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Abstract BACKGROUND: Although chemoimmunotherapy (CIT) has improved response rates, treatment free survival, and overall survival in patients with chronic lymphocytic leukemia (CLL), only 40-50% of patients achieve a complete remission and the majority have residual disease when evaluated using sensitive assays. Interactions with nurturing environments can enhance CLL B-cell resistance to apoptosis. These interactions include cytokine mediated prosurvival signals by angiogenic molecules, such as VEGF and bFGF that nurture CLL B-cells in an autocrine fashion and promote CLL cell survival partly through up regulation of anti-apoptotic proteins. These findings provide a strong rationale for testing anti-VEGF therapy in combination with a purine nucleoside analogue CIT regimen for upfront treatment. We conducted a randomized phase 2 CIT trial using pentostatin, cyclophosphamide, and rituximab with (PCR-B) or without (PCR) bevacizumab (B), an anti-VEGF monoclonal anti-body. METHODS: Eligible patients were previously untreated and had CLL in need of treatment by NCI-WG criteria (Blood 111:5446). Patients were randomized using a dynamic allocation procedure stratifying for stage (0-II vs. III-IV) and FISH (17p or 11q deletion vs. other) to receive either 6 cycles of rituximab (100 mg on day 1 of cycle 1; 375 mg/m2on day 2 of cycle 1 and day 1 of cycles 2-6) followed by pentostatin (2 mg/m2) and cyclophosphamide (600 mg/m2) (PCR) administered every 21 days. Patients in the PCR-B cohort also received bevacizumab 15mg/kg on day 1 of cycles 1-5 and days 1, 22, & 43 of cycle 6. All patients underwent complete response evaluation 3 months after day 1 of cycle 6 (or last cycle of treatment for those completing < 6 cycles). MRD was assessed using 6-color flow cytometry (Leukemia 21:956) at the completion of treatment. RESULTS: 68 patients were enrolled through the Mayo Clinic Cancer Research Consortium between 1/2009 and 1/2013. Three patients were excluded from analysis: 1 patient canceled prior to treatment, 1 was dosed incorrectly, and 1 was ineligible due to immunophenotyping inconsistent with CLL. Median age of eligible patients was 63 years (range 43-81) and 43 (66%) were men. With respect to disease stage, 3 (5%), 38 (58%), and 24 (37%) had low, intermediate and high Rai stage disease. Eleven (17%) patients had deletion 17p or 11q & 29 (45%) had unmutated IGHV. No statistically significant differences were observed in these variables by treatment arm. All 65 evaluable patients have completed active treatment, with 54 (83.1%) completing the intended 6 cycles (PCR group 27/32 [84.4%] and PCR-B 27/33 [81.8%]). Hematologic grade 3+ adverse events deemed at least possibly related to treatment were observed in 10 (31.3%) patients on PCR and 12 (36.4%) on PCR-B (p=0.79). Non-hematologic grade 3+ adverse events deemed at least possibly related to treatment were observed in 9 (28.1%) patients on PCR and 18 (54.4%) on PCR-B (p=0.04). The most common such events were hypertension (PCR: 3.1% vs. PCR-B: 21.2%), proteinuria (0% vs. 6.1%) and creatinine increase (3.1% vs. 6.1%). Across both arms, 64/65 (98.5%) patients achieved a response including 31/32 (96.9%) treated with PCR and 33/33 (100%) treated with PCR-B (p=0.49). CR/CRi was achieved in 10/32 (31.3%) patients treated with PCR & 18/33 (54.5%) treated with PCR-B (p=0.08). Of the 28 who achieved a CR/CRi, MRD analysis was completed on 26, of whom 12 (46%) were MRD negative. With respect to treatment arm, 5/32 (16%) patients on PCR and 7/33 (21%) on PCR-B achieved an MRD negative CR. Median time to retreatment for all 65 patients was 44.8 (95% CI: 34.6 – NA) months. Median overall survival has not yet been reached. With current follow-up no differences between treatment-free survival (p=0.38), progression-free survival (p=0.23), or overall survival (p=0.45) are observed by treatment arm. Plasma levels of angiogenic cytokines VEGF, bFGF, thrombospondin (TSP) and the chemokines CCL3 and CCL4 were measured prior to treatment and at the time of the post treatment response evaluation. Correlations of these cytokines with clinical outcome will be presented. CONCLUSION: The addition of bevacizumab to purine analogue-based CIT was generally well-tolerated and may increase complete remission rates in patients with CLL. No clear improvement in treatment free survival has been observed to date. Disclosures Shanafelt: Hospiria: Research Funding; Pharmacyclics/Jannsen: Research Funding; Cephalon: Research Funding; Celgene: Research Funding; glaxoSmithKline: Research Funding; Genetech: Research Funding; Polyphenon E Int'l: Research Funding. Off Label Use: Off label use of pentostatin for treatment of CLL. Off label use of bevacizumab for treatment of CLL. . Kay:Genetech: Research Funding; Pharmacyclics: Research Funding; Hospira: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees.

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. The detection of minimal residual disease (MRD) at the level of 0.01%/10-4 or above is a strong independent predictor of reduced progression-free (PFS) and overall survival (OS) in patients with CLL treated with chemoimmunotherapy. Although newer agents such as B-cell receptor pathway inhibitors can result in prolonged survival without achieving complete response, there remains a important role for MRD analysis in assessing therapeutic strategies aimed at disease eradication and cure. This is particularly important in front-line trials for fit patients which now require at least five years of follow-up if PFS is used as an endpoint. The feasibility of using MRD as a surrogate or intermediate endpoint for accelerated approval of new treatments is under review by regulatory agencies but further prospective validation is required. At the same time technology is rapidly evolving and high-throughput sequencing (HTS) technologies now detect MRD at the 0.0001%/10-6 level. It is therefore important to determine the most effective approaches for quantifying MRD that are compatible with previous studies but sufficiently sensitive for current treatments. AIMS. This collaborative project had two objectives. First, to identify the simplest and most flexible flow cytometry panel capable of detecting MRD at the 0.01%/10-4 or lower, that is compatible with published data and independent of instrument/reagent manufacturer. Second, to compare the flow cytometry approach with HTS analysis using the ClonoSEQ assay (Adaptive Biotechnologies, Seattle, WA). METHODS AND RESULTS. A core panel of antibodies for MRD detection was identified by testing an 8-marker combination in 52 samples (27 post-treatment and 25 dilution study) and re-analysing data with serial exclusion of single markers to determine redundancy. A 1-tube core panel of CD19, CD20, CD5, CD43, CD79b, and CD81 was identified and validated against the previously published 2-tube 6-marker and 4-tube 4-marker ERIC panels in 76 samples (19 post-treatment and 57 dilution study). The results showed good concordance (for log-transformed data above the LoQ, linearity=0.977, Pearson correlation co-efficient=0.983, average difference=0.026 log, 95% limit of agreement 0.20log) and a limit of detection of 0.001%/10-5 for the 1-tube core panel. Inter-operator variation was similar to CML MRD monitoring with both experienced operators, or inexperienced cytometrists after ~1 hour of specific education, achieving a 95% limit of agreement less than 0.3log in samples with MRD levels ranging from 0.0001 – 100%. The flow cytometry approach was compared with the ClonoSEQ HTS assay in 109 samples (21 dilution study and 88 post-treatment samples, complete data currently available on 13/88). The assay was applicable to the vast majority CLL patients, often with two clonal markers. There was 94% concordance at the 0.01% (10-4) threshold (15 samples with ≥0.01% CLL by both methods, 14 samples with <0.01% by both methods, 1 sample with 0.03% CLL by HTS and <0.003% CLL by flow cytometry, and 1 sample with 0.005% CLL by HTS and 0.012% by flow cytometry. HTS detected CLL IGH sequences in 22% (7/31) samples with no detectable CLL cells by flow cytometry (i.e. CLL level 0.0001-0.001%, 3/13 patient samples and 4/18 dilution samples). HTS demonstrated a relatively high variability in quantification, as seen in previous studies, but with a clear superiority in the limit of detection and good linearity (linearity=0.905, Pearson correlation co-efficient=0.870, average difference=0.078 log, 95% limit of agreement 1.5 log). CONCLUSIONS. The 1-tube 6-marker flow cytometry core panel is compatible with published studies, manufacturer-independent and flexible, providing directly quantitative results to 0.001%/10-5 without requiring a pre-treatment sample. HTS requires further work to standardise the quantitative analysis and prospective validation but the ClonoSEQ assay is applicable to >95% of CLL patients, does not require viable cells and is extremely sensitive, detecting residual disease in a significant proportion of cases with <0.01% CLL. The results indicate that flow cytometry and HTS are complementary technologies with a combined approach offering the most reliable way of quantifying CLL at the 0.01%/10-4 threshold while allowing higher sensitivity in clinical trials aimed at disease eradication. Disclosures Rawstron: Roche: Honoraria; Biogen Idec: Consultancy; Gilead: Consultancy, Honoraria; Abbvie: Honoraria; BD Biosciences: Intrasure reagent Patents & Royalties; Celgene: Honoraria; GSK: Honoraria. Williamson:Adaptive Biotechnologies: Employment, Equity Ownership. Sanders:Adaptive Biotechnologies: Employment, Equity Ownership. Robins:Adaptive Biotechnologies: Consultancy, Equity Ownership, Patents & Royalties. Hallek:Celgene: Honoraria, Research Funding; Mundipharma: Honoraria, Research Funding; Roche: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; GSK: Honoraria; Gilead: Honoraria. Hillmen:Roche: Honoraria, Research Funding; GSK: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; Pharmacyclics: Honoraria, Research Funding; Gilead: Honoraria, 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 4931 Background: Autoimmunity, evidenced by positive serology or autoimmune diseases, has been noted to co-exist in pts with MDS. Autoimmune dysfunction has been found in some pts with a variant of MDS called hypocellular MDS, where immune suppressant medications have role in treatment. Clinical implications of AI on survival are not well described. Aim: To study clinical influence of autoimmunity on pts with LR-MDS. Methods: All adult pts diagnosed with LR (RCUD, RARS, and RCMD) MDS at the Mayo Clinic between 1996 to 2000 were studied. Retrospective data collection included pts' demographics, laboratory tests, bone marrow biopsies, treatment modalities and survival information. Autoimmunity (AI) was considered present if pts had evidence of positive serological testing (such as rheumatoid factor (RF), anti-nuclear antibodies (ANA), antineutrophil cytoplasmic antibodies (ANCA)) and/or were diagnosed with autoimmune diseases (such as rheumatoid arthritis, vasculitis, autoimmune hemolytic anemia (AIHA), immune thrombocytopenia (ITP)). IRB approval was obtained in accordance with Helsinki Declaration. Chi-Square, t-test and Anova were used for comparatives between groups, and Kaplan-Meier test was applied for survival estimates using JMP 9. 0 software. Results: A total of 134 adult pts were found to have LR-MDS at the time of their diagnosis. Sixty-six percent (89) were males, 13% (17) had antecedent hematological disease (AHD), and only 7% (9) had prior radio- or chemotherapy. Thirty-nine (29%) had evidence of AI. At the time of diagnosis, pts' median Hgb was 9. 3 g/dL, white blood cells (WBC) 4. 1×109/L, and platelets 151×109/L. On comparison, there was no difference between pts with AI (group 1) to the rest of the sample (group 2) (p = 0. 12, 0. 85 and 0. 23, respectively). Bone marrow cytogenetics were abnormal in 42% (56) pts, with 44 pts have one cytological anomaly, and only 2 have four anomalies. Twenty-four pts (18%) had RCUD, 60 (44%) RARS and 50 (37%) RCMD, as defined by World Health Organization (WHO) classification (Vardiman et al, 2008). Karyotype anomalies within the three WHO classes were found in 12/19 pts (63%), 15/52 pts (29%), and in 29/42 pts (70%), respectively. Of note, among those with karyotype anomalies, the mean number of cytogenetic abnormalities was significantly different across the three categories (F=6. 89, p=. 0014), with means of 0. 5, 0. 3, and 0. 9 respectively. Seven pts (5%) progressed into acute myeloid leukemia. Seventy percent of pts (94) remained as stable disease. Of the 134 pts studied, 39 (29%) were found to have evidence of AI, with 24/48 (50%) had abnormal serological tests, and 29/134 (21%) had an autoimmune disease. When tested, positive RF was found in 7/25 (28%), ANA in 14/42 (33%), anti dsDNA in 1/11 (9%), anti SS-A/-B in 2/3 (66%), ANCA in 1/12 (8%), anti-smooth muscle in 1/2 (50%), and anti-histone in 1 pt. As per autoimmune diseases, rheumatoid arthritis was identified in 6 pts (4%), vasculitides in 9 (7%), AIHA in 4 pts (3%), Sjögren syndrome in 3 (2%), myositis in 2 (1. 4%), ITP in 2 pts (1. 4%). There was no difference in AI frequency based on WHO classification (p 0. 17) or based on cytogenetic grouping (p 0. 37). Overall survival in pts with LR-MDS was found to be lower in group 1 as compared to group 2 but did not reach statistical significance (p=0. 109), with median survival of 40 months and 81 months, respectively. Conclusion: AI is a frequent finding in pts with LR-MDS, seen in up to 29% of pts. On comparison there was no difference in hematological parameters of both groups with or without AI (CBC, cytogenetics, and WHO classification). There was no survival difference in LR-MDS pts with AI compared to pts without AI. Larger size studies are needed to confirm our findings. Disclosures: No relevant conflicts of interest to declare.

Abstract Abstract 423 Background: Cytogenetic abnormalities at diagnosis are seen in 20–70% of patients with myelodysplastic syndromes (MDS). The International Prognostic Scoring System -revised (IPSS-R) classifies these cytogenetic abnormalities into five prognostic groups: very good (del(11q), ΠY with overall survival (OS) of 61 months); good (normal, del(20q), del(5q), del(12p) with OS 49 months); intermediate (+8,7q-, i(17q),+19,+21 with OS 26 months); poor (der(3)q21/q26, −7, complex with 3 abnormalities with OS 16 months); and very poor (complex with >3 abnormalities with OS of 6 months) (Schanz J, JCO 2012, Greenberg P, Blood 2012). Monosomal karyotype (MK) is defined as the presence of two or more autosomal monosomies or a single monosomy associated with a structural abnormality. We have previously shown that MK identifies a prognostically worse subgroup of MDS patients with a complex karyotype (Patnaik M, Leukemia 2010). Objectives: Methods: The Mayo Clinic database for MDS was used to identify patients in whom bone marrow histologic and cytogenetic information was obtained at the time of diagnosis. WHO criteria were used for MDS diagnosis and leukemic transformation. Results: i) Patient characteristics: A total of 1,014 patients met the above-stipulated criteria. Median age of the cohort was 71 years (range: 18–98 years) with 684 (67%) males. 819 patients (81%) had primary MDS with 195 cases (19%) of therapy-related MDS. 759 patients (75%) are dead at a median follow-up of 18 months (range: 0–223 months) with leukemic transformation documented in 125 cases (12%). IPSS-R risk distribution was as follows: very low (n=149, 15%), good (n=261, 26%), intermediate (n=221, 22%), high (n=131, 13%), and very high (n=252, 25%). ii) IPSS-R karyotype (Entire cohort; n=1,014): The five cytogenetic groups by IPSS-R were as follows: very good (n=43, 4%), good (n=577, 57%), intermediate (n=187, 18%), poor (n=83, 8%), and very poor (n=124, 12%). We evaluated the prognostic impact of the above groups by Kaplan Meier and Cox proportional hazards analysis. OS for the five cytogenetic groups was as follows: good (36 months), very good (28 months), intermediate (20 months), poor (13 months), and very poor (6 months) (Figure 1). OS of patients with very good karyotype was significantly better than patients with very poor and poor karyotype (p<0.0001, RR 3.2 and p=0.04, RR 1.6 respectively) but similar to patients with intermediate and good karyotype (p=0.22 and 0.28 respectively). iii) IPSS-R karyotype (Primary MDS; n=819): Cytogenetic risk groups by IPSS-R were as follows: very good (n=38, 5%), good (n=512, 63%), intermediate (n=153, 19%), poor (n=46, 6%), and very poor (n=70, 9%). OS of the five groups was as follows: good (39 months), very good (23 months), intermediate (21.5 months), poor (14.5 months), and very poor (6.5 months). OS of patients with very good karyotype was significantly better than patients with very poor karyotype (p=0.0002, RR 2.5) but similar to patients with poor, intermediate and good karyotype (p=0.23, 0.26 and 0.18 respectively). iv) Monosomal karyotype: MK was identified in 153 (15%) cases of which 4 cases were intermediate, 42 poor, and 107 very poor by IPSS-R. OS of patients with MK was similar to those with very poor karyotype (6 months). In addition, OS of patients with very poor without MK was akin to patients with poor without MK (p=0.21). Furthermore, among primary MDS we identified 83 (8%) cases of MK of which 4 were intermediate, 21 were poor, and 58 very poor by IPSS-R. We confirmed that OS of patients with MK was similar to patients with very poor karyotype (6.5 months). Moreover, survival of patients with very poor without MK was similar to patients with poor without MK (p=0.51). Conclusions: In this independent analysis of 1,014 patients with MDS, IPSS-R cytogenetic risk characterization failed to discriminate between very good, good and intermediate prognostic groups. In addition, patients with very poor without MK have a similar prognosis to patients with poor without MK and should be included in the poor category whereas the presence of MK should warrant inclusion into the very poor risk category. Disclosures: No relevant conflicts of interest to declare.

Abstract Abstract 2342 Poster Board II-319 PURPOSE: Numerous clinical and biologic parameters are able to predict time to first treatment (TFT) and overall survival (OS) for patients with CLL. The utility of prognostic testing in CLL patients may vary based on age at diagnosis given the higher mortality from other causes among older individuals. The goals of the present study were to i) evaluate differences in natural history of CLL patients based on age at diagnosis, ii) compare survival to age-matched individuals in the general population, and iii) determine the age-stratified utility of prognostic testing. METHODS: All 2487 CLL/SLL patients diagnosed between January 1995 and June 2008 and cared for in the Mayo Clinic Division of Hematology were categorized by age at diagnosis (<55 years, 55-64 years, 65-74 years, or ≥75 years) and evaluated for differences in clinical characteristics, TFT, and OS using chi-square tests. IGHV gene mutation analysis, ZAP-70 status, CD38 status, and cytogenetics abnormalities by interphase FISH testing were performed as part of clinical and/or research studies using methods previously described by our group. Cox regression was used to evaluate the ability of prognostic parameters to predict clinical outcome stratified by age at diagnosis. Patient survival was compared to that of the age matched Minnesota population. RESULTS: When grouped by age, 593 patients were age <55, 713 age 55-64, 748 age 65-74, and 433 age ≥75 at diagnosis. As of last follow-up, 268, 282, 296, and 108 patients in these age groups have been treated, respectively and 112, 171, 254, and 199 patients have died. Survival decreased as the age at diagnosis increased (p<0.001). OS of CLL patients was significantly shorter than that of the age-matched general population for patients age <55 years (p<0.001), 55-64 years (p<0.001), and 65-74 years (p<0.001) at diagnosis but not those ≥75 years (p=0.136). Among Rai stage 0 patients, survival was also shorter than that of the age-matched general population for CLL patients age <55 years (p<0.001), 55-64 years (p<0.001), and 65-74 years (p<0.001) but not those ≥ age 75 at diagnosis (p=0.07). No statistically significant differences were observed in CD38 status, IGHV mutation status, ZAP-70 status or the frequency of common cytogenetic abnormalities on FISH based on age at diagnosis category. Consistent with prior reports, all of these parameters were powerful predictors of TFT and OS for the overall cohort on univariate analysis (all p<0.001 for both TFT and OS). Given the variation in TFT and OS based on age at diagnosis, we next evaluated the utility of these prognostic parameters for predicting TFT and OS in each age category after adjusting for stage. CD38, IGHV mutation, and ZAP-70 each predicted TFT independent of stage for all age groups (all p <0.05). FISH results predicted TFT independent of stage for patients age 55-64 and 65-74 however did not reach statistical significance for those age <55 (p=0.18) or ≥75 (p=0.07). The utility of these parameters for predicting OS independent of stage was less consistent and varied by age. IGHV predicted OS independent of stage for patients <age 55 (p<0.001), 55-64 (p=0.007), and 65-74 (p'0.001) but was not a significant predictor of OS among those ≥75 (p=0.15). CD38, ZAP-70, and FISH each predicted survival independent of stage for only 2 of the 4 age categories (ZAP-70 for age <55 and 55-64; FISH for age <55 and 65-74; CD38 for 55-64 and ≥75). CONCLUSIONS: Survival of CLL patients is shorter than that of the age-matched general population for individuals age <75 at diagnosis regardless of disease stage. In contrast, survival does not differ from the age-matched general population among CLL patients ≥age 75 at diagnosis. Prognostic testing using CD38, IGHV mutation, and ZAP-70 is useful for predicting TFT independent of stage for CLL patients of all ages (including those ≥age 75) but has less value for predicting OS particularly as the age at diagnosis increases. IGHV appeared to be the best predictor of OS independent of stage among all patients age <75. Unexpectedly, prognostic testing had little utility for predicting OS independent of stage among patients age ≥75. These findings have important implications regarding the use of prognostic tests in patients with CLL as well as the use of test results to select patients for clinical trials testing early treatment for asymptomatic individuals. Disclosures: Shanafelt: Cephalon: Research Funding; Celgene: Research Funding; Polyphenon Pharma : Research Funding; Hospira: Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech: Research Funding; Bayer Health Care Pharmaceuticals: Research Funding. Kay:Biogenc-Idec, Celgene, Genentech, genmab: Membership on an entity's Board of Directors or advisory committees; Genentech, Celgene, Hospira, Polyphenon Pharma, Sanofi-Aventis: Research Funding. Zent:Genentech, Bayer, Genzyme, Novartis: Research Funding.

Abstract Abstract 3790 Background: Chronic myelomonocytic leukemia (CMML) is a clonal stem cell disorder characterized by: persistent peripheral blood (PB) monocytosis (>1 × 10(9)/L), absence of BCR-ABL1 fusion, absence of rearrangement of the PDGFRA/B genes, <20% bone marrow (BM) & PB blasts, and dysplasia involving one or more myeloid cell lines. It is clinically considered to be an overlapping syndrome with myelodysplastic and myeloproliferative features. The natural history and prognostic features of CMML are not well defined with the MD Anderson prognostic score (MDAPS) and the Spanish risk stratification by cytogenetics being the two major prognostic tools currently being used in clinical practice. Methods: 227 patients with WHO defined CMML were seen at the Mayo Clinic from 1997 through 2007. All patients underwent bone marrow (BM) examination and cytogenetic evaluation at diagnosis. We evaluated the prognostic relevance of several clinical and laboratory parameters including those previously identified by the MDAPS (Blood 2002;99:840) and the Spanish cytogenetic risk stratification (Haematologica 2011;96:375). Results: Among the 227 study patients, 153 (67%) were males and median age was 71 years (range, 17–90 years). There were 192 (85%) patients with CMML-1 & the remainder had CMML-2. At a median follow-up of 15 months, 166 (73%) deaths and 33 (14.5%) leukemic transformations were documented. Median survivals were 22 months for CMML-1 and 14 months for CMML-2. In univariate analysis, significant risk factors for survival included decreased hemoglobin level, decreased platelet count and increased levels of white blood cells (WBC), absolute neutrophils (ANC), absolute monocytes (AMC), absolute lymphocytes (ALC), PB blasts, BM blasts and presence of circulating immature myeloid cells (IMC; inclusive of PB blasts). However, on multivariable analysis that included the aforementioned Spanish cytogenetic risk stratification, only increased AMC (>10 × 10(9)/L, RR 2.5, 95% CI 1.7–3.8), presence of circulating IMC (RR 2.0, 95% CI 1.4–2.7), decreased hemoglobin (<10 g/dL; RR 1.6, 99% CI 1.2–2.2), and decreased platelet count (<100 × 10(9)/L; RR 1.4, 99% CI 1.0–1.9) retained significance. Using these four independent risk factors, we prepared a new prognostic risk model that performed better than both the MDAPS and the Spanish cytogenetic risk models (Figure). The Mayo risk model was also predictive of leukemic transformation: high risk RR 4.9 (95% CI 1.9–12.8) and intermediate risk RR 2.6 (1.1–5.9). Individual parameters of independent significance for leukemic transformation included PB blast count and AMC >10 × 10(9)/L. Conclusions: Absolute monocyte count is the strongest predictor of survival in CMML. Other independent risk factors include circulating immature myeloid cells, anemia and thrombocytopenia. A risk model based on these four risk factors is effective in predicting both overall and leukemia-free survival and outperforms both the MDAPS and risk stratification by cytogenetics. Disclosures: No relevant conflicts of interest to declare.