Citations

Abstract Introduction: We employed a customized Multiple Myeloma (MM) specific Mutation-Panel (M3 P) to screen a homogenous cohort of refractory MM (rMM) patients in a timely and cost-effective manner. rMM was defined as progressive disease (PD) during therapy or within 60 days after discontinuation of therapy. The M3 P provides a practical alternative to whole genome/exome sequencing approaches and includes 88 genes selected for being either actionable targets, potentially related to drug response or part of known key pathways in MM biology. Patients and Methods: Tumor and germline samples of 50 rMM patients were screened using M3 P. Patients received a median of five lines of treatment at the time of tumor sampling (range 2-15 lines). All patients received at least one immunomodulatory agent (IMiD) and proteasome inhibitor (PI), and 88%, 76% and 66% were refractory to either an IMiD, PI or both. All patients had received lenalidomide and bortezomib, 48% and 34% were additionally exposed to pomalidomide and thalidomide and 18% to carfilzomib at any time prior to sampling. The majority of patients had a progressive and refractory disease immediately prior to sampling (82% and 78%), with 43% of them being IMiD-refractory and 46% being PI-refractory in the most recent line of therapy. Cytogenetic data at time of sampling were available from 78% of patients. Adverse cytogenetics were detectable in 82% of patients with gain 1q21 > 2 copies (62%), deletion 17p (33%), t(4;14) (13%) and t(14;16) (8%) being the most common. Results: An average sequencing depth of 750x was obtained across the samples. Our screening revealed an increased prevalence of mutations in the MAPK pathway (72%), including 34% of KRAS, 26% of NRAS, 18% of BRAF (with one patient carrying two BRAF mutations and 8% in actionable p.V600E). Additionally, two mutations (4%) were found in RASA2, a RAS inhibitor. Other potentially actionable mutations were seen in p.R132H IDH1 and p.R248C FGFR3 (2% each). Most prominently, the CRBN pathway was found mutated in 22% of cases, including CRBN (12%, one case with concomitant CUL4B mutations), CUL4B (4%), IRF4 (4%) and IKZF1 (2%). In CRBN we found four cases with mutations leading to a truncated protein (frameshift, nonsense and splicing) and two cases with missense mutations located within the thalidomide-binding domain, suggesting a causal effect on IMiD resistance. All CRBN mutated patients and 91% of the CRBN pathway mutated patients were at least once unresponsive to IMiD based treatment. In one patient with IRF4 mutation sensitivity to IMiDs remained unknown. A majority of patients were also resistant to PI treatment (76%), however mutations in proteasome subunits (PSMD1 and PSMB8) and XBP1 wererare (4%), but only a limited number of this gene family were represented in our panel. Other recurrently mutated genes were TP53 (26%), FAM46C (12%), ATM (10%) and TRAF3 (8%). Notably, DIS3 mutations were identified in only 6% of cases. As previously reported, TP53 mutations were associated with deletion 17p (8/13 cases, 62%). A correlation between the absolute number of mutations and previous lines of treatment was not observed (r=0.05, p=0.73). Conclusion: Targeted sequencing on a homogenous cohort of heavy pretreated rMM patients gives key insights in the landscape of the rMM genome, uncovering an increasing frequency of MAPK, TP53 and CRBN mutations. Importantly, this is the first study showing recurrent mutations in CRBN in patients unresponsive to IMiD treatment, supporting a potential association with resistance to IMiD based therapies. Disclosures Mai: Onyx: Other: Travel Grant; Janssen-Cilag: Other: Travel Grant; Celgene: Other: Travel Grant; Mundipharma: Other: Travel Grant. Merz:Janssen: Other: Travel grants; Celgene: Other: Travel grants. Hillengass:Takeda: Honoraria, Other: Travel support; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding; Janssen-Cilag: Honoraria, Other: Travel support; Celgene: Honoraria, Other: Travel support. Goldschmidt:Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Janssen-Cilag: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Millennium: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Onyx: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Chugai: Research Funding, Speakers Bureau. Stewart:Oncospire Genomics: Research Funding.

Abstract Background: Over the last two decades several phenotypic, molecular, and chromosomal markers have been identified that are significantly associated with the prognosis of CLL patients. Therefore, clinicians managing CLL patients would benefit from a simplified prognostic index. Methods: We analyzed prospectively collected data from 337 Binet A CLL patients enrolled in Italian the O-CLL1-GISL protocol with the aim of developing scores capable of predicting treatment free survival (TFS). Factors independently associated with TFS were included in the prognostic indexes. To account for differences in the magnitude of the association between the individual independent factors and TFS, we assigned a weighted risk score to each factor based on ranges of their corresponding hazard ratios (HRs) (i.e., 1 point for HR 1.1-1.9; 2 points for HR 2.0-2.9, etc.). The total risk score was then calculated by the sum of the ratings of each factor on individual basis. Risk groups were identified combining risk categories with a non-statistically different TFS. Results: We developed two scores based on weighted multivariable models: the first included clinical and laboratory parameters [clinical score (c-score)], while the second was based on biological markers [biological score (b-score)] (Table 1). The c-score allowed to predict the TFS of patients through the combination of Rai stage, b2-microglobulin and absolute lymphocyte count (ALC), while the b-score predicted TFS by IGHV mutational status and CD38 expression. The c-score showed a C-statistic of 0.72, while the b-score was 0.67, although cases stratified according to the b-score showed a more specific mRNA/microRNA profile. When the two scores were forced in a multivariate analysis, both showed an independent predictive value on TFS with a similar HR, demonstrating their complementarity. Thus, we attempted to integrate the two scores performing a further multivariate analysis in which all parameters, significantly associated with TFS at univariate analysis, were tested (Table 1). ALC, Rai stage, b2-microglobulin together with IGHV mutational status, resulted independently associated with TFS. We constructed a weighted score [comprehensive score (co-score)], including all the above 4 variables, which allowed the identification of 3 different risk groups with significantly different TFS (Figure 1). The C-statistic of the g-score was 0.75, showing a better concordance than the other two scores. Moreover, its validity was externally validated in a series of 297 newly diagnosed Binet A CLL patients from the Mayo Clinic, USA. Conclusions: Using this multistep process and external validation, we developed a score with high discriminatory power and predictive significance on the individual patient level. Table 1. Univariate and multivariate Cox proportional Hazards Models Variable Univariate analysis Multivariate analysis Clinical model Biological model Comprehensive model HR (95% CI) P HR (95% CI) P score HR (95% CI) P score HR (95% CI) P score Age (years) <60/>60 1.12 (0.73-1.74) 0.59 - - - - - - - - - Sex Male/Female 0.93 (0.6-1.44) 0.93 - - - - - - - - - Rai stage 0/I-II 2.30 (1.47-3.50) <0.0001 2.13 (1.24-3.03) 0.004 0/2 - - - 1.76 (1.11-2.78) 0.015 0/1 ALC (109/L) <10/>10 3.43 (1.99-5.92) <0.0001 2.91 (1.85-5.20) <0.0001 0/2 - - - 2.70 (1.54-4.72) 0.001 0/2 b-2 microglobulin normal/elevated 3.04 (1.96-4.70) <0.0001 2.78 (1.79-4.30) <0.0001 0/2 - - - 2.65 (1.66-4.21) <0.0001 0/2 LDH normal/elevated 1.25 (0.57-2.71) 0.57 - - - - - - - - - CD38 negative/positive 3.22 (2.06-5.02) <0.0001 - - - 2.11 (1.15-3.16) 0.02 0/2 1.40 (0.80-2.42) 0.24 - ZAP-70 negative/positive 2.34 (1.51-3.61) <0.0001 - - - 1.21 (0.70-2.16) 0.485 - 1.0 (0.98-1.01) 0.72 - IGHV mutated/unmutated 3.57 (2.32-5.50) <0.0001 - - - 2.10 (1.12-3.90) 0.019 0/2 2.39 (1.27-4.50) 0.007 0/2 FISH risk low+int/high 2.93 (1.46-5.90) 0.002 - - - 1.65 (0.76-3.34) 0.216 - 1.80 (0.84-3.88) 0.13 - Abbreviations: ALC: absolute lymphocyte count; CI: confidential interval; HR: hazard ratio. Figure 1. TFS according to comprehensive progression risk score. Figure 1. TFS according to comprehensive progression risk score. Disclosures Shanafelt: Cephalon: Research Funding; Glaxo-Smith-Kline: Research Funding; Genentech: Research Funding; Hospira: Research Funding; Celgene: Research Funding; Jannsen: Research Funding; Polyphenon E International: Research Funding; Pharmacyclics: Research Funding. Kay:Genentech: Research Funding; Celgene Corporation: Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Membership on an entity's Board of Directors or advisory committees, Research Funding; Hospira: Research Funding; Tolero Pharma: Research Funding; Pharmacyclics: Research Funding.

Abstract The inhibitory effects exerted by transforming growth factor-β (TGF-β) on adult erythropoiesis has been well established. Canonical SMAD-depedent TGF-β signaling inhibits erythroid differentiation at multiple levels: it induces hematopoietic stem cells into quiescence (Chabanon et at Stem Cells. 2008;26:3150), it elicits a Smad5-dependent inhibition of progenitor cell proliferation (Bruno et al, Blood 1998; 91:1971) by increasing the length of G1 through reduction of G1 cyclin and cyclin-dependent protein kinases (Jacobsen et al, Blood 1995; 86:2957; Geng and Weinberg, PNAS 1993; 90:10315) and triggers Smad4-signaling accelerating terminal erythroid maturation (Zermati et al, Exp hematol 2000; 28:885; Choi et al MCB 2005;271:23). TGF-β is expressed by almost every cell type, but is produced in the greatest amount by megakaryocytes (Assonian et al, JBC 1983;258:7155; Massague, Cell 2008;134, 215). TGF-β has been implicated in the pathogenesis of primary myelofibrosis (PMF) by Schmitt et al (Blood. 2000;96:1342). Plasma, bone marrow and spleen washes of PMF patients, as well as those from murine PMF models, contain 2 fold-greater levels of total and bioactive TGF-β than those from normal controls (Zingariello et al, Blood 2013;121:3345). In addition, megakaryocytes from PMFpatients contain greater amounts of TGF-β than those from other MPNs such as polycythemia vera (PV) and essential thrombocythemia (Ciurea et al, Blood 2007;110:986). Published data, however, also suggest that malignant MPN cells are insensitive to TGF-β. Microarray analyses of PMF bone marrow and spleen cells revealed TGF-β signaling abnormalities which predict activation of non-canonical p38/ERK-dependent rather than canonical SMAD-dependent signaling (Ciaffoni et al, BCMD 2015;54:234). In addition, by phosphoproteomic profiling of PV erythroblasts (Erys) expanded in vitro express lower levels of pSmad2 as compared to Erys from healthy controls (Hricik et al. AJH 2013;88:723). The hypothesis that malignant MPN cells are insensitive to TGF-β was tested here by evaluating the effect of SB431542 [1,3,10 and 26µM], a small molecule inhibitor of TGF-β receptor 1, on ex vivo erythropoiesis in cultures generated by peripheral blood mononuclear cells from patients with JAK2 V617+-PV (n=2) and JAK2 V617F+ or CALR pQ365f+-PMF. Identical experiments were performed with Erys generated from adult peripheral blood (AB, n=3) and cord blood (CB, n=2) of healthy controls. All cultures were stimulated with SCF, IL-3 and EPO with and without dexamethasone (Dex). In cultures of JAK2 V617F+ -PV, SB431542 increased by 2-fold the numbers of progenitor cells observed by day 6, but had no effect on that of Erys observed by day 12-17 [fold increase (FI) ~4 fold in all cases]. Moreover, neither the number of progenitor cells nor that of Erys were affected by SB431542 treatment in cultures generated from JAK2 V617F+ (n=1) and CALR pQ365fs+ -PMF (n=1) patients (Fig. 1). This lack of effects was observed in cultures with and without Dex. By contrast, as expected, in cultures of AB, SB431542 significantly increased by 2.5-fold the number of progenitor cells observed by day 6 and that of Erys observed by day 14-17 (Fig. 1). This increase was associated with greater retention of an immature erythroid phenotype (CD36+ CD235a+ cells 16% vs 3%) and an increased proliferative index (>3 Erys in metaphases per field vs 0). This was observed up to day 17 in cultures both with and without Dex. The effects of SB431542 in cultures of CB were, however, affected by the presence of Dex. In cultures without Dex, SB431542 increased by 2-fold the number of progenitor cells by day 6 but had no effect on that of Erys by day 12-17 (FI=10-15 and CD36+CD235a+ cells >60%). In the presence of Dex, SB431542 did not affect the number of progenitor cells at day 6 but reduced that of Erys by 3-fold on day 12-17. These results suggest that in the case of CB, TGF-β promotes erythroid maturation in synergy with Dex. In conclusion, SB431542 promoted proliferation and maturation of normal adult progenitor cells but had no effect on PMF progenitor cells suggesting that treatments with TGF-β receptor 1 inhibitors may reactivate normal hematopoiesis in PMF patients by providing a proliferative advantage to the resident non-diseased hematopoietic stem cells over the malignant clone. This therapeutic approach will be explored in a MPD-RC, multi-center, phase II trial in patients with PMF. Disclosures Hoffman: Geron: Consultancy, Membership on an entity's Board of Directors or advisory committees; All Cells, LLC: Consultancy, Membership on an entity's Board of Directors or advisory committees; Promedior: Research Funding. Mascarenhas:Roche: Research Funding; Incyte Corporation: Research Funding; Kalobios: Research Funding; CTI Biopharma: Research Funding; Novartis Pharmaceuticals Corporation: Research Funding; Promedior: Research Funding.

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.

Lineage-specific growth factors mobilize peripheral blood progenitor cells (PBPC) and accelerate hematopoietic recovery after high-dose chemotherapy. Recombinant human thrombopoietin (rhTPO) may further increase the progenitor-cell content and regenerating potential of PBPC products. We evaluated the safety and activity of rhTPO as a PBPC mobilizer in combination with granulocyte colony-stimulating factor (G-CSF) in 29 breast cancer patients treated with high-dose chemotherapy followed by PBPC reinfusion. Initially, patients received escalating single doses of rhTPO intravenously (IV) at 0.6, 1.2, or 2.4 μg/kg, on day 1. Subsequent patients received rhTPO 0.6 or 0.3 μg/kg on days −3, −1, and 1, or 0.6 μg/kg on days −1 and 1. G-CSF, 5 μg/kg IV or subcutaneously (SC) twice daily, was started on day 3 and continued through aphereses. Twenty comparable, concurrently and identically treated patients (who were eligible and would have been treated on protocol but for the lack of study opening) mobilized with G-CSF alone served as comparisons. CD34+ cell yields were substantially higher with the first apheresis following rhTPO and G-CSF versus G-CSF alone: 4.1 × 106/kg (range, 1.3 to 17.6) versus 0.8 × 106/ kg (range, 0.3 to 4.2), P = .0003. The targeted minimum yield of 3 × 106CD34+ cells/kg was procured following a single apheresis procedure in 61% of the rhTPO and G-CSF–mobilized group versus 10% of G-CSF–mobilized patients (P = .001). In rhTPO and G-CSF mobilized patients, granulocyte (day 8 v 9, P= .0001) and platelet recovery (day 9 v 10, P= .07) were accelerated, and fewer erythrocyte (3 v 4,P = .02) and platelet (4 v 5, P = .02) transfusions were needed compared with G-CSF–mobilized patients. Peripheral blood platelet counts, following rhTPO and G-CSF, were increased by greater than 100% and the platelet content of PBPC products by 60% to 110% on the first and second days of aphereses (P < .0001) with the greatest effect seen with repeated dosing of rhTPO at 0.6 μg/kg. rhTPO is safe and well tolerated as a mobilizing agent before PBPC collection. Mobilization with rhTPO and G-CSF, in comparison to a comparable, nonrandomized G-CSF–mobilized group of patients, decreases the number of apheresis procedures required, may accelerate hematopoietic recovery, and may reduce the number of transfusions required following high-dose chemotherapy for breast cancer.

Abstract Background: Treatment of multiple myeloma has evolved considerably in the past few years with availability of several news drugs as well as increasing use of multidrug combinations. These changes have no doubt led to the improved survival seen among patients with MM. We have previously shown that outcomes of patients intolerant or refractory to one of the IMiDs and bortezomib had a poor outcome. Since that time, other drugs of the same class as well as new classes of drugs have been introduced for the treatment of MM. We designed this retrospective study to estimate the outcomes in patients with relapsed myeloma, who have become refractory to the current generation IMiDs and proteasome inhibitors. Patients and Methods: Patients with relapsed multiple myeloma who have received at least 3 prior lines of therapy, is refractory to both an IMiD (lenalidomide or pomalidomide) AND a proteasome inhibitor (bortezomib or carfilzomib), and has been exposed to an alkylating agent were identified from multiple centers. The time patients met the above criteria was defined as T0, and details of all treatment regimens before and after T0 were collected using electronic CRFs. The study was approved by the IRB at the respective centers. Results: 543 patients were enrolled in this study; median age was 62 years (31-87) and 61% were males. Patients were enrolled from centers in North America (n=181), Europe (n=318), and Asia Pacific (n=44). Patients were diagnosed between 2006 and 2014, the median duration between diagnosis of myeloma and study entry (T0) was 3.1 years (0.3 to 9). The median (95% CI) estimated follow up from diagnosis and from T0 were 61 (57, 66) months and 13 (11, 15) months respectively. The median number of lines of therapy prior to T0 was 4 (3-13), 48% had a prior transplant. The median OS from T0 for the entire cohort was 13 (11, 15) months. For these 462 patients, the median number of recorded regimens was 2 (1-9). The overall response and the depth of response to each line of treatment following T0 are as shown in the table. The median (95% CI) PFS and OS from T0 was 5 (4, 6), and 15.2 (13, 17), respectively. The overall survival for the 81 patients with no treatment post T0 was only 2.1 months. In a multivariate analysis, duration from diagnosis to T0, ISS stage III and number of lines of therapy were all associated with inferior PFS, as well as OS, and in addition, serum creatinine>2 mg/dL at T0 also predicted inferior OS. Conclusions: The study provides the expected outcome following development of myeloma that is refractory to a PI and an IMiD. The outcomes of these patients appear to be better than we had seen historically in patients refractory/ intolerant to bortezomib and IMiDs, highlighting the increased treatment options available for these patients. However, there is decreasing response rate to sequential regimens highlighting the development of drug resistance. The data provides a bench mark for comparison of new therapies that are being evaluated in this disease. Table Table. Disclosures Dimopoulos: Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Genesis: Consultancy, Honoraria; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Kastritis:Takeda: Consultancy, Honoraria; Genesis: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Amgen: Consultancy, Honoraria. Terpos:BMS: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Other: Travel expenses, Research Funding; Celgene: Honoraria; Takeda: Consultancy, Honoraria; Genesis: Consultancy, Honoraria, Other: Travel expenses; Amgen: Consultancy, Honoraria, Other: Travel expenses, Research Funding; Novartis: Honoraria. Hillengass:Sanofi: Research Funding; Novartis: Research Funding; Amgen: Consultancy, Honoraria; BMS: Honoraria; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria. Leleu:TEVA: Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria; LeoPharma: Honoraria; Amgen: Honoraria; Bristol-Myers Squibb: Honoraria; Pierre Fabre: Honoraria; Celgene: Honoraria; Novartis: Honoraria; Takeda: Honoraria. Oriol:Janssen: Honoraria, Other: Expert board committee; Amgen: Honoraria, Other: Expert board committee. Cavo:Celgene: Consultancy, Honoraria; Millennium: Consultancy, Honoraria; Bristol-Myers Squibb: Consultancy, Honoraria; Janssen-Cilag: Consultancy, Honoraria; Amgen: Consultancy, Honoraria. Mateos:Janssen: 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; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees. Vij:Shire: Consultancy; Takeda: Consultancy, Research Funding; Jazz: Consultancy; Karyopharma: Consultancy; Janssen: Consultancy; Novartis: Consultancy; Celgene: Consultancy; Bristol-Myers Squibb: Consultancy; Amgen: Consultancy, Research Funding. Lokhorst:Genmab: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding. van de Donk:Amgen: Research Funding; Janssen: Research Funding; BMS: Research Funding; Celgene: Research Funding. Mark:Onyx: Research Funding, Speakers Bureau; Millenium: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau. Ludwig:Amgen: Research Funding, Speakers Bureau; Takeda: Research Funding, Speakers Bureau; BMS: Speakers Bureau; Janssen: Speakers Bureau. Jagannath:Novartis: Consultancy; Janssen: Consultancy; Bristol-Myers Squibb: Consultancy; Celgene: Consultancy; Merck: Consultancy. Usmani:Array: Research Funding; Britsol-Myers Squibb: Consultancy, Research Funding; Skyline: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; BioPharma: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Onyx: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Pharmacyclics: Research Funding; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Sanofi: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Amgen: Consultancy, Research Funding, Speakers Bureau; Millenium: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Novartis: Speakers Bureau. Dytfeld:Janssen Poland: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Research Funding; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Membership on an entity's Board of Directors or advisory committees. Moreau:Novartis: Honoraria; Amgen: Honoraria; Celgene: Honoraria; Bristol-Myers Squibb: Honoraria; Takeda: Honoraria; Janssen: Honoraria, Speakers Bureau. Lee:Amgen: Membership on an entity's Board of Directors or advisory committees. Shustik:Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Millenium: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: 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. de la Rubia:Celgene: Consultancy; Bristol Myers: Consultancy; Amgen,: Consultancy; Janssen: Consultancy. Durie:Takeda: Consultancy; Amgen: Consultancy; Janssen: Consultancy.

Abstract Abstract 2883 CLL-like monoclonal B-cell lymphocytosis (MBL) shares common immunophenotypic features and cytogenetic abnormalities with CLL and is generally perceived as its premalignant state. The World Health Organization has set a consensus cut-off of 5×109/L circulating B cells to discriminate between what constitutes ‘disease’ and what not. However, the clonal size within MBL is extremely variable. High-count (HC), clinical MBL is associated with absolute lymphocytosis and progresses to CLL requiring treatment at a rate of 1–2% per year, whereas low-count (LC) MBL is found in the general population through high-sensitivity techniques and carries a risk of progression that is limited if any. Given the high frequency of CLL-like MBL in the general population, it is important to understand the underlying mechanisms and also identify biological markers endowing malignant potential that may distinguish between the different forms. To this end, we performed a detailed immunogenetic profiling of 334 CLL-like MBL cases (78 LC and 256 HC) for a total of 355 productive VDJ rearrangements (including double rearrangements), 91 from LC MBL and 264 from HC MBL. We also compared the immunoglobulin (IG) gene repertoires of MBL to 544 CLL Rai Stage 0 (CLL-0) that were part of an IG sequence dataset of 7424 CLL cases previously analyzed by our group. LC and HC MBL had distinct IG gene repertoires, with over-representation of the IGHV1–69 and IGHV4–34 genes in HC and the IGHV4–59/61 genes in LC MBL, respectively (p<0.001). The HC MBL repertoire exhibited clear similarities to CLL-0 in terms of IGHV gene usage (similar frequencies of IGHV1–69 and IGHV4–34). Regarding somatic hypermutation, no differences were identified between LC MBL versus HC MBL versus CLL-0, in that the frequency of mutated rearrangements (<98% identity to the germline) was overall similar (LC MBL: 72.5%, HC MBL: 76.1%, CLL-0: 75%). In this respect, all the aforementioned subgroups differed significantly (p<0.001) from the frequency previously reported by us in CLL where only 55% of rearrangements carried mutated IGHV genes. We finally analyzed the expression of stereotyped B cell receptor (BcR) IGs, identified through a cluster analysis of the MBL sequences together with all CLL sequences from our cohort and 5494 non-CLL IG sequences retrieved from public databases. Overall, only 6/91 (5.5%) LC MBL rearrangements could be clustered with other sequences in subsets with stereotyped BcRs. Two of these six LC MBL cases were clustered together with IG sequences from various entities, including CLL, other lymphomas and autoimmune diseases; thus, they were considered to carry ‘public’ BcR stereotypes. In contrast, HC MBL showed a significantly (p=0.0002) higher frequency of ‘CLL-specific’ BcR stereotypes versus LC MBL, with 60/264 (22.7%) HC MBL cases carrying stereotyped VH CDR3s. This frequency was comparable to the one observed in CLL-0 (20.2%). Notably, a gradation was observed in the frequency of BcR IG stereotypy depending on the absolute count of CLL-like cells, starting with 5.5% in LC MBL, raising to 22.7–20.2% in in HC MBL/CLL-0 and, finally, peaking at 30.4% in the entire CLL cohort as previously reported. Altogether, these findings suggest that rather than a true premalignant condition, LC MBL may merely reflect immune senescence or result from persistent antigen stimulation. On the other hand, HC MBL appears to be a continuum with Rai stage 0 in the evolution to clinically overt CLL, being maybe one step behind where it requires either additional genetic hits or simply extra time to cross the numerical border that discriminates it from CLL. Hence, the identification of molecular genetic markers that may predict progression of HC MBL/CLL-0 into full-fledged CLL is strongly warranted. Disclosures: Shanafelt: Genentech: Research Funding; GlaxoSmith Klein: Research Funding; Teva/Cephalon: Research Funding; Celgene: Research Funding.

Abstract Introduction: APL, while highly curable in the modern era, remains a therapeutic challenge in the high-risk subset, with high rates of early mortality and relapse compared to non-high-risk APL. Recent evidence has confirmed excellent outcomes in non- high-risk APL with the combination of ATO and ATRA, and a previous pilot study had indicated the efficacy of a combination of ATO + ATRA + GO in high-risk APL. The North American Leukemia Intergroup designed a larger phase 2 study to confirm the efficacy and safety of this combination in high-risk APL. Primary Objectives: 1) assessment of 3-year event-free survival (EFS); 2) assessment of early (6 week) death rate. Methods: Adult patients with newly diagnosed high-risk APL (WBC ≥10k/uL) were eligible. Induction therapy consisted of: ATRA (45 mg/m2/day), beginning on day 1; ATO 0.15 mg/kg/day, beginning on day 10; GO 9 mg/m2on day 1. ATRA and ATO were continued until remission achieved. Patients in remission went on to receive consolidation with ATO x 2 cycles, followed by ATRA + daunorubicin x 2 cycles, followed by GO x 2 cycles. Subsequent maintenance therapy consisted of ATRA + 6-mercaptupurine + methotrexate for up to 1 year. Results: Between 2008 and 2013, 73 registered patients began protocol treatment. Median age was 46.5 years, with 52% females and 48% males. Sixty-two (85%) patients completed induction therapy as planned, and 50 patients (68%) completed all planned consolidation. Sixty-two patients (85%) achieved a documented complete response (CR). Non-responses were attributable to lack of response assessment (n=10), most commonly related to death. One patient had resistant disease. With a median follow-up of 3.3 years, the Kaplan Meier 3-year EFS estimate was 79% (95% CI 68% - 87%), which was significantly improved compared to the protocol-defined historical rate of 50% (p<0.001). The 3-year overall survival estimate was 88% (95% CI 78% to 93%). The 3-year relapse-free survival estimate was 93% (95% CI 82% to 97%). At data cut-off, there was 1 documented death during remission and no reported cases of relapse. Eight of 73 patients (11%) died within 6 weeks of treatment initiation (95% confidence interval 5-20%), at a median time of 11 days (range 3-31), which was significantly lower than the protocol defined null rate of 30% (p<0.001). The most common treatment-emergent grade 3-4 adverse events during induction included: febrile neutropenia (34%), AST/ALT elevation (12%), hypoxia/differentiation syndrome (11%), hyperglycemia (11%), headache (11%), prolonged QTc (11%). Summary: the combination of ATO + ATRA + GO was safe and effective in patients with high-risk APL, producing highly durable responses, low rates of early mortality, and comparing favorably with chemotherapy-based induction regimens in this setting. Although GO is not currently commercially available in the US, this regimen should be considered as a therapeutic option for patients with high-risk APL in the future. Support: NIH/NCI grants CA180888, CA180819, CA180820, CA180821, and in part by Wyeth Pharmaceuticals (Pfizer, Inc.) Figure Figure. Disclosures Komrokji: Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Consultancy, Speakers Bureau; Incyte: Consultancy. Coutre:Gilead Sciences: Consultancy, Research Funding. DeAngelo:Amgen: Consultancy; Ariad: Consultancy; Baxter: Consultancy; Novartis: Consultancy; Pfizer: Consultancy; Incyte: Consultancy; Celgene: Consultancy. Othus:Glycomimetics: Consultancy; Celgene: Consultancy.

Abstract Background: ENESTop, an ongoing, single-arm, phase 2 study (ClinicalTrials.gov, NCT01698905), is the first trial specifically evaluating treatment-free remission (TFR; ie, stopping tyrosine kinase inhibitor [TKI] treatment without a loss of response) in patients with chronic myeloid leukemia in chronic phase (CML-CP) who achieved a sustained deep molecular response after switching from imatinib (IM) to nilotinib (NIL). Of 126 patients in ENESTop who were eligible to stop NIL, 57.9% (95% CI, 48.8%-66.7%) maintained TFR at 48 weeks. Here we present results from a subgroup analysis based on reasons for switching from IM to NIL, categorized as intolerance, resistance, and physician preference. Methods:Eligible patients were adults with CML-CP who received ≥ 3 years of total TKI therapy (> 4 weeks of IM, followed by ≥ 2 years of NIL) and achieved a sustained MR4.5 (BCR-ABL1 ≤ 0.0032% on the International Scale [BCR-ABL1IS]) on NIL therapy; patients with a documented MR4.5 at the time of switch from IM to NIL were not eligible. Enrolled patients continued NIL treatment in a 1-year consolidation phase, and those without confirmed loss of MR4.5 (ie, consecutive BCR-ABL1IS > 0.0032%) were eligible to stop NIL in the TFR phase. Patients with loss of major molecular response (MMR; ie, BCR-ABL1IS > 0.1%) or confirmed loss of MR4 (ie, consecutive BCR-ABL1IS > 0.01%) during the TFR phase reinitiated NIL treatment. The primary endpoint was the proportion of patients who maintained TFR (ie, no loss of MMR, confirmed loss of MR4, or treatment reinitiation) at 48 weeks after stopping NIL. In this post hoc analysis, rates of TFR at 48 weeks after stopping NIL and a Kaplan-Meier (KM) analysis of treatment-free survival (TFS; defined as the time from the start of TFR to the earliest occurrence of any of the following: loss of MMR, confirmed loss of MR4, reinitiation of NIL due to any cause, progression to accelerated phase/blast crisis, death due to any cause) were evaluated in subgroups of patients who switched from IM to NIL due to intolerance, resistance, or physician preference. These categories were determined by grouping the reasons for switching from IM to NIL, as reported by the investigators, based on relatedness to safety (intolerance), loss of response/treatment failure (resistance), and the physician's clinical judgment (physician preference); individual reasons included within each category are presented in the Figure. Results:A total of 125 patients who entered the TFR phase were included in this analysis; 1 patient who was found to have had atypical transcripts was excluded. Among these 125 patients, the reasons for switching to NIL were categorized as intolerance in 51 patients (40.8%), resistance in 30 patients (24.0%), and physician preference in 44 patients (35.2%). The proportion of patients who maintained TFR at 48 weeks after stopping NIL was generally similar across the 3 subgroups: 30 of 51 (58.8%; 95% CI, 44.2%-72.4%) in the intolerance subgroup, 16 of 30 (53.3%; 95% CI, 34.3%-71.7%) in the resistance subgroup, and 27 of 44 (61.4%; 95% CI, 45.5%-75.6%) in the physician preference subgroup. KM analysis of TFS showed that in all 3 subgroups, the majority of TFS events occurred within the first 24 weeks after stopping NIL (Figure). There were no notable differences in the kinetics of TFS events among subgroups. The KM-estimated median duration of TFS was not reached by the data cutoff date in all 3 subgroups. Conclusion: Primary analysis from ENESTop showed that among patients with CML-CP who achieved a sustained MR4.5after switching from IM to NIL, 57.9% of those who stopped NIL maintained TFR at 48 weeks. In the present analysis, TFR was maintained at 48 weeks after stopping NIL by > 50% of patients in the intolerance, resistance, and physician preference subgroups, with generally similar results across subgroups. These findings suggest that the rate of successful TFR following second-line NIL does not differ based on the reasons for switching from IM to NIL. Figure. Figure. Disclosures Hughes: Ariad: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Australasian Leukaemia and Lymphoma Group (ALLG): Other: Chair of the CML/MPN Disease Group. Boquimpani:Novartis: Research Funding, Speakers Bureau; BMS: Speakers Bureau. Takahashi:Novartis: Honoraria, Research Funding; Pfizer: Honoraria, Research Funding; BMS: Honoraria. Shuvaev:Pfizer: Honoraria; BMS: Honoraria; Novartis pharma: Honoraria. Ailawadhi:Pharmacyclics: Consultancy; Novartis: Consultancy; Amgen Inc: Consultancy; Takeda Oncology: Consultancy. Lipton:Pfizer: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; BMS: Consultancy, Research Funding; Ariad: Consultancy, Research Funding. Turkina:Pfizer: Honoraria; Novartis Pharma: Honoraria; BMS: Honoraria. Moiraghi:BMS: Speakers Bureau; NOVARTIS: Speakers Bureau. Nicolini:Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Consultancy, Honoraria; Ariad pharmaceuticals: Honoraria, Membership on an entity's Board of Directors or advisory committees. Sacha:BMS: Consultancy, Honoraria, Speakers Bureau; Incyte: Consultancy, Honoraria, Speakers Bureau; Pfizer: Consultancy, Honoraria, Speakers Bureau; Novartis: Consultancy, Honoraria, Speakers Bureau; Adamed: Consultancy, Honoraria. Kim:Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Novartis: Consultancy, Honoraria, Research Funding, Speakers Bureau; ILYANG: Consultancy, Honoraria, Research Funding. Fellague-Chebra:Novartis: Employment. Acharya:Novartis Healthcare Pvt. Ltd.: Employment. Krunic:Novartis: Employment, Equity Ownership. Jin:Novartis: Employment, Equity Ownership. Mahon:BMS: Honoraria; PFIZER: Honoraria; NOVARTIS PHARMA: Honoraria, Research Funding; ARIAD: Honoraria.

Abstract Background: ENESTop (NCT01698905) is an ongoing, single-arm, phase 2 study evaluating treatment-free remission (TFR) in patients (pts) with chronic myeloid leukemia in chronic phase (CML-CP) who achieved sustained molecular response 4.5 (MR4.5; BCR-ABL1 ≤ 0.0032% on the International Scale [BCR-ABL1IS]) on second-line nilotinib (NIL). In the primary analysis, 57.9% (95% CI, 48.8%-66.7%) of pts who stopped NIL maintained TFR (no loss of major molecular response [MMR; ie, BCR-ABL1IS > 0.1%], confirmed loss of MR4 [ie, consecutive BCR-ABL1IS > 0.01%], or treatment reinitiation) at 48 weeks. Adverse events (AEs) were reported in 73.8% of pts during the first 48 weeks of TFR vs 77.0% during the year prior to stopping treatment. The incidence of musculoskeletal pain-related AEs was higher during TFR (42.1% vs 14.3%). To assess the potential effect of stopping NIL on quality of life (QOL), pt-reported outcomes were assessed before and during TFR. Methods: ENESTop enrolled adult pts with CML-CP with ≥ 3 years of prior tyrosine kinase inhibitor (TKI) therapy (> 4 weeks of imatinib [IM], then ≥ 2 years of NIL). Pts must have achieved sustained MR4.5 on NIL after switching from IM. Enrolled pts entered a 1-year NIL treatment consolidation phase; those without confirmed loss of MR4.5 (ie, consecutive BCR-ABL1IS > 0.0032%) entered the TFR phase and stopped NIL. Pts with loss of MMR or confirmed loss of MR4 during the TFR phase reinitiated NIL. QOL was assessed via questionnaires completed by pts at specified time points. The MD Anderson Symptom Inventory for CML (MDASI-CML) questionnaire assessed, for a defined set of symptoms, the levels of severity and interference with daily life on a scale of 0 to 10, with 0 being the lowest level. The EQ-5D-5L questionnaire assessed problems experienced by pts (no, slight, moderate, severe, or extreme [ie, interfering with functioning] problems) in 5 dimensions: mobility, self-care, usual activities, anxiety/depression, and pain/discomfort; additionally, overall level of health was assessed on a scale of 0 to 100 using the EQ VAS, with 0 being the lowest level. Results: Of 163 enrolled pts, 126 met the criteria for stopping NIL in the TFR phase; of these 126, 53 had loss of MMR or confirmed loss of MR4, of whom 51 reinitiated NIL. Among pts who completed each questionnaire at week 48 of the consolidation phase, week 12 of the TFR phase, or week 48 of the TFR phase, mean MDASI-CML severity scores were 1.7, 1.5, and 1.2, respectively; mean MDASI-CML interference scores were 1.7, 1.6, and 1.4, respectively; and mean EQ VAS scores were 82.2, 78.8, and 82.3, respectively (Table). Among pts with sustained TFR and scores at both week 48 of the consolidation phase and week 12 or 48 of the TFR phase, minimal changes were observed in MDASI-CML and EQ VAS scores during TFR vs week 48 of the consolidation phase. Among pts who reinitiated NIL, mean MDASI-CML severity and interference scores and mean EQ VAS scores at 24 weeks after the start of retreatment were 1.6, 1.5, and 78.8, respectively; changes in scores between week 24 after treatment reinitiation and week 48 of the consolidation phase were minimal among pts with scores at both time points. Among pts who completed the EQ-5D-5L questionnaire, the proportions who reported problems (any level of severity) in the 5 dimensions were generally similar across time points, although problems with mobility and pain/discomfort were more common during TFR vs week 48 of the consolidation phase, particularly at week 12 of the TFR phase (Table). Conclusion: Changes in QOL after stopping NIL, as assessed using these questionnaires, were minimal. This may be related to pts having a relatively high QOL prior to stopping treatment given that they had tolerated ≥ 3 years of TKI therapy, including ≥ 2 years of NIL, prior to enrollment. Despite the higher incidence of musculoskeletal pain-related AEs observed during TFR (42.1% vs 14.3%), the overall QOL was generally similar between the TFR and consolidation phases. This suggests that these AEs did not have a significant negative impact on QOL. Longer follow-up in ENESTop will be needed to further evaluate trends in QOL after stopping second-line NIL. Disclosures Mahon: NOVARTIS PHARMA: Honoraria, Research Funding; BMS: Honoraria; ARIAD: Honoraria; PFIZER: Honoraria. Boquimpani:BMS: Speakers Bureau; Novartis: Research Funding, Speakers Bureau. Takahashi:Novartis: Honoraria, Research Funding; Pfizer: Honoraria, Research Funding; BMS: Honoraria. Shuvaev:Novartis pharma: Honoraria; Pfizer: Honoraria; BMS: Honoraria. Ailawadhi:Pharmacyclics: Consultancy; Novartis: Consultancy; Amgen Inc: Consultancy; Takeda Oncology: Consultancy. Lipton:Novartis: Consultancy, Research Funding; Ariad: Consultancy, Research Funding; BMS: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding. Turkina:Novartis Pharma: Honoraria; Pfizer: Honoraria; BMS: Honoraria. Moiraghi:NOVARTIS: Speakers Bureau; BMS: Speakers Bureau. Nicolini:Ariad: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Consultancy, Honoraria. Sacha:Pfizer: Consultancy, Honoraria, Speakers Bureau; Incyte: Consultancy, Honoraria, Speakers Bureau; BMS: Consultancy, Honoraria, Speakers Bureau; Novartis: Consultancy, Honoraria, Speakers Bureau; Adamed: Consultancy, Honoraria. Kim:BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; ILYANG: Consultancy, Honoraria, Research Funding; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Novartis: Consultancy, Honoraria, Research Funding, Speakers Bureau. Fellague-Chebra:Novartis: Employment. Acharya:Novartis Healthcare Pvt. Ltd.: Employment. Brandt:Novartis: Employment. Gnanasakthy:Novartis: Consultancy, Equity Ownership, Research Funding. Jin:Novartis: Employment, Equity Ownership. Hughes:Ariad: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding.