Citations

Background: NGS of myeloid mutations is an integral part of AML clinical decision-making. There is currently no information regarding concordance between NGS panels in AML using samples from the same patient across various platforms in different diagnostic laboratories. To study this important question, we analyzed NGS of myeloid mutations in diagnostic samples from The Beat AML Master Trial (BAMT) for newly diagnosed older AML patients, and compared variant calls made between institutional laboratories enrolling the study subject with those made by Foundation Medicine (FM), the central laboratory used for treatment assignment in this precision medicine trial. Methods: We identified newly diagnosed AML patient samples (peripheral blood (PB) and/or bone marrow (BM)) from 2 lead institutions in the BAMT(Ohio State, OSU and Oregon Health and Sciences University, OHSU) that were analyzed by both the institutional and by FM from Nov 15, 2016 to Apr 15, 2019. Samples sent to both laboratories >3 days apart were excluded. Samples were analyzed at the institutional laboratories using their respective NGS mutational panels and by FM using the FoundationOne®Heme(FMH) NGS panel which utilizes capture based sequencing. The OSU NGS assay utilizes sequencing on Illumina MiSeq. The OHSU NGS assay employs semiconductor-based sequencing (Ion Torrent PGM platform). The variant allele frequency (VAF) sensitivity for detection for all 3 laboratories range from 1-2%. We evaluated the ability to identify mutations in 8 genes : FLT3, IDH1/ 2, NPM1, TET2, DNMT3A, WT1 and TP53 used in treatment assignment in theBAMT. A detection cutoff of 2% was used to define the presence or absence of a mutation. Overall, agreement was defined as the number of times the local and central laboratories made the same call divided by the total number of patients. Sensitivity was defined as the number of present calls made locally divided by the number of present calls made centrally, and specificity as the number of absent calls made locally divided by the number of absent calls made centrally. The overall kappa statistic, controlling for institution, provided another measure of agreement between local and central calls, where a value of 1 indicates perfect agreement. Results: 194 patient samples were identified using methods above and analyzed locally at the screening institution (125 at OSU, 69 at OHSU) and centrally at FM. Type of tissue analyzed for variants between local site and FM were 59 PB, 129 BM, and 6 with BM/PB mismatch. Overall agreement in presence/absence calls between local and central results for each of the 8 genes was over 95% (Table 1). There was perfect agreement for NPM1. The sensitivity was above 94% for all genes except TP53 (88.6%) and WT1 (63.6%). Failure to detect a mutation locally was primarily due to reporting of all TP53 variants, including variants of unknown significance (VUS) (5) by FM as agreed upon in the study protocol, detection at low levels below local site sensitivity cutoff (1), detection of variants in a portion of gene not covered at the local site(1)and possible artifact (1). For the WT1 gene, discordance in 5 samples included VUS (3) reported by FM ,a variant detected in a portion of the gene not covered at the local site(1).and difference in leukemic tissue analyzed with mutation not detected by the central laboratory on a PB sample, and present at the institutional lab on a BM sample; affecting the overall agreement and specificity but not sensitivity. Specificity was at least 98% for each of the 8 genes. Finally, most discrepancies in reported mutations in FLT3 (n=2), IDH1 (n=1), IDH2 (n=2), DNMT3A (n=4) and TET2 (n=5) were due to reporting of VUS in one laboratory and not by another. Conclusion: Detection of pathogenic myeloid mutations using orthogonal assays showed a high degree of concordance for genes used in therapeutic assignment on the BAMT.The small number of discordant results, in TP53 and WT1, were attributed to the reporting of VUS. This study illustrates the importance of quality control and standardization as NGS continues to be widely utilized in AML for clinical decision making, with a variety of platforms across multiple laboratories. Our next steps involve evaluating the differences in VAFs reported between local and central laboratories when a given mutation is identified, as well as the potential reasons for observed differences and clinical implications of known pathogenic mutations vs putative VUS. Disclosures Borate: Daiichi Sankyo: Consultancy; AbbVie: Consultancy; Novartis: Consultancy; Takeda: Consultancy; Pfizer: Consultancy. Vergilio:Foundation Medicine: Employment; Roche Holding AG: Equity Ownership. Stein:Novartis: Membership on an entity's Board of Directors or advisory committees; Celgene Corporation: Membership on an entity's Board of Directors or advisory committees; Daiichi Sankyo, Inc.: Membership on an entity's Board of Directors or advisory committees; Agios: Consultancy, Membership on an entity's Board of Directors or advisory committees; Astellas Pharma US, Inc: Membership on an entity's Board of Directors or advisory committees; Bioline: Membership on an entity's Board of Directors or advisory committees; Genentech: Membership on an entity's Board of Directors or advisory committees; PTC Therapeutics: Membership on an entity's Board of Directors or advisory committees; Syros: Membership on an entity's Board of Directors or advisory committees. Patel:France Foundation: Honoraria; Dava Oncology: Honoraria; Celgene: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Baer:Astellas: Research Funding; Abbvie: Research Funding; AI Therapeutics: Research Funding; Forma: Research Funding; Incyte: Research Funding; Kite: Research Funding; Takeda: Research Funding. Stock:Daiichi: Membership on an entity's Board of Directors or advisory committees; Astellas: Membership on an entity's Board of Directors or advisory committees; Agios: Membership on an entity's Board of Directors or advisory committees; Research to Practice: Honoraria; UpToDate: Honoraria; Kite, a Gilead Company: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees. Schiller:Amgen: Other, Research Funding; Astellas: Research Funding; Biomed Valley Discoveries: Research Funding; Bristol Myer Squibb: Research Funding; Celgene: Research Funding, Speakers Bureau; Constellation Pharmaceutical: Research Funding; Daiichi Sankyo: Research Funding; Eli Lilly and Company: Research Funding; FujiFilm: Research Funding; Genzyme: Research Funding; Gilead: Research Funding; Incyte: Research Funding; J&J: Research Funding; Jazz Pharmaceuticals: Honoraria, Research Funding; Karyopharm: Research Funding; Novartis: Research Funding; Onconova: Research Funding; Pfizer Pharmaceuticals: Equity Ownership, Research Funding; Sangamo Therapeutics: Research Funding; Agios: Research Funding, Speakers Bureau. Blum:AmerisourceBergen: Consultancy; Boehringer Ingelheim: Research Funding; Celgene: Research Funding; Astellas,: Research Funding; Xencor: Research Funding; Forma: Research Funding. Kovacsovics:Pfizer: Research Funding; Jazz: Consultancy; Novartis: Research Funding; Abbvie: Research Funding; Amgen: Consultancy, Research Funding. Foran:Agios: Honoraria, Research Funding. Druker:Pfizer: Research Funding; OHSU (licensing fees): Patents & Royalties: #2573, Constructs and cell lines harboring various mutations in TNK2 and PTPN11, licensing fees ; Cepheid: Consultancy, Honoraria; Aileron Therapeutics: #2573, Constructs and cell lines harboring various mutations in TNK2 and PTPN11, licensing fees , Membership on an entity's Board of Directors or advisory committees; ALLCRON: Membership on an entity's Board of Directors or advisory committees; Amgen: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Aptose Biosciences: Consultancy, Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Beta Cat: Membership on an entity's Board of Directors or advisory committees, Other: Stock options; GRAIL: Equity Ownership, Other: former member of Scientific Advisory Board; Patient True Talk: Consultancy; The RUNX1 Research Program: Membership on an entity's Board of Directors or advisory committees; Vivid Biosciences: Membership on an entity's Board of Directors or advisory committees, Other: Stock options; Beat AML LLC: Other: Service on joint steering committee; CureOne: Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy; Gilead Sciences: Other: former member of Scientific Advisory Board; ICON: Other: Scientific Founder of Molecular MD, which was acquired by ICON in Feb. 2019; Monojul: Other: former consultant; Novartis: Other: PI or co-investigator on clinical trial(s) funded via contract with OHSU., Patents & Royalties: Patent 6958335, Treatment of Gastrointestinal Stromal Tumors, exclusively licensed to Novartis, Research Funding; Bristol-Myers Squibb: Other: PI or co-investigator on clinical trial(s) funded via contract with OHSU., Research Funding; Pfizer: Other: PI or co-investigator on clinical trial(s) funded via contract with OHSU., Research Funding; Merck & Co: Patents & Royalties: Dana-Farber Cancer Institute license #2063, Monoclonal antiphosphotyrosine antibody 4G10, exclusive commercial license to Merck & Co; Dana-Farber Cancer Institute (antibody royalty): Patents & Royalties: #2524, antibody royalty; Burroughs Wellcome Fund: Membership on an entity's Board of Directors or advisory committees; Blueprint Medicines: Consultancy, Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Patents & Royalties, Research Funding. Byrd:Gilead: Other: Travel Expenses, Research Funding, Speakers Bureau; Genentech: Research Funding; Acerta: Research Funding; TG Therapeutics: Other: Travel Expenses, Research Funding, Speakers Bureau; Novartis: Other: Travel Expenses, Speakers Bureau; Pharmacyclics LLC, an AbbVie Company: Other: Travel Expenses, Research Funding, Speakers Bureau; Janssen: Consultancy, Other: Travel Expenses, Research Funding, Speakers Bureau; BeiGene: Research Funding; Ohio State University: Patents & Royalties: OSU-2S. Levine:C4 Therapeutics: Membership on an entity's Board of Directors or advisory committees; Isoplexis: Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Research Funding; Roche: Consultancy, Research Funding; Loxo: Membership on an entity's Board of Directors or advisory committees; Qiagen: Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria; Prelude Therapeutics: Research Funding; Novartis: Consultancy; Gilead: Consultancy; Lilly: Honoraria; Imago Biosciences: Membership on an entity's Board of Directors or advisory committees. Mims:Jazz Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Astellas Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; PTC Therapeutics: Membership on an entity's Board of Directors or advisory committees; Agios Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees.

Abstract Heritable mitochondrial DNA (mtDNA) mutations are common, yet only a few recurring pathogenic mtDNA variants account for the majority of known familial cases in humans. Purifying selection in the female germline is thought to be responsible for the elimination of most harmful mtDNA mutations during oogenesis. Here we show that deleterious mtDNA mutations are abundant in ovulated mature mouse oocytes and preimplantation embryos recovered from PolG mutator females but not in their live offspring. This implies that purifying selection acts not in the maternal germline per se, but during post-implantation development. We further show that oocyte mtDNA mutations can be captured and stably maintained in embryonic stem cells and then reintroduced into chimeras, thereby allowing examination of the effects of specific mutations on fetal and postnatal development.

Abstract Introduction: Mutations localized in the tyrosine kinase domain activation loop of FLT3 (FLT3-TKD), representing point mutations in codon D835/I836 and rarely deletions of codon I836, induce constitutive tyrosine phosphorylation and activation of the receptor tyrosine kinase similarly to FLT3 internal tandem duplication (ITD) mutations. However, the prognostic role of FLT3-TKD in AML, particularly in the presence of NPM1 mutations, is not well established. The phase 3 RATIFY trial [NCT00651261; Stone et al. N Engl J Med. 2017] showed that in combination with standard chemotherapy, midostaurin (PKC412) improved survival outcomes across all 3 FLT3 stratification subgroups (ITD high allelic ratio [≥ 0.7], ITD low allelic ratio [< 0.7], and TKD) vs placebo in patients with newly diagnosed FLT3-mutated AML. Here, we evaluated the prognostic impact of FLT3-TKD and NPM1 mutations in a post hoc analysis from the RATIFY trial. Methods: In RATIFY, newly diagnosed patients with AML 18-60 years old were randomly assigned to receive midostaurin or placebo together with standard induction and consolidation therapy followed by 12 28-day cycles of maintenance therapy with midostaurin or placebo. FLT3-TKD mutation was detected by PCR and capillary electrophoresis at 9 reference laboratories. Patients were categorized as NPM1 mutated (mut) or NPM1 wild-type (WT) using PCR. Efficacy outcomes included complete remission (CR), overall survival (OS), event-free survival (EFS) and disease-free survival (DFS). EFS and DFS analyses were performed considering CR within a 60-day window. P values presented have not been adjusted for multiplicity. Results: Of the total randomized 162 FLT3-TKD patients, 134 with available NPM1 data had consented for exploratory analysis and thus were included in this study (see Table for subgroup distribution). Overall, 47.8% of patients were male, and the median age was 49 years (95% CI, 45.5-51.1 years). The median white blood cell (WBC) count was higher in patients with NPM1-mut than in patients with NPM1-WT (34.1 vs 15.5 × 109/L, P = .0011). CR rates (during the first 60 days) were higher in patients with FLT3-TKD/NPM1-mut vs FLT3-TKD/NPM1-WT (66% vs 53%); however, this was driven by the higher rate of CR in the midostaurin arm (76% NPM1-mut vs 44% NPM1-WT) rather than the placebo arm (53% NPM1-mut vs 60% NPM1-WT). The overall CR rate (regardless of NPM1 genotype) was 64% for midostaurin and 56% for placebo in FLT3-TKD patients. The prognostic effect of the NPM1 mutation concurrent with FLT3-TKD was seen for all endpoints consistently with hazard ratios (HRs) around 0.50 or lower (Figures 1 and 2 and Table). Overall (regardless of treatment) OS, EFS, and DFS estimates at 3 years were 73% vs 52%, 48% vs 25%, and 74% vs 47%, respectively, in patients with FLT3-TKD/NPM1-mut vs FLT3-TKD/NPM1-WT. Whereas the HRs for midostaurin vs placebo were 0.73 for both OS and EFS, the impact of treatment on outcomes varied between the individual NPM1/TKD subgroups and was not consistently observed when endpoints were censored at stem cell transplant (SCT) (Table). It should be noted that the number of patients in each subgroup was small and therefore the HRs with 95% CIs should be interpreted with caution. Multivariate analyses in these FLT3-TKD patients revealed that NPM1 genotype was an independent prognostic factor for OS, EFS and DFS (2-sided P < .05), whereas study drug, age, sex, WBC at baseline and SCT (no/yes) did not reach this level of significance in the Cox model. Conclusions: This post hoc analysis of the FLT3-TKD patient subset in the RATIFY trial showed the high prognostic value of NPM1 mutational status. Whereas midostaurin showed an overall benefit in the FLT3-TKD patients for OS, EFS, CR and DFS, the impact of treatment on outcome varied between the individual NPM1 subgroups within these FLT3-TKD patients and was not consistently observed.Further analyses using additional endpoints and additional multivariate analyses are planned. Support: U10CA180821, U10CA180882, U10CA180820, U10CA180791, U10CA180888, U10CA180863, (CCSRI) #704970, U24CA196171; ClinicalTrials.gov Identifier: NCT00651261 Disclosures Voso: Celgene: Research Funding, Speakers Bureau. Larson:Ariad/Takeda: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; BristolMyers Squibb: Consultancy, Research Funding. Heuser:Janssen: Consultancy; Pfizer: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria, Research Funding; StemLine Therapeutics: Consultancy; Astellas: Research Funding; BergenBio: Research Funding; Karyopharm: Research Funding; Bayer Pharma AG: Consultancy, Research Funding; Tetralogic: Research Funding; Sunesis: Research Funding; Daiichi Sankyo: Research Funding. Wei:Novartis: Honoraria, Other: Advisory committee, Research Funding, Speakers Bureau; Pfizer: Honoraria, Other: Advisory committee; Amgen: Honoraria, Other: Advisory committee, Research Funding; Abbvie: Honoraria, Other: Advisory board, Research Funding, Speakers Bureau; Servier: Consultancy, Honoraria, Other: Advisory committee, Research Funding; Celgene: Honoraria, Other: Advisory committee, Research Funding. Brandwein:Lundbeck: Consultancy; Celgene: Consultancy; Pfizer: Consultancy; Novartis: Consultancy; Boehringer Ingelheim: Consultancy, Research Funding. de Witte:Novartis: Research Funding; Amgen: Consultancy, Research Funding; Celgene: Honoraria, Research Funding. Medeiros:Celgene: Consultancy, Research Funding; Genentech: Employment. Tallman:Cellerant: Research Funding; Orsenix: Other: Advisory board; BioSight: Other: Advisory board; ADC Therapeutics: Research Funding; AROG: Research Funding; AbbVie: Research Funding; Daiichi-Sankyo: Other: Advisory board. Schlenk:Pfizer: Research Funding, Speakers Bureau. Ganser:Novartis: Membership on an entity's Board of Directors or advisory committees. Cheng:Novartis: Employment. Gathmann:Novartis: Employment. Tiecke:Novartis: Employment. Thiede:AgenDix: Other: Ownership; Novartis: Honoraria, Research Funding. Döhner:AbbVie: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Seattle Genetics: Consultancy, Honoraria; Celator: Consultancy, Honoraria; Sunesis: Consultancy, Honoraria, Research Funding; Bristol Myers Squibb: Research Funding; Novartis: Consultancy, Honoraria, Research Funding; Seattle Genetics: Consultancy, Honoraria; AROG Pharmaceuticals: Research Funding; Sunesis: Consultancy, Honoraria, Research Funding; Astellas: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria; AROG Pharmaceuticals: Research Funding; Celator: Consultancy, Honoraria; Astex Pharmaceuticals: Consultancy, Honoraria; Bristol Myers Squibb: Research Funding; Agios: Consultancy, Honoraria; Agios: Consultancy, Honoraria; Astellas: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Astex Pharmaceuticals: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Jazz: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Jazz: Consultancy, Honoraria; Pfizer: Research Funding; Pfizer: Research Funding; Novartis: Consultancy, Honoraria, Research Funding. Stone:Otsuka: Consultancy; Argenx: Other: Data and Safety Monitoring Board; Amgen: Consultancy; Agios: Consultancy, Research Funding; Orsenix: Consultancy; Ono: Consultancy; Novartis: Consultancy, Research Funding; Astellas: Consultancy; Arog: Consultancy, Research Funding; Merck: Consultancy; Cornerstone: Consultancy; Fujifilm: Consultancy; Jazz: Consultancy; Celgene: Consultancy, Other: Data and Safety Monitoring Board, Steering Committee; Pfizer: Consultancy; Sumitomo: Consultancy; AbbVie: Consultancy.

Abstract Introduction: Selinexor is a novel, oral Selective Inhibitor of Nuclear Export (SINE) compound that blocks exportin 1 (XPO1). Selinexor treatment results in nuclear accumulation and activation of tumor suppressor proteins, inhibition of NF-kB, and translational suppression of several oncoprotein mRNAs (e.g., c-myc, cyclin D).Multiple myeloma (MM) remains incurable, and most patients (pts) eventually progress through standard drug classes of proteasome inhibitors (PIs), immunomodulatory drugs (IMiDs), anti-CD38 mAbs and others. The increased use of combinations in MM treatment, (PIs/IMiDs/mAbs), has led to a growing number of pts with penta-refractory MM (pts that have been treated with bortezomib (bort), carfilzomib (carfil), lenalidomide (len), pomalidomide (pom) and daratumumab (dara)). Active novel therapies with different mechanisms of actions are needed to address this unmet medical need. Part 1 of STORM enrolled pts with both quad- (bort, carfil, len, pom, treated MM) or penta-refractory MM and demonstrated an overall response rate (ORR) of 21% (Vogl et al, JCO 2018). Based on these findings, the Pivotal Part 2 of STORM was initiated, enrolling an additional cohort of 122 patients with penta-refractory MM. Methods: Pts with penta-refractory MM were treated with 80 mg selinexor plus 20 mg dexamethasone (Sd) twice weekly. Pts must have received an alkylator, bort, carfil, len, pom and dara, and had MM refractory to ≥1 PI, ≥1 IMiD, dara, a glucocorticoid, and their last therapy. Pts must have a total ANC ≥1000 mm3,platelets ≥50k/mm3 (or ≥75k if marrow plasma cells <50%), and creatinine clearance ≥20 mL/min. The primary endpoint was ORR. Secondary endpoints: duration of response (DOR), clinical benefit rate (CBR), progression free survival (PFS), and overall survival (OS). Efficacy was assessed by an Independent Review Committee (IRC) based on IMWG criteria. OS was also compared to a cohort of pts with PI, IMiD, dara refractory MM from the Flatiron Health Analytic Database (FHAD), (ref: ASH 2018 abs ID: 116493),who met all the inclusion criteria for STORM. Results: As of 1-Jun-2018, 122 pts (71 M/ 51 F) were enrolled in 38 sites (US and EU). Pt characteristics were [medians (range)]: age 65 yrs (40-85); 7 (3 - 18) prior treatment regimens, 6.6 yrs (<1 - 23.4) from initial MM diagnosis.65 pts (53%) had high risk cytogenetics, 86 pts (70%) had prior dara in combination, 102 pts (84%) had prior stem cell transplantation, 2 pts had prior CAR-T therapy. All pts enrolled with progressive disease (PD), 72% of pts had increases (3% - 792%) in MM markers from screening to C1D1 (median 11 days). Frequently reported Sd treatment related adverse events (AEs) included (all grades, grades 3/4): thrombocytopenia (67%, 53%), nausea (67%, 10%), fatigue (68%, 21%), anorexia (50%, 2%), anemia (46%, 28%), and weight loss (46%, 0%). Eight pts remain on study and 114 pts discontinued treatment (most commonly for PD). There were 4 deaths on treatment: sepsis, respiratory failure, pulmonary embolism, and an unrelated, unspecified cardiac event. IRC determined ORR (≥PR) was 26.2%, with 6.5% ≥ very good partial response, including 2 stringent complete responses (sCRs; MRD negative at 1:10-6 and at 1:10-4sensitivity). Both pts who relapsed after CAR-T achieved PRs. The CBR (≥minimal response, [MR]) was 39.3%, and 79% of pts achieved ≥stable disease (SD). Responses typically occurred within the first month. Medians: DOR 4.4 months (mo) (range <1 - 10 mo), PFS 3.7 mo, and OS 8.0 mo. Pts with ≥MR had significantly longer OS than pts with PD/NE (median not reached vs 1.9 mo, p=<0.0001). Compared to the FHAD cohort, STORM cohort had longer OS (Figure 1, HR 0.41, p=0.0001). Conclusions: Results of the pivotal STORM Part 2 in penta (PI, IMiD, dara)-refractory MM demonstrated that oral selinexor plus low-dose dexamethasone (Sd) was highly active with an ORR of 26.2%. Importantly, responses were rapid and deep with 2 patients achieving sCRs (both MRD negative) in these heavily pre-treated penta-refractory MM pts (median 7 prior regimens, 53% high risk). AEs are a function of dose/schedule/disease severity and can be managed with dose modifications and supportive care. No major organ toxicity was observed and AEs were typically transient and reversible. Sd is an all-oral, first in class mechanism with novel MOA and represents a potential therapeutic option to the growing number of pts with penta-refractory MM who have exhausted approved therapies. Disclosures Chari: Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive Biotechnology: Membership on an entity's Board of Directors or advisory committees; The Binding Site: Consultancy; Seattle Genetics: Membership on an entity's Board of Directors or advisory committees; Array Biopharma: Research Funding; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pharmacyclics: Research Funding; Takeda: Consultancy, 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, Research Funding; Bristol Myers Squibb: Consultancy. Vogl:Karyopharm Therapeutics: Consultancy. Dimopoulos:Takeda: Honoraria; Bristol-Myers Squibb: Honoraria; Janssen: Honoraria; Amgen: Honoraria; Celgene: Honoraria. Nooka:GSK: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees; Adaptive technologies: Consultancy, Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; BMS: Consultancy, Membership on an entity's Board of Directors or advisory committees; Spectrum Pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees. Moreau:Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Abbvie: 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. Cole:University of Michigan: Employment; Cancer Support Community myeloma advisory board: Membership on an entity's Board of Directors or advisory committees. Dingli:Millennium Takeda: Research Funding; Alexion Pharmaceuticals, Inc.: Other: Participates in the International PNH Registry (for Mayo Clinic, Rochester) for Alexion Pharmaceuticals, Inc.; Alexion Pharmaceuticals, Inc.: Other: Participates in the International PNH Registry (for Mayo Clinic, Rochester) for Alexion Pharmaceuticals, Inc.; Millennium Takeda: Research Funding. Vij:Jazz Pharmaceuticals: Honoraria; Karyopharm: Honoraria; Janssen: Honoraria; Amgen: Honoraria; Takeda: Honoraria, Research Funding; Bristol Myer Squibb: Honoraria, Research Funding; Celgene: Honoraria, Research Funding. Raab:BMS: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria; Amgen: Consultancy, Honoraria, Research Funding. Weisel:Amgen, BMS, Celgene, Janssen, and Takeda: Honoraria; Amgen, Celgene, Janssen, and Sanofi: Research Funding; Amgen, BMS, Celgene, Janssen, Juno, Sanofi, and Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees. Delforge:Celgene and Janssen: Research Funding; Amgen, Celgene, Janssen and Takeda: Consultancy. Stewart:Amgen Inc., BMS, Celgene, Takeda, Roche, Seattle Genetics, Janssen, Ono: Consultancy; Amgen Inc., Celgene, Roche, Seattle Genetics: Research Funding. Mohty:Amgen: Consultancy, Honoraria; Molmed: Consultancy; Sanofi: Consultancy, Honoraria, Research Funding, Speakers Bureau; Servier: Consultancy; Jazz Pharmaceuticals: Honoraria, Research Funding, Speakers Bureau; Janssen: Honoraria, Research Funding, Speakers Bureau; MaaT Pharma: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Honoraria; Takeda: Honoraria, Speakers Bureau; Bristol Myers: Consultancy, Research Funding. Sylvain:Gilead: Other: scientific advisor board. Costa:Celgene: Honoraria, Research Funding; Abbvie: Research Funding; Karyopharm: Research Funding; Janssen: Research Funding; Amgen: Honoraria, Research Funding; Sanofi: Honoraria; BMS: Research Funding. Shah:Karyopharm Therapeutics: Employment. Picklesimer:Karyopharm Therapeutics: Employment. Saint-Martin:Karyopharm Therapeutics: Employment. Li:Karyopharm Therapeutics: Employment. Kauffman:Karyopharm Therapeutics: Employment, Equity Ownership, Membership on an entity's Board of Directors or advisory committees. Shacham:Karyopharm Therapeutics: Employment, Equity Ownership, Membership on an entity's Board of Directors or advisory committees. Richardson:Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Jazz Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding; Karyopharm: Membership on an entity's Board of Directors or advisory committees; BMS: Research Funding; Amgen: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees. Jagannath:Celgene: Consultancy; Bristol-Myers Squibb: Consultancy; Multiple Myeloma Research Foundation: Speakers Bureau; Medicom: Speakers Bureau; Novartis: Consultancy; Merck: Consultancy.

Background The incidence of VTE in African-Americans (AAs) is similar to or higher than in Americans of European ancestry. However, the carrier frequencies of inherited thrombophilias common in whites (i.e., Factor V Leiden, Prothrombin G20210A) are very low in AAs, suggesting that other inherited thrombophilias may be associated with VTE in AAs. Objective To identify potentially novel non-hypothesis-driven single nucleotide polymorphisms (SNPs) associated with VTE in AAs. Methods We used the resources of the eMERGE Network to perform a GWAS of VTE in AAs. The eMERGE Network (funded by NHGRI) is comprised of nine sites each with DNA biobanks linked to electronic health records (EHRs). Approximately 39,206 unique DNA samples have been genotyped using either Affymetrix or Illumina genome-wide SNP arrays. Led by the Coordinating Center and eMERGE genomics workgroup, an imputation pipeline was developed for merging genomic data across the different SNP arrays used by the eMERGE sites, to maximize sample size and the power to detect associations. The imputation was performed using the 1000 Genomes Cosmopolitan reference panel which includes 1092 individuals and over 36 million SNPs. From our previously-identified cohort of Olmsted County, MN residents with incident or recurrent VTE, 1996-2005, we derived and validated an EHR-driven phenotype extraction algorithm that leveraged structured data based on ICD-9-CM codes and unstructured data from clinical notes via natural language processing to identify VTE cases and controls with 100% and 94% positive and negative predictive values, respectively. We tested for an association between each SNP and VTE among AAs using unconditional logistic regression, adjusting for age, sex and eMERGE site. Results Among 294 AA VTE cases and 3,661 AA controls (total n=3,955; females, n=2,512), the Factor V Leiden (F5 rs6025) was not analyzed due to a very low minor allele frequency (MAF=0.0036). The prothrombin G20210A (F2 rs1799963) and ABO blood type O (ABO rs8176719) SNPs were not genotyped in any of the arrays and could not be imputed. Among SNPs with an imputation score >0.8, the most significant SNPs associated with VTE were ITPR3 (inositol 1,4,5-triphosphate receptor type 3) rs2229637 (OR=1.65; p=3.61E-07; MAF=0.19) and CLEC7A (C-type lectin domain family 7, member A) rs59819090 (OR=2.16; p=1.06E-06; MAF=0.056). ITPR3 SNPs have been associated with coronary artery aneurysm in Kawasaki disease, type 1 diabetes mellitus and other autoimmune disorders. CLEC7A rs59819090 encodes for a serine82 to leucine nonsynonymous amino acid change in dectin-1. Dectin-1 is a transmembrane innate immune pattern recognition receptor on myeloid cells that upon binding it’s agonist, β-glucans, stimulates cytokine production and the respiratory burst, a prerequisite for formation of neutrophil extracelluar traps (NETs). NETs have been associated with VTE (van Montfoort, et al. Ateriosclero Thromb Vasc Biol 2013;33:147-51). Dectin-1 serine82 is not evolutionarily conserved and the serine82 to leucine amino acid change is predicted to be tolerated, with a moderate effect on protein function. Conclusions ITPR3 rs2229637 and CLAC7A rs59819090 may be associated with VTE in African-Americans. These observations require replication and functional studies toward understanding how they may lie on the causal pathway to VTE. Disclosures: No relevant conflicts of interest to declare.

Abstract Background: Obesity is increasing in prevalence worldwide and has potential implications on chemotherapy dosing and selection of patients for therapy. Auto HCT improves outcomes for patients with MM, but optimal chemotherapy dosing for obese patients is poorly defined. Methods: We identified 1087 patients reported to the CIBMTR between 1995 and 2003 who underwent auto HCT for MM as part of initial therapy, defined as within 18 months of diagnosis, and received high-dose melphalan conditioning, with or without total body irradiation (TBI). We categorized patients by body mass index (BMI) as normal (18.5– 24.9), overweight (25–29.9), obese (30–34.9), or severely obese (≥35). Underweight patients (BMI <18.5, N=9) were excluded from analysis. We analyzed overall survival (OS) and progression-free survival (PFS) from date of transplant, using Kaplan-Meier curves and the log-rank test for univariate analyses and using Cox proportional hazards models for multivariate analyses. Results: Cases were reported from 114 centers in 10 countries. There were 292 patients of normal weight (27%); 472 were overweight (43%), 198 were obese (18%), and 125 severely obese (11%). Median follow-up of survivors was 63, 61, 60 and 59 months, respectively. Significant baseline differences among BMI groups indicate that obese patients selected for transplant were younger (median age 58, 58, 56, and 55 years, respectively, p=0.005) and had less severe disease at diagnosis, with lower bone marrow plasmacytosis and less frequent renal failure, hypercalcemia, and severe anemia. Obese patients received higher total melphalan doses but lower doses per square meter of body surface area (calculated based on actual body weight). Univariate analyses show no significant effect of BMI category on either OS or PFS. However, among patients who received TBI as part of conditioning, multivariable analyses show a significant effect of BMI on PFS (p-value for interaction 0.006). In this subgroup, a higher BMI was associated with longer PFS (p=0.006, Figure 1). Among patients who received melphalan alone, no effect of BMI was apparent (Figure 2). The difference in PFS for patients receiving melphalan/TBI was due to a decreased risk of relapse among obese patients. Pairwise comparisons of conditioning regimen (TBI vs. no TBI) within BMI categories showed significant reduction in risk of treatment failure for obese (HR=0.54, p=0.04) and severely obese (HR=0.32, p=0.001) patients who received TBI. No differences in OS were apparent in multivariate analyses. Relative risks (RR) for PFS from a multivariable model adjusting for possible confounders are shown below: TBI No TBI n RR (95% CI) P n RR (95% CI) P Normal 44 1.00 Poverall=0.006 248 1.00 Poverall=0.18 Overweight 62 0.92 (0.60–1.40) 0.69 405 0.90 (0.75–1.08) 0.24 Obese 21 0.49 (0.27–0.90) 0.021 177 0.85 (0.68–1.07) 0.16 Severely obese 22 0.39 (0.20–0.76) 0.005 100 1.12 (0.86–1.45) 0.42 Conclusion: Obesity, when measured by BMI, has no statistically significant effect on OS among patients with myeloma receiving high-dose melphalan. Among patients receiving melphalan with TBI, a higher BMI is associated with improved PFS. The reason for the restriction of this effect to TBI-containing conditioning regimens requires further investigation. The current common strategy of reducing melphalan doses (i.e. calculating based on ideal or adjusted body weight) does not appear to impair outcomes for obese patients. Obesity should not exclude patients from consideration of autologous transplantation. Figure Figure

Abstract Abstract 4034 Natural Killer (NK) cells are lymphocytes of the innate immune system with anti-viral and anti-cancer activity. Over the past decade, they have gained interest as a promising cellular source for use in adoptive immunotherapy for the treatment of cancer. Most notably, NK cells play an important role in the graft-vs-tumor effect seen in allogeneic hematopoietic stem cell transplantation (allo-HSCT), and a better understanding of NK cell biology has translated into improved transplant outcomes in acute myelogenous leukemia (AML). Small studies have demonstrated a role for NK cell activity in multiple myeloma (MM) patients receiving allo-HSCT. Investigators have also utilized haplo-identical killer immunoglobulin-like receptor (KIR) mismatched NK cells for adoptive immunotherapy in patients with multiple myeloma (MM). Our group has focused on the development of NK cells from human embryonic stem cells (hESCs) and induced pluripotent stem cells (iPSCs) as a novel starting source of lymphocytes for immunotherapy. We have previously demonstrated potent anti-tumor activity of hESC-derived NK cells in vitro and in vivo against a variety of different targets. We have also shown that iPSC-derived NK cells from a variety of different somatic cell starting sources posses potent anti-tumor and anti-viral activity. Here, we demonstrate hESC- and iPSC-derived NK cell development in a completely defined, feeder-free system that is amenable to clinical scale-up. These cultures contain a pure population of mature NK cells devoid of any T or B cell contamination, which are common adverse bystanders of cellular products isolated and enriched from peripheral blood. Our cultures are homogenous for their expression of CD56 and express high levels of effector molecules known to be important in anti-MM activity, including KIR, CD16, NKG2D, NKp46, NKp44, FasL and TRAIL. We have now tested the activity of hESC- and iPSC-derived NK cells against MM tumor cells in order to provide a universal source of lymphocytes for adoptive immunotherapy in patients with treatment refractory disease. We find that similar to peripheral blood NK cells (PB-NK), hESC- and iPSC-derived NK cells are cytotoxic against 3 distinct MM cell lines in a standard chromium release cytotoxicity assay. Specifically, activated PB-NK cells killed 48.5% of targets at 10 to 1 effector to target ratios, whereas hESC (46.3%) and iPSC (42.4%) derived NK cells also demonstrated significant anti-MM activity. Also, hESC- and iPSC-derived NK cells secrete cytokines (IFNγ and TNFα) and degranulate as demonstrated by CD107a surface expression in response to MM target cell stimulation. When tested against freshly isolated samples from MM patients, hESC- and IPSC-derived NK cells respond at a similar level as activated PB-NK cells, the current source of NK cells used in adoptive immunotherapy trials. These MM targets (both cell lines and primary tumor cells) are known to express defined ligands (MICA/B, DR4/5, ULBP-1, BAT3) for receptors expressed on NK cells as well as a number of undefined ligands for natural cytotoxicity receptors (NCRs) and KIR. As these receptor-ligand interactions drive the anti-MM activity of NK cells, we are currently evaluating expression of each of these molecules on the surface of both the effector and target cell populations. Not only do hESC- and iPSC-derived NK cells provide a unique, homogenous cell population to study these interactions, they also provide a genetically tractable source of lymphocytes for improvement of the graft-vs-myeloma effect and could be tailored on a patient specific basis using banks of hESC-or iPSC-derived NK cells with defined KIR genotypes for use as allogeneic or autologous effector cells. Disclosures: No relevant conflicts of interest to declare.

Abstract This study was coordinated by the ECOG-ACRIN Cancer Research Group (Robert L. Comis, MD and Mitchell D. Schnall, MD, PhD, Group Co-Chairs) and the Medical Research Counsel, United Kingdom, and supported in part by Public Health Service Grants CA180820, CA180794, CA180790, CA189859, CA180853, CA180791, and from the National Cancer Institute, National Institutes of Health and the Department of Health and Human Services. Its content is solely the responsibility of the authors and does not necessarily represent the official views of the National Cancer Institute. Background: Late relapse in acute leukemia is considered a relatively rare event. Patients with acute myeloid leukemia (AML) are often considered cured of the disease at 3 years, but information regarding adult acute lymphoblastic leukemia (ALL) patients is scarce. Data are presented from one of the largest prospective adult ALL studies, the MRC UKALLXII/ECOG E2993, to evaluate the rate and characteristics of late relapse in ALL. For this purpose, late relapse was defined, arbitrarily, as relapse 3 years post achievement of complete remission (CR) and very late relapse was defined as relapse > 5 years from CR. Methods: The UKALLXII/ECOG E2993 was an international ALL trial conducted jointly by the MRC in the United Kingdom and ECOG in the United States. All patients received identical induction therapy, followed by central nervous system prophylaxis. Patients with a sibling donor (or a matched unrelated donor in Philadelophia-chromosome-positive ALL) were assigned to receive an allogeneic hematopoietic stem cell transplant (HSCT); all others were randomized to undergo an autologous transplant or protracted standard consolidation/ maintenance therapy. The study accrued 2109 patients from 1993 to 2008. Following relapse, patients were followed for survival. For this report only patients registered before the tyrosine kinase inhibitors era are included in the analysis. Results: 1518 study patients were eligible for this analysis, 1208 (79.6%) Philadelphia-chromosome negative (Ph-neg) and 267 (17.5%) Philadelphia-chromosome positive (Ph-pos). 1381 (91%) of the patients achieved CR; 93% of the Ph-neg and 82% of the Ph-pos. 572 patients (37.7%) underwent allogeneic HSCT. The median duration of follow-up of patients who achieved CR was 10 years. Among the 1381 patients who achieved CR, 626 (45.3%) had a documented relapse; 566 (90.4%) relapsed within 3 years of CR and 60 (9.6%) relapsed beyond 3 years ('late relapse') (Figure 1). Among these 60 patients, 18(2.9%) relapsed after 5 years ('very late relapse'). Table. Patients n CR All relapses Relapses< 3 years Relapses≥ 3 years Relapses≥ 5 years All patients 1518 1381 (91%) 626 (45.3%) 566 (90.4%) 60 (9.6%) 18 (2.9%) Ph-neg 1208 (79.6%) 1123 (93%) 485 (40.1%) 429 (88.5%) 56 (11.5%) 17 (3.5%) Ph-pos 268 (17.5%) 219 (82%) 124 (56.6%) 122 (98.4%) 2 (1.6%) 1 (0.8%) Relapse beyond 3 years occurred in 4.3% of all who achieved CR, in 5% of Ph-neg and 0.01% of Ph-pos patients. Among the 60 late relapses, the median time to relapse was 46 months. 61.7% of the late-relapse patients were males, median age was 32 years, 88.3% were B-lineage ALL and the median white cell count at diagnosis was 6000/ul. 56.7% were in cytogenetic standard risk, 8.3% at high risk and the data of 35% are unknown. The median survival for the late relapse patients was longer than for those who relapsed within 3 years. The overall survival (OS) of the 56 Ph-neg patients who relapsed beyond 3 years is shown in Fig 2. Table.Relapse > 3 yearsRelapse > 3 yearsMedian survival from relapse (months)5.411.23-year OS from relapse6.5%29%5-year OS from relapse5.6%19% Conclusions: Late relapses in adults with Ph-neg ALL are not uncommon. About 10% of relapses occur beyond 3 years and 4.3% of all ALL patients who achieved a CR can expect to have a late relapse. These data are in contrast to AML where only 1% of patients relapse beyond 3 years (Watts JM et al, 2014). Most of the late relapse patients were at standard risk and appeared to have a relatively favorable outcome post relapse. Patients with ALL, particularly those who are Ph-neg, cannot be considered as cured at 3 years and need to be closely followed. Figure 1. Time to relapse of Ph-pos and Ph-neg ALL Figure 1. Time to relapse of Ph-pos and Ph-neg ALL Figure 2. Survival from relapse for Ph-neg patients who relapsed after 3 years from CR. Figure 2. Survival from relapse for Ph-neg patients who relapsed after 3 years from CR. Disclosures Rowe: Amgen: Consultancy; BioSight Ltd.: Consultancy, Membership on an entity's Board of Directors or advisory committees; BioLineRx Ltd.: Consultancy. Douer:Gilead: Consultancy.

Abstract Background: Large case-control studies have identified common epidemiologic exposures associated with risk of AML development, including obesity [BMI ≥30 kg/m2] associated with 2-fold increase risk. However it is not known whether individual risk factors are associated with unique AML genetic lesions. We have recently identified a significant association of some common exposures including obesity with unique disease cytogenetic subgroups in a cohort of n=295 consecutive AML patients diagnosed and treated at Mayo Clinic [Cancer Epidemiol 39:1084, 2015]. Aberrant DNA methylation is a hallmark of cancer and has been reported in AML, and we therefore performed an analysis of global DNA methylation in patients in this cohort to determine whether specific epidemiologic exposures are associated with a unique pattern of DNA methylation. Methods: Patients in the initial cohort were previously reported. An available baseline AML bone marrow cytogenetic pellet from diagnosis was identified for n=148 patients (50.2%). Following IRB approval and using previously reported techniques [Leukemia 24:1283, 2010], leukemia DNA was isolated from the remnant diagnostic cytogenetic samples and processed on the HumanMethylation450 BeadChip array (Illumina). Individual CpG dinucleotides were assigned a Beta value (i.e. methylation value) ranging from 0 (unmethylated) to 1 (methylated). We excluded those with minor methylation changes (<0.2 between any two samples), resulting in 383,524 CpG's. For the purposes of this first analysis we have focused only on CpG's with an inter-quartile range (IQR, i.e. difference between 75th and 25th percentiles) of greater than 0.25, comprising a total of 39,657 CpG's. An unsupervised cluster analysis of differential methylation was generated ("Heatmap", Figure). Univariate and multivariable analyses were performed adjusting for age as a continuous variable to determine the association of individual exposures with unique methylation clusters (primary endpoint), and we also evaluated the association of clinical characteristics and clinical outcomes after therapy (secondary endpoint). The median age of patients was 69 yrs (range 19-89), male 65%, and Caucasian 89%. The median BMI was 27.2 (range 16.9-59.9), and n=47 patients (32%) had BMI ≥30. Standard cytogenetic risk groups were applied [favorable (n=8), normal (n=61), intermediate abnormal (n=32) and poor (n=47)]. Results: We identified 4 distinct methylation clusters (Figure: Cluster #1, Black horizontal bar; Cluster #2, Green; Cluster #3, Blue; and Cluster #4, Red). Multivariate analysis of select variables is shown in Table. Patients in cluster #1 were significantly more likely to have a BMI ≥30 [Odds Ratio (OR) 2.49, p=0.017] and more likely to have favorable risk cytogenetics although this was not statistically significant [OR 6.71, p=0.088], while those in cluster #2 were significantly more likely to be have a history of regular NSAID use [OR 3.26, p=0.03] and less likely to have normal [OR 0.40, p=0.044] and possibly intermediate abnormal cytogenetics [OR 0.34, p=0.051]. Those in cluster #3 were significantly younger [median age 48 yrs, p<0.001] and were also more likely to have prior history MDS although this was not statistically significant [OR 3.7, p=0.082]. Cluster #4 was not correlated with any distinct exposure apart from possible decreased alcohol use [OR 0.3, p=0.079]. History of past or current tobacco use, regular acetaminophen use, documented myelotoxin exposure, family history, and secondary AML did not correlate with a unique methylation cluster. There was no independent association of methylation cluster with overall survival (p=0.46), although among patients receiving intensive therapy cluster #2 was associated with lower complete remission rate [OR 0.28 (95% CI 0.09-0.86), p=0.026]. Conclusion: This first analysis of AML molecular epidemiology and clinical outcome suggests that specific disease risk factors (esp. obesity and age) are associated with unique leukemia DNA methylation clusters. In addition, aberrant methylation is associated with some clinical features and with outcome after therapy, suggesting that epidemiologic risk factors may have a prognostic impact. This provides novel insight into leukemogenesis, and will guide prospective studies of AML epidemiology and outcome. Figure. Figure. Disclosures Foran: medscape: Honoraria; pfizer: Honoraria; Millennium Pharmaceuticals, Inc.: Research Funding; novartis: Honoraria; karyopharm: Honoraria; boehringer ingelheim: Research Funding; agios: Research Funding; Cellerant: Research Funding.