Kumar, Shaji

Abstract Introduction: Histone lysine methylation, a reversible event dynamically and reciprocally regulated by lysine methyltransferases (KMTs) and demethylases (KDMs), represents one of the major epigenetic mechanisms for regulation of chromatin remodeling and gene expression re-programming. The KDM4 family, which belongs to the Jumonji C (JmjC)-domain-containing proteins (JMJDs), consists of five members, including KDM4A-E that demethylate H3K9me2/3 and/or H3K36me2/3 in a Fe2+- and α-ketoglutarate-dependent manner. KDM4 proteins are involved in various cellular processes such as gene transcription and translation, DNA replication, DNA repair, apoptosis, and stem cell renewal. Notably, increasing evidence implicates KDM4 dysregulation in promoting genomic instabilities and oncogenesis, thereby which is considered as a potential target for emerging cancer epigenetic therapy. Although KDM4A, a member of the KDM4 family, has been widely studied in many solid tumors including breast, prostate, bladder cancer, its role in hematopoietic malignancies, including multiple myeloma (MM), remains unknown. Materials and Methods: Human MM cell lines (U266, RPMI8226, H929, OPM-2) were employed. After exposed to hypoxia (or the chemical hypoxia mimetic lactic acid) and anti-MM agents (e.g., bortezomib/Btz), cells were analyzed by flow cytometry, qPCR, Western blot to monitor apoptosis, cell cycle, proliferation (Ki67), DNA double-strand break/DSB (γH2A.X), expression of 1q21 and anti-apoptotic genes, as well as activation of the NF-κB and HIF pathways. The shRNA approach was used to knock down KDM4A for functional evaluation. The findings from in vitro experiments involving cell lines were then validated in primary MM samples to link KDM4A expression to disease progression and therapeutic response. Results: Analysis of the MM genome-wide GEP databases revealed that KDM4A mRNA was significantly up-regulated in MGUS and MM, but not SMM, compared to normal control, as well as in relapsed MM, compared to newly-diagnosed MM. To our surprise, KDM4A expression rather favored overall survival of MM patients, including those carrying 1q21 gain in whom KDM4A expression was indeed lower than those who did not have this high risk cytogenetic abnormality. Moreover, KDM4A expression correlated adversely with expression of 1q21 genes (e.g., CKS1B, MCL1, PSMD4, ARNT). Whereas basal KDM4A protein level was moderately but clearly higher in MM cell lines carrying 1q21 gain or acquired drug resistance than their counterparts, exposure to hypoxia or lactic acid (but not cobalt chloride) resulted in marked KDM4A up-regulation, accompanied by NF-κB and HIF pathway activation. However, while NF-κB inhibition and to a lesser extent ARNT/HIF-1β knockdown led to a robust increase in hypoxia-induced KDM4A expression, shRNA knockdown or pharmacological inhibition of KDM4A triggered NF-κB activation and HIF expression, as well as up-regulated anti-apoptotic proteins (e.g., Mcl-1, TNFAIP3/A20, CKS1B), in association with increased H3K36me3 rather than H3K9me3. Furthermore, KDM4A knockdown or inhibition sharply diminished Btz lethality and overrode hypoxia-mediated cytoprotection. Interestingly, KDM4A knockdown also increased MM cell proliferation, promoted S phase entry, and attenuated Btz-induced DSB. Last, IHC of sequential bone marrow biopsies revealed that while KDM4A protein was relatively low at diagnosis, its level was markedly increased when patients achieved CR and then fell to the baseline low level at relapse. Conclusion: KDM4A/JMJD2A, a lysine demethylase that has been recognized as an pro-oncogenic protein via its epigenetic and/or non-epigenetic properties, is identified for the first time as a potential tumor suppressor in MM, particularly in a high risk subtype carrying 1q21 gain. Whereas KDM4A is expressed in MM and can be further induced by hypoxia that naturally exists in bone marrow niche, it seems to play multiple inhibitory roles in cell growth, cell cycle, DNA repair, and drug resistance by suppressing expression of oncogenic and anti-apoptotic genes (especially 1q21 genes), likely via H3K36me3 demethylation, and antagonizing NF-κB and HIF activation. These findings suggest that in contrast to its pro-oncogenic role in certain solid tumors, KDM4A might instead act as a tumor suppressor in MM. This work was supported by NNSFC (81471165, 81670189, and 81670190). Disclosures Kumar: AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding.

Abstract Introduction Development of anti-CD38 monoclonal antibody therapies (MoABs), including daratumumab and isatuximab, have drastically changed the therapeutic landscape for management of relapsed and/or refractory multiple myeloma (RRMM). However, there is a paucity of information regarding response to treatment after progression on CD38 MoABs. This collaborative research study (MAMMOTH: Monoclonal Antibodies in Multiple Myeloma: Outcomes after Therapy Failure) investigates the therapeutic choices and outcomes of subsequent treatments after refractoriness to MoABs. Methods Patients from 14 US academic institutions with diagnosis of MM and refractory to daratumumab or isatuximab, administered alone or in combination, were evaluated. Patients were considered refractory to a CD38 MoAB if treated with at least 4 weeks of therapy and had evidence of progressive disease (PD) while on therapy or within 60 days after last dose. Time of progression was defined as time zero (T0). Data was collected by electronic platform and submitted to peer-based quality check for completeness and internal consistency. Results Two hundred and seventy-five patients with MM refractory to CD38 MoAB were evaluated; 249 (90.5%) of those patients who received at least one subsequent line of therapy were included in this analysis. The median age at T0 was 65 years (range 27-90) and 54% were male. At the time of diagnosis, 28% had ISS stage III disease and 29% had high-risk cytogenetics. Patients were heavily pre-treated at T0 with a median of 5 lines of therapy (range 2-17); most (74%) underwent a prior autologous stem cell transplant. The majority of patients were refractory to other anti-myeloma therapies including lenalidomide (78%), pomalidomide (65%), bortezomib (69%) and carfilzomib (45%). In total, 97.1% of patients were exposed to at least one immunomodulatory agent (IMiD) and one proteasome inhibitor (PI), 79.3% were ≥ triple-refractory (refractory to 1 IMiD, 1 PI and 1 CD38 MoAB), while 25.3% were penta-refractory (refractory to 2 IMiDs, 2 PIs and 1 CD38 MoAB). Responses to the next subsequent line of therapy after progression with CD38 MoAB are shown (Table). The overall response rate (ORR; ≥PR) of first regimen post-T0 was 31% with a median progression free survival (PFS) of 3.4 mo and median overall survival (OS) of 9.3 mo. Carfilzomib-based therapy resulted in an ORR of 32% with median PFS 4.2 mo and overall OS of 10.9 mo. The addition of an IMiD to daratumumab yielded an ORR of 37% with median PFS 4.5 mo and OS 12.6 mo. The addition of a PI to daratumumab yielded no responses. Elotuzumab-based therapy had an ORR of 21% with median PFS 2.6 mo and OS 8.3 mo. By multivariate analysis, alkylator-based therapies were found to have the highest ORR (OR 3.1, 95% CI 1.8-5.7, p<0.001), however, resulted in median PFS of only 3 mo and OS of 7.7 mo. Multivariate analysis evaluating for PFS and adjusting for refractoriness to prior therapies found lower risk of progression with carfilzomib-based therapy (HR 0.60, 95% CI 0.42-0.85, p=0.004, Figure 1) and with the addition of an IMiD to daratumumab (HR 0.64, 95% CI 0.43-0.94, p=0.02). The benefit of IMiD + daratumumab was essentially restricted to patients previously refractory to CD38 MoAB as monotherapy. These patients demonstrated improved PFS with subsequent daratumumab-combination therapy at time of progression compared with patients refractory to CD38 MoAB combination therapy (log-rank p=0.02, Figure 2). No particular regimen was associated with improved OS compared with the rest. Conclusions After progression on CD38 MoAB, treatment with carfilzomib-based regimens and the addition of an IMiD to daratumumab-monotherapy resulted in a higher ORR and PFS compared with other regimens. Alkylating agents resulted in the highest ORR but relatively short PFS and OS. The use of elotuzumab and the addition of a PI to daratumumab monotherapy resulted in relatively low response rates. Overall, progression after CD38 MoAB therapy is associated with a poor prognosis and innovative therapeutic strategies are needed. Disclosures Malek: Celgene: Consultancy, Speakers Bureau; Amgen: Consultancy, Speakers Bureau; Takeda: Consultancy, Speakers Bureau; Janssen: Consultancy, Speakers Bureau; Sanofi: Consultancy, Speakers Bureau. Paul:Bristol Myer Squibb: Other: Stock and pension plan (past employee). Neppalli:Celgene: Consultancy; Amgen: Consultancy. Liedtke:Amgen/Onyx: Consultancy, Honoraria, Research Funding; Caelum: Membership on an entity's Board of Directors or advisory committees; Genentech/Roche: Research Funding; Gilead: Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Prothena: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; celgene: Research Funding; BlueBirdBio: Research Funding; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Hari:Takeda: Consultancy, Honoraria, Research Funding; Spectrum: Consultancy, Research Funding; Kite Pharma: Consultancy, Honoraria; Sanofi: Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Amgen Inc.: Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding; Janssen: Honoraria. Vij:Bristol-Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Jazz Pharmaceuticals: 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, Research Funding; Jansson: Honoraria, Membership on an entity's Board of Directors or advisory committees; Karyopharma: 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; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Usmani:Amgen, BMS, Celgene, Janssen, Merck, Pharmacyclics,Sanofi, Seattle Genetics, Takeda: Research Funding; Abbvie, Amgen, Celgene, Genmab, Merck, MundiPharma, Janssen, Seattle Genetics: Consultancy. Costa:Amgen: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; BMS: Research Funding; Abbvie: Research Funding; Janssen: Research Funding; Karyopharm: Research Funding; Sanofi: Honoraria. Kumar:Roche: Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding.

Abstract History of prior cancer is a widespread exclusion criterion in cancer trials. Up to 80% of NCI-sponsored and 80% of industry-sponsored lung cancer trials exclude patients with a prior cancer. We suspect this exclusion is commonly applied in other cancer trials, although no definitive data exist. Prior cancer is especially common among older patients and those with certain cancer types. Among patients >65 years, 15.1% overall have prior cancer. In Multiple Myeloma, the most common plasma cell disorder (PCD), prevalence of prior cancer is as high as 17.4%. Examining the prior cancer exclusion criterion is important because the number of US cancer survivors is large and rapidly growing. Arbitrarily excluding cancer survivors from trials is not evidence-based and exclusion presumably arises from assumptions that higher mortality of patients with prior cancer could hinder study conduct and bias trial outcomes. However, few data exist to support this assumption of higher mortality. In fact, we demonstrated that lung cancer patients with a prior cancer have similar or lower mortality risk, compared to those without prior cancer. In this abstract, we reviewed prior cancer related eligibility criteria in three of the most common PCD (Multiple Myeloma, Amyloidosis and Waldenström Macroglobulinemia) clinical trials sponsored or endorsed by 5 major Co-Operative groups in North America (Table 1). We use descriptive statistics (n, %) and Fisher's exact tests to describe characteristics of trials with and without exclusion criteria. Of 33 trials, 26 (79%) excluded patients with prior cancer as follows - active cancer (12%), within 2-3 years of PCD diagnosis (9%), or within 5 years of PCD diagnosis (55%). Many trials had exceptions to prior cancer exclusion. Specifically, 67% of trials allowed non-melanoma skin cancer, 58% allowed in-situ cervical cancer, 12% allowed early stage prostate cancer. Table 2 shows the association between clinical trial characteristics and prior cancer exclusion. There was no association between prior cancer exclusion and phase of study, transplant studies, or survival end point. Exclusion criteria varied across year of activation (p=0.01); for example, 75% of studies activated 1990-1999 excluded prior cancer, compared to 100% of studies activated after 2010. Type of PCD was marginally associated with exclusion criteria (p=0.08); 74% of Multiple Myeloma trials excluded patients with prior cancer compared to 100% of the Amyloidosis and Waldenström Macroglobulinemia trials. Conclusion: A substantial proportion of potential participants may be excluded from PCD clinical trials because of a history of prior cancer. This practice impacts accrual, generalizability, and fair access to cutting-edge treatments and the highest level of clinical care. As treatment outcomes for other cancers continue to improve, it is likely that the prevalence of multiple primary cancers will increase. This exclusion criterion is applied widely across studies, including more than two-thirds of those with non-survival endpoints. Our study is the first to examine the prevalence and potential impact of prior cancer exclusion in PCD clinical trials. Using population-based cancer registry data, we plan to undertake further research to understand the appropriateness and ramifications of this standard exclusion policy in PCD cancer trials. Disclosures Collins: Agios: Research Funding; Bristol Myers Squibb: Research Funding; Celgene Corporation: Research Funding; Arog Pharmaceuticals: Research Funding. Devine:Kiadis Pharma: Consultancy. Usmani:Amgen, BMS, Celgene, Janssen, Merck, Pharmacyclics,Sanofi, Seattle Genetics, Takeda: Research Funding; Abbvie, Amgen, Celgene, Genmab, Merck, MundiPharma, Janssen, Seattle Genetics: Consultancy. Anderson:Amgen: Speakers Bureau; Takeda: Speakers Bureau; Celgene: Speakers Bureau. Kumar:Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees; Roche: Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding.

Abstract INTRODUCTION: Traditional cytometry methods have been unable to capture the immense heterogeneity of the tumor immune microenvironment in various malignancies including multiple myeloma (MM). Cytometry by time of flight (CyTOF) can, to some extent, overcome this limitation. However, the computational challenges that come with analyzing these complex datasets in a reproducible manner remain. In this study, using a large cohort of patients, we compare the bone marrow immunomes from patients with MGUS, multiple myeloma (MM), smoldering MM (SMM) and light chain amyloidosis (AL) at diagnosis, after induction therapy with lenalidomide and dexamethasone and after autologous transplant (ASCT). METHODS: We studied a total of 118 cryopreserved samples as follows: 14 healthy donors, 43 AL (27 newly diagnosed-ND, of which 13 with <10% bone marrow plasma cells, 16 matched samples post ASCT), 12 with ND MGUS, 11 with SMM (of which 6 were ND), 14 with ND MM, 13 paired MM samples post induction therapy and 11 paired MM samples post ASCT. Our CyTOF surface staining panel included the following 33 markers: CD45, HLA-DR, CD19, CD3, CD4, CD8, CD14, CCR6, CD11a, Cd123, CCR5, CD7, ICOS, CD25, CD57, CD45RA, CD163, PD-1, PDL-1, CXCR3, CCR4, CCR7, CD28, CTLA4, CD11c, CD56, CD45RO, CD44, CD27, CD138, CD38, CD-127 and CD16. Data processing and analysis was performed using Cytobank. Live cells were identified based on Pt195 and Ir193 staining. Myeloma cells and CD45- cells were excluded and only CD45+ cells were used for subsequent analyses. Single-cell data were downsampled using VisNE, a permutation of t-Distributed Stochastic Neighbor Embedding (tSNE) and clustered using CITRUS (using 10,000 events per sample with a minimum cluster size of 1%). A Significance analysis of microarrays (SAM) analysis was performed to ascertain differences between groups. Significance was inferred for a false discovery rate <1% . All CITRUS analyses were repeated at least 3 times and only clusters found to differ consistently across runs were considered. RESULTS: The proportions of immune subsets identified to vary by CITRUS before and after induction therapy and ASCT for MM and AL are shown in the table. No differences were identified between MGUS, SMM and NDMM. The proportion of a subset (369850) of CD14+/C16- monocytes, a group of cells shown to correlate positively with survival and response to therapy in solid malignancies, increased after induction therapy in MM. Naïve B cells increased dramatically post ASCT in both AL (429918) and MM (369948), consistent with expected immune reconstitution patterns, although a CCR6+ B Cell subset (429940) shown to mediate effective antibody responses, decreased (in grey). A subset (369980) of functionally exhausted (PD1/CTLA4+) central memory (CM) CD4 T cells decreased after induction therapy in MM but recovered early post ASCT whereas a CM CD4+ subset (369986) lacking major activation markers (CD28, CD25) decreased gradually with therapy and post ASCT. A subset (369953) of naïve CD8 T cells shown to be actively recruited in tumor sites (CXCR3+) decreased after ASCT. CD57+ senescent effector memory (EM) CD8 T cells (369962) decreased with induction therapy but recovered post ASCT. EM CD8 T cells associated with long term immune memory (CCR5+, CD127+, cluster 369959), also decreased after ASCT. LIMITATIONS: Include a) No barcoding b) batch effects were difficult to avoid when processing large number of samples c) use of cryopreserved samples d) need for downsampling to cope with the computational burden. The latter could have been one of the reasons we did not identify any differences between MGUS, SMM and MM. At the time of the meeting we will present confirmatory analyses using conceptually different methods of clustering and of performing across group comparisons as well as analyses that do not include downsampling. CONCLUSIONS: Mass cytometry can provide a more granular view of the bone marrow immunome in plasma cell dyscrasias. Novel agent induction therapy can create an immunologically favorable anti-tumor microenvironment although, in some cases, these favorable immunomic shifts are temporarily reversed by ASCT. Confirmatory analyses, baseline immune profiles, comparisons with healthy donors and correlation with other clinically relevant patient characteristics and outcomes will be reported at the meeting. Disclosures Dispenzieri: Celgene, Takeda, Prothena, Jannsen, Pfizer, Alnylam, GSK: Research Funding. Kumar:Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding.

Abstract Introduction. Efficacy and safety of daratumumab monotherapy (DARA mono) in relapsed/refractory multiple myeloma (rrMM) has been shown in the single-arm phase I/II trial GEN501 and the single-arm phase II trial SIRIUS (1, 2). Since then, several indirect treatment comparisons of DARA mono versus comparator therapies have been published showing consistent results with an overall survival benefit for DARA mono (3, 4, 5, 6). This analysis compares efficacy and for the first time also safety of DARA mono data versus an international historic control group, adjusting for differences in patient populations based on individual patient level data (IPD). Methods. IPD from the SIRIUS trial and from the International Myeloma Foundation (IMF)-cohort (7), a retrospective, multicenter cohort, were compared using a multivariate Cox proportional hazards model, on the endpoints of efficacy (overall survival (OS)) and safety (discontinuation due to adverse events (DISCONAE)). The IMF-cohort included patients with rrMM who received at least three prior lines of therapy, were refractory to both an immunomodulator (IMiD) and a proteasome inhibitor (PI), and were exposed to an alkylating agent. An inclusion criterion for the historic control group in this analysis was treatment with EU approved regimens. Baseline covariates adjusted for in the regression model included age, gender, prior lines of therapy, albumin, beta-2 microglobulin, prior exposure to pomalidomide and carfilzomib, and PI/IMiD refractory status. Several sensitivity analyses were run, including multiple imputation of missing values. Results. Data from 106 patients treated with DARA mono (16 mg/kg) were available from SIRIUS; 258 patients from the IMF chart review fulfilled the inclusion criteria; most frequent treatment regimens contained pomalidomide plus dexamethasone (PomDex) (n=172), bortezomib (n=31), carfilzomib (n=21), cyclophosphamide (n=14) and lenalidomide (n=9). The adjusted HR for OS was 0.41 [0.25, 0.69], p<0.001, and 0.23 [0.05, 1.00], p=0.050 for DISCONAE, in favor of daratumumab. Results were consistent across a range of sensitivity analyses and were similar when restricting the comparison to DARA vs. PomDex, with HR=0.35 [0.19, 0.64], p<0.001 for OS and 0.20 [0.03, 1.54], p=0.123 for DISCONAE. Conclusions. This comparison using real-world data of rrMM patients suggests improved efficacy and safety for DARA mono compared to approved therapy regimens used in clinical practice, including PomDex. References. Lokhorst, H. M., Plesner, T., Laubach, J. P., Nahi, H., Gimsing, P., Hansson, M., et al. Targeting CD38 With Daratumumab Monotherapy in Multiple Myeloma. The New England Journal of Medicine. 2015. Lonial S, Weiss BM, Usmani SZ, Singhal S, Chari A, Bahlis NJ, et al. Daratumumab Monotherapy in Patients with Treatment-Refractory Multiple Myeloma (SIRIUS): An Open-Label, Randomised, Phase 2 Trial. The Lancet. 2016. Usmani S, Ahmadi T, Ng Y, Lam A, Desai A, Potluri R, Mehra M. Analysis of Real-World Data on Overall Survival in Multiple Myeloma Patients With ≥3 Prior Lines of Therapy Including a Proteasome Inhibitor (PI) and an Immunomodulatory Drug (IMiD), or Double Refractory to a PI and an IMiD. The Oncologist. 2016. Van Sanden S, Ito T, Diels J, Vogel M, Belch A, Oriol A. Comparative Efficacy of Daratumumab Monotherapy and Pomalidomide Plus Low-Dose Dexamethasone in the Treatment of Multiple Myeloma: A Matching Adjusted Indirect Comparison. The Oncologist. 2017. Usmani SZ, Diels J, Ito T, Mehra M, Khan I, Lam A. Daratumumab monotherapy compared with real-world historical control data in heavily pretreated patients with highly refractory multiple myeloma: An adjusted treatment comparison. American Journal of Heamtology. 2017. Jelínek T, Maisnar V, Pour L, Špička I, Minařík J, Gregora E, et al. Adjusted comparison of daratumumab monotherapy versus real-world historical control data from the Czech Republic in heavily pretreated and highly refractory multiple myeloma patients. Current Medical Research an Opinion. 2017. Kumar SK, Dimopoulos MA, Kastritis E, Terpos E, Nahi H, Goldschmidt H, et al. Natural history of relapsed myeloma, refractory to immunomodulatory drugs and proteasome inhibitors: a multicenter IMWG study. Leukemia. 2017. Disclosures Demmer: Janssen: Employment. Huschens:Janssen: Employment. Potthoff:Janssen: Employment. Tomeczkowski:Janssen: Employment. Englisch:Janssen: Employment. Thilakarathne:Janssen: Employment. Diels:Janssen: Employment. Kumar:AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche: Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; Novartis: Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding. Durie:Celgene: Consultancy; Amgen: Consultancy; Takeda: Consultancy; Janssen: Consultancy. Eisele:Janssen: Employment.

Abstract Background: Limited data exist regarding histological transformation in patients with Waldenström macroglobulinemia (WM). In this study, we present the disease characteristics, outcomes and risk factors for histological transformation in WM. Methods: Patients with WM seen at Mayo Clinic, Rochester, MN between January 1996 and December 2017 were included. Patients with aggressive non-Hodgkin lymphoma in the setting of WM were considered to have transformation. Univariate analysis for comparing baseline characteristics of transformed versus non-transformed WM was performed using Wilcoxon, Fisher's exact and Chi square tests, as appropriate. Multivariate analysis was performed using logistic regression analysis. Cox proportional hazard method was used to assess the impact on time-to-transformation. All time-to-event analyses were calculated by the Kaplan-Meier method. Results: Of 1014 patients with WM, 42 patients (4.1%) developed histological transformation. The median follow-up for the entire cohort was 9.5 years (95% CI: 8.8-10.5 years). The cumulative probability of transformation was 2.3% at 5 years, 5.3% at 10 years and 8.5% at 15 years from diagnosis of WM, respectively. There was no difference in the 5-year cumulative probability of transformation in patients with WM diagnosed between 1996-2000 (2.1%), 2001-2005 (2.9%), 2006-2010 (2.7%) and 2011-2015 (3.8%), p=0.61.The disease characteristics, laboratory parameters and histology at transformation are outlined in Table 1. In patients with DLBCL histology (n=39), Revised-International Prognostic Index was calculable in 28 patients, with 50% (n=14), 46% (n=13) and 4% (n=1) of DLBCL belonging to poor, good and very good risk groups, respectively. For DLBCL histology, 18 patients were classifiable using Hans algorithm into germinal center B-cell (GCB) type (n=3, 17%) and non-GCB type histology (n=15, 83%). The median lines of therapy received prior to transformation for the entire cohort was 2 (range 0-9), with 5 (11%) patients not having received any therapy for WM before transformation. Number of lines of alkylator-based therapy used prior to transformation [median 1 line (range 0-4)] was comparable to that used in patients in whom WM did not occur [median 1, (range 0-6); p=0.78]. The median time-to-transformation from diagnosis of WM was 4.8 years (95% CI: 2.6- 6.8 years). Overall survival (OS) from transformed disease was 3.2 years (95% CI 1.1-3.9 years). The 10-year OS of patients with WM who transformed was lower (46%) compared to patients without transformation (60%) with a trend towards statistical significance (p=0.08), Figure 1. The MYD88L265P mutation status was available in 333 patients in the entire cohort (22/42 pts in the transformed cohort and 311/972 in the non-transformed cohort. Of the 22 patients in the transformed WM cohort, 13 (59%) exhibited MYD88WT genotype and 9 (41%) exhibited MYD88L265P genotype. The risk of transformation was higher in patients with MYD88WT status [Odds ratio 6.3 (95% CI: 2.6-15.5); p<0.0001]. Additionally, serum lactate dehydrogenase (LDH) was higher at diagnosis of WM in patients who transformed, Table 2. On multivariate analysis, MYD88WT status remained an independent predictor of disease transformation [p=0.003; odds ratio 10 (95% CI: 2.1-48)]. On univariate Cox proportional hazard analysis for identifying predictors of time-to-transformation, only MYD88WT mutational status was associated with shorter time-to-transformation with a 5-year transformation rate of 15.5 % for MYD88WT versus 2.6 % with MYDL265P mutated patients [risk ratio 6.2 (95% CI: 2.5-16.4); p<0.0001]. Treatment-related details in the transformed cases were available for 37 (90%) patients; R-CHOP was the most common (41%) frontline therapy for transformation; 33% patients underwent autologous stem cell transplantation for transformed disease during their disease course. Conclusion: Histological transformation is an uncommon event in WM but confers poorer survival. MYD88WT genotype is independently associated with histological transformation a shorter time-to- transformation in patients with WM. Disclosures Ansell: Trillium: Research Funding; Pfizer: Research Funding; LAM Therapeutics: Research Funding; Seattle Genetics: Research Funding; Affimed: Research Funding; Takeda: Research Funding; Celldex: Research Funding; Regeneron: Research Funding; Merck & Co: Research Funding; Bristol-Myers Squibb: Research Funding. Gertz:Apellis: Consultancy; Alnylam: Honoraria; spectrum: Consultancy, Honoraria; janssen: Consultancy; annexon: Consultancy; Prothena: Honoraria; Abbvie: Consultancy; Amgen: Consultancy; celgene: Consultancy; Teva: Consultancy; Medscape: Consultancy; Ionis: Honoraria; Research to Practice: Consultancy; Physicians Education Resource: Consultancy. Dingli:Millennium Takeda: Research Funding; Millennium Takeda: Research Funding; Alexion Pharmaceuticals, Inc.: Other: Participates in the International PNH Registry (for Mayo Clinic, Rochester) for Alexion Pharmaceuticals, Inc.; Alexion Pharmaceuticals, Inc.: Other: Participates in the International PNH Registry (for Mayo Clinic, Rochester) for Alexion Pharmaceuticals, Inc.. Witzig:Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Dispenzieri:Celgene, Takeda, Prothena, Jannsen, Pfizer, Alnylam, GSK: Research Funding. Lacy:Celgene: Research Funding. Kumar:Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees; Novartis: Research Funding; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding. Kapoor:Takeda: Research Funding; Celgene: Research Funding.

Abstract Introduction Proteasome inhibitors (PIs) and immunomodulatory drugs (IMiDs) have significantly improved survival in patients with multiple myeloma (MM). Refractoriness to PIs and IMiDs results in poor outcomes with a median survival of about 13 months.Daratumumab and isatuximab are CD38-targeting monoclonal antibodies (MoABs) with remarkable activity in relapsed and refractory MM. The outcome of MM patients in US clinical practice who becomes refractory to CD38 MoABs is unknown. The aim of this multicenter, retrospective study is to investigate the natural history of patients with MM who become refractory to CD38 MoABs (Monoclonal Antibodies in Multiple Myeloma: Outcomes after Therapy Failure: MAMMOTH study). Methods We identified patients from 14 academic institutions in the US with diagnosis of active MM and refractory to daratumumab or isatuximab, administered alone or in combination. Patients were considered refractory to CD38 MoAB if treated with at least 4 weeks of therapy and had evidence of progressive disease (PD) while on therapy or within 60 days after last dose. The time when patients met the above criteria of progression was defined as time zero (T0). Data including patient-disease characteristics and all therapies administered before and after T0 were collected with an electronic platform and submitted to peer-based quality check for completeness and internal consistency. For survival outcome analysis, patients were classified into three groups: "Penta-refractory" (refractory to 1 CD38 MoAB + 2 PIs + 2 IMiDs), "Triple-refractory and quad-refractory" (refractory to 1 CD38 MoAB + 1 PI + 1/2 IMiDs, or 1 CD38 MoAB + 1/2 PIs + 1 IMiD), and "Not triple-refractory" (refractory to 1 CD38 MoAB, and not both of a PI and an IMiD). Responses were evaluated using the IMWG criteria. Results Two hundred and seventy-five patients were included in this study; median age at T0 was 65 years (range 27-90). Fifty five percent of patients were males, 52% had IgG isotype, 29% had ISS stage III disease, and 29% had high-risk cytogenetics at diagnosis. Median interval from diagnosis of MM to T0 was 50.1 months (mo) (range 2.5-230.1). Patients received a median of 4 lines of treatment (1-16) prior to the CD38 MoAB-containing regimen; 72% underwent prior autologous transplant. Daratumumab-refractory patients formed a majority (256, 93.1%) of this cohort. Most of the patients were refractory to lenalidomide (77%), pomalidomide (65%), bortezomib (68%), and carfilzomib (47%). Seventy patients (25.5%) were "penta-refractory" and 148 (53.8%) were "triple-refractory and quad-refractory". Median follow-up from T0 for survivors was 10.6 mo (range 1.9-42.3 mo). The median overall survival (OS) from T0 for the entire cohort was 8.6 mo (95% C.I. 7.2-9.9); OS for the groups based on refractoriness to prior treatments are shown (Figure). Two hundred and forty-nine patients (90.5%) received at least one line of treatment after T0, (median 2, range 1-10). The response rates and depth of responses to each line of treatment post T0 are shown (Table). Among patients who received ≥ 1 subsequent treatment, the median PFS and OS from T0 were 3.4 (95% C.I. 2.8-4.0) mo and 9.3 (95% C.I. 8.1-10.6) mo, respectively; the median OS for the 26 patients who received no further treatment was only 1.3 (95% C.I. 0.6-1.9) mo. By multivariate analysis, penta-refractoriness (HR 2.4, p <0.001), high-risk cytogenetics (HR 1.5, p=0.01), elevated LDH (HR 2, p<0.001) and creatinine > 2 (HR 2.4, p=0.01) at the onset of CD38-based therapy predicted inferior OS. Conclusions Patients with MM who become refractory to CD38 MoAB are increasingly less responsive to subsequent therapies. While survival is particularly dismal for penta-refractory patients, the outcomes are poor even for patients who are not refractory to other mainstream MM agents. The MAMMOTH study defines a MM population in urgent need for new therapies, and provides benchmark OS, PFS and response data for subsequent investigational therapies in this setting. Disclosures Malek: Celgene: Consultancy, Speakers Bureau; Janssen: Consultancy, Speakers Bureau; Takeda: Consultancy, Speakers Bureau; Sanofi: Consultancy, Speakers Bureau; Amgen: Consultancy, Speakers Bureau. Paul:Bristol Myer Squibb: Other: Stock and pension plan (past employee). Neppalli:Amgen: Consultancy; Celgene: Consultancy. Liedtke:Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Prothena: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen/Onyx: Consultancy, Honoraria, Research Funding; BlueBirdBio: Research Funding; celgene: Research Funding; Takeda: 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; Genentech/Roche: Research Funding; Caelum: Membership on an entity's Board of Directors or advisory committees. Hari:Amgen Inc.: Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Spectrum: Consultancy, Research Funding; Kite Pharma: Consultancy, Honoraria; Bristol-Myers Squibb: Consultancy, Research Funding; Sanofi: Honoraria, Research Funding; Janssen: Honoraria; Takeda: Consultancy, Honoraria, Research Funding. Vij: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, Research Funding; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol-Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Karyopharma: Honoraria, Membership on an entity's Board of Directors or advisory committees; Jansson: Honoraria, Membership on an entity's Board of Directors or advisory committees; Jazz Pharmaceuticals: Honoraria, Membership on an entity's Board of Directors or advisory committees. Usmani:Abbvie, Amgen, Celgene, Genmab, Merck, MundiPharma, Janssen, Seattle Genetics: Consultancy; Amgen, BMS, Celgene, Janssen, Merck, Pharmacyclics,Sanofi, Seattle Genetics, Takeda: Research Funding. Kumar:Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding. Costa:Karyopharm: Research Funding; Sanofi: Honoraria; Janssen: Research Funding; BMS: Research Funding; Abbvie: Research Funding; Amgen: Honoraria, Research Funding; Celgene: Honoraria, Research Funding.

Abstract From 2013-2017, numerous new approvals and expanded indications have dramatically changed the treatment (tx) landscape for MM. Since that time, experienced MM physicians from leading academic institutions and cancer centers (experts) have annually updated and contributed tx recommendations for an online decision support tool designed to provide healthcare providers (HCPs) with patient-specific tx guidance. This MM tool is freely available online at www.clinicaloptions.com/myelomatool and HCPs can use the tool to enter details of a patient case, indicate their intended tx plan, and then expert tx recommendations for that case are provided. Methods This study includes analysis of tx recommendations from 5 MM experts for 270 unique MM case scenarios made during development of the 2018 update to this tool. We also aim to compare the evolving tx recommendations among the experts over time, from 2013-2017, and to determine practice patterns of HCPs using the tool over the same time span. Results Based on analysis of these annually updated MM tools, consensus (≥ 3 of 5 experts choosing the same tx for the same case) among experts has been increasing for induction tx since 2013. In ASCT-eligible patients with no specific comorbidities, experts recommended bortezomib/lenalidomide/dexamethasone (VRd) in 100% and 90% of tool cases in 2018 and 2017, respectively, which increased from 65% to 75% consensus in 2013-2015. In previous analyses, the percentage of HCPs using VRd has also increased, albeit more slowly than with experts. In 2017, 42% of HCPs indicated that they are using VRd as induction in this setting compared with 22% in 2015-2016 and 9% in 2014-2015. For ASCT-ineligible patients with ECOG > 2 but no specific comorbidities, all 5 experts recommend triplet therapy for all cases regardless of risk in 2018, but in 2017, 3 of 5 recommended triplet therapy and 2 of 5 recommended doublets for normal-risk disease. Expert recommendations for induction change, however, based on specific patient comorbidities. For patients with peripheral neuropathy, 4 of 5 experts recommended carfilzomib/lenalidomide/dexamethasone instead of VRd. For patients with renal insufficiency, 4 of 5 experts recommended bortezomib/cyclophosphamide/dexamethasone. For patients with cardiac dysfunction, all 5 experts continue to recommend VRd for patients with ECOG ≤ 2 while 2 of 5 change from VRd to Rd for patients with ECOG > 2. For patients who achieve VGPR or better to induction, all 5 experts recommend lenalidomide maintenance for standard risk disease. But for patients with high risk disease who achieve VGPR or better to induction, 3 of 5 experts recommend bortezomib/lenalidomide combination maintenance therapy regardless of induction regimen, 1 expert recommends single-agent bortezomib regardless of induction regimen, and 1 expert recommends bortezomib after a PI-based induction regimen or lenalidomide for an IMiD or IMiD/PI-based induction regimen. In the 2018 tool update, the number of R/R case scenarios with 100% expert consensus increased over previous years: 20% of cases had all 5 experts agreeing on tx vs 12% in 2017. In addition, 29% of cases had 3 of 5 experts agreeing and 8% had 2 pairs of experts agreeing in 2018 vs none with 3 of 5 experts agreeing and 21% with 2 pairs of experts agreeing in 2017. In 2018, experts recommended daratumumab/pomalidomide/dexamethasone all cases with 100% consensus, which comprises patients who are refractory to multiple agents including lenalidomide, bortezomib, and/or carfilzomib. Overall, 23 different regimens were recommended for R/R MM; and additional majority expert consensus included daratumumab/lenalidomide/dexamethasone, daratumumab/carfilzomib/dexamethasone, and carfilzomib/pomalidomide/dexamethasone (Table 1). Conclusions Practice patterns are changing rapidly and are more complex, particularly in the R/R setting, in response to the evolving tx landscape for MM. This analysis highlights several areas of expert consensus, but disparities remain for select cases. The newest approved therapies continue to have a strong impact on experts' recommendations as they have been fully integrated into their tx approaches. These analyses provide a real-time assessment of changing tx patterns among experts as well as HCPs. We will present analyses of cases entered in the 2018 online tool by HCPs and detailed comparisons of expert and the intended tx of clinicians using the tool. Disclosures Ghobrial: Takeda: Consultancy; Janssen: Consultancy; Celgene: Consultancy; BMS: Consultancy. Lonial:Amgen: Research Funding. Raje:Research to Practice: Honoraria; Takeda: Consultancy; AstraZeneca: Research Funding; Celgene: Consultancy; BMS: Consultancy; Merck: Consultancy; Janssen: Consultancy; Amgen Inc.: Consultancy; Medscape: Honoraria. Kumar:Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche: Research Funding; Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding.

Abstract Introduction Multiple myeloma (MM) is a result of a malignant transformation of plasma cells that is preceded by the presence of an asymptomatic clonal plasma cell expansion, a condition referred to as monoclonal gammopathy of undetermined significance (MGUS). We and others have shown familial aggregation of MM and MGUS. Evidence from epidemiologic, family and genome-wide association studies (GWAS) suggests a genetic component underlying MM etiology. GWAS have successfully established 17 common genetic risk loci for MM to date and recently, rare inherited susceptibility variants in the LSD1 / KDM1A and USP45 genes were identified in familial MM / MGUS kindreds. Family-based approaches may be used to elucidate genetic variation contributing to familial MM. Genetic linkage analysis has historically been used to detect the chromosomal location of disease genes. The objective of this study was to conduct a linkage analysis of MM / MGUS families to identify genomic regions for MM / MGUS. Methods Linkage analysis was performed on whole exome sequencing (WES) data generated from germline DNA extracted from peripheral blood from MM / MGUS families ascertained at four sites, of which 79 were selected with 2 or more affected members with any combination of MM or MGUS. Whole exome capture was performed using Agilent SureSelect 38 Mb paired end sequencing and ran on Illumina HiSeq 2000s/2500s; standard analyses for alignment (GRCh37) and quality control were conducted. The Genome Analysis Toolkit's (GATK) HaplotypeCaller in per-sample mode was used to jointly call all the samples together. Quality control included removing variants that had <75% call rate, <8x coverage, or minor allele frequency <0.01 (1KGenomes). The jointly called WES data from the 79 families consisted of 230 individuals, including 119 MM, 93 MGUS and 18 unaffected relatives. Additional early onset (defined as age <60) MM cases (n=400), sporadic MM cases (n=879) and controls (n=2389) were also included in the joint calling to be used for follow-up of linkage regions. We included independent variants defined as linkage disequilibrium (LD) r2 <0.05 using both PLINK 1.07's LD based variant pruner and also MERLIN's pairwise r2 cluster marker-marker modeling to ensure variant independence. After quality control and LD filtering: 12,946 variants remained. We conducted multipoint linkage analysis using MERLIN (Multipoint Engine for Rapid Likelihood Inference using the Lander-Green approach) and considered both non-parametric and parametric (dominant and recessive) models to test for co-segregation of chromosomal regions with MM / MGUS. A logarithm of the odds (LOD) score greater than 3.3 was significant evidence for linkage. Within the same families, we interrogated any suggestive regions by performing gene-level association tests using the PEDGENE R package to calculate burden and kernel statistics, accounting for family relationships. Follow-up of these genes in the early onset and sporadic MM cases and controls and interrogation of single variants driving the associations of these genes is ongoing. Results Among the 79 families, 28 consisted of two or more MM, 41 had two or more MM and MGUS cases and 10 had two or more MGUS. Analyses of the 79 MM / MGUS families identified chromosome 6 at 123420001-149070000 BP region, with evidence for linkage by the non-parametric model (LOD score=3.3) and supportive evidence for linkage by the dominant parametric model (LOD=2.5) (Figure). The chromosome 6 region, which is outside the HLA-region, contains a total of 72 genes. Using gene-level association tests, we identified four genes within the region (MOXD1, TRDN, ADAT2, LTV1) that were associated within MM / MGUS in the family cases (p<0.05). Discussion We found evidence for a locus on chromosome 6 linked to MM / MGUS. Four genes in this region may be associated with MM / MGUS in these families. Follow-up of these genes/variants in high-risk individuals (early-onset / age <60), sporadic cases and controls will help elucidate genetic mechanisms contributing to familial MM / MGUS. In addition, we demonstrate the benefit of applying a linkage analysis framework to familial WES data for discovery of genomic regions influencing MM / MGUS. Disclosures Dumontet: Roche: Research Funding; Merck: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria; Sanofi: Honoraria. Kumar:AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees; Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding; Roche: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding.

Abstract Introduction: Venetoclax (Ven), an oral agent that targets the antiapoptotic protein, BCL-2, has demonstrated efficacy, as monotherapy and combined with proteasome inhibitor (PI) bortezomib, in relapsed/refractory (R/R) multiple myeloma (MM). We report preliminary safety and efficacy data for Ven combined with the second generation PI carfilzomib (K) and dexamethasone (VenKd) in R/R MM. Methods: In this ongoing phase 2, dose escalation study (NCT02899052), patients with R/R MM and no prior K exposure received VenKd on 28-d cycles in 4 dose finding and one expansion cohorts: Ven 400 mg/day + K 27 mg/m2 Day 1, 2, 8, 9, 15, 16 + dex 40 mg Day 1, 8, 15, 22 (Cohort 1), same regimen but with Ven 800 mg/day (Cohort 2), Ven 800 mg/day + K 70 mg/m2 Day 1, 8, 15 + dex 40 mg Day 1, 8, 15, 22 (Cohort 3/expansion cohort), or Ven 800 mg + K 56 mg/m2 Day 1, 2, 8, 9, 15, 16 + dex 40 mg Day 1, 2, 8, 9, 15, 16, 22, 23 (Cohort 4). Treatment continued until progressive disease (PD) or unacceptable toxicity. Results: As of June 11, 2018, 42 patients were enrolled. The median age was 66.5 years (min, max: 37, 79), 63% had ISS II/III disease, and 8 patients (19%) had t(11;14). Patients received a median of 2 prior therapies (range: 1 - 3), 93% had received prior PI (50% refractory), 62% were refractory to immunomodulatory therapies, and 33% double refractory. At the data cut off, 29 patients were still active and had completed ≥2 cycles and 13 patients discontinued with the primary reason being disease progression (n=4), death (n=3), physician decision (n=2), withdrawal of consent (n=2), lack of efficacy (n=1), and AE (n=1). All patients experienced at least one AE, and grade 3/4 AEs experienced by >10% of subjects included: decreased lymphocyte count (26%), decreased neutrophil count (14%), and hypertension (12%). Thirteen subjects experienced at least one serious AE. Maximum tolerated dose was not reached and Ven 800 mg/day + K 70 mg/m2 was selected for expansion. Ven mean (% coefficient of variation) maximum plasma concentration (Cmax) and area under the plasma concentration-time curve over 24 hours (AUC24) on Cycle 1 Day 15 were 2.7 (57) mg/mL and 33.1 (54) mg×h/mL, respectively, at 400 mg venetoclax (n=4); and were 2.42 (53) mg/mL and 38.7 (51) mg×h/mL, respectively, at 800 mg venetoclax (n=13) in the dose escalation cohorts. The overall response rate (ORR) was 78% and the very good partial response (VGPR) or better rate was 56% (Table). Median time from first dose to the data cut or discontinuation was 5.7 months (range: 0.9 - 16.3) and the median time to first response was 1.9 months (95% CI: 0.9, 9.2). ORRs for subgroups of interest are reported in the Table. Conclusions: The combination of VenKd appears tolerable with no new safety signals or changes in Ven pharmacokinetics. VenKd shows promising preliminary efficacy in R/R MM patient subgroups. Response rates were comparable in all high risk subgroups and overall population. However, the subset of patients with t(11;14) had the highest response. Overall, these results demonstrate that VenKd is a safe and efficacious regimen in R/R MM and support the continued study of VenKd. Disclosures Costa: Abbvie: Research Funding; BMS: Research Funding; Karyopharm: Research Funding; Amgen: Honoraria, Research Funding; Sanofi: Honoraria; Celgene: Honoraria, Research Funding; Janssen: Research Funding. Stadtmauer:Celgene: Consultancy; AbbVie, Inc: Research Funding; Janssen: Consultancy; Takeda: Consultancy; Amgen: Consultancy. Morgan:Bristol-Myers Squibb: Consultancy, Honoraria; Janssen: Research Funding; Takeda: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding. Kovacsovics:Amgen: Honoraria, Research Funding; Abbvie: Research Funding. Jakubowiak:Takeda: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Bristol-Myers Squibb: Consultancy, Honoraria; SkylineDx: Consultancy, Honoraria; Adaptive Biotechnologies: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria; Karyopharm: Consultancy, Honoraria; Celgene: Consultancy, Honoraria. Kaufman:Roche: Consultancy; BMS: Consultancy; Karyopharm: Other: data monitoring committee; Janssen: Consultancy; Abbvie: Consultancy. Mobasher:Genentech Inc: Employment; F. Hoffmann-La Roche Ltd: Other: Ownership interests non-PLC. Freise:AbbVie, Inc: Employment, Equity Ownership. Ross:AbbVie, Inc: Employment, Equity Ownership. Pesko:AbbVie, Inc: Employment, Equity Ownership. Munasinghe:AbbVie, Inc: Employment, Equity Ownership. Gudipati:AbbVie, Inc: Employment, Equity Ownership. Mudd:AbbVie, Inc: Employment, Equity Ownership. Bueno:AbbVie, Inc: Employment, Equity Ownership. Kumar:Oncopeptides: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche: Research Funding; Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding.