Fiala, Mark A.

Abstract Background: SCT is a standard therapeutic approach for patients with MM and has contributed to improved outcomes. While SCT utilization in MM has increased for all racial-ethnic subgroups over time, population-based studies have repeatedly shown that racial minorities are less likely to receive it. We explored factors that determine SCT utilization among patients within a given race to understand intra-racial disparities and how to address them in order to maximize the use of this imperative treatment among eligible patients. Methods: The 2016 National Cancer Database (NCDB) for MM with patients diagnosed between 2004-2013 was studied. Cases without information on the selected patient or facility characteristics evaluated in this analysis, including SCT use, race, median income, insurance status or facility type of initial MM diagnosis and/or treatment were excluded. The association between utilization of SCT as part of initial therapy of MM and socio-demographic factors was studied stratifying patients into mutually exclusive racial-ethnic subgroups non-Hispanic Whites (NHW), non-Hispanic Blacks (NHB), Hispanics, non-Hispanic Asians (NHA) and others using multivariate GEE logistic regression analysis (clustered on facility ID). Interactions between race and patient/facility characteristics and SCT utilization were tested using similar methods but including all races. Results: Of the 123480 unique MM patients in NCDB diagnosed between 2004-2013, 111799 met the inclusion criteria. Of these, 15021 patients (13.4%) received SCT as part of initial MM therapy. Of those who received SCT, 77.5% were NHW (14.4% of all NHW), 15.1% NHB (10.3% of all NHB), 5.2% Hispanics (13.2% of all Hispanics), 2% NHA (15.5% of all NHA) and <1% others. There was no difference by gender but significantly reduced odds of receiving SCT were noted for every 10-year increase in age at diagnosis for all racial subgroups. NHA were the only subgroup not to have a significant year-wise increase over time in odds of receiving SCT between 2004-2013. A significant increase in SCT utilization was seen with increasing median income (quartiles; 2008-2012 data), for NHW and Hispanics but not for NHB and NHA, while increased education (% population with high-school degree; 2008-2012 data) was associated with a significant increase in SCT use for NHW and NHB, but not among Hispanics or NHA. An increase in great circle distance (GCD) from the treating facility as well as a lower Charlson-Deyo comorbidity index (CCI) was associated with significantly increased odds of receiving SCT for all racial groups. Insurancepayer status significantly affected odds of receiving SCT among all races with those having private insurance to be most likely to receive SCT among NHW, NHB and Hispanics while those with "other government" insurance payer type being most likely among NHA. Among treating facility characteristics, patients of all races were more likely to receive SCT if treated at an academic/researchfacility (including NCI-designated centers) or centers with highest quartile of patientvolume seen. For analysis by geographicalregion, NHW and NHA had the highest odds of receiving SCT in mountain region but there was no impact of geography on SCT for NHB or Hispanics. Odds ratio (OR) of receiving SCT as part of initial MM therapy by socio-demographic and facility characteristics for patients of individual racial subgroups are shown in Table 1. A significant interaction between odds of receiving SCT and various racial subgroups was noted for patient age at diagnosis (p<.001, decreased odds among NHW and NHA), GCD from treating facility (p=0.013, increased odds among NHB and NHA), CCI (p=0.043, decreased odds among NHA) and treatment facility volumes (p=0.046, increased odds among NHA and Hispanics). Conclusions: In the largest analysis exploring socio-demographic factors affecting SCT utilization in MM we note a significant disparity within races for who gets SCT as a part of initial MM management and who does not. While some of these factors are non-modifiable, others including access to healthcare, income, insurance and literacy levels, proximity to treatment center, treating facility type as well as volumes are modifiable and appear to be barriers to SCT among in some races, while not in others. These must be addressed to minimize disparities within racial subgroups, especially the minorities and realize maximal benefit of SCT for MM. Disclosures Ailawadhi: Novartis: Consultancy, Honoraria; Pharmacyclics: Research Funding; Amgen: Consultancy, Honoraria; Takeda: Consultancy, Honoraria. Sher: LAM Therapeutics, Inc: Research Funding.

Abstract Background: Persons of African ancestry (AA) experience a 1.5-2-fold risk of multiple myeloma (MM) compared to persons of European ancestry (EA). We assembled a set of MM patients with self-reported AA in order to evaluate the contribution of genetics to etiology in this high-risk group. Methods: Here we present the results of a meta-analysis of two GWAS in 1,813 cases and 8,871 controls of AA. We also conducted an admixture mapping scan to identify risk alleles associated with local ancestry, 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. Finally, we conducted an eQTL analysis measuring gene expression in those genes harboring a risk variant in malignant plasma cells from 292 of the patients from a single site. Results: In GWAS analysis, we identified two suggestive novel loci located at 9p24.3 and 9p13.1 at P<1 × 10-6, but 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. 20 of the 23 known EA risk variants showed directional consistency and 9 replicated at P<0.05 in AA individuals. In eight regions, we identified markers that better capture MM risk in persons of AA. AA individuals with a PRS in the top 10% had a 1.82-fold (95%CI: 1.56, 2.11) increased MM risk compared to 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). Conclusion: Our study shows that common genetic variation contributes to MM risk individuals of AA. This abstract is also being presented as Poster C040. Citation Format: Zhaohui Du, Niels Weinhold, Gregory Chi Song, Kristen A. Rand, David J. Van Den Berg, Amie E. Hwang, Xin Sheng, Victor Hom, Sikander Ailawadhi, Ajay K. Nooka, Seema Singhal, Karen Pawlish, Edward Peters, Cathryn Bock, Ann Mohrbacher, Alexander Stram, Sonja I. Berndt, William J. Blot, Graham Casey, Victoria L. Stevens, Rick Kittles, Phyllis J. Goodman, W. Ryan Diver, Anselm Hennis, Barbara Nemesure, Eric A. Klein, Benjamin A. Rybicki, Janet L. Stanford, John S. Witte, Lisa Signorello, Esther M. John, Leslie Bernstein, Antoinette Stroup, Owen W. Stephens, Maurizio Zangari, Frits Van Rhee, Andrew Olshan, Wei Zheng, Jennifer J. Hu, Regina Ziegler, Sarah J. Nyante, Sue Ann Ingles, Michael Press, John David Carpten, Stephen Chanock, Jayesh Mehta, Graham A Colditz, Jeffrey Wolf, Thomas G. Martin, Michael Tomasson, Mark A. Fiala, Howard Terebelo, Nalini Janakiraman, Laurence Kolonel, Kenneth C. Anderson, Loic Le Marchand, Daniel Auclair, Brian C.-H. Chiu, Elad Ziv, Daniel Stram, Ravi Vij, Leon Bernal-Mizrachi, Gareth J. Morgan, Jeffrey A. Zonder, Carol Ann Huff, Sagar Lonial, Robert Z. Orlowski, David V. Conti, Christopher A. Haiman, Wendy Cozen. A meta-analysis of genome-wide association study and eQTL analysis of multiple myeloma among African Americans [abstract]. In: Proceedings of the Twelfth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2019 Sep 20-23; San Francisco, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl_2):Abstract nr PR05.

Purpose: Multiple myeloma (MM) treatment has changed tremendously, with significant improvement in patient out-comes. One group with a suboptimal benefit is patients with high-risk cytogenetics, as tested by conventional karyotyping or fluorescence in situ hybridization (FISH). Methodology for these tests has been published, but not necessarily standardized. Methods: We address variability in the testing and reporting methodology for MM cytogenetics in the United States using the ongoing African American Multiple Myeloma Study (AAMMS). We evaluated clinical and cytogenetic data from 1,221 patients (1,161 with conventional karyotyping and 976 with FISH) tested between 1998 and 2016 across 58 laboratories nationwide. Results: Interlab and intralab variability was noted for the number of cells analyzed for karyotyping, with a significantly higher number of cells analyzed in patients in whom cytogenetics were normal (P 5.0025). For FISH testing, CD138-positive cell enrichment was used in 29.7% of patients and no enrichment in 50% of patients, whereas the remainder had unknown status. A significantly smaller number of cells was analyzed for patients in which CD138 cell enrichment was used compared with those without such enrichment (median, 50 v 200; P, .0001). A median of 7 loci probes (range, 1-16) were used for FISH testing across all laboratories, with variability in the loci probed even within a given laboratory. Chromosome 13–related abnormalities were the most frequently tested abnormality (n5956; 97.9%), and t(14;16) was the least frequently tested abnormality (n 5 119; 12.2%). Conclusions: We report significant variability in cytogenetic testing across the United States for MM, potentially leading to variability in risk stratification, with possible clinical implications and personalized treatment approaches.

Background: Maintenance therapy with lenalidomide post-autologous stem cell transplantation (ASCT) has shown to improve progression-free survival (PFS) in multiple myeloma (MM), and has largely become the standard of care. However, toxicity leads to early discontinuation in nearly one-third of patients and additional options are needed (McCarthy, et al, JCO, 2017). Ixazomib is another maintenance option that has been shown to improve PFS; however, studies comparing lenalidomide and ixazomib are lacking. In this randomized phase 2 study, we analyzed the safety and efficacy of using lenalidomide and ixazomib as part of consolidation and maintenance therapies after ASCT (NCT02253316). Methods: Eligible patients, age 18-70 with newly diagnosed MM undergoing ASCT during first-line treatment, were consented prior to ASCT. Approximately 4 months following ASCT, patients received 4 cycles of consolidation therapy with IRd [ixazomib 4 mg on days 1, 8 and 15 of a 28-day cycle, lenalidomide 15 mg on days 1 through 21, and dexamethasone 40 mg on days 1, 8 and 15]. Primary data on IRd consolidation were presented at ASH 2018 (Abstract 109920). One month after the last consolidation cycle, patients were randomized (1:1) to maintenance therapy with single-agent ixazomib (4 mg on days 1, 8 and 15 of a 28-day cycle) or lenalidomide (10 mg daily months 1-3 followed by 15 mg for months 4+). The arms were stratified based on MRD-status post-consolidation. In total, 237 patients were enrolled from 10 US centers. This abstract coincides with planned interim analysis 3 which is the first comparison of ixazomib and lenalidomide maintenance. While the study was not powered to compare PFS between the two arms, the sample will provide a reasonable power to estimate non-inferiority. There is a planned stopping rule for non-inferiority set at a hazard ratio of >1.3 in favor of lenalidomide. Secondary end-points include MRD-negativity following 12 cycles and toxicity. Results: At time of abstract submission, 215 patients had completed IRd consolidation and 191 had begun maintenance. 90 were randomized to ixazomib and 94 to lenalidomide. 7 patients were not randomized due to toxicity during consolidation; data from these patients are not included in the analyses. The characteristics of the two arms are summarized in Table 1. Hematologic toxicity has been infrequent with ixazomib with neutropenia and thrombocytopenia occurring in 11% and 23% of patients. In comparison, neutropenia and thrombocytopenia occurred in 45% and 35% of patients on lenalidomide. The most common non-hematologic toxicities in both arms have been GI-related and infections, both expected events. 16% of patients on ixazomib have experienced Grade 3-4 non-hematologic toxicity compared to 34% on lenalidomide. No grade 3 or higher peripheral neuropathy has been reported in either arm. 11% of patients on ixazomib have discontinued due to toxicity and another 9% have required a dose reduction to 3mg. Lenalidomide toxicity has led to discontinuation in 15% of patients and another 12% were dose reduced to 5mg. Only 45% of patients receiving 4+ cycles of lenalidomide were able to titrate to the 15mg dose. After a median follow-up of 11.2 months from randomization (19.7 months post-ASCT), 30% of patients on ixazomib have discontinued treatment due to disease progression. After a median follow-up of 12.3 months from randomization (20.2 months post-ASCT), 18% patients on lenalidomide have discontinued treatment due to disease progression. Conclusion: Ixazomib and lenalidomide maintenance have been well tolerated to date. A comparison of PFS is currently being conducted as part of interim analysis 3 and final results will be presented, representing the first report directly comparing lenalidomide and ixazomib maintenance. Table 1: Disclosures Vij: Genentech: Honoraria; Karyopharm: Honoraria; Celgene: Honoraria, Research Funding; Bristol-Myers Squibb: Honoraria, Research Funding; Takeda: Honoraria, Research Funding; Janssen: Honoraria; Sanofi: Honoraria. Martin:Amgen, Sanofi, Seattle Genetics: Research Funding; Roche and Juno: Consultancy. Fiala:Incyte: Research Funding. Deol:Novartis: Other: Advisory board; Kite: Other: Advisory board; Agios: Other: Advisory board. Kaufman:Celgene: Consultancy; Winship Cancer Institute of Emory University: Employment; Amgen: Consultancy; Bristol-Myers Squibb: Consultancy; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees; AbbVie: Consultancy; Janssen: Honoraria; Incyte: Consultancy; Karyopharm: Membership on an entity's Board of Directors or advisory committees; TG Therapeutics: Consultancy; Takeda: Consultancy. Hofmeister:Karyopharm: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria; Nektar: Honoraria, Membership on an entity's Board of Directors or advisory committees; Imbrium: Membership on an entity's Board of Directors or advisory committees. Gregory:Poseida: Research Funding; Celgene: Speakers Bureau; Amgen: Speakers Bureau; Takeda: Speakers Bureau. Berdeja:AbbVie Inc, Amgen Inc, Acetylon Pharmaceuticals Inc, Bluebird Bio, Bristol-Myers Squibb Company, Celgene Corporation, Constellation Pharma, Curis Inc, Genentech, Glenmark Pharmaceuticals, Janssen Biotech Inc, Kesios Therapeutics, Lilly, Novartis, Poseida: Research Funding; Poseida: Research Funding; Amgen Inc, BioClinica, Celgene Corporation, CRISPR Therapeutics, Bristol-Myers Squibb Company, Janssen Biotech Inc, Karyopharm Therapeutics, Kite Pharma Inc, Prothena, Servier, Takeda Oncology: Consultancy. Chari:Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol-Myers Squibb: Consultancy; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Millennium/Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Karyopharm: Consultancy, Membership on an entity's Board of Directors or advisory committees; Array Biopharma: Research Funding; GlaxoSmithKline: Research Funding; Novartis Pharmaceuticals: Research Funding; Oncoceutics: Research Funding; Pharmacyclics: Research Funding; Seattle Genetics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Membership on an entity's Board of Directors or advisory committees. Rosko:Vyxeos: Other: Travel support.

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 < 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 < .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.

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.

Introduction: Proteasome inhibitors (PI), immunomodulatory agents (IMiDs) and the CD38 monoclonal antibody daratumumab (dara) have transformed the management of MM, yet eventual refractoriness to these agents seems inevitable. Relapsed and refractory MM (RRMM) which becomes triple class refractory (TCR, i.e. refractory to a PI, an IMiD and Dara) uncommonly responds to further lines of therapy and survival is dismal. Selinexor is a selective inhibitor of nuclear export compound targeting exportin 1 (XPO1) which is overexpressed in MM cells and essential for their survival. In the STORM study, selinexor in combination with low-dose dexamethasone (Sd) demonstrated promising efficacy in TCR, penta-exposed (TCR-PE, i.e. exposed to lenalidomide, pomalidomide, bortezomib, carfilzomib and dara) MM. Establishing the natural history for outcomes in the TCR-PE population can help provide context to understand the outcomes observed with Sd in STORM. In the retrospective MAMMOTH study, we reported the outcomes of patients with RRMM after they became refractory to dara, including a subset of patients who were TCR. We further analyzed the MAMMOTH dataset to generate a cohort of patients similar to patients in STORM in order to compare conventional care vs. Sd. Methods: We included all patients in STORM who received Sd as the first line therapy after they achieved TCR-PE status (n=64). We extracted from the MAMMOTH dataset all patients who were not exposed to Sd in a subsequent line of therapy, became TCR-PE and who received subsequent MM-directed therapy (n=128). Overall response rate (ORR) was evaluated according to IMWG criteria. Overall survival (OS) was calculated from the time of initiation of next line of therapy after TCR-PE status until death or last follow-up. We compared OS in STORM vs. MAMMOTH utilizing cox-regression analysis with adjustment for covariables potentially influencing the outcome. Results: Baseline patient characteristics and prior therapies are per table. The two cohorts were similar in terms of age, number of prior lines of therapy and presence of high-risk cytogenetic abnormalities. STORM patients had longer time between MM diagnosis and post TCR-PE therapy with a higher proportion of refractoriness to carfilzomib. Patients in STORM had ORR to Sd of 32.8% vs 25.0% for patients receiving conventional care in MAMMOTH (P=0.078). In direct comparison, patients in STORM had better OS than patients in MAMMOTH (median 10.4 vs. 6.9 months) (P=0.043, figure). In multivariate analysis, STORM patients had lower risk of death in comparison with MAMMOTH patients (aHR=0.55, 95%C.I. 0.35-0.86, P=0.009). Refractoriness to carfilzomib (aHR=2.20, 95%C.I. 1.16-4.15, P=0.015) and high-risk cytogenetics (aHR-1.66, 95% C.I. 1.13-2.42, P=0.009) were also associated with inferior OS. Conclusion: Despite inherent limitations in comparison of trial enrollees vs. real world patients, this analysis suggests improved OS with Sd vs conventional care in patients with TCR-PE RRMM. Prognosis for these patients remains poor and underscores the need for therapeutic advancements. Disclosures Costa: Janssen: Research Funding, Speakers Bureau; Celgene: Consultancy, Honoraria, Research Funding; Sanofi: Consultancy, Honoraria, Speakers Bureau; GSK: Consultancy, Honoraria, Research Funding; Abbvie: Consultancy; Karyopharm: Consultancy; Fujimoto Pharmaceutical Corporation Japan: Other: Advisor; Amgen: Consultancy, Honoraria, Research Funding, Speakers Bureau. Hari:Kite: Consultancy, Honoraria; Amgen: Research Funding; Spectrum: Consultancy, Research Funding; Sanofi: Honoraria, Research Funding; Janssen: Consultancy, Honoraria; BMS: Consultancy, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria, Research Funding; Cell Vault: Equity Ownership; AbbVie: Consultancy, Honoraria. Kumar:Janssen: Consultancy, Research Funding; Takeda: Research Funding; Celgene: Consultancy, Research Funding. Tang:Karyopharm: Employment. Shah:Karyopharm Therapeutics Inc: Employment, Equity Ownership. Jagannath:BMS: Consultancy; Merck: Consultancy; Medicom: Speakers Bureau; Celgene: Consultancy; Novartis: Consultancy; Multiple Myeloma Research Foundation: Speakers Bureau. Chari:Oncoceutics: Research Funding; Novartis Pharmaceuticals: Research Funding; GlaxoSmithKline: Research Funding; Array Biopharma: Research Funding; Karyopharm: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Millennium/Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol-Myers Squibb: Consultancy; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Membership on an entity's Board of Directors or advisory committees; Seattle Genetics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Pharmacyclics: Research Funding. Shacham:Karyopharm Therapeutics Inc: Employment, Equity Ownership, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties. Ma:Karyopharm: Employment, Equity Ownership. Siegel:Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Bristol-Myers Squibb Company: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau. Biran:Amgen: Consultancy, Honoraria, Research Funding; Merck: Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Bristol Meyers Squibb: Research Funding. Lonial:BMS: Consultancy; Genentech: Consultancy; GSK: Consultancy; Janssen: Consultancy, Research Funding; Takeda: Consultancy, Research Funding; Amgen: Consultancy; Celgene Corporation: Consultancy, Research Funding; Karyopharm: Consultancy. Richardson:Amgen: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Sanofi: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Oncopeptides: 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; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol-Myers Squibb: Research Funding. Kauffman:Karyopharm Therapeutics Inc: Employment, Equity Ownership, Membership on an entity's Board of Directors or advisory committees. Malek:Adaptive: Consultancy; Amgen: Speakers Bureau; Janssen: Speakers Bureau; Celgene: Consultancy; Takeda: Consultancy; Sanofi: Consultancy; Medpacto: Research Funding. Fiala:Incyte: Research Funding. Usmani:Amgen, Celgene, Janssen, Sanofi, Takeda: Speakers Bureau; Amgen, Bristol-Myers Squibb, Celgene, Janssen, Merck, SkylineDX, Takeda: Other: Consultant/Advisor; Amgen Array Biopharma, Bristol-Myers Squibb, Celgene, Janssen, Merck, Pharmacyclics, Sanofi, Takeda: Other: Research Grant. Kang:Takeda Oncology: Consultancy; InCyte Corportation: Research Funding. Cornell:Takeda: Consultancy; KaryoPharm: Consultancy.

Abstract Introduction: Monoclonal antibodies (MoAbs) have shown activity in relapsed and refractory multiple myeloma (MM). Elotuzumab is an anti-SLAMF7 MoAb that synergizes with immunomodulatory agents (IMiDs) and is approved for treatment of relapsed and refractory MM. Anti-CD38 MoAbs (daratumumab, FDA approved and isatuximab, in clinical trials) have also entered the therapeutic MM landscape but little is known about how to best sequence MoAbs and the existence of cross resistance between different classes of MoAbs. We analyzed outcomes of patients who become refractory to elotuzumab with emphasis on the activity of anti-CD38 MoAbs in the post-elotuzumab setting. Methods: We identified patients from 14 academic institutions within the US who were refractory to elotuzumab administered alone or in combination with other agents. Patients were considered refractory to elotuzumab if treated with at least 4 weeks of therapy and had evidence of progressive disease (PD) within 60 days of last dose. Time zero (T0) was defined as point when myeloma became refractory to elotuzumab-containing regimen. Data were collected with an electronic platform and submitted to peer-based quality check for completeness and internal consistency. We analyzed demographics, characteristics of their myeloma and prior therapy including number and type of therapy prior to elotuzumab, duration of elotuzumab therapy, and outcome after becoming refractory to elotuzumab. We performed a multi-variable analysis of these factors to determine significant factors associated with survival post T0. We subsequently identified a subset of patients who received an anti-CD38 MoAb alone or in combination as next or subsequent line of therapy after T0 and report their outcomes. Results: Eighty-nine patients were evaluated. Eighty-six (96.6%) had progression on elotuzumab in combination with IMiD (N=82) or another agent (N=4). Median age at T0 was 65 years (range 28-90), 51% of patients were males, 65% were White, 54% had IgG subtype, 27% had ISS stage III at diagnosis, and 27% had high-risk cytogenetics. Patients received a median of 4 prior lines of treatment (range 1-11) prior to elotuzumab-containing regimen, including 66% who underwent autologous transplant. Sixty-one patients (69%) were refractory to at least one IMiD and one proteasome inhibitor (PI) at T0, classified as double-refractory. Twenty-one (23.6%) were quad-refractory, i.e. refractory to 2 IMiDs and 2 PIs. Twenty-eight patients (31.5%) were refractory to prior anti-CD38 MoAb. The median time from diagnosis to T0 was 59.5 months and duration of elotuzumab therapy was 3 months (range 0.4 - 59.5). Median OS from T0 for the entire cohort was 15.1 months (95% C.I. 9.3-20.9). In multivariate analysis, the only factors affecting OS after T0 were high-risk cytogenetics (HR 3.31, 95% C.I. 1.74-6.27, P<0.001) and refractoriness to prior anti-CD38 MoAb (HR 4.22, 95% C.I. 2.22-8.01, P<0.001). Interestingly, median OS for patients not refractory to anti-CD38 MoAb was 33.1 months vs. 4.5 months for anti-CD38 MoAb-refractory patients (Figure 1). After T0, 45 patients (50.6%) received an anti-CD38 MoAb in the next (N=28, 62.5%) or subsequent regimens (N=17, 37.8%). Median time between T0 and initiation of anti-CD38 MoAb was 1.2 months (0-15.0). Anti-CD38 MoAbs employed were: isatuximab in 4 (8.9%) and daratumumab in 41 patients (91.1%). In most cases, the anti-CD38 MoAb was administered in combination with IMiD (N=30, 66.6%) or bortezomib (N=7, 15.6%). The overall response rate (ORR) for anti-CD38 MoAb regimens was 35.6%; responses to specific combinations are outlined in the Table. Median PFS for elotuzumab-refractory patients receiving therapy with anti-CD38 MoAbs was 4.6 months (95% C.I. 1.6-7.6), while median OS was 15.3 months (95% C.I. 8.2-22.4) (Figure 2). Conclusion: Patient who become refractory to elotuzumab have guarded prognosis, particularly dismal among patients also refractory to anti-CD38 MoAb, defining a population with great need for novel therapies. Failure of elotuzumab-based therapy does not preclude disease control with anti-CD38 MoAb, particularly in combination. Disclosures Paul: Bristol Myer Squibb: Other: Stock and pension plan (past employee). Amarendra:Amgen: Consultancy; Celgene: Consultancy. Liedtke:Caelum: Membership on an entity's Board of Directors or advisory committees; celgene: Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech/Roche: Research Funding; BlueBirdBio: Research Funding; Prothena: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Honoraria, 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. Hari:Kite Pharma: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria, Research Funding; Sanofi: Honoraria, Research Funding; Janssen: Honoraria; Bristol-Myers Squibb: Consultancy, Research Funding; Amgen Inc.: Research Funding; Spectrum: Consultancy, Research Funding. Vij:Karyopharm: Honoraria; Jazz Pharmaceuticals: Honoraria; Janssen: Honoraria; Amgen: Honoraria; Takeda: Honoraria, Research Funding; Bristol Myer Squibb: Honoraria, Research Funding; Celgene: Honoraria, Research Funding. Usmani:Abbvie, Amgen, Celgene, Genmab, Merck, MundiPharma, Janssen, Seattle Genetics: Consultancy; Amgen, BMS, Celgene, Janssen, Merck, Pharmacyclics,Sanofi, Seattle Genetics, Takeda: Research Funding. Kumar:Celgene: 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; Janssen: 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. Costa:Karyopharm: Research Funding; Abbvie: Research Funding; Amgen: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; BMS: Research Funding; Sanofi: Honoraria; Janssen: Research Funding.

Abstract Introduction Development of anti-CD38 monoclonal antibody therapies (MoABs), including daratumumab and isatuximab, have drastically changed the therapeutic landscape for management of relapsed and/or refractory multiple myeloma (RRMM). However, there is a paucity of information regarding response to treatment after progression on CD38 MoABs. This collaborative research study (MAMMOTH: Monoclonal Antibodies in Multiple Myeloma: Outcomes after Therapy Failure) investigates the therapeutic choices and outcomes of subsequent treatments after refractoriness to MoABs. Methods Patients from 14 US academic institutions with diagnosis of MM and refractory to daratumumab or isatuximab, administered alone or in combination, were evaluated. Patients were considered refractory to a CD38 MoAB if treated with at least 4 weeks of therapy and had evidence of progressive disease (PD) while on therapy or within 60 days after last dose. Time of progression was defined as time zero (T0). Data was collected by electronic platform and submitted to peer-based quality check for completeness and internal consistency. Results Two hundred and seventy-five patients with MM refractory to CD38 MoAB were evaluated; 249 (90.5%) of those patients who received at least one subsequent line of therapy were included in this analysis. The median age at T0 was 65 years (range 27-90) and 54% were male. At the time of diagnosis, 28% had ISS stage III disease and 29% had high-risk cytogenetics. Patients were heavily pre-treated at T0 with a median of 5 lines of therapy (range 2-17); most (74%) underwent a prior autologous stem cell transplant. The majority of patients were refractory to other anti-myeloma therapies including lenalidomide (78%), pomalidomide (65%), bortezomib (69%) and carfilzomib (45%). In total, 97.1% of patients were exposed to at least one immunomodulatory agent (IMiD) and one proteasome inhibitor (PI), 79.3% were ≥ triple-refractory (refractory to 1 IMiD, 1 PI and 1 CD38 MoAB), while 25.3% were penta-refractory (refractory to 2 IMiDs, 2 PIs and 1 CD38 MoAB). Responses to the next subsequent line of therapy after progression with CD38 MoAB are shown (Table). The overall response rate (ORR; ≥PR) of first regimen post-T0 was 31% with a median progression free survival (PFS) of 3.4 mo and median overall survival (OS) of 9.3 mo. Carfilzomib-based therapy resulted in an ORR of 32% with median PFS 4.2 mo and overall OS of 10.9 mo. The addition of an IMiD to daratumumab yielded an ORR of 37% with median PFS 4.5 mo and OS 12.6 mo. The addition of a PI to daratumumab yielded no responses. Elotuzumab-based therapy had an ORR of 21% with median PFS 2.6 mo and OS 8.3 mo. By multivariate analysis, alkylator-based therapies were found to have the highest ORR (OR 3.1, 95% CI 1.8-5.7, p<0.001), however, resulted in median PFS of only 3 mo and OS of 7.7 mo. Multivariate analysis evaluating for PFS and adjusting for refractoriness to prior therapies found lower risk of progression with carfilzomib-based therapy (HR 0.60, 95% CI 0.42-0.85, p=0.004, Figure 1) and with the addition of an IMiD to daratumumab (HR 0.64, 95% CI 0.43-0.94, p=0.02). The benefit of IMiD + daratumumab was essentially restricted to patients previously refractory to CD38 MoAB as monotherapy. These patients demonstrated improved PFS with subsequent daratumumab-combination therapy at time of progression compared with patients refractory to CD38 MoAB combination therapy (log-rank p=0.02, Figure 2). No particular regimen was associated with improved OS compared with the rest. Conclusions After progression on CD38 MoAB, treatment with carfilzomib-based regimens and the addition of an IMiD to daratumumab-monotherapy resulted in a higher ORR and PFS compared with other regimens. Alkylating agents resulted in the highest ORR but relatively short PFS and OS. The use of elotuzumab and the addition of a PI to daratumumab monotherapy resulted in relatively low response rates. Overall, progression after CD38 MoAB therapy is associated with a poor prognosis and innovative therapeutic strategies are needed. Disclosures Malek: Celgene: Consultancy, Speakers Bureau; Amgen: Consultancy, Speakers Bureau; Takeda: Consultancy, Speakers Bureau; Janssen: Consultancy, Speakers Bureau; Sanofi: Consultancy, Speakers Bureau. Paul:Bristol Myer Squibb: Other: Stock and pension plan (past employee). Neppalli:Celgene: Consultancy; Amgen: Consultancy. Liedtke:Amgen/Onyx: Consultancy, Honoraria, Research Funding; Caelum: Membership on an entity's Board of Directors or advisory committees; Genentech/Roche: Research Funding; Gilead: 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, Research Funding; Prothena: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; celgene: Research Funding; BlueBirdBio: Research Funding; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Hari:Takeda: Consultancy, Honoraria, Research Funding; Spectrum: Consultancy, Research Funding; Kite Pharma: Consultancy, Honoraria; Sanofi: Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Amgen Inc.: Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding; Janssen: Honoraria. Vij:Bristol-Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Jazz Pharmaceuticals: 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, Research Funding; Jansson: Honoraria, Membership on an entity's Board of Directors or advisory committees; Karyopharma: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: 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, Research Funding. Usmani:Amgen, BMS, Celgene, Janssen, Merck, Pharmacyclics,Sanofi, Seattle Genetics, Takeda: Research Funding; Abbvie, Amgen, Celgene, Genmab, Merck, MundiPharma, Janssen, Seattle Genetics: Consultancy. Costa:Amgen: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; BMS: Research Funding; Abbvie: Research Funding; Janssen: Research Funding; Karyopharm: Research Funding; Sanofi: Honoraria. Kumar:Roche: 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; Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: 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; Takeda: Membership on an entity's Board of Directors or advisory committees; Oncopeptides: 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; 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.