Kaiser, Martin

Despite significant improvements in survival of patients with multiple myeloma (MM), outcomes remain heterogeneous, and a significant proportion of patients experience suboptimal outcomes. Importantly, traditional prognostic factors based on data from patients treated with older therapies no longer capture prognosis accurately in the contemporary era of novel triplet or quadruplet therapies. Therefore, risk stratification requires refinement in the context of available and investigational treatment options in routine practice and clinical trials, respectively. The current identification of high-risk MM (HRMM) in routine practice is based on the Revised International Staging System, which stratifies patients using a combination of widely available serum biomarkers and chromosomal abnormalities assessed via fluorescence in situ hybridization. In recent years, a substantial body of evidence concerning additional clinical, biological, and molecular/genomic prognostic factors has accumulated, along with new MM risk stratification tools and consensus reports. The International Myeloma Society, along with the International Myeloma Working Group, convened an Expert Panel with the primary aim of revisiting the definition of HRMM and formulating a practical and data-driven consensus definition, based on new evidence from molecular/genomic assays, updated clinical data, and contemporary risk stratification concepts. The Panel proposes the following Consensus Genomic Staging (CGS) of HRMM which relies upon the presence of at least one of these abnormalities: (1) del(17p), with a cutoff of >20% clonal fraction, and/or TP53 mutation; (2) an IgH translocation including t(4;14), t(14;16), or t(14;20) along with 1q+ and/or del(1p32); (3) monoallelic del(1p32) along with 1q+ or biallelic del(1p32); or (4) β2 microglobulin ≥5.5 mg/L with normal creatinine (<1.2 mg/dL).

Introduction: Although not formally approved for the treatment of multiple myeloma (MM), the BCL2 inhibitor venetoclax (ven) has shown promising activity in patients (pts) with MM whose disease harbors t(11;14). The randomized BELLINI trial (VenVd vs Vd in unselected MM pts, Kumar Lancet Oncol 2020) demonstrated improved PFS, especially in the 35 patients with t(11;14) [HR 0.11], although worse OS in the intention to treat population due to increased treatment related mortality. The subsequent CANOVA trial (Vendex vs Pomdex in MM pts with t(11;14), Mateos IMS 2023) failed to show a PFS benefit (median PFS 9.9 mo vs 5.8 mo, p=0.237), leaving an uncertain future for ven in myeloma, despite the biological rationale and clinical activity. We therefore analyzed real world physician practice patterns using off-label ven for MM in the US. Methods: This retrospective observational study used data from the US nationwide Flatiron Health electronic health record (EHR)-derived de-identified longitudinal database. The Flatiron Health database contains structured and unstructured data curated via technology-enabled abstraction from approx. 280 cancer clinics and 800 unique sites of care. We included all patients in the Flatiron Health database with multiple myeloma (ICD-9 203.0x or ICD-10 C90.0x, confirmed with clinical review) who had received ven as part of any line of MM treatment. This included patients who commenced ven between 2016-2024. The primary endpoint was time to next treatment or death (TTNT) from ven initiation, with overall survival (OS) from ven initiation as the key secondary endpoint, both of which were estimated using the Kaplan-Meier method. Outcomes were compared using Cox proportional hazards model, using R v 4.3.0. Results: We included 208 patients who received ven for MM. They had a median of three prior lines of therapy (range 0-12), a median age of 67 years (Range 34-85 yrs), and 59% were male. Race/ethnicity breakdown was: Non-Hispanic White: 136 pts (72.7%), Black 36 (19.3%), Hispanic 10 (5.3%), Asian 5 (2.7%), other/unknown 21 (10.1%). Most had commercial insurance (188 pts, 91.3%) and 108 pts (52%) were cared for in academic settings while 100 (48%) were in community settings. ECOG performance status was 0 in 50 pts (24%), 1 in 80 pts (38.5%), ≥2 in 31 pts (14.9%) and unknown in 47 (22.6%). ISS Stage was I in 42 pts (20.2%), II in 43 pts (20.7%), III in 52 pts (25.0%) and unknown in 71 (34.1%). 148 pts had t(11;14) (71.2%), while 25 pts did not (12%) and 35 pts had unknown t(11;14) status (16.8%). Most pts received ven as part of a triplet combination (106 pts, 51%), followed by doublets (39, 18.8%; 21 ven+dex and 18 ven+non-dex doublet), quads (38, 18.3%), as a single agent (17, 8.2%) or in other combinations such as with multi-agent cytotoxic chemotherapy or in addition to quadruplet therapy (8, 3.9%). Most common first ven-containing regimens used were VenDd (34 pts), VenKd (31), VenVd (25), Vendex (21), VenDVd (13), VenDKd (7). Ven was used as part of ≥2 different regimens in 20 patients, in 10 of whom those regimens were non-consecutive. Median TTNT was 10.2 months (mo) in all comers, 12 mo in pts with t(11;14), 3.4 mo in pts without t(11;14) and 7.6 mo in pts with unknown t(11;14) status. Median OS was 27.6 mo in all comers, 30.5 mo in pts with t(11;14), 8.1 mo in pts without t(11;14) and 27.9 mo in pts with unknown t(11;14) status. Pts with t(11;14) receiving ven had a significantly longer TTNT than those without t(11;14) [median 12 mo vs 3.4 mo, HR 0.59, 95%CI 0.42-0.84, p=0.003]. and a significantly longer OS [median 30.5 mo vs 8.1 mo, HR 0.58, 95% CI 0.38 - 0.89, p=0.012]. Discussion: We evaluated US ven prescribing patterns in 208 pts with MM in the largest real world study of ven in MM to date. While it was mostly used in pts with t(11;14) (71%), there was occasional use in pts without t(11;14), and it was used in a wide variety of combination regimens. Ven achieved meaningful TTNT in some patients and both TTNT and OS were greater in pts with t(11;14) than those without. This suggest that despite mixed data from clinical trials, clinicians are using ven for MM patients in practice and further data is required to optimize its use and understand its best combination treatment partners in MM.

AbstractMultiple myeloma (MM) is a heterogeneous and complex disease, both in mutational biology as well as in the clinical presentation of patients. While tailored and biomarker‐targeted therapy remains the direct goal for patient‐centric management, existing therapies in MM remain largely uniform. Translocation t(14;16) is a rare primary genetic event found in less than 5% of patients with newly diagnosed MM. Here, we present an overview of the biology of t(14;16), epidemiology, clinical presentation, prognostic impact, and discuss the future clinical and therapeutic strategies for targeting this rare yet high‐risk group in MM to optimize patient outcomes.

PURPOSE Outcomes for patients with newly diagnosed multiple myeloma (NDMM) are heterogenous, with overall survival (OS) ranging from months to over 10 years. METHODS To decipher and predict the molecular and clinical heterogeneity of NDMM, we assembled a series of 1,933 patients with available clinical, genomic, and therapeutic data. RESULTS Leveraging a comprehensive catalog of genomic drivers, we identified 12 groups, expanding on previous gene expression–based molecular classifications. To build a model predicting individualized risk in NDMM (IRMMa), we integrated clinical, genomic, and treatment variables. To correct for time-dependent variables, including high-dose melphalan followed by autologous stem-cell transplantation (HDM-ASCT), and maintenance therapy, a multi-state model was designed. The IRMMa model accuracy was significantly higher than all comparator prognostic models, with a c-index for OS of 0.726, compared with International Staging System (ISS; 0.61), revised-ISS (0.572), and R2-ISS (0.625). Integral to model accuracy was 20 genomic features, including 1q21 gain/amp, del 1p, TP53 loss, NSD2 translocations, APOBEC mutational signatures, and copy-number signatures (reflecting the complex structural variant chromothripsis). IRMMa accuracy and superiority compared with other prognostic models were validated on 256 patients enrolled in the GMMG-HD6 (ClinicalTrials.gov identifier: NCT02495922 ) clinical trial. Individualized patient risks were significantly affected across the 12 genomic groups by different treatment strategies (ie, treatment variance), which was used to identify patients for whom HDM-ASCT is particularly effective versus patients for whom the impact is limited. CONCLUSION Integrating clinical, demographic, genomic, and therapeutic data, to our knowledge, we have developed the first individualized risk-prediction model enabling personally tailored therapeutic decisions for patients with NDMM.

Summary: The multiple myeloma treatment landscape has changed dramatically. This change, paralleled by an increase in scientific knowledge, has resulted in significant improvement in survival. However, heterogeneity remains in clinical outcomes, with a proportion of patients not benefiting from current approaches and continuing to have a poor prognosis. A significant proportion of the variability in outcome can be predicted on the basis of clinical and biochemical parameters and tumor-acquired genetic variants, allowing for risk stratification and a more personalized approach to therapy. This article discusses the principles that can enable the rational and effective development of therapeutic approaches for high-risk multiple myeloma.

Introduction: Despite advances in treatment strategy, multiple myeloma (MM) remains a challenging, incurable disease as patients (pts) often relapse. Here we describe preclinical data of a novel cereblon (CRBN) E3 ligase modulatory compound (CELMoD), iberdomide (IBER; CC-220), as well as clinical and translational data from a current phase 1/2 clinical trial (NCT02773030). These data support a differentiated profile for IBER from immunomodulatory agents (IMiD agents), and development of IBER as a foundation of combination therapy for the treatment of relapsed/refractory MM (RRMM). Methods: Preclinical analyses were performed on pomalidomide (POM)-sensitive and acquired-resistant MM cell lines and peripheral blood mononuclear cells from healthy volunteers. Eligible pts enrolled on the clinical trial had RRMM and had received ≥ 2 prior regimens, containing at least an IMiD agent and proteasome inhibitor (PI), and had experienced disease progression within 60 days of last MM therapy. Escalating doses of IBER were given on Days 1-21, in combination with dexamethasone (DEX; 40 mg; 20 mg in pts aged > 75 years) on Days 1, 8, 15, and 22, of each 28-day cycle. Immunohistochemistry (IHC) data on CRBN, Ikaros, Aiolos, and ZFP91 expression was obtained from pt bone marrow specimens at screening and at Cycle 2, Day 15. Immune profiling was evaluated by flow cytometry of peripheral blood at Cycle 1, Day 1 and Cycle 2, Day 15. Primary objectives were to evaluate maximum tolerated dose (MTD), recommended phase 2 dose (RP2D), safety, and preliminary efficacy. Results: Preclinically, IBER exhibited potent tumoricidal anti-MM and immunostimulatory activity. IBER was more potent than lenalidomide (LEN) or POM in overcoming the immunosuppressive activity of bortezomib (BORT), inducing a more than twofold increase in T cell proliferation in the presence of BORT. IBER also enhanced the antibody-dependent cell-mediated cytotoxicity and complement-dependent cytotoxicity of daratumumab (DARA), leading to deeper responses than combinations with LEN or POM. Further differentiating from both LEN and POM, IBER showed activity alone and in combination with BORT or DARA in POM-resistant MM cell lines. As of June 28, 2019, 69 pts with RRMM had received IBER + DEX. Median age was 65 years (range 33-80), and median number of prior regimens was 5 (range 2-12). Prior therapies included autologous stem cell transplantation (80%), LEN (100%), POM (70%), PIs (100%), DARA (71%) and anti-BCMA (6%), including CAR T cells. Clinical activity was observed across all dose levels with an overall response rate (ORR) of 29%, clinical benefit rate of 45%, and disease control rate of 80%. ORR was 30%, 28% and 29% in IMiD agent-refractory, DARA-refractory and Quad-class (IMiD agents/PIs/steroids/CD-38 antibodies)-refractory pts, respectively. IBER + DEX showed a favorable safety profile, with grade 3-4 neutropenia, infections, and thrombocytopenia, occurring in 29%, 25%, and 12% of pts, respectively. To date, IBER doses range from 0.3 to 1.3 mg and the MTD/RP2D has not yet been reached. Pharmacodynamic immunophenotyping changes were dose-dependent. Treatment with IBER (at doses > 0.75mg) + DEX doubled the percentage of proliferating T cells and NK cells (P < 0.001 for each) and increased activated and effector memory CD8+ and CD4+ T cells by > 50% (P < 0.01 for each subset). Pharmacodynamic changes in pt bone marrow by quantitative IHC scoring showed significant degradation of substrates (Ikaros, P = 0.006; Aiolos, P < 0.001; ZFP91, P < 0.001) and downregulation of c-myc (P = 0.027), including in pts refractory to POM and with low CRBN expression. Conclusions: IBER + DEX has shown notable clinical activity and favorable tolerability in heavily pretreated pts with RRMM, including pts refractory to prior IMiD therapy. Preclinical and translational data suggest a differentiated profile of IBER from IMiD agents in regard to activity in POM-resistant models, potency in combination with BORT and DARA, and by inducing changes in CD4+ T cells that were not observed in pts treated with POM from prior studies. Taken together, these data support a differentiated profile for IBER from IMiD agents, and the clinical development of IBER as a foundation of combination therapy for the treatment of RRMM. This study is ongoing, and includes cohorts evaluating the combinations of IBER + DEX with DARA, BORT, and carfilzomib. Updated results will be presented at the meeting. Disclosures Lonial: Karyopharm: Consultancy; GSK: Consultancy; Takeda: Consultancy, Research Funding; Celgene Corporation: Consultancy, Research Funding; Amgen: Consultancy; Genentech: Consultancy; Janssen: Consultancy, Research Funding; BMS: Consultancy. Amatangelo:Celgene Corporation: Employment, Equity Ownership. Popat:Celgene Corporation: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: travel, accommodations, expenses; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees; GSK: Consultancy, Honoraria; Takeda: Honoraria, Other: travel, accommodations, expenses; Janssen: Honoraria, Other: travel support to meetings. Minnema:Gilead: Honoraria; Celgene Corporation: Honoraria, Research Funding; Amgen: Honoraria; Servier: Honoraria; Jansen Cilag: Honoraria. Zonder:Alnylam: Consultancy, Membership on an entity's Board of Directors or advisory committees; BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Consultancy, Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Intellia: Consultancy, Membership on an entity's Board of Directors or advisory committees; Caelum: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene Corporation: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Larsen:Janssen Oncology: 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. Oriol Rocafiguera:Celgene Corporation: Consultancy, Speakers Bureau; Janssen: Consultancy; Amgen: Consultancy, Speakers Bureau. Rodriguez Otero:Celgene Corporation: Consultancy, Honoraria, Speakers Bureau; Janssen: Consultancy, Honoraria; Takeda: Consultancy; BMS: Honoraria; Kite Pharma: Consultancy. Badros:Celgene Corporation: Consultancy; Amgen: Consultancy. Siegel:Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Bristol-Myers Squibb Company: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Janssen: Consultancy, 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. Jagannath:Bristol-Myers Squibb: Consultancy; Janssen Pharmaceuticals: Consultancy; Karyopharm Therapeutics: Consultancy; AbbVie: Consultancy; Merck & Co.: Consultancy; Celgene Corporation: Consultancy. Bringhen:Bristol-Myers Squibb: Honoraria; Celgene Corporation: 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; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy. Gironella:Amgen: Honoraria; Janssen: Honoraria; Celgene Corporation: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Kaiser:Takeda, Janssen, Celgene, Amgen: Honoraria, Other: Travel Expenses; Abbvie, Celgene, Takeda, Janssen, Amgen, Abbvie, Karyopharm: Consultancy; Celgene, Janssen: Research Funding. Cook:Janssen, Takeda, Sanofi, Karyopharm, Celgene: Consultancy, Honoraria, Speakers Bureau; Amgen, Bristol-Myers Squib, GlycoMimetics, Seattle Genetics, Sanofi: Honoraria; Celgene, Janssen-Cilag, Takeda: Honoraria, Research Funding. Gamberi:Janssen: 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; Amgen: Honoraria; Celgene Corporation: Consultancy, Membership on an entity's Board of Directors or advisory committees. Sonneveld:SkylineDx: Research Funding; Takeda: Honoraria, Research Funding; Karyopharm: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; BMS: Honoraria; Amgen: Honoraria, Research Funding. Nguyen:Celgene Corporation: Employment, Equity Ownership. Chen:Celgene Corporation: Employment, Equity Ownership. Homan:Celgene Corporation: Employment. Bjorklund:Celgene Corporation: Employment, Equity Ownership. Wang:Celgene Corporation: Employment, Equity Ownership. Pierceall:Celgene Corporation: Employment, Equity Ownership. Bensmaine:Celgene Corporation: Employment, Equity Ownership. Thakurta:Celgene: Employment, Equity Ownership. Peluso:Celgene Corporation: Employment. Van De Donk:Janssen Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene Corporation: Membership on an entity's Board of Directors or advisory committees, Research Funding; Servier: 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; Roche: 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; Bayer: Membership on an entity's Board of Directors or advisory committees.

Abstract Introduction Maintenance therapy has been extensively explored as a strategy for prolonging the duration of disease control and potentially survival following ASCT. To date, only lenalidomide has been approved for this indication. However, lenalidomide maintenance is associated with the development of second primary malignancies and tolerability issues. PIs are a backbone of MM treatment, and bortezomib-based maintenance has shown promising activity post-ASCT, yet the benefit of PI-based maintenance has not been demonstrated in a phase 3 trial vs placebo. Moreover, the feasibility of bortezomib maintenance in routine clinical practice is limited due to tolerability and the need for regular parenteral administration. There is a need for an oral PI maintenance therapy that can be administered for a prolonged period, improve depth of response without cumulative or late-onset toxicity, and improve convenience for patients. Methods The phase 3, double-blind, placebo-controlled, multicenter TOURMALINE-MM3 study (NCT02181413) compared weekly ixazomib vs placebo maintenance in NDMM patients who had at least a partial response (≥PR) to induction therapy with a PI and/or immunomodulatory drug (IMiD) followed by single ASCT. Patients were randomized (3:2) to receive ixazomib or matched placebo on days 1, 8, and 15 of 28-day cycles for up to 2 years or until progressive disease (PD) or unacceptable toxicity. Randomization was stratified by induction regimen (PI without IMiD vs IMiD without PI vs PI+IMiD), pre-induction ISS stage (I vs II or III), and post-ASCT response (complete response [CR] or very good partial response [VGPR] vs PR). Patients were ineligible if they had received post-ASCT consolidation or tandem ASCT. The ixazomib dose was 3.0 mg during cycles 1-4, increasing to 4 mg from cycle 5 if tolerated during cycles 1-4. The primary endpoint was PFS per independent review committee (IRC), who were blinded to treatment assignment. The key secondary endpoint was OS. Here, we report data from the final analysis for PFS (data cut-off: April 16, 2018). Results 656 patients were randomized (395 ixazomib; 261 placebo). Patient demographics were balanced between groups; overall median age was 57 years (range, 24-73), 37% vs 63% had ISS I vs II or III, 59%/11%/30% had received PI without IMiD / IMiD without PI / PI+IMiD induction therapy, 34%/45%/21% had achieved CR / VGPR / PR following induction/ASCT, and 18% had high-risk cytogenetics [del(17p), t(4;14), or t(14;16)]. After a median follow-up of 31 months with 54% of PFS events, there was a 28% reduction in the risk of progression/death, corresponding to a 39% improvement in PFS with ixazomib vs placebo (median 26.5 vs 21.3 months; hazard ratio [HR] 0.72; 95% CI: 0.582, 0.890; p=0.002; Figure). In a landmark analysis from ASCT, PFS was 30.7 vs 24.9 months (HR 0.684; 95% CI: 0.551, 0.848; p<0.001). Median PFS2 and OS have not yet been reached in either arm. Ixazomib maintenance led to higher rates of deepened response compared with placebo (relative risk 1.41; 95% CI: 1.10, 1.80; p=0.004). Conversion from documented MRD positivity at study entry to MRD negativity occurred at a higher rate with ixazomib compared with placebo (12% vs 7%). PFS benefit was seen broadly across subgroups, including ISS III (HR 0.661), PI-exposed (HR 0.750), PI-naïve (HR 0.497), and patients with high-risk cytogenetics (HR 0.625). Discontinuation due to AEs was low (7% ixazomib vs 5% placebo). With ixazomib vs placebo, 42% vs 26% of patients had grade ≥3 AEs; 27% vs 20% had serious AEs; and 1 patient vs 0 died on treatment. Common grade ≥3 AEs were infections (15% vs 8%) including pneumonia (6% vs 4%), gastrointestinal disorders (6% vs 1%), neutropenia (5% vs 3%), and thrombocytopenia (5% vs <1%). Peripheral neuropathy rates were 19% vs 15% (<1% vs 0 grade 3). Rate of second primary malignancies was 3% in both arms. Global Quality of Life scores (EORTC QLQ-C30) on ixazomib were similar to placebo. Conclusions This study demonstrated a 28% reduction in the risk of progression/death, corresponding to a 39% improvement in PFS with ixazomib maintenance, with deepening of responses and increased conversions to MRD negativity over control, as well as a favorable safety profile, including an absence of risk of second primary malignancies and low rates of peripheral neuropathy, supporting ixazomib as a valuable option for maintenance therapy in responding patients post-ASCT. Figure. Figure. Disclosures Dimopoulos: Janssen: Honoraria; Takeda: Honoraria; Amgen: Honoraria; Celgene: Honoraria; Bristol-Myers Squibb: Honoraria. Gay:Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen Takeda Celgene, Amgen, BMS, and Roche: Other: Advisor; Janssen, Amgen, Takeda, Celgene, BMS: Honoraria; 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; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Abbvie: Consultancy; Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; Roche: Membership on an entity's Board of Directors or advisory committees. Schjesvold:Oncopeptides: Consultancy; Abbvie: Honoraria; Novartis: Honoraria; Janssen: Consultancy, Honoraria, Research Funding; Adaptive: Consultancy; Bayer: Consultancy; Bristol Myers Squibb: Consultancy; Takeda: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Amgen: Consultancy, Honoraria, Research Funding. Beksac:Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Takeda: 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, Speakers Bureau; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen Cilag: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Deva: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Hajek:Amgen: Consultancy, Honoraria, Research Funding; Bristol Myers Squibb: Consultancy, Honoraria; Takeda: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Novartis: Research Funding. Weisel:Amgen, BMS, Celgene, Janssen, and Takeda: Honoraria; Amgen, BMS, Celgene, Janssen, Juno, Sanofi, and Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees; Amgen, Celgene, Janssen, and Sanofi: Research Funding. Goldschmidt:Novartis: Honoraria, Research Funding; Amgen: Consultancy, Research Funding; Adaptive Biotechnology: Consultancy; Sanofi: Consultancy, Research Funding; Takeda: Consultancy, Research Funding; Chugai: Honoraria, Research Funding; Bristol Myers Squibb: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; ArtTempi: Honoraria; Mundipharma: Research Funding. Maisnar:Celgene: 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; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria. Moreau:Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Abbvie: 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; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees. Chng:Merck: Research Funding; Takeda: Consultancy, Honoraria, Other: Travel, accommodation, expenses; Amgen: Consultancy, Honoraria, Other: Travel, accommodation, expenses; Aslan: Research Funding; Janssen: Consultancy, Honoraria, Other: Travel, accommodation, expenses, Research Funding; Celgene: Consultancy, Honoraria, Other: Travel, accommodation, expenses, Research Funding. Kaiser:Janssen: Consultancy, Honoraria; Takeda: Consultancy, Other: Travel Support; Bristol-Myers Squibb: Consultancy, Other: Travel support; Chugai: Consultancy, Honoraria, Research Funding; Amgen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding. Zweegman:Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene Corp.: 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; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding. Mateos:Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; GSK: Consultancy, 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; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Abbvie: Consultancy, 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; GSK: Consultancy, Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Spencer:Celgene: Honoraria, Research Funding, Speakers Bureau; Janssen-Cilag: Honoraria, Research Funding, Speakers Bureau; Amgen: Honoraria, Research Funding; BMS: Research Funding; Takeda: Honoraria, Research Funding, Speakers Bureau; STA: Honoraria. Iida:Janssen: Consultancy, Honoraria, Research Funding; Kyowa-Hakko Kirin: Research Funding; Bristol Myers Squibb: Honoraria, Research Funding; Astellas: Research Funding; Chugai: Research Funding; Novartis: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Ono: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria, Research Funding; Toyama Chemical: Research Funding; MSD: Research Funding; Gilead: Research Funding; Teijin Pharma: Research Funding; Sanofi: Consultancy. Morgan:Takeda: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Janssen: Research Funding; Bristol-Myers Squibb: Consultancy, Honoraria. Teng:Millennium Pharmaceuticals, Inc., Cambridge, MA, USA, a wholly owned subsidiary of Takeda Pharmaceutical Company Limited: Employment. Suryanarayan:Millennium Pharmaceuticals, Inc., Cambridge, MA, USA, a wholly owned subsidiary of Takeda Pharmaceutical Company Limited: Employment. Skacel:Millennium Pharmaceuticals, Inc., Cambridge, MA, USA, a wholly owned subsidiary of Takeda Pharmaceutical Company Limited: Employment; Department of Hematology, Charles University General Hospital, Prague, Czech Republic: Other: Affiliation. Dash:Takeda Pharmaceuticals International Co.: Employment. Labotka:Millennium Pharmaceuticals, Inc., Cambridge, MA, USA, a wholly owned subsidiary of Takeda Pharmaceutical Company Limited: Employment.

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

Abstract Introduction High expression of the H3K27 histone methyltransferase EZH2 mRNA in myeloma (MM) patient samples is associated with molecular features of high risk disease, including increased proliferation, and adverse outcomes (1). Mutations or deletions in the H3K27 demethylase KDM6A are associated with similar findings (2) and would be expected to have the same epigenetic effect, increasing H3K27me3 levels, a mark associated with repression of gene expression. We, therefore, sought to identify the role EZH2 plays in controlling myeloma cell proliferation. Methods A panel of MM cell lines and primary patient samples (CD138 selected from bone marrow with consent) representing a variety of different MM molecular subgroups were used. Cell viability (WST-1), cell cycle (PI) and apoptosis (AnnexinV/PI, Caspase-Glo 3/7) assays were performed. Affymetrix gene expression arrays followed by validation with RT-PCR were used to identify patterns of gene expression change with EZH2i. Western blotting confirmed changes at the protein level and Chip-PCR was performed using a validated antibody and isotype control to identify H3K27me3 changes at the relevant gene promotors. Affymetrix gene expression data for 1213 patients enrolled in the Total Therapy studies were used to investigate the relevance of our findings in myeloma patient samples. Results We confirmed a reduction in viability following EZH2i using two chemically distinct, specific small molecule inhibitors (EPZ005687 and UNC1999) and the negative control compound UNC2400. There was a reduction in viability in 6/8 cell lines and 5/6 patient samples. Response to inhibition was not related to molecular subgroup or the presence of high-risk molecular features including del17p. Global levels of H3K27me3 measured by Western blot were reduced in all cell lines regardless of response to EZH2i. In responding cell lines EZH2i induced cell cycle arrest at G1/S followed by induction of apoptosis. Gene expression arrays performed using mRNA from KMS11 and KMM1 cell lines highlighted a change in expression of cell cycle control genes associated with EZH2i. This finding was validated using qRT-PCR, which demonstrated upregulation of the cyclin dependent kinase inhibitors CDKN2B, CDKN1A or both. These findings were confirmed at the protein level by Western blotting. Chip-PCR experiment using cell lysates from KMS11 cells following incubation with EZH2i over 6 days identified changes in H3K27me3 at the promoter and transcriptional start site (PROM/TSS) regions of the CDKN2B and CDKN1A genes. The most specific changes occurred at the CDKN1A PROM/TSS, which were more heavily marked with H3K27me3 at baseline compared to a region approx. 5KB upstream. Given these results, which suggest that CDKN1A expression may be controlled by changes in H3K27me3, we explored the effect of CDKN1A mRNA expression in our patient datasets. We found the expression of EZH2 and CDKN1A to be inversely correlated (R=-0.170, p<0.0001) and that low expression of CDKN1A was associated with a significantly shorter progression free and overall survival (p<0.001). In order to confirm whether these gene expression changes could be used as a potential biomarker of response we looked at our panel of cell lines with variable responses to EZH2i. We identified a consistent increase in expression of CDKN1A only in responding cell lines suggesting it could be used as a biomarker of efficacy in the clinic. Conclusions These data support the hypothesis that CDKN1A expression is suppressed by increased H3K27me3, due to high expression of EZH2 and that this can be reversed with pharmacological EZH2 inhibition leading to a reduction in proliferation of myeloma cells. We provide data which supports the investigation of EZH2i in clinical trials of myeloma patients, which has the potential to be an effective therapeutic strategy even for those with high-risk disease, for whom current treatment approaches are ineffective.Pawlyn et al, EZH2 Overexpression in Myeloma Patients Shortens Survival and in-vitro Data Supports a Potential New Targeted Treatment Strategy. AACR and IMW abstracts, 2015Pawlyn et al, The Spectrum and Clinical Impact of Epigenetic Modifier Mutations in Myeloma. Clinical Cancer Research, 2016 Disclosures Pawlyn: Celgene: Consultancy, Honoraria, Other: Travel Support; Takeda Oncology: Consultancy. Kaiser:Celgene: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; BMS: Consultancy, Other: Travel Support; Takeda: Consultancy, Other: Travel Support; Chugai: Consultancy. Jones:Celgene: Honoraria, Research Funding. Jackson:Amgen: Consultancy, Honoraria, Speakers Bureau; Roche: Consultancy, Honoraria, Speakers Bureau; MSD: Consultancy, Honoraria, Speakers Bureau; Janssen: Consultancy, Honoraria, Speakers Bureau; Celgene: Consultancy, Honoraria, Other: Travel support, Research Funding, Speakers Bureau; Takeda: Consultancy, Honoraria, Other: Travel support, Research Funding, Speakers Bureau. Bergsagel:Novartis: Research Funding; Amgen, BMS, Novartis, Incyte: Consultancy. Morgan:Univ of AR for Medical Sciences: Employment; Janssen: Research Funding; Bristol Meyers: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding. Davies:Celgene: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Janssen: Consultancy, Honoraria.