, hemoglobin level <10 g/dL, red blood cell transfusion need, constitutional symptoms, and age >65 years (JCO 2011;29:392). Among these risk factors, karyotype holds a dominant role in predicting both overall (OS) and leukemia-free (LFS) survival (Blood 2011;118:4595). More recently, certain PMF-associated somatic mutations (IDH, EZH2, ASXL1, SRSF2) have been reported (in print or at recent meetings) to carry prognostic relevance for OS or LFS in PMF while other mutations (JAK2, MPL, TET2, SF3B1) did not. The purpose of the current study was to examine the individual and combined prognostic relevance of the former in the context of cytogenetic risk stratification and DIPSS-plus. Methods: An updated Mayo Clinic database of 1008 karyotypically- and DIPSS-plus-annotated patients with PMF was used to identify study patients in whom DNA at time of referral was available for mutation analysis. OS and LFS were calculated from the time of referral, which was also the time of study sample collection. Results: In an ongoing project, a total of 397 PMF patients have so far been studied for IDH1/2 (n=367), SRSF2 (n=355), ASXL1 (n=260) and EZH2 (n=43) mutations. The corresponding mutational frequencies were 5.4% (20/367), 14.4% (51/355), 31.2% (81/260) and 7% (3/43). These mutations were not exclusive of either each other or JAK2 or MPL mutations and a significant clustering was noted between SRSF2 and IDH mutations; IDH mutational frequency was 21% (10/48) in SRSF2-mutated versus 3% (9/279) in unmutated cases (P<0.0001). Mutational hotspots were P95 in exon 1 for SRSF2 and exons 1, 2 and 5 for ASXL1. OS and LFS effect have so far been examined for ASXL1, SRSF2 and IDH 1/2 mutations; in univariate analysis, all three mutations significantly affected OS (ASXL1 RR 1.9, 95% CI 1.4–2.7; SRSF2 RR 1.7, 95% CI 1.2–2.5; IDH 1/2 RR 1.8, 95% CI 1.1–3.1) whereas only IDH 1/2 (RR 5.5, 95% CI 2.5–11.8) and SRSF2 (RR 3.5, 95% CI 1.7–7.0) but not ASXL1 (p=0.29) mutations affected LFS. The observed prognostic relevance for OS was sustained during multivariable analysis that included ASXL1 with either SRSF2 or IDH mutations, as co-variates, whereas both IDH and SRSF2 mutations remained significant for LFS. Based on the above observations, study patients were classified into two groups: i) unmutated for ASXL1, SRSF2 and IDH1/2 (all unmutated; n=146) and ii) mutated for at least one of the three mutations (one or more mutated; n=130); the latter group constituted 62%, 52%, 18% and 27% of DIPSS-plus high, intermediate-2, intermediate-1and low risk patients, respectively (p<0.0001). The corresponding rates for patients with favorable and unfavorable karyotype were 47% and 43% (p=0.7) and for normal vs. abnormal karyotype were 53% and 36% (p=0.008). The “all unmutated group”, compared to the “one or more mutated group” enjoyed a significantly superior OS (RR 0.5, 95% CI 0.4–0.7) and LFS (RR 0.3, 95% CI 0.2–0.7) that was DIPSS-plus-independent for OS (p=0.03) and karyotype-independent for LFS (p=0.004). The prognostic value of distinguishing “all unmutated” from “one or more mutated” patient groups was most evident for DIPSS-plus intermediate-2 or lower risk groups (p=0.002) and its added value for high-risk group was limited (p=0.23) (Figure). Conclusions: A concomitant analysis strategy reveals that SRSF2, ASXL1 and IDH mutations carry inter-independent prognostic relevance for overall or leukemia-free survival in PMF. Any one of these three mutations is more likely to occur in patients with normal karyotype and such an event predicts shortened survival that is not accounted for by DIPSS-plus and a higher risk of leukemic transformation that is independent of karyotype. The current study suggests that such information might be useful in treatment decisions involving intermediate-2 or lower risk patients. Disclosures: No relevant conflicts of interest to declare.

Abstract Abstract 925 Diffuse large B-cell lymphomas (DLBCL) consists of biologically distinct subtypes: Germinal Center B-cell (GCB)–like and Activated B-cell (ABC)-like. Studies to date suggest that patients with tumors that have ABC features have an inferior survival; therefore, it is important to develop new therapies specifically for ABC-type DLBCL based on mechanistic differences. It has been shown that the ABC-DLBCL has high levels of total and phosphorylated STAT3 (pSTAT3) protein and this STAT3 activity may play a role in the survival of ABC-DLBCL cells. Indeed, when ABC and GCB cell were incubated with the novel JAK2 inhibitor TG101348 (TargeGen, San Diego, CA) we found potent cytotoxicity (LD50 2μM) in ABC DLBCL but not in GCB DLBCL. This provides further rationale to study the regulation of STAT3 in the survival of ABC type DLBCL cells. In studies of HDAC expression in ABC DLBCL cells, we found over-expression of the class 1 histone deacetylases, specifically HDAC1 and HDAC3. We then performed co-immunoprecipitation experiments to learn the functional interaction between STAT3 and HDACs. We found that STAT3 formed complexes with HDAC1 to a greater extent than HDAC3. We also showed that STAT3 did co-precipitate with HDAC1 suggesting a reciprocal relationship between these two proteins. These results suggested that HDAC1 (but not HDAC3) might be involved in the regulation of STAT3. The HDAC inhibitor LBH589 (LBH, Novartis Pharm) was more cytotoxic to ABC (LD50, 10-20nM) than GCB (LD50, 50-100nM) and was shown to dephosphorylate STAT3. These results led to experiments designed to determine the effect of LBH on STAT3 acetylation. When ABC cells were incubated with LBH, co-immunoprecipitation data showed a dose-dependent increased in acetylation of STAT3 without significant change on the levels of STAT3 immunoprecipitated. Next, we asked that how LBH is dephosphorylating STAT3. One potential mechanism is activation of a protein phosphatase. Immunoprecipitation of protein phosphatase 2A (PP2A) in the lysates of LBH-treated cells followed by western blotting of STAT3 demonstrated a positive correlation between LBH dose and amount of STAT3 co-immunoprecipitated with PP2A. Our data show that when LBH is incubated with ABC cells, the LBH increases binding of PP2A to STAT3 and the increased phosphatase activity turns off STAT3 signaling. Since both HDAC inhibitor (LBH) and the JAK2 inhibitor (TG) had selective cytotoxic effects on ABC cells, and since both agents dephosphorylate STAT3, we combined the two drugs. We found that the combination exhibited enhanced inhibitory effects on the growth of ABC cells and was able to alter the association of STAT3 with HDAC1 and subsequently dephosphorylate STAT3 to greater extent than either agent alone. Furthermore, we knocked down HDAC1 expression (through siRNA) in OCILy10 (ABC) cells and showed that inhibition of HDAC1 inhibits constitutively activated STAT3. This data suggests that inhibiting HDAC1 expression results in STAT3 dephosphorylation. In summary, we have demonstrated that a key consequence of HDAC expression in ABC cells is continuous activation of STAT3. These data indicate that HDACs activate STAT3 and that PP2A may be important in maintaining STAT3 in the activated state in the ABC cells. This study describes a new mechanism by which STAT3 mediates ABC cell survival and provides the rationale for targeting ABC type DLBCL by simultaneously inhibiting HDAC activity and STAT3 activation by pharmacologic grade inhibitors such as LBH589 and TG101348, which are currently in clinical trial. A phase 1 and 2 trial of JAK2 inhibitor, TG101348 for ABC/GCB type DLBCL is planned. Disclosures: No relevant conflicts of interest to declare.