Ketterling, Rhett P.

Abstract The impact of fluorescence in-situ hybridization (FISH) on outcome in AL amyloidosis remains uncertain. We analyzed the response and overall survival (OS) of 692 AL amyloidosis patients with available FISH testing at diagnosis. First line treatment was categorized as autologous stem cell transplant or three non-transplant regimens (melphalan-based; bortezomib-based, and immunomodulatory drug (IMiD)-based). Forty-nine percent of patients had t(11;14), 37% del 13q/monosomy 13 and 19% had trisomy/tetrasomy. Analysis by abnormality type was restricted to t(11;14) and trisomy/tetrasomy sub-groups as chromosome 13 abnormalities were commonly associated with the other abnormalities. Patients with t(11;14) had lower rate of very good partial response or better (≥VGPR) compared to those lacking t(11;14) (56% vs 70%, P=0.001). By regimen stratification, this difference was maintained for bortezomib-based (52% vs 77%; P=0.004) and IMiD-based therapy (13% vs 54%; P=0.04) (Figure 1). Patients with trisomy/tetrasomy had no difference in the rate of ≥VGPR compared to those who did not (66% vs 63%, P=0.62), with no difference within regimen types. OS was similar between t(11;14)-positive and negative patients (median 43 vs 57 months; P=0.58). However, sub-analysis by regimen type showed a significantly inferior OS among t(11;14)-positive bortezomib-treated patients (median 15 vs 27 months; P=0.05) and t(11;14)-positive IMiD-treated patients (median 12 vs 32 months; P=0.05) (Figure 2). Among t(11;14)-positive bortezomib-treated patients, the OS difference was maintained among favorable-prognosis patients, but was absent for poor-prognosis sub-groups (Table). Trisomy/tetrasomy was associated with inferior OS (median 29 vs 69 months; P=0.001), a difference that was maintained for melphalan (median 15 vs 32 months; P=0.01) and borderline significance for bortezomib (median 14 vs 38 months; P=0.09). Multivariate analysis confirmed an independent effect on OS for trisomy/tetrasomy in the study cohort and for t(11;14) among bortezomib-treated patients. FISH analysis is essential in newly diagnosed AL amyloidosis, as it provides prognostic information among treatment groups and may influence the selection of induction treatment. Patients with t(11;14) should be considered for ASCT at diagnosis. Disclosures Dispenzieri: Celgene: Research Funding; Alnylam: Research Funding; pfizer: Research Funding; Prothena: Membership on an entity's Board of Directors or advisory committees; GSK: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Jannsen: Research Funding. Kumar:Glycomimetics: Consultancy; AbbVie: Research Funding; Array BioPharma: Consultancy, Research Funding; Kesios: Consultancy; Onyx: Consultancy, Research Funding; Noxxon Pharma: Consultancy, Research Funding; BMS: Consultancy; Skyline: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Research Funding; Sanofi: Consultancy, Research Funding; Millennium: Consultancy, Research Funding; Celgene: Consultancy, Research Funding. Kapoor:Amgen: Research Funding; Takeda: Research Funding; Celgene: Research Funding.

Abstract Background In myelodysplastic syndromes (MDS), we have previously shown the adverse prognostic effect of ALC <1.2 x 10(9)/L (Nisha et al. Am J Hematol 2010;85:160). In the current larger study of 889 patients with MDS, we sought to validate and expand on our previous observations and also examine the effect of lymphocyte-to-monocyte ratio (LMR). Methods We retrospectively recruited 889 consecutive patients with primary MDS who were untreated at the time of referral to our institution, and in whom ALC and absolute monocyte count (AMC) at time of referral was documented. The diagnosis of MDS and leukemic transformation (LT) was according to WHO criteria (Blood. 2009;114:937). Complete follow-up information was updated in January 2015. Comparison of laboratory and clinical features was made between patients with subnormal and normal ALC; patients with above normal ALC were considered separately. Overall and leukemia-free survivals of patients with normal ALC was compared to those with either subnormal ALC or, in order to validate our previous observation, with ALC <1.2 x 10(9)/L. Results Patient characteristics: Median (range) values for the 889 study patients (69% males) included: age 72 (18-98), hemoglobin 9.6 g/dL (5.4-15.7), leukocyte count 3.4 x 10(9)/L (0.4-35), AMC 0.2 x 10(9)/L (0-1.7), platelet count 106 x 10(9)/L (2-1804), circulating blasts 0% (0-18) and bone marrow blasts 3% (0-19). Transfusion need was documented in 33% of patients and abnormal karyotype in 49%. Risk stratification by the revised international prognostic scoring system (IPSS-R) was very high in 10%, high in 16%, intermediate in 20%, low in 36% and very low in 16%. The median (range) ALC for the entire study population of 889 patients was 1.16 x 10(9)/L (0.02-8.9). The normal range of ALC at our institution was 0.9-2.9 x 10(9)/L; the number of patients with subnormal, normal and above normal ALC was 261 (29%), 598 (67%) and 30 (4%), respectively. In addition, 442 (50%) and 417 (47%) patients had ALC below 1.2 x 10(9)/L and ALC between 1.2 and the upper limit of normal, respectively. After a median follow-up of 27 months, 712 (80%) deaths and 116 (13%) leukemic transformations were documented. Comparison of patients stratified by absolute lymphocyte count Compared to patients with normal ALC, patients with subnormal ALC displayed lower hemoglobin (p=0.002), higher red blood cell transfusion need (p=0.0003), lower leukocyte count (p<0.0001), lower monocyte count (p=0.002) and lower platelet count (p<0.0001), whereas borderline association was also apparent for older age (p=0.06). In univariate analysis, survival was adversely affected by lower ALC, treated as a continuous variable (p=0.01). Similarly, when compared to patients with normal ALC, patients with subnormal ALC (p=0.001; HR 1.3, 95% CI 1.1-1.5) and those with ALC <1.2 x 10(9)/L (p=0.0002; HR 1.3, 95% CI 1.2-1.6) experienced significantly shortened survival. There was no difference in survival between patients with above normal ALC and those with either subnormal (p=0.58) or normal (p=0.41) ALC; accordingly, patients with above normal ALC were excluded from subsequent analysis. In multivariable analysis, the adverse effect of subnormal ALC was shown to be independent of age, gender, anemia, thrombocytopenia, neutropenia , circulating blast percentage, bone marrow blast percentage or cytogenetic risk stratification by and IPSS; the same held true for ALC <1.2 x 10(9)/L. The association with IPSS-R was of borderline significance for both ALC <1.2 x 10(9)/L (p=0.06) and subnormal ALC (p=0.1). The adverse effect of ALC was most apparent in patients with very low or low risk disease per IPSS-R (p=0.0007 for subnormal ALC and 0.0003 for ALC <1.2 x 10(9)/L), compared to those with higher risk status (p=0.67 and 0.7, respectively). Neither subnormal ALC (p=0.4) nor ALC <1.2 x 10(9)/L (p=0.1) affected leukemia free survival. Analysis using LMR in place of ALC showed similar but not necessarily superior results. Conclusions Compared to those with normal ALC, MDS patients with either subnormal ALC or with ALC below 1.2 x 10(9)/L experienced shorter overall, but not leukemia-free, survival; this adverse effect was most apparent in lower risk patients and was independent of most of the currently established risk factors for survival in MDS. The observations from the current study suggest the possible therapeutic value of augmenting host immunity in lower risk MDS. Disclosures Al-Kali: Onconova Therapeutics, Inc.: Research Funding; Celgene: Research Funding.

Abstract Background Spliceosome pathway gene mutations are recurrent in myeloid malignancies with the highest frequencies reported for myelodysplastic syndromes associated with ring sideroblasts (MDS-RS; 85%), MDS without RS (44%) and chronic myelomonocytic leukemia (CMML; 55%) (Nature 2011;478:64). SF3B1 mutations were the most frequent (75%) in MDS-RS and SRSF2 mutations in CMML (28%); U2AF1 mutational frequencies were 12% in MDS without RS and 8% in CMML. We have previously described SRSF2 (Blood. 2012;120:4168) and SF3B1 (Leukemia. 2012;26:1135) mutations in 17% and 6.5% of patients with primary myelofibrosis (PMF); prognostic relevance was shown for the former but not the latter. Objectives The objectives of the current study were to i) describe the incidence of U2AF1 mutations in PMF and their correlation with clinical features, karyotype and other mutations and ii) examine the prognostic significance of U2AF1 mutations in PMF, in the context of both conventional prognostic models and other prognostically-relevant mutations. Methods Information on clinical and laboratory parameters and karyotype was available in all study patients, at time of referral, which coincided with time of sample collection for mutation screening. Risk stratification was according to the Dynamic International Prognostic Scoring System (DIPSS)-plus system. U2AF1 and other mutations were analyzed using standard PCR techniques and bidirectional sequencing; for U2AF1, two hot spots that included residues S34 and Q157 were amplified. Results A total of 251 PMF patients (median age 63 years; 160 males) were studied. DIPSS-plus risk distribution was high in 32%, intermediate-2 in 38%, intermediate-1 in 17% and low in 13% of the patients. The frequency of each DIPSS-plus adverse feature was as follows: age >65 years (42%), transfusion need (32%), hemoglobin <10 g/dL (47%), leukocyte count >25 x 10(9)/L, (16%), platelet count <100 x 10(9)/L (22%), ≥1% blasts (57%), constitutional symptoms (35%), and unfavorable karyotype (9%). Karyotype was normal in 156 (63%) patients. At a median follow-up of 48 months, 158 (63%) deaths and 27 (11%) leukemic transformations were recorded. Mutational frequencies Forty-one (16.3%) patients harbored U2AF1 mutations: 16 (39%) Q157P, 10 (24%) Q157R, 8 (20%) S34F, 4 (10%) S34Y and one each for Q157P/E159A, Q157R/S34Y and Q157-Y158insYE. Frequencies for other mutations were 11% for SRSF2, 7.3% for SF3B1, 31% for ASXL1, 5.5% for EZH2, 5% for IDH1/2 and 58% for JAK2V617F. U2AF1 mutations were usually, but not always, exclusive of other spliceosomal mutations: one patient expressed all three spliceosomal mutations. The frequency of any one of the three spliceosomal mutations was 34%. Clinical correlates U2AF1 mutations were significantly associated with older age (p=0.02), JAK2V617F (p=0.002), mutant ASXL1 (p=0.04), transfusion need (p<0.0001), hemoglobin <10 g/dL (p<0.0001), platelets <100 x 10(9)/L (p<0.0001) and normal karyotype (p=0.006). The associations with anemia, thrombocytopenia, JAK2V617F and normal karyotype were inter-independent; the frequency of U2AF1 mutations in the presence of anemia was 29%, transfusion need 36%, thrombocytopenia 35%, JAK2V617F 23% and normal karyotype 21%. Prognostic interactions U2AF1 mutations were associated with inferior overall (p=0.004) but not leukemia-free (p=0.6) survival. However, the survival association was fully accounted for by the above-mentioned clustering of U2AF1 mutations with anemia and thrombocytopenia. Similarly, although multivariable analysis of U2AF1, SRSF2, ASXL1, EZH2 and IDH mutations identified the first three as being independently predictive of poor survival, only ASXL1 and SRSF2 remained significant when either anemia or thrombocytopenia was included as a co-variate. Conclusions U2AF1 mutations are the most frequent spliceosome pathway mutations in PMF, cluster with normal karyotype and JAK2V617F, and are strongly associated with anemia and thrombocytopenia; the latter suggests a pathogenetic contribution to ineffective hematopoiesis in PMF. The current study also suggests that more than one third of patients with PMF carry a spliceosome mutation. Disclosures: No relevant conflicts of interest to declare.

Abstract Background: Cytogenetic evaluation using fluorescence in situ hybridization (FISH) at the time of diagnosis is essential for initial risk stratification in multiple myeloma. Despite the absence of cytogenetic high-risk abnormalities a subset of patients does experience poor overall survival comparable high-risk disease (i.e. median overall survival less than three years after diagnosis). We aimed to identify demographic, clinical, and cytogenetic characteristics predicting poor three-year overall survival in patients with standard-risk cytogenetics. Methods: We studied 428 patients who were diagnosed with multiple myeloma between July 2004 and July 2014 at Mayo Clinic Rochester, underwent FISH evaluation within six months of diagnosis, and received treatment with novel agents (immunomodulator, proteasome-inhibitor, or a combination thereof). Patients with high- and intermediate-risk cytogenetics as well as patients lost to follow-up within three years were excluded. High-risk cytogenetics were defined as del(17p), t(14;16), and t(14;20). Intermediate-risk cytogenetics were defined as t(4;14) and gain(1q). Bone marrow aspirates were evaluated for deletions, monosomies, trisomies, and tetrasomies using chromosome- or centromere-specific FISH probes. IGH rearrangements were evaluated using an IGH break-apart probe and evaluating up to five potential partners (FGFR3, CCND1, CCND3, MAF, and MAFB). A multivariable-adjusted logistic regression model was used to assess the associations between the parameters of interest and three-year overall survival. Discrimination and calibration of the model were evaluated using the c-statistic and the Hosmer-Lemeshow test, respectively. The odds ratios of the identified predictors were rounded up to the next integer and assigned as points in a scoring system. Receiver operating characteristic analysis was used to determine the optimal cut-point and associated test performance characteristics. P-values below 0.05 were considered statistically significant. Results: The median age at diagnosis was 65 years (31 - 95), 259 (61%) of the patients were male. The median overall survival was 7.4 years (6.1 - 8.6) for the entire cohort (n = 428), 10.5 years (8.3 - NR) for those who survived at least three years (n = 327, 76%), and 1.6 years (1.2 - 1.7) for those who did not survive three years after diagnosis (n = 101, 24%). The factors associated with poor three-year overall survival and the derived scoring system are summarized in Table 1. Conclusions: Patients with multiple myeloma and standard-risk cytogenetics are a heterogeneous group. One fourth of the patients are experiencing less than three years of overall survival after diagnosis. Stage, age, extent of bone marrow involvement, karyotype, and platelet count at the time of diagnosis were helpful in identifying patients at risk for poor three-year overall survival. These findings emphasize the importance of further risk stratification in this patient population and warrant external validation. Disclosures Dispenzieri: Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Jannsen: Research Funding; pfizer: Research Funding; Prothena: Membership on an entity's Board of Directors or advisory committees; GSK: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; Alnylam: Research Funding. Kapoor:Takeda: Research Funding; Amgen: Research Funding; Celgene: Research Funding. Kumar:AbbVie: Research Funding; BMS: Consultancy; Amgen: Consultancy, Research Funding; Takeda: Consultancy, Research Funding; Sanofi: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Noxxon: Consultancy, Honoraria; Janssen: Research Funding; Skyline: Consultancy, Honoraria.

Abstract Background: The current standard of care for eligible newly diagnosed multiple myeloma (MM) patients is induction therapy with novel agents followed by high dose chemotherapy and autologous stem cell transplant (ASCT). The International Myeloma Working Group proposed the Revised International Staging System (R-ISS) based on the presence of adverse chromosomal abnormalities (CA) detected by FISH (t(4;14), t(14;16) or del17p), in combination with ISS and LDH at diagnosis. However, there are a limited number of studies that have validated this risk model in the transplant and novel agents setting. Aims: To determine whether R-ISS is an appropriate risk-model for estimating overall survival (OS) and progression free survival (PFS) for transplant-eligible MM patients. Patients and Methods: We retrospectively studied a cohort of 519 MM patients who received novel drugs in the induction and subsequently underwent ASCT at Mayo Clinic Arizona from 2005 to 2014. In all, 95 patients met the inclusion criteria: comprising complete data at diagnosis (ISS, serum LDH level, and CA by FISH). The primary endpoint was OS from SCT and the secondary end point was PFS from ASCT. R-ISS groups were defined as described by Palumbo et al. J Clin Oncol. 2015; 33(26):2863-2869. Results: There were 50 (52.6%) men and 45 (47.4%) women who underwent ASCT in this period, with a median age at the time of transplant of 66-years-old (range, 36-78). There were 27 patients (28.4%) with high-risk CA: 12 patients (12.6%) with del17p; 11 patients (11.6%) with t(4;14); and 6 (6%) with t(14;16). In addition, 8 patients (8.5%) had high LDH levels and 9 patients (9.5%) presented with renal impairment at diagnosis. The patients were staged at diagnosis according to the three R-ISS groups: 44 patients (46.3%) had stage I, 26 (27.4%) had stage II, and 25 (26.3%) had stage III. CyBorD was the preferred induction regimen which was received by 42 patients (44%). There were 14 patients (15%) who received at least 2 lines of induction. All patients were in at least partial response (PR) at the moment of transplant: 32 in complete response (CR), 32 in very good partial response (VGPR) and the remaining 31 in PR. The response achieved at day +100 after ASCT improved, with 54 patients (57%) in CR, and only 18 patients (19%) in PR. After a median follow-up of 61 months (range, 14-135), median OS from SCT was 108 months (95% CI: 85 - 132 months) and the median PFS was 45.4 months (95% CI: 31.1 - 53.8 months) in the whole series.MM patients with R-ISS III had a significantly shorter median OS compared to patients with R-ISS II or R-ISS I (32.1 months vs. 94.7 months vs. not reached, respectively, P<0.0001) (Figure). No statistically significant differences in baseline characteristics were identified among these groups to explain the differences in OS observed. PFS among these groups was not statistically significant, only showing a trend towards shorter PFS in R-ISS III compared with either R-ISS I or II: median 22.1 months vs. 35.7 months, respectively, (P=0.2). Renal impairment at diagnosis, IgA subtype, ≥ 2 lines of induction treatment, and less than CR achieved at day +100 after ASCT were also associated with significantly inferior OS. Multivariate analysis selected R-ISS as an independent predictor for OS (HR: 2.3, 95% CI: 1.1-4.8; P=0.03), as well as ≥ 2 lines before ASCT. CR at day +100 after ASCT was the most important independent factor for predicting PFS (HR: 0.4; 95% CI: 0.2-0.6; P<0.001). Conclusion: R-ISS assessed at diagnosis was an independent predictor for OS after ASCT in our series, with median OS for the different R-ISS groups comparable to those reported by Palumbo et al. in their subgroup of younger patients. Thus, this study lends further support for the R-ISS as a reliable prognostic tool for estimating OS in transplant-eligible MM patients. In addition, new treatment approaches are needed for the high-risk patients (R-ISS III) with a median OS of 2.5 years. Figure Figure. Disclosures Reeder: Millennium: Research Funding; BMS: Research Funding; Celgene: Research Funding; Novartis: Research Funding. Mikhael:Abbvie: Research Funding; Onyx: Research Funding; Sanofi: Research Funding; Celgene: Research Funding. Bergsagel:Amgen, BMS, Novartis, Incyte: Consultancy; Novartis: Research Funding. Stewart:celgene: Consultancy. Fonseca:Janssen: Consultancy; Celgene: Consultancy; Sanofi: Consultancy; Novartis: Consultancy; Bayer: Consultancy; AMGEN: Consultancy; AMGEN: Consultancy; AMGEN: Consultancy; Patent: Patents & Royalties: Prognostication of MM based on genetic categorization of FISH of the disease; AMGEN: Consultancy; Millennium, a Takeda Company: Consultancy; Janssen: Consultancy; Sanofi: Consultancy; Patent Pending: Patents & Royalties: The use of calcium isotopes as biomarkers for bone metabolisms; Novartis: Consultancy; Patent: Patents & Royalties: Prognostication of MM based on genetic categorization of FISH of the disease; Millennium, a Takeda Company: Consultancy; Millennium, a Takeda Company: Consultancy; Bayer: Consultancy; Celgene: Consultancy; Patent Pending: Patents & Royalties: The use of calcium isotopes as biomarkers for bone metabolisms; Patent: Patents & Royalties: Prognostication of MM based on genetic categorization of FISH of the disease; Patent Pending: Patents & Royalties: The use of calcium isotopes as biomarkers for bone metabolisms; BMS: Consultancy; Millennium, a Takeda Company: Consultancy; BMS: Consultancy; Patent: Patents & Royalties: Prognostication of MM based on genetic categorization of FISH of the disease; Patent Pending: Patents & Royalties: The use of calcium isotopes as biomarkers for bone metabolisms.

Abstract Background Increased serum levels of lactate dehydrogenase (LDH) typically accompany primary myelofibrosis (PMF) and might be linked to increased cell turnover from clonal myeloproliferation, including leukocytosis, low grade hemolysis and extra-medullary hematopoiesis in the liver. Despite the fact that serum LDH has been extensively utilized as a prognostic marker in both lymphoid neoplasms and solid tumors, there are limited studies in PMF that have systematically examined the clinical significance of the degree of serum LDH elevation in PMF. Methods Study patients fulfilled the 2016 WHO criteria for the diagnosis of PMF, including both pre-PMF and overt PMF (Blood. 2016;127:2391). Additional selection criteria included the availability of serum LDH at time of referral. Marked elevation of serum LDH was defined as a value of ≥1000 U/L (i.e. over 4-fold increase from the upper limit of the normal range for our institution, which was 122-222 U/L), based on preliminary analysis of the threshold for prognostic effect. Targeted next generation sequencing was used to screen for prognostically-relevant mutations (Blood 2015126:354). Statistical analyses considered clinical and laboratory parameters obtained at time of initial referral to the Mayo Clinic. Results LDH values in overt PMF versus pre-PMF: The entire study population consisted of 357 patients, including 311 with overt PMF and 46 with pre-PMF. The median serum LDH level was 514 U/L (range 136-2263): overt PMF 532 U/L (range 136-2263); pre-PMF 401 U/L (range 180-1237) (p=0.0003). Accordingly, in order to avoid the confounding effect of the difference in serum LDH level between overt PMF and pre-PMF, and considering the small number of patients with pre-PMF, further analysis was limited to the 311 patients with overt PMF. Patient characteristics: The 311 patients (median age 64 years; 66% males) with overt PMF included 205 (66%) JAK2, 49 (16%) type 1/like CALR, 13 (4%) type 2/like CALR, 16 (5%) MPL mutated cases and 28 (9%) were "triple-negative". DIPSS-plus risk distribution was 31% high, 43% intermediate-2, 15% intermediate-1 and 12% low; 30% displayed red cell transfusion-dependency and 37% abnormal karyotype, including 14% with unfavorable karyotype. 184 patients were screened for ASXL1 mutations with 42% mutated and 205 for SRSF2 mutations with 16% mutated. Clinical correlates of markedly elevated LDH (≥1000 U/L): Among all 311 study patients with overt PMF, 37 (12%) displayed marked elevation of LDH (≥1000/L). Patients with marked elevation of LDH displayed significantly higher leukocyte count (p=0.005; R-squared = 0.05), circulating blast percentage (p=0.03; R-squared = 0.07) and SRSF2 mutational frequency (44% vs 12%; p<0.0001). Survival analysis: After a median follow up of 3 years, 199 (64%) deaths and 31 (10%) leukemic transformations were documented. In univariate analysis, increased serum LDH level was associated with inferior survival, both as a continuous variable (p=0.002) and as a categorical variable with the cutoff level of 1000 U/L (HR 2.02, 95% CI 1.3-3.1; p=0.001); the survival effect LDH ≥1000/L was independent of DIPSS-plus (HR 1.6, 95% CI 1.1-2.5). Other variables that were significantly associated with shortened survival, on univariate analysis, included all 8 DIPSS-plus variables (p≤0.01 in all instances), absence of CALR type 1/type 1-like (p<0.0001) and presence of ASXL1 (p<0.0001) or SRSF2 (p=0.0006) mutations. In multivariable analysis that included only genetic risk factors, serum LDH retained its significance (HR 2.2, 95% CI 1.3-3.6), along with absence of CALR type 1/type 1-like, or presence of ASXL1 or SRSF2 mutations or unfavorable karyotype. In multivariable analysis that included only clinical variables, serum LDH ≥1000/L was again independently predictive of poor survival (HR 1.7, 95% CI 1.1-2.6), along with age >65 years, hemoglobin <10 g/dL, platelets <100 x 10(9)/L, leukocyte count >25 x 10(9)/L and constitutional symptoms. Patients with marked LDH elevation were also more likely to undergo leukemic transformation (HR 3.1, 95% CI 1.2-7.6). Conclusion The current study suggests that marked elevation of serum LDH in PMF indicates aggressive tumor biology that is currently not accounted for by established clinical or genetic risk factors; the low R-squared values seen in relation to leukocyte count and circulating blasts are consistent with this assumption. Disclosures No relevant conflicts of interest to declare.

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: Outcome studies for the unique cohort of young patients with multiple myeloma (MM) are sparse. In general, MM is a heterogenous disease with the genetic signature being one of the major determinants of prognosis. We have recently reported on improvement in overall survival (OS) of young patients with the use of novel agents, but the maximal survival gain has been achieved by integrating autologous stem cell transplant (SCT) to our current approach. Herein, we report on outcomes of patients with MM who were 50 years or younger at diagnosis and stratified by fluorescence in situ hybridization (FISH) results. Our study focuses on t(11;14) myeloma as its prognostic impact remains unclear with the use of novel agents upfront. Methods: Out of 1384 patients with MM, evaluated consecutively at Mayo Clinic, Rochester, MN between 1/1/2000 and 12/31/2011, 290 (21%) were 50 years or younger at diagnosis. Interphase FISH, performed within 100 days of diagnosis of MM, was utilized to stratify patients as high-risk [deletion 17p, t(14;16), t(14;20) or t(4;14)] or standard-risk [normal FISH, trisomies, t(11;14), t(6;14) or monosomy13/deletion 13q]. FISH results were available in 125 young patients that comprise the cohort of interest in the current study. OS from diagnosis was estimated by the Kaplan-Meier method. Results: Median age at diagnosis of MM was 47 years (range: 22 to 50 years) and 58% of the patients were male. At the time of data cut-off (7/31/2014), 45 (36%) patients had died with 90% of all known causes of deaths (n=39) being MM related. FISH abnormalities were noted in 114 (91%) patients. At diagnosis, 46%, 30% and 24% patients were categorized as International Staging System (ISS) stage I, II and III, respectively. The estimated median follow up was 60 months (95% CI: 54-67) and the 5-year OS rate was 69% [median 86 months (95% CI: 76-108)]. Standard (n=100; 80%) and high (n=25; 20%) risk patients had a median OS of 89 months (95% CI: 76-108) and 77.6 months (95% CI: 42-130), respectively (p=0.87). In order to further investigate the similar outcomes between these broad risk-groups with typically diverse disease course, we assessed the outcomes based on the common genetic abnormalities (Table 1) within each of the 2 categories. Presence of t(11;14) (n=37; 29%) was associated with a significantly shorter median OS (76 months) compared to patients with trisomic and normal FISH profile (n=46) (91 months, p=0.01; Figure 1). Patients with t(11;14) also had a significantly shorter median OS compared to those with other standard-risk FISH abnormalities (median OS 96 months, p=0.02). Presence of t(11;14) was not associated with higher plasma cell labeling index (PCLI, p=0.29) or worse ISS stage (p=0.99) compared to patients without t(11;14). OS survival of patients with t(11;14) was similar to those with high risk features (median 76.2 vs. 77.6 months, p=0.32). Of 24 (65%) patients with t(11;14) who underwent SCT, 79% had early SCT (within 12 months from diagnosis). Median OS was 79.4 months (95% CI: 36-108) vs. not reached (NR) (95% CI: 27-NR), respectively (p=0.79) in early versus late SCT. Twenty-one (57%) and 13 (35%) patients with t(11;14) received initial immunomodulatory drugs or bortezomib-based therapies, respectively. Those receiving frontline bortezomib had a higher median OS (76.2 months, 95% CI 76-79) compared to 64.8 months (95% CI 32-108) with other initial agents although it did not reach statistical significance (p=0.78). Conclusion: Presence of t(11;14) is associated with an inferior OS compared to patients with normal FISH, trisomies, or other standard risk abnormalities in young patients with MM. Given, the inherent biases associated with a retrospective study from a referral institution, our findings require external validation. However, our data suggest that our current therapeutic approaches in managing young patients with this unique genetic signature are inadequate. Table 1FISHn(%)Median OS in months (95% CI)t(11;14)37(29)76.2 (53.5-107.7)Trisomies35(28)91.3 (76.4-NR)13/del(13q)11(9)NR (32-NR)Normal11(9)95.5 (45.4-95.6)t(4;14)11(9)NR (40.1-NR)del(17p)/-1710(8)42 (19.2-129.6)t(14;16)4(3)77.6 (42.4-NR)Others6(5)NR (11.5-NR) Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

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.