Citations

Aims: To evaluate AMG 701, a BiTE® molecule binding BCMA on MM cells and CD3 on T cells, in RR MM (Amgen, NCT03287908); primary objective was to evaluate safety and tolerability and estimate a biologically active dose; secondary objectives were to characterize pharmacokinetics (PK), anti-myeloma activity per IMWG criteria, and response duration. Methods: Patients with MM RR or intolerant to ≥3 lines [proteasome inhibitor (PI), IMiD, anti-CD38 Ab as available] received AMG 701 IV infusions weekly in 4-week cycles until disease progression (PD). A 0.8-mg step dose was added prior to target doses ≥1.2 mg to prevent severe cytokine release syndrome (CRS). Target dose was achieved by day 8 or sooner with earlier escalation. Exclusion criteria included: solely extramedullary disease; prior allogeneic stem cell transplant (SCT) in the past 6 months; prior autologous SCT in the past 90 days; CNS involvement; prior anti-BCMA therapy. The first 3 cohorts (dose 5-45 μg) had 1 patient each, the next cohorts (0.14-1.2 mg) had 3-4 patients each, and subsequent cohorts (1.6-12 mg) were to have 3-10 patients each. Minimal residual disease (MRD) was measured by next-generation sequencing (NGS, ≤10-5 per IMWG) or flow cytometry (≤3×10-5). Results: As of July 2, 2020, 75 patients received AMG 701. Patients had a median age of 63 years, a median time since diagnosis of 5.9 years, and a median (range) of 6 (1-25) prior lines of therapy; 27% of patients had extramedullary disease, 83% prior SCT, and 93% prior anti-CD38 Ab; 68% were triple refractory to a PI, an IMiD, and an anti-CD38 Ab. Median (Q1, Q3) treatment duration was 6.1 (3.1, 15.3) weeks and median follow-up on treatment was 1.7 (1.0, 3.7) months. Patients discontinued drug for PD (n=47), AEs (adverse events, n=4, 3 CRS, 1 CMV / PCP pneumonia), withdrew consent (4), other therapy (1), investigator discretion (1), and CNS disease (1); 17 patients remain on AMG 701. The most common hematological AEs were anemia (43%), neutropenia (23%), and thrombocytopenia (20%). The most common non-hematological AEs were CRS (61%), diarrhea (31%), fatigue (25%), and fever (25%). CRS was mostly grade 1 (n=19) or 2 (n=21) per Lee Blood 2014 criteria. All grade 3 CRS (n=5, 7%) were assessed as dose-limiting toxicities (DLTs); all were reversible with corticosteroids and tocilizumab, with median duration of 2 days. CRS grade 3 drivers included transient LFT increases in 3 patients and hypoxia in 2 patients. Other DLTs were 1 case each of transient grade 3 atrial fibrillation, transient grade 3 acidosis, and grade 4 thrombocytopenia. Serious AEs (n=29, 39%) included infections (13), CRS (7), and asymptomatic pancreatic enzyme rise (2, no imaging changes, 1 treatment related). There were 4 deaths from AEs, none related to AMG 701 (2 cases of sepsis, 1 of retroperitoneal bleeding, and 1 of subdural hematoma). Reversible treatment-related neurotoxicity was seen in 6 patients, with median duration of 1 day, all grade 1-2, and associated with CRS in 4 patients. The response rate was 36% (16/45) at doses of 3-12 mg; at ≤1.6 mg (n=27), there was 1 response at 0.8 mg in a patient with low baseline soluble BCMA (sBCMA). With earlier dose escalation with 9 mg, the response rate was 83% (5/6, 3 PRs, 2 VGPRs), with 4/5 responders being triple refractory and 1 DLT of grade 3 CRS in this group. Across the study, responses included 4 stringent CRs (3 MRD-negative, 1 not yet tested), 1 MRD-negative CR, 6 VGPRs, and 6 PRs (Table). Median (Q1, Q3) time to response was 1.0 (1.0, 1.9) month, time to best response was 2.8 (1.0, 3.7) months, and response duration was 3.8 (1.9, 7.4) months, with maximum duration of 23 months; responses were ongoing at last assessment in 14/17 patients (Figure). MRD was tested in 4 patients (3 sCR, 1 CR) and all were negative (3 by NGS, 1 by flow); MRD negativity was ongoing at last observations up to 20 months later. AMG 701 exhibited a favorable PK profile in its target patient population of RR MM, with AMG 701 exposures increasing in a dose-related manner. Patient baseline sBCMA levels were identified as a determinant of AMG 701 free drug exposures; at higher doses, encouraging preliminary responses were seen even at the higher end of baseline sBCMA values. Summary: In this FIH study with ongoing dose escalation, AMG 701, an anti-BCMA BiTE® molecule, demonstrated a manageable safety profile, encouraging activity, and a favorable PK profile in patients with heavily pre-treated RR MM, supporting further evaluation of AMG 701. Disclosures Harrison: Janssen: Honoraria; Novartis: Consultancy, Honoraria, Patents & Royalties: wrt panobinostat; GSK: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Consultancy, Honoraria; CRISPR Therapeutics: Consultancy, Honoraria; Haemalogix: Consultancy; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen-Cilag: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; F. Hoffmann-La Roche: Consultancy, Honoraria. Minnema:Amgen: Honoraria; Servier: Honoraria; Gilead: Honoraria; Celgene Corporation: Honoraria, Research Funding; Janssen Cilag: Honoraria. Lee:Celgene: Consultancy, Research Funding; Genentech: Consultancy; GlaxoSmithKline: Consultancy, Research Funding; Genentech: Consultancy; Regeneron: Research Funding; Takeda: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Sanofi: Consultancy; Daiichi Sankyo: Research Funding; Amgen: Consultancy, Research Funding. Spencer:AbbVie: Consultancy, Honoraria, Research Funding; Roche: Honoraria; Takeda: Honoraria, Research Funding, Speakers Bureau; Sanofi: Consultancy, Honoraria; Amgen: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding, Speakers Bureau; Secura Bio: Consultancy, Honoraria; Servier: Consultancy, Honoraria, Research Funding; HaemaLogiX: Consultancy, Honoraria, Research Funding; BMS: Consultancy, Honoraria, Research Funding, Speakers Bureau; Pfizer: Consultancy, Honoraria; Pharmamar: Research Funding. Kapoor:Cellectar: Consultancy; Amgen: Research Funding; Janssen: Research Funding; Sanofi: Consultancy, Research Funding; Takeda: Honoraria, Research Funding; GlaxoSmithKline: Research Funding; Celgene: Honoraria. Madduri:Takeda: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Foundation Medicine: Consultancy, Honoraria; GSK: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Speaking Engagement, Speakers Bureau; Kinevant: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Speaking Engagement, Speakers Bureau; Legend: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Speaking Engagement, Speakers Bureau; Celgene: Consultancy, Honoraria. Larsen:Janssen Oncology: 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. Ailawadhi:Cellectar: Research Funding; BMS: Research Funding; Medimmune: Research Funding; Amgen: Research Funding; Takeda: Honoraria; Janssen: Research Funding; Pharmacyclics: Research Funding; Celgene: Honoraria; Phosplatin: Research Funding. Kaufman:Amgen: Consultancy, Honoraria; Incyte: Consultancy, Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Consultancy, Honoraria; AbbVie: Consultancy; Celgene: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Tecnopharma: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees; TG Therapeutics: Consultancy, Membership on an entity's Board of Directors or advisory committees; Sanofi/Genyzme: Consultancy, Honoraria. Raab:Takeda: Membership on an entity's Board of Directors or advisory committees; Heidelberg Pharma: Research Funding; Amgen: Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Membership on an entity's Board of Directors or advisory committees; Janssen: 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; Novartis: Membership on an entity's Board of Directors or advisory committees; Sanofi: Membership on an entity's Board of Directors or advisory committees, Research Funding. Hari:BMS: Consultancy; Amgen: Consultancy; GSK: Consultancy; Janssen: Consultancy; Incyte Corporation: Consultancy; Takeda: Consultancy. Iida:AbbVie: Research Funding; Merck Sharpe Dohme: Research Funding; Kyowa Kirin: Research Funding; Chugai: Research Funding; Sanofi: Honoraria, Research Funding; Bristol-Myers Squibb: Honoraria, Research Funding; Daiichi Sankyo: Honoraria, Research Funding; Takeda: Honoraria, Research Funding; Ono: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Janssen: Honoraria, Research Funding. Davies:Celgene/BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncopeptides: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Roche: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Adaptive Biotech: Honoraria; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees. Lesley:Amgen Inc.: Current Employment, Current equity holder in publicly-traded company. Upreti:Amgen Inc.: Current Employment, Current equity holder in publicly-traded company. Yang:Amgen Inc.: Current Employment, Current equity holder in publicly-traded company. Sharma:Amgen Inc.: Current Employment, Current equity holder in publicly-traded company. Minella:Amgen Inc.: Current equity holder in publicly-traded company, Ended employment in the past 24 months; Beam Therapeutics Inc.: Current Employment, Current equity holder in publicly-traded company. Lentzsch:Mesoblast: Divested equity in a private or publicly-traded company in the past 24 months; Janssen: Consultancy; Caelum Biosciences: Current equity holder in private company, Membership on an entity's Board of Directors or advisory committees; Magenta: Current equity holder in private company; Sanofi: Research Funding; Karyopharm: Research Funding; Celularity: Consultancy; Sorrento: Consultancy. OffLabel Disclosure: AMG 701, a half-life extended BiTE® (bispecific T-cell engager) molecule is an investigational agent for multiple myeloma.

Introduction: Multiple myeloma (MM) is a genetically complex and clinically heterogeneous disease. Disease biology and phenotype is heavily influenced by the tumor microenvironment and the interaction between the immune milieu and malignant plasma cell population. Understanding the molecular profile of tumor along with the immune ecosystem can provide insights into key pathways that are important in disease pathobiology. Therefore, in this study, we have used single-cell RNA-Seq (scRNA-Seq) to compare the detailed maps of the bone marrow microenvironment of patients with rapid progressing disease (PFS < 18 months) with those whose disease had not progressed at the time of analysis (PFS < 4 years) Methods: MM patients (n=18) with rapid and no progression were identified from the Multiple Myeloma Research Foundation (MMRF) CoMMpass study, a longitudinal genomic study of patients with newly diagnosed, active multiple myeloma (NCT01454297). To generate a robust scRNA-Seq profile with minimal false positive, we profiled multiple technical replicates/aliquots of viably frozen CD138-negative bone marrow cells from each patient at three medical centers/universities (Beth Israel Deaconess Medical Center, Boston, Washington University in St. Louis and Mount Sinai School of Medicine, NYC using droplet-based single-cell barcoding technique. After batch correction and normalization, the cellular clusters were identified using principal component analysis and Uniform Manifold Approximation and Projection (UMAP) approach (Becht et al, 2018). Differential expression, pathways and systems biology analysis between rapid and non-progressors revealed differences for specific cell clusters (Panigrahy, Gartung et al. 2019). To determine association of plasma cell overexpressed genes with survival in CoMMpass study, survival analysis was performed using Kaplan-Meier (K-M) approach. Results: In this study, comparative analysis was performed of the bone marrow microenvironment of patients with aggressive and indolent disease by generating single-cell profiles of ~102,207 cells from 48 samples of 18 patients with MM. The UMAP approach identified multiple transcriptionally diverse clusters of plasma (CD138+), immune (PTPRC+) and erythroid (GYPA1/2+) cells (Fig 1a). Interestingly, the analysis identified CD138+ plasma/tumors cells clusters in a subset of samples from patients with rapid -progression and these clusters depicted a high degree of inter-patient heterogeneity (Fig 1a). Further characterization of plasma tumor cells depicted significant activation (Z score >2 and P-value <.001) of pathway related to "Unfolded protein response", epithelial-mesenchymal transition (EMT), and "p38 MAPK Signaling". These rapid progressions associated with plasma cells overexpressing multiple genes (e.g., Hazard ratio (HR) CCL3=1.9 95% CI= (1.5-3.9) log-rank P=0.0004, HSPA5 HR=1.4 (1-2.6), P=0.03) that are associated with poor outcome in multiple myeloma based CoMMpass data. The bone marrow microenvironment cells formed 22 clusters, comprising of cells from myeloid, macrophages, T cells, B cells, dendritic cells, Natural Killer T (NKT) cells, and erythroid lineages. The Non-progressive patients depicted enrichment of GZMB+ T and NKT cells with overexpression of genes associated with "Natural Killer Cell Signaling", "CD28 Signaling in T Helper Cells", "NF-kB Signaling" and "Th17 Activation Pathway" (Fig1b, c). Systems biology analysis depicted significant activation of TNF, STAT4, and NFATC2 regulatory signatures in NKT cells. The analysis also observed enrichment of macrophages, several types of monocytes, and myeloid cells in the samples from patients with non-progressive disease (Fig 1d). The myeloid/monocytes cluster depicted significant activation of multiple metabolic (i.e., Glycolysis, Gluconeogenesis) and immune response (i.e. IL8) pathways (Fig 1e). In summary, this multi-site study provides insights into potentially significant differences in the transcriptomic landscape of multiple myeloma patients with rapid and non-progression of disease. The non-progressive patients depict significant enrichment of activated T cells and myeloid lineage populations, suggesting their role toward better outcomes. These findings will be further expanded by ongoing single cell analyses of the CoMMpass tissue bank under the MMRF Immune Atlas initiative. Figure 1 Disclosures Bhasin: Canomiiks Inc: Current equity holder in private company, Other: Co-Founder. Dhodapkar:Roche/Genentech: Membership on an entity's Board of Directors or advisory committees, Other; Amgen: Membership on an entity's Board of Directors or advisory committees, Other; Celgene/BMS: Membership on an entity's Board of Directors or advisory committees, Other; Janssen: Membership on an entity's Board of Directors or advisory committees, Other; Kite: Membership on an entity's Board of Directors or advisory committees, Other; Lava Therapeutics: Membership on an entity's Board of Directors or advisory committees, Other. Kumar:Merck: Consultancy, Research Funding; Adaptive Biotechnologies: Consultancy; Genecentrix: Consultancy; Tenebio: Other, Research Funding; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Kite Pharma: Consultancy, Research Funding; Novartis: Research Funding; Sanofi: Research Funding; MedImmune: Research Funding; Karyopharm: Consultancy; BMS: Consultancy, Research Funding; Cellectar: Other; Carsgen: Other, Research Funding; Dr. Reddy's Laboratories: Honoraria; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding.

Compared with traditional bulk sequencing technologies, single-cell technologies have advantages to evaluate cellular heterogeneity and investigate the evolution of cellular subpopulations from the tumor and microenvironment. Application of single-cell sequencing in Multiple Myeloma (MM) is especially beneficial given MM is a highly heterogeneous disease with uncontrolled clonal expansion of plasma cells. Single-cell RNA sequencing (scRNA-seq) has been previously utilized to understand this hematopoietic malignancy in both tumor and immune populations in MM (Ledergor G. et al., 2018, Zavidij, O. et al., 2020). Mass cytometry (CyTOF) has also been used to identify the expansion of novel memory B cells in MM. (Hansmann, L. et al., 2015). Among the various single cell techniques, cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) is a multimodal approach with simultaneous quantification of single-cell transcriptomes and surface proteins. Since these three single-cell approaches enable the identification of cell types, cell states and characterization of cellular heterogeneity at transcriptomic and/or protein levels, understanding the concordance of the measurements among these three modalities is of great interest. We applied scRNA-seq, CyTOF and CITE-seq on four baseline samples of CD138-negative 'immune cell' fractions from patients enrolled in the MMRF CoMMpass study (NCT01454297). Two subjects were fast progressors (PFS < 18 months) and two subjects were non-progressors (PFS not reached). With multi-center collaboration coordinated by Multiple Myeloma Research Foundation (MMRF), each sample was subject to scRNA-seq and CyTOF by 3 independent centers. All sites received aliquots of the same sample. On average, 1,060 immune cells were detected in each sample using scRNA-seq and >64K CD45+ cells were detected using CyTOF. CITE-seq was performed in one center and 4,805 CD138-negative immune cells were identified on average. To compare cell type abundance between scRNA-seq, CyTOF and CITE-seq, we calculated the cell subset frequency of each immune population relative to the CD45+ populations. Overall, all three approaches were concordant while there is a stronger concordance between scRNA-seq and CyTOF. Cell type abundance is especially consistent for B cells, monocytes/macrophages, and plasmacytoid dendritic cells (pDC) among the 3 methods. For the same patient of interest, natural killer (NK) cell frequency was detected at the lowest level in CyTOF relative to scRNA and CITE-seq. The T cell population showed the highest discrepancy among techniques, with highest abundance in scRNA-seq followed by CyTOF and lowest abundance in CITE-seq. Interestingly, CITE-seq detected far less CD4 T cells compared to the other two techniques while CD8 T cell frequency did not show drastic differences. In addition to cell type abundance, we further examined the concordance of expression of cell type signature genes between scRNA-seq and CyTOF. Overall, expression between RNA-level and protein-level is positively correlated with typical cell type markers highly expressed in both techniques, especially in the following cell populations: CD8+ T cells (CD3, CD8), NK cells (CD56, GranzymeB/GZMB, NKG2A/KLRC1), B cells (CD19, CD38), Monocytes (CD14, CD11c/ITGAX, CD33). To note, although the concordance in CD4+ T cells is generally good, we found the expression of CD4 is higher in CyTOF compared to scRNA-seq whereas CD127/IL7R tends to be overexpressed in scRNA-seq. This could explain why IL7R is often identified as a differentially expressed gene (DEG) in CD4+ T cell population while CD4 is barely seen in DEG list in scRNA-seq analysis. It is also interesting to notice that the expression of most NK cell markers has strong concordance between scRNA-seq and CyTOF except NKG2D/KLRK1, which has much higher expression in CyTOF relative to scRNA-seq. Our preliminary results suggested good concordance of immune cell type abundance identified in CyTOF, scRNA-seq and CITE-seq as well as concordant expression of some canonical cell type markers between RNA level and protein level. This work provides the field with reference data sets and shows more detailed examination of NK and T cell subsets is needed when handling single cell sequencing with different modalities. Disclosures Dhodapkar: Roche/Genentech: Membership on an entity's Board of Directors or advisory committees, Other; Lava Therapeutics: Membership on an entity's Board of Directors or advisory committees, Other; Kite: Membership on an entity's Board of Directors or advisory committees, Other; Janssen: Membership on an entity's Board of Directors or advisory committees, Other; Celgene/BMS: Membership on an entity's Board of Directors or advisory committees, Other; Amgen: Membership on an entity's Board of Directors or advisory committees, Other. Kumar:MedImmune: Research Funding; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Carsgen: Other, Research Funding; Merck: Consultancy, Research Funding; Adaptive Biotechnologies: Consultancy; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Kite Pharma: Consultancy, Research Funding; Novartis: Research Funding; Sanofi: Research Funding; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Tenebio: Other, Research Funding; Karyopharm: Consultancy; BMS: Consultancy, Research Funding; Genecentrix: Consultancy; Cellectar: Other; Dr. Reddy's Laboratories: Honoraria. Gnjatic:Neon Therapeutics: Consultancy, Membership on an entity's Board of Directors or advisory committees; OncoMed: Consultancy, Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Research Funding; Genentech: Research Funding; Immune Design: Research Funding; Agenus: Research Funding; Janssen R&D: Research Funding; Pfizer: Research Funding; Takeda: Research Funding; Regeneron: Research Funding; Merck: Consultancy, Membership on an entity's Board of Directors or advisory committees. Bhasin:Canomiiks Inc: Current equity holder in private company, Other: Co-Founder.

BackgroundMultiple myeloma (MM) with the translocation t(11;14) may have inferior outcomes in comparison with other standard‐risk MM, and it has been suggested to portend a worse prognosis in African Americans in comparison with Whites. This study used the Center for International Blood and Marrow Transplant Research (CIBMTR) database to examine the impact of t(11;14) on the clinical outcomes of patients with MM of African American and White descent.MethodsThis study evaluated 3538 patients who underwent autologous hematopoietic cell transplantation (autoHCT) for MM from 2008 to 2016 and were reported to the CIBMTR. Patients were analyzed in 4 groups: African Americans with t(11;14) (n = 117), African Americans without t(11;14) (n = 968), Whites with t(11;14) (n = 266), and Whites without t(11;14) (n = 2187).ResultsAfrican Americans with t(11;14) were younger, had lower Karnofsky scores, and had more advanced stage MM with a higher Hematopoietic Cell Transplantation–Comorbidity Index (HCT‐CI). Fewer African Americans with t(11;14) (21%) had a coexistent high‐risk marker in comparison with Whites with t(11;14) (27%). In a multivariate analysis, race and t(11;14) had no association with progression‐free survival. However, overall survival was superior among African Americans with t(11;14) in comparison with Whites with t(11;14) (hazard ratio, 0.53; 95% confidence interval, 0.30‐0.93; P = .03). Survival was also associated with female sex, stage, time from diagnosis to transplant, a low HCT‐CI, and receipt of maintenance.ConclusionsRace may have a differential impact on the survival of patients with t(11;14) MM who undergo autoHCT and needs to be further studied.

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.

8537 Background: Carfilzomib (CFZ) is a proteasome inhibitor, active against hematologic malignancies. Preclinically, CFZ overcomes bortezomib (BTZ) resistance in multiple tumors, including myeloma (MM). PX-171–004 is an ongoing Phase II study evaluating safety and efficacy of CFZ in MM patients with relapsed disease after 1–3 prior therapies. Overall Response Rate (ORR) of 35.5% for all subjects was previously reported (ASH 2008); updated data are now available. Methods: Patients were divided into two cohorts: BTZ-naïve and BTZ-exposed. CFZ 20 mg/m2 was administered Days 1, 2, 8, 9, 15 and 16 in a 28-day cycle, for up to 12 cycles. Dexamethasone 4 mg po was administered prior to each dose in Cycle 1. The primary endpoint was ORR, defined as Partial Response (PR) or better. Secondary endpoints included Duration Of Response (DOR) and Time To Progression (TTP). Results: 31 patients were enrolled; 14 (45%) BTZ-naïve and 17 (55%) BTZ-exposed. Of the BTZ-exposed cohort, 2 subjects received BTZ exclusively as a single agent, 6 had BTZ in a chemotherapy combination, and 9 received BTZ in a transplant regime. Overall, 23 (74%) subjects had > 1 prior therapy and 27 (87%) received transplant. In BTZ-naïve patients, CFZ achieved an ORR of 57%; median DOR of 8.6 mos (range >1.9 to >9.7 mos). To date, 7 patients (50%) remain progression free and 3 patients have completed 12 cycles. The median follow-up was 10 mos and the median TTP has not been reached. For the BTZ- exposed group, CFZ achieved an ORR of 18%; median DOR not yet reached (>8.5 mos) (range >1 d to >8.5 mos). 7 patients (41%) are progression free and 3 patients have completed 12 cycles. Median follow-up and TTP were 9.2 and 8.9 mos, respectively. Conclusions: These preliminary results demonstrate that single-agent CFZ is tolerable for at least 1 yr and achieves sustained responses in relapsed MM. Prior BTZ mono/combination therapy does not preclude durable response with CFZ. These data support continuing evaluation of CFZ in the treatment of relapsed MM. [Table: see text] [Table: see text]

8504 Background: CFZ is a novel proteasome inhibitor of the epoxyketone class that exhibits a high level of proteasome selectivityand demonstrates antitumor activity in bortezomib (BTZ)-resistant MM pts in phase I studies. Methods: PX-171–003-A0 was an open-label, multicenter study that enrolled MM pts who relapsed from >2 prior therapies, failed BTZ and at least 1 immunomodulatory agent [thalidomide (THAL) or lenalidomide (LEN)], and were refractory to last treatment [progressing on or within 60 d of last therapy or <25% response to last therapy]. Pts received CFZ 20 mg/m2 IV d 1, 2, 8, 9, 15 and 16 every 28 d for up to 12 cycles (C). Clinical benefit response (CBR) was defined as MR or better. Results: 46 pts were enrolled, including 78% with progression on or within 60 d of last therapy and 22% with no response to last therapy. 39 pts completed at least 1 C of CFZ, had measurable M-protein, and were evaluable for response. Median prior therapies was 5 (range 2–15). 100% of pts received prior BTZ, 91% prior THAL, 89% prior LEN, and 83% prior stem cell transplant (SCT) and all had failed combinations including anthracyclines (80%) and/or alkylating agents (94%). Pts received a median of 3 C (range 1–12); 13 pts completed ≥6 C. CBR was 26% (10/39 eval pts), including 5 pts achieving PR and 5 pts achieving MR. 5 BTZ-refractory pts achieved MR or PR. Median TTP was 6.2 mo, the median DOR for the MR + PR was 7.4 mo. 8/10 pts achieved response during C1. 16 additional pts achieved SD for at least 6 wks. The most common adverse events were fatigue, anemia, thrombocytopenia, nausea, upper respiratory infection, increased creatinine and diarrhea. Peripheral neuropathy occured in < 10% of pts with 1 Gr 3 in a pt with pre-existing Gr 2. Conclusions: Single-agent CFZ achieved a TTP of > 6 mo in relapsed and refractory MM pts who failed available therapies. 26% of patients had at least an MR and median duration of >7 mo with this steroid- and anthracycline-sparing regimen. CFZ toxicities were manageable and importantly, exacerbation of pre-existing PN was rare. The study has been expanded to enroll an additional 250 pts in this unmet medical need population at an escalated dose, and treatment has been extended beyond a year. [Table: see text]

Outcomes in multiple myeloma (MM) have improved dramatically in the last two decades with the advent of novel therapies including immunomodulatory agents (IMiDs), proteasome inhibitors and monoclonal antibodies. In recent years, immunotherapy for the treatment of MM has advanced rapidly, with the approval of new targeted agents and monoclonal antibodies directed against myeloma cell-surface antigens, as well as maturing data from late stage trials of chimeric antigen receptor (CAR) T cells. Therapies that engage the immune system to treat myeloma offer significant clinical benefits with durable responses and manageable toxicity profiles, however, the appropriate use of these immunotherapy agents can present unique challenges for practicing physicians. Therefore, the Society for Immunotherapy of Cancer convened an expert panel, which met to consider the current role of approved and emerging immunotherapy agents in MM and provide guidance to the oncology community by developing consensus recommendations. As immunotherapy evolves as a therapeutic option for the treatment of MM, these guidelines will be updated.

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.