Citations

Purpose: Multiple myeloma (MM) is a plasma cell (PC) malignancy with an increasing incidence in the US. Epidemiological studies demonstrate a 2-3 fold higher incidence of the pre-malignant monoclonal gammopathy of undetermined significance (MGUS) and MM with a ~4-year younger age of onset among African Americans (AA) compared to European Americans (EAs) (Fonseca, Leukemia, 2017). With equal access to care, AAs have better overall survival compared to EAs (Waxman, Blood, 2010). This disparity may be explained by ancestral-associated genetic predisposition of AAs to development of monoclonal gammopathies and to specific acquired, cytogenetically-defined subtypes. Using calculated genetic ancestry data, we have previously identified a higher prevalence of IgH translocations t(11;14), t(14;16) and t(14;20) in individuals with >80% African ancestry (Baughn, BCJ, 2018). Since SNP rs9344 encoding the CCND1 870G>A polymorphism has been reported in association with increased risk of t(11;14) (Weinhold, Nature Genetics, 2013), we investigated whether rs9344 correlates with African ancestry and with t(11;14) in our cohort of patients with plasma cell dyscrasias. Methods: We studied 898 patients with monoclonal gammopathies who had undergone uniform testing to identify MM-specific cytogenetic abnormalities. DNA from bone marrow samples was genotyped on the Precision Medicine Research Array and biogeographical ancestry was assessed using the Geographic Population Structure Origins tool (Elhaik, Nat Commun, 2014). Plasma cell proliferative disorder FISH of immunoglobulin (cIg)-stained positive plasma cells was performed as described (Baughn, BCJ, 2018). Individuals were divided into three ancestral groups: 1. EAs (<0.1% African ancestry and <30% Asian ancestry); 2. AAs (> 80% African ancestry); and 3. Other. Chi-squared test was used to determine the overall comparison between the 3 ancestral groups and also between ancestral groups 1 vs 2, and 2 vs 3 using pairwise comparison. All tests were two-sided with alpha level set at 0.05 for overall statistical significance. Pairwise comparison was considered statistically significant when p<0.025 based on Bonferroni method for multiple comparisons. Results: We identify increased risk of development of either a t(11;14), t(14;16) or t(14;20) in AAs (48.8%) compared to EAs (33.6%) (p-value=0.0051). To explore the genetic basis of increased t(11;14) specifically (37.4% AAs vs. 27.3% p-value=0.049), we evaluated the frequency of the G risk allele of rs9344 in relation to African ancestry. The frequency of the G risk allele was higher in AAs (0.81) compared to EAs (0.59) (p-value <0.0001) and also higher in t(11;14) cases (0.73) compared to non-t(11;14) controls (0.58) (p-value <0.0001). A multivariate model identified only rs9344 as significantly associated with t(11;14) after adjusting for age, gender and race group suggesting that it plays a role in the development of t(11;14) (p-value <0.001 for GG, p-value=0.005 for AG). To test if these results are replicable, we studied the MMRF CoMMpass cohort. This cohort includes individuals with newly diagnosed MM along with self-report race information and translocation data from long insert whole genome sequencing. Although t(11;14) was not enriched in self-reported Black individuals from this cohort (17.5% Black vs. 20.4% White, p-value=0.47), there was association between the rs9344 and self-reported Black race (p-value <0.0001) and with the presence of t(11;14) when the t(11;14) was analyzed by long insert whole genome sequencing (p-value=0.0001). Conclusions: To our knowledge, this study includes the largest group of African individuals with an abnormal plasma cell clone along with uniformly collected FISH, genotyping and ancestry data. We have identified in this diverse population the association of the CCND1 870G>A polymorphism (rs9344) with African ancestry and with t(11;14) suggesting that it plays a role in the development of t(11;14) plasma cell dyscrasias. Disclosures Elhaik: DNA Diagnostics Center: Consultancy. Baird:DNA Diagnostics Center: Employment. Cerhan:Janssen: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; NanoString: Research Funding. Bergsagel:Celgene: Consultancy; Ionis Pharmaceuticals: Consultancy; Janssen Pharmaceuticals: Consultancy. Dispenzieri:Alnylam: Research Funding; Akcea: Consultancy; Intellia: Consultancy; Janssen: Consultancy; Pfizer: Research Funding; Takeda: Research Funding; Celgene: Research Funding. Kumar:Janssen: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Takeda: Research Funding.

Uproleselan (GMI-1271) is a novel antagonist of E-selectin, an adhesion molecule expressed on endothelial cells. E-selectin is expressed transiently in the normal vasculature during an inflammatory response and constitutively in the bone marrow (BM). Binding of E-selectin (E-sel) to sialyl Lex, the E-sel ligand (E-sel-L), on the leukemic cell surface activates cell survival pathways and promotes chemotherapy resistance in AML. In preclinical models, blockade of E-selectin with uproleselan disrupts the activation of cell survival pathways and enhanced the efficacy of chemotherapy across multiple AML tumor models. Furthermore, uproleselan protected against chemotherapy-induced mucositis by regulating macrophage trafficking to the site of injury in the gut lining. A previous phase I/II study of uproleselan added to chemotherapy in patients with untreated AML (older adults ≥60 yrs) and relapsed/refractory AML (≥ 18yrs) showed promising remission rates (CR/CRi) and survival outcomes, and reduced rates of mucositis. In the newly diagnosed older patients, high remission rates were achieved overall (CR/CRi 72%) and for the high risk subgroup with sAML (CR/CRi 69%). In this phase 2/3 study, we will test the addition of uproleselan to a standard daunorubicin/cytarabine regimen in older adults with previously untreated AML. The study will enroll patients age ≥ 60 yrs with untreated acute myeloid leukemia. Patients with acute promyelocytic leukemia, activating mutations in FLT3, or evidence of central nervous system involvement are excluded. Subjects are randomized to 7+3 induction (cytarabine + daunorubicin) +/- uproleselan. Subjects achieving a CR/CRi may receive up to 3 cycles of consolidation with intermediate dose cytarabine 2 gm/m2 IV d1-5 +/- uproleselan. The primary phase II objective is to compare the event-free survival (EFS). A sample size of 262 patients was selected for the phase II to detect an improvement in median EFS from 7 months to 11 months (HR= 0.64) with &gt; 95% power, using a log rank test. The phase III primary objective will compare overall survival (OS). For the phase III, a sample size of 335 evaluable patients per arm (670 total inclusive of patients enrolled in phase II) will provide &gt;90% power to detect an improvement in median OS from 12 months to 16 months (HR= 0.75), using a log-rank test. Correlative studies will measure E-selectin ligand on AML blasts and soluble E-selectin and will also measure minimal residual disease after remission induction by multiparameter flow cytometry. A comprehensive geriatric assessment will identify baseline measures associated with EFS and develop a risk model to predict OS among older adults receiving intensive AML therapy. The study is endorsed by SWOG and ECOG-ACRIN and opened to enrollment on 1/16/2019. Figure Disclosures Uy: Astellas: Consultancy; Pfizer: Consultancy; Curis: Consultancy; GlycoMimetics: Consultancy. Dinner:Agios: Consultancy; Pfizer: Consultancy; AstraZeneca: Consultancy. Strickland:Jazz: Consultancy; Sunesis Pharmaceuticals: Research Funding; Pfizer: Consultancy; Kite: Consultancy; Astellas Pharma: Consultancy; AbbVie: Consultancy. Liesveld:Onconova: Other: Data safety monitoring board; Abbvie: Membership on an entity's Board of Directors or advisory committees. Byrd:Acerta: Research Funding; Acerta: Research Funding; Genentech: Research Funding; Janssen: Consultancy, Other: Travel Expenses, Research Funding, Speakers Bureau; Ohio State University: Patents & Royalties: OSU-2S; BeiGene: Research Funding; Janssen: Consultancy, Other: Travel Expenses, Research Funding, Speakers Bureau; BeiGene: Research Funding; Gilead: Other: Travel Expenses, Research Funding, Speakers Bureau; Gilead: Other: Travel Expenses, Research Funding, Speakers Bureau; BeiGene: Research Funding; Novartis: Other: Travel Expenses, Speakers Bureau; Novartis: Other: Travel Expenses, Speakers Bureau; Gilead: Other: Travel Expenses, Research Funding, Speakers Bureau; Pharmacyclics LLC, an AbbVie Company: Other: Travel Expenses, Research Funding, Speakers Bureau; Pharmacyclics LLC, an AbbVie Company: Other: Travel Expenses, Research Funding, Speakers Bureau; Novartis: Other: Travel Expenses, Speakers Bureau; TG Therapeutics: Other: Travel Expenses, Research Funding, Speakers Bureau; Genentech: Research Funding; Genentech: Research Funding; Pharmacyclics LLC, an AbbVie Company: Other: Travel Expenses, Research Funding, Speakers Bureau; Acerta: Research Funding; TG Therapeutics: Other: Travel Expenses, Research Funding, Speakers Bureau; Ohio State University: Patents & Royalties: OSU-2S; Ohio State University: Patents & Royalties: OSU-2S; TG Therapeutics: Other: Travel Expenses, Research Funding, Speakers Bureau; Janssen: Consultancy, Other: Travel Expenses, Research Funding, Speakers Bureau. Stone:Argenx, Celgene, Takeda Oncology: Other: Data and Safety Monitoring Board/Committee: ; AbbVie, Actinium, Agios, Argenx, Arog, Astellas, AstraZeneca, Biolinerx, Celgene, Cornerstone Biopharma, Fujifilm, Jazz Pharmaceuticals, Amgen, Ono, Orsenix, Otsuka, Merck, Novartis, Pfizer, Sumitomo, Trovagene: Consultancy; Novartis, Agios, Arog: Research Funding. OffLabel Disclosure: Uproleselan in AML

Disease monitoring in nonalcoholic steatohepatitis (NASH) is limited by absence of noninvasive biomarkers of disease regression or progression. We aimed to examine the role of multiparametric three‐dimensional magnetic resonance elastography (3D‐MRE) and magnetic resonance imaging proton density fat fraction (MRI‐PDFF) in the detection of NASH regression after interventions. This is a single‐center prospective clinical trial of 40 patients who underwent bariatric surgery. Imaging and liver biopsies were obtained at baseline and 1 year after surgery. The imaging protocol consisted of multifrequency 3D‐MRE to determine the shear stiffness at 60 Hz and damping ratio at 40 Hz, and MRI‐PDFF to measure the fat fraction. A logistic regression model including these three parameters was previously found to correlate with NASH. We assessed the model performance in the detection of NASH resolution after surgery by comparing the image‐predicted change in NAFLD activity score (delta NAS) to the histologic changes. A total of 38 patients (median age 43, 87% female, 30 of 38 with NAS ≥ 1, and 13 of 38 with NASH) had complete data at 1 year. The NAS decreased in all subjects with NAS ≥ 1 at index biopsy, and NASH resolved in all 13. There was a strong correlation between the predicted delta NAS by imaging and the delta NAS by histology (r = 0.73, P < 0.001). The strength of correlation between histology and the predicted delta NAS using single conventional parameters, such as the fat fraction by MRI‐PDFF or shear stiffness at 60 Hz by MRE, was r = 0.69 (P < 0.001) and r = 0.43 (P = 0.009), respectively. Conclusion: Multiparametric 3D‐MRE and MRI‐PDFF can detect histologic changes of NASH resolution after bariatric surgery. Studies in a nonbariatric setting are needed to confirm the performance as a composite noninvasive biomarker for longitudinal NASH monitoring.

Applications in early-phase cancer trials have motivated the development of many statistical designs since the late 1980s, including dose-finding methods, futility screening, treatment selection, and early stopping rules. These methods are often proposed to address the conventional cytotoxic therapeutics for neoplastic diseases and cancer. Recent advances in precision medicine have motivated novel trial designs, most notably the idea of master protocol (eg, platform trial, basket trial, umbrella trial, N-of-1 trial), for the evaluation of molecularly targeted cancer therapies. In this article, we review the concepts and methodology of early-phase cancer trial designs with a focus on dose finding and treatment screening and put these methods in the context of platform trials of molecularly targeted cancer therapies. Because most cancer trial designs have been developed for cytotoxic agents, we will discuss how these time-tested design principles hold relevance for targeted cancer therapies, and we will delineate how a master protocol may serve as an efficient platform for safety and efficacy evaluations of novel targeted therapies.

Recent advances in biotechnology and cancer genomics have afforded enormous opportunities for development of more effective anticancer therapies. A key thrust of this modern drug development paradigm is successful identification of predictive biomarkers that can distinguish patients who might be sensitive to new targeted therapies. To respond to this challenge, a number of phase III cancer trial designs integrating biomarker-based objectives have been proposed and implemented in oncology drug development. In this article, we provide an updated review of commonly used biomarker-based randomized clinical trial designs, with a particular focus on design efficiency. When the efficacy of a new therapy may be limited to a biomarker-defined subgroup, the choice of an appropriate randomized clinical trial design should be guided by the strength of the biomarker’s credentials. If compelling evidence indicates that a targeted therapy is beneficial only in a particular biomarker-defined subgroup, an enrichment design should be used. If there is strong evidence that the treatment is likely to be more beneficial in the biomarker-positive patients but a meaningful benefit is also possible in the biomarker-negative patients, then a properly powered biomarker-stratified design (eg, a subgroup-specific or Marker Sequential Test strategy) would provide the most rigorous determination of the sensitive populations. If the evidence supporting the predictive value of the biomarker is weak and the treatment is expected to work in the overall population, then a fallback design could be used. Careful selection of an appropriate phase III design strategy that integrates evaluation of a new anticancer therapy and its companion diagnostic is critical to the success of precision medicine in oncology.

Abstract Introduction: PRM-151, a recombinant human pentraxin-2 molecule, has been shown to prevent and reverse fibrosis in animal models of myelofibrosis (MF) by postulated targeting differentiation of fibrocytes (essential cells in fibrotic process) from monocytes. In the first stage of a two-stage trial, 27 patients (pts) with primary myelofibrosis (PMF), post-essential thrombocythemia/polycythemia vera (post-ET/PV) MF, and Grade 2 or 3 bone marrow fibrosis (BMF) received PRM-151 10 mg/kg IV ± ruxolitinib (RUX) for 6 cycles (24 weeks). A reduction in BMF, decrease in symptoms (MPN-SAF Total Symptom Score [TSS]), and a reduction of palpable splenomegaly were observed, along with a favorable safety profile. Pts experiencing clinical benefit were allowed to continue beyond 24 weeks in an open label extension (OLE) study. Here, we report interim efficacy and safety data for 18 pts enrolled in the OLE, who had been treated for up to 35 cycles (140 weeks). Methods: All pts in the OLE received a monthly infusion of PRM-151 10 mg/kg IV. Pts receiving PRM-151 alone or in combination with RUX in the main study continued with their respective drugs. Safety and hematology parameters were assessed monthly, and MPN-SAF TSS Q3 months. BM biopsies were obtained at baseline, end of main study, and at physician discretion in the OLE. These were evaluated centrally by two independent, blinded hematopathologists for the degree of reticulin and collagen fibrosis. Immunostaining for fibrocytes was performed on available biopsies. The primary objective of the OLE was to assess safety and efficacy of long-term administration of PRM-151. Results: Of the 18 pts enrolled in the OLE, 9 received PRM-151 as single agent, and 9 in conjunction with RUX. Baseline characteristics included median age of 66 years (51-78); 8 pts were DIPSS Int-1, 9 Int-2, and 1 high-risk; 6 (33%) had Hgb < 100 g/L, 12 (67%) had PLT < 100 x 109/L; 7 (39%) had PLT <50 x 109/L; 8 pts had PMF, 10 had post-ET/PV MF; 13 pts (72%) had a palpable spleen, and 9 (50%) had Grade 3 BMF. Median time on study for these 18 pts was 30.9 months (15.9-47.2 months). All pts experienced at least 1 adverse event (AE), with 8 pts (44%) reporting a possible study drug-related AE. No unexpected AEs were observed, and no deaths were reported during the study period. The mean best percent change (by palpation) in spleen size from baseline was −37%, with a median percent reduction of −26.1% (Figure). The mean best percent improvement in MPN-SAF TSS was −54%, with a median percent reduction of TSS of −64%. Pts in the PRM-151 monotherapy group showed similar improvements in MPN-SAF TSS and splenomegaly as those receiving PRM-151 + RUX (Figure). Complete data on hematology parameters will be available at the time of presentation. Improvement in BM reticulin grade was observed in 5 of 7 pts (71%) with Grade 2 BMF at baseline, and in 4 of 9 pts (44%) with Grade 3 BMF at baseline. Of the pts with Grade 3 BMF at baseline, 2 of 9 pts (22%) had a 2-grade reduction (Table). In addition, 5 of 6 pts (83%) with Grade 2 collagen fibrosis at baseline had a 1-grade reduction, with 2 of 6 pts (33%) improving to Grade 0. Also, 2 of 7 pts (28%) with Grade 3 collagen fibrosis had a reduction of 1-grade with 1 of 7 (14%) improving to Grade 0 (Table). Eight of 18 pts had BM fibrocyte immunostaining done: mean fibrocyte count in the hematopoietic BM decreased from 378.0 ± 255.3 per mm2 (11.2 ± 7.7% of total cells) at study baseline to 81.3 ± 86.5 per mm2 (2.0 ± 2.1% of total cells; 7 of 8 pts evaluable) at cycle 25, with continuous reduction in fibrocyte numbers observed at interim. Over the same period, improvement in BM reticulin grade was detected in 4 of 7 pts (57%), and collagen fibrosis grade was decreased in 3 of 7 pts (43%). Conclusions: This long-term follow-up study of 18 pts with MF who received PRM-151 for a median of 31 months showed the drug to be well tolerated. An overall improvement in BM reticulin and collagen fibrosis grade, as well as reductions in MPN-SAF TSS and splenomegaly were observed. In a subset of pts for whom bone marrow fibrocyte immunostaining data were available, a mean reduction in fibrocyte counts was observed, as well as improved bone marrow reticulin and collagen fibrosis grade. These data warrant confirmation in a larger controlled study. Figure. Figure. Disclosures Verstovsek: Incyte: Consultancy; Italfarmaco: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Celgene: Membership on an entity's Board of Directors or advisory committees. Pozdnyakova:Promedior, Inc.: Consultancy. Mesa:Promedior: Research Funding; Incyte: Research Funding; Ariad: Consultancy; Novartis: Consultancy; Celgene: Research Funding; Galena: Consultancy; Gilead: Research Funding; CTI: Research Funding. Foltz:Incyte: Research Funding; Promedior: Research Funding; Gilead: Research Funding; Novartis: Consultancy, Honoraria, Research Funding. Mascarenhas:Incyte: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees; Merck: Research Funding; Roche: Research Funding; CTI Biopharma: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding; Promedior: Research Funding. Ritchie:Astellas Pharma: Research Funding; NS Pharma: Research Funding; Pfizer: Consultancy, Research Funding; Bristol-Myers Squibb: Research Funding; ARIAD Pharmaceuticals: Speakers Bureau; Novartis: Consultancy, Other: Travel, Accommodations, Expenses, Research Funding, Speakers Bureau; Celgene: Consultancy, Other: Travel, Accommodations, Expenses, Speakers Bureau; Incyte: Consultancy, Speakers Bureau. Palmer:Novartis: Research Funding. Kremyanskaya:Incyte: Research Funding. van den Blink:Promedior, Inc.: Employment. Gupta:Promedior, Inc.: Employment. Gotlib:Deciphera: Consultancy, Honoraria, Research Funding; Incyte: Consultancy, Honoraria, Research Funding; Kartos: Consultancy; Promedior: Research Funding; Gilead: Consultancy, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Blueprint Medicines: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria, Research Funding.

Abstract Dasatinib with corticosteroid yields high complete remission (CR) rates in Ph+ ALL with minimal induction death. Optimal post-remission therapy is not known. We report a prospective study evaluating dasatinib/dexamethasone induction then consolidation with reduced-intensity conditioning (RIC) allogeneic hematopoietic cell transplantation (alloHCT), autologous HCT (autoHCT), or chemotherapy alone (chemo), followed by dasatinib-based maintenance. Methods: We conducted a phase II, 3-arm, non-randomized trial (NCT01256398, Support: U10CA180821, U10CA180882, U10CA180861, U24CA196171) at 17 US centers with primary objectives to determine 3-year overall survival (OS) and disease-free survival (DFS) of adults ≥18 years (yrs) old with untreated Ph+ ALL treated with dasatinib/dexamethasone induction, CNS prophylaxis with systemic and intrathecal methotrexate, consolidation with alloHCT, autoHCT, or chemo, then dasatinib maintenance. Induction (Course I) used dasatinib 140 mg orally daily and dexamethasone 10 mg/m2/day orally or IV days 1-7. If ≤20% lymphoblasts in marrow at Day 15, Course II continued dasatinib with 7 days of dexamethasone. If >20% lymphoblasts, patients (pts) also received vincristine and daunorubicin. Pts not in CR/CRi received a second induction (Course III) with dasatinib, cyclophosphamide, vincristine, daunorubicin, and dexamethasone. CNS prophylaxis (Course IV) used dasatinib, IV vincristine and IV, oral, and intrathecal methotrexate. Course V consisted of HCT or chemo. Pts 18-70 yrs old underwent RIC alloHCT if they had a HLA-matched donor; otherwise they underwent autoHCT. AlloHCT conditioning used fludarabine 30 mg/m2/day IV day -7 through -3, alemtuzumab 20 mg/day IV day -7 through -3, and melphalan 140 mg/m2 IV once on day -2. GVHD prophylaxis with tacrolimus began day -2. Pts undergoing autoHCT received etoposide 10 mg/kg/day (age >65, 5 mg/kg/day) CIV for 4 days and cytarabine 2 g/m2 (age >65, 1 g/m2) IV every 12 hours for 8 doses then G-CSF for mobilization. AutoHCT conditioning was melphalan 100 mg/m2/day IV on days -2 and -1. Pts >70 yrs old or unable to undergo HCT received etoposide/cytarabine alone. Dasatinib maintenance (Course VI) began day 30 of Course V and continued for 12 months and until 2 consecutive negative BCR-ABL1 RT-PCR assays 3 months apart or relapse. BCR-ABL1 isoform and ABL1 kinase domain (KD) mutation determination were done locally. Results: From 12/15/2010 to 11/14/2014, 64 eligible pts enrolled. Median age was 60 yrs (22-87); median WBC 23.2 x 103/μl (0.3-454). The dominant BCR-ABL1 isoform was p190 in 59%, p210 in 17%, and not reported in 23%. The CR rate was 97% with no induction deaths. Fifty-five pts completed CNS prophylaxis (Course IV). Twenty pts underwent protocol-specified alloHCT, 7 autoHCT, and 9 chemo. Nine pts underwent off-study alloHCT and 5 skipped Course V. Dasatinib maintenance was tolerable with 72%, 80%, and 80% receiving >50% of planned maintenance doses in alloHCT, autoHCT, and chemo arms, respectively. With a median follow up of 48 months (37-78) for survivors, 3-yr OS and DFS were 55% (median OS 45 months) and 43% (median DFS 30 months), respectively. For pts undergoing consolidation with protocol-specified alloHCT, autoHCT, or chemo, 3-yr OS was 75%, 71%, and 55% respectively with median OS not reached (NR) for all groups. DFS at 3-yrs was 55%, 43%, and 46% respectively. Median DFS for alloHCT was 42 months vs 15 months for autoHCT and 34 months for chemo (Log-Rank P=0.4). Outcomes were similar with inclusion of off-study alloHCT and chemo patients skipping Course V. Relative to p190 BCR-ABL1 isoform, p210 was associated with shorter median OS (NR vs 16 months, P=0.04) and median DFS (35 months vs 10 months, P<0.0001). Three-year DFS was 9% with p210. Relapse occurred in 23 pts with 5 CNS relapses reported, one isolated. Relapse occurred in 25% of alloHCT, 43% of autoHCT, and 37% of chemo pts. T315I mutation in ABL1 KD was detected in 6 of 8 marrow relapses (75%). One isolated CNS relapse had no ABL1 KD mutations. Conclusions: Dasatinib and dexamethasone followed by alloHCT, autoHCT, or chemo yield similar 3-yr survival comparable to approaches using intensive induction chemotherapy. Pts with the p210 BCR-ABL1 isoform had dismal outcomes and may benefit from alternate approaches. T315I mutation was the major cause of relapse and should be addressed in future studies. Disclosures Wieduwilt: Amgen: Research Funding; Reata Pharmaceuticals: Equity Ownership; Daiichi Sankyo: Membership on an entity's Board of Directors or advisory committees; Leadiant: Research Funding; Shire: Research Funding; Merck: Research Funding. Uy:GlycoMimetics: Consultancy; Curis: Consultancy. Powell:Rafael Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees. Kolitz:Magellan Health: Consultancy, Honoraria. Liedtke:Caelum: 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; Amgen/Onyx: Consultancy, Honoraria, Research Funding; Gilead: Membership on an entity's Board of Directors or advisory committees, Research Funding; celgene: Research Funding; Genentech/Roche: Research Funding; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Prothena: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; BlueBirdBio: Research Funding. Stock:Jazz Pharmaceuticals: Consultancy. Devine:Kiadis Pharma: Consultancy. Larson:BristolMyers Squibb: Consultancy, Research Funding; Ariad/Takeda: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding.

Abstract Monoclonal gammopathies, including multiple myeloma (MM), represent a group of plasma cell (PC) disorders that comprise of mostly incurable hematopoietic malignancies with an increasing incidence in the US. Previous epidemiological studies demonstrated a 2-3 fold higher incidence of monoclonal gammopathy of undetermined significance (MGUS) and a similarly higher incidence of MM along with a ~4-year younger age of onset among African Americans (AA) compared to European Americans (EAs) (Fonseca, Leukemia, 2017). This suggests a possible ancestral-associated genetic predisposition of AAs to the development of monoclonal gammopathies (Landgren, Blood, 2006). When access to care is equal, AAs have a better overall survival compared to EAs suggesting that AAs may have a genetic predisposition that renders them better responders to treatment or have more favorable cytogenetic subtypes of MM (Waxman, Blood, 2010). Previous efforts to understand this disparity have relied on self-reported race rather than genetic ancestry. We hypothesize that quantifying genetic ancestry is necessary to fully understand the genetic mechanisms of racial disparities of monoclonal gammopathies. We describe our study of 881 patients with monoclonal gammopathies who had undergone uniform testing to identify MM-specific cytogenetic abnormalities. DNA from the bone marrow samples was genotyped on the Precision Medicine Research Array. Biogeographical ancestry was assessed using the Geographic Population Structure Origins tool, which provides the ancestral breakdown of 36 admixture components for each individual representing different geographic regions and outputs admixture proportions corresponding to those ancestries (Elhaik, Nat Commun, 2014). We evaluated whether an increase in the percentage of African Ancestry altered the odds of any primary cytogenetic abnormality. We demonstrated that a 10% increase in the percentage of African ancestry was associated with a 6% increase in the odds of detecting either an t(11;14), t(14;16) or t(14;20) (odds ratio = 1.06, 95% CI: 1.02 - 1.11; p-value = 0.05). Although we observed an increase in the odds of each of the individual translocations with 10% increase in African ancestry, l t(11;14) (OR=1.03) t(14;16) (OR=1.11) and t(14;20) (OR=1.10), these three abnormalities were combined to achieve greater statistical power. The differences in cytogenetic abnormalities were most striking among individuals with ≥80.0% African (n=120) compared to individuals with <0.1% African ancestry (n=235). Using these cutoff values comparing the ≥80.0% and <0.1% African ancestry cohorts, there was a higher prevalence of t(11;14), t(14;16) and t(14;20) (51% vs. 33%, respectively, p-value=0.008) and a lower prevalence of trisomies (with or without IgH translocations) (48.3% vs. 61.3%, respectively, p-value=0.066). In addition, the ≥80% African ancestry cohort also displayed a slightly lower prevalence of monosomy 13/13q deletion compared to the cohort with <0.1% African ancestry (34.2% vs. 38.7%, respectively, p-value=0.021). Further, we observed a significantly higher prevalence in the proportion of females with monoclonal gammopathies among the ≥80% African ancestry cohort compared to the cohort with <0.1% African ancestry (56.7% vs. 42.1%, respectively, p-value=0.028). We complement our past studies that relied on self-reported race and characterized patients' demographic and uniformly collected cytogenetic data in relation to genetically defined African ancestry. We demonstrate the prevalence of having one of three specific subtypes (i.e., t(11;14), t(14;16), or t(14;20)) was significantly higher in those with highest (≥80%) compared to lowest (<0.1%) African ancestry demonstrating African ancestry is associated with a subtype distribution of MM that differs from non-African individuals. These differences were only revealed after analysis of individuals with the highest and lowest percentage of African ancestry. Since 38.3% of the individuals with ≥80% African ancestry have the favorable t(11;14) translocation (in comparison to 26.8% of <0.1% African individuals), this finding may explain improved survival with equal access to care. Understanding the genetic mechanisms of this disparity is a fundamental step to understanding differences in incidence and outcomes of patients with monoclonal gammopathies. Disclosures Elhaik: DNA Diagnostics Center: Consultancy. Baird:DNA Diagnostics Center: Employment. Cerhan:Jannsen: Other: Scientific Advisory Board; Nanostring: Research Funding; Celgene: Research Funding. Stewart:Amgen Inc., BMS, Celgene, Takeda, Roche, Seattle Genetics, Janssen, Ono: Consultancy; Amgen Inc., Celgene, Roche, Seattle Genetics: Research Funding. Dispenzieri:Celgene, Takeda, Prothena, Jannsen, Pfizer, Alnylam, GSK: Research Funding. Kumar:Novartis: Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche: Research Funding.

Abstract Immunomodulatory drugs (IMiDs) are widely used in the treatment of patients with Multiple Myeloma (MM) however, only 30% of relapsed MM patients respond to single agent therapy and most patients eventually develop drug resistance. The molecular target of IMiDs in MM is cereblon but other parallel pathways or downstream events which enhance or preclude drug responsiveness are unknown. We therefore conducted a genome scale small interfering RNA (siRNA) lethality study in MM in the presence of increasing concentrations of lenalidomide. Primary screening was performed in a single-siRNA-per-well format with the human druggable genome siRNA set V4 comprising four siRNAs targeting each of 6,992 genes (total 27968 siRNAs). Lenalidomide was added 24 hours post transfection and cell viability was measured by ATP-dependent luminescence at 144 hours after transfection. Primary screen data was rigorously evaluated for multiple quality control metrics and found to exceed all expected performance parameters with >98% global transfection efficiency, <0.25 CV values, and minimal plate-to-plate and set-to-set variations observed. Hit selection was performed by analysis of IC50 value shift in the presence of each testing siRNA compared with three different control siRNA oligos. 160 candidate genes that enhance lenalidomide sensitivity upon silencing (sensitizers) were selected and re-screened with four siRNA oligos targeting each gene. 50 genes were identified as reproducible lenalidomide sensitizers including three Peroxisome (PEX) family proteins (PEX1, PEX10 and PEX7) and seven RAB family proteins (RAB17, RAB1A, RAB26, RAB30, RAB36, RAB4A and RAB8A). Four kinase genes were also identified in sensitizer hits and two of these, I-Kappa-B Kinase-Alpha (IKK1 or CHUK) and ribosomal protein S6 kinase (RPS6KA3 or RSK2), encode proteins that associate with significance together with a phosphorylation dependent transcription factor (CREB1) in Toll signaling pathways (p-value 0.0068). RSK2 is a serine/threonine-protein kinase that acts downstream of oncogenic FGFR3 mediated signaling and is phosphorylated by ERK (MAPK1/ERK2 and MAPK3/ERK1 signaling) during hematopoietic transformation. Phosphorylated RSK2 was previously reported to be frequently expressed in myeloma cell lines and primary myeloma cells. Using lentiviral shRNA expression, we demonstrated that knockdown of RSK2 in three genetically variable MM cell lines induced cyctocytoxiticy and consistently sensitized to lenalidomide. Two selective small molecular inhibitors of RSK2 (SL 0101-1 and BI-D1870) were then demonstrated to synergize with lenalidomide to induce myeloma cell cytotoxicixity. To further understand the mechanism underlying sensitization, immunoblotting analysis was performed to look at downstream changes after either RSK2 knockdown or RSK2 inhibition by BI-D1870. We found that both RSK2 knockdown and BI-D1870 treatment, mimicking lenalidomide treatment or cereblon inhibition, induced downregulation of both IRF4 and MYC in MM cells. The combination of lenalidomide and BI-D1870 not only produced a substantial synergistic effect inducing MM cytotoxicity, but also demonstrated a significant enhancement of downregulation of IRF4 and MYC. Forced overexpression of RSK2 attenuated the synergistic effects of lenalidomide and BI-D1870. In summary, our high throughput screen identified multiple gene targets that associate with increasing sensitivity to IMiDs in MM cells, of which, RSK2 was further validated by both shRNA silencing and specific inhibitors as an effective target to cooperate with IMiDs to induce myeloma cytotoxicity. Clinical studies of RSK2 inhibition in concert with IMiD (cereblon inhibitor) therapy would be appropriate. Disclosures: Stewart: Onyx: Consultancy, Research Funding; Millennium: Honoraria, Research Funding; Celgene: Honoraria; BMS: Honoraria.