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B-cell maturation antigen (BCMA) is selectively expressed as a surface protein on plasma cells and is a validated target for multiple myeloma (MM). A soluble form of BCMA (sBCMA) is elevated in the sera of patients with MM. The bispecific antibodies teclistamab (BCMA×CD3) and talquetamab (G protein-coupled receptor family C group 5 member D [GPRC5D]×CD3) are in clinical development as therapies for MM. Using data from patients with relapsed/refractory MM (N=300) who participated in phase 1 studies of teclistamab (NCT03145181) or talquetamab (NCT03399799), baseline serum sBCMA levels were quantitatively analyzed relative to response to treatment, percentage of bone marrow plasma cells (BMPCs), and cytogenetic risk. By cycle 3 day 1 of treatment, sBCMA levels declined from baseline in 50 (88%) of 57 responders and 49 (98%) of 50 responders to teclistamab and talquetamab, respectively. Depth of response correlated with the magnitude of sBCMA reduction. In contrast, sBCMA increased in 33 (80%) of 41 patients and 24 (49%) of 49 patients who did not respond to teclistamab or talquetamab, respectively. Baseline sBCMA levels correlated with the percentage of BMPC; patients with extramedullary plasmacytomas who had low levels of BMPC (≤10%) tended to have high baseline sBCMA levels (≥400 ng/mL), based on limited data. Baseline sBCMA levels and changes in sBCMA levels at cycle 3 day 1 were similar in patients with high- and standard-risk cytogenetics treated with teclistamab or talquetamab. These results support the use of sBCMA as a potential surrogate marker of tumor burden and treatment response in MM.

Introduction: Multiple Myeloma (MM) is an incurable plasma cell malignancy commonly preceded by the asymptomatic stage smoldering multiple myeloma (SMM). MM is characterized with significant genomic heterogeneity of chromosomal gains and losses (CNVs), translocations, and point mutations (SNVs); alterations that are also observed in SMM patients. However, current SMM risk models rely solely on clinical markers and do not accurately capture progression risk. While incorporating some genomic biomarkers improves prediction, using all MM genomic features to comprehensively stratify patients may increase risk stratification precision in SMM. Methods: We obtained a total of 214 patient samples at SMM diagnosis. We performed whole-exome sequencing on 166 tumors; of these, RNA sequencing was performed on 100. Targeted capture was done on 48 additional tumors. Upon binarization of DNA features, we performed consensus non-negative matrix factorization to identify distinct molecular clusters. We then trained a random forest classifier on translocations, SNVs, and CNVs. The predicted clinical outcomes for the molecular subtypes were further validated in an independent SMM cohort of 74 patients. Results: We identified six genomic subtypes, four with hyperdiploidy (>48 chromosomes, HMC, HKR, HNT, HNF) and two with IgH translocations (FMD, CND) (Table 1). In multivariate analysis accounting for IMWG (20-2-20) clinical risk stages, high-risk (HMC, FMD, HKR) and intermediate-risk (HNT, HNF) genetic subtypes were independent predictors of progression (Hazards ratio [HR]: 3.8 and 5.5, P = 0.016 and 0.001, respectively). The low-risk, CND subtype harboring translocation (11;14) was enriched for the previously defined CD-2 MM signature defined by the B cell markers CD20 and CD79A (FDR = 0.003 ), showed upregulation of CCND1, E2F1, and E2F7 (FDR = 0.01, 0.0004, 0.08), and was enriched for G2M checkpoint, heme metabolism, and monocyte cell signature (FDR = 0.003, 0.003, 0.003, respectively). The FMD subtype with IgH translocations (4;14) and (14;16) was enriched for P53, mTORC1, unfolded protein signaling pathways and plasmacytoid dendritic cell signatures (FDR = 0.01, 0.005, 0.008, respectively). The HKR tumors were enriched for inflammatory cytokine signaling, MYC target genes, T regulatory cell signature, and the MM proliferative (PR) signatures (FDR = 0.02, 0.03, 0.007, 0.02, respectively). The APOBEC mutational signature was enriched in HMC and FMD tumors (P = 0.005), while there was no statistical difference across subtypes in the AID signature. The median follow-up for the primary cohort is 7.1 years. Median TTP for patients in HMC, FMD, and HKR was 3.8, 2.6, and 2.2 years, respectively; TTP for HNT and HNF was 4.3 and 5.2, respectively, while it was 11 years in CND patients (P = 0.007). Moreover, by analyzing the changes in MM clinical biomarkers over time, we found that patients from high-risk subgroups had higher odds of developing evolving hemoglobin and monoclonal protein levels over time (P = 0.01 and 0.002, respectively); Moreover, the absolute increase in M-protein was significantly higher in patients from the high-risk genetic subtypes at one, two, and five years from diagnosis (P = 0.001, 0.03, and 0,01, respectively). Applying the classifier to the external cohort replicated our findings where intermediate and high-risk genetic subgroups conferred increased risk of progression to MM in multivariate analysis after accounting for IMWG staging (HR: 5.5 and 9.8, P = 0.04 and 0.005, respectively). Interestingly, within the intermediate-risk clinical group in the primary cohort, patients in the high-risk genetic subgroups had increased risk of progression (HR: 5.2, 95% CI 1.5 - 17.3, P = 0.007). In the validation cohort, these patients also had an increased risk of progression to MM (HR: 6.7, 95% CI 1.2 - 38.3, P = 0.03), indicating that molecular classification improves the clinical risk-stratification models. Conclusion: We identified and validated in an independent dataset six SMM molecular subgroups with distinct DNA alterations, transcriptional profiles, dysregulated pathways, and risks of progression to active MM. Our results underscore the importance of molecular classification in addition to clinical evaluation in better identifying high-risk SMM patients. Moreover, these subgroups may be used to identify tumor vulnerabilities and target them with precision medicine efforts. Figure 1 Figure 1. Disclosures Bustoros: Janssen, Bristol Myers Squibb: Honoraria, Speakers Bureau; Takeda: Consultancy, Honoraria. Casneuf: Janssen: Current Employment. Kastritis: Amgen: Consultancy, Honoraria, Research Funding; Takeda: Honoraria; Pfizer: Consultancy, Honoraria, Research Funding; Genesis Pharma: Honoraria; Janssen: Consultancy, Honoraria, Research Funding. Walker: Bristol Myers Squibb: Research Funding; Sanofi: Speakers Bureau. Davies: Takeda: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria; BMS: Consultancy, Honoraria; Roche: Consultancy, Honoraria; Janssen: Consultancy, Honoraria. Dimopoulos: Amgen: Honoraria; BMS: Honoraria; Takeda: Honoraria; Beigene: Honoraria; Janssen: Honoraria. Bergsagel: Genetech: Consultancy, Honoraria; Oncopeptides: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria; Novartis: Consultancy, Honoraria, Patents & Royalties: human CRBN mouse; GSK: Consultancy, Honoraria; Celgene: Consultancy, Honoraria. Yong: BMS: Research Funding; Autolus: Research Funding; Takeda: Honoraria; Janssen: Honoraria, Research Funding; Sanofi: Honoraria, Research Funding; GSK: Honoraria; Amgen: Honoraria. Morgan: BMS: Membership on an entity's Board of Directors or advisory committees; Jansen: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; GSK: Membership on an entity's Board of Directors or advisory committees. Getz: IBM, Pharmacyclics: Research Funding; Scorpion Therapeutics: Consultancy, Current holder of individual stocks in a privately-held company, Membership on an entity's Board of Directors or advisory committees. Ghobrial: AbbVie, Adaptive, Aptitude Health, BMS, Cellectar, Curio Science, Genetch, Janssen, Janssen Central American and Caribbean, Karyopharm, Medscape, Oncopeptides, Sanofi, Takeda, The Binding Site, GNS, GSK: Consultancy.

Introduction: Daratumumab (DARA)-based regimens are effective and well tolerated in both newly diagnosed and relapsed/refractory multiple myeloma (RRMM) patients. However, the prognosis for patients who have become refractory to proteasome inhibitors (PIs), immunomodulatory drugs (IMiDs) and DARA is poor. A better understanding of determinants of response and mechanisms of resistance to DARA may lead to new rationally designed treatment strategies. We therefore characterized the effect of DARA on the immune system in MM patients treated with DARA monotherapy in part A of the DARA-ATRA study (ClinicalTrials.gov NCT02751255). Methods: In part A of this prospective multicenter phase 2 trial, 63 DARA-naïve patients were treated with DARA monotherapy (16 mg/kg; approved schedule). Median number of prior lines of treatment was 4 (range 2-11), all patients were previously exposed to lenalidomide and a PI; 89% was refractory to an IMiD, 71% to a PI and 67% to both IMiD and PI. Bone marrow (BM) aspirates obtained at baseline (BL) and at progression (PD; primary refractory, or acquired resistance after prior response) were subjected to deep immune profiling using 28 surface- and intracellular proteins measured by flow cytometry (BL n=51, PD n=47). In a subset of these patients (BL n=39, PD n=33) mass cytometry (CyTOF) was also performed profiling 39 proteins. In addition, peripheral blood (PB) samples obtained at BL (n=44) and PD (n=37) were analyzed using CyTOF. Computational analyses of flow data were performed using UMAP and FlowSOM; CyTOF data were analyzed using SPADE and Freeviz. Statistical analyses included Wilcoxon rank-sum and signed-rank tests, Generalized Linear Mixed Models and ANOVA. Results: A partial response or better was achieved in 41% of patients treated with DARA monotherapy. We compared immune profiles of responding and non-responding (primary-refractory) patients. At BL, the percentages of MM-, T-, B- and NK cells in BM were similar between both groups. However, NK cells of non-responding patients had a lower proportion of CD16 + (P=0.029), and a higher proportion of TIM-3 + (P=0.010) and HLA-DR + (P=0.043) NK cells, suggesting an exhausted phenotype. Non-responders also had a higher proportion of TIM-3 + CD4 + (P=0.022) and TIM-3 + CD8 + T-cells (P=0.004), and a higher proportion of TIM-3 + regulatory T-cells (Tregs) (P=0.042). A higher proportion of TIM-3 + -NK cells, -T-cells, or -Tregs in BM was also associated with poor progression-free and overall survival (PFS; OS). In addition, clinical characteristics associated with poor PFS such as LDH (P=0.016), extramedullary disease (P=0.001) and (R-)ISS stage III (P=0.015) were associated with an increased number of phenotypically exhausted NK- and T-cells. Similar to prior studies, DARA treatment resulted in reduced levels of CD38 on all immune cell subsets and a marked decrease in Tregs, regulatory B cells (Bregs) and NK cells in both BM and PB. Upon acquired resistance, remaining NK cells displayed higher proportions of TIM-3 + (P=0.022), HLA-DR + (P=0.0007) and LAG-3 + (P=0.011), and lower proportions of CD16 + (P=0.002) (Figure 1), compatible with an exhausted phenotype. Furthermore, disease progression was associated with an increase in CD4 + and CD8 + terminally differentiated effector memory T-cells and a decrease in CD4 + and CD8 + central memory T-cells in BM. There was no significant change in the proportion of T-cells expressing immune checkpoint molecules. CyTOF analysis of BM and PB samples confirmed flow cytometric findings. Furthermore, data-driven analysis identified immune profiles specific to progression, including a significant decrease in the fraction of Granzyme B + NK cells, and increase in the fraction of Granzyme B + Bregs at the time of progression. Based on NK cell depletion and -exhaustion observed at PD, we hypothesized that NK cell repletion may restore DARA sensitivity. Indeed, in ex vivo experiments we show that DARA-resistance can be overcome by addition of healthy donor derived NK cells to MM cells obtained from DARA-refractory patients. Conclusion: Here we show that an increased proportion of NK cells with an exhausted phenotype is associated with primary and acquired DARA-resistance, which is in line with the important role of NK cells in DARA-mediated tumor cell elimination ex vivo. Future DARA-based treatment strategies may benefit from reinvigorating NK cells and restoring their cytotoxic capacities. Figure 1 Figure 1. Disclosures Zweegman: Takeda: 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; BMS: Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; Sanofi: Membership on an entity's Board of Directors or advisory committees. Minnema: Celgene: Other: Travel expenses; Alnylam: Consultancy; Cilag: Consultancy; Janssen: Consultancy; Kite/Gilead: Consultancy; BMS: Consultancy. Broyl: Celgene/BMS: Consultancy, Honoraria; Sanofi: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Janssen: Consultancy, Honoraria. Levin: Roche, Janssen, Abbvie: Other: Travel Expenses, Ad-Board. Kersten: Kite/Gilead: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria; Roche: Honoraria; Takeda: Consultancy; BMS/Celgene: Consultancy; Miltenyi Biotech: Consultancy. Krevvata: Janssen: Current Employment. Casneuf: Janssen: Current Employment. Abraham: Janssen: Current Employment. Verona: Janssen: Current Employment. Smets: Janssen: Current Employment. Vanhoof: Janssen: Current Employment. Cortes-Selva: Janssen: Current Employment. van Steenbergen: Biolizard working for Janssen: Current Employment. Vieyra: Janssen: Current Employment. Sonneveld: Karyopharm: Consultancy, Honoraria, Research Funding; SkylineDx: Honoraria, Research Funding; Celgene/BMS: Consultancy, Honoraria, Research Funding; Amgen: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria, Research Funding. Mutis: Janssen: Honoraria; Genmab: Research Funding; Takeda: Research Funding; Novartis: Research Funding; ONK Therapeutics: Research Funding. van de Donk: Adaptive Biotechnologies: Membership on an entity's Board of Directors or advisory committees; Bristol Myers Squibb: 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; Janssen Pharmaceuticals: 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; Cellectis: Research Funding; Servier: Membership on an entity's Board of Directors or advisory committees; Roche: Membership on an entity's Board of Directors or advisory committees; Bayer: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees, Research Funding.

Multiple myeloma (MM) is a malignancy of plasma cells that arises from premalignant Monoclonal Gammopathy of Undetermined Significance (MGUS) and often progresses through an asymptomatic Smoldering (SMM) phase lasting months or years before manifesting clinical symptoms warranting therapy. Current research indicates that the tumor microenvironment (TME) in the bone marrow may play a significant role in governing progression to symptomatic disease. Therefore, understanding of the interactions between malignant plasma cells and the TME in early disease states is critical in the pursuit of therapies that will prevent progression to symptomatic disease. We performed high dimensional genomic and immunologic analysis of bone marrow specimens from 73 subjects with SMM. We performed RNA-seq on the malignant plasma cells isolated by anti-CD138 magnetic bead positive selection, mass cytometry (CyTOF) and T cell receptor sequencing (TCR Seq) of CD138-depleted bone marrow mononuclear cells, and proteomics, seromic, and grand serology analysis of bone marrow plasma. These samples and assays provided a broad view of the tumor cells and the cellular and soluble components of the TME. Each of these assays identified self-organizing clusters of subjects, indicating that subgroups of SMM patients shared common characteristics in the tumor or TME populations. We then applied novel bioinformatic methods to compare data from pairs, trios, quartets, and quintets of assays to identify communities of subjects with similar immunologic and genomic characteristics. Integrated analysis of CyTOF, proteomic, and TCR Seq resolved three distinct communities with a high degree of significance. These communities shared distinct cellular and proteomic features that suggested early adaptive, activated adaptive, or innate immune characteristics. These results suggest that the continuum from MGUS to MM does not consist of a single pathway in either the tumor cells or the TME, and that complex interactions ultimately determine progression. This suite of assays (CyTOF, proteomics, and TCR Seq) may be applicable in translational and clinical studies to understand key tumor and immune determinants of SMM and lead to rationally designed therapy to replicate these conditions to prevent progression to symptomatic disease. Disclosures Cho: Genentech: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; The Multiple Myeloma Research Foundation: Employment; Takeda: Research Funding; BMS: Consultancy; Agenus: Research Funding; GSK: Consultancy. Adams:Janssen Pharmaceuticals R&D: Employment, Other: Own Stock. Parekh:Foundation Medicine Inc.: Consultancy; Celgene Corporation: Research Funding; Karyopharm Inc.: Research Funding.

Introduction: Daratumumab is a human IgGκ monoclonal antibody targeting CD38 with a direct on-tumor and immunomodulatory mechanism of action. Daratumumab induces rapid, deep, and durable responses in combination with a proteasome inhibitor (bortezomib) or an immunomodulatory drug (lenalidomide or pomalidomide) in patients with RRMM (Palumbo A, et al. N Engl J Med 2016. 375(8):754-766; Dimopoulos MA, et al. N Engl J Med 2016.375(14):1319-1331; Chari A, et al. Blood 2017. Epub ahead of print). At the time of the pre-specified interim analysis of the phase 3 study POLLUX (median follow-up of 13.5 months), DRd reduced the risk of disease progression or death by 63% and significantly improved the overall response rate (ORR) compared with Rd alone (92.9% vs 76.4%; P Methods: Patients (pts) who received ≥1 prior line of therapy were randomized (1:1) to Rd (lenalidomide: 25 mg PO on Days 1-21 of each 28-day cycle; dexamethasone: 40 mg PO per week) with or without daratumumab (16 mg/kg IV weekly for Cycles 1 and 2, q2w for Cycles 3-6, then q4w until disease progression). The primary endpoint was progression free survival (PFS). Minimal residual disease (MRD) was assessed on bone marrow aspirate samples at the time of suspected complete response (CR) and at 3 and 6 months after suspected CR at sensitivity thresholds of 10-4, 10-5, and 10-6 via the clonoSEQTM next-generation sequencing assay (V.1.3; Adaptive Biotechnologies, Seattle, WA). For PFS on subsequent line of therapy (PFS2; defined as time from randomization to progression after next line of subsequent therapy or death) was examined as an exploratory endpoint. Results: Pts in both treatment groups (DRd, n=286; Rd, n=283) received a median of 1 prior line of therapy and 18% of patients received prior treatment with lenalidomide. After a median follow-up of 25.4 months, PFS was significantly prolonged with DRd vs Rd (median, not reached [NR] vs 17.5 months; HR, 0.41; 95% CI, 0.31-0.53; P MRD-negative rates were >3-fold higher with DRd vs Rd at all sensitivity thresholds evaluated. At a sensitivity threshold of 10-5, MRD-negative rates were 26% with DRd vs 6% for Rd (P PFS2 was significantly improved with DRd vs Rd in the intent to treat (ITT) population (HR, 0.55; 95% CI, 0.40-0.76; P=0.0002; Figure 2A). Among MRD-negative (10-5) pts who received DRd (n=75) or Rd (n=18), no significant differences in PFS2 were observed between treatment groups (Figure 2B). Time to next therapy was also significantly prolonged with DRd vs Rd in the ITT population (median, NR vs 22.7 months; HR, 0.34; 95% CI, 0.25-0.46; P The most common (≥10%) grade 3/4 TEAEs included neutropenia (54% vs 40%), anemia (16% vs 21%), thrombocytopenia (14% vs 16%), and pneumonia (12% vs 9%), in pts treated with DRd vs Rd, respectively. The incidence of TEAE-related treatment discontinuations was similar between groups, occurring in 12% of pts in both treatment groups. No differences in the incidence of secondary primary malignancies were observed between treatment groups (16 [6%] patients in each group). Updated data will be presented at the meeting. Conclusion: This updated analysis reveals that DRd continues to demonstrate a significant PFS benefit compared with Rd alone, and pt responses continue to deepen with DRd with longer follow up. Pts who receive DRd demonstrated longer time to next therapy and responded more favorably to subsequent therapy as evidenced by prolonged PFS2, suggesting that patients continue to observe clinical benefit from prior daratumumab treatment. Importantly, the favorable safety profile was maintained with longer follow-up. These data support the addition of daratumumab to standard of care regimens in RRMM. Disclosures Dimopoulos: Genesis Pharma: Research Funding; Amgen Inc, Celgene Corporation, Janssen Biotech Inc, Onyx Pharmaceuticals, an Amgen subsidiary, Takeda Oncology: Consultancy, Honoraria, Other: Advisory Committee: Amgen Inc, Celgene Corporation, Janssen Biotech Inc, Onyx Pharmaceuticals, an Amgen subsidiary, Takeda Oncology; Novartis: Consultancy, Honoraria. White: Bristol-Myers Squibb: Consultancy, Honoraria; Amgen, Celgene, Janssen, Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Benboubker: Takeda, Celgene, Janssen, Amgen: Consultancy. Cook: Glycomimetcs: Consultancy, Honoraria; Takeda: Consultancy, Honoraria, Research Funding, Speakers Bureau; Amgen: Consultancy, Honoraria, Research Funding, Speakers Bureau; Bristol-Myers Squibb: Consultancy, Honoraria; Sanofi: Consultancy, Honoraria, Speakers Bureau; Janssen: Consultancy, Honoraria, Research Funding, Speakers Bureau; Celgene: Consultancy, Honoraria, Research Funding, Speakers Bureau. Ho: Amgen, Bristol-Myers Squibb, Celgene, Novartis, Janssen, Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees. Trivedi: Janssen: Employment. Wu: Janssen: Employment. Casneuf: Janssen: Employment. Chiu: Janssen: Employment. Schecter: Janssen: Employment. Moreau: Amgen: Honoraria; Millennium: Consultancy, Honoraria; Celgene, Janssen, Takeda, Novartis, Amgen, Roche: Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Honoraria; Onyx Pharmaceutical: Consultancy, Honoraria; Bristol-Myers Squibb: Honoraria; Celgene: Consultancy, Honoraria; Takeda: Honoraria; Novartis: Consultancy, Honoraria.

Introduction: Daratumumab is a first-in-class monoclonal antibody targeting the plasma cell antigen, CD38, that demonstrated significant activity in combination with bortezomib and dexamethasone (DVd) compared with bortezomib and dexamethasone alone (Vd) in a pre-specified interim analysis of CASTOR, a randomized phase 3 study of relapsed or refractory multiple myeloma (RRMM; Palumbo A. N Engl J Med 2016; in press). In this abstract, we report on subgroup analyses according to the number of prior lines of therapy received, and include outcomes based on cytogenetic status, in order to identify the patient population who derived the most benefit from the DVd combination. Methods: Eligible patients (pts) received at least 1 prior line of therapy and were randomized (1:1) to 8 cycles (q3w) of Vd with or without daratumumab (16 mg/kg IV qw in Cycles 1-3, Day 1 of Cycles 4-8, then q4w until progression). For each cycle, bortezomib 1.3 mg/m2 SC was administered on Days 1, 4, 8, and 11, and dexamethasone 20 mg PO was given on Days 1, 2, 4, 5, 8, 9, 11, 12. Progression-free survival (PFS) was the primary endpoint. Numbers of prior lines of therapy were determined by the site investigator according to the IMWG consensus guidelines. High-risk cytogenetic status based on local laboratory assessments was defined as having at least one of the following abnormalities via karyotyping or fluorescence in-situ hybridization: del17p, t(4;14), or t(14;16). Minimal residual disease (MRD) was evaluated on bone marrow aspirate samples that had been prepared with Ficoll using three different thresholds (10-4, 10-5, and 10-6) based on the ClonoSEQ assay (Adaptive Biotechnologies, Seattle, WA, USA). Results: Median follow-up was 7.4 months. In the 1 to 3 prior lines (1-3 PL) subgroup (DVd, n=229; Vd, n=219), PFS was significantly longer with DVd vs Vd (median: not reached [NR] vs 7.3 mo; HR, 0.39; 95% CI, 0.28-0.55; P In the 1 prior line (1 PL) subgroup (DVd, n=122; Vd, n=113), PFS was also significantly improved for DVd vs Vd (median: NR vs 7.5 mo; HR, 0.31; 95% CI, 0.18-0.52; P Updated efficacy and safety data, including analyses of MRD status across different sensitivity thresholds (10-4, 10-5, and 10-6), will be presented at the meeting. Conclusions: The treatment benefit of DVd vs Vd was maintained across 1-3 PL and 1 PL pts. Responses for DVd were deep and durable and correlated with significantly improved outcomes vs Vd. Despite small group sizes, treatment benefit of DVd vs Vd was also observed in high-risk cytogenetic pts receiving 1-3 PL. These data continue to support the addition of daratumumab to a standard-of-care regimen in RRMM. Figure Progression-free Survival in High-risk Patients (Defined by Cytogenetic Abnormalities) who Received 1 to 3 Prior Lines of Therapy Figure. Progression-free Survival in High-risk Patients (Defined by Cytogenetic Abnormalities) who Received 1 to 3 Prior Lines of Therapy Disclosures Mateos: Janssen, Celgene, Amgen, Takeda, BMS: Honoraria. Estell:Janssen: Membership on an entity's Board of Directors or advisory committees. Corradini:Celgene, Janssen, Novartis, Roche, Takeda, Sanofi, Servier, Gilead: Honoraria; Takeda: Consultancy. Medvedova:Oregon Health and Science University: Employment. Qi:Janssen: Employment. Schecter:Janssen: Employment, Equity Ownership. Amin:Janssen: Employment. Qin:Janssen: Employment. Deraedt:Janssen: Employment; Johnson & Johnson: Equity Ownership. Casneuf:Johnson & Johnson: Equity Ownership; Janssen R&D, Beerse, Belgium: Employment. Chiu:Janssen: Employment. Sasser:Janssen: Employment; Johnson & Johnson: Equity Ownership. Nooka:Amgen, Novartis, Spectrum: Consultancy.

Introduction: Daratumumab is a human monoclonal antibody targeting CD38 that demonstrated superior efficacy in combination with lenalidomide and dexamethasone (DRd) versus lenalidomide and dexamethasone alone (Rd) in a pre-specified interim analysis of a randomized phase 3 study of relapsed or refractory multiple myeloma (RRMM; Dimopoulos MA, et al. N Engl J Med 2016; in press). We report subgroup analyses from this study in patients (pts) who received 1 to 3 prior lines of therapy (1-3 PL), including outcomes based on high-risk cytogenetics within these subgroups. Methods: Patients (pts) who received ≥1 prior line of therapy were randomized (1:1) to Rd (lenalidomide: 25 mg PO on Days 1-21 of each 28-day cycle; dexamethasone: 40 mg PO weekly) with or without daratumumab (16 mg/kg IV qw for 8 weeks, q2w for 16 weeks, then q4w until progression). The primary endpoint was progression-free survival (PFS). The site investigator determined the number of prior lines of therapy according to IMWG consensus guidelines. Treatment-free interval (TFI) was defined as the duration between the end/start date of last line of prior therapy and the date of randomization. Pts with high-risk cytogenetic status had at least one of the following abnormalities as assessed via fluorescence in-situ hybridization or karyotyping by local laboratory assessment: t(4;14), t(14;16), or del17p. Results: In the 1-3 PL subgroup (DRd, n=272; Rd, n=264), PFS was significantly improved with DRd vs Rd (median: not reached [NR] vs 18.4 months; HR, 0.36; 95% CI, 0.25-0.50; P For 1-3 PL pts who had a TFI of >12 months (DRd, n=138; Rd, n=145), median PFS was NR in DRd vs 18.4 months in Rd (HR, 0.42; 95% CI, 0.24-0.74; P=0.0019; Figure A); the estimated 12-month PFS rate was 88.0% vs 74.5%, respectively. ORR was significantly higher with DRd vs Rd (96% vs 86%, P=0.0084), along with rate of VGPR or better (77% vs 56%; P=0.0008) and rate of CR or better (43% vs 27%; P=0.0083). Among pts with a TFI of ≤12 months (DRd, n=134; Rd, n=119), median PFS was NR in DRd vs 10.3 months in Rd (HR, 0.32; 95% CI, 0.21-0.51; P Among pts with 1-3 PL who were refractory to their last line of therapy (DRd, n=73; Rd, n=67), PFS was significantly prolonged with DRd vs Rd (median: NR vs 10.3 mo; HR, 0.42; 95% CI, 0.25-0.72; P=0.0010). ORR (92% vs 66%; P=0.0002), rate of VGPR or better (72% vs 34%; P Data for all subgroup analyses will be updated for the meeting. Conclusions: Responses with DRd were deep and durable which translated into significantly improved clinical outcomes vs Rd in 1-3 PL pts with RRMM. The results of these subgroup analyses suggest that the treatment benefit of DRd vs Rd was maintained across these subgroups, including pts with TFI of ≤12 months and those who were refractory to their last line of therapy. Figure Progression-free survival in patients with 1 to 3 prior lines of therapy and treatment-free interval of (A) >12 months (B) ≤12 months prior to randomization Figure. Progression-free survival in patients with 1 to 3 prior lines of therapy and treatment-free interval of (A) >12 months (B) ≤12 months prior to randomization Disclosures Usmani: Britsol-Myers Squibb: Consultancy, Research Funding; Skyline: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Array: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Pharmacyclics: Research Funding; BioPharma: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Millenium: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Novartis: Speakers Bureau; Sanofi: Consultancy, 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; Amgen: Consultancy, Research Funding, Speakers Bureau; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau. Dimopoulos:Novartis: 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; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Genesis: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Belch:Celgene: Honoraria; Takeda: Honoraria; Amgen: Honoraria; Janssen: Honoraria. White:Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Honoraria. Benboubker: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; Janssen: 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. Cook:Takeda Oncology: Consultancy, Research Funding, Speakers Bureau; Amgen: Consultancy, Speakers Bureau; Celgene: Consultancy, Research Funding, Speakers Bureau; Janssen: Consultancy, Research Funding, Speakers Bureau; Sanofi: Consultancy, Speakers Bureau; Glycomimetics: Consultancy. Ho:Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; 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. Khokhar:Janssen: Employment. Guckert:Janssen: Employment; Johnson & Johnson: Equity Ownership. Wu:Janssen: Employment. Qin:Janssen: Employment. Casneuf:Johnson & Johnson: Equity Ownership; Janssen R&D, Beerse, Belgium: Employment. Chiu:Janssen: Employment. Sasser:Janssen: Employment; Johnson & Johnson: Equity Ownership. San-Miguel:Amgen: Membership on an entity's Board of Directors or advisory committees; MSD: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Onyx: Membership on an entity's Board of Directors or advisory committees; Millennium: Membership on an entity's Board of Directors or advisory committees; BMS: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees.

Introduction: Daratumumab (DARA) is a human monoclonal IgG1κ CD38-targeting antibody that functions through several mechanisms of action (MOA), including CDC, ADCC, ADCP and induction of apoptosis. An additional, novel role of immune modulation and increased adaptive immune response was revealed from translational studies of DARA (16 mg/kg) in single-agent, phase 1/2 studies (SIRIUS [MMY2002] and GEN501; Krejcik J et al, Blood 2016;128:384-94). To further explore the ability of DARA to promote adaptive T-cell responses, we profiled T-cell repertoires (TCR) to evaluate T-cell clonality, expansion, and diversity from samples collected in POLLUX (MMY3003), a phase 3, randomized, open-label, multicenter study for patients with relapsed/refractory MM, in which DARA was tested in combination with lenalidomide plus dexamethasone versus lenalidomide plus dexamethasone alone (DRd vs. Rd; Dimopoulos MA et al, N Engl J Med 2016; in press). Methods: T-cell receptor beta (TCRβ) sequencing for repertoire profiling was conducted on whole blood samples collected at baseline and eight weeks after DARA treatment (cycle 3 [C3]) from subjects on both arms using the ImmunoSEQ assay (Adaptive Biotechnologies. Seattle, WA, USA). 133 subjects in DRd and 124 subjects in Rd treatment groups were included in this analysis and represented a balanced subgroup of the POLLUX clinical trial subjects. T-cell metric changes were compared between arms with ANOVA, including the treatment arm and visit interaction term. Within treatment-arm changes were evaluated with a Wilcoxon signed-rank test comparing baseline to on-treatment values per patient. Results: Consistent with the randomized treatment groups, no baseline differences were observed in T-cell repertoire metrics between the treatment arms, including T-cell clonality, diversity (or richness), and T-cell fraction. Similar to prior findings from DARA monotherapy studies, significantly larger increase of TCRβ clonality was observed in the DRd arm (median of 0.166 at baseline to 0.263 at C3). Interestingly, there was no increase in TCRβ clonality in the Rd arm (median of 0.175 at baseline to 0.175 at C3). The change in TCRβ clonality between C1 and C3 was significantly different between DRd and Rd (p=3.26E-10), demonstrating that the addition of DARA to Rd induces a specific clonal expansion of T cells. Estimated richness (diversity), on the other hand, slightly decreased with DRd treatment but not with Rd treatment (median of 503,951 at baseline to 427,096 at C3 [p= 1.01E-04] vs 572,182 to 532,806 [p= 3.58-01]). Among patients in both treatment groups, a bigger increase in T-cell fraction was observed in DRd vs Rd (median of 0.231 at baseline to 0.278 at C3 [p= 2.62E-3] vs 0.228 to 0.249 [p= 1.91E-01]). Although there were no significant differences in baseline characteristics in T-cell clonality, richness, and T-cell fraction, quartile analysis demonstrated that high baseline TCR richness predicted for better PFS with DRd but not for Rd. Conclusion: DARA in combination with lenalidomide plus dexamethasone specifically induced robust increases in T-cell clonality, which was not observed within the control lenalidomide plus dexamethasone arm. Interestingly, baseline TCR richness was associated with improved PFS in DRd subjects. This observation is similar to results with immune checkpoint inhibitors (Postow MA et al, J Immunother Cancer 2015;3:23), and together with the significant increase in T-cell clonality, provides further evidence for the immunomodulatory activity of DARA, even in combination therapy. These data support DARA's immune-modulatory MOA and provide additional insights into DARA's effect on the TCR in combination with standard of care treatment. Figure Figure. Disclosures Chiu: Janssen: Employment. Casneuf:Janssen R&D, Beerse, Belgium: Employment; Johnson & Johnson: Equity Ownership. Axel:Janssen Pharmaceuticals Research and Development: Employment. Lysaght:Immuneering Corp: Employment; Janssen: Research Funding. Bald:Janssen: Employment. Khokhar:Janssen: Employment. Plesner:Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding. Usmani:Amgen: Consultancy, Research Funding, Speakers Bureau; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Onyx: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Millenium: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Sanofi: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Skyline: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Novartis: Speakers Bureau; BioPharma: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Pharmacyclics: Research Funding; Array: Research Funding; Britsol-Myers Squibb: Consultancy, Research Funding. Goldschmidt:Onyx: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Membership on an entity's Board of Directors or advisory committees, Research Funding; Millennium: 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, Research Funding; 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; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Chugai: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Amgen: Membership on an entity's Board of Directors or advisory committees. Ahmadi:Janssen: Employment. Chan:Adaptive Biotechnologies: Employment; University of Washington: Other: Visiting scholar. Sasser:Johnson & Johnson: Equity Ownership; Janssen Pharmaceuticals R&D: Employment.

Introduction: Daratumumab (DARA) is a human CD38-targeting monoclonal antibody that induces deep clinical responses in MM pts through multifaceted mechanisms of action (MOA) including complement-dependent cytotoxicity, antibody-dependent cellular cytotoxicity, antibody-dependent cellular phagocytosis and induction of apoptosis. Flow cytometry analysis revealed a previously unknown immunomodulatory role of DARA, via T-cell induction expansion, T-cell activity enhancement, and reduction of immune suppressive cell populations including CD38+ myeloid-derived suppressor cells, CD38+ regulatory T cells (TRegs), and CD38+ regulatory B cells (BRegs). Next-generation mass cytometry (CyTOF), which allows high parameter evaluation of the immune system, was used to assess the effects of DARA alone or in combination on a more comprehensive profile of immune cell subpopulations. Methods: Relapsed/refractory MM pt samples from a subset of single agent studies; SIRIUS (32 pts; whole blood [WB] only; Lonial S et al. The Lancet, 2016) and GEN501 (5 pts; WB and bone marrow [BM], Lokhorst HM et al. NEJM, 2015) along with GEN503, a study of DARA plus lenalidomide and dexamethasone (9 pts; WB and BM; Plesner T et al. ASH 2015) were analyzed. Fluorochrome or metal-conjugated antibody panel stained samples were evaluated by flow cytometry or cytometry by time-of-flight (CyTOF®) platforms, respectively. FACS analyses were performed and analyzed by FACS Canto II flow cytometers and FACSDiva software. For CyTOF analysis, events were clustered by phenotype by a spanning tree progression of density normalized events (SPADE) algorithm, and each cluster was associated with an immune population via Cytobank® software. Differential analysis of population fractions and marker intensity, over time and between response groups, derived raw P values from t-tests and single cell level bootstrap adjusted P values corrected for multiple dependent hypothesis testing. Results were visualized using SPADE trees (Figure) and Radviz projections, a new method that allows for the comparison of populations and conditions while preserving the relation to original dimensions. Results: Flow cytometry and high-dimensional CyTOF analyses confirmed previous findings including higher CD38 expression on plasma cells compared with other immune populations of natural killer (NK), monocytes, B and T cells, and depletion of both plasma cells and NK cells upon DARA treatment. Interestingly, while NK cells were significantly reduced with DARA treatment, remaining active NK cells (CD16+CD56dim) demonstrated increased expression of activation markers CD69, CD25 and CD137 while also decreasing granzyme B and increasing naive marker CD27. Though functionality tests weren't performed, the ability to evaluate several markers simultaneously suggests these cells possess limited cytotoxicity. Additionally, these studies indicated depletion of CD38 positive immune suppressive subsets of Tregs and Bregs. CD38+ basophil reductions occurred independent of response and may provide insight to short-lived infusion related reactions. Several observations within the T-cell compartment were indicative of a DARA-mediated adaptive response in both WB and BM samples. T cells displayed increases in total numbers and shifted towards higher CD8:CD4 and effector:naïve ratios after 2 months of DARA treatment. Responders had higher expression levels of several activation markers including CD69 and HLA-DR along with increased production of cytolytic enzyme granzyme B in CD8+ T cells following DARA treatment. Interestingly, in the GEN503 sample set, pts who achieved a complete response presented with a distinct BM CD4 T-cell phenotype of high granzyme B positivity versus those that achieved a partial response or very good partial response. This observation suggests pts with an active immune phenotype may achieve deeper responses to DARA in combination with standard of care agents lenalidomide and dexamethasone. Conclusion: CyTOF analysis of pt samples from both single agent and combination DARA studies agree with flow cytometry and support the pharmacodynamics and immune modulatory MOA of DARA while providing additional insight into changes in T-cell subtypes and activation status. Future CyTOF analyses of clinical samples from phase 3 combination studies aim to confirm these observations and expand the understanding of the MOA of DARA. Disclosures Adams: Janssen Research & Development, LLC: Employment. Stevenaert:Janssen: Employment. Van der Borght:Janssen: Employment. Casneuf:Janssen R&D, Beerse, Belgium: Employment; Johnson & Johnson: Equity Ownership. Smets:Janssen: Employment. Bald:Janssen: Employment. Abraham:Janssen: Employment. Ceulemans:Janssen: Employment. Vanhoof:Janssen: Employment; Johnson & Johnson: Equity Ownership. Ahmadi:Janssen: Employment. Usmani:Onyx: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Array: Research Funding; BioPharma: Research Funding; Pharmacyclics: Research Funding; Takeda: Consultancy, Research Funding, Speakers Bureau; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Amgen: Consultancy, Speakers Bureau; Janssen: Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Research Funding; Millenium: Membership on an entity's Board of Directors or advisory committees; Skyline: Membership on an entity's Board of Directors or advisory committees. Plesner:Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding. Lonial:Janssen: Consultancy; BMS: Consultancy; Merck: Consultancy; Novartis: Consultancy; Janssen: Consultancy; Onyx: Consultancy; Onyx: Consultancy; Millenium: Consultancy; Celgene: Consultancy; Novartis: Consultancy; BMS: Consultancy; Celgene: Consultancy. Lokhorst:Genmab: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding. Mutis:Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Genmab: Research Funding; Celgene: Research Funding. van de Donk:Janssen: Research Funding; BMS: Research Funding; Amgen: Research Funding; Celgene: Research Funding. Sasser:Janssen Pharmaceuticals R&D: Employment; Johnson & Johnson: Equity Ownership.

Introduction: Daratumumab is a human CD38 IgGκ monoclonal antibody that demonstrated significant activity and a manageable safety profile in combination with bortezomib and dexamethasone. In a randomized phase 3 study, daratumumab in combination with bortezomib and dexamethasone (DVd) significantly prolonged progression-free survival (PFS) versus bortezomib and dexamethasone alone (Vd) in a pre-specified interim analysis of patients (pts) with relapsed or refractory multiple myeloma (RRMM; Palumbo A. N Engl J Med 2016; in press). Herein, we examine subgroups from this study to compare the efficacy of DVd vs Vd in bortezomib-naive and bortezomib-experienced pt populations. In addition, the efficacy of DVd vs Vd in pts who were refractory to lenalidomide at last prior line of therapy was also evaluated. Methods: Pts who received ≥1 prior line of therapy were randomized (1:1) to 8 cycles (q3w) of Vd (bortezomib: 1.3 mg/m2 SC on Days 1, 4, 8, 11; dexamethasone: 20 mg PO on Days 1, 2, 4, 5, 8, 9, 11, 12) with or without daratumumab (16 mg/kg IV qw in Cycles 1-3, Day 1 of Cycles 4-8, then q4w until progression). Pts who were refractory to bortezomib were not eligible. The primary endpoint was PFS. Bone marrow aspirate samples that had been prepared with Ficoll were evaluated for minimal residual disease (MRD) using three different thresholds (10-4, 10-5, and 10-6) based on the ClonoSEQ assay (Adaptive Biotechnologies, Seattle, WA, USA). Results: Median follow-up was 7.4 months. Among bortezomib-naive pts (DVd, n=89; Vd, n=83), PFS was significantly improved with DVd vs Vd (median: not reached [NR] vs 7.5 months; HR, 0.25; 95% CI, 0.13-0.47; P For pts who previously received a bortezomib-containing regimen (DVd, n=162; Vd, n=164), PFS was also significantly longer with DVd vs Vd (median: 12.3 vs 6.7 months; HR, 0.46; 95% CI, 0.32-0.66; P Among pts who were refractory to lenalidomide at the last prior line of therapy (DVd, n=45; Vd, n=60), PFS was significantly longer in DVd vs Vd (median: 10.3 vs 4.4 mo; HR, 0.37; 95% CI, 0.21-0.65; P=0.0004; Figure). Within this subgroup, ORR was significantly higher for DVd vs Vd (81% vs 50%; P=0.0021), and the same trends were observed for rates of ≥VGPR (54% vs 12%; P Updated efficacy and safety data, including MRD analyses across different sensitivity thresholds (10-4, 10-5, and 10-6), will be presented at the meeting. Conclusions: These analyses confirm that addition of daratumumab to Vd significantly improves outcomes for RRMM pts regardless of prior treatment with bortezomib. Importantly, this treatment benefit of DVd vs Vd was maintained in pts who were refractory to lenalidomide at the last prior line of therapy. These data lend further support to adding daratumumab to a standard-of-care regimen in RRMM. Figure Progression-free Survival in Patients Refractory to Lenalidomide at the Last Prior Line of Therapy Figure. Progression-free Survival in Patients Refractory to Lenalidomide at the Last Prior Line of Therapy Disclosures Lentzsch: BMS: Consultancy; Foundation One: Consultancy; Celgene: Consultancy, Honoraria. Quach:Celgene: Membership on an entity's Board of Directors or advisory committees; Janssen Cilag: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees. Ovilla:Janssen: Consultancy. Qi:Janssen: Employment. Deraedt:Janssen: Employment, Equity Ownership. Schecter:Janssen: Employment, Equity Ownership. Amin:Janssen: Employment. Qin:Janssen: Employment. Casneuf:Johnson & Johnson: Equity Ownership; Janssen R&D, Beerse, Belgium: Employment. Chiu:Janssen: Employment. Sasser:Johnson & Johnson: Equity Ownership; Janssen Pharmaceuticals R&D: Employment. Sonneveld:Karyopharm: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Takeda: Consultancy, Honoraria; Amgen: Consultancy, Honoraria, Research Funding.

Introduction: Daratumumab (DARA) is a human monoclonal IgG1κ CD38 antibody that functions through multifaceted mechanisms of action, including CDC, ADCC, ADCP, induction of apoptosis and immunomodulatory activity (Krejcik et al, Blood 2016;128:384-394). DARA was added to standard of care (SOC) regimens in two randomized, controlled, phase 3 trials in RRMM: POLLUX (DARA+lenalidomide/dexamethasone [DRd] vs lenalidomide/dexamethasone [Rd]) and CASTOR (DARA+bortezomib/dexamethasone [DVd] vs bortezomib/dexamethasone [Vd]). The addition of DARA to these regimens resulted in significant improvements in PFS (hazard ratio for PFS: 0.37 and 0.39 for POLLUX and CASTOR, respectively) and ORR (POLLUX: 93% DRd vs 76% Rd; CASTOR: 83% DVd vs 63% Vd) (Dimopoulos MA et al, N Engl J Med 2016; in press; Palumbo A et al, N Engl J Med 2016; in press). To determine the ability of DARA to drive deep clinical responses beyond complete response (CR), MRD was assessed in both POLLUX and CASTOR using next-generation sequencing (NGS) of B cell receptor (Ig). This is the first comprehensive and prospective study of MRD to date in randomized phase 3 clinical trials of RRMM patients and investigates the ability of DARA-containing regimens to drive deep responses in this challenging population. Methods: MRD was assessed in POLLUX (blinded to treatment group) at the time of suspected CR, and at 3 and 6 months post-suspected CR for patients who maintained this response. Similarly, in CASTOR, MRD was assessed for patients at the time of suspected CR (blinded to treatment group) and at 6 months and 12 months after first dose (at the end and 6 months after end of Vd background therapy, respectively). MRD was assessed on bone marrow aspirate samples prepared using Ficoll and evaluated by the ClonoSEQTM assay (Adaptive Biotechnologies, Seattle, WA, USA) at sensitivities of 0.01% (1 cancer cell per 10,000 nucleated cells or 10-4), 0.001% (10-5), and 0.0001% (10-6). The MRD negative rate per treatment arm was determined as the proportion of patients with negative MRD at any time point after the first dose and compared using the likelihood-ratio test. To allow for a stringent, unbiased evaluation of MRD in these studies, the entire intent-to-treat population was evaluated where patients were considered MRD positive if they had only MRD positive test result or had no MRD assessment. In POLLUX, 63% in DRd and 87% in Rd did not receive a MRD assessment, and for CASTOR, 76% in DVd and 87% in Vd were not assessed for MRD. Results: Median duration of follow-up was 13.5 months and 7.4 months in POLLUX and CASTOR, respectively. The addition of DARA to SOC regimens (Rd in POLLUX or Vd in CASTOR) resulted in significantly higher MRD negative rates at all three thresholds examined (10-4, 10-5, and 10-6; Table). Additionally, patients who achieved MRD negative status experienced fewer PFS events compared with MRD positive patients at a threshold of 10-5 (Figure). Among pts who achieved CR or better, the rate of MRD negativity was at least 3-fold higher across all sensitivity thresholds in the DARA + SOC treatment groups compared with SOC alone. In MRD positive patients, PFS was significantly longer in the DARA + SOC treatment groups compared with SOC alone treatment arms. Updated data from both studies will be presented at the annual meeting. Conclusion: These two studies represent the first randomized, controlled, prospective evaluation of MRD in the RRMM phase 3 clinical trial setting and demonstrate that DARA-containing therapies are able to drive patients to remarkably deep levels of clinical response. Regardless of the SOC component, DARA-containing regimens consistently demonstrated ≥3-fold increase in MRD negative rate compared with the control groups at all evaluated thresholds. Importantly, since patients who achieved MRD negative status demonstrated low PFS event rates, the deep clinical responses induced by DARA may lead to improved survival. Table MRD negative Rate Based on Threshold Used Table. MRD negative Rate Based on Threshold Used Figure Progression-free survival by MRD status in POLLUX and CASTOR Figure. Progression-free survival by MRD status in POLLUX and CASTOR Disclosures Avet-Loiseau: Celgene: Honoraria, Research Funding, Speakers Bureau; Amgen: Honoraria, Speakers Bureau; BMS: Honoraria, Speakers Bureau; Sanofi: Honoraria, Speakers Bureau; Janssen: Honoraria, Research Funding, Speakers Bureau. Casneuf:Janssen R&D, Beerse, Belgium: Employment; Johnson & Johnson: Equity Ownership. Chiu:Janssen: Employment. Moreau:Janssen: Honoraria, Speakers Bureau; Amgen: Honoraria; Novartis: Honoraria; Takeda: Honoraria; Bristol-Myers Squibb: Honoraria; Celgene: Honoraria. Plesner:Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding. Khokhar:Janssen: Employment. Qi:Janssen: Employment. Schecter:Janssen: Employment, Equity Ownership. Carlton:Adaptive Biotechnologies: Employment, Equity Ownership. Qin:Janssen: Employment. Liu:Janssen: Employment; J&J: Equity Ownership; Merck: Equity Ownership. Wu:Janssen: Employment. Zhuang:Janssen: Employment. Ahmadi:Janssen: Employment. Sasser:J&J: Equity Ownership; Janssen: Employment. San-Miguel:Amgen: Membership on an entity's Board of Directors or advisory committees; BMS: Membership on an entity's Board of Directors or advisory committees; Onyx: Membership on an entity's Board of Directors or advisory committees; Millennium: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; MSD: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees.

Introduction: Daratumumab (DARA) is a human IgG1κ monoclonal antibody that binds with high affinity to a unique epitope on CD38. DARA monotherapy has shown promising activity in relapsed and/or refractory multiple myeloma (MM) patients with a median of 5 prior lines of therapy in two clinical studies (Study GEN501; Lokhorst HM. J Clin Oncol. 2014;32 Suppl:abstr 8513 and Study MMY2002; Lonial S. J Clin Oncol. 2015;33 Suppl:abstr LBA8512). The aim of this analysis was to identify proteins indicative of DARA's multiple mechanisms of action (MOA) and potential predictive pharmacodynamic response markers. A broad aptamer based proteomics platform (SomaSCANTM) evaluated clinical serum samples at study entry and during treatment to determine proteins and biological pathways associated with DARA MOA or clinical response. Methods: All patients were treated with 16 mg/kg DARA and whole blood samples were collected at baseline and after 8 weeks of treatment. Blood samples were processed for serum and stored frozen until batch analysis. Profiling of 1129 serum proteins was performed using the SOMAscan assay. Patients were classified based on overall best response: responders (stringent and complete responses, very good partial and partial responses), stable disease (stable disease or minimal response) and non-responders (progressive disease). Differential level testing included application of the Wilcoxon rank sum test and Limma for responder versus non-responder analysis, and ANOVA for repeated-measures with post-hoc test validation, Wilcoxon signed rank and Friedman tests for baseline versus on-treatment analysis. Results: In MMY2002 at baseline, 51 proteins were significantly different between responders and non-responders. Many have known associations with MM or CD38, and interestingly a subset is associated with T-cell biology. We recently observed that DARA induces a multi-factorial T-cell response in patients including CD8+ T-cell expansion and activation, and increased clonality. Proteins differentially expressed between responders/non-responders at baseline included tumor necrosis factor subfamily 8 (TNFSF8/CD30L), TNFSF9/CD137L, macrophage stimulating 1 (MST1), interleukin-1B (IL1B), cadherin 1 (CDH1) and cadherin 3 (CDH3). Protein profiles were evaluated at baseline and at 8 weeks (Cycle 3 Day 1) to study pharmacodynamic changes. Significant treatment-induced changes were identified in 142 proteins. Of particular interest were the 60 proteins that changed differentially over time in responders vs non-responders. Proteins associated with MM tumor load, such as beta-2-microglobulin [B2M], and immunoglobulins decreased in responders and increased in non-responders. Novel MM therapeutic targets such as signaling lymphocyte activation molecule F7 [SLAMF7] (i.e. CS1) and B-cell maturation antigen [BCMA] decreased in responders and increased in non-responders during DARA treatment. Many proteins associated with immune or T-cell response were also significantly changed by DARA treatment, including TNFRSF1B, CD163, TNFRSF25, TLR2, CCL5, IL5RA, FCGR2A, ICOS, Granzyme B, and programmed cell death ligand 1 [PD-L1] many of which were differential between responders and non-responders. Differential level testing of GEN501 samples identified a small set of proteins that were significantly altered by DARA treatment over time. Many of these proteins overlapped with those identified in the MMY2002 analysis, increasing confidence in the statistical results. Conclusions: This exploratory serum proteomic analysis identified proteins that were differentially expressed between responders and non-responders at baseline, including proteins associated with immune response and T-cell biology (TNFSF8/CD30L, TNFSF9/CD137L, IL1B). In addition, significant differential changes in protein expression between responders and non-responders after DARA treatment were seen. Many of these are associated with MM tumor load (BCMA, immunoglobulins, SLAMF7, and B2M) and decreased in responders and increased in non-responders. In addition, proteins related to T-cell activity, immune checkpoints and immune response (TNFRSF1B, CD163, TNFRSF25, TLR2, CCL5, IL5RA, FCGR2A, ICOS, Granzyme B, PD-L1) also showed changes associated with DARA treatment, supporting the recent findings that DARA induces a T-cell response in MM patients that may contribute to clinical response. Disclosures Casneuf: Janssen: Employment. Lysaght:Immuneering Corp: Employment, Other: Stockholder. LeFave:Immuneering Corp.: Employment. Bald:Janssen: Employment. Weiss:Janssen and Millennium: Consultancy; Janssen and Onclave: Research Funding. van de Donk:Janssen Pharmaceuticals: Research Funding; Amgen: Research Funding; Celgene: Research Funding. Lokhorst:Amgen: Honoraria; Janssen: Honoraria, Research Funding; Genmab: Honoraria, Research Funding. Ahmadi:Janssen: Employment.

Introduction: Daratumumab (DARA) is a novel human monoclonal antibody that targets CD38, a protein that is highly expressed on multiple myeloma (MM) cells. DARA acts through multiple immune effector-mediated mechanisms, including complement-dependent cytotoxicity, antibody-dependent cell-mediated cytotoxicity, and antibody-dependent cellular phagocytosis. In two clinical studies (NCT00574288 [GEN501] and NCT01985126 [Sirius]) of DARA monotherapy in patients with relapsed and refractory MM, overall response rates were 36% and 29%, respectively. CD38 is highly expressed in myeloma cells but also expressed in lymphocytes and other immune cell populations. Therefore, the effects of DARA on immune cell populations and adaptive immune response pathways were investigated. Methods: The patient population investigated included treated subjects with MM that were relapsed after or were refractory to ≥2 prior therapies (GEN501) or had received ≥3 prior therapies, including a proteasome inhibitor (PI) and an immunomodulatory drug (IMiD), or were refractory to both a PI and an IMiD (Sirius). Patients assessed in this analysis were treated with 16 mg/kg DARA. When both studies were combined, median age (range) was 64 (31-84) years and median time from diagnosis was 5.12 (0.77-23.77) years. Seventy-six percent of patients had received >3 prior therapies and 91% were refractory to their last treatment. Clinical response was evaluated using IMWG consensus recommendations. Peripheral blood (PB) samples and bone marrow (BM) biopsies/aspirates were taken at prespecified time points and immunophenotyped by flow cytometry to enumerate various T-cell sub-types. T-cell clonality was measured by TCR sequencing. Antiviral T-cell response and regulatory T-cell (Treg) activity were analysed by functional in vitro assays. T-cell subpopulation counts were modelled over time with linear mixed modelling. Two group comparisons were performed using non-parametric Wilcoxon rank sum tests. Results: Data from 148 patients receiving 16 mg/kg DARA in GEN501 (n = 42) and Sirius (n = 106) were analyzed for changes in immune response. In PB, robust mean increases in CD3+ (44%), CD4+ (32%) and CD8+ (62%) T-cell counts per 100 days were seen with DARA treatment. However, responding evaluable patients (n = 45) showed significantly greater increases from baseline than nonresponders (n = 93) in CD3+ (P = 0.00012), CD4+ (P = 0.00031), and CD8+ (P = 0.00018) T cells. In BM aspirates the number of CD3+, CD4+, and CD8+ T-cells increased during treatment compared to baseline (the median percent increases were 19.95%, 5.66%, and 26.99% [n = 58]). Additionally, CD8+: CD4+ T-cell ratios significantly increased compared to baseline in both PB (P = 0.00017), and BM (P = 0.00016). T cell clonality, assessed by TCR sequencing, increased after DARA treatment compared with pretreatment (P = 0.049), with greater sums of absolute expansion in the repertoire (P = 0.037), as well as greater maximum expansion of a single clone (P = 0.048) in responders compared to nonresponders. Increased antiviral T-cell responses were observed post-DARA treatment, particularly in responders. Interestingly, a novel subpopulation of regulatory T cells was identified that expressed high levels of CD38. These cells comprised ~10% of all Tregs and were depleted by one DARA infusion. In ex vivo analyses, CD38+ Tregs appeared to be highly immune suppressive compared to CD38-Tregs. Conclusions: Robust T cell increases, increased CD8+: CD4+ ratios, increased antiviral responses, and increased T cell clonality were all observed after DARA treatment in a heavily pretreated, relapsed, and refractory patient population not expected to have strong immune responses. Improved clinical responses were associated with changes in these parameters. In addition, a sub-population of regulatory T cells expressing high CD38 levels was determined to be extremely immune suppressive and sensitive to DARA treatment. These data suggest a previously unknown immune modulatory role of DARA that may contribute to its efficacy, and a potential role for CD38 immune targeted therapies. We postulate that there are several distinct and complementary mechanisms that contribute to DARA's efficacy including increased antigen presentation through phagocytosis, targeting of immune suppressive Tregs, and increased adaptive immune responses. JK and TC contributed equally to this work. Disclosures Casneuf: Janssen: Employment. Verbist:Janssen: Employment. Bald:Janssen: Employment. Plesner:Genmab: Membership on an entity's Board of Directors or advisory committees; Roche and Novartis: Research Funding; Janssen and Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding. Liu:Janssen: Employment. van de Donk:Janssen Pharmaceuticals: Research Funding; Amgen: Research Funding; Celgene: Research Funding. Weiss:Janssen and Onclave: Research Funding; Janssen and Millennium: Consultancy. Ahmadi:Janssen: Employment. Lokhorst:Genmab: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; Amgen: Honoraria. Mutis:Janssen: Research Funding; Genmab: Research Funding.

Premalignant states are known to precede malignancy in many different cancers, including multiple myeloma (MM). Each year, 1% of Monoclonal Gammopathy of Undetermined Significance (MGUS) patients and 10% of Smoldering Multiple Myeloma (SMM) patients transition to symptomatic MM, which remains an incurable disease. By identifying patients at imminent risk (within 2 years) of progression to MM, treatment could begin early and potentially prevent full blown MM and associated morbidity and mortality. Multiple risk-factor models are currently utilized to identify patients at high-risk of developing MM. Commonly cited risk factors include percentage of bone marrow plasma cells, free light chain ratio, serum levels of M-protein, IgG subtype and levels of circulating plasma cells. These tests have individual and combined merit but there remains no consensus for measuring imminent risk of MM progression. To determine whether serum proteomics could help predict progression or provide information on relevant pathways involved in progression to MM, we evaluated 200 MGUS and SMM (187 non-IgM) patient samples on the Myriad DiscoveryMAP(r) platform (250+ serum proteins), supplemented by demographic and clinical information. Of the 187 non-IgM patients, 100 progressed to MM within 2 years (high-risk), and 87 did not progress to MM within 5 years (low-risk). We performed different subset analyses to screen for proteins that were informative and predictive of disease progression from MGUS/SMM to MM. First, a univariate Wilcoxon rank sum test was performed. The top 10 proteins that were found to be differential between high-risk/low-risk for all MGUS and SMM patients were IgM, Progesterone, MCP-2, Kallikrein-5, FGF4, EPO, MCP-4, MIP-1β, MCP-1, and TF. Interestingly, when analyzing MGUS and SMM patients separately, additional proteins that were important in distinguishing high-risk/low-risk patients included IgM, EN-RAGE, BAFF, and several others previously shown to be relevant in MM, as well as a handful of novel proteins with unidentified roles in MM. Second, to determine whether specific combinations of proteins could be utilized together to define high/low-risk, a classification tree was assembled. The combination of 8 features (IgM, Progesterone, Aldose Reductase, E-Selectin, Fas Ligand, Hemoglobin, Age and Creatine kinase-MB) appropriately classified 86% of the 187 patients into high/low-risk. Future analyses will include examining this high/low risk classifier in contrast to current risk factor models, and application to two additional sets of similar patient samples that serve as an independent validation set. Disclosures: No relevant conflicts of interest to declare.