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Abstract Introduction Multiple myeloma (MM) is characterized by a highly variable disease course, which can be traced to initiating and acquired genomic events. Whole exome analysis of matched tumor and germline DNA from 287 MM patients identified recurrently somatically mutated genes (RSMGs) (Lohr et al. - Cancer Cell 2014, Bolli et al. - Nat Commun 2014). Despite the fact that these RSMGs affect pathways that are biologically important in MM, the clinical relevance of many of these genes in the context of conventional prognostic markers remains to be elucidated. Aims The aims of this pilot study were: (1) To validate the prevalence of RSMGs in our newly diagnosed MM patient cohort; (2) To assess the correlation between RSMGs, clinical parameters and outcome; (3) To thereby identify the potential clinical usefulness of introducing RSMG mutational profiling in larger MM trial cohorts. Material and Methods CD138+ enriched MM cells and peripheral blood were obtained with informed consent from chemotherapy-naive patients, participating in 3 clinical trials: HOVON-65/GMMG-HD4, HOVON-87/NMSG-18 and Carthadex (EudraCT number 2004-000944-26, 2007-004007-34 and 2009-014922-40, respectively). Matched tumor and germline DNA were sequenced on an Ion Torrent sequencing platform (PGM, Life Technologies), using the M3 P Mutational Panel v3.0, comprising 1327 customized oligos (Life Technologies), targeted at the coding sequences of 88 MM-relevant genes, including the RSMGs. Somatic mutations were considered positive when present in >=10% of tumor reads and <=10% germline reads, with a minimal coverage of 10x and being non-synonymous, or splice donor variants. All statistical analyses were performed in SPSS version 23, using the log-rank and Mann-Whitney U-test, with the Bonferroni test to correct for multiple comparisons. Results A total of 206 DNA samples were sequenced from 103 patients (HOVON-65/GMMG-HD4 (n=16), HOVON-87/NMSG-18 (n=67), Carthadex (n=20)) with an average coverage of 574x in tumor DNA, 451x in germline DNA and an overall coverage of 98%. We collected follow-up data from 102/103 patients, with a median follow-up time of 30 months. 168 somatic mutations were detected in 44/88 genes. 82% of patients had at least 1 somatic mutation. Genes most frequently mutated were: (1) NRAS (26%), (2) KRAS (22%), (3) DIS3 (14%), (4) FAM46C (9%), (5) TP53 (7%) and (6) BRAF (6%) (Figure 1). Of note, NRAS and KRAS mutations were mutually exclusive in our cohort. Moreover, all TP53 mutations were located in its DNA binding domain. Three out of 6 BRAF mutations were predicted to cause a V600E amino acid change. We focused on these 6 RSMGs in all further analyses. Correlating mutational status with Progression Free Survival (PFS) and Overall Survival (OS) showed that TP53 mutated patients had a significantly shorter PFS compared to those with wildtype TP53 (adj. p-value=0,018; n=7 versus n=95). Comparing the mutational status of the 6 RSMGs, transplant versus non-transplant protocol, number of mutated genes in the M3 P panel, del17p and t(4;14) status, EMC92 score and ISS stage between patients with a PFS <=1 year and >1 year (n=23 versus n=79), only showed a significant correlation with TP53 mutational status (adj. p-value=0,012). TP53 mutational status remained the only significant prognostic factor when comparing patients with an OS <=1 year and >1 year (adj. p-value=0,003; n=13 versus n=89). When comparing the number of mutated genes, del17p and t(4;14) status, EMC92 score, transplant versus non-transplant protocol and ISS stage between TP53 mutated and wildtype MM, TP53 mutated patients had a significantly higher number of mutated genes in the M3 P panel (adj. p-value=0,001). Conclusions (1) With the M3 P Mutational Panel, we confirm the published prevalence of RSMGs in MM in our cohort of chemotherapy-naive patients. NRAS, KRAS, DIS3, FAM46C, TP53 and BRAF are the most frequently mutated genes. (2) TP53 mutational status is the strongest unfavorable prognostic factor in our cohort and it seems to be associated with greater mutational burden. Validation in a more extensive population is planned. (3) This warrants further investigation of the mutational status of these genes in larger clinical trial cohorts, enabling a more robust comparison with conventional prognostic markers in a multivariate analysis. Disclosures Broijl: Celgene: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees. Zweegman:Takeda: Research Funding; Janssen: Research Funding; Celgene: Research Funding. Sonneveld:Janssen: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Amgen: Honoraria, Research Funding; Karyopharm: Research Funding; SkylineDx: Membership on an entity's Board of Directors or advisory committees.

Abstract Introduction Over the last 15 years gene expression profiling (GEP) has been used to define myeloma molecular subgroups and to determine clinical prognosis. Two major molecular subgroup classifications have been used: the UAMS which determines 7 subgroups and the TC classification based on the presence of IgH translocations and expression of D group cyclins. For prognosis, although a number of different GEP signatures have been defined, the widely used GEP70 identifies 15% of patients with high risk (HR) disease who have a median PFS and OS of 1.75 and 2.83 years. An ideal classification system would identify clinically relevant subgroups with distinct etiology and biology using standardized techniques. We have examined a large group of patients characterized at multiple genetic levels to optimize the diagnostic approach of newly diagnosed patients going forward. Materials and methods Study subjects included 1349 cases enrolled in Total Therapy trials (median follow up 7.5 years). Gene expression profiling was used to determine GEP70 risk status, molecular subgroup by UAMS and TC classifications, and to devise a new and extended TC classification (TC10). Interphase FISH associated with IgH translocations and 1q+ and 17p- were used to build GEP proxies. Data from mutational analysis generated by the FoundationOne targeted sequence panel was also incorporated. Results were validated on the UK MRC MyelomaIX and Hovon65/GMMG-4 studies. Results An initial agnostic analysis of GEP data using sparse k-means clustering verified the existence of TC based groups. Six groups were identified that corresponded overwhelmingly with known TC subgroups; CCND1-t(11;14), D1-HRD, D2-HRD, MMSET, MAF/CCND2, and CCND3. Further comparisons between the molecular subgroup and TC classifier revealed that the UAMS 7 subgroups clustered strongly within one predominant TC group: CD-1 and CD-2 to t(11;14), HY to D1, LB and PR to D2, MF to t(14;16) or t(14;20), and MS to t(4;14). As the UAMS molecular subgroups are largely contained within the TC framework, we aimed to extend the TC by developing the TC10. To extend the known TC subgroups, unsupervised clustering was applied to the 3 largest subgroups [t(11;14), D1, and D2] to determine the strongest single divisor within each respective subgroup. The dominant feature within the t(11;14) cases was CD20 expression, while the D1 and D2 subgroups both split according to RRAS2. CD20 is associated with PAX5 and VPREB3 expression, and RRAS2 is associated with decreased PTP4A3 and increased TNFAIP3 and BIRC3 expression. RRAS2 activation within D1 subgroup and CD20 activation within t(11;14) cases corresponds to an increased time to response to induction therapy suggesting they constitute important biological subgroups. The TC10 combines the known etiologic subgroups of the TC with functionally relevant subdivisions to create 10 novel subgroups: t(11;14) CD20+/-, D1: RRAS2+/-, D2: RRAS2+/-, t(4;14), t(14;16), t(14;20), and t(6;14). Analysis of mutational data revealed that RRAS2 and CD20 activation within the D1, D2, and t(11;14) subgroups reduced the number of mutations in the MAPK pathway. Further mutational analysis revealed that median mutational load was highest in t(14;16) and lowest in D2: RRAS2+ subgroups. The GEP70 score identifies 15% of patients with HR disease and is specific for this purpose. In an analysis of risk assessment methods, we compared GEP detected adverse lesions [t(4;14), t(14;16), t(14;20), 17p- and 1q+] with the GEP70 and revealed that GEP70 HR identified samples have lower OS rates than cases with more than one adverse lesion (validated in external sets). GEP70 HR segregates non-uniformly across molecular subgroups as over 40% of all HR cases are found in the TC10 t(4;14), t(14;16), and t(14;20) subgroups. GEP70 HR cases also have a higher mutational load than low risk cases. Furthermore, GEP70 HR is uniquely associated with 1q+ and 17p- as cases with at least one of these adverse lesions are 4.9 times as likely to be GEP70 HR as cases with neither. Conclusion GEP profiling has a central role in simplifying and standardizing the molecular subgroup designation and risk stratifying of MM patients. The GEP70 risk score reliably identifies HR cases and outperforms FISH in risk assessment, even in validation data sets. The TC10 provides a classification system that improves upon previous methods by defining both etiological and functionally meaningful subgroups. Disclosures Stein: University of Arkansas for Medical Sciences: Employment. Davies:University of Arkansas for Medical Sciences: Employment; Celgene: Consultancy; Janssen: Consultancy; Millenium: Consultancy; Onyx: Consultancy. Heuck:University of Arkansas for Medical Sciences: Employment; Celgene: Consultancy; Janssen: Other: Advisory Board; Millenium: Other: Advisory Board; Foundation Medicine: Honoraria. Weinhold:University of Arkansas for Medical Sciences: Employment; Janssen Cilag: Other: Advisory Board. Chavan:University of Arkansas for Medical Sciences: Employment. Thanendrarajan:University of Arkansas for Medical Sciences: Employment. Epstein:University of Arkansas for Medical Sciences: Employment. Yaccoby:University of Arkansas for Medical Sciences: Employment. Zangari:University of Arkansas for Medical Sciences: Employment; Novartis: Research Funding; Onyx: Research Funding; Millennium: Research Funding. van Rhee:University of Arkansa for Medical Sciences: Employment. Kaiser:Janssen: Honoraria; Amgen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; BristolMyerSquibb: Consultancy; Chugai: Consultancy. Sonneveld:Janssen-Cilag, Celgene, Onyx, Karyopharm: Honoraria, Research Funding; novartis: Honoraria. Goldschmidt:Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees; Onyx: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Bristol-Myers Squibb: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen-Cilag: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Millenium: Honoraria, Research Funding, Speakers Bureau; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Chugai: Honoraria, Research Funding, Speakers Bureau; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau. Barlogie:University of Arkansas for Medical Sciences: Employment. Morgan:Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; MMRF: Honoraria; CancerNet: Honoraria; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; University of Arkansas for Medical Sciences: Employment; Weismann Institute: Honoraria; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees.

Abstract Introduction: Customized gene panel sequencing is an attractive approach to genomic tumor characterization in clinical care. Based on published MM exome data we developed a MM Mutation Panel (M3 P) that includes the most commonly mutated genes, actionable drug targets, genes targeted by current standard of care (SOC) therapies and which allows tracking of clonal evolution, copy number and sample purity. Methods and Material: M3 P (v3.0) covers 88 genes (1327 amplicons, 181kb). MM samples from 504 patients (pts) have been analyzed (corresponding germline in 81%) through collaborations between Mayo Clinic and Hospital-12-de-Octubre (Madrid, Spain), the DSMM and GMMG (Würzburg, Ulm, Freiburg and Heidelberg, Germany) and the HOVON trial groups (Rotterdam, The Netherlands). The investigated cohort includes 410 untreated pts (81%), which includes a high risk cohort of 72 pts with del17p, 25 paired samples with later follow up from the same cohort, and 94 relapsed patients, of which 50 were relapsed and refractory. Results: Overall coverage per mutation averaged >500x depth. We identified 945 variants (1.9 per pt) and in 83% of the pts a mutation was found. Clonal heterogeneity was assessed with mutations ranging from 3%-100% variant reads suggesting the presence of a significant number of subclones (e.g. 21% of mutations were in < 10% of reads). The mutation incidence was compared with and closely resembles the most recent MM comprehensive genomic data from the MMRF CoMMpass study: We compare here all pts sequenced by M3 P, untreated pts sequenced by M3 P and CoMMpass: KRAS (24%/23%/24%), NRAS (20%/20%/18%), DIS3 (13%/14%/10%), BRAF (9%/7%/6%), FAM46C (6%/6%/8%) and TRAF3 (6%/6%/7%). TP53 mutation incidence, however, was significantly increased in our cohort (14%/12%/4.2%), a difference explained by the inclusion of del17p (untreated) and relapsed refractory MM in panel sequenced pts, cohorts with elevated incidences of TP53 mutations (32% / 26% respectively). Potentially actionable targets include BRAF mutationsin 43 patients (9%), with druggable p.V600E in 19 or 5%, 8 pts (2%) with FGFR3 (p.R248C and p.G375C one patient each), p.R132 mutation in 4 out of 5 IDH1 (1%) and p.R172K IDH2 mutation in 1 of 3 (1%) pts. Mutations in the MAPK pathway (NRAS, KRAS, BRAF) were detected in 59% of pts, ranging from 36% untreated MM to 72% in refractory MM. Similarly, the CRBN/CUL4B/IKZF1/IKZF3/IRF4 pathway, important for IMiD function, harbored a significant enrichment of mutations in advanced disease (6% untreated vs 17% relapsed), including CRBN mutations (0.5% vs 7%). Nine of 17 IRF4 mutations were located at the p.K123R hotspot, with minor difference between early or late disease (1% vs 3%). Notably, in 8 of 9 pts with CRBN mutation and clinical information, all were unresponsive to IMiD therapy, supporting association of these mutations with resistance to IMiDs. Conversely, M3 P genes related to other SOC therapies, including NR3C1 (targeted by steroids) and 5 proteasome subunit genes (proteasome inhibitors), were rarely mutated across the cohorts not exceeding 1% mutation incidence for each gene. Significant differences in DIS3 and FAM46C mutation incidences were observed across cohorts: DIS3 mutations are more common in untreated pts with a 1.7 fold increased predominance (14% untreated and 8% treated). FAM46C has an expected incidence of 8% but was rarely mutated in untreated del17p high risk disease with only one of 100 patients harboring both mutations. The significance of this finding needs to be determined but implies a possible overlap in function. Finally we assessed impact on survival of the mutation variants identified in 142 untreated Mayo patients and found STAT3 mutations negatively impacting PFS (p=0.034) and OS (p=0.001). This gene is rarely mutated in MM (2% of the total cohort) thus the sample size was small and this finding needs further validation. Conclusion: We here describe 504 MM patients sequenced using the M3 P gene panel, which identified mutations in >80% of investigated patients, overlaps well with published whole exome sequence data and provides clinically relevant information. New findings were the high frequency of minor clones, the relative lack of overlap of del17 and FAM46C mutation, a higher frequency of DIS3 mutation at diagnosis compared to relapse, the prognostic significance of STAT3 mutation and the frequent presence of CRBN pathway mutation in drug resistant relapsed patients. Disclosures Sonneveld: Janssen-Cilag, Celgene, Onyx, Karyopharm: Honoraria, Research Funding; novartis: Honoraria. Mai:Janssen-Cilag: Other: Travel Grant; Onyx: Other: Travel Grant; Mundipharma: Other: Travel Grant; Celgene: Other: Travel Grant. Goldschmidt:Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Onyx: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Millenium: Honoraria, Research Funding, Speakers Bureau; Bristol-Myers Squibb: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Chugai: Honoraria, Research Funding, Speakers Bureau; Janssen-Cilag: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau. Knop:Celgene Corporation: Consultancy. Kull:Bristol-Myers Squibb: Membership on an entity's Board of Directors or advisory committees. Martinez-Lopez:Novartis: Honoraria, Research Funding; Bristol-Meyer Squibb: Honoraria; Celgene: Honoraria; Janssen: Honoraria. Einsele:Celgene: Consultancy, Honoraria, Research Funding, Speakers Bureau; Janssen: Consultancy, Honoraria, Research Funding, Speakers Bureau; Novartis: Consultancy, Honoraria, Speakers Bureau; Amgen/Onyx: Consultancy, Honoraria, Speakers Bureau. Raab:Novartis: Research Funding. Stewart:Oncospire Inc.: Equity Ownership; Celgene: Consultancy; Novartis: Consultancy; BMS: Membership on an entity's Board of Directors or advisory committees.

Abstract Introduction: There are few effective treatment options available for patients (pts) with myelofibrosis (MF). Pts with thrombocytopenia, a risk factor for shorter overall survival, have poorer prognosis (Gangat, J Clin Oncol 2010). Pacritinib is a kinase inhibitor with specificity for JAK2, FLT3, IRAK1, and CFSR1 and has demonstrated minimal myelosuppression in clinical trials (Hart, Leukemia 2011; Komrokji, Blood 2015; Mesa, ASCO 2015). In the phase III open-label PERSIST-1 trial, a significantly greater proportion of pts treated with pacritinib achieved spleen volume reductions (SVR) ≥35% vs BAT (ITT: 19.1% vs 4.7%, p=0.0003; pts evaluable at baseline and Week 24: 25.0% vs 5.9%, p=0.0001; Mesa, ASCO 2015). This analysis examines pt responses across subgroups. Methods: Pts naive to treatment with JAK inhibitors were randomized 2:1 to receive oral pacritinib 400 mg once daily or BAT. Stratification factors included DIPSS risk status and baseline platelet count. Pts were eligible who had DIPSS Intermediate (Int)-1, Int-2, or High risk disease; absolute neutrophil count >500/µL; palpable splenomegaly ≥5 cm; and baseline Total Symptom Score (TSS) ≥13 using the Modified MPN Symptom Assessment Form Total Symptom Score (MPN-SAF TSS and TSS 2.0). There was no restriction on baseline platelets or hemoglobin (Hgb) levels. The primary endpoint was the proportion of pts achieving SVR ≥35% at Week 24 by centrally-reviewed MRI or CT and the secondary endpoint was the proportion of pts achieving ≥50% reduction in TSS from baseline at Week 24 using 6 symptoms from the MPN-SAF TSS. Pt responses were analyzed by baseline risk factors for MF including platelet counts (<50,000/µL vs ≥ 50,000/µL and <100,000/µL vs ≥100,000/µL), sex, age (≥65 y vs <65 y), JAK2V617F mutation status (positive vs negative), baseline MF diagnosis (primary MF [PMF] vs secondary MF), reticulin and collagen fibrosis staging (> 1 vs ≤1), TSS (≥20 vs <20), white blood cell count (>25×109/L vs ≤25×109/L), peripheral blasts (≥5% vs <5%), Hgb (<10 g/dL vs ≥10 g/dL), transfusion dependency by Gale criteria (Y vs N), time from diagnosis (<12 mos vs ≥12 mos), ECOG PS (2-3 vs 0-1), and bone pain (>3 vs ≤3). In multivariate logistic regressions, the odds of SVR ≥35% and TSS reduction ≥50% at Week 24 were modeled as a function of prognostic factors for MF and adjusted for treatment (pacritinib vs BAT). Results for the 6 symptoms common to both TSS versions are reported. Results: 327 pts were enrolled and randomized (pacritinib: 220, BAT: 107). Overall, 62% of pts had PMF; 32% had baseline platelets <100,000/µL and 16% had <50,000/µL; 75% were positive for JAK2V617F. After a median follow-up of 8.4 months, treatment with pacritinib resulted in consistent rates of SVR across subgroups (Figure 1). When comparing vs BAT, the greatest differences in SVR ≥35% rates between treatment arms were observed in pts with baseline platelets <50,000/μL (+22.9% vs BAT), JAK2V617F-negative pts (+23.0% vs BAT) and those aged <65 y (+21.2% vs BAT). Improvements in TSS (TSS and TSS 2.0 reduction ≥50%) were also consistent for pts receiving pacritinib (Figure 2). By multivariate analysis, SVR ≥35% was significantly correlated only with ECOG PS ≥2 (odds ratio [OR]=2.97, p=0.030) and TSS reduction ≥50% was significantly correlated only with bone pain >3 (OR=0.35, p=0.004). Conclusions: Treatment with pacritinib resulted in consistent rates of SVR ≥35% and TSS reduction ≥50% irrespective of baseline characteristics. Comparisons vs BAT were favorable for all patient subpopulations examined for both endpoints. These results support the use of pacritinib across all intermediate- or high risk MF pt subgroups analyzed. Figure 1. Proportion of Patients Receiving PAC who Achieved ≥35% SVR from baseline to Week 24 (95% CI) Figure 1. Proportion of Patients Receiving PAC who Achieved ≥35% SVR from baseline to Week 24 (95% CI) Figure 2. Proportion of Patients Receiving PAC who Achieved ≥50% TSS reduction (6 common symptoms in MPN-SAF TSS and MPN-SAF TSS 2.0) from baseline to Week 24 (95% CI) Figure 2. Proportion of Patients Receiving PAC who Achieved ≥50% TSS reduction (6 common symptoms in MPN-SAF TSS and MPN-SAF TSS 2.0) from baseline to Week 24 (95% CI) Disclosures Vannucchi: Shire: Speakers Bureau; Novartis Pharmaceuticals Corporation: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Baxalta: Membership on an entity's Board of Directors or advisory committees. Off Label Use: This abstract discusses off-label use of pacritinib. Mesa:Gilead: Research Funding; NS Pharma: Research Funding; Incyte Corporation: Research Funding; Genentech: Research Funding; Novartis Pharmaceuticals Corporation: Consultancy; Promedior: Research Funding; Pfizer: Research Funding; CTI Biopharma: Research Funding. Cervantes:Novartis: Consultancy, Speakers Bureau; Sanofi-Aventis: Consultancy; CTI-Baxter: Consultancy, Speakers Bureau. Prasad:BIOGEN IDEC: Consultancy, Membership on an entity's Board of Directors or advisory committees; BMS: Speakers Bureau. Elinder:Celgene: Consultancy. Recher:Sunesis: Consultancy, Membership on an entity's Board of Directors or advisory committees; Amgen: Research Funding; Chugai: Research Funding; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. te Boekhorst:CTI Biopharma: Consultancy; Novartis: Consultancy. Somervaille:Novartis Pharmaceuticals Corporation: Consultancy, Membership on an entity's Board of Directors or advisory committees. Dean:CTI Biopharma: Employment, Equity Ownership. Harrison:Shire: Speakers Bureau; Gilead: Honoraria; CTI Biopharma: Consultancy, Honoraria, Speakers Bureau; Sanofi: Honoraria, Speakers Bureau; Novartis: Honoraria, Research Funding, Speakers Bureau.

Abstract Abstract 1876 Poster Board I-901 Background: Multiple Myeloma (MM) remains incurable in spite of new effective agents and combination regimens. SRC family kinases (SFK) are potential targets for therapy in MM: Hck, Fyn and Lyn are implicated in IL6-induced proliferation. Dasatinib is a potent inhibitor of not only BCR-ABL, but also SFK, c-KIT, PDGFRb, and EPHA. In myeloma and endothelial cells (ECs) isolated from MM patients (pts), dasatinib blocked proliferation, survival, adhesion, migration, and angiogenic potential, through a combined targeting of PDGFRβ as well as VEGF-triggered phosphorylation of SRC. Lenalidomide has clinical efficacy in the treatment of multiple myeloma (MM) as a single agent and in combination with dexamethasone. The combination of dasatinib, lenalidomide and dexamethasone exhibits synergistic inhibition of MMIS cells. Methods: The primary objective of this Phase I, multicenter, open-label, non-randomized study was to determine the maximum tolerated dose (MTD) of the combination of dasatinib, with lenalidomide and dexamethasone in pts with relapsed or refractory (RR) MM. Secondary objectives were to assess the tolerability of the combination, to establish the dose for future clinical investigations, and to assess the efficacy by International Uniform Response and EBMT Criteria. Pts ≥18 years with confirmed RR MM, measurable disease (at least 1 g/dL for IgG or 0.5 g/dL for IgA in serum or urinary excretion of 200 mg monoclonal light chain/24 hours), and at least one prior treatment were enrolled sequentially into increasing dose cohorts (using a 3+3 design). Pts received oral dasatinib daily on a continuous schedule, oral lenalidomide daily for 21 days, and oral dexamethasone 40 mg/day (Days 1, 8, 15, and 22). Cycles were repeated every 28 days. Dose-limiting toxicities (DLTs) were assessed in the first cycle. If there was no DLT, dose escalation continued to MTD, followed by an expansion phase of the established dose. Results: Enrollment is ongoing. 16 pts (6 M, 10 F; median age 70.5 years, range 51–80) were treated in cohorts 1, 2, 3 and 4; MTD has not been established (as by July 2009). The median number of prior lines of therapy was 3 (range 1–6). Seven pts had prior autologous stem cell transplantation; 8 pts had prior thalidomide, 4 prior lenalidomide and 3 pts both. Baseline β2 microglobulin levels of >3.5mg/L were reported in 4 pts. The most common (310%) treatment related adverse events (AEs) diarrhea 6 (38%); nausea 4 (25%); constipation 2 (13%); stomatitis 2 (13%); asthenia 3 (19%); weight decrease 5 (31%); dyspnea 2 (13%); rash 2 (13%); vertigo 2 (13%); insomnia 2 (13%). The most common grade 3 / 4 hematologic AEs included neutropenia 6 (38%), anemia 4 (25%) and thrombocytopenia 3 (19%). Two DLTs were identified in cohorts 1 and 4: 1 pt had 2 point decline in ECOG Performance Status and other pt had a drug interruption > 15 days due to nausea and vomiting, respectively. Six out of 16 pts discontinued treatment: 1 due to death in first cycle (D19); 3 for AEs (2 study drug related and 1 unrelated), 1 withdrawal of consent, 1 following maximal clinical benefit (minor response) after 12+ cycles. As of July 2009, 10 pts remain on treatment, with a median duration of treatment of 4.2 months (range 0.6–12). Responses were observed in 13 pts: 8 partial responses (PR), and 5 minor responses (MR). 1 pt had stable disease (SD) and 2 pts were not evaluable (1 pts died before completion of cycle 1 and other pt was too early for assessment). Conclusion: Dasatinib in combination with lenalidomide and dexamethasone is well tolerated and preliminary activity has been observed. Disclosures: Facon: Celgene: Membership on an entity's Board of Directors or advisory committees; Janssen Cilag: Membership on an entity's Board of Directors or advisory committees; BMS: Membership on an entity's Board of Directors or advisory committees. Stewart:Takeda-Millenium, Celgene, Novartis, Amgen: Consultancy; Takeda, Millenium: Research Funding; Genzyme, Celgene, Millenium, Proteolix: Honoraria. Garzon:BMS: Employment. Bleickardt:BMS: Employment. Gialelis:BMS: Employment. Tuozzoli:BMS: Employment. Derreumaux:BMS: Employment. Sonneveld:Janssen-Cilag: Honoraria.

Abstract Abstract 2878 Poster Board II-854 Background: Significant advances have been made in the treatment of myeloma with the introduction of thalidomide, its analogue, lenalidomide, and the proteasome inhibitor bortezomib. While these new drugs have improved the outcome of patients with myeloma, the disease still remains incurable. Effectiveness of upcoming new therapies will need to be assessed in the context of anticipated outcome with the currently available therapies. However, given the rapid pace of development over the past decade, outcome of patients who have relapsed on the new therapies remain unclear. Methods: In order to further study this group of patients, we undertook a study of patients who have relapsed on or are refractory to one of the IMiDs (thalidomide or lenalidomide) as well as bortezomib. A total of 300 cases from 8 sites in the US, 5 sites in Europe and one site in Asia were identified for this study. Enrolled patients had relapsed and refractory multiple myeloma, per the EBMT or IMWG response criteria, after at least 2 prior treatments. Patients were refractory to bortezomib, defined as having no response on a prior bortezomib-containing regimen or experiencing disease progression within 60 days of a bortezomib-containing regimen. Patients also should have relapsed, refractory, intolerant, and/or ineligible in the opinion of the investigator, to other therapies, including an IMiD (thalidomide or lenalidomide). Clinical and laboratory data pertaining to the time of diagnosis and from the time of individual relapses were obtained from the clinical records. The date patients satisfied the above entry criteria was defined as time zero. Results: The current analysis includes the first 119 patients with complete data available. The median age at initial diagnosis was 59 years (range, 31-86 yr); 71% were males. The ISS stage distribution at diagnosis was 33%, 39% and 28% for stages 1, 2, and 3 respectively. 19 patients (37%) had high risk disease by FISH [t(4;14), t(14;16), del17p] or by cytogenetics [del 13, hypodiploidy]. The median time from diagnosis to time zero was 3.8 yrs (range 0.2-18.7 yr) and the median reported lines of therapy before time zero was 2. 74% patients had at least 1 autologous stem cell transplant prior to becoming eligible for the study. Following time zero, 77 (65%) pts had a treatment recorded, including an autologous SCT in 21 (18%), with the treatment regimen starting at a median of 1 month after time zero. A variety of treatment regimens were utilized beyond time zero (median=1; range 0-7). Thirty-two (27%) patients had a response any time following time zero, and only 8 had a subsequent response. Response to the first treatment, or supportive care for patients not treated, recorded following time zero included minor response or stable disease (n=14; 12%), PR (n=17, 14%), and VGPR or better (n=6, 5%). Patients treated with SCT had a higher rate of PR or better compared to patients receiving other treatments (85%; 17/20 vs. 26%; 15/57). In a multivariate analysis, the only significant predictor of a PR or better after time zero was younger age (<60 yrs). The median overall survival (OS) and event free survival (EFS) were 6 mos (95% CI, 4-7 mos) and 1 month (95% CI,1-2 mos) respectively. In a multivariate analysis normal creatinine predicted for a better overall survival and having an IgG M protein type predicted for better EFS. A complete analysis from all 300 patients will be presented at the meeting. Conclusions: This study confirms the poor outcome of patients once they become relapsed and refractory to agents that have become the mainstay of myeloma therapy. The findings highlight the incurable nature of the disease and urgent need to develop newer effective therapeutic agents for this group of patients, who currently do not have effective treatment options. Disclosures: Kumar: CELGENE: Research Funding; MILLENNIUM: Research Funding; BAYER: Research Funding; GENZYME: Research Funding; NOVARTIS: Research Funding. Jagannath:Merck: Membership on an entity's Board of Directors or advisory committees; Millennium: Membership on an entity's Board of Directors or advisory committees. Laubach:Novartis: . Palumbo:Ortho Biotech, Janssen-Cilag: Honoraria; Celgene: Honoraria, Speakers Bureau. Richardson:Millennium Pharmaceuticals, Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Johnson and Johnson: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Novartis: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Keryx: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; BMS: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. San Miguel:Millennium: Membership on an entity's Board of Directors or advisory committees; Janssen-Cilag: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees. Siegel:Celgene: Speakers Bureau; Millennium: Speakers Bureau. Sonneveld:Janssen-Cilag: Honoraria. Durie:Celgene: Membership on an entity's Board of Directors or advisory committees; Millennium: Membership on an entity's Board of Directors or advisory committees.

Abstract We have taken a genetic strategy to define the mechanisms underlying the increased risk of VTE in myeloma patient treated with thalidomide using clinical trial data derived from the MRC, ECOG, Little Rock and HOVON trial groups. Baseline VTE rates in the MRC IX study, (CTD vs CVAD; n=748 no prophylactic anticoagulation), were 14%. Rates in both arms were equal but in the thalidomide arm, thrombotic events were all DVT’s or PE’s, whereas in the CVAD arm they split equally between line related and VTE’s. In the other comparison (CTD vs MP; n=542), the VTE rate was 17%, all in the thalidomide arm. Rates were similar or higher (30%) in the other trials depending on the intensity of treatment used. We carried out a nested case control on DNA from MRC IX on 90 VTE (45 thalidomide, 45 non-thalidomide related), matched to 180 controls. SNPlex analysis for 60 SNPs in the coagulation cascade, DNA repair, thalidomide, metabolism and myeloma specific pathways, identified 7 genes which affected risk (NBS1, MTHFR, Ku80, Cyp3A5, LGAL52 and IL12B). This suggests three major pathways contribute to the risk of thalidomide related VTE, metabolism of thalidomide, tumour responsiveness and some pro-thrombotic factors. These factors differ from non-thalidomide related risk where a strong pro-inflammatory response is most relevant. We tested this hypothesis further using an expanded panel of 3,404 SNPs (BOAC panel), using the Megalle system. Statistical analysis of this data defined the top 20 thalidomide and non-thalidomide associated SNPs, which were consistent with the initial hypothesis, the results of which exclude variation in the coagulation cascade as being a significant risk factor. We explored this hypothesis further using pathway-based analysis focussing on the MTHFR, DNA repair and WNT pathways on data from the ECOG, HOVON and Little Rock data sets. The biological relevance of the SNPs and genes identified was validated by correlating the level of expression using the Affymetrix U133 CHIP with genetic variation at the DNA level. To verify the relevance of DNA repair variability to tumour response further, we correlated gene expression profiling with response and again Ku80 was identified as one of a cluster of genes defining increased risk. The data suggests that the risk of thalidomide related VTE relates to rapid tumour lysis combined with a prothrombotic tendency, whereas in line related thrombosis, risk is dependent upon a strong proinflammatory response. We are building this genetic data into a clinical risk model in order to allow us to develop a rationale for intervention strategies.

Abstract Purpose: Deep vein thrombosis (DVT) is increasingly recognized as a major complication of thalidomide (T; Thal) and lenalidomide (R; Rev) based therapy for multiple myeloma. Estimated incidence varies widely in the literature. There is no consensus on specific risk factors, indications for thromboprophylaxis or the agent of choice for DVT prophylaxis. The purpose of this study was to develop a consensus among members of the IMWG. Patients and Methods: A survey was electronically mailed to 67 IMWG members on July 21, 2006 and consisted of 24 multiple-choice questions. Results: Twenty-three IMWG members (34%) sent in their responses by the cut-off date. All (100%) felt that DVT was an important question, but most (95%) did not avoid Thal/Rev based therapy because of the DVT risk. Overall results are summarized in the Table below. A majority of physicians felt that concomitant therapy with high dose dexamethasone (90% of physicians), alkylators (55%), doxorubicin/liposomal doxorubicin (90%), and erythropoietin (75%) increase the risk of DVT associated with Thal or Rev based therapy. Aspirin (81 mg or 325 mg per day) was the preferred choice of prophylaxis when necessary. However, 65% of respondents preferred warfarin to a therapeutic INR or LMW heparin if either doxorubicin or liposomal doxorubicin was added to the regimens. Most (95–100%) felt that DVT prophylaxis was not indicated for: VAD, MP, bortezomib +/− dexamethasone regimens. Seventy-five percent felt it to be safe to resume therapy with Thal/Rev after therapeutic anticoagulation. Most (95%) believed randomized trials were needed. Conclusion: DVT is recognized as a major clinical problem associated with Thal/Rev containing regimens. Most respondents felt that the DVT risk did not warrant any prophylaxis when either Thal or Rev were used as single agents. Aspirin was the preferred form of DVT prophylaxis for most Thal/Rev containing regimens, except when doxorubicin/liposomal doxorubicin or melphalan were added. Additional responses will be analyzed both electronically and by conference call prior to the meeting. Therapy Estimated incidence of DVT (% respondents) Choice of thromboprophylaxis (% respondents) Single agent thal <5% (61%) None (65%) Single agent Rev <5% (80%) None (65%) Thal-Dex 10–20% (52%) Aspirin (60%) Rev-Dex 10–20% (48%) Aspirin (60%) MPT 10–20% (65%) Aspirin (40%) R-MP 5–10% (57%) Aspirin (70%)

Abstract Background: Isolated brain parenchyma relapse as initial site of relapse is a rare complication of NHL and carries a poor prognosis. Few large series focus on treatment characteristics and outcomes of isolated brain parenchyma relapse of NHL. Methods: The IPCG conducted a retrospective review of patient and treatment characteristics and outcomes of this complication. Following initial diagnosis and treatment of NHL (1980–2004), cases with brain parenchyma relapse as initial relapse site, with no evidence of lymphoma elsewhere in the body at the time of brain relapse, were eligible. Cases with brain, spine or leptomeningeal involvement at NHL diagnosis were not eligible. Results: 113 cases were assembled from 13 investigators in 8 countries. Preliminary data summaries are: 94 (83%) cases had diffuse large B-cell NHL, 5 (4%) follicular lymphoma, 3 (3%) Burkitt’s lymphoma, other NHL subtypes (11) . Median age at NHL diagnosis was 61yrs (16–85 yrs). 55% were male. Median ECOG at NHL diagnosis was 1. Median time from NHL diagnosis to isolated brain relapse was 1.8 yrs (3 months–15.9 yrs). 76 (67%) relapsed in brain less than 3 yrs after NHL diagnosis. Symptoms at brain relapse included mental status changes in 37%, gait/balance disturbance (27%), motor/sensory symptoms (23%). Median ECOG at brain relapse was 2. Parenchyma relapse was documented by brain imaging plus biopsy in 54 (48%), or imaging without biopsy in 58 (52%); not reported (1). 53 (48%) cases had one brain lesion; 56 (50%) had two or more lesions; not reported (4). Site of relapse was cerebral hemispheres in 53 (48%) cases, deep brain structures (brain stem/cerebellum) in 30 (27%), cerebral hemispheres and deep brain structures in 23 (21%); not reported (7). At brain relapse, CSF was positive in 11 (10%) cases, negative in 56 (50%); not reported (46[40%]). Treatment for brain relapse was chemotherapy alone in 52 (46%) cases, WBRT alone in 34 (30%), chemotherapy followed by RT in 26 (23%), and brain surgery alone (1). 78 (69%) cases are deceased. Median survival from brain parenchyma relapse to death was 1.6 yrs (95% CI: 11 months–2.6 yrs). Effect of treatment type at brain relapse on survival, will be reported. Brain lymphoma was the cause of death in 49 (63%) cases; CNS toxicity was the cause in 6 (8%) cases. Conclusion: Though a rare relapse site, prospective studies are needed to improve understanding and outcomes of isolated brain parenchyma relapse of NHL.

Abstract Abstract 1731 Background: Symptom burden in primary, post-ET and post-PV myelofibrosis (MF) is frequently severe and correlates with a poor prognosis. However, symptom manifestations are heterogeneous with variable presence of specific symptoms, splenomegaly and cytopenias. We sought to identify the spectrum and features of MF symptomatic phenotypes by cluster analysis of prospectively gathered information on MF symptoms and disease features. Methods: Data was collected among an international cohort of subjects with MF. Data included demographics, disease features and completion of the Brief Fatigue Inventory (BFI) and Myeloproliferative Neoplasm Symptom Assessment Form Total Symptom Score (MPN-SAF TSS) (Blood 2011; 118:401–408). Surveyed symptoms addressed key disease features on a 0 (absent) to 10 (worst-imaginable) scale. Cluster development was based on consideration of r-squared in hierarchical clustering using Ward's linkage. Final cluster assignment was based on the nonhierarchical k-means method. Comparisons between symptom clusters were based on ANOVA and chi-squared tests. Results: Subject Demographic and Disease Characteristics: Data from 329 prospectively enrolled persons with MF was collected (Chinese 102, French 54, German 19, Italian 22, Dutch 45, English 51, Spanish 29, Swedish 7) including 223 PMF, 67 post-ET MF and 39 post-PV MF patients. Participants were of typical age (mean 59) and gender (47% F). Among all participants, four natural symptom clusters were identified (Figure 1). Among clusters, disease features including leukopenia, thrombocytopenia, and enlarged spleen varied significantly between clusters (P<0.05). Cluster 1: The “Fatigue Dominant with Few Lab Abnormalities” Profile (n=150 (46%; 69% PMF, 20% post-ET MF, 11% post-PV MF)). Cluster 1, the largest, is characterized by fatigue-dominant complaints in the setting of the lowest overall MPN-SAF TSS and highest proportion of males (59%). Individuals among this group have the lowest prevalence of laboratory abnormalities (65% total; anemia, 67%; thrombocytopenia, 20%) or clinical deficiencies including enlarged spleen (average 6.0 cm below costal margin), prior thrombosis (9%), prior hemorrhage (5%) or prior RBC-transfusions (20.4%). Interestingly, individuals in this group are most likely to have had prior splenectomy (5.8%). Cluster 2: The “Cognitive Complaints with Enlarged Spleen” Cluster (n=105 (32%; 65% PMF, 20% post-ET MF, 15% post-PV MF)). Cluster 2 is the 2nd largest cluster. Subjects have relatively few abnormal lab values (67% vs 65%–77%) but have high severity of fatigue, sexual difficulties, insomnia, inactivity and reduced QOL. These individuals have the largest spleen size (8.7cm below costal margin). Cluster 3: The “Nighttime and Cognitive Complaints” Group (n=53 (16%; 64% PMF, 25% post-ET MF, 11% post-PV MF)). Cluster 3 is the smallest cluster. Subjects have many cognitive and nighttime-related complaints including sexual difficulties, night sweats, insomnia, and concentration problems. Subjects with post-ET MF are predominant. This cluster also has the 2ndsmallest spleen size (7 cm) or history of prior thrombosis (9.6%), hemorrhage (7.8%) or requirement for transfusions (21.2%). Cluster 4: The “Severe Fatigue with Few End-organ Complaints” Cluster (n=21 (6%; 81% PMF, 14% post-ET MF, 5% post-PV MF)). Cluster 4 is the most symptomatic cohort with the highest proportion of subjects with PM. There is a lower frequency of end-organ complaints including abdominal pain, cough, and headaches. Symptoms including sexual difficulties, sad mood and insomnia are predominant. No subjects had prior splenectomy. Subjects also have the highest prevalence of prior thrombosis (29%), hemorrhage (14%), and transfusions (43%). Additionally, this cohort has the largest prevalence of lab abnormalities (77%) with thrombocytopenia (71%), leukopenia (41%) and anemia (41%). Conclusion: This analysis will allow us to examine a new framework for evaluating persons with MF using symptom profiles and is the 1st cluster evaluation of MF. Lab and physical findings contrast significantly between symptom clusters indicating these phenotypic symptoms likely result from etiological factors present in specific disease phenotypes. Future studies should evaluate whether there is a correlation between cluster profiles, prognosis and genotype. Disclosures: Kiladjian: Celgene: Research Funding; Novartis: Honoraria, Research Funding; Shire: Honoraria. Roy:Novartis, BMS: Speakers Bureau. Harrison:Novartis: Honoraria, Research Funding, Speakers Bureau; YM Bioscience: Consultancy, Honoraria; Sanofi Aventis: Honoraria; Shire: Honoraria, Research Funding. Vannucchi:Novartis: Membership on an entity's Board of Directors or advisory committees. Passamonti:Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees. Mesa:Incyte: Research Funding; Lilly: Research Funding; Sanofi: Research Funding; NS Pharma: Research Funding; YM Bioscience: Research Funding.