Avigan, David

As part of the Multiple Myeloma Research Foundation (MMRF) immune atlas pilot project, we compared immune cells of multiple myeloma bone marrow samples from 18 patients assessed by single-cell RNA sequencing (scRNA-seq), mass cytometry (CyTOF), and cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) to understand the concordance of measurements among single-cell techniques. Cell type abundances are relatively consistent across the three approaches, while variations are observed in T cells, macrophages, and monocytes. Concordance and correlation analysis of cell type marker gene expression across different modalities highlighted the importance of choosing cell type marker genes best suited to particular modalities. By integrating data from these three assays, we found International Staging System stage 3 patients exhibited decreased CD4+ T/CD8+ T cells ratio. Moreover, we observed upregulation of RAC2 and PSMB9, in natural killer cells of fast progressors compared with those of nonprogressors, as revealed by both scRNA-seq and CITE-seq RNA measurement. This detailed examination of the immune microenvironment in multiple myeloma using multiple single-cell technologies revealed markers associated with multiple myeloma rapid progression which will be further characterized by the full-scale immune atlas project. Significance: scRNA-seq, CyTOF, and CITE-seq are increasingly used for evaluating cellular heterogeneity. Understanding their concordances is of great interest. To date, this study is the most comprehensive examination of the measurement of the immune microenvironment in multiple myeloma using the three techniques. Moreover, we identified markers predicted to be significantly associated with multiple myeloma rapid progression.

Abstract Multiple Myeloma (MM) is a hematologic malignancy marked by uncontrolled clonal expansion of plasma cells. Previous research has examined single-cell transcriptome profiles of Monoclonal gammopathy of undetermined significance (MGUS) and MM tumor microenvironment (TME) and found that natural killer (NK) cell abundance is elevated in the early stages and correlated with altered chemokine receptor expression. This study suggested the critical role of immune cells on myeloma progression from asymptomatic MGUS to symptomatic MM. Up to date, however, there are no published studies comprehensively comparing tumor and immune populations differences between MM NON-progressors (NPs) and FAST-progressors (FPs) and investigating how clonal plasma cells affect disease progression in a large cohort. Therefore, understanding how tumor and immune cells influence disease progression within symptomatic MM is of great interest.Here, we subjected CD138-negative Bone Marrow Mononuclear cells (BMMC) samples from 418 MM patients to scRNA-seq. From MMRF CoMMpass study (NCT01454297), we also have whole exome sequencing (WES) and bulk RNA-seq from CD138-positive fraction of BMMC samples. Based on time to progressive disease (TTPD), we classified patients into 2 categories. Patients with TTPD less than 18 months were classified as FAST-progressors (FPs), whereas patients with TTPD more than 5 years were classified as NON-progressors (NPs). By analyzing patient genomic alterations and its association with progression, we found that there was a significant association of slow MM progression with t(11;14) (p = 0.048), consistent with previous study. In our preliminary analysis, we profiled 83 CD138-sorted MM bone marrow samples using scRNA-seq. Interestingly, we found plasma cells from samples with the same genetic alterations tend to cluster together, highlighting the important role of genetic drivers in transcriptome profiles of plasma cells. Moreover, integrated analysis of bone marrow samples from 83 MM patients and 4 healthy donors revealed an atypical naïve-B cell subset with enrichment of cells from fast-progressors and partial expression of MS4A1. Differentially expressed genes for this naïve-B cell subset includes KLF9, BCL2L11, JOSD1, and IRS2, etc. Overall, as part of MMRF immune profiling research, this study will help to interrogate how genetic alterations and disease progression interplay MM tumor and TME and provide a sufficiently broad and valuable dataset for systematically characterizing MM at single-cell resolution. Hopefully, this study could identify novel targets for MM immunotherapies, and ultimately identify patients with high risk of fast progression for early intervention in the clinic. Citation Format: Lijun Yao, Tianjiao Wang, Kazuhiro Sato, Reyka Jayasinghe, I-Ling Chiang, Darwin D'souza, William Pilcher, Edgar Gonzalez-Kozlova, Yered Pita-Juarez, Taxiarchis Kourelis, Deon Bryant Doxie, Beena Thomas, Brian Lee, Swati Sharma Bhasin, Upadhyaya Bhaskar, Mark Fiala, Julie Fortier, Travis Dawson, John Leech, Shaji Kumar, Hearn Cho, Seunghee Kim-Schulze, Bee Raj, Stephen Oh, the MMRF Immune Profiling Research Team, John Dipersio, Ravi Vij, Adeeb Rahman, Ionnis Vlachos, Shaadi Mehr, Mark Hamilton, Daniel Auclair, Surendra Dasari, David Avigan, Madhav Dhodapkar, Sacha Gnjatic, Manoj Bhasin, Li Ding. Single-cell transcriptome profiling of multiple myeloma bone marrow samples suggests that disease progression interplays with tumor and tumor microenvironment in The MMRF CoMMpass Study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1729.

PURPOSE CARTITUDE-1, a phase Ib/II study evaluating the safety and efficacy of ciltacabtagene autoleucel (cilta-cel) in heavily pretreated patients with relapsed/refractory multiple myeloma, yielded early, deep, and durable responses at 12 months. Here, we present updated results 2 years after last patient in (median follow-up [MFU] approximately 28 months), including analyses of high-risk patient subgroups. METHODS Eligible patients had relapsed/refractory multiple myeloma, had received ≥ 3 prior lines of therapy or were double refractory to a proteasome inhibitor and immunomodulatory drug and had received prior proteasome inhibitor, immunomodulatory drug, and anti-CD38 therapy. Patients received a single cilta-cel infusion 5-7 days after lymphodepletion. Responses were assessed by an independent review committee. RESULTS At a MFU of 27.7 months (N = 97), the overall response rate was 97.9% (95% CI, 92.7 to 99.7); 82.5% (95% CI, 73.4 to 89.4) of patients achieved a stringent complete response. Median duration of response was not estimable. Median progression-free survival (PFS) and overall survival (OS) were not reached; 27-month PFS and OS rates were 54.9% (95% CI, 44.0 to 64.6) and 70.4% (95% CI, 60.1 to 78.6), respectively. Overall response rates were high across all subgroups (95.1%-100%). Duration of response, PFS, and/or OS were shorter in patients with high-risk cytogenetics, International Staging System stage III, high tumor burden, or plasmacytomas. The safety profile was manageable with no new cilta-cel–related cytokine release syndrome and one new case of parkinsonism (day 914 after cilta-cel) since the last report. CONCLUSION At approximately 28 months MFU, patients treated with cilta-cel maintained deep and durable responses, observed in both standard and high-risk subgroups. The risk/benefit profile of cilta-cel remained favorable with longer follow-up.

Abstract Introduction: Multiple myeloma (MM) is a complex hematological malignancy with the heterogenous immune bone marrow (BM) environment contributing to tumor growth, drug resistance, and immune escape. T-Cells play a critical role in the clearance of malignant plasma cells from the tumor environment. However, T-Cells in multiple myeloma demonstrate impaired cytotoxicity, proliferation, and cytokine production due to the activation of immune inhibitory receptors from ligands produced by the myeloma cells. In this study, we investigate the behavior of T-Cells in MM patients by using single-cell RNA-Seq (scRNA-Seq) to compare the transcriptomic profiles of BM T-Cells of patients with rapid progressing (FP; PFS < 18mo) and non-progressing (NP; PFS > 4yrs) disease. Methods: Newly diagnosed MM patients (n=18) from the Multiple Myeloma Research Foundation (MMRF) CoMMpass study (NCT01454297) were identified as either rapid progressors or non-progressors based on their progression free survival since diagnosis. To capture transcriptomic data, scRNA-Seq was performed on 48 aliquots of frozen CD138-negative BM cells at three medical centers/universities (Beth Israel Deaconess Medical Center, Boston, Washington University in St. Louis, and Mount Sinai School of Medicine, NYC). Samples were collected at diagnosis prior to treatment. Surface marker expression for 29 proteins was captured for at least one sample per patient using CITE-Seq. After integration and batch correction, clustering was performed to identify cells of T or NK lineage. Uniform Manifold Approximation and Projection (UMAP) and differential expression were used to identify T-Lymphoid subtypes, and differences in NP and FP samples. Results: In this study, single cell transcriptomic profiles were identified for ~102,207 cells from 48 samples of 18 MM patients. 40,328 T (CD3+) and NK (CD3-, NKG7+) cells were isolated, and subclustered for further analysis (Fig 1A). Using differentially expressed markers for each cluster, the T-Lymphoid subset was refined into seven subtypes, consisting of various CD4+ T-Cells, CD8+ T-Cells, and NK cells (Fig 1B). The CD8+ cells were divided into three distinct phenotypes, namely a GZMK-, GZMB- CD8+ T-Cell cluster, a GZMK+ CD8+ Exhausted T-Cell cluster enriched in TIGIT and multiple chemokines (CCL3, CCL4, XCL2), and a GZMB+ NkT cluster enriched in cytolytic markers (PRF1, GNLY, NKG7) (Fig 1C). Differential expression between NP and FP samples in this CD8+ subset showed enrichment of the NkT cytotoxic markers in NP samples, while FP samples were enriched in the CD8+ Exhausted chemokine markers (Fig 1D). Furthermore, the proportion of CD8+ Exhausted T-Cells was enriched in FP samples (p.val < 0.05) (Fig 1E). Exhaustion markers were measured through both RNA and surface marker levels. In RNA, TIGIT was uniquely associated with the FP-enriched CD8+ Exhausted T-Cell cluster, and CD160 was uniquely expressed in FP samples (Fig 1F). CITE-Seq surface marker expression confirms enrichment of both TIGIT and PD1 in the CD8+ Exhausted T-Cell cluster, and along with more exhaustion in FP samples (p.val < 0.01). Conclusion: In this study, we have identified significant differences in T-Cell activity in patients with non-progressing and rapid-progressing multiple myeloma. T-Cells in rapid progressing patients appear to be in a suppressed state, with low cytolytic activity and enriched exhaustion markers. This GZMK+ T-Cell population shows strong similarities with an aging-associated subtype of effector memory T-Cells found to be enriched in older populations (Mogilenko et al, Immunity 54, 2021). These findings will be further validated in an expanded study, consisting both of a larger number of samples, and multiple samples at different timepoints from the same patient. Figure 1 Figure 1. Disclosures Jayasinghe: MMRF: Consultancy; WUGEN: Consultancy. Vij: BMS: Research Funding; Takeda: Honoraria, Research Funding; Sanofi: Honoraria, Research Funding; BMS: Honoraria; GSK: Honoraria; Oncopeptides: Honoraria; Karyopharm: Honoraria; CareDx: Honoraria; Legend: Honoraria; Biegene: Honoraria; Adaptive: Honoraria; Harpoon: Honoraria. Kumar: Carsgen: Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Beigene: Consultancy; Bluebird Bio: Consultancy; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Tenebio: Research Funding; Oncopeptides: Consultancy; Antengene: Consultancy, Honoraria; Roche-Genentech: Consultancy, Research Funding; Merck: Research Funding; Astra-Zeneca: Consultancy, 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: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding; Amgen: Consultancy, Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Consultancy, Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding. Avigan: Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Pharmacyclics: Research Funding; Kite Pharma: Consultancy, Research Funding; Juno: Membership on an entity's Board of Directors or advisory committees; Partner Tx: Membership on an entity's Board of Directors or advisory committees; Karyopharm: 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; Aviv MedTech Ltd: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees; Legend Biotech: Membership on an entity's Board of Directors or advisory committees; Chugai: Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy; Parexcel: Consultancy; Takeda: Consultancy; Sanofi: Consultancy.

Abstract Multiple Myeloma (MM) is the second most common hematologic malignancy, marked by uncontrolled clonal expansion of plasma cells. MM genome is complex and heterogeneous, with a high frequency of structural variants (SVs) and copy-number abnormalities (CNAs). Single-cell sequencing technologies offer advantages over traditional bulk methods in cancer genomics research for evaluating cellular heterogeneity and investigating evolution of cellular subpopulations within the tumor. Thus, there is an impetus to translate the growing understanding of the genomic landscape of MM into dissecting the tumor heterogeneity using scRNA-seq. So far, there are no reported studies systematically comparing tumor and immune populations differences between MM NON-progressors (NPs) and RAPID-progressor (RPs) and investigating how clonal plasma cells contribute to progression in a large cohort. In addition, the bone marrow microenvironment plays an important role in the evolution of premalignant MM and MM progression. A previous study of single-cell transcriptomics analysis of Monoclonal gammopathy of undetermined significance (MGUS) and MM tumor microenvironment (TME) revealed that natural killer (NK) cell abundance is frequently increased in the early stages and associated with altered chemokine receptor expression. This study shed the light on the role of immune cells on disease progression from asymptomatic MGUS to symptomatic MM. However to date, how immune cells influence disease progression within symptomatic MM is still unclear. Here, we subjected 344 CD138-negative Bone Marrow Mononuclear cells (BMMC) samples to scRNA-seq. To control for the first line therapy, 272 patients were treated with RVD and Autologous stem cell transplant (ASCT) and were stratified into 3 groups based on progression: 200 NON-progressors (NPs) (PFS> 5 years), 7 Intermediate Progressors (IPs, PFS 2-4 years) and 38 RAPID-progressors (RPs) (PFS<=18 months). In addition, there are 72 subjects treated with RVD but without ASCT, including 34 NPs, 2 IPs and 36 RPs. From MMRF CoMMpass study (NCT01454297), we also have whole exome sequencing (WES) and bulk RNA-seq from CD138-positive fraction of BMMC samples. Our preliminary analysis of scRNA-seq of 6 samples treated by the same first-line therapies (RVD but without ASCT) revealed that plasma cells (PCs) from two patients (MMRF2550 and MMRF2562) with chromosome 13q deletion clustered together, whereas PCs from a patient (MMRF2187) with t(8;14) Myc translocation formed a distinct cluster. Interestingly, PCs from a patient (MMRF2271) with both chromosome 13q deletion and t(8;14) formed another independent cluster. These observations highlight the important role of genetic drivers in transcriptome profiles of plasma cells. In addition, we further investigated how progression features correlate with the immune microenvironment and identified differentially expressed genes between NK cells from RPs versus those from NPs, which could potentially serve as MM progression markers. Interestingly, several cytotoxicity genes are significantly upregulated in FPs, such as GZMB and KLRB1 (log Fold Change=1.44, and 8.41 respectively). Overall, our preliminary results provide a small glimpse of the interconnected nature of driver genetic alterations and progression features in MM tumor and TME. This study will provide a sufficiently broad, deep, and diverse vast dataset for accurately characterizing MM at single-cell resolution to help interrogate how genetic alterations and disease progression interplay MM tumor and TME. We hope this study could identify novel candidate targets for therapeutic approaches, and ultimately stratify patients by risk of progression for early intervention in the clinic. Disclosures Kumar: Roche-Genentech: Consultancy, Research Funding; Merck: Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Research Funding; Novartis: Research Funding; Abbvie: 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; Beigene: Consultancy; Carsgen: Research Funding; Bluebird Bio: Consultancy; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncopeptides: Consultancy; Tenebio: Research Funding; BMS: Consultancy, Research Funding; Antengene: Consultancy, Honoraria; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding. Oh: Abbvie: Membership on an entity's Board of Directors or advisory committees; Blueprint Medicines: Membership on an entity's Board of Directors or advisory committees; Celgene Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees; Constellation: Membership on an entity's Board of Directors or advisory committees; CTI Biopharma: Membership on an entity's Board of Directors or advisory committees; Disc Medicine: Membership on an entity's Board of Directors or advisory committees; Geron: Membership on an entity's Board of Directors or advisory committees; Incyte: Membership on an entity's Board of Directors or advisory committees; Kartos Therapeutics: Membership on an entity's Board of Directors or advisory committees; PharamaEssentia: Membership on an entity's Board of Directors or advisory committees; Sierra Oncology: Membership on an entity's Board of Directors or advisory committees. Vij: BMS: Research Funding; Takeda: Honoraria, Research Funding; Sanofi: Honoraria, Research Funding; BMS: Honoraria; GSK: Honoraria; Oncopeptides: Honoraria; Karyopharm: Honoraria; CareDx: Honoraria; Legend: Honoraria; Biegene: Honoraria; Adaptive: Honoraria; Harpoon: Honoraria. Avigan: Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Pharmacyclics: Research Funding; Kite Pharma: Consultancy, Research Funding; Juno: Membership on an entity's Board of Directors or advisory committees; Partner Tx: Membership on an entity's Board of Directors or advisory committees; Karyopharm: 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; Aviv MedTech Ltd: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees; Legend Biotech: Membership on an entity's Board of Directors or advisory committees; Chugai: Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy; Parexcel: Consultancy; Takeda: Consultancy; Sanofi: Consultancy.

Abstract Introduction: Ciltacabtagene autoleucel (cilta-cel), a chimeric antigen receptor T (CAR-T) cell therapy with 2 B-cell maturation antigen (BCMA) targeting single-domain antibodies, demonstrated early, deep, and durable responses in the phase 1b/2 CARTITUDE-1 study in patients (pts) with relapsed/refractory multiple myeloma (RRMM) who had been heavily pretreated (Berdeja, Lancet, 2021). After a median follow-up of 12.4 months, the overall response rate (ORR; as assessed by independent review committee) was 97%, with 67% of pts achieving stringent complete response (sCR). The 12-month progression-free survival (PFS) and overall survival (OS) rates were 77% and 89%, respectively. Here, we report updated results from CARTITUDE-1 with longer duration of follow-up (median 18 months). Methods: Eligible pts had MM and received ≥3 prior therapies or were refractory to a proteasome inhibitor (PI) and an immunomodulatory drug (IMiD), and had received a PI, IMiD, and an anti-CD38 antibody. After apheresis, bridging therapy was permitted. Pts received a single cilta-cel infusion (target dose 0.75×10 6 CAR+ viable T cells/kg; range 0.5-1.0×10 6) 5-7 days (d) after lymphodepletion (300 mg/m 2 cyclophosphamide, 30 mg/m 2 fludarabine daily for 3 d). Primary objectives were to characterize cilta-cel safety, confirm the recommended phase 2 dose (phase 1b), and evaluate cilta-cel efficacy (phase 2). Response was assessed per IMWG criteria by an independent review committee and minimal residual disease (MRD) negativity at 10 -5 by next-generation sequencing. In this combined phase 1b and phase 2 analysis, cytokine release syndrome (CRS; per Lee et al Blood 2014 grading criteria) and neurotoxicity (by CTCAE v5.0) were mapped to the ASTCT criteria for CRS and immune effector cell-associated neurotoxicity (ICANS), respectively. Results: As of Feb 11, 2021, 97 pts (58.8% male; median age 61.0 years [range 43-78]) received cilta-cel. Pts had received a median of 6 (range 3-18) prior lines of therapy; 83.5% were penta-drug exposed, 87.6% were triple-class refractory, 42.3% were penta-drug refractory, and 99.0% were refractory to last line of therapy. ORR was 97.9% (95% CI: 92.7-99.7); 80.4% of pts achieved sCR, and 94.8% achieved very good partial response or better (Figure). The median time to first response was 1 month (range 0.9-10.7), median time to best response was 2.6 months (range 0.9-15.2), and median time to complete response or better was 2.6 months (range 0.9-15.2). The median duration of response was 21.8 months (95% CI: 21.8-not estimable). Of 61 pts evaluable for MRD, 91.8% were MRD negative at the 10 -5 threshold; MRD 10 -5 negativity was sustained for ≥6 months in 44.3% (27/61) of pts and ≥12 months in 18% (11/61) of pts. The 18-month PFS and OS rates were 66.0% (95% CI: 54.9-75.0) and 80.9% (95% CI: 71.4-87.6), respectively. 18-month PFS rates in pts who achieved sustained MRD for ≥6 months and ≥12 months were 96.3% (95% CI: 76.5-99.5) and 100%, respectively. The most common grade 3/4 hematologic AEs in ≥25% of pts were neutropenia (94.8%), anemia (68.0%), leukopenia (60.8%), thrombocytopenia (59.8%), and lymphopenia (49.5%). There were no fatalities related to cytopenias, and no new safety signals with longer follow-up. CRS occurred in 94.8% of pts (mostly grade 1/2); median time to onset was 7 d (range 1-12), and CRS resolved within 14 d in 98.9% of pts. There was no new CAR T-cell neurotoxicity since the previous report. Post cilta-cel infusion, 21 deaths occurred during the study: 0 within first 30 d, 2 within 100 d, and 19 more than 100 d post infusion. Ten deaths were due to disease progression, 6 were treatment-related (as assessed by the investigator), and 5 were due to AEs unrelated to treatment. One patient was retreated with cilta-cel (for progressive disease) and had stable disease (per computerized algorithm) post-retreatment with no incidence of CAR T-cell neurotoxicity. Conclusions: At a longer median follow-up of 18 months, a single cilta-cel infusion led to early, deep, and durable responses in heavily pre-treated pts with MM. Follow-up is ongoing and updated data will be presented. Cilta-cel demonstrated a manageable safety profile with no new safety signals observed with longer follow-up. Further investigations of cilta-cel are ongoing in earlier lines of therapy (CARTITUDE-2 [NCT04133636], CARTITUDE-4 [NCT04181827], and CARTITUDE-5 [NCT04923893]) and in outpatient settings. Figure 1 Figure 1. Disclosures Martin: GlaxoSmithKline: Consultancy; Janssen: Research Funding; Sanofi: Research Funding; Amgen: Research Funding. Usmani: Takeda: Consultancy, Research Funding, Speakers Bureau; SkylineDX: Consultancy, Research Funding; Seattle Genetics: Consultancy, Research Funding; Pharmacyclics: Consultancy, Research Funding; Merck: Consultancy, Research Funding; Janssen Oncology: Consultancy, Research Funding; Bristol-Myers Squibb: Research Funding; EdoPharma: Consultancy; Array BioPharma: Consultancy, Research Funding; Celgene/BMS: Consultancy, Research Funding, Speakers Bureau; GSK: Consultancy, Research Funding; Sanofi: Consultancy, Research Funding, Speakers Bureau; Janssen: Consultancy, Research Funding, Speakers Bureau; Amgen: Consultancy, Research Funding, Speakers Bureau; Abbvie: Consultancy. Berdeja: Lilly, Novartis: Research Funding; Poseida, Sanofi, Teva: Research Funding; GSK, Ichnos Sciences, Incyte: Research Funding; Bluebird bio, BMS, Celgene, CRISPR Therapeutics, Janssen, Kite Pharma, Legend Biotech, SecuraBio, Takeda: Consultancy; Celularity, CRISPR Therapeutics: Research Funding; Abbvie, Acetylon, Amgen: Research Funding; EMD Sorono, Genentech: Research Funding. Jakubowiak: Amgen: Membership on an entity's Board of Directors or advisory committees; GSK: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees; BMS: Membership on an entity's Board of Directors or advisory committees; Gracell: Membership on an entity's Board of Directors or advisory committees; Sanofi: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees. Cohen: Novartis: Research Funding; BMS/Celgene: Consultancy; Takeda: Consultancy; Genentech/Roche: Consultancy; Oncopeptides: Consultancy; AstraZeneca: Consultancy; Janssen: Consultancy; GlaxoSmithKline: Consultancy, Research Funding. Hari: Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other, Research Funding, Speakers Bureau; Karyopharm: Consultancy; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Oncopeptides: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Millenium: Membership on an entity's Board of Directors or advisory committees, Research Funding; GSK: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other, Research Funding, Speakers Bureau; Adaptive Biotech: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other, Research Funding, Speakers Bureau; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other, Research Funding, Speakers Bureau; Celgene-BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other, Research Funding, Speakers Bureau. Avigan: Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Pharmacyclics: Research Funding; Kite Pharma: Consultancy, Research Funding; Juno: Membership on an entity's Board of Directors or advisory committees; Partner Tx: Membership on an entity's Board of Directors or advisory committees; Karyopharm: 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; Aviv MedTech Ltd: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees; Legend Biotech: Membership on an entity's Board of Directors or advisory committees; Chugai: Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy; Parexcel: Consultancy; Takeda: Consultancy; Sanofi: Consultancy. Deol: Kite, a Gilead Company: Consultancy. Lesokhin: bristol myers squibb: Research Funding; Iteos: Consultancy; pfizer: Consultancy, Research Funding; Behringer Ingelheim: Honoraria; Trillium Therapeutics: Consultancy; Serametrix, Inc: Patents & Royalties; Genetech: Research Funding; Janssen: Honoraria, Research Funding. Munshi: Adaptive Biotechnology: Consultancy; Karyopharm: Consultancy; Oncopep: Consultancy, Current equity holder in publicly-traded company, Other: scientific founder, Patents & Royalties; Legend: Consultancy; Novartis: Consultancy; Abbvie: Consultancy; Celgene: Consultancy; Janssen: Consultancy; Takeda: Consultancy; Amgen: Consultancy; Pfizer: Consultancy; Bristol-Myers Squibb: Consultancy. O'Donnell: Onocopeptide: Consultancy; Karyopharm: Consultancy; Janssen: Consultancy; Bristol Myer Squibb: Consultancy; Adaptive: Consultancy; Takeda: Consultancy. Stewart: Oncopeptides: Honoraria; Janssen: Honoraria; GSK: Honoraria; BMS: Honoraria; Amgen: Honoraria; Skyline diagnostics: Consultancy; Genomcs England: Membership on an entity's Board of Directors or advisory committees; Tempus Inc.: Current holder of individual stocks in a privately-held company, Membership on an entity's Board of Directors or advisory committees; PikSci Inc.: Current holder of individual stocks in a privately-held company, Patents & Royalties; Sanofi Aventis: Honoraria. Schecter: Janssen: Current Employment, Current holder of stock options in a privately-held company. Goldberg: Janssen: Current Employment, Current holder of individual stocks in a privately-held company. Jackson: Janssen: Current Employment; Memorial Sloan Kettering Cancer Center: Consultancy. Yeh: Janssen: Current Employment. Banerjee: Janssen: Current Employment, Current holder of individual stocks in a privately-held company. Allred: Janssen: Current Employment, Current holder of individual stocks in a privately-held company, Current holder of stock options in a privately-held company. Zudaire: Janssen: Current Employment. Deraedt: Janssen: Current Employment. Olyslager: Janssen: Current Employment. Pacaud: Legend Biotech: Current Employment. Lin: Juno: Consultancy; Bluebird Bio: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Novartis: Consultancy; Takeda: Research Funding; Kite, a Gilead Company: Consultancy, Research Funding; Vineti: Consultancy; Gamida Cell: Consultancy; Sorrento: Consultancy; Legend: Consultancy; Merck: Research Funding; Janssen: Consultancy, Research Funding. Jagannath: Legend Biotech: Consultancy; Karyopharm Therapeutics: Consultancy; Janssen Pharmaceuticals: Consultancy; Bristol Myers Squibb: Consultancy; Sanofi: Consultancy; Takeda: Consultancy. OffLabel Disclosure: At the time of abstract submission, cilta-cel is being investigated for the treatment of multiple myeloma but is not yet approved.

The application of novel single-cell technologies provides personalized profiles on patient samples to improve standard of healthcare and evolve the field of precision medicine. In the field of Immuno-oncology, application of single cell RNA-seq (scRNA-seq) to evaluate gene expression profiles has provided new insights on the cancer subpopulation dynamic, network reconstruction, and cell trajectory inferences. Here we present a standardized and validated scRNA-seq analytical workflow applied to a series of common cryopreserved Multiple Myeloma (MM) bone marrow samples obtained from subjects enrolled in the Multiple Myeloma Research Foundation (MMRF) CoMMpass study (NCT01454297). scRNA-seq data was generated from common samples at three different academic research centers. While the high variability of scRNA-seq data raises computational challenges in data analysis, we have tested different quality control, alignment, batch correction, clustering and annotation methods to prove that the results are consistent for subsets of cells, independent of the center generating the data. To evaluate differences in cell type composition and cross-center differences, an in-depth analysis was performed on four CD138- sorted samples (>18,000 total cells) that were subject to scRNA-sequencing at 3 different centers. We tested three different batch correction methods including: Harmony, Seurat Merge and Seurat Anchor. Immune cell types (CD4 T, CD8 T, NK, Monocytes, Macrophages and pDCs), exhibited similarities in clustering structure and shared complementary differentially expressed genes while Plasma and B cells exhibited distinct center variation when using Seurat Merge. The evaluation of batch effects across samples generated at 3 centers identified subtle batch effects without significant impact of cellular clusterings. For data concordance analyses, Seurat Merge was used for batch effect correction and data normalization and a beta-variational autoencoder and random forest classifier was utilized to assign cell types. In comparing the proportion of each cell type identified across centers using dead cell removal bead depletion, the overall population of plasma and B cells were found to be dissimilar for a subset of samples which could be attributed to differences in bone marrow aliquot sampling. We further explored how the application of dead cell removal altered the distribution of tumor and immune populations for the same sample of interest. Samples that underwent dead cell removal have consistently higher NK and CD8+T cell proportion, while CD4+T is higher more often in non-treated samples. In summary, dead cell removal ultimately improved the overall data quality (more viable cells) without significantly altering the gene expression signatures or proportions of each cell type. Further comparative analysis of transcriptome signatures of various cell types (e.g., B cells, T cells, Plasma cells) across 3 centers depicted significant similarity in transcriptome profile. This suggests even if three centers captured different numbers of various cell types due to variation in protocols and aliquots, the cells still have significantly similar transcriptome profiles that might be helpful in producing the same biological results across three sites. Our in-depth cross-institutional assessment of tumor and immune cell types in MM will provide a valuable resource and thorough analysis strategy to the broader scientific community. Disclosures Dhodapkar: 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; 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.

Background: Ciltacabtagene autoleucel (cilta-cel; JNJ-68284528; LCAR-B38M CAR-T cells) is a chimeric antigen receptor T (CAR-T) cell therapy with 2 B-cell maturation antigen-targeting single-domain antibodies designed to confer avidity. In the phase 1 LEGEND-2 study in China, LCAR-B38M yielded deep, durable responses with a manageable safety profile in patients (pts) with relapsed/refractory multiple myeloma (R/R MM). The phase 1b/2 CARTITUDE-1 study (NCT03548207) is further evaluating cilta-cel in this pt population in the US. We present updated data from the phase 1b portion along with initial phase 2 data. Methods: Eligible pts (aged ≥18 y) were diagnosed with MM per International Myeloma Working Group (IMWG) criteria and had measurable disease, Eastern Cooperative Oncology Group performance status ≤1, received ≥3 prior regimens or were double-refractory to a proteasome inhibitor and immunomodulatory drug, and received an anti-CD38 antibody. After apheresis, bridging therapy was permitted. Cyclophosphamide 300 mg/m2 and fludarabine 30 mg/m2 daily for 3 d were used for lymphodepletion. A single infusion of cilta-cel at a target dose of 0.75×106 (range 0.5-1.0×106) CAR+ viable T cells/kg was administered 5-7 d after start of lymphodepletion. The primary objective of the phase 1b portion was to characterize cilta-cel safety and establish the recommended phase 2 dose; the primary objective of the phase 2 portion was to evaluate cilta-cel efficacy. Response was assessed per IMWG criteria and minimal residual disease (MRD) by next-generation sequencing. Adverse events (AEs) were graded using CTCAE v5.0. In the phase 1b portion, cytokine release syndrome (CRS) was graded by Lee et al (Blood 2014) and neurotoxicity by CTCAE v5.0; in the phase 2 portion, CRS and neurotoxicity were graded by American Society for Transplantation and Cellular Therapy (ASTCT) criteria. In this combined analysis, Lee et al and CTCAE v5.0 were mapped to ASTCT criteria for CRS and immune effector cell-associated neurotoxicity syndrome (ICANS), respectively. Results: As of the May 20, 2020 clinical cutoff, 97 pts (58.8% male; median age 61.0 y [range 43-78]) with R/R MM received cilta-cel (29 in phase 1b; 68 in phase 2). Median follow-up duration was 8.8 mo (range 1.5-20.4). Pts had received a median of 6 prior lines of therapy (range 3-18); 83.5% were penta-exposed, 87.6% were triple-refractory, 41.2% were penta-refractory, and 97.9% were refractory to last line of therapy. Overall response rate per independent review committee (primary endpoint) was 94.8% (95% CI 88.4-98.3), with a stringent complete response rate of 55.7% (95% CI 45.2-65.8), very good partial response rate of 32.0% (95% CI 22.9-42.2), and partial response rate of 7.2% (95% CI 3.0-14.3). All pts achieved a reduction in M-protein. Median time to first response was 1.0 mo (range 0.9-5.8; 80.4% ≤1.0 mo), and median time to complete response or better was 1.8 mo (range 0.9-12.5; 74.1% ≤3.0 mo); responses deepened over time (Figure). Median duration of response was not reached (NR). Of 52 MRD-evaluable pts, 94.2% were MRD-negative at 10-5. The 6-mo progression-free survival (PFS) and overall survival (OS) rates (95% CI) were 87.4% (78.9-92.7) and 93.8% (86.7-97.2), respectively; median PFS and OS were NR. Ten deaths occurred during the study; 8 were due to AEs (both related and unrelated; CRS/hemophagocytic lymphohistiocytosis, neurotoxicity, respiratory failure, sepsis, septic shock, pneumonia, lung abscess, and acute myelogenous leukemia [n=1 each]), and 2 due to progressive disease. AEs reported in >70% of pts were CRS (94.8%; grade [gr] 3/4 4.1%), neutropenia (90.7%; gr 3/4 90.7%), anemia (81.4%; gr 3/4 68.0%), and thrombocytopenia (79.4%; gr 3/4 59.8%). Median time to CRS onset was 7.0 d (range 1-12) and median duration 4.0 d (range 1-27, excluding n=1 with 97 d). CAR-T cell-related neurotoxicity was reported in 20.6% of pts (gr 3/4 10.3%). Cilta-cel CAR+ T cells showed maximum peripheral expansion at 14 d (range 9-43). Among pts with 6 mo' individual follow-up, 67% had cilta-cel CAR+ T cells below the level of quantification (2 cells/µL) in peripheral blood. Conclusions: Preliminary phase 1b/2 data from CARTITUDE-1 indicate a single low-dose infusion of cilta-cel leads to early, deep, and durable responses in heavily pretreated pts with MM with a safety profile consistent with LEGEND-2. Further investigation of cilta-cel in other MM populations is underway. Disclosures Madduri: Celgene: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria; Foundation Medicine: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Legend: 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; GSK: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Speaking Engagement, Speakers Bureau. Berdeja:Teva: Research Funding; Bluebird: Research Funding; Bioclinica: Consultancy; Celgene: Consultancy, Research Funding; EMD Sorono: Research Funding; Kite Pharma: Consultancy; Prothena: Consultancy; Cellularity: Research Funding; Karyopharm: Consultancy; Servier: Consultancy; Legend: Consultancy; Poseida: Research Funding; Lilly: Research Funding; Acetylon: Research Funding; CURIS: Research Funding; Janssen: Consultancy, Research Funding; Genentech, Inc.: Research Funding; Glenmark: Research Funding; Takeda: Consultancy, Research Funding; BMS: Consultancy, Research Funding; Constellation: Research Funding; CRISPR Therapeutics: Consultancy, Research Funding; Vivolux: Research Funding; Abbvie: Research Funding; Amgen: Consultancy, Research Funding; Kesios: Research Funding; Novartis: Research Funding. Usmani:Celgene: Other; BMS, Celgene: Consultancy, Honoraria, Other: Speaking Fees, Research Funding; GSK: Consultancy, Research Funding; Pharmacyclics: Research Funding; Merck: Consultancy, Research Funding; Abbvie: Consultancy; Sanofi: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria, Other: Speaking Fees, Research Funding; Janssen: Consultancy, Honoraria, Other: Speaking Fees, Research Funding; SkylineDX: Consultancy, Research Funding; Seattle Genetics: Consultancy, Research Funding; Incyte: Research Funding; Array Biopharma: Research Funding; Amgen: Consultancy, Honoraria, Other: Speaking Fees, Research Funding. Jakubowiak:Adaptive, Juno: Consultancy, Honoraria; AbbVie, Amgen, BMS/Celgene, GSK, Janssen, Karyopharm: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Cohen:Celgene: Membership on an entity's Board of Directors or advisory committees; Takeda,: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; GlaxoSmithKline: Membership on an entity's Board of Directors or advisory committees; Kite Pharma: Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; Seattle Genetics: Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Membership on an entity's Board of Directors or advisory committees; Genentech/Roche: 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, Research Funding; Novartis: Other: Patents/Intellectual property licensed, Research Funding. Stewart:Janssen, BMS, Sanofi-Aventis, GSK: Honoraria; Tempus, Inc., Genomics England LLC: Membership on an entity's Board of Directors or advisory committees. Hari:Amgen: Consultancy; BMS: Consultancy; GSK: Consultancy; Janssen: Consultancy; Takeda: Consultancy; Incyte Corporation: Consultancy. Htut:City of Hope Medical Center: Current Employment. Munshi:OncoPep: Consultancy, Current equity holder in private company, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties; BMS: Consultancy; Janssen: Consultancy; Adaptive: Consultancy; Legend: Consultancy; Amgen: Consultancy; Karyopharm: Consultancy; Takeda: Consultancy; AbbVie: Consultancy; C4: Current equity holder in private company. Deol:Novartis: Consultancy; Kite, a Gilead Company: Consultancy. Lesokhin:BMS: Consultancy, Honoraria, Research Funding; Genentech: Research Funding; Janssen: Research Funding; Juno: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Serametrix Inc.: Patents & Royalties; GenMab: Consultancy, Honoraria. Singh:Janssen: Current Employment. Zudaire:Janssen: Current Employment. Yeh:Janssen: Current Employment. Allred:Janssen: Current Employment. Olyslager:Janssen: Current Employment. Banerjee:Janssen: Current Employment. Goldberg:Johnson & Johnson: Current Employment, Current equity holder in publicly-traded company. Schecter:Janssen: Current Employment. Jackson:Janssen: Current Employment; Memorial Sloan Kettering Cancer Center: Consultancy. Deraedt:Janssen: Current Employment, Current equity holder in publicly-traded company. Zhuang:Janssen: Current Employment. Infante:Janssen: Current Employment. Geng:Legend Biotech USA Inc.: Current Employment. Wu:Legend Biotech USA Inc.: Current Employment. Carrasco:Legend Biotech USA Inc.: Current Employment. Akram:Legend Biotech USA Inc.: Current Employment. Hossain:Legend Biotech USA Inc.: Current Employment. Rizvi:Legend Biotech USA Inc.: Current Employment. Fan:Legend Biotech USA Inc.: Current Employment. Jagannath:BMS, Janssen, Karyopharm, Legend Biotech, Sanofi, Takeda: Consultancy. Lin:Kite, a Gilead Company: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Merck: Research Funding; Legend BioTech: Consultancy; Juno: Consultancy; Bluebird Bio: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Novartis: Consultancy; Vineti: Consultancy; Takeda: Research Funding; Gamida Cells: Consultancy; Sorrento: Consultancy, Membership on an entity's Board of Directors or advisory committees. Martin:AMGEN: Research Funding; Seattle Genetics: Research Funding; Janssen: Research Funding; GSK: Consultancy; Sanofi: Research Funding.

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.