Abstract: Multiple myeloma (MM) is a neoplasm thought to arise from a damaged germinal center B-cell that progresses to a plasma cell clone arising in bone marrow. MM comprises 20% of all hematologic cancer deaths. Persons of African ancestry (AA) have a 1.5 to 2-fold higher risk compared to individuals of European ancestry (EA). Genetically driven differences in hematopoiesis may lead to variation in the levels white blood cell (WBC) subsets which could, in turn, be associated with MM etiology. There are differences in genetic determinants of WBC traits between EA and AA populations, with possible implications for the racial disparity in risk. We tested the above hypothesis using Mendelian randomization (MR), an approach that leverages genetic determinants of specific traits (i.e. WBC counts) to estimate their effects on the risk of an outcome; and a transcriptome-wide association study (TWAS), which utilizes genetic predictors of gene expression to identify susceptibility genes. These analytic approaches were applied to data from the African American Multiple Myeloma Study (AAMMS) consisting of 1813 cases and 8871 AA cancer-free controls to examine how differences in heritable WBC gene expression profiles influence MM risk. Genetic determinants of variation in WBC subsets in AA were obtained from the literature and supplemented with new genome-wide association findings in AA subjects from the UK Biobank cohort (n=6108). Odds ratios (OR) for MM per 1 standard deviation (SD) increase in each WBC phenotype were estimated using independent (linkage disequilibrium (LD) r2 〈 0.10) variants with P 〈 10-6 as genetic instruments. Analyses based on variants associated with WBC traits in AA populations did not identify any statistically-significant associations between MM risk and WBC overall (p=0.81, using 15 SNPs) or subsets (lymphocytes, monocytes, eosinophils, neutrophils and basophils, p 〉 0.05 for each). However, when we applied genetic determinants of WBC identified in 330,000 cancer-free EA UK Biobank participants (P 〈 10-8, replication P 〈 0.05, LD r2 〈 0.05), a statistically significant inverse relationship emerged between increasing lymphocyte counts and MM risk (OR=0.80, 95% CI: 0.66-0.97, p=0.02, using 385 SNPs), as well as increasing basophil counts (OR=0.63, 95% CI: 0.41-0.96, p=0.03, using 140 SNPs). Next, we examined the association between WBC gene expression profiles and MM risk in AAMMS data. We applied published and validated ancestry-specific models developed using the PrediXcan approach, which leverage germline genetic and transcriptomic data from the Multi-Ethnic Study of Atherosclerosis (MESA) (Mogil et al. PMID: 30096133). The primary TWAS used gene expression models trained in AA subjects (n=233), with sensitivity analyses using models developed in AA and Hispanic subjects (n=585). The TWAS significance threshold was based on the number of genes with significant germline prediction models (p 〈 0.05 and R2 ≥0.05) in AA, corresponding to P 〈 0.05/2700 = 1.85×10-5. The expression of two genes was significantly associated with MM risk: KANK1at 9p24.3 (P = 1.01×10-5) and DNAJC27at 2p23.3 (P = 1.56×10-5). KANK1is a candidate tumor suppressor gene for renal cell carcinoma and has recently been associated with MM risk in AA [Du, Blood 2017 130:3058]. Here we provide additional evidence for its role in MM etiology via gene expression-mediated mechanisms. DNAJC27 (previously known as RBJ) is a novel MM risk gene linked to constitutive activation of ERK in solid tumors. We also identified two suggestively associated genes: PRR14 (P = 1.34×10-4; combined AA-Hispanic sample: P = 1.56×10-6), which has been linked to MM risk in EA populations, and PARP16 (P = 9.46×10-5). To our knowledge this is the first study to comprehensively examine variation in WBC traits and gene expression profiles with respect to MM risk in AA. Our TWAS analysis leveraged data from the largest collection of genetic and gene expression data in AA, enabling ancestry-matched inference and identification of two novel risk genes. Although the limited availability of genetic instruments for WBC limited the power of MR analysis, findings using variants identified in European populations may offer some insight into trans-ethnic etiologic pathways and contribute to risk stratification strategies using genetic and blood cell count biomarkers. Future studies, particularly with MGUS-free controls, are needed to validate these results. Disclosures Song: Millennium Pharmaceuticals Inc: Employment. Rand:Ancestry.com: Employment. Ailawadhi:Cellectar: Research Funding; Janssen: Consultancy, Research Funding; Celgene: Consultancy; Pharmacyclics: Research Funding; Amgen: Consultancy, Research Funding; Takeda: Consultancy. Nooka:Takeda: Honoraria, Other: advisory board participation; Janssen: Honoraria, Other: advisory board participation; GSK: Honoraria, Other: advisory board participation; Spectrum pharmaceuticals: Honoraria, Other: advisory board participation; Adaptive technologies: Honoraria, Other: advisory board participation; Amgen: Honoraria, Other: advisory board participation; Celgene: Honoraria, Other: advisory board participation; BMS: Honoraria, Other: advisory board participation. Singhal:Bureau of Millennium/Takeda, Celgene, Janssen, Celgene, Bristol-Myers Squibb and Bluebird: Speakers Bureau. van Rhee:Takeda: Consultancy; Sanofi Genzyme: Consultancy; Castleman Disease Collaborative Network: Consultancy; EUSA: Consultancy; Adicet Bio: Consultancy; Kite Pharma: Consultancy; Karyopharm Therapeutics: Consultancy. Mehta:Millennium/Takeda, Celgene; stock in Celgene, Bristol-Myers Squibb and Bluebird: Speakers Bureau. Wolf:Takeda: Consultancy; Celgene: Consultancy; Novartis: Consultancy; Janssen: Consultancy; Amgen: Consultancy. Martin:Roche and Juno: Consultancy; Amgen, Sanofi, Seattle Genetics: Research Funding. Fiala:Incyte: Research Funding. Terebelo:Jannsen: Speakers Bureau; Celgene: Honoraria; Newland Medical Asociates: Employment. Anderson:Bristol-Myers Squibb: Other: Scientific Founder; Oncopep: Other: Scientific Founder; Amgen: Consultancy, Speakers Bureau; Janssen: Consultancy, Speakers Bureau; Takeda: Consultancy, Speakers Bureau; Celgene: Consultancy, Speakers Bureau; Sanofi-Aventis: Other: Advisory Board. Vij:Bristol-Myers Squibb: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Genentech: Honoraria; Janssen: Honoraria; Karyopharm: Honoraria; Sanofi: Honoraria; Takeda: Honoraria, Research Funding. Bernal-Mizrachi:TAKEDA: Research Funding; Kodikas Therapeutic Solutions, Inc: Equity Ownership; Winship Cancer Institute: Employment, Patents & Royalties. Morgan:Amgen, Roche, Abbvie, Takeda, Celgene, Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Other: research grant, 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. Huff:Member of Safety Monitoring Board for Johnson and Johnson: Membership on an entity's Board of Directors or advisory committees; Karyopharm, Sanofi, MiDiagnostics: Consultancy. Lonial:Karyopharm: Consultancy; Takeda: Consultancy, Research Funding; Amgen: Consultancy; BMS: Consultancy; Janssen: Consultancy, Research Funding; GSK: Consultancy; Celgene Corporation: Consultancy, Research Funding; Genentech: Consultancy. Orlowski:Poseida Therapeutics, Inc.: Research Funding.

Abstract: Persons of African ancestry (AA) have a twofold higher risk for multiple myeloma (MM) compared with persons of European ancestry (EA). Genome-wide association studies (GWASs) support a genetic contribution to MM etiology in individuals of EA. Little is known about genetic risk factors for MM in individuals of AA. We performed a meta-analysis of 2 GWASs of MM in 1813 cases and 8871 controls and conducted an admixture mapping scan to identify risk alleles. We fine-mapped the 23 known susceptibility loci to find markers that could better capture MM risk in individuals of AA and constructed a polygenic risk score (PRS) to assess the aggregated effect of known MM risk alleles. In GWAS meta-analysis, we identified 2 suggestive novel loci located at 9p24.3 and 9p13.1 at P & lt; 1 × 10−6; however, no genome-wide significant association was noted. In admixture mapping, we observed a genome-wide significant inverse association between local AA at 2p24.1-23.1 and MM risk in AA individuals. Of the 23 known EA risk variants, 20 showed directional consistency, and 9 replicated at P & lt; .05 in AA individuals. In 8 regions, we identified markers that better capture MM risk in persons with AA. AA individuals with a PRS in the top 10% had a 1.82-fold (95% confidence interval, 1.56-2.11) increased MM risk compared with those with average risk (25%-75%). The strongest functional association was between the risk allele for variant rs56219066 at 5q15 and lower ELL2 expression (P = 5.1 × 10−12). Our study shows that common genetic variation contributes to MM risk in individuals with AA.

Abstract: Background: Persons of African ancestry (AA) have a 2-3-fold higher risk of multiple myeloma (MM) than persons of European ancestry (EA). Like other B-cell malignancies, genome-wide association scans (GWAS) have identified MM risk variants in the HLA region in persons of EA. We conducted a case-control analysis with data from the National Marrow Donor Program (NMDP)1comprising MM patients typed for bone marrow transplant to donor controls matched by race-ethnicity, and found associations between specific HLA alleles/haplotypes and MM risk that varied by race and ethnicity. To confirm our results and identify additional novel signals, we have now investigated associations between HLA alleles and haplotypes and MM risk in the African American Multiple Myeloma Study (AAMMS) Cohort. Methods: The source of subjects was the AAMMS, in which AA MM patients were identified from 10 cancer centers and 4 Surveillance, Epidemiology and End-Results (SEER) Program cancer registries in order to identify genetic risk factors for MM among AAs. A GWAS was conducted using the Illumina Human Core BeadChip array on DNA samples from 1,305 AA MM patients in the AAMMS comparing results to those from 7,078 AA controls with GWAS data generated from the Illumina 1MDuo2. The major histocompatibility complex (MHC) region single nucleotide polymorphisms (SNPs) were imputed to classical HLA variants using HIBAG. Unconditional logistic regression was used to estimate HLA associations, adjusting for sex, age and the first 2 principal components. P-values were adjusted for false discovery rate (FDR) for each locus group. Results: We did not identify any single HLA alleles associated with MM risk among AAs. However, several B*07:02-containing haplotypes were associated with MM risk (odds ratios [OR] ranging from 2.38 to 2.64 and FDR P-values ranging from 1.43 x 10-6 to 3.57 x 10-8). We found associations between MM risk and genotypes containing DRB3*02:02, including DRB3*02:02~DRB1*11:01+ DRB3*02:02~DRB1*11:01 (OR=1.93, PFDR= 9.36 x 10-5) similar to those observed in the NMDP study1. Novel findings included associations between MM risk and HLA Class I haplotypes B*53:01+ B*57:01 (OR=1.94, PFDR= 0.003) and C04:01~B*53:01+C*06:02~B*57:01 (OR=1.96, PFDR= 0.0050). Results from an ongoing meta-analysis between the two data sets (one based on an imputed GWAS and one based on NMDP HLA typing) will be presented. Conclusions: This study is the second to examine HLA alleles and risk of MM among AA's and is by far the largest. We confirmed a previously observed association between an HLA Class II DRB3 variant and MM risk and confirmed an association with B*07 haplotypes previously observed among EAs1. We also identified novel associations between other HLA Class I haplotypes and MM risk in AA's. Because HLA is highly polymorphic, many HLA alleles are rare variants for which genetic associations are difficult to detect without very large sample sizes. Further investigation with large sample sizes will be necessary to refine these associations in order to better identify the underlying causal alleles and determine the functional significance of these HLA associations. 1Beksac M, Gragert L, Fingerson S, et al.: HLA polymorphism and risk of multiple myeloma.Leukemia. 2016 Jul 27. doi: 10.1038/leu.2016.199. 2Rand KA, Song C, Hwang AE, et al. Genetic susceptibility markers of multiple myeloma in African-Americans. Abstract # 2030, 56th Annual American Society of Hematology Meeting, San Francisco, California, 2014. Disclosures Ailawadhi: Pharmacyclics: Consultancy; Novartis: Consultancy; Amgen Inc: Consultancy; Takeda Oncology: Consultancy. Nooka:Spectrum, Novartis, Onyx pharmaceuticals: Consultancy. Zonder:Pharmacyclics: Other: DSMC membership; Prothena: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Bristol Myers Squibb: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Janssen: Consultancy, Honoraria. Lonial:BMS: Consultancy; Novartis: Consultancy; Millenium: Consultancy; Celgene: Consultancy; Janssen: Consultancy; Merck: Consultancy; Celgene: Consultancy; BMS: Consultancy; Novartis: Consultancy; Onyx: Consultancy; Janssen: Consultancy; Onyx: Consultancy.

Abstract: Abstract 4002 African-Americans (AA) have a 2–3-fold higher risk of multiple myeloma (MM) relative to Whites (Gebregziabher, 2006). We have formed a consortium and are conducting a multi-center study with 9 clinical centers and 4 NCI Surveillance, Epidemiology and End-Results (SEER) Program population-based cancer registries to determine the causes of the disease in this population and explain the excess risk (Myeloma in African-American Patients, MAP). Participation involves providing a blood or saliva specimen for DNA and answering a lifestyle and medical history questionnaire. At the end of the data collection period, a genome-wide scan will be performed and our results compared to those from 2,000 African-American controls participating in cohort studies. Patients with African ancestry (predominantly African-Americans) are identified from outpatient clinic rosters or from population-based cancer registries. For patients recruited at clinics, information on subtype, cytogenetics, FISH and lytic bone lesions is abstracted from medical records. To date, 601 patients have agreed to be in the study and we have received DNA samples from 592 patients; 54.6% are female and 45.4% are male. The mean age at diagnosis is 57 years (SD =11.2) with a median age at diagnosis of 58 years (range 27 to 90 years of age). Of the 514 subjects who completed a questionnaire, 7.8% were obese at age 20 (body mass index 〉 30) and 39% were obese 5 years prior to diagnosis. A first-degree relative with MM was reported by 17 cases (3%), 74% higher than the lifetime risk of 1.7% in the general population based on SEER data. In addition, cases reported 21 first-degree relatives with leukemia (4%), 7 with non-Hodgkin lymphoma (1%) and 14 with Hodgkin lymphoma (3%). To date, clinical information has been abstracted for 351 patients. Of these, 207 (58%) have active disease with the following distribution: stage I (30%), stage II (27%) and stage III (43%). The remainder have relapsed (13%), refractory (1%), relapsed and refractory (4%), or smoldering myeloma (6%), or are in remission (18%). The subtype distribution is: IgG (74%), IgA (11.4%), IgD (0.9%) and IgM (0.3%), and light chain only (13.5%); a distribution significantly different from that observed in a predominantly White population (P 〈 0.007) (Kyle, 2003), (Table 1). Lytic bone lesions were present in 67% of patients, similar to the prevalence observed in other series. FISH and cytogenetics data on hyperdiploidy, deletions in chromosome 13 and 17p, and IGH translocations are being collected on this large cohort of African-Americans patients and will be presented at the ASH meeting. Disease characteristics in AA patients appear to be different than those previously reported in predominantly White populations. Table 1. Type of multiple myeloma and presence of bony lesions in 351 African-American patients. African-American Patients Mayo Clinic1 n % % Type     IgA 38 11.4 20     IgD 3 0.9 〈 10     IgG 247 74 50     IgM 1 0.3 〈 10     Light Chain only 45 13.5 20     Total 334     Not Available 17 Lytic Bone Lesions     Present 160 67 70     Absent 79 33     Total 239     Not Available 112 1 Kyle RA, Gertz MA, Witzig TE, Lutz JA, Lacy MQ, Dispenzieri A, Fonseca R, Rajkumar SV, Offord JR, Larson DR, Plevak ME, Themeau TM, Gregg PR, Review of 1,027 patients with newly diagnosed multiple myeloma. Mayo Clin Proc, 78: 21–33, 2003. Disclosures: No relevant conflicts of interest to declare.

Abstract: African-American ethnicity, male sex, older age and obesity are accepted risk factors for multiple myeloma (MM). Obesity early in life is a risk factor for many cancers, including MM; most studies have focused on populations of European origin. African-Americans have a higher prevalence of obesity than other populations, and may have a distinct genetic contribution to this condition. We established a multi-center collaborative study to investigate possible explanations for the excess risk of MM among African-Americans. The aim of the present case-case analysis was to determine whether body mass index (BMI) was associated with risk factors and clinical characteristics at presentation in African-American MM patients. Methods Patients diagnosed with active MM since January 1, 2009 were recruited from nine outpatient centers and three Surveillance, Epidemiology, End-Results Program (SEER) population-based cancer registries. Information on weight and height at 20 years of age and at 5 years prior to diagnosis was obtained from questionnaires. Clinical information collected included age at diagnosis, stage, percent plasmacytosis on bone marrow biopsy, β2 microglobulin level, Ig serotype, light vs. heavy chain disease, and presence of lytic bone lesions. BMI (ht/wt2) was categorized into 3 levels (normal 〈 25, overweight 25-29, obese 〉 30) according to World Health Organization standard. The Pearson chi-square test was used to test the association between BMI category, and risk factors and clinical characteristics. Mean ages at diagnosis across BMI categories were compared using linear regression and a t-test for trend calculated. Results To date, 1,044 African-American MM patients have been enrolled and of those, 1,014 provided a DNA sample. At present, 970 patients have completed a questionnaire, clinical records have been abstracted for 823 patients, and 509 patients have some information on gender, age at diagnosis, weight, height and clinical characteristics.The mean age at diagnosis was 59. Increasing BMI at age 20 was associated with younger age at diagnosis (p= 0.0004), whereas BMI at 5 years prior to diagnosis was not associated with age at diagnosis (p=0.9477). Among men, mean age at diagnosis decreased with increasing BMI at age 20 (p= 0.0125) (Table 1a) and at 5 years prior to diagnosis (p=0.0252) (Table 1b). Among women, the trend was signficant at age 20 (p=0.0018) (Table 1a) but not at 5 years prior to diagnosis (p= 0.7094) (Table 1b). Increasing BMI was not significantly associated with any other clinical characteristics. Conclusion/Discussion In a large collection of African-American MM patients, we observed a strong association between increasing BMI at age 20 and younger age at diagnosis. A similar trend was observed in men only at 5 years prior to diagnosis, consistent with previous reports. Obesity is one of the few known potentially modifiable risk factors for MM. Younger age at diagnosis reflects an earlier accumulation of either or both genetic and environmental risk factors. Obesity at an early age may influence MM risk through shared biological pathways such as interleukin-6 and insulin-like growth factor, by contributing to chronic B-cell activation, thereby increasing susceptibilty for MM later in life. The significance of the gender difference for the association closer to diagnosis is unclear and requires additional study. Disclosures: Terebelo: Amgen: Honoraria; Millennium: Honoraria. Mehta:Celgene: Speakers Bureau; Millennium: Speakers Bureau. Zonder:Skyline: Consultancy. Orlowski:Bristol-Myers Squibb: Honoraria, Membership on an entity’s Board of Directors or advisory committees, Research Funding; Celgene: Honoraria, Membership on an entity’s Board of Directors or advisory committees, Research Funding; Millennium: The Takeda Oncology Company: Honoraria, Membership on an entity’s Board of Directors or advisory committees, Research Funding; Onyx: Honoraria, Membership on an entity’s Board of Directors or advisory committees, Research Funding; Resverlogix: Research Funding; Array Biopharma: Honoraria, Membership on an entity’s Board of Directors or advisory committees; Genentech: Honoraria, Membership on an entity’s Board of Directors or advisory committees; Merck: Membership on an entity’s Board of Directors or advisory committees. Lonial:Celgene Corporation: Consultancy; Millennium: Consultancy; Novartis: Consultancy; Bristol Myers Squibb: Consultancy; Sanofi: Consultancy; Onyx: Consultancy.

Abstract: We recently demonstrated that multiple myeloma (MM) is organized in a hierarchical manner in which clonogenic MM progenitors or stem cells resembling post-germinal B cells give rise to MM plasma cells (PC). To study the potential biologic differences between MM stem cells and MM PC, we examined each cellular subset for characteristics found in normal stem cells as well as their responses to various antitumor agents. The human MM cell lines RPMI 8226 and NCI-H929 were initially studied as we previously found that they recapitulate clinical MM specimens and consist of distinct cell populations based on the expression of the PC surface antigen CD138; CD138+ cells resemble typical MM PC, whereas CD138neg cells express B cell surface antigens and have greater clonogenic capacity. Examination of these cellular subpopulations by flow cytometry demonstrated that CD138neg cells were smaller and less granular by light scatter than CD138+ PC and expressed higher levels of the intracellular enzyme aldehyde dehydrogenase that is present in normal hematopoietic progenitors with self-renewal potential. Furthermore, cells expressing the side population phenotype after staining with the DNA binding dye Hoechst 33342 were exclusively CD138neg. We also investigated the effects of different clinically applicable agents on CD138+ and CD138neg cells. CD138+ and CD138neg cells isolated from RPMI 8226 and NCI-H929 cells by fluorescence activated cell sorting were treated with dexamethasone (dex, 100nM), bortezomib (velcade, 10nM), CC5013 (revlimid, 1μM), rituximab (10μg/ml) or alemtuzumab (campath,10μg/ml) for 72 hours followed by plating in methylcellulose to assess clonogenic capacity. CD138+ PC were significantly inhibited by dex (27 ± 11% recovery compared to untreated control cells), velcade (14 ± 6%) and revlimid (44 ± 27%), whereas rituximab (92 ± 25%) and campath (97 ± 18%) had little activity. In contrast, clonogenic growth of CD138neg cells was not significantly inhibited by dex (82 ± 19%), velcade (88 ± 29%), or revlimid (91 ± 14%), but was significantly decreased by rituximab (63 ± 22%) and campath (47 ± 27%). Similarly, clonogenic MM growth of CD138neg cells from 4 clinical MM samples was not affected by dex (84 ± 9%), velcade (82 ± 24%), or revlimid (93 ± 11%), but was significantly inhibited by rituximab (19 ± 7%) or campath (15 ± 11%). Clonogenic MM precursors may be distinguished from MM PC by a variety of biological parameters typically expressed by normal stem cells. Furthermore, these cellular subsets have different susceptibilities to a variety of clinical agents, and agents with activity against MM PC may be ineffective against MM stem cells. Moreover, agents without activity agasint MM PC may have major activity against MM stem cells. The divergent sensitivities of MM stem cells and PC may explain the dramatic, but transient, responses seen with many agents. Therapeutic strategies that result in long-term remissions may require the inhibition of both MM PC to reduce clinical symptoms and MM stem cells responsible for relapse.

Abstract: Background: Contemporary trials in adult Ph+ ALL patients with TKIs continue to show improved outcomes with allogeneic blood or marrow transplantation (alloBMT) in first remission (CR1) (Chalandon. Blood. 2015 AND Ravandi. Blood Adv. 2016). These studies have relied on myeloablative conditioning (MAC) and largely required an HLA-matched donor. Post-transplant survival in Ph+ ALL has been shown to be similar between patients transplanted with reduced-intensity conditioning (RIC) and MAC, but the incidence of relapse after RIC is higher (Bachanova. Leukemia. 2014). Post-transplant TKI maintenance reduces the incidence of relapse (Brissot. Haematologica. 2015), but this strategy has not specifically been investigated after RIC. Additionally, HLA-haploidentical donor transplants using post-transplant cyclophosphamide (PTCy) as a component of graft-versus-host disease (GVHD) prophylaxis have comparable outcomes to HLA-matched transplants (McCurdy. Haematologica. 2017). We analyzed outcomes among patients who universally received PTCy and attempted post-transplant TKI prophylaxis to determine the importance of remission status (CR1 vs. later), conditioning regimen, donor type, and TKI choice. Methods: The bone marrow transplant database at Johns Hopkins was queried for adult patients with de novo Ph+ ALL who received alloBMT using PTCy between January 2008 and August 2018. Characteristics of patients were summarized and compared using the student's T test for continuous variables and Fisher's exact test for categorical variables. Estimators of OS and RFS were reported using the Kaplan-Meier method. Differences in time-to-event outcomes were estimated using Cox proportional hazards model. Results: A total of 81 transplants for Ph+ ALL were performed: 69 (85%) in CR1 and 12 (15%) in second or greater remission (CR2+). The demographics are presented in Table 1 and separated by conditioning regimen [MAC vs. nonmyeloablative (NMAC)] for transplants in CR1. The cumulative incidences of grade 2-4 and grade 3-4 aGVHD at 1 year were 33% (95% CI, 23% to 44%) and 9% (95% CI, 3% to 15%), respectively. The incidence of moderate or severe cGVHD at 2 years was 8% (95% CI, 2% to 13%). Nearly all patients (91.4%) initiated a post-transplant TKI at a median of 56 days. Overall, 44.4% of patients were able to take a TKI on ≥85% of nonrelapse days from day 31-395 post-transplant. AlloBMT in CR1 (compared to CR2+) improved RFS (HR=0.25, p=0.0002) and pre-transplant minimal residual disease (MRD) by flow cytometry (MFC) was associated with decreased RFS (HR=2.57, p=0.039). The presence of pre-transplant MRD by PCR did not confer an increased risk of relapse (HR 1.12, p=0.84). Among the 69 patients transplanted in CR1, the 5-year OS was 77.6% (95% CI, 64.8% to 86.2%) and RFS was 67% (95% CI, 52.4-76.5%). As shown in Figure 1, the use of NMAC versus MAC (HR 0.37, p=0.02) and dasatinib versus imatinib at diagnosis (HR 0.21, p=0.007) led to improved relapse-free survival (RFS) in univariate analyses. Neither donor type (with the majority being haploidentical) nor recipient age ≥60 affected RFS. Post-transplant TKI prophylaxis was discontinued prior to relapse in 20 patients among whom 12 remain in an MRD-negative remission, 4 died of non-relapse causes, 3 relapsed, and 1 developed recurrent MRD controlled by a TKI. The median duration of post-transplant TKI prophylaxis prior to discontinuation was 46.5 months in those who remain in treatment-free remission versus 15.6 months in those who relapsed (p=0.01). Eighteen relapses occurred on maintenance therapy, and 90% of tested cases were positive for a kinase domain mutation conferring resistance to the TKI in use at relapse. No significant difference in the median time to TKI initiation post-transplant was noted between those who relapsed on maintenance and those who did not (70 days vs. 55 days, p=0.6). All patients in ongoing remission were MRD-negative by PCR at their most recent evaluation. Conclusions: AlloBMT with PTCy in Ph+ ALL was most effective when performed in CR1 with negative MFC for MRD. The initiation of post-transplant TKI prophylaxis was nearly universal. Among patients transplanted in CR1, the best results were achieved in patients treated with dasatinib at diagnosis (5-year RFS 83%) and NMAC (5-year RFS 73.1%). Thus post-transplant TKI prophylaxis appeared to overcome any relapse control advantage for MAC, yielding better outcomes with NMAC. Disclosures Webster: Amgen: Consultancy; Pfizer: Consultancy. Luznik:WindMil Therapeutics: Patents & Royalties: Patent holder; Genentech: Research Funding; Merck: Research Funding, Speakers Bureau; AbbVie: Consultancy. DeZern:Abbvie: Consultancy; Astex: Research Funding; MEI: Consultancy; Celgene: Consultancy, Honoraria. Pratz:Jazz Pharmaceutical: Consultancy; Millennium: Research Funding; Daiichi Sankyo: Research Funding; Agios: Other: Scientific Advisory Board, Research Funding; Celgene: Other: Scientific Advisory Board; Boston BioMedical: Consultancy; Astellas: Other: Scientific Advisory Board, Research Funding; AbbVie: Other: Scientific Advisory Board, Research Funding. Levis:Astellas: Honoraria, Research Funding; Menarini: Honoraria; Amgen: Honoraria; FujiFilm: Honoraria, Research Funding; Daiichi-Sankyo: Honoraria. Gojo:Amgen: Research Funding; Merck: Research Funding; Genentech: Research Funding; BMS: Membership on an entity's Board of Directors or advisory committees; Amphivena: Research Funding. Bolanos-Meade:Incyte: Other: DSMB Fees. Dalton:Eli Lilly: Research Funding; AbbVie: Research Funding. Jain:Takeda: Consultancy, Honoraria; Bristol Myer Squibb: Other: for advisory board participation; CareDx: Other: Advisory Board. Ali:Celgene: Membership on an entity's Board of Directors or advisory committees. Borrello:Celgene: Research Funding; Aduro: Patents & Royalties; WindMIL Therapeutics: Other: Founder , Research Funding. Wagner-Johnston:ADC Therapeutics, Regeneron, CALIB-R, Verastem: Membership on an entity's Board of Directors or advisory committees. Smith:Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Agios: Consultancy, Membership on an entity's Board of Directors or advisory committees; Jazz: Consultancy, Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees; Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees.

Abstract: Background: Reduced-intensity induction (RII) with imatinib yields comparable outcomes to HyperCVAD with imatinib with fewer induction deaths and an improved CR rate in Ph+ ALL (Chalandon. Blood. 2015). Dasatinib with steroids also produces excellent responses with little toxicity (Foa. Blood. 2011). Allogeneic bone marrow transplant (AlloBMT) remains the goal of therapy in Ph+ ALL based on contemporary trials with TKIs demonstrating improved survival in patients transplanted in CR1, and we have shown that transplant following induction with dasatinib yields better outcomes than with imatinib. Thus we implemented RII with dasatinib for the treatment of Ph+ ALL and compared to patients who received HyperCVAD with a 2nd generation TKI. Methods: Patients with newly diagnosed Ph+ ALL admitted to Johns Hopkins Hospital from September 2017-June 2020 underwent a 4-week RII with: vincristine 2 mg/d weekly, dexamethasone 40 mg PO weekly on days 1 and 2, and dasatinib 100 mg PO daily. CNS prophylaxis with IT MTX was given on day 8. Dexamethasone and vincristine were reduced by 50% for patients over age 70. Filgrastim was started on day 15 for patients without ANC recovery. Patients who received HyperCVAD with dose adjustments for age (Rausch et al. Cancer. 2020) from July 2011-June 2020 were included for comparison. Dasatinib 100 mg PO daily or nilotinib 400 mg PO BID were given with HyperCVAD at the discretion of the treating physician. Rituximab 375 mg/m^2 on days 1 and 8 was given based on CD20 status. Subsequent therapy after induction was not specifically mandated. Results: 21 patients received RII and 24 received HyperCVAD. The cohorts were comparable in terms of gender (38.1% female vs. 50%, p=0.55), age (median 49.8 vs. 50.3, p=0.33), age & gt;60 (33.3% vs. 29.2%, p & gt;0.99), median WBC at diagnosis (19 vs. 23.5, p=0.56), and the presence of decompensated DIC (fibrinogen & lt;150) prior to treatment initiation (4.8% vs. 8.3%, p & gt;0.99). Among the patients treated with HyperCVAD, 15 received dasatinib (62.5%) and 9 received nilotinib (37.5%). Rituximab use was balanced between the cohorts (61.9% vs. 58.3%, p & gt;0.99). Table 1 compares the time to ANC recovery & gt;500, transfusion requirements within 30 days of chemotherapy initiation, rates of decompensated DIC following treatment initiation, and the duration of inpatient hospitalization for induction. While the rates of decompensated DIC were similar in each cohort, patients treated with RII required fewer platelet and pRBC transfusions. ANC recovery was faster following RII, and only 5 patients (23.8%) received growth factor support. All patients achieved a hematologic response. There was one induction death with HyperCVAD (4.2%). Most patients received a subsequent cycle of high-dose (HD) MTX and Ara-C with TKI (76.2% following RII and 91.7% following HyperCVAD). The remaining patients treated with RII subsequently received HD MTX (14.2%) or blinatumomab (9.5%) with TKI due to co-morbidities. Among those patients treated with HD MTX and Ara-C, blinatumomab was given with TKI to 6 patients (37.5%) who initially received RII and 1 patient (4.5%) after HyperCVAD (p=0.03) due to persistent MRD. As shown in Figure 1, the incidence of MRD-negativity by multi-color flow cytometry (MFC) with a sensitivity of 10-4 at day 120 after treatment initiation was similar for RII (85.4%, 95% CI 64.8-97.1) versus HyperCVAD (86.7%, 95% CI 69.8-96.6). Among patients subsequently treated with HD MTX and Ara-C, 62.5% proceeded to alloBMT after RII with an additional 12.5% currently undergoing transplant evaluation, while 86.4% proceeded to alloBMT after HyperCVAD. The 1-year RFS and OS following RII were 87.9% (95% CI 59.6-96.8) and 100% compared to 87.5% (95% CI 66.1-95.8) and 95.8% (95% CI 73.9-99.4) following HyperCVAD. Conclusion: RII with dasatinib results in fewer transfusions and less myelosuppression compared to HyperCVAD with a 2nd generation TKI. More patients treated with RII received blinatumomab following high-dose MTX and Ara-C, but the rates of MRD-negativity were comparable between the two regimens. Thus RII with dasatinib followed by MRD-guided follow-up therapy facilitates MRD negative remissions with less toxicity than HyperCVAD. The vast majority of fit patients were able to proceed to alloBMT following either regimen. Transplant outcomes following dasatinib with induction are presented in our concurrent abstract demonstrating a 5-year RFS of 83% (95% CI 59.8-93.5). Disclosures Webster: Amgen: Consultancy; Pfizer: Consultancy. Jain:Bristol Myer Squibb: Other: for advisory board participation; CareDx: Other: Advisory Board; Takeda: Consultancy, Honoraria. Dalton:AbbVie: Research Funding; Eli Lilly: Research Funding. DeZern:Abbvie: Consultancy; Astex: Research Funding; Celgene: Consultancy, Honoraria; MEI: Consultancy. Gojo:Genentech: Research Funding; Amphivena: Research Funding; Merck: Research Funding; BMS: Membership on an entity's Board of Directors or advisory committees; Amgen: Research Funding. Bolanos-Meade:Incyte: Other: DSMB Fees. Luznik:WindMil Therapeutics: Patents & Royalties: Patent holder; AbbVie: Consultancy; Merck: Research Funding, Speakers Bureau; Genentech: Research Funding. Ali:Celgene: Membership on an entity's Board of Directors or advisory committees. Borrello:Celgene: Research Funding; Aduro: Patents & Royalties; WindMIL Therapeutics: Other: Founder , Research Funding. Wagner-Johnston:ADC Therapeutics, Regeneron, CALIB-R, Verastem: Membership on an entity's Board of Directors or advisory committees. Smith:Jazz: Consultancy, Membership on an entity's Board of Directors or advisory committees; Agios: 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; Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees. Levis:Menarini: Honoraria; Amgen: Honoraria; Daiichi-Sankyo: Honoraria; FujiFilm: Honoraria, Research Funding; Astellas: Honoraria, Research Funding.

Abstract: From 2013-2017, numerous new approvals and expanded indications have dramatically changed the treatment (tx) landscape for MM. Since that time, experienced MM physicians from leading academic institutions and cancer centers (experts) have annually updated and contributed tx recommendations for an online decision support tool designed to provide healthcare providers (HCPs) with patient-specific tx guidance. This MM tool is freely available online at www.clinicaloptions.com/myelomatool and HCPs can use the tool to enter details of a patient case, indicate their intended tx plan, and then expert tx recommendations for that case are provided. Methods This study includes analysis of tx recommendations from 5 MM experts for 270 unique MM case scenarios made during development of the 2018 update to this tool. We also aim to compare the evolving tx recommendations among the experts over time, from 2013-2017, and to determine practice patterns of HCPs using the tool over the same time span. Results Based on analysis of these annually updated MM tools, consensus (≥ 3 of 5 experts choosing the same tx for the same case) among experts has been increasing for induction tx since 2013. In ASCT-eligible patients with no specific comorbidities, experts recommended bortezomib/lenalidomide/dexamethasone (VRd) in 100% and 90% of tool cases in 2018 and 2017, respectively, which increased from 65% to 75% consensus in 2013-2015. In previous analyses, the percentage of HCPs using VRd has also increased, albeit more slowly than with experts. In 2017, 42% of HCPs indicated that they are using VRd as induction in this setting compared with 22% in 2015-2016 and 9% in 2014-2015. For ASCT-ineligible patients with ECOG 〉 2 but no specific comorbidities, all 5 experts recommend triplet therapy for all cases regardless of risk in 2018, but in 2017, 3 of 5 recommended triplet therapy and 2 of 5 recommended doublets for normal-risk disease. Expert recommendations for induction change, however, based on specific patient comorbidities. For patients with peripheral neuropathy, 4 of 5 experts recommended carfilzomib/lenalidomide/dexamethasone instead of VRd. For patients with renal insufficiency, 4 of 5 experts recommended bortezomib/cyclophosphamide/dexamethasone. For patients with cardiac dysfunction, all 5 experts continue to recommend VRd for patients with ECOG ≤ 2 while 2 of 5 change from VRd to Rd for patients with ECOG 〉 2. For patients who achieve VGPR or better to induction, all 5 experts recommend lenalidomide maintenance for standard risk disease. But for patients with high risk disease who achieve VGPR or better to induction, 3 of 5 experts recommend bortezomib/lenalidomide combination maintenance therapy regardless of induction regimen, 1 expert recommends single-agent bortezomib regardless of induction regimen, and 1 expert recommends bortezomib after a PI-based induction regimen or lenalidomide for an IMiD or IMiD/PI-based induction regimen. In the 2018 tool update, the number of R/R case scenarios with 100% expert consensus increased over previous years: 20% of cases had all 5 experts agreeing on tx vs 12% in 2017. In addition, 29% of cases had 3 of 5 experts agreeing and 8% had 2 pairs of experts agreeing in 2018 vs none with 3 of 5 experts agreeing and 21% with 2 pairs of experts agreeing in 2017. In 2018, experts recommended daratumumab/pomalidomide/dexamethasone all cases with 100% consensus, which comprises patients who are refractory to multiple agents including lenalidomide, bortezomib, and/or carfilzomib. Overall, 23 different regimens were recommended for R/R MM; and additional majority expert consensus included daratumumab/lenalidomide/dexamethasone, daratumumab/carfilzomib/dexamethasone, and carfilzomib/pomalidomide/dexamethasone (Table 1). Conclusions Practice patterns are changing rapidly and are more complex, particularly in the R/R setting, in response to the evolving tx landscape for MM. This analysis highlights several areas of expert consensus, but disparities remain for select cases. The newest approved therapies continue to have a strong impact on experts' recommendations as they have been fully integrated into their tx approaches. These analyses provide a real-time assessment of changing tx patterns among experts as well as HCPs. We will present analyses of cases entered in the 2018 online tool by HCPs and detailed comparisons of expert and the intended tx of clinicians using the tool. Disclosures Ghobrial: Takeda: Consultancy; Janssen: Consultancy; Celgene: Consultancy; BMS: Consultancy. Lonial:Amgen: Research Funding. Raje:Research to Practice: Honoraria; Takeda: Consultancy; AstraZeneca: Research Funding; Celgene: Consultancy; BMS: Consultancy; Merck: Consultancy; Janssen: Consultancy; Amgen Inc.: Consultancy; Medscape: Honoraria. Kumar: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; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche: Research Funding; Merck: 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; 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; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: 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; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding.

Abstract: Introduction - With over 12,000 deaths from MM anticipated in 2016, nearly all patients (pts) with multiple myeloma (MM) will become "quad refractory" to IMIDs (lenalidomide and pomalidomide) and proteasome inhibitors (bortezomib and carfilzomib), and eventually "penta refractory" to anti-CD38 Abs (daratumumab and isatuximab), defining high unmet need populations. Selinexor, an oral selective XPO1 inhibitor, induces nuclear accumulation and activation of tumor suppressor proteins, inhibition of NF-kB, and inhibition of translation of several oncoprotein mRNAs such as c-myc and cyclin D. Selinexor showed potent induction of apoptosis of MM cells independent of p53 signaling. In phase 1 clinical studies, selinexor with low dose dexamethasone (Sd) demonstrated potent anti MM activity in pts with MM. Methods - This phase II clinical trial evaluated Sd in pts with MM refractory to bortezomib, carfilzomib, lenalidomide, and pomalidomide ("quad"), with a subset also refractory to an anti-CD38 Ab ("penta"). Inclusion required CrCL≥20 mL/min, ANC≥1000/µL, platelets ≥50K/µL (≥30K if plasma cells were ≥50% of marrow cellularity). Pts were treated twice weekly (BIW) with oral selinexor 80 mg for 6 or 8 doses per 28 day cycle and dexamethasone (dex) 20 mg BIW. All pts received 5-HT3 antagonists. The primary objective was to determine the overall response rate (ORR) per IMWG criteria and duration of response (DOR), both adjudicated by an independent review committee (IRC). Secondary endpoints include progression free survival (PFS) and overall survival (OS). FISH analyses and gene expression profiling were performed on bone marrow aspirates. Results - 79 pts were enrolled: 48 quad (24 M/24 F, median age 62 yrs) and 31 penta (13 M / 18 F, median age 68 yrs). Both groups had a median of 7 prior treatment regimens including multiple dex-containing regimens. Baseline laboratory abnormalities included grade (Gr)≥3 anemia in 13% and Gr≥3 thrombocytopenia in 8%. Most penta pts received 8 doses / cycle (65%); most quad pts received 6 doses / cycle (83%). Common treatment-related adverse events (TRAEs) hematological: thrombocytopenia (72%, Gr 3/4 58%), anemia (48%, Gr 3 25%) and neutropenia (29%, Gr≥3 21%). TRAEs non-hematological: nausea (72%, Gr 3 6%), fatigue (62%, Gr 3 14%) anorexia (49%, Gr 3 3%), vomiting (43%, Gr3 4%), asymptomatic hyponatremia (42%. Gr 3 20%), diarrhea (42%, Gr 3 5%) and weight loss (33%, Gr 3 1%). There was one case of febrile neutropenia (1%) and one case of clinically significant bleeding related to thrombocytopenia (1%). Seventy pts have discontinued therapy: PD (73%), AEs (17%), physician/pt preference (1%) and 6 deaths (one case related to selinexor, intracranial bleed in pt with Gr4 thrombocytopenia). Nine pts remain on study. Efficacy was evaluated in 78 pts (1 pt did not have measurable disease). The IRC-determined ORR (≥PR) for all pts was 21%, including 5% VGPR. ORR was 21% for quad pts and 20% for penta pts. Clinical benefit rates (≥MR) were 32% (all), 29% (quad), and 37% (penta). Median OS was 9.3 months (mo) for all pts, 〉 11 mo (median not reached) for responders (≥PR), and 5.7 mo for non-responders. Median DOR in responding pts was 5 mo, and median PFS in all pts was 2.1 mo. Baseline cytogenetics were assessed in 41 pts. The ORR in 18 pts with high-risk FISH abnormalities was 33% (Table 1). Notably, 3 of the 13 pts with a 17p abnormality responded (ORR 23%). Transcriptomic profiling revealed differentially expressed genes (DEGs) between responders and non-responders in both whole blood RNA and CD138+ bone marrow cells. Pathways enriched in responders included IL-6, IL-8 and IGF-1 pathways. Conclusions - Oral Sd is active in heavily pretreated pts with refractory MM, including those with MM refractory to anti-CD38 Ab and those with high-risk cytogenetic abnormalities. Response was associated with longer survival. The main toxicities of Sd are thrombocytopenia, nausea, anorexia, and fatigue. AEs were manageable with supportive care and dose interruptions/reductions. To our knowledge, this is the first report of anti-tumor activity in the penta-refractory MM population. This population of MM pts has exhausted all currently available treatment options and has an extremely poor prognosis and therefore requires new therapies. Expansion of this trial in this high unmet medical need, penta refractory population is planned. Table 1 Activity of Sd in Patients with High Risk MM Cytogenetics Table 1. Activity of Sd in Patients with High Risk MM Cytogenetics Disclosures Vogl: Constellation: Research Funding; Karyopharm: Consultancy; Acetylon: Research Funding; GSK: Research Funding; Calithera: Research Funding; Teva: Consultancy; Celgene: Consultancy; Takeda: Consultancy, Research Funding. Jagannath:Bristol-Myers Squibb: Consultancy; Janssen: Consultancy; Novartis: Consultancy; Merck: Consultancy; Celgene: Consultancy. Baz:Bristol-Myers Squibb: Research Funding; Takeda/Millennium: Research Funding; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Signal Genetics: Research Funding; Novartis: Research Funding; Karyopharm: Research Funding; Merck: Research Funding. Nooka:Spectrum, Novartis, Onyx pharmaceuticals: Consultancy. Richter:Takeda: Consultancy, Speakers Bureau; Amgen: Consultancy, Speakers Bureau; Celgene: Consultancy, Speakers Bureau; Janssen: Speakers Bureau; Bristol-Myers Squibb: Speakers Bureau; Novartis: Speakers Bureau. Vij:Karyopharm: Honoraria; Amgen: Honoraria, Research Funding; Celgene: Consultancy; Takeda: Honoraria, Research Funding; Novartis: Honoraria; Bristol-Myers Squibb: Honoraria; Janssen: Honoraria. Schiller:Incyte Corporation: Research Funding. Costa:Sanofi: Honoraria, Research Funding. Chari:Array Biopharma: Consultancy, Research Funding; Takeda: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Pharmacyclics: Research Funding; Janssen: Consultancy, Research Funding; Amgen Inc.: Honoraria, Research Funding; Novartis: Consultancy, Research Funding. Siegel:Takeda: Honoraria, Speakers Bureau; Novartis: Honoraria, Speakers Bureau; Amgen: Honoraria, Speakers Bureau; Celgene: Honoraria, Speakers Bureau; BMS: Honoraria, Speakers Bureau; Merck: Honoraria. Fonseca:Janssen: Consultancy; AMGEN: Consultancy; Millennium, a Takeda Company: Consultancy; Bayer: Consultancy; Sanofi: Consultancy; Patent Pending: Patents & Royalties: The use of calcium isotopes as biomarkers for bone metabolisms; Patent: Patents & Royalties: Prognostication of MM based on genetic categorization of FISH of the disease; AMGEN: Consultancy; Novartis: Consultancy; Millennium, a Takeda Company: Consultancy; Sanofi: Consultancy; AMGEN: Consultancy; Janssen: Consultancy; BMS: Consultancy; Celgene: Consultancy; BMS: Consultancy; Millennium, a Takeda Company: Consultancy; Millennium, a Takeda Company: Consultancy; Patent: Patents & Royalties: Prognostication of MM based on genetic categorization of FISH of the disease; Bayer: Consultancy; Novartis: Consultancy; Patent Pending: Patents & Royalties: The use of calcium isotopes as biomarkers for bone metabolisms; AMGEN: Consultancy; Patent: Patents & Royalties: Prognostication of MM based on genetic categorization of FISH of the disease; Patent: Patents & Royalties: Prognostication of MM based on genetic categorization of FISH of the disease; Patent Pending: Patents & Royalties: The use of calcium isotopes as biomarkers for bone metabolisms; Patent Pending: Patents & Royalties: The use of calcium isotopes as biomarkers for bone metabolisms; Celgene: Consultancy. Kauffman:Karyopharm Therapeutics Inc: 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. Saint-Martin:Karyopharm: Employment. Picklesimer:Karyopharm: Employment. Friedlander:Karyopharm Therapeutics: Employment. Choe-Juliak:Karyopharm Therapeutics: Employment.