Davies, Faith E.

Abstract Proteins in the antiapoptotic B-cell lymphoma 2 (BCL-2) family play a role in the pathophysiology of multiple myeloma (MM). Venetoclax is a highly selective, potent, oral BCL-2 inhibitor that induces apoptosis of MM cells, and its efficacy may be potentiated through combination with agents that increase BCL-2 dependency or have complementary mechanisms of action. The safety, tolerability, pharmacokinetics, and antitumor activity of venetoclax in combination with carfilzomib and dexamethasone (VenKd) in adults with relapsed/refractory MM (RRMM) were investigated in this phase 2 dose-escalation study. Oral venetoclax (400 or 800 mg) was administered daily in combination with intravenous carfilzomib (27, 56, or 70 mg/m2) and oral dexamethasone (20 or 40 mg) in 4 dose-finding cohorts. The expansion cohort received venetoclax 800 mg, carfilzomib 70 mg/m2, and dexamethasone 40 mg. Forty-nine patients received treatment. Median prior lines of therapy was 1 (range, 1-3), and median time in the study was 27 months. The most common treatment-emergent adverse events were diarrhea (65%), fatigue (47%), nausea (47%), and lymphopenia (35%). Serious adverse events occurred in 26 (53%) patients. Of 3 treatment-emergent deaths, 1 was considered treatment related. The overall response rate was 80% in all patients, 92% in patients with t(11;14) (n = 13), and 75% in patients without (n = 36). The rate of complete response or better was 41%. Median progression-free survival was 22.8 months. Treatment with VenKd was well tolerated and showed promising response rates in this RRMM patient population, with greater responses observed in patients with t(11;14). This trial is registered at www.clinicaltrials.gov as #NCT02899052.

Aims: To evaluate AMG 701, a BiTE® molecule binding BCMA on MM cells and CD3 on T cells, in RR MM (Amgen, NCT03287908); primary objective was to evaluate safety and tolerability and estimate a biologically active dose; secondary objectives were to characterize pharmacokinetics (PK), anti-myeloma activity per IMWG criteria, and response duration. Methods: Patients with MM RR or intolerant to ≥3 lines [proteasome inhibitor (PI), IMiD, anti-CD38 Ab as available] received AMG 701 IV infusions weekly in 4-week cycles until disease progression (PD). A 0.8-mg step dose was added prior to target doses ≥1.2 mg to prevent severe cytokine release syndrome (CRS). Target dose was achieved by day 8 or sooner with earlier escalation. Exclusion criteria included: solely extramedullary disease; prior allogeneic stem cell transplant (SCT) in the past 6 months; prior autologous SCT in the past 90 days; CNS involvement; prior anti-BCMA therapy. The first 3 cohorts (dose 5-45 μg) had 1 patient each, the next cohorts (0.14-1.2 mg) had 3-4 patients each, and subsequent cohorts (1.6-12 mg) were to have 3-10 patients each. Minimal residual disease (MRD) was measured by next-generation sequencing (NGS, ≤10-5 per IMWG) or flow cytometry (≤3×10-5). Results: As of July 2, 2020, 75 patients received AMG 701. Patients had a median age of 63 years, a median time since diagnosis of 5.9 years, and a median (range) of 6 (1-25) prior lines of therapy; 27% of patients had extramedullary disease, 83% prior SCT, and 93% prior anti-CD38 Ab; 68% were triple refractory to a PI, an IMiD, and an anti-CD38 Ab. Median (Q1, Q3) treatment duration was 6.1 (3.1, 15.3) weeks and median follow-up on treatment was 1.7 (1.0, 3.7) months. Patients discontinued drug for PD (n=47), AEs (adverse events, n=4, 3 CRS, 1 CMV / PCP pneumonia), withdrew consent (4), other therapy (1), investigator discretion (1), and CNS disease (1); 17 patients remain on AMG 701. The most common hematological AEs were anemia (43%), neutropenia (23%), and thrombocytopenia (20%). The most common non-hematological AEs were CRS (61%), diarrhea (31%), fatigue (25%), and fever (25%). CRS was mostly grade 1 (n=19) or 2 (n=21) per Lee Blood 2014 criteria. All grade 3 CRS (n=5, 7%) were assessed as dose-limiting toxicities (DLTs); all were reversible with corticosteroids and tocilizumab, with median duration of 2 days. CRS grade 3 drivers included transient LFT increases in 3 patients and hypoxia in 2 patients. Other DLTs were 1 case each of transient grade 3 atrial fibrillation, transient grade 3 acidosis, and grade 4 thrombocytopenia. Serious AEs (n=29, 39%) included infections (13), CRS (7), and asymptomatic pancreatic enzyme rise (2, no imaging changes, 1 treatment related). There were 4 deaths from AEs, none related to AMG 701 (2 cases of sepsis, 1 of retroperitoneal bleeding, and 1 of subdural hematoma). Reversible treatment-related neurotoxicity was seen in 6 patients, with median duration of 1 day, all grade 1-2, and associated with CRS in 4 patients. The response rate was 36% (16/45) at doses of 3-12 mg; at ≤1.6 mg (n=27), there was 1 response at 0.8 mg in a patient with low baseline soluble BCMA (sBCMA). With earlier dose escalation with 9 mg, the response rate was 83% (5/6, 3 PRs, 2 VGPRs), with 4/5 responders being triple refractory and 1 DLT of grade 3 CRS in this group. Across the study, responses included 4 stringent CRs (3 MRD-negative, 1 not yet tested), 1 MRD-negative CR, 6 VGPRs, and 6 PRs (Table). Median (Q1, Q3) time to response was 1.0 (1.0, 1.9) month, time to best response was 2.8 (1.0, 3.7) months, and response duration was 3.8 (1.9, 7.4) months, with maximum duration of 23 months; responses were ongoing at last assessment in 14/17 patients (Figure). MRD was tested in 4 patients (3 sCR, 1 CR) and all were negative (3 by NGS, 1 by flow); MRD negativity was ongoing at last observations up to 20 months later. AMG 701 exhibited a favorable PK profile in its target patient population of RR MM, with AMG 701 exposures increasing in a dose-related manner. Patient baseline sBCMA levels were identified as a determinant of AMG 701 free drug exposures; at higher doses, encouraging preliminary responses were seen even at the higher end of baseline sBCMA values. Summary: In this FIH study with ongoing dose escalation, AMG 701, an anti-BCMA BiTE® molecule, demonstrated a manageable safety profile, encouraging activity, and a favorable PK profile in patients with heavily pre-treated RR MM, supporting further evaluation of AMG 701. Disclosures Harrison: Janssen: Honoraria; Novartis: Consultancy, Honoraria, Patents & Royalties: wrt panobinostat; GSK: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Consultancy, Honoraria; CRISPR Therapeutics: Consultancy, Honoraria; Haemalogix: Consultancy; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen-Cilag: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; F. Hoffmann-La Roche: Consultancy, Honoraria. Minnema:Amgen: Honoraria; Servier: Honoraria; Gilead: Honoraria; Celgene Corporation: Honoraria, Research Funding; Janssen Cilag: Honoraria. Lee:Celgene: Consultancy, Research Funding; Genentech: Consultancy; GlaxoSmithKline: Consultancy, Research Funding; Genentech: Consultancy; Regeneron: Research Funding; Takeda: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Sanofi: Consultancy; Daiichi Sankyo: Research Funding; Amgen: Consultancy, Research Funding. Spencer:AbbVie: Consultancy, Honoraria, Research Funding; Roche: Honoraria; Takeda: Honoraria, Research Funding, Speakers Bureau; Sanofi: Consultancy, Honoraria; Amgen: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding, Speakers Bureau; Secura Bio: Consultancy, Honoraria; Servier: Consultancy, Honoraria, Research Funding; HaemaLogiX: Consultancy, Honoraria, Research Funding; BMS: Consultancy, Honoraria, Research Funding, Speakers Bureau; Pfizer: Consultancy, Honoraria; Pharmamar: Research Funding. Kapoor:Cellectar: Consultancy; Amgen: Research Funding; Janssen: Research Funding; Sanofi: Consultancy, Research Funding; Takeda: Honoraria, Research Funding; GlaxoSmithKline: Research Funding; Celgene: Honoraria. Madduri:Takeda: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Foundation Medicine: Consultancy, Honoraria; GSK: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Speaking Engagement, Speakers Bureau; Kinevant: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Speaking Engagement, Speakers Bureau; Legend: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Speaking Engagement, Speakers Bureau; Celgene: Consultancy, Honoraria. 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. Ailawadhi:Cellectar: Research Funding; BMS: Research Funding; Medimmune: Research Funding; Amgen: Research Funding; Takeda: Honoraria; Janssen: Research Funding; Pharmacyclics: Research Funding; Celgene: Honoraria; Phosplatin: Research Funding. Kaufman:Amgen: Consultancy, Honoraria; Incyte: Consultancy, Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Consultancy, Honoraria; AbbVie: Consultancy; Celgene: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Tecnopharma: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees; TG Therapeutics: Consultancy, Membership on an entity's Board of Directors or advisory committees; Sanofi/Genyzme: Consultancy, Honoraria. Raab:Takeda: Membership on an entity's Board of Directors or advisory committees; Heidelberg Pharma: Research Funding; Amgen: 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; Janssen: 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; Novartis: Membership on an entity's Board of Directors or advisory committees; Sanofi: Membership on an entity's Board of Directors or advisory committees, Research Funding. Hari:BMS: Consultancy; Amgen: Consultancy; GSK: Consultancy; Janssen: Consultancy; Incyte Corporation: Consultancy; Takeda: Consultancy. Iida:AbbVie: Research Funding; Merck Sharpe Dohme: Research Funding; Kyowa Kirin: Research Funding; Chugai: Research Funding; Sanofi: Honoraria, Research Funding; Bristol-Myers Squibb: Honoraria, Research Funding; Daiichi Sankyo: Honoraria, Research Funding; Takeda: Honoraria, Research Funding; Ono: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Janssen: Honoraria, Research Funding. Davies:Celgene/BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncopeptides: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Roche: Consultancy, Honoraria, 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; Adaptive Biotech: Honoraria; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees. Lesley:Amgen Inc.: Current Employment, Current equity holder in publicly-traded company. Upreti:Amgen Inc.: Current Employment, Current equity holder in publicly-traded company. Yang:Amgen Inc.: Current Employment, Current equity holder in publicly-traded company. Sharma:Amgen Inc.: Current Employment, Current equity holder in publicly-traded company. Minella:Amgen Inc.: Current equity holder in publicly-traded company, Ended employment in the past 24 months; Beam Therapeutics Inc.: Current Employment, Current equity holder in publicly-traded company. Lentzsch:Mesoblast: Divested equity in a private or publicly-traded company in the past 24 months; Janssen: Consultancy; Caelum Biosciences: Current equity holder in private company, Membership on an entity's Board of Directors or advisory committees; Magenta: Current equity holder in private company; Sanofi: Research Funding; Karyopharm: Research Funding; Celularity: Consultancy; Sorrento: Consultancy. OffLabel Disclosure: AMG 701, a half-life extended BiTE® (bispecific T-cell engager) molecule is an investigational agent for multiple myeloma.

Abstract There is a high background risk of venous thrombotic events (VTE) in patients with Multiple Myeloma (MM) and this is significantly increased following treatment with Thalidomide. The risk may be mediated by the production of a prothrombotic state, via an angiopathic mechanism, or alternatively it may arise from the release of prothrombotic factors from dying myeloma cells targeted by the treatment. No unifying evidence of a prothrombotic state has been demonstrated to date and it remains important to understand the mechanism underlying VTEs in order to prevent them effectively. Inherited genetic variants in the form of SNPs can affect the behaviour of clotting factors. These SNPs are functional and well characterised in the coagulation system and we have used them to analyse the mechanism underlying thalidomide induced VTE. As part of the Bank On A Cure TM project we have carried out an analysis of SNPs in 11 genes: GPIIA, ITGA, MTHFR, MTR, PPARG2, TFP1, VCAM, factor V, HABP2, prothrombin and THDB in a case series of 90 patients treated with thalidomide, with and without DVTs. This study showed a significant association with MTHFR and factor V polymorphisms. In order to validate and extend these initial observations we carried out an analysis of a second nested case control study using 131 Myeloma patients from within the MRC Myeloma IX trial, comprising 47 cases with a VTE and 94 age and sex matched controls exposed to the same treatment. We used a SNPlex panel containing 16 functional venous thrombosis associated SNPs, all of these functional polymorphisms have reported mechanisms and biology. We looked at polymorphisms in the genes: fibrinogen A (Ala331Thr), B (-455G>A, Lys478Arg) and G polypeptides (His140Tyr); Coagulation factors V(Arg534Gln), VIII (Glu1260Asp), IX(Ala194Thr), XI (Phe339Cys) and XII(-4G>T); PROCR(Gly219Ser); prothrombin(19911A>G ,20210G>A); MTHFR(Glu429Ala, Ala222Val); Serpine1(-844G>A) and TFPI(Met292Val). We have typed our selected SNPs using the SNPlex™ Genotyping System, which is based on the oligonucleotide ligation/PCR assay with a universal fluorescently labeled ZipChute™ probe detection. The probes are hybridized to complementary ZipCode™ sequences that are part of genotype-specific amplicons. Probes are eluted and detected on a Applied Biosystems 3130x DNA Analyser. This approach is an attractive alternative to existing genotyping methodologies, as it requires only three unlabeled probes per SNP, and consumes very little gDNA. The data analysis on the polymorphisms frequencies is ongoing to examine associations of thalidomide treatment with VTE events and will be presented. These datasets will allow a better definition of the pathogenesis of thalidomide related VTE, so that we can intervene therapeutically in a rational fashion.

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.

Background:Venetoclax (Ven) is a highly selective, potent, oral BCL‐2 inhibitor that induces apoptosis in malignant cells dependent on BCL‐2 for survival. Proteasome inhibitors (PIs) and dexamethasone (d) were shown to increase BCL‐2 dependence in multiple myeloma (MM) cells, and preclinical studies showed enhanced inhibition of MM tumor growth with Ven+PI compared to either alone. Moreover, d has been shown to indirectly promote BCL‐2 dependency in MM cells. Clinical trials have since demonstrated efficacy of Ven in combination with the PI bortezomib in patients (pts) with relapsed/refractory MM (RRMM).Aims:We report interim data for Ven combined with second‐generation PI carfilzomib (K) and d in pts with RRMM.Methods:In this ongoing Phase 2 study (NCT02899052), pts with RRMM (1–3 prior lines of therapy) and no prior K exposure received VenKd on 28‐day cycles in 4 dose‐finding and 1 expansion cohort: Ven 400 mg/day + K 27 mg/m2 Day 1, 2, 8, 9, 15, 16 + d 40 mg Day 1, 8, 15, 22 (Cohort 1); same regimen but with Ven 800 mg/day (Cohort 2); Ven 800 mg/day + K 70 mg/m2 Day 1, 8, 15 + d 40 mg Day 1, 8, 15, 22 (Cohort 3/expansion cohort); or Ven 800 mg + K 56 mg/m2 Day 1, 2, 8, 9, 15, 16 + d 40 mg Day 1, 2, 8, 9, 15, 16, 22, 23 (Cohort 4). Treatment continued until progressive disease or unacceptable toxicity.Results:As of the clinical data cut‐off of 1 Feb 2019, 43 pts were enrolled. Median age was 67 (range, 37–79), 26 (62%) pts had ISS II/III disease, and 8 (19%) were t (11;14)+. Median number of prior lines of therapy was 2 (range, 1–3). Forty (93%) pts received prior PI (49% refractory), 33 (77%) received prior immunomodulatory drug (IMiD, 61% refractory), and 33 (77%) received prior PI+IMiD (33% double refractory).All pts had at least 1 adverse event (AE). The most common AEs of any grade were diarrhea (65%), nausea (49%), fatigue (47%), cough (35%), insomnia, dyspnea, vomiting, upper respiratory infection (33% each), lymphopenia (28%), thrombocytopenia, and dyspepsia (26% each). Thirty‐six (84%) pts had a Grade 3/4 AE, the most common being lymphopenia (23%), pneumonia, hypertension (16% each), and hypophosphatemia (12%).The overall response rate (ORR) was 79%, complete response or better (≥CR) rate was 40%, and very good partial response or better (≥VGPR) rate was 64% for all pts (Table). Median follow‐up for 42 pts was 10.4 months (95% CI = 8.0–13.8); 15 pts had progression‐free survival (PFS) events, with median PFS yet to be achieved. Baseline bone marrow core biopsy samples from 25 pts were evaluated for BCL‐2 expression by immunohistochemistry, with high expression (≥50% of tumor cells with moderate or higher cytoplasmic staining) seen in 23 (92%) samples. Pts with high BCL‐2 expression had response rates similar to the overall study population. Other correlative biomarker analyses are ongoing.Summary/Conclusion:The combination of VenKd was found to be tolerable with no new safety signals. VenKd demonstrates promising efficacy in pts with RRMM. The study remains ongoing with an additional 60 pts with RRMM enrolling to assess efficacy and safety in a larger group of pts with similar eligibility (Cohort 6) and t (11;14)+ pts (Cohort 7).image

Key Points Using the largest set of patients with newly diagnosed myeloma, we identified 63 mutated driver genes. We identified oncogenic dependencies, particularly relating to primary translocations, indicating a nonrandom accumulation of genetic hits.

Abstract Treatment of myeloma has benefited from the introduction of more effective and better tolerated agents, improvements in supportive care, better understanding of disease biology, revision of diagnostic criteria, and new sensitive and specific tools for disease prognostication and management. Assessment of minimal residual disease (MRD) in response to therapy is one of these tools, as longer progression-free survival (PFS) is seen consistently among patients who have achieved MRD negativity. Current therapies lead to unprecedented frequency and depth of response, and next-generation flow and sequencing methods to measure MRD in bone marrow are in use and being developed with sensitivities in the range of 10−5 to 10−6 cells. These technologies may be combined with functional imaging to detect MRD outside of bone marrow. Moreover, immune profiling methods are being developed to better understand the immune environment in myeloma and response to immunomodulatory agents while methods for molecular profiling of myeloma cells and circulating DNA in blood are also emerging. With the continued development and standardization of these methodologies, MRD has high potential for use in gaining new drug approvals in myeloma. The FDA has outlined two pathways by which MRD could be qualified as a surrogate endpoint for clinical studies directed at obtaining accelerated approval for new myeloma drugs. Most importantly, better understanding of MRD should also contribute to better treatment monitoring. Potentially, MRD status could be used as a prognostic factor for making treatment decisions and for informing timing of therapeutic interventions. Clin Cancer Res; 23(15); 3980–93. ©2017 AACR.