Waller, Daniel Dirck

DISCUSSION AND CONCLUSION Chimeric antigen receptor (CAR)-T cells directed against B-cell maturation antigen (BCMA), have yielded impressive results in clinical trials for multiply relapsed/refractory multiple myeloma (MM). However, progression-free survival is short, demonstrating a need for improvements. While numerous advances have been made to improve this treatment modality, these have not always translated to superior clinical outcomes. A major limitation is that novel therapeutics are often not tested in a relevant in vivo model. These novel strategies have been largely tested only in immunodeficient models of MM. To better recapitulate the host-tumour-effector cell interactions, particularly in the TME, we sought to develop a system to study CAR-T cell activity in the Vk*MYC model of MM. Here, we report on the first known successful model of CAR-T cell activity in an immunocompetent model of MM. We sought to identify a BCMA CAR construct that is capable of binding to both human and mouse BCMA. A novel nanobody recognizing BCMA was developed by immunizing llamas with human BCMA and the resulting single-domain antibodies (sdAbs) were subsequently isolated and cloned. These sdAbs were then screened for binding to mouse BCMA. A binder capable of recognizing both human and mouse BCMA was identified and cloned into our murine CAR construct, with CD28 and CD3z signaling domains, herein referred to as sdBCMA2.CD28.CD3z. Murine CAR-T cells were then generated by transducing activated healthy murine splenocytes with a retroviral vector carrying the sdBCMA2.CD28.CD3z construct. These CAR-T cells were then characterized in vitro using standard cytotoxicity, proliferation, and cytokine release assays. To assess activity in an immunocompetent model, female C57BL/6J mice were injected intravenously with Vk12598 Vk*MYC cells. CAR-T cells were later administered intravenously. Mice were bled weekly to quantify M-protein disease burden by serum protein electrophoresis and for phenotypic characterization of circulating cells. When co-cultured with BCMA+ human MM cell lines and with Vk*MYC cell lines, murine sdBCMA2.CD28.CD3z CAR-T cells effectively lysed target cells, proliferated, and released inflammatory cytokines. To assess the in vivo activity of these CAR-T cells, we injected intravenously female C57BL/6J mice with Vk12598 cells, and then administered sdBCMA2.CD28.CD3z CAR-T cells intravenously. While there was some evidence of survival improvement, the median overall survival (mOS) of 35 days compared to 28 days, for CAR-T vs. Mock T-cells, respectively, the difference was non-significant, and the survival benefit was not durable. To address this, we incorporated lymphodepletion by total body irradiation (TBI) followed by CAR-T cell administration the next day. By incorporating lymphodepletion prior to CAR-T cell administration we were able to significantly reduce M-protein surrogates of disease burden, as well as achieve durable remissions in the TBI + CAR-T arm with an mOS not yet reached after experimental day 91, compared to an mOS of 42 days in the TBI + Mock T-cell arm. The addition of TBI also significantly improved the engraftment of CAR-T cells, as assessed by flow cytometry. The TBI + CAR-T arm also had significantly increased IL-6, IL-1b, IL-2, and TNF-a in the serum, compared to the TBI + Mock arm, at 7 days post administration of CAR-T cells. The durable remission achieved using the combination of our novel sdBCMA2.CD28.CD3z CAR-T cells with lymphodepletion is a pivotal advancement in modelling MM CAR-T cell activity in this clinically relevant model system. Our approach represents the first time that CAR-T cells were successfully used to treat the Vk12598 model of MM that faithfully recapitulates relapsed MM. The incorporation of lymphodepletion significantly improves CAR-T cell engraftment, in line with clinical CAR-T cell therapy paradigms. The cytokine profile observed is consistent with the cytokine elevations typically observed after CAR-T cell administration in patients. As our construct is capable of binding to both human and mouse BCMA, we are therefore able to fully characterize our lead assets in a relevant model system. Our strategy will enable further research to dissect host-tumour-effector cell interactions, to better inform the design and characterization of novel CAR-T cell therapies in MM.

Abstract Introduction: Immune checkpoint receptor (ICR) blockade has emerged as an effective anti-tumour modality, but only in a subset of cancer patients. Moreover, in Multiple myeloma (MM), single-agent activity has not been observed, highlighting the need to better understand the mechanism of action of this class of drugs. We recently showed that combinatorial ICR blockade using αLAG3 and αPD-1 delays disease progression and improves survival in the transplantable Vκ*MYC model of MM (Croucher et al. ASH 2018). However, despite this being a controlled study with genetically-homogeneous tumours, anti-tumour immune responses were heterogeneous, with only a subset of mice demonstrating a delay in tumour progression (17/29 mice, response rate = 58.6%). Thus, using this model, we set out to define mechanisms underlying variability in response to ICR blockade. Methods: We established a cohort of mice by engrafting 5-week-old C57BL/6 mice with Vκ12598 cells via tail vein injection. Treatment with αLAG3/αPD-1 or Ig-control was initiated 1-week post-engraftment and bone marrow (BM) samples were collected 3 weeks after the start of treatment. Following FACS-enrichment of T cells and plasma cells (PCs), single cell suspensions were subjected to matched single-cell gene expression (5' scRNA-seq) and T cell receptor (TCR)/B cell receptor (BCR) profiling (10x Genomics). Results: Samples were selected for profiling based on response to treatment, with responders (n=4) defined by significantly lower disease burden compared to non-responders (n=3) and control-treated mice (n=5), as measured by serum M-protein and %PCs in BM/spleen at sacrifice. Unsupervised clustering of scRNA-seq data from PCs (n=3,318 cells) identified no gene expression or BCR repertoire differences between control and treated, or between responder and non-responder samples, supporting that variability in response was not related to malignant Vκ12598 cells themselves. Across all samples, a statistically significant difference was not detected between the total number of unique TCR sequences (clonotypes) comparing control-treated (351-2369), non-responders (1185-2327) and responders (1378-1698), with no overlapping TCR sequences between top clonotypes. Evaluation of TCR repertoire diversity revealed that αLAG3/αPD-1 treatment induces clonal T cell expansion in control versus treated mice, but this was not significantly different between responders and non-responders. Analysis of paired scRNA-seq data (n=21,520 cells) revealed that expanded T cells from αLAG3/αPD-1-treated mice occupy a different cell state in responder vs. non-responder mice. We speculate that underlying differences in the TCR repertoire may dictate the downstream phenotype of expanded, anti-tumour T cells in mice treated with combinatorial αLAG3/αPD-1. Tumour control following treatment was associated with clonal expansion of T cells expressing genes related to cytoxicity and activation (Ccl5, Ifng, Fasl, Gzmb), whereas tumour progression was associated with clonal expansion of proliferative T cells (Cdkn3, Birc5, Ccna2, Aurka, Mki67). Although T cell proliferation is typically a phenotype ascribed to effector T cells, recent studies have similarly observed this proliferative cell state in dysfunctional T cells within melanoma tumours. Moreover, emerging evidence supports suppression of T cell proliferation by CDK4/6 inhibitors as a means to augment anti-tumour activity of ICR-based therapy. Thus, studies exploring whether reversal of the observed proliferative T cell state can restore response to αLAG3/αPD-1 treatment in non-responding Vκ12598 mice are ongoing and will be reported. Conclusions: ICR inhibitors demonstrate significant activity in some cancers, however many patients fail to respond and a similarly promising level of efficacy has not been achieved in MM. Studies aimed at unraveling the mechanisms of response and resistance to ICR inhibitors are therefore needed to improve the utility of this class of drugs for all patients. Our approach of using paired single-cell gene expression and TCR repertoire profiling has enabled identification of molecular cell states specifically in expanded T cells of responder vs. non-responder mice. In turn, our work nominates novel mechanisms that may be used as potential biomarkers for anti-tumour immune responses as well as potential targets to augment responses to ICR blockade therapy. Disclosures Chesi: Abcuro: Patents & Royalties: Genetically engineered mouse model of myeloma; Novartis: Consultancy, Patents & Royalties: human CRBN transgenic mouse; Pfizer: Consultancy; Pi Therapeutics: Patents & Royalties: Genetically engineered mouse model of myeloma; Palleon Pharmaceuticals: Patents & Royalties: Genetically engineered mouse model of myeloma. Bergsagel: GSK: Consultancy, Honoraria; Genetech: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Oncopeptides: Consultancy, Honoraria; Novartis: Consultancy, Honoraria, Patents & Royalties: human CRBN mouse; Pfizer: Consultancy, Honoraria; Celgene: Consultancy, Honoraria. Sebag: Janssen: Research Funding; Bristol Myers-Squibb: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Novartis: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Sanofi: Consultancy, Honoraria; Karyopharm Therapeutics: Consultancy, Honoraria. Trudel: BMS/Celgene: Consultancy, Honoraria, Research Funding; Amgen: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; GlaxoSmithKline: Consultancy, Honoraria, Research Funding; Roche: Consultancy; Sanofi: Honoraria; Pfizer: Honoraria, Research Funding; Genentech: Research Funding.

Abstract Introduction: Multiple Myeloma (MM) is consistently preceded by pre-malignant asymptomatic monoclonal gammopathies (AMG). To date, our understanding of the pathogenesis of progression to MM remains incomplete. Genetic analyses of AMG cells compared to MM-derived plasma cells (PCs) have found few differences, suggesting that progression may be mediated in part by tumour-extrinsic mechanisms. To comprehensively examine the cellular and molecular complexities of MM pathogenesis, we performed an unbiased single cell RNA-sequencing (scRNA-seq) analysis of tumour cells as well as immune cells from the tumour microenvironment (TME) derived from transgenic mice transitioning from AMG to MM. Methods: We employed the Vk*MYC immune-competent mouse model of MM (C57BL/6/KaLwRij), which is a clinically and biologically faithful model of untreated disease that similarly progresses from AMG to MM with age. We established an age-based cohort of Vk*MYC mice to recapitulate a range of MM disease stages, generated single-cell suspensions from flushed bone marrow and subjected these cells to scRNA-seq profiling (10x Genomics). Results: Across 12 samples profiled to date, our scRNA-seq dataset contains 82,853 high-quality cells, expressing 17,922 genes. We employed dimensionality reduction and unsupervised graph-based clustering to visualize and group transcriptionally-similar cell populations, which revealed 42 clusters. Expression of known marker genes and computed correlation scores with bulk gene expression reference datasets enabled annotation of cell types, revealing both malignant cells and non-malignant immune cell populations. We first focused on single cell T/NK profiles in our data given the emerging utility of immune checkpoint inhibitors that target these populations. Although we did not observe numerical differences in the proportion of CD8+ T cells across disease stages, analysis of immune checkpoint receptor genes revealed increased expression of Pdcd1 (PD-1) and Lag3 in CD8+ T cells from mice with disease. Co-expression of LAG3 and PD-1 proteins was also confirmed using a Vk*MYC transplantable model, with a positive correlation between disease burden (%CD138+/B220- cells) and %PD1+LAG3+ CD8+ T cells by flow cytometry. Consistent with reports of PD-1 and LAG3 co-expression on non-functional exhausted T cells, CD8+ T cells from diseased mice demonstrated elevated T cell exhaustion scores in our scRNA-seq dataset. These observations suggest that T cell exhaustion may be mediated by multiple immune checkpoint receptors during disease evolution. Although combinatorial treatment with PD-1 and LAG3 antibodies failed to induce tumour regression in mice with established disease, the addition of cyclophosphamide (Cy) to these antibodies resulted in marked improvement in survival of the mice compared to Cy alone, presumably by promoting immunogenic cell death. Studies exploring the combination of LAG3 and PD-1 antibodies as a strategy to inhibit transition from AMG to MM in the Vk*MYC mice are ongoing and will be reported. We also performed subclustering analysis of 5,228 Sdc1+ (CD138) PCs in our scRNA-seq dataset revealing 11 distinct clusters, with evidence of inter- and intra-tumoural heterogeneity across all Vk*MYC mice. Differential gene expression analysis revealed a non-malignant PC (nPC) cluster as supported by lower Myc transgene and Ccnd2 expression. Moreover, this cluster was predominantly comprised of cells from age-matched control mice or mice with earlier disease. Single-cell chromosomal copy number analysis revealed loss of Chr5 in the majority of tumour cells from MM mice, but not in the nPC cluster. Loss of Chr5 was observed in tumor subclones from all AMG mice suggesting that it is an early and potentially unifying event in Vk*MYC mice during disease progression. Further, the data support the establishment of intratumoural heterogeneity early in disease evolution. Conclusions: Our approach of using scRNA-seq to characterize the pathogenesis of disease evolution in MM has enabled simultaneous measurement of intratumoural heterogeneity and immune cell phenotypes in the TME. In turn, this has provided insights into mechanisms that may contribute to transition from AMG to MM, including induction of T cell exhaustion and loss of mouse Chr5. Ongoing and future work aims to evaluate whether these mechanisms can be exploited therapeutically in pre-malignant AMG. Disclosures Sebag: Amgen Canada: Membership on an entity's Board of Directors or advisory committees; Janssen Inc.: Membership on an entity's Board of Directors or advisory committees; Celgene Canada: Membership on an entity's Board of Directors or advisory committees; Takeda Canada: Membership on an entity's Board of Directors or advisory committees. Pugh:Prosigna: Honoraria; N/A: Patents & Royalties: Hybrid-capture sequencing for determining immune cell clonality; N/A: Patents & Royalties: Combined hybrid-capture DNA sequencing for disease detection; Boehringer Ingelheim: Research Funding; Chrysalis Biomedical Advisors: Honoraria; Merck: Honoraria; DynaCare: Consultancy.

Abstract Background: The initial therapies for multiple myeloma have changed significantly in the recent years with routine incorporation of combinations containing IMiDs and proteasome inhibitors. However, patients with MM invariably relapse after their initial treatment and undergo successive therapies for continued control of their disease. The increasing access to new therapies for treatment of relapsed disease has led to improved survival of patients with MM. Many recent phase 3 trials have studied the impact of new agents on outcome of patients with MM who are relapsing after the initial lines of therapy for relapsed disease. However, the natural history of relapsed myeloma earlier in the course of relapsed disease has not been studied in detail. Patients and methods: We designed a global, multicenter, retrospective study to examine the current treatment approaches for initial relapses in MM and patient outcomes following application of successive treatment regimens. Patients with multiple myeloma who experience a first relapse between January 1, 2007 and December 31, 2011 were identified at participating sites. Clinical and laboratory data pertaining to the time of diagnosis and from the time of individual relapses up to and including the third relapse will be obtained from the clinical records. The first date of treatment with an anti-myeloma regimen for first disease relapse was termed time zero (T0). Results: Three hundred and fifteen patients were enrolled; median age at diagnosis was 59 years (range: 35 - 86), 59% were male. Patients were enrolled from North America (33%), Europe (35%) or Asia (32%). The patients were diagnosed between 1997 and 2011 and the median time to T0 from diagnosis was 23.9 months (range: 0.8 - 131.9 months). An IMiD (thalidomide or lenalidomide), bortezomib or alkylator (melphalan or cyclophosphamide) was part of the initial therapy in 63%, 36% and 51% of patients, respectively; 93 (33%) patients had stem cell transplantation as part of initial treatment. The median follow up from the study entry was 56 months; 117 were alive at the time of data extraction. A second line, third line and fourth line of treatment were recorded in 307, 163 and 84 patients respectively. An IMiD (thalidomide, lenalidomide, or pomalidomide), proteasome inhibitor (bortezomib or carfilzomib) or alkylator (melphalan or cyclophosphamide) was part of the therapy for first relapse in 50%, 59% and 33% of patients, respectively. The responses to the regimens after T0, the TTNT, PFS and OS to each line of therapy are provided in the Table. Conclusion: The current study provides an assessment of the current treatment approaches used for initial treatment of MM and the salvage treatment options utilized. The study again demonstrates the progressively shorter duration of disease control with each successive treatment regimen, reflecting ongoing development of drug resistance. The overall survival of over 3 years from the time of therapy for first relapse highlights the impact of the newer therapies that have been introduced for this disease. Table. Treatment outcomes after initial relapse Endpoint 2nd line therapyN=307 3rd line therapyN=163 4th line therapyN=84 Partial response or better Median in Months (95% Confidence Interval) Overall Survival 36.1 (30.2, 42.4) 18.4 (14.5, 26.8) 12.6 (10.4, 19.0) Progression-Free Survival 13.4 (11.8, 15.8) 8.3 (6.5, 11.2) 6.4 (5.0, 8.1) Time to Next Treatment 15 (12,17) 9.8 (7.4, 12.0) 6.6 (5.8, 8.7) Figure 1. Figure 1. Disclosures Kumar: Onyx: Consultancy, Research Funding; Skyline: Consultancy, Honoraria; BMS: Consultancy; Sanofi: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Novartis: Research Funding; Takeda: Consultancy, Research Funding; Celgene: Consultancy, Research Funding. Dimopoulos:Novartis: Honoraria; Amgen: Honoraria; Janssen-Cilag: Honoraria; Genesis: Honoraria; Janssen: Honoraria; Onyx: Honoraria; Celgene: Honoraria. Leleu:Janssen: Honoraria; Celgene: Honoraria; Takeda: Honoraria; Amgen: Honoraria; TEVA: Honoraria; Novartis: Honoraria; BMS: Honoraria; Pierre Fabre: Honoraria; LeoPharma: Honoraria; Chugai: Honoraria. Moreau:Celgene, Janssen, Takeda, Novartis, Amgen: Membership on an entity's Board of Directors or advisory committees. Lahuerta:Janssen Cilag, Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees. Vij:Takeda, Onyx: Research Funding; Celgene, Onyx, Takeda, Novartis, BMS, Sanofi, Janssen, Merck: Consultancy.

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.