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Abstract Background : Chronic myelomonocytic leukemia (CMML), a myeloid neoplasm with overlapping features of myelodysplastic syndromes and myeloproliferative neoplasms (MPN), is characterized by peripheral blood (PB) monocytosis and a risk for leukemic transformation (LT). Gene mutations commonly seen in CMML include, TET2 (~60%), SRSF2 (~50%) and ASXL1 (~40%). MPN associated-driver mutations such as JAK2V617F (~10%), MPL (<1%) and CALR (<1%) are uncommon, and in fact, the 2016 World Health Organization (WHO) guidelines state that the presence of these mutations tends to support a diagnosis of MPN with monocytosis. We carried out this study to assess the i) clinical correlates and ii) survival outcomes of MPN associated-driver mutations in CMML. Methods : 323 molecularly annotated patients with WHO-defined CMML were included in the study. All patients had bone marrow (BM) biopsies and cytogenetics performed at diagnosis. Targeted capture assays were carried out on BM DNA specimens obtained at diagnosis for 30 myeloid relevant genes, by previously described methods. Results: Among the 323 study patients, 67% were males and median age was 71 years (range, 18-95). Twenty five (8%) patients had CMML with MPN associated-driver mutations; 24 (96%) with JAK2V617F and 1(4%) with a MPLW515L mutation. There were no patients with CALR or JAK2 exon 12 mutations. Additional signal-pathway mutations included NRAS (15%), KRAS (4%), CBL (14%), PTPN11 (3%), CSF3R (1%), and SH2B3 (<1%). i) Phenotypic correlates: The median age of CMML patients with MPN-associated driver mutations was 71 years and 66% were male. The WHO morphological subtypes included CMML-0 60%, CMML-1 24% and CMML-2 16%; while 91% of patients had a normal karyotype. The distribution of mutations included TET2 75%, SRSF2 54%, ASXL1 48%, RUNX1 20%, NRAS and EZH2 12% each, SETBP1 8%, SF3B1, U2AF1, CBL, PTPN11, FLT3-TKD, & Tp53 4% each, respectively. Risk stratification by the Mayo Molecular Model included high 16%, intermediate-2 32%, intermediate-1 36% and low risk 16%, respectively. In comparison to CMML patients without MPN associated-driver mutations, those with, had a higher hemoglobin (HB, p=0.001) and hematocrit (p=0.001), were more likely to have leukocytosis (p=0.02) and elevated LDH levels (p=0.0002), less likely to have thrombocytopenia (p=0.003), more likely to have a "proliferative" CMML phenotype (p=0.01) with palpable splenomegaly (p=0.0007), and more likely to have mutations involving TET2 (p=0.02). Six (2%) thrombotic events were documented in the cohort; 2 (8%) in patients with MPN-driver mutations and 4 (1%) in those without (p=0.07). There were no differences between the two groups with regards to the degree of monocytosis, PB and BM blasts, BM cellularity, BM megakaryocytic atypia, and BM fibrosis. ii) Survival outcomes: At last follow up 219 (68%) deaths and 55 (17%) LT were documented, of which 14 (56%) deaths and 2 (8%) LT occurred in the MPN-driver mutation group. The median OS for the entire cohort was 28 months (22-32); 31 months for CMML patients with MPN associated-driver mutations and 24 months for those without (p=0.4). On a univariate analysis, survival was adversely impacted by low HB (p<0.0001), high white blood count (p=0.0009) and absolute monocyte count (p=0.0004), circulating immature myeloid cells (p=0.02) and blasts (p=0.005), BM blasts (p=0.02), palpable splenomegaly (p=0.03), abnormal karyotype (p=0.001), presence of DNMT3A (p=0.006), ASXL1 (p=0.009), EZH2 (p=0.03) and Tp53 (p=0.02) mutations and the absence of TET2 (p=0.0009) mutations. Survival was not affected by the presence of JAK2V617F (p=0.4) or MPL (p=0.46) mutations. On a multivariable analysis that included the aforementioned significant variables, only HB <10 gm/dl (p=0.0016), presence of PB blasts (p=0.01), presence of DNMT3A (p=0.003) and the absence of TET2 mutations (p=0.02) retained significance. The presence of MPN associated-driver mutations did not impact LFS (p=0.36). Conclusions: The occurrence of MPN associated-driver mutations in CMML is infrequent (~8%) and is largely restricted to JAK2V617F. CMML patients with MPN-associated driver mutations have a higher HB/hematocrit, are more likely to have proliferative features and palpable splenomegaly, and are less likely to be thrombocytopenic. There was a trend towards an increased thrombotic risk, with no impact of these mutations on overall and leukemia free survival. Disclosures No relevant conflicts of interest to declare.

Abstract Background: Trabectedin is an FDA-approved DNA minor groove binder (MGB) that has activity against translocation-associated sarcomas. Lurbinectedin is a next-generation MGB with pre-clinical activity against myeloid leukemia cells. A dose-finding phase 1 clinical trial was performed in patients with acute myeloid leukemia (AML) and myelodysplastic syndrome (MDS) with further assessment of safety and tolerability. Methods: Forty-two patients with relapsed/refractory AML/MDS received lurbinectedin administered as a 1-hour intravenous infusion in a 3+3 study design. Two dosing schedules were used: 3.5 mg, 5 mg, 7 mg, or 6 mg on days 1 and 8 or 2 mg, 3 mg, 1 mg, or 1.5 mg for 3 consecutive days on days 1 to 3. Patients 18 years or older with a diagnosis of advanced, relapsed/refractory AML (non-acute promyelocytic leukemia) and MDS were eligible and treated on study. Eligible patients had adequate hepatic, renal, and cardiac function and an Eastern Cooperative Oncology Group (ECOG) performance status of 0 to 2. Patients with uncontrolled infection, human immunodeficiency virus, cardiac and neurological disorders, or those who were pregnant were ineligible. Clinical trial information: NCT01314599. Results: Three patients experienced dose-limiting toxicities of rhabdomyolysis (grade 4), hyperbilirubinemia (grade 3), and oral herpes (grade 3) with the days 1 and 8 schedule. Otherwise, adverse events mainly consisted of gastrointestinal manifestations (n=11), febrile neutropenia/infections (n=4), pulmonary toxicity (n=2), and renal failure (n=2). The most common laboratory abnormalities observed were an increase in creatinine (93%) and anemia, neutropenia, and thrombocytopenia (100%). Overall, 33 of 42 patients (79%) had reduction in blasts in peripheral blood or bone marrow. One patient achieved a partial response and two patients a morphologic leukemia-free state. Most (n=30, 71%) were discontinued due to progressive disease. Early deaths occurred from disease-related causes that were not attributable to lurbinectedin. Four patients with a chromosome 11q21-23 abnormality had significantly greater bone marrow blast reduction than those without such abnormality, with decrease of 31±14% (n=4) vs. 8±8% (n=16), respectively (P=0.04). Conclusions: Overall, lurbinectedin was safe and tolerated using the schedules and dose levels tested. While no sustained remissions were observed, single-agent lurbinectedin was transiently leukemia suppressive for some patients. Disclosures Rodríguez: PharmaMar: Employment. Ravandi:Bristol-Myers Squibb: Research Funding; Jazz: Honoraria; Abbvie: Research Funding; Seattle Genetics: Research Funding; Abbvie: Research Funding; Amgen: Honoraria, Research Funding, Speakers Bureau; Orsenix: Honoraria; Seattle Genetics: Research Funding; Astellas Pharmaceuticals: Consultancy, Honoraria; Sunesis: Honoraria; Orsenix: Honoraria; Macrogenix: Honoraria, Research Funding; Astellas Pharmaceuticals: Consultancy, Honoraria; Jazz: Honoraria; Xencor: Research Funding; Bristol-Myers Squibb: Research Funding; Amgen: Honoraria, Research Funding, Speakers Bureau; Macrogenix: Honoraria, Research Funding; Xencor: Research Funding; Sunesis: Honoraria. Daver:Sunesis: Consultancy; Alexion: Consultancy; Daiichi-Sankyo: Research Funding; BMS: Research Funding; ImmunoGen: Consultancy; Kiromic: Research Funding; Incyte: Research Funding; Pfizer: Consultancy; Incyte: Consultancy; ARIAD: Research Funding; Karyopharm: Consultancy; Pfizer: Research Funding; Karyopharm: Research Funding; Novartis: Consultancy; Sunesis: Research Funding; Novartis: Research Funding; Otsuka: Consultancy. Jain:Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; ADC Therapeutics: Research Funding; Infinity: Research Funding; Pfizer: Research Funding; Novimmune: Honoraria, Membership on an entity's Board of Directors or advisory committees; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees; BMS: Research Funding; Servier: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees; Genentech: Research Funding; ADC Therapeutics: Honoraria, Membership on an entity's Board of Directors or advisory committees; Adaptive Biotechnologioes: Research Funding; Pharmacyclics: Research Funding; Incyte: Research Funding; Verastem: Research Funding; Seattle Genetics: Research Funding; Pharmacyclics: Honoraria, Membership on an entity's Board of Directors or advisory committees; Astra Zeneca: Research Funding; Astra Zeneca: Research Funding; Servier: Research Funding; Celgene: Research Funding; Seattle Genetics: Research Funding; Verastem: Honoraria, Membership on an entity's Board of Directors or advisory committees; Astra Zeneca: Honoraria, Membership on an entity's Board of Directors or advisory committees; Infinity: Research Funding; Adaptive Biotechnologies: Honoraria, Membership on an entity's Board of Directors or advisory committees; Pfizer: Research Funding; Cellectis: Research Funding; ADC Therapeutics: Research Funding; Abbvie: Honoraria, Membership on an entity's Board of Directors or advisory committees; Adaptive Biotechnologioes: Research Funding; Pharmacyclics: Research Funding; Cellectis: Research Funding; Verastem: Research Funding; Servier: Research Funding; Abbvie: Research Funding; Incyte: Research Funding; Genentech: Research Funding; Abbvie: Research Funding; BMS: Research Funding; Astra Zeneca: Honoraria, Membership on an entity's Board of Directors or advisory committees; Verastem: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees; ADC Therapeutics: Honoraria, Membership on an entity's Board of Directors or advisory committees; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees; Servier: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novimmune: Honoraria, Membership on an entity's Board of Directors or advisory committees; Adaptive Biotechnologies: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Honoraria, Membership on an entity's Board of Directors or advisory committees; Abbvie: Honoraria, Membership on an entity's Board of Directors or advisory committees. Maiti:Celgene Corporation: Other: Research funding to the institution. Martinez:PharmaMar: Employment. Siguero:PharmaMar: Employment. Al-Kali:Novartis: Research Funding.

Abstract Background Myelofibrosis (MF) is a myeloproliferative neoplasm (MPN) characterised by the frequent presence of driver mutations in genes causing activation of JAK2 signalling pathways (JAK2, CALR and MPL). Additional mutations affecting epigenetic regulators and splicing machinery are common. Anaemia with RBC-transfusion-dependence is common in patients with advanced myelofibrosis and represents a major unmet need. The RESUME study assessed the rates of RBC-transfusion independence (TI) after therapy with Pomalidomide (POM) vs placebo in persons with MPN-associated myelofibrosis and RBC-transfusion dependence. 16% of patients in both the POM and placebo arms became TI. Aims The genetic landscape of strictly confirmed transfusion dependent MF is not fully characterised. Our aim was to analyse the genetics of transfusion-dependent myelofibrosis patients in the RESUME trial and correlate with clinical characteristics, outcome and therapy response. Methods DNA samples were available from 207 of 252 patients and analysed by targeted re-sequencing using a Fluidigm Access Array gene panel followed by next generation sequencing. The panel included JAK2, CALR, MPL, TET2, ASXL1, EZH2, DNMT3A, IDH1/2, CBL, IKZF1, U2AF1, CHEK2, TP53, SF3B1, SRSF2, SH2B3, BARD1, DAP3, HRAS, IRF4, KRAS, KIT, Mir662, NFE2, POLG, SCRIB, SETBP1, TCF12 and VPS45. Results 97% (95-99%) of subjects had a mutation in ≥1 targeted gene. 2 mutations were detected in 41% (34-48%) and ≥3 in 27% (21-33%). 7 had no detectable mutation. Mutations in JAK2V617F, CALR and MPL were identified in 66% (59-72%), 14% (8-19%) and 7% (4-11%) of subjects (Figure 1), with no driver mutation in 27 patients (13%; 9-18%) (triple-negative). 68% (61-74%) had additional non-driver mutations. 42% (35-48%) (N=86) had spliceosome mutations (U2AF1 [21%]; SF3B1 [11%]; SRSF2 [8%]; ZRSR2; [6%]). More spliceosome mutations were detected in men than women (47% [39-55%] vs 27% [15-40%]; p=0.009). Spliceosome mutations were mutually exclusive in 83 subjects and were less common in subjects with prior polycythaemia vera (17% [5-37%]) compared with prior essential thrombocythaemia (39% [22-58%]) and primary MF (46% [38-54%]; p=0.024). Mutations in epigenetic regulators (ASXL1, 28%; TET2, 8%; DNMT3A 5%; EZH2 4%) were detected at similar rates to those previously reported. High molecular risk (HMR) mutations (ASXL1, EZH2, IDH1/2, SRSF2) were detected in 36% [29-43%] of subjects. Only 10 of 105 subjects with an epigenetic regulator gene mutation had ≥1 related mutation. Subjects with JAK2V617F were significantly more likely than subjects with a CALR mutation to have: (1) ≥1 additional mutation (72% [64-79%] vs. 35% [18-54%], p=0.0001); (2) a spliceosome mutation (44% [36-53%] vs. 17% [6-36%], p=0.07), in particular a U2AF1 mutation (24% [17-32%] vs. 0%; p=0.004) and (3) a HMR mutation (38% [30-47%] vs. 21% [8-40%]; p=0.07). Survival at 1.5 years was 62% (55-67%) and was not significantly associated with the presence or number of mutations in this uniformly high-risk cohort. Survival in subjects without an SF3B1 mutation was better than those SF3B1-mutated (80% [56-91%]) vs. 59% [52-65%]; p=0.07). Driver mutation status did not influence the probability of achieving red blood cell (RBC) TI, regardless of therapy. Additional non-driver mutations were more often detected in those failing to achieve RBC-TI than those achieving RBC-TI (70% [63-77%] vs 56% [40-71%], p=0.07). Furthermore, those with additional non-driver mutations were less likely to achieve ≥50% reduction in RBC transfusions (24% [17-32%] vs. 39% [27-51%]; p=0.03). A significant correlation persisted in subjects receiving POM but not in those receiving placebo. There was also a significant correlation between U2AF1 mutations and RBC-TI in POM treated subjects compared with controls; U2AF1-mutated subjects were less likely to achieve RBC-TI (3% [1, 17%]) than U2AF1-unmutated subjects (25% [17, 34%], p=0.008). No other mutations were significantly correlated with response. Conclusion We found a high incidence of spliceosome mutations in persons with MPN-associated MF and RBC-transfusion-dependence. Mutation of U2AF1 correlated with response in subjects receiving POM but not in those receiving placebo. Incorporation of mutation profiling into clinical trial design may help to inform subgroups of patients that may benefit from the intervention. Disclosures Devos: Novartis: Consultancy; Celgene: Consultancy; Takeda: Consultancy. Gisslinger:Shire: Consultancy, Honoraria; Novartis: Honoraria, Research Funding; AOP Orphan Pharmaceuticals AG: Consultancy, Honoraria, Research Funding; Janssen Cilag: Consultancy, Honoraria. Kiladjian:Celgene: Membership on an entity's Board of Directors or advisory committees; AOP Orphan: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding. Mesa:Celgene: Research Funding; UT Health San Antonio - Mays Cancer Center: Employment; Pfizer: Research Funding; Gilead: Research Funding; NS Pharma: Research Funding; CTI Biopharma: Research Funding; Incyte Corporation: Research Funding; Novartis: Consultancy; Promedior: Research Funding; Genentech: Research Funding. Ribrag:argenX: Research Funding; BMS: Consultancy, Honoraria, Other: travel; NanoString Technologies: Consultancy, Honoraria; pharmamar: Other: travel; Infinity: Consultancy, Honoraria; MSD: Honoraria; Amgen: Research Funding; Gilead: Consultancy, Honoraria; Servier: Consultancy, Honoraria; Roche: Honoraria, Other: travel; epizyme: Consultancy, Honoraria; Incyte Corporation: Consultancy. Schiller:Celator/Jazz Pharmaceuticals: Research Funding; Pharmacyclics: Research Funding. Vannucchi:Celgene: Membership on an entity's Board of Directors or advisory committees; ITALFARMACO: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau. Reiser:Celgene: Employment. Zhong:Celgene: Employment. Mead:Novartis: Consultancy, Honoraria, Research Funding, Speakers Bureau; ARIAD: Consultancy; Bristol-Myers Squibb: Consultancy; Cell Therapeutics: Consultancy; Celgene: Research Funding; Elstar: Research Funding; Evotek: Research Funding.

Abstract Background: Current prognostic models in primary myelofibrosis (PMF) target overall survival (OS) and utilize MIPSS70 (mutation-enhanced international prognostic scoring system for transplant-age patients), MIPSS70+ version 2.0 (karyotype-enhanced MIPSS70) and GIPSS (genetically-inspired prognostic scoring system, which is based on mutations and karyotype) (JCO 2018;36:310; JCO doi: 10.1200/JCO.2018.78.9867; Leukemia. 2018;doi:10.1038/s41375-018-0107). In the current study, we used logistic regression statistics to identify risk factors for leukemic transformation (LT) within 5 years of diagnosis/referral (i.e. early events) and also performed Cox regression analysis of overall leukemia-free survival (LFS). Methods : Study patients were recruited from the Mayo Clinic, Rochester, MN, USA. Diagnoses of LT and chronic phase PMF were confirmed by both clinical and bone marrow examinations, in line with the 2016 World Health Organization criteria (Blood. 2016;127:2391); specifically, LT required presence of ≥20% blasts in the peripheral blood (PB) or bone marrow (BM) (Blood 2016;127:2391). Statistical analyses considered clinical and laboratory data collected at the time of initial PMF diagnosis or Mayo Clinic referral point. Logistic regression statistics was used to identify predictors of LT at 5 years from initial diagnosis/referral; in the particular method, patients with documented LT within 5 years were "uncensored" while those followed up for at least 5 years, without developing LT, were "censored"; the analysis excluded patients without LT and not followed for at least 5 years. In addition, Cox regression analysis was performed to identify risk factors for overall LFS. The JMP® Pro 13.0.0 software from SAS Institute, Cary, NC, USA, was used for all calculations. Results: 1,306 patients with PMF (median age 65 years; 63% males) were included in the current study; MIPSS70+ version 2.0 risk distribution was 20% very high risk, 41% high risk, 19% intermediate risk, 16% low risk and 4% very low risk. 149 (11%) patients were documented to experience LT, and compared to the remaining patients (n=1157), they were more likely to be males (p=0.02) and mutated for ASXL1 (p=0.01), SRSF2 (0.001) and IDH1 (0.02) and present with higher risk MIPSS70+ version 2.0 (p=0.02). Multivariable logistic regression identified the following as predictors of LT in the first 5 years of disease: IDH1 mutation (odds ratio; OR 78.4), very high risk (VHR) karyotype (OR 57.6), ASXL1 mutation (OR 15.1), age >70 years (OR 13.3), SRSF2 mutation (OR 8.5), male sex (OR 6.9), PB blasts ≥3% (OR 5.4), presence of moderate or severe anemia, adjusted for sex (OR 3.6) and constitutional symptoms (OR 3.1). On Cox regression analysis, the following were associated with inferior LFS: IDH1 mutation (HR 4.3), PB blasts ≥3% (HR 3.3), SRSF2 mutation (HR 3.0), age >70 years (HR 2.1), ASXL1 mutation (HR 2.0) and presence of moderate or severe anemia, adjusted for sex (HR 1.9). Subsequently, HR-based risk point allocation resulted in highly discriminating LT predictive model with HR (95% CI) of 39.4 (10.8-114) for high risk and 4.1 (2.4-7.3) for intermediate risk (Figure 1). Conclusions: The current study identifies IDH1 mutation as a main predictor of LT in PMF. Our study also implicates SRSF2 and ASXL1 mutations and VHR karyotype as other genetic markers of early LT. Other independent contributors of early LT and inferior LFS, overall, included PB blasts ≥3%, moderate to severe anemia and older age. We provide LT prediction model, based on these variables, with leukemia risk ranging from 8% to 57%. Disclosures No relevant conflicts of interest to declare.

Abstract Background: The 2016 World Health Organization (WHO) system lists five morphological categories of systemic mastocytosis (SM): indolent (ISM), smoldering (SSM), SM with an associated hematological neoplasm (SM-AHN), aggressive (ASM) and mast cell leukemia (MCL) (Blood. 2016;127:2391). In the current study, we capitalized on the large number of accumulated cases of SM seen at the Mayo Clinic, between 1968 and 2015 (n=580), in order to devise two separate but complementary prognostic models that are based on either clinically-derived variables, or a combination of both clinical and molecular information. Methods : Study patients (n=580) were recruited from the Mayo Clinic, Rochester, MN, USA. Diagnoses of SM and its morphological subcategories were confirmed by both clinical and bone marrow examinations, in line with the 2016 WHO criteria (Blood. 2016;127:2391). Next-generation sequencing (NGS) was performed in a subset of the study population (n=150). Statistical analyses considered clinical and laboratory data collected at the time of initial diagnosis at the Mayo Clinic. Conventional statistics was used for calculation and of overall survival and determination of inter-independent risk factors. Receiver operating characteristic (ROC) curves were used to determine the prognostically most discriminative platelet threshold. The JMP® Pro 13.0.0 software from SAS Institute, Cary, NC, USA, was used for all calculations. Results: 580 patients with SM (median age 55 years; range 18-88 years; 52% males) were included in the current study; 291 (50%) constituted indolent and 289 (50%) advanced variants; the latter included 85 (15%) ASM, 199 (34%) SM-AHN and 5 MCL cases. At presentation, anemia defined by hemoglobin level below the lower limit of the sex-adjusted reference range, was present in 41% of the patients, hemoglobin <10 g/dl in 16%, red cell transfusion-dependency in 9%, platelet count below the ROC-determined limit of 150 x 109/l in 26%, serum albumin below the lower normal limit (LNL) of the reference range in 22%, serum alkaline phosphatase (ALP) above the upper normal limit (UNL) of the reference range in 54%, urticaria pigmentosa in 41%, mast cell mediator symptoms in 46%, palpable hepatomegaly in 21%, palpable splenomegaly in 31%, "C" findings in 23% and "B" findings in 42%. Median follow-up was 34 months with 239 (41%) deaths and 9 (1.5%) leukemic transformations documented. Cytogenetic information was available in 342 cases, including 51 (15%) with abnormal karyotype and 27 (8%) with unfavorable karyotype. NGS-derived mutation information was available in 150 cases and most frequent mutations were KIT (75%), TET2 (29%), ASXL1 (17%) and CBL (11%). Age-adjusted multivariable analysis of clinical variables, which did not include mutation or cytogenetic information, identified age >60 years (HR 2.5, 95% CI 1.8-3.4), advanced vs ISM (HR 2.3, 95% CI 1.5-3.7), thrombocytopenia <150 x 109/l (HR 2.4, 95% CI 1.8-3.4), anemia (HR 2.1, 95% CI 1.5-3.0), ALP above UNL (HR 2.1, 95% CI 1.5-3.1) and albumin below LNL (HR 1.4, 95% CI 1.0-1.9). A similar age-adjusted multivariable analysis for mutations identified ASXL1 (HR 3.3, 95% CI 1.9-5.5), RUNX1 (HR 4.1, 95% CI 1.2-10.2) and NRAS (HR 5.7, 95% CI 1.7-14.9) as independent molecular risk factors; these mutations were henceforth labelled as "adverse". The addition of "adverse" mutations (HR 2.7, 95% CI 1.6-4.7) to the list of the aforementioned clinical risk factors resulted in loss of significance for age and anemia while platelets below 150 x 109/l (HR 2.9, 95% CI 1.8-4.8), ALP above UNL (HR 3.2, 95% CI 1.8-6.1), albumin below LNL (HR 2.5, 95% CI 1.6-4.0) and advanced vs ISM (HR4.2, 95% CI 1.9-10.7) remained significant. Subsequently, based on the number of risk factors present, a "clinical" (figure 1a; n=380 informative cases) and "clinical-molecular" (figure 1b; n=129 informative cases) risk models were prepared; both risk models performed effectively for advanced and indolent SM, when analyzed separately (data not shown). Conclusions: The current study advances two separate but complimentary risk models for SM and illustrates the additional prognostic contribution of mutations and underlines the importance of thrombocytopenia and serum ALP and albumin levels in both risk models. Furthermore, we show effective application of both risk models in advanced and indolent SM. Disclosures No relevant conflicts of interest to declare.

Abstract Background While unfavorable karyotype at referral is associated with significantly inferior overall and leukemia-free survival in myelofibrosis (MF) patients (Blood. 2011 Oct 27;118(17):4595), the incidence of clonal evolution during JAK inhibitor (JAKi) treatment and its clinical significance are not currently known. We conducted a sponsor-independent, single-center retrospective analysis examining the phenotypic correlates and prognostic impact of clonal evolution during JAKi treatment. Methods Clinical, cytogenetic and molecular data were collected on MF patients treated with one or more JAKi on a clinical trial at the Mayo Clinic, Rochester, MN. Baseline data pertained to the onset of treatment with first JAKi. Karyotype risk categories were as previously defined (Blood. 2011 Oct 27;118(17):4595). Serial bone marrow biopsies were obtained at varying frequencies based on individual JAKi protocol requirements. Mutation screening was performed as previously described (Leukemia. 2013 Apr 26. doi: 10.1038/leu.2013.119). Information on survival and leukemic transformation was updated in July 2013. Results A total of 157 MF patients were studied (60% male; median age 65 years, range 34-89 years). The DIPSS-plus distribution was: Low/Int-1 20 (13%), Int-2 66 (42%), and High 71 (45%). The first JAKi was momelotinib (CYT387) in 79 patients (50%), ruxolitinib in 51 (33%) and fedratinib (SAR302503) in 27 (17%). Median follow up from first JAKi treatment was 30 months (range 1-67 months); during this period, 72 deaths (46%) and 14 (9%) leukemic transformations were documented. Eighty nine patients (57%) had a median total 3 (range 2-8) bone marrow biopsies with karyotype analysis during JAKi treatment. Of these, 21 patients (24%) showed clonal evolution (ie, acquisition or loss of one or more chromosome abnormalities when comparing last observed karyotype during JAKi treatment to baseline). Overall, 13 patients (15%) had upstaging of karyotype risk category (eg, normal to unfavorable), 9 (10%) had downstaging (eg, favorable to normal) and 67 (75%) had no change. Acquisition of worse-than-baseline karyotype was significantly higher in DIPSS-plus high-risk patients (26%) versus non-high risk patients (6%) (p=0.03). There was no association between acquisition of a worse karyotype category and baseline karyotype risk category or ASXL1 or SRSF2 mutation status. There was borderline association with RBC transfusion-dependence and constitutional symptoms at baseline (p=0.06). There was no relationship between clonal evolution and achievement of spleen or anemia response during JAKi treatment (p>0.05). The median overall survival of the entire cohort was 41 months. On univariate analysis, overall survival was significantly worse in patients who acquired a worse-than-baseline karyotype risk category during JAKi treatment (n=13, 77% deaths, median survival=31 months) versus those who did not (n=76, 43% deaths, median survival=52 months) (p=0.01) (Figure). On multivariate analysis, the prognostic significance of acquiring a worse karyotype risk category was maintained against all individual DIPSS-plus prognostic variables, including baseline karyotype risk category, except age >65 years. On univariate analysis, leukemia-free survival was significantly worse in patients who acquired a worse-than-baseline karyotype risk category during JAKi treatment (n=13, 31% leukemic transformation, median leukemia-free survival=32 months) versus those who did not (n=76, 8% leukemic transformation, median leukemia-free survival not reached) (p=0.0006) (Figure). On multivariate analysis against known predictors of leukemic risk in PMF patients (ie, baseline unfavorable karyotype, SRSF1 mutated status and platelet count <100 x 109/L), only acquisition of a worse-than-baseline karyotype risk category maintained its prognostic value (HR 5.3, p=0.03) Conclusions This is the first study to examine the incidence of clonal evolution during JAKi treatment in MF patients. Approximately 25% of patients exhibited clonal evolution; acquisition of a worse-than-baseline karyotype risk category had a strong and independent association with inferior leukemia-free survival. A similar association was also observed for inferior overall survival, albeit not independent of older age. In contrast, there was no association with spleen or anemia response during JAKi treatment. Disclosures: Pardanani: Bristol Myers Squibb: Clinical trial support Other; Sanofi: Clinical trial support. Publication support service., Clinical trial support. Publication support service. Other; PharmaMar: Clinical trial support, Clinical trial support Other; JW Pharmaceutical Corp.: Clinical trial support, Clinical trial support Other.

Abstract Background Recent studies have suggested that increased circulating free light chains, inflammatory cytokines, hepcidin, ferritin, and ASXL1 mutated status have independent prognostic value for survival in primary myelofibrosis (PMF). In the current retrospective study, we studied all the aforementioned variables in the context of DIPSS-plus to examine their relative prognostic contributions for overall and leukemia-free survival. Methods The diagnosis of PMF was according to WHO criteria. The study population included all consecutive referrals to the Mayo Clinic, Rochester, MN where complete information on clinical and laboratory parameters and bone marrow karyotype was available. Inclusion to the study required availability of a research blood sample collected at referral. Levels of circulating free light chains (FLC) (J Clin Oncol. 2012 Apr 1;30(10):1087), inflammatory cytokines (J Clin Oncol. 2011 Apr 1;29(10):1356), hepcidin and ferritin (Am J Hematol. 2013 Apr;88(4):312) were determined as previously described. Disease-relevant mutations (ASXL1, SRSF2, EZH2, IDH-1/2, SF3B1, JAK2V617F and MPLW515) were identified as previously described (Leukemia. 2013 Apr 26. doi: 10.1038/leu.2013.119). Results A total of 224 PMF patients were studied (66% male; median age 63 years, range 18-83 years). The DIPSS-plus distribution was: Low 23 (10%), Int-1 26 (12%), Int-2 98 (44%), and High 77 (34%). Clinical characteristics were: unfavorable karyotype 13%, hemoglobin <10 g/dL 58%, leukocyte count >25 x 109/L 13%, platelet count <100 x 109/L 20%, peripheral blasts ≥1% 62%, red blood cell transfusion-dependent 38%, and constitutional symptoms 36%. Mutation frequencies were: JAK2V617F 61% (n=220), MPLW515 6% (n=204), ASXL1 34% (n=154), SRSF2 16% (n=189), IDH-1/2 3% (n=209), EZH2 1.5% (n=134), SF3B1 5% (n=91) and SETBP1 4% (n=114). Distribution of circulating biomarkers was: FLC >receiver operating characteristic (ROC) cutoff of 3.78 mg/dL 37% (n=222), interleukin (IL)-2R and/or IL-8 >3 standard deviations above normal mean (SD) 75% (n=197), ferritin ≥1000 mcg/L 18% (n=146), ferritin ≥500 30% (n=146), and hepcidin >3SD 72% (n=203). Median follow up from the time of referral was 45 months (range 1-317 months); during this period, 139 deaths (62%) and 27 (12%) leukemic transformations have been documented. The median overall survival of the entire cohort was 61 months. The following variables had DIPSS-plus independent predictive value for inferior survival: ferritin ≥1000 mcg/L (HR 1.9), ASXL1 mutated status (HR 1.7) and FLC >ROC cutoff (HR 2.0) and IL-2R and/or IL-8 >3SD (HR 1.6) (all p<0.05). When the aforementioned variables were added to the multivariate model (sequentially or altogether), only serum ferritin >1000 mcg/L retained its significance for overall survival independent of DIPSS-plus (HR 2.1; p=0.03). The predictive significance for increased ferritin level was maintained in RBC transfusion-dependent (ferritin ≥1000 mcg/L; n=26/54; median survival 21 versus 59 months; p=0.03) and -independent (ferritin >500 mcg/L; n=5/92; median survival 20 versus 80 months; p=0.0002) patients. Multivariable analysis identified the following predictors for inferior leukemia-free survival: SRSF2 mutated status (HR 4.8), unfavorable karyotype (HR 4.0), and circulating blasts ≥1% (HR 3.0) (p<0.05). Conclusions When considering composite risk-assessment in PMF where input variables were disease-relevant mutations and circulating biomarkers in addition to traditional clinical parameters, only increased serum ferritin levels at time-of-referral retained adverse predictive value for overall survival independent of DIPSS-plus. The prognostic value of serum ferritin was independent of anemia and RBC transfusion need. It appears to more fully capture the severity of the underlying erythropoietic defect in PMF by also likely reflecting (as an acute-phase reactant) the marrow-suppressive effect of disease-related inflammation. The shortened survival in patients with increased ferritin levels was unrelated to iron overload since none of the deaths, where information was available, were caused by cardiac siderosis. Serum ferritin levels were not associated with leukemic transformation risk. In the latter analysis, only SRSF2 mutations, unfavorable karyotype and presence of circulating blasts were independently associated with inferior leukemia-free survival. Disclosures: No relevant conflicts of interest to declare.

Abstract Background : Pre-treatment determinants of survival in adult acute myeloid leukemia (AML) include performance status, age, karyotype, the distinction between primary and non-primary AML and FLT3-ITD/NPM1 mutational status. Current literature on AML natural history and risk factors is often based on information derived from stringent protocol studies. In the current series of 1,123 adult patients seen at the Mayo Clinic between 2004 and 2017, we examined long-term survival specified by a number of primarily established risk factors. Methods: Diagnosis of AML and its sub-classification was according to World Health Organization criteria. Study subjects were recruited from the Mayo Clinic AML database. Conventional response criteria were used for CR and CRi assignment; the latter met all criteria for CR with the exception of platelet count <100 x 109/l or absolute neutrophil cunt <1 x 109/l. Standard statistical methods were used for analysis of overall survival, calculated from the initial diagnosis of AML to date of death or last follow-up; analyses were performed both in the absence and in the presence of censoring of survival at time of allogenic stem cell transplant (ASCT). The JMP® Pro 13.0.0 software from SAS Institute, Cary, NC, USA, was used for all calculations. Results: 1,123 adult patients (median age 65 years, range 18-94; 61% males) with non-APL AML were considered; 61% were age >60 years. 351 (31%) patients were seen between 2004 and 2009 and 772 (69%) between 2010 and 2017. AML subcategories were primary (56%), post-myelodysplastic syndromes (post-MDS; 24%), therapy-related (10%), post-myeloproliferative neoplasm (post-MPN; 8%) and post-MDS/MPN (3%). Cytogenetic risk distribution, according to the European LeukemiaNet classification, was favorable in 47 (4%), intermediate in 650 (58%) and adverse risk in 426 (38%) patients. FLT3, NPM1 and CEBPA mutation information was available in 462 (24% mutated), 393 (27% mutated) and 228 (11% mutated) patients, respectively. Treatment included intensive chemotherapy (IC) in 766 (68%) patients, less aggressive chemotherapy, including the use of hypomethylating agents in 144 (13%) and supportive care alone in 213 (19%) patients. ASCT was utilized in 258 (23%) cases, almost all performed after achieving CR/CRi. Complete remission (CR) and CR with incomplete count recovery (CRi) were listed in 333 (30%) and 248 (22%) patients, respectively; the corresponding rates in IC-treated patients were 43% and 32%. Almost all cases of CR/CRi occurred in IC-treated patients; 2 (1.4%) CRs were listed for less aggressive chemotherapy. After a median follow-up of 11 months, 798 (71%) deaths were recorded. Median survival for all 1,123 patients was 14 months with 1-, 3- and 5-year survival rates of 54%, 29% and 23%, respectively; a slight but significant (p=0.01) improvement in survival was apparent in more recent years (Figure 1a). Figures 1b, 1c and 1d depict analysis stratified by AML subcategories, treatment received and response obtained, respectively. Similarly, figures 2a, 2b and 2c depict analysis stratified by karyotype, use of ASCT and age. Multivariable analysis of pre-treatment parameters evaluable in all 1,123 patients identified age >60 years (HR 2.2, 1.9-2.6), adverse karyotype (HR 2.9, 1.9-4.9), intermediate-risk karyotype (HR 1.6, 1.02-2.6), post-MPN AML (HR 1.9, 1.5-2.4) and other secondary AML (HR 1.3 (1.1-1.6), as risk factors for shortened survival; the inclusion in the model of FLT3/NPM1 mutational status in 392 informative cases confirmed the adverse prognostic effect of age >60 years (HR 1.8, 1.4-2.5), adverse karyotype (HR 3.7, 1.4-15.3), post-MPN AML (HR 2.8, 1.6-4.6), other secondary AML (HR 1.4, 1.0-1.9) and FLT3+NPM1- (HR 2.8, 1.6-4.9) and FLT3-NPM1- (HR 1.7, 1.2-2.7) profile. Results were unchanged when survival was censored at time of ASCT. Additional prognostic interaction with treatment strategy and ASCT is further elaborated in an accompanying abstract to be presented. Conclusions: The current study, the largest coming from a single institution, provides practically useful information that should assist with patient consultation on AML prognosis and treatment. The study confirms the primary prognostic importance of age, karyotype and FLT3/NPM1 mutational status, in real-life practice. Novel observations included comparable value of CRi vs CR and the particularly worse prognosis associated with post-MPN AML. Disclosures Al-Kali: Novartis: Research Funding.

Abstract Myeloproliferative disorders (MPD) are a group of heterogeneous diseases that include polycythemia vera (PV), essential thrombocythemia (ET), and primary myelofibrosis (PMF). They are characterized by increased hematopoiesis leading to elevated numbers of non-lymphoid cells and/or platelets in the peripheral blood. Beside thrombotic and hemorrhagic complications, MPD may evolve into secondary acute myeloid leukemia (sAML). Recently characterized markers suggest an opportunity to diagnose and identify subpopulations of MPD patients. In particular, altered expression and point mutations of PRV-1, MPL and JAK2 were commonly found in MPD, as well as deletions on chromosome 20q (del20q). Acquired uniparental disomy (UPD) on chromosome 1p (1pUPD) and 9p (9pUPD) leading to copy-neutral loss of heterozygosity (LOH) is a further mechanism found in MPD which often leads to homozygous activated mutations of MPL and JAK2, respectively. However, the molecular mechanisms involved in the transformation process to sAML remains unclear. Using standard metaphase cytogenetics (MC), chromosomal abnormalities are found in only a proportion of patients with MPD. We hypothesized that with new precise methods more genomic lesions can be uncovered that may be associated with leukemic transformation. To address this issue, we used 250K single nucleotide polymorphisms (SNP) Chip arrays to study chromosomal lesions in 40 sAML samples from patients who evolved from MPD; 7 had preexisting PV, 25 PMF, and 8 ET. Moreover, 43 additional samples of MPD (10 PV, 17 ET, and 16 PMF) were included in this study. SNP-chip analysis showed major chromosomal changes in almost all the sAML samples including monosomy 16, deletions of 1q-, 3p-, 6p-, 5q-, 7q-, 9q-, 12p-, 6q-, 3q-, 17p-, 19q-, and 20q- as well as trisomy 2, 3, 8, 9, 12, 15, 19, 21, and 22. We validated these data by MC. However, numerous new genomic alterations which contained potentially interesting genes that might contribute to leukemic transformation were detected by SNP Chip Array in patient samples with normal karyotype. Moreover, UPD was very frequent: 44% (19/43) of MPD and 53 % (21/40) sAML samples. 1pUPD occurred in 5 patients with MPD (1PV, 4 PMF; 12 %) compared to 5 patients with sAML (1 PV, 4 PMF; 13 %). 9pUPD was found in 16 MPD patients (8 PV, 7 PMF, 1 ET; 37%) and 6 sAML patients (3 PV, 2 PMF, 1ET; 15 %). All patients with 9pUPD proved to be positive for the JAK2 V617F mutation seen by allele specific PCR. Interestingly, the MPD samples only had UPD on 1p, 9p, and 12q. In contrast, sAML samples showed additional UPD regions on 7q, 11q, 12q, 16p, 17p, 19q, and 21q. Beside the evaluation of the non-matching groups of patients with MPD and sAML, we also evaluated 4 patients during their PMF and sAML stages by SNP Chip. The sAML samples acquired additional genomic changes including trisomy 8, 10, 14, 19, duplication on 3q and 6p, and heterozygote deletion on 18q. In contrast, 1pUPD, 9pUPD, and 12qUPD were detected in both MPD and sAML matching samples, suggesting that these changes do not play an immediate role in causing transformation. In conclusion, we detected chromosomal regions possessing genes which may be involved in the leukemic transformation of MPD patients.

Abstract Background : Thrombosis is a characteristic feature in essential thrombocythemia (ET) and polycythemia vera (PV). Previous studies had focused on thrombotic events occurring after diagnosis and did not always distinguish between arterial and venous thrombosis. Arterial thrombosis in ET has been associated with age >60 years, JAK2 mutations, leukocyte count >11 x 109/l, history of thrombosis and cardiovascular risk factors, and venous thrombosis with male sex (Blood 2011;117:5857). In the current two-enter study, we looked for associations between both driver and other mutations, with first incidences of arterial and venous thrombosis in ET and PV, analyzed together and separately. Methods : Study patients were recruited from the Mayo Clinic, Rochester, MN, USA and the University of Florence, Florence, Italy, based on availability of next-generation sequencing-derived mutation information. Diagnoses were according to the 2016 World Health Organization criteria (Blood. 2016;127:2391). Conventional statistics was employed to examine significance of associations, with separate analysis of arterial vs venous thrombosis, occurring at any time before or after formal diagnosis of ET or PV. For the purposes of the current study, only first events were considered. Results: 906 molecularly-annotated patients (416 from Mayo and 490 from Florence), including 502 ET and 404 PV cases, were included in the current study. The Mayo/Florence cohorts included 270/232 ET (median age 57/54 years, 60%/59% females) and 146/258 PV (median age 63/58 years, 52%/44% females) patients; median follow-up was 9.9/12.9 years for ET and 10.7/12.4 years for PV. Driver mutation distribution in ET was 55% JAK2, 27% CALR, 5% MPL and 13% triple-negative. Most frequent mutations, other than JAK2/CALR/MPL, were TET2 (14%; 11% in ET and 18% in PV) and ASXL1 (13%; 13% in ET and 13% in PV). 301 (33%) patients experienced first time thrombosis, before or after diagnosis, including 152 (30%) in ET and 149 (37%) in PV (p=0.03); arterial events occurred in 174 (19%) patients, including 96 (19%) in ET and 78 (19%) in PV (p=0.9); venous events occurred in 177 (20%) patients, including 82 (16%) in ET and 95 (24%) in PV (p=0.007). The number of vascular events after diagnosis was 174 (19%) for arterial and 154 (17%) for venous thrombosis, with no significant difference between ET and PV. Associations with arterial thrombosis: In multivariable logistic regression analysis that included both ET and PV (n=906), age >60 years (23% vs 16%; OR, 1.6, 95% CI 1.1-2.2) and absence of ASXL1 and RUNX1 mutations (21% vs 9%; OR 2.6, 95% CI 1.4-4.8) were associated with arterial thrombosis; these associations remained significant (or near significant) when ET and PV were analyzed separately; in addition, JAK2 mutations in ET displayed borderline significance (p=0.05). Overall incidence of arterial events in ET was estimated at 27% in the presence of all three risk factors (i.e. older age, presence of JAK2 mutations and absence of ASXL1/RUNX1 mutations), 21% with two risk factors, 13% with one risk factor and 9% in the absence of all three risk factors (p=0.01). Associations with venous thrombosis: In multivariable analysis, including both ET and PV (n=906), JAK2 mutations (p<0.001), higher leukocyte count (p=0.03) and younger age (p=0.04) were identified as being significant. Analysis of ET patients only (n=502) identified JAK2 mutations (p<0.001; OR 2.4, 95% CI 1.4-4.1), absence of SRSF2 mutations (p=0.03) and younger age (p=0.04) as independent risk factors and in PV patients (n=404), higher leukocyte count (p=0.06). Prognostic interaction between JAK2 mutations and age: In ET, the overall frequency of venous events was 27% for young patients with JAK2 mutations vs 13% for older JAK2 mutated cases vs 10% for JAK2 unmutated young patients vs 13% for JAK2 unmutated older patients (p<0.001). The corresponding percentages for arterial events were 20%, 24%, 14% and 19%, respectively (p=0.1). Conclusions: JAK2 mutations contribute to the risk of both venous (younger patients) and arterial (young and older patients) thrombosis, in an age-dependent manner; the association with venous thrombosis might explain the higher incidence of venous thrombosis in PV, compared to ET. Additional studies are required to confirm the observed lower risk of thrombosis in patients with ASXL1, RUNX1 and SRSF2 mutations and provide insight into the underlying biological explanation. Disclosures No relevant conflicts of interest to declare.