ALBERT

Description: Minerals, Vol. 7, Pages 143: Technological and Profitable Analysis of Airlifting in Deep Sea Mining Systems Minerals doi: 10.3390/min7080143 Authors: Wenbin Ma Cees van Rhee Dingena Schott Airlifting technology utilized in deep-sea mining (DSM) industry was proposed in the 70s of last century, which was triggered by the discovery of vast amounts of mineral resources on the seabed. The objective of this paper is to assess the technological feasibility and profitability analyses in terms of solid production rate, energy consumption per tonnage of mineral, and profitability per tonnage of mineral. The effects of submergence ratio, pipe diameter, particle diameter, mining depth, and gas flux rate are investigated. The analysis is based on a numerical calculation performed in a Matlab environment. The research reported in this paper can assist to select an optimal transport plan for DSM projects depending on its solid production rate, energy consumption, and profitability.

Description: Introduction Mutant NRAS and KRAS lead to the activation of the RAS/RAF/MEK/ERK pathway in approximately 50% of multiple myeloma (MM). Blocking this pathway with MEK1/2 inhibitors (MEKi) such as trametinib (Tram) is a therapeutic option but the response rate in MM varies between 30-50% (Heuck et al, Leukemia 2015). In MM it is unknown whether RAS mutation status correlates with sensitivity to Tram. The purpose of this study was to characterize factors which predict response to Tram and to identify mechanism mediating resistance. Methods We established the IC50 of Tram using MTT assays in 32 MM cell lines (HMCL) including 16 RAS mutant positive (RASm+), and 15 wildtype RAS (RASm-), and 1 BRAF mutant (BRAFm+) line which acted as a positive control. HMCLs were classified according to the IC50 value as sensitive (10μM). All lines underwent immunoblotting for pERK at baseline and following treatment with serial concentrations of Tram to identify correlation of activation with sensitivity. BrdU incorporation analyzed by FACS was performed to determine the molecular action of Tram. A lentiviral mediated expression system was used to engineer a MAF overexpressing cell line in a RASm+ HMCL lacking MAF (MMRASm+MAF) and silencing MAF in two lines with co-occurring MAF and RASm+ (MMRASm+shMAF). The clinical characteristics of 84 relapsed RASm+ patients who received Tram either as a single agent or in combination with other anti-MM therapies were also examined. Results 6/16 (37.5%) of RASm+ HMCLs were sensitive to Tram, 5/16 (31.1%) were IMS and 5/16 (31.1%) resistant. There was no difference in sensitivity to Tram between KRASm+ (IC50 = 9.5μM, n = 11) and NRASm+ (IC50 =12.5μM, n=4, p=0.65). In contrast, 13/15 (87%) RASm- HMCLs were resistant to Tram. Mechanistically, Tram blocked cell cycle progression in Tram-sensitive RASm+ cells with an increase in G0/G1 phase (22.25%) and a decrease in S phase (16.76%) compared with untreated controls (p

Description: Introduction - Multiple Myeloma (MM) is a hematologic malignancy characterized by clonal growth of differentiated plasma cells (PCs). Despite improvement in MM therapy, the disease remains mostly incurable and is characterized by recurrent relapses with development of resistant clones that eventually lead to patient death. The pathways that lead to resistant and aggressive MM are not fully understood highlighting the need to improve our understanding of MM biology to identify potential new pathways and therapeutical targets. PHD Finger Protein 19 (PHF19) is a regulator of Polycomb Repressive Complex 2 (PRC2), the sole methyltransferase complex capable of catalyzing H3K27me3 to induce and enforce gene repression. PRC2 employs enhancer of zeste homolog 1 and 2 (EZH1/EZH2) as enzymatic subunits to hypermethylate H3K27. While overexpression and gain of function mutations of EZH1/2 have been observed in many cancers the role of this particular pathway in MM remains poorly understood. In the present study, we report on PHF19 as a new candidate gene to play a potential crucial role in MM oncogenesis. Methods- Gene expression profiling (GEP; Affymetrix U133 Plus 2.0) was performed on 739 MM patients (from total therapy trials [TT] 3-5; low risk MM n=636, high risk MM n=103), 42 patients with monoclonal gammopathy of undetermined significance (MGUS), 73 smoldering MM patients, 42 patients with primary plasma cell leukemia and 34 healthy donors. Myeloma risk was determined by the GEP 70 signature as previously defined. To test the implications of functional PHF19 knock down (KD) we used TRIPZ inducible PHF19 shRNA vs. scrambled control (Dharmacon) in two MM cell lines (JJN3 and ARP1). Real time PCR as well as western blotting was used to confirm PHF19 KD as well as to elucidate the effect on H3K27me3 (Cell Signaling). Functional in vitro studies included proliferation (Promega), clonogenic assays (StemCell), cell cycle and apoptosis assays (both Invitrogen). In vivo studies were performed using SCID mice that were subjected to tail vain injection with PHF19 KD JJN3 cells (n=10) or scrambled shRNA control (n=10). Weekly ELISA (Bethyl) and in vivo imaging (Xenogen) were performed and survival was recorded. Results- GEP of the previously mentioned patient populations and healthy controls identified PHF19 (chr9q33.2) as a candidate gene that was consistently dysregulated in MM patients. Mean expression levels at different MM stages correlated with disease aggressiveness (ANOVA, p10.46) at diagnosis correlated significantly with adverse clinical parameters, including ISS III, anemia and elevated LDH, as well as worse overall survival (5 yr OS = 29% for patients with high PHF19 expression vs 77% for patients with low PHF19 expression [log275% reduction in both cell lines, p

Description: Introduction Chromosome instability (CIN) is a driver of copy number aberrations (CNAs) in cancer, and is a major factor leading to tumor heterogeneity and resistance to therapy. By definition, CIN is an increased rate or ongoing acquisition and accumulation of CNAs and not simply the existence of structurally and numerically abnormal aneuploid clones. In multiple myeloma (MM), the most common whole-chromosome CNAs involve either hyperdiploid or non-hyperdiploid clones. Secondary segmental CNAs are associated with high-risk (HR) in MM and involve gains of 1q21 and deletions of 17p (del17p). These types of intra-chromosomal segmental CNAs are also found in the CIN phenotypes of the autosomal recessive (AR) chromosome instability syndromes. These syndromes include Fanconi anemia, Bloom's syndrome, and ICF syndrome (Immunodeficiency, Centromeric instability and Facial anomalies). These chromosome instability syndromes display a spectrum of aberrations characterized by higher rates of chromosomal breaks, chromatid exchanges, quadriradials, and pericentromeric aberrations. In particular, patients with ICF syndrome show a marked increase of 1q12 pericentromeric instability including 1q12 decondensation, triradials, multibranched chromosomes 1q, and 1q micronuclei. ICF patients also show transient 1q aberrations including isochromosome 1q (iso1q) and unbalanced translocations of 1q to 9q and 16q. In MM, we have previously reported increasing pericentromeric instability during tumor progression resulting in increasing CNAs of 1q21 by unbalanced jumping translocations of 1q12 (JT1q12). Strikingly, in a subset of MM patients with 1q21 CNAs of ≥ 5 a distinct cytogenetic phenotype emerges which demonstrates transient 1q12 aberrations including 1q12 decondensation, triradials, and multibranched chromosomes 1q morphologically identical to those seen in ICF patients. In MM this chromosome instability leads to a cascade of increasing clonal 1q21 duplications, iso 1qs, and unbalanced 1q translocations with 16q and 17p, resulting in losses in these receptor chromosomes (RC) and massive intra-clonal CNA heterogeneity. Methods To investigate the cytogenetic impact and progression of high CNAs of 1q21, we performed a comprehensive metaphase analysis of 50 patients showing segmental aneuploidies with 4 or more copies of 1q by G-banding. Locus specific FISH and spectral karyotyping were used to identify the key transient unstable and clonal structural aberrations of 1q12 resulting in segmental aneuploidies in the derivative RCs. Probe for 1q12 (Vysis) was used according to the manufacturer's protocol. Locus specific BAC clones for 1q21 (CKS1B) and 17p (TP53) were prepared and analyzed as previously described (Sawyer et al., Blood 123: 2014). IGH translocations were investigated with IGH break apart probes (Vysis). Results Data for 50 patients including CNAs of 1q21 of ≥ 4, IGH translocations, del(17p), derivative RCs, are presented. The t(4;14) was found in 15 patients, del(17p) in 23, and both aberrations were found in 8 patients. All patients showed unbalanced gains of 1q and deletions of RCs, the most frequent being 7 patients with der(1;16) and 6 with iso1q. In four of the 23 patients with del(17p), the deletion was due to a JT1q12 to 17p. Seven patients with 1q21 CNAs of ≥ 5 showed profound instability involving the 1q12 satellite DNA, demonstrating both transient and clonal aberrations driving the 1q21 CNAs. These aberrations included unstable 1q21 triplications, JT1q12s, iso1q formation with intra-arm 1q12 CNAs, and region specific breakage-fusion-bridge cycle amplifications. Conclusions Among patients with ≥ 5 CNAs of 1q21, a subset develop an acquired HR chromosome instability phenotype with an elevated rate of 1q12 pericentromeric instability characterized by concomitant deletions in 16q, iso1q, del(17p), and intra-arm segmental instability. These patients show pronounced instability in the 1q12 satellite DNA, morphologically identical to ICF syndrome, suggesting hypomethylation of this region as a driver of both 1q21 CNAs and deletions in RCs. We hypothesize that region specific hypomethylation of 1q12 provides the genomic background for the onset of an acquired 1q12 chromosome instability phenotype in MM similar to that found in ICF syndrome. For myeloma patients demonstrating this 1q12 chromosome instability phenotype we propose the term "jumping 1q syndrome." Disclosures Epstein: University of Arkansas for Medical Sciences: Employment. Davies:Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; ASH: Honoraria; Abbvie: Consultancy; TRM Oncology: Honoraria; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees; MMRF: Honoraria; Janssen: Consultancy, Honoraria. Morgan:Takeda: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Janssen: Research Funding; Bristol-Myers Squibb: Consultancy, Honoraria.

Description: Background Multiple groups of pts, including elderly/frail pts and those with comorbidities, are typically under-represented in randomized controlled trials (RCTs). A recent study found an average of 16 eligibility criteria per cancer trial, 60% of which were related to comorbidity or performance status (PS; Unger, JNCI 2014). Phase 3 RCTs in MM have similar extensive eligibility criteria, resulting in populations that are not reflective of RW MM pts. Data from CONNECT-MM (Shah, CLML, 2017) and CoMMpass (Fiala, IMW 2017) suggest that 22-40% of RW pts are ineligible for MM RCTs, and an analysis of US RW relapsed/refractory MM (RRMM) pts showed that only 25-47% of pts would have been eligible for the phase 3 ASPIRE, TOURMALINE-MM1, ELOQUENT-2, and POLLUX studies, based on their differing eligibility criteria (Chari, EHA 2018). Further, data from CONNECT MM show that clinical trial ineligibility is associated with poorer long-term outcome (Shah, CLML, 2017). Thus, it is important to characterize RW MM pts and understand the discrepancies vs RCT populations. INSIGHT MM (NCT02761187) is the largest prospective, observational study in MM to date, following ~4,200 pts from 15 countries. Here we analyze RCT eligibility in INSIGHT MM pts, with a focus on the treatment of frail MM pts in the real world. Methods INSIGHT MM is following newly diagnosed (≤3 mos since treatment initiation) MM (NDMM) and RRMM (≤3 prior lines) pts. Demographics and disease characteristics, including medical history, comorbidities, PS, and frailty status (per IMWG Frailty Index criteria, Palumbo, JCO 2015), are collected using electronic case report forms at study baseline visit. For this analysis, pt data were reviewed vs 20 standard RCT eligibility criteria, using a conservative approach of classifying 'not available' data as 'eligible'; laboratory/PS and medical history exclusion criteria are summarized in the Table. Presence of hypertension was reviewed but omitted, as INSIGHT MM only collected data on 'hypertension requiring treatment' vs the standard RCT exclusion criterion of 'uncontrolled hypertension'. Results Data from 3,201 pts (1,761 NDMM, 1,440 RRMM) were analyzed. The proportions of pts who would be ineligible for RCTs based on each individual parameter, and the overall rate of ineligible pts, are shown in the Table. Overall, 39.2% of pts would have been ineligible for RCTs based on not meeting at least one of the 20 standard eligibility criteria included in this analysis, including 38.8% of NDMM and 39.7% of RRMM pts. The most common criteria excluding pts overall were another prior malignancy (7.5%), CrCl ≤30 mL/min (6.4%), cardiac arrhythmias (5.4%), platelets ≤75,000/mm3 (5.1%), and hemoglobin

Description: Background Ixazomib, the first oral proteasome inhibitor, has been approved for 〉3 years in 〉70 countries, for the treatment of RRMM pts who have received ≥1 prior therapy, on the basis of the TOURMALINE-MM1 study, which reported an overall response rate (ORR) of 78% and median progression free survival (PFS) of 20.6 mos. Although outcomes and tolerability in routine clinical practice often differ from data reported in clinical trials, growing evidence suggest that outcomes in patients treated with ixazomib-based regimens are comparable to those in the Phase 3 TOURMALINE-MM1 trial. We report on an expanded pooled analysis with longer follow-up of IRd therapy from the INSIGHT MM study (NCT02761187) and the Czech Registry of Monoclonal Gammopathies (RMG) to evaluate the effectiveness of IRd in RRMM pts in routine clinical practice. Methods INSIGHT MM is a large, prospective, observational study which has enrolled over 4,200 adult pts with MM from Europe (plus Israel, EUR), the US, Asia, and Latin America, with a planned follow-up of ≥5 years. The RMG comprises clinical data for 〉6,000 MM pts enrolled at 19 Czech and 4 Slovak centers. Eligible pts had 1-3 (INSIGHT) or ≥1 prior therapy (RMG) including an IR-based regimen. Individual pt level data on demographics, disease characteristics, treatment history, effectiveness, and safety from INSIGHT and RMG were integrated and analyzed. Best response or time to first response and PFS were determined as per investigator assessment, using IMWG criteria. PFS, duration of treatment (DOT), and overall survival (OS) were estimated using Kaplan Meier (KM) methodology, applying an exclusion criterion to account for immortal time bias (INSIGHT only). Results At data cutoff of 22 Nov 2018, 217 pts (83 in INSIGHT and 134 in RMG) from 11 countries had been included: 191 (88%) from EUR, 17 (8%) from the US, and 9 (4%) from Taiwan; 89% of pts were treated in an academic facility. At diagnosis, 32% of pts had ISS Stage III disease, 78% had bone lesions, 46% had anemia, and 12% had elevated creatinine. At study start, median age was 67 years with 12% 〉75 years; 58%/14% of pts had ECOG performance status 1/2. The distribution of immunoglobulin (Ig) heavy and light chain MM was as expected; 69% of pts had IgG MM. Overall, 21% of pts had extramedullary disease. Prior therapies included: bortezomib (90%), stem cell transplant (60%), thalidomide (47%), lenalidomide (26%), carfilzomib (8%), daratumumab (6%), and pomalidomide (2%). Median time from diagnosis to start of IRd therapy was 42.1 mos; 43%/35%/22% of pts received IRd at 2nd/3rd/≥4th line. The most common reasons for starting IRd were relapse/progression (87%) and insufficient response (10%). The most common CRAB criteria present were bone lesions (48%) and anemia (18%). Median duration of follow-up was 12.6 mos in all pts. At data cutoff, 117 (54%) pts had discontinued IRd; median DOT was 11.9 (95% CI: 9.4-15.2) mos; at 12 mos, 49% (41.3-56.2) of pts were still on treatment (KM estimates). Data on best response to therapy were available for 152 pts. The ORR was 74%, with 36% ≥VGPR; ORR with IRd at 2nd/3rd/ ≥4th-line therapy was 82%/71%/59%, including 43%/37%/17% ≥VGPR. Median time to first response was 1.2 mos (RMG); median time to best response was 3.7 mos (INSIGHT). Median PFS was 21.6 (95% CI: 13.6-26.7) mos across all lines. PFS rate at 12 mos was 62%, and 86 (40%) pts had progressed at data cutoff. Median time to next therapy (TTNT) was 31.5 (95% CI: 24.5-35.9) mos, with a 12-month rate of 74% across all lines. Overall, 60 (28%) pts received subsequent therapies including daratumumab (22%), pomalidomide (22%), bortezomib (20%), carfilzomib (17%), lenalidomide (15%), and thalidomide (12%). At data cutoff, 53 (24%) pts had died. Median OS was 36.7 (95% CI: 24.4-NR) mos, with 79% of pts alive at 12 mos (Figure). Regarding safety, ixazomib and lenalidomide dose reductions were required in 16% and 36% of pts, respectively, including 10% and 21% who required dose reductions due to AEs. Conclusions These findings show that the effectiveness of IRd in routine clinical practice (ORR 74%, median PFS 21.6 mos) is comparable to the efficacy of IRd reported in the registrational TOURMALINE MM1 trial (ORR 78%, median PFS 20.6 mos). IRd is well tolerated with no new safety signals, and low rates of dose reductions due to AEs for ixazomib (10%) and lenalidomide (21%). Outcomes should be interpreted with caution due to limited maturity of data. Disclosures Hajek: Janssen: Honoraria, Other: Consultant or advisory relationship, Research Funding; Amgen: Honoraria, Other: Consultant or advisory relationship, Research Funding; Celgene: Honoraria, Other: Consultant or advisory relationship, Research Funding; AbbVie: Other: Consultant or advisory relationship; Bristol-Myers Squibb: Honoraria, Other: Consultant or advisory relationship, Research Funding; Novartis: Other: Consultant or advisory relationship, Research Funding; PharmaMar: Honoraria, Other: Consultant or advisory relationship; Takeda: Honoraria, Other: Consultant or advisory relationship, Research Funding. Minarik:Celgene: Consultancy, Honoraria, Research Funding; Amgen, BMS, Janssen-Cilag, Takeda: Consultancy, Honoraria. Straub:Amgen, Takeda, Celgene: Consultancy. Berdeja:Amgen Inc, BioClinica, Celgene Corporation, CRISPR Therapeutics, Bristol-Myers Squibb Company, Janssen Biotech Inc, Karyopharm Therapeutics, Kite Pharma Inc, Prothena, Servier, Takeda Oncology: Consultancy; AbbVie Inc, Amgen Inc, Acetylon Pharmaceuticals Inc, Bluebird Bio, Bristol-Myers Squibb Company, Celgene Corporation, Constellation Pharma, Curis Inc, Genentech, Glenmark Pharmaceuticals, Janssen Biotech Inc, Kesios Therapeutics, Lilly, Novartis, Poseida: Research Funding; Poseida: Research Funding. Boccadoro:AbbVie: Honoraria; Mundipharma: Research Funding; Novartis: Honoraria, Research Funding; Bristol-Myers Squibb: Honoraria, Research Funding; Sanofi: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Amgen: Honoraria, Research Funding; Janssen: Honoraria, Research Funding. Spencer:AbbVie: 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, Speakers Bureau; Haemalogix: 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, Research Funding, Speakers Bureau; Secura Bio: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Servier: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Specialised Therapeutics Australia: Consultancy, Honoraria; Sanofi: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen Oncology: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. van Rhee:Karyopharm Therapeutics: Consultancy; Kite Pharma: Consultancy; Adicet Bio: Consultancy; EUSA: Consultancy; Castleman Disease Collaborative Network: Consultancy; Takeda: Consultancy; Sanofi Genzyme: Consultancy. Thompson:Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; VIA Oncology: Membership on an entity's Board of Directors or advisory committees; Adaptive: Membership on an entity's Board of Directors or advisory committees; UpToDate: Patents & Royalties: Myeloma reviewer; GSK: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Doximity: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; AbbVie: Research Funding; BMS: Research Funding; Lynx Bio: Research Funding. Abonour:BMS: Consultancy; Celgene: Consultancy, Research Funding; Takeda: Consultancy, Research Funding; Janssen: Consultancy, Research Funding. Chari:Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncoceutics: Research Funding; Novartis Pharmaceuticals: Research Funding; GlaxoSmithKline: Research Funding; Array Biopharma: Research Funding; Karyopharm: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Millennium/Takeda: Consultancy, 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; Bristol-Myers Squibb: Consultancy; Pharmacyclics: Research Funding; Seattle Genetics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Membership on an entity's Board of Directors or advisory committees. Cook:Karyopharm: Consultancy, Honoraria, Speakers Bureau; Celgene: Consultancy, Honoraria, Research Funding, Speakers Bureau; Sanofi: Consultancy, Honoraria, Speakers Bureau; Takeda: Consultancy, Honoraria, Research Funding, Speakers Bureau; Janssen: Consultancy, Honoraria, Research Funding, Speakers Bureau. Costello:Takeda: Honoraria, Research Funding; Janssen: Research Funding; Celgene: Consultancy, Honoraria, Research Funding. Davies:Amgen, Celgene, Janssen, Oncopeptides, Roche, Takeda: Membership on an entity's Board of Directors or advisory committees, Other: Consultant/Advisor; Janssen, Celgene: Other: Research Grant, Research Funding. Hungria:Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; BMS: Consultancy, Honoraria, Speakers Bureau; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; BMS: Consultancy, Honoraria, Speakers Bureau; Abbvie: Consultancy, 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, Speakers Bureau. Lee:Amgen: Consultancy, Research Funding; GlaxoSmithKline plc: Research Funding; Sanofi: Consultancy; Daiichi Sankyo: Research Funding; Celgene: Consultancy, Research Funding; Takeda: Consultancy, Research Funding; Janssen: Consultancy, Research Funding. Leleu:Sanofi: Honoraria; Takeda: Honoraria; Oncopeptide: Honoraria; Karyopharm: Honoraria; Amgen: Honoraria; Carsgen: Honoraria; Incyte: Honoraria; Novartis: Honoraria; Celgene: Honoraria; Janssen: Honoraria; BMS: Honoraria; Merck: Honoraria. Puig:Takeda: Consultancy, Honoraria; The Binding Site: Honoraria; Janssen: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau. Rifkin:Takeda: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees. Terpos:Celgene: Honoraria; Takeda: Honoraria, Other: Travel expenses, Research Funding; Medison: Honoraria; Janssen: Honoraria, Other: Travel expenses, Research Funding; Amgen: Honoraria, Research Funding; Genesis: Honoraria, Other: Travel expenses, Research Funding. Usmani:Bristol-Myers Squibb: Consultancy, Research Funding; Sanofi: Patents & Royalties, Research Funding, Speakers Bureau; Janssen: Consultancy, Patents & Royalties, Research Funding, Speakers Bureau; Takeda: Consultancy, Patents & Royalties, Research Funding, Speakers Bureau; Celgene: Consultancy, Patents & Royalties, Research Funding, Speakers Bureau; Merck: Consultancy, Research Funding; Pharmacyclics: Patents & Royalties, Research Funding; Amgen: Consultancy, Patents & Royalties, Research Funding, Speakers Bureau; Array Biopharma: Patents & Royalties, Research Funding; Skyline DX: Consultancy. Weisel:Sanofi: Consultancy, Honoraria, Research Funding; Juno: Consultancy; GSK: Honoraria; Takeda: Consultancy, Honoraria; Amgen: Consultancy, Honoraria, Research Funding; Bristol-Myers Squibb: Consultancy, Honoraria; Celgene Corporation: Consultancy, Honoraria, Research Funding; Adaptive Biotech: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Research Funding. Zonder:Celgene Corporation: Consultancy, Honoraria, 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; 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; 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. Skacel:Millennium Pharmaceuticals, Inc., subsidiary of Takeda Pharmaceutical Company Limited: Employment. Elliott:Takeda: Employment. Demers:Takeda: Employment. Stull:Takeda: Employment. Ren:Takeda: Employment. Maisnar:Janssen, Amgen, Celgene, Takeda, BMS: Consultancy, Honoraria.

Description: Introduction Rearrangements at 8q24 are seen in up to 47% of multiple myeloma (MM) patients by a combination of fluorescence in situ hybridization (FISH), spectral karyotyping and classical cytogenetics. The gene of interest in this region is MYC, a known oncogene which acts a transcription factor and is involved in various pathways including cell cycle progression, apoptosis and cellular transformation. In myeloma, activation of MYC may be mediated through copy number changes or translocations where B-cell super-enhancers are juxtaposed to MYC resulting in its over-expression. In 30% of samples the partner super-enhancer comes from an Ig loci, and in the remainder the super-enhancer comes from genes commonly associated with myeloma such as FAM46C, FOXO3, and XBP1. The nature and extent of MYC abnormalities in MM still remains debatable, with a range of abnormalities including deletions, trisomies, jumping MYC rearrangements and translocations. Here we identify the range of abnormalities, the clonality and partner chromosomes involved. Methods We conducted a systematic investigation using interphase FISH (iFISH), gene expression profiling (GEP), karyotyping, and targeted sequencing to determine the prevalence and genetic basis for MYC aberrations in groups of plasma cell disorders incorportating monoclonal gammopathy of undetermined significance (MGUS, n=97), smoldering MM (SMM, n=64), and newly diagnosed symptomatic MM (NDMM, n=307). Two FISH probes were used that are 1 Mb telomeric and centromeric of MYC, as well as a third probe targeting MYC itself. These were co-hybridized to cells from bone marrow aspirates. Translocations were defined where the MYC probe and an adjacent probe hybridized to another chromosome, whereas jumping translocations were defined where only the MYC probe hybridized to another chromosome. Cells were also analyzed for common IGH translocations, gain of 1q and del(17p) by FISH as well as common myeloma mutations and copy number abnormalities using a targeted sequencing panel. Results By iFISH, copy number variations of either loss or gain of the 8q24 region were present in 18.2% of NDMM; and structural aberrations including translocations and jumping MYC rearrangements were present in 28.5%. By karyotyping, the partner chromosomes of the MYC translocations included 1p, 1q, 2p, 4q, 5q, 6q, 14q, or 22q. The most frequent genomic rearrangement was translocations of MYC to chromosome 1 [t(1;8)]. Altogether, MYC alterations were detected in 54.8% of NDMM patients. As the disease stage progressed more MYC abnormalities were detected from MGUS to SMM to NDMM, especially translocations (0%, 0%, 13.4%) and jumping rearrangements (4.1%, 4.7%, 15.1%). Some MYC abnormalities were detected in MGUS and SMM samples, but they consisted of many different FISH signal patterns which were present in fewer than 20% of cells, indicating a heterogeneous population of subclonal cells at the early stages of myeloma development. These subclonal populations were present in 17% of MGUS samples and 23% of SMM samples. Using gene expression arrays, samples with translocations and jumping rearrangements had higher levels of MYC expression compared to samples without these variants. Those with monosomy of MYC had lower expression of MYC and those with a heterogeneous population of abnormal MYC signals showed no difference in expression compared to samples with no abnormal signal. These data indicate that jumping MYC rearrangements result in over-expression of MYC in the same way as translocations of 8q24. However, current commercial probe designs do not incorporate the MYC locus and instead label the surrounding region. These assays do not identify jumping MYC rearrangements and as a result under-estimate the frequency of MYC abnormalities in myeloma. Conclusion MYC abnormalities are present in 54.8% of NDMM samples and occur by a variety of mechanisms from copy number changes to translocations. MYC translocations and jumping rearrangements are associated with over-expression of MYC, driving pathogenesis of the disease. MYC translocations are not present in MGUS or SMM samples, indicating this is a key lesion mediating the progression of disease to a symptomatic state. Disclosures Davies: Celgene: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Janssen: Consultancy, Honoraria. Morgan:Bristol Meyers: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Janssen: Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Univ of AR for Medical Sciences: Employment.

Description: Introduction We previously reported on the generation of highly activated/expanded natural killer cells (ENKs) after coculture with K562 cells modified to express membrane bound IL15 and 41BB-ligand. These cells have potent antimyeloma properties in vitro, in a NGS mouse model, and are safe when given to advanced multiple myeloma (MM) patients. (Szmania et al, J Immunother 2015) A potential obstacle to the effectiveness of ENK-based immunotherapy of MM is the evasion of immune recognition. We have generated 4 MM cell lines (OPM2, JJN3, ANBL6, and INA-6) which are resistant to ENK-mediated lysis to study mechanisms of resistance. These lines were derived from parental lines by repeated challenge with ENKs and maintained resistance long term when cultured without further exposure to ENKs.(Garg et al, Blood 2012, 120:4020) We have shown by stable isotope labeling with amino acids in cell culture-mass spectrometry, gene expression profiling (GEP), and flow cytometry that ICAM3 is downregulated in the ENK-resistant version of OPM2 (OPM2-R) compared to the parental OPM2. (OPM2-P; Garg et al, Blood 2013, 122:3105) We investigated OPM2-P and OPM2-R by whole exome sequencing (WES) and RNA sequencing (RNAseq) with a focus on ICAM3, evaluated ICAM3 cell surface expression on patient myeloma cells, and studied the importance of ICAM3 expression on ENK functionality. Methods DNA and RNA were extracted from OPM2-P and OPM2-R cells using the Qiagen AllPrep kit. WES libraries were prepared with the Agilent qXT and Agilent SureSelect Clinical Research Exome kits with additional baits covering the Ig and MYC loci. RNAseq libraries were prepared using the Illumina TruSeq stranded mRNA kit. Samples were sequenced 100bp PE on an Illumina HiSeq2500. Samples for WES were sequenced to a mean coverage of 〉120x and RNAseq to a target of 〉100M reads. WES data were aligned to the Ensembl GRCh37/hg19 human reference using BWA mem. Somatic variants were called MuTect. RNAseq data were analyzed using Tuxedo Suite. Data were aligned to the Ensembl GRCh37/hg19 human reference using TopHat with Bowtie2. Transcriptome reconstruction, quantification and differential analysis was performed using CuffLinks. ENK-mediated lysis of myeloma cells was measured by 4 hour chromium release assay in the presence of isotype or ICAM3 blocking antibody. Bone marrow aspirates were obtained from MM patients after informed consent in accordance with the Declaration of Helsinki. Primary myeloma cells were selected with CD138-coated immunomagnetic beads and ICAM3 expression was assessed by flow cytometry gated on viable CD138 positive cells. Results There was no mutation in ICAM3 in OPM2-R by WES, but RNAseq found a significant reduction in ICAM3 RNA in OPM2-R compared to OPM2-P (p

Description: Introduction: Despite the enormous progress in MM therapy brought about by the rapid development of many novel agents, many patients end up with limited treatment options. We have previously reported on the efficacy and safety of metro16 in RRMM (Papanikolaou, Haematology 2013). Here we are reporting on an extension of such treatment to 28 d (metro28). Patients and Methods: The treatment consisted of a cycle of 28d continuous iv infusions of ADR and DDP each at 1mg/m2/d, along with thalidomide 50 to 100mg/d x 28; bortezomib 0.8 to 1.0mg/m2 on days 1, 4, 7, 10, 13, 16, 19, 22, 25, 28; DEX 8 to 12mg on days 1-4, 7-10, 13-16, 19-22, 25-28; some patients also received vincristine 0.07mg flat dose by CI for 28 days. This was off-protocol therapy that patients provided written informed consent for. The IRB permitted data retrieval and analysis. Results: 150 patients were identified, virtually all had received prior tandem transplants, bortezomib, lenalidomide, carfilzomib and pomalidomide. The median age was 64yr; B2M was elevated 〉=3.5mg/L in 48%, abnormal cytogenetics (CA) were present in 86%, and 44% had GEP70-defined high risk MM. Figure 1 portrays clinical outcomes. As of April 2015, 60 patients had died, and the 2-yr OS estimate was 45% (Figure 1A); the 6-mo PFS estimate was 31% although 15% had no progression at 18mo (Figure 1B). Analysis by GEP70 and GEP5 risk revealed 18-mo OS estimates of 80% among the 53 patients with low risk in both models, whereas the presence of high risk (HRMM) in either model conferred a significantly reduced 18-mo OS estimate of 25% (p

Description: 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.