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Introduction: The treatment of multiple myeloma (MM) has dramatically improved due to the availability of immunotherapies such as daratumumab (Dara). However, in Canada, myeloma treatments now account for up to 20% of some provincial drug budgets. As Dara may be effective for a prolonged period and is quickly moving into first-line therapy, the Canadian body which provides guidelines to the provincial ministries of health recommended in 2019 against open sequencing of drugs in relapsed MM. Specifically, patients who receive Dara are now only eligible for public funding for either carfilzomib (CAR) or pomalidomide (POM)--but not both-- for relapsed MM. Given the known heterogeneity of myeloma, data gaps regarding the optimal sequencing of the available agents and uncertainly regarding the impact of this new restriction on patient outcomes, we utilized our Canadian national myeloma database to assess the sequencing of these two agents. The goal of our study was to understand the efficacy of these two commonly used treatments in the relapsed setting: 1) POM- after CAR-based therapy and 2) CAR- after POM-based therapy. Methods: We performed a retrospective observational study using the Canadian Myeloma Research Group Database (CMRG-DB), analyzed up to 30/06/2020. The CMRG-DB (formerly Myeloma Canada Research Network Database/MCRN-DB) is a prospectively maintained disease-specific database with over 7000 patients enrolled from 14 academic sites across Canada and includes legacy data collected from 2007. All patients with MM who were treated for relapsed disease with approved regimens using POM after CAR, or CAR after POM were included. Our primary outcomes were overall response rates (ORR) in each respective cohort. Secondary outcomes were progression-free survival (PFS), overall survival (OS), and a landmark OS analysis from treatment initiation with the first of the two agents. Survival was estimated using Kaplan-Meier methods and compared between groups using log rank test. Results: A total of 121 patients were included: 49 treated with POM after CAR, and 72 with CAR after POM. In the POM after CAR group, the median line of treatment was 4th for POM and 3rd for CAR. In the CAR after POM group, the median line of treatment was 4th for POM and 5th for CAR. In 79/121 patients (65%), the two therapies were directly sequential, 40/49 (82%) for the POM after CAR group, and 38/72 (54%) in the CAR after POM group. Baseline characteristics and treatment details are shown in Table 1. The ORR was 51% for patients treated with POM after CAR, and 49% for patients treated with CAR after POM. The median PFS for POM after CAR was 4.93 months (95% CI, 2.76-7.07), and for CAR after POM was 5.36 months (95% CI, 3.75-6.94). The median OS for patients treated POM after CAR was 11.01 months (95% CI, 4.50-19.13), and for patients treated with CAR after POM the median OS was 10.98 months (95% CI, 8.98-19.17) (Figure 1). In a landmark analysis using the time of the treatment initiation with the first of the two agents, the median OS of patients treated with CAR after POM was 37.61 months (95% CI 26.66-46.52) and 25.32 months (95% CI 14.56-41.19) for patients treated with POM after CAR (p=0.1270) (Figure 2). Conclusion: In this real-world observational study we demonstrated that both CAR- and POM-based therapies were effective treatment options for patients with advanced relapsed MM as each produced responses in approximately 50% of patients with a median PFS of about 5 months and median OS of 11 months. These results are comparable to those noted in prospective clinical trials leading to the approval of these agents in this setting. Further, a landmark analysis showed that using both agents sequentially late in the disease course provided reasonable OS outcomes, regardless of the order in which they are sequenced. Finally, as the cost of MM therapy increases, the use of real-world data can help determine the impact of funding decisions on the outcome of patients treated in a publicly funded universal health care system such the one in Canada. Disclosures McCurdy: GSK: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Sanofi: Honoraria; Amgen: Consultancy, Honoraria. Venner:Janssen, BMS/Celgene, Sanofi, Takeda, Amgen: Honoraria; Celgene, Amgen: Research Funding. Louzada:Janssen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Takeda: Consultancy, Honoraria. LeBlanc:Celgene: Research Funding; Celgene Canada; Janssen Inc.; Amgen Canada; Takeda Canada: Membership on an entity's Board of Directors or advisory committees. Sebag:Takeda: Honoraria; Celgene: Honoraria; Janssen: Honoraria, Research Funding; Amgen: Honoraria. Song:Celgene: Research Funding; Celgene, Janssen, Amgen, Takeda: Honoraria. Jimenez-Zepeda:Janssen, Celgene, Amgen, Takeda: Honoraria. Kotb:Takeda: Honoraria; Merck: Honoraria, Research Funding; Celgene: Honoraria; Janssen: Honoraria; Sanofi: Research Funding; Karyopharm: Current equity holder in publicly-traded company; Amgen: Honoraria. Mian:Sanofi: Consultancy; Takeda: Consultancy, Honoraria; Celgene: Consultancy; Janssen: Consultancy, Honoraria; Amgen: Consultancy, Honoraria. White:Amgen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Sanofi: Consultancy, Honoraria; Takeda: Consultancy, Honoraria. Stakiw:Roche: Research Funding; Lundbeck: Honoraria; BMS: Honoraria; Novartis: Honoraria; Amgen: Honoraria; Celgene: Honoraria; Janssen: Honoraria, Research Funding. Reece:Janssen, Bristol-Myers Squibb, Amgen, Takeda: Consultancy, Honoraria; Janssen, Bristol-Myers Squibb: Membership on an entity's Board of Directors or advisory committees; Merck: Honoraria, Research Funding; Otsuka: Research Funding.

Background: Within the spectrum of monoclonal gammopathies, there are various subgroups with unique biological and clinical profiles. Namely, the presence of multiple myeloma (MM) and light-chain amyloidosis (AL) pts with MGUS-like phenotype has been hypothesized, but the criteria to identify this subgroup are poorly defined and lack clinical validation. Aim: Develop an algorithm based on a large flow cytometry dataset across the spectrum of monoclonal gammopathies, for automated identification of MM and AL pts with MGUS-like phenotype. Methods: This study included 5,114 pts with monoclonal gammopathies and available flow cytometry data on the frequency of bone marrow (BM) plasma cells (PC) and the percentages of normal and clonal PC within the BM PC compartment, at diagnosis. An algorithm to classify pts with MGUS-like phenotype was developed based on these three parameters, obtained from 548 MGUS, 393 smoldering MM (SMM) and 2,011 MM pts. Newly diagnosed MM pts were homogeneously treated according to the GEM2000 (n = 486), GEM2005MENOS65 (n = 330), GEM2005MAS65 (n = 239), GEM2010MAS65 (n = 230), GEM2012MENOS65 (n = 450) and CLARIDEX (n = 276) protocols. The prognostic value of the MGUS-like phenotype was validated in 96 SMM pts studied in Arkansas and 1,859 MM pts treated outside clinical trials in Czech Republic. The clinical significance of the algorithm was investigated in two independent series of Spanish (n = 102) and Italian (n = 105) AL pts. Results: The frequency of BM PC and of normal and clonal PC within the BM PC compartment were used to plot MGUS, SMM and MM pts in a principal component analysis (PCA). Lines defining 1.5 standard deviations of MGUS and MM pts were used as reference to classify each of the 5,114 cases. Once plotted against the dataset, individual pts were classified as MGUS-, intermediate- or MM-like, if their location in the PCA fell inside the MGUS, the overlapping or the MM reference lines, respectively. In the training SMM series, patient classification into MGUS-, intermediate- and MM-like phenotype resulted in significantly different rates of disease progression (0%, 54% and 66% at 5y, respectively; P < .001). These results were validated in the Arkansas series (8%, 27% and 71% at 5y, respectively; P < .001). Only 5% of SMM pts with high-risk disease according to Mayo or PETHEMA criteria had an MGUS-like phenotype, and these had virtually no risk of progression at 5y. In the training MM series, pts with MGUS-like phenotype showed significantly longer progression free (PFS) and overall survival (OS) vs the remaining pts. Median PFS was 10y vs 3y (hazard ratio [HR]: 0.46, P < .001) and median OS was not reached (NR) vs 6.5y (HR: 0.48, P < .001), respectively. These results were validated in the Czech Republic series with significant differences in PFS (HR: 0.45, P < .001) and OS (HR: 0.38, P < .001) between MGUS-like vs other MM pts. MGUS-like classification in the training MM series retained independent prognostic value in multivariate analyses of PFS (HR: 0.48, P < .001) and OS (HR: 0.54, P = .033), together with ISS, LDH, cytogenetics, induction regimen, transplant-eligibility and complete remission (CR). MGUS-like pts showed similar PFS (P = .932) and OS (P = .285) regardless of having standard vs high risk cytogenetics. Notably, MGUS-like transplant-eligible MM pts treated with proteasome inhibitors, immunomodulatory drugs and corticoids during induction showed PFS and OS rates at 5y of 86% and 96%, respectively. Differences in PFS among MGUS-like MM pts achieving ≥CR vs Classification of AL pts into the MGUS-, intermediate- and MM-like phenotype resulted in significantly different PFS in the Spanish (median of 28, 20 and 1 months, respectively; P = .001) and Italian (median 32, 11 and 3 months, respectively; P < .001) cohorts. Conclusions: We developed an algorithm that can be readily installed in clinical flow cytometry software, and requires three parameters that are routinely assessed at screening. Patient' automated classification using the algorithm was validated in large series across the spectrum of monoclonal gammopathies. Because pts with MGUS-like phenotype have a distinct clinical behavior, their identification could become part of the diagnostic workup in SMM, MM and AL. Disclosures Cedena: Janssen, Celgene and Abbvie: Honoraria. Milani: Celgene: Other: Travel support; Janssen-Cilag: Honoraria. Cordon: Cytognos SL: Research Funding. Oriol: Takeda: Consultancy, Speakers Bureau; Celgene: Consultancy, Speakers Bureau; Amgen: Consultancy, Speakers Bureau; Janssen: Consultancy. de la Rubia: Amgen, Bristol Myers Squibb,: Honoraria, Speakers Bureau; Celgene, Takeda, Janssen, Sanofi: Honoraria; Ablynx/Sanofi: Consultancy; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: TRAVEL, ACCOMMODATIONS, EXPENSES; AbbVie: Consultancy; Bristol Myers Squibb: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Travel Accommodations; GSK: Consultancy; Takeda: Consultancy; Sanofi: Membership on an entity's Board of Directors or advisory committees. De Arriba: Amgen: Consultancy, Honoraria; Glaxo Smith Kline: Consultancy, Honoraria; BMS-Celgene: Consultancy, Honoraria, Speakers Bureau; Janssen: Consultancy, Honoraria, Speakers Bureau. Cabañas: Janssen: Consultancy, Honoraria; BMS: Consultancy, Honoraria; Sanofi: Honoraria. Gonzalez De La Calle: Celgene-BMS, Janssen, Amgen: Honoraria. Rodríguez-Otero: Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Regeneron: Membership on an entity's Board of Directors or advisory committees; Abbvie: Honoraria, Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Honoraria, Membership on an entity's Board of Directors or advisory committees; Kite: Honoraria, Membership on an entity's Board of Directors or advisory committees; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees; GlaxoSmithKline: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; BMS/Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel and other expenses. Hajek: Pharma MAR: Consultancy, Honoraria; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Consultancy, Research Funding; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Research Funding; BMS: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding. Jimenez-Zepeda: BMS, Amgen, Takeda, Janssen: Honoraria. Palladini: Janssen Global Services: Honoraria, Other: advisory board fees; Pfizer: Honoraria; Siemens: Honoraria. Rosinol: Janssen, Celgene, Amgen and Takeda: Honoraria. Bladé Creixenti: Janssen, Celgene, Takeda, Amgen and Oncopeptides: Honoraria. Martínez-López: Janssen, BMS, Novartis, Incyte, Roche, GSK, Pfizer: Consultancy; Roche, Novartis, Incyte, Astellas, BMS: Research Funding. Mateos: Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees; Regeneron: Honoraria, Membership on an entity's Board of Directors or advisory committees; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees; Adaptive Biotechnologies: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene - Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Sea-Gen: 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; AbbVie: Honoraria; Oncopeptides: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bluebird bio: Honoraria; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; GSK: Honoraria; Oncopeptides: Honoraria. San-Miguel: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, GlaxoSmithKline, Janssen, Karyopharm, Merck Sharpe & Dohme, Novartis, Regeneron, Roche, Sanofi, SecuraBio, Takeda: Consultancy, Other: Advisory board. Paiva: Bristol-Myers Squibb-Celgene, Janssen, and Sanofi: Consultancy; Adaptive, Amgen, Bristol-Myers Squibb-Celgene, Janssen, Kite Pharma, Sanofi and Takeda: Honoraria; Celgene, EngMab, Roche, Sanofi, Takeda: Research Funding.

Introduction Lenalidomide-based regimens represent a cornerstone of treatment for newly-diagnosed transplant-ineligible patients with multiple myeloma (TI NDMM). Although lenalidomide-containing regimens are associated with improved outcomes, there is also significant toxicity leading to dose reductions and/or interruptions even among patients selected for clinical trial participation. Product monograph recommendations suggest full dose lenalidomide (25 mg) for CrCl ≥ 60 mL/min; however, there is limited data on how these dose modifications are applied in the real-world. Furthermore, it is unknown how real-world dosing strategies and modifications impact patient outcomes. Understanding the dosing, efficacy and tolerability of lenalidomide is important as this drug continues to form the backbone of many novel combination regimens. The objective of our study was to understand the dosing, efficacy and tolerability of lenalidomide among TI NDMM patients started on lenalidomide-dexamethasone (Rd) in the real-world. Methods The Canadian Myeloma Research Group (CMRG) Database is a national multi-centre prospectively maintained disease-specific database. All consecutive TI NDMM patients treated with Rd outside of a clinical trial were analyzed up to 30/09/2020. Patients were stratified by starting lenalidomide dose. Within each dose category, age and renal function (eGFR Results Of 298 TI NDMM patients receiving Rd in first-line treatment, 131 patients were excluded as they received the regimen on a clinical trial. Baseline characteristics of the 167 included patients are shown in Table 1. The median age was 77 with 22.6% having high-risk cytogenetics. Impaired renal function (eGFR < 60 ml/min) was present in 41.4% of patients. Median time from diagnosis to Rd initiation was 0.7 months (range 0.1 - 92.5). Starting dose, age and renal function at therapy initiation, dose modification details and treatment duration are outlined in Table 2 for 163 patients. Sixty-two (38.0%) were started on a dose of 25 mg. The median age in this dose group was 74 years and 87.5% had normal renal function. One hundred and one patients (62.0%) were started on a dose < 25 mg of lenalidomide. Among this group 42.2% had normal renal function. In the overall cohort, fifty-seven (35.0%) patients required dose reduction during therapy. Among patients started on 25 mg, 40.3% required dose reduction with the median time to first dose reduction of 11.5 months (range 0.8-56.9). Among patients started on < 25 mg, 31.7% required dose reduction with details shown in Table 2. Dose reduction reasons were documented in 35.0% patients. Most frequent causes of dose reduction (>20% of the patients) included fatigue (31.6%), neutropenia (29.8%), diarrhea (22.8%), rash (22.8%) and thrombocytopenia (21.1%). For the entire cohort, the median follow-up was 33.2 months (95% Cl 0.5-113.2). The ORR was 78.7% with 52.0% ≥ VGPR. The median PFS and OS was 21.0 months (95% CI 14.9-27.4) and 55.5 months (95% CI 45.7-84.0) respectively. In a landmark analysis at 12 months following therapy initiation, there were no significant differences noted for PFS and OS between patient groups that required dose modification versus not in the first year following diagnosis (Figure 1A and B). Conclusion In this real-world observational study, lenalidomide dose modifications were common both at diagnosis and during therapy. Among patients started on Figure 1 Figure 1. Disclosures Mian: Celgene, Janssen, Amgen, Takeda, Sanofi, GSK: Honoraria; Janssen: Research Funding. Leblanc: Janssen Canada: Membership on an entity's Board of Directors or advisory committees; BMS/Celgene Canada: Membership on an entity's Board of Directors or advisory committees; Amgen Canada: Membership on an entity's Board of Directors or advisory committees; Sanofi Canada: Membership on an entity's Board of Directors or advisory committees; Takeda Canada: Membership on an entity's Board of Directors or advisory committees; Celgene/BMS: Research Funding. Louzada: Celgene: Honoraria; Janssen: Honoraria; Pfizer: Honoraria; Amgen: Honoraria. McCurdy: Sanofi: Honoraria; GSK: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria. Venner: Celgene: Research Funding; Takeda: Honoraria; Amgen: Honoraria; Janssen: Honoraria; Amgen: Research Funding. Jimenez-Zepeda: BMS, Amgen, Takeda, Janssen: Honoraria. Sebag: Karyopharm Therapeutics: Consultancy, Honoraria; Sanofi: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Novartis: Consultancy, Honoraria; Bristol Myers-Squibb: Consultancy, Honoraria; Janssen: Research Funding. White: Takeda: Consultancy, Honoraria; Sanofi: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Antengene: Consultancy, Honoraria; Forus: Consultancy, Honoraria; GSK: Consultancy, Honoraria; Karyopharm Therapeutics Inc.: Consultancy, Honoraria. Song: Celgene: Research Funding; Celgene, Janssen, Amgen, Takeda: Honoraria. Reiman: Compositions and Methods for Inhibiting Blood Cancer Cell Growth. Canadian Patent Pending 176000 (2017-10-20) Peptides for the Treatment of Resorptive Bone Disease. Murugesan A and Reiman T. United States Provisional Patent; 62/249,471 (2015-11-02). Cance: Patents & Royalties; Myeloma Canada, Canadian Institutes of Health Research, New Brunswick Health Research Foundation, Canadian Cancer Society, Terry Fox Research Institute, AstraZeneca, Roche, Pfizer, Amgen, BristolMyersSquibb,: Research Funding; Myeloma Canada: Membership on an entity's Board of Directors or advisory committees. Kotb: Amgen: Honoraria; Sanofi: Honoraria, Research Funding; Merck: Honoraria, Research Funding; Akcea: Honoraria; Pfizer: Honoraria; Karyopharm: Current holder of individual stocks in a privately-held company; Celgene: Honoraria; BMS: Honoraria; Takeda: Honoraria; Janssen: Honoraria. Reece: Karyopharm: Consultancy, Research Funding; Amgen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Millennium: Research Funding; Takeda: Consultancy, Honoraria, Research Funding; Sanofi: Honoraria; BMS: Honoraria, Research Funding; GSK: Honoraria; Janssen: Consultancy, Honoraria, Research Funding.

Purpose: Acute myeloid leukemia (AML) is the most common acute leukemia in adults, affecting approximately 20,000 patients annually in the United States. AML genetic subtypes, as defined by the World Health Organization (WHO), are identified through fluorescence in situ hybridization (FISH), conventional chromosome analysis, and sequencing techniques. Mate pair sequencing (MPseq) is a next generation sequencing (NGS) technology optimized to detect genome wide structural variants and copy number alterations at high resolution. Our study goal was to investigate the prognostic value of MPseq in comparison to FISH, chromosome, and sequencing studies in the evaluation of AML patients. Methods: We performed a prospective study using blood and bone marrow samples from 105 patients with a diagnosis of AML, using MPseq, along with chromosome, FISH, and NGS or PCR studies to detect small mutations. Cytogenetic and molecular genetic results were correlated with MPseq findings. We also analyzed the MPseq data for chromoplexy, chromothripsis, and progressive complexity. Junction and copy number burden, the incidence of structural variation in the genome and the percent of the genome with aberrant copy number, were evaluated. Overall survival statistics were stratified by AML subtypes and observed anomalies. Results: Although structural variants in AML were characterized at a high resolution using MPseq when compared to conventional cytogenetic methods, risk stratification using current European Leukemia Net (ELN) guidelines was not improved by MPseq. The cohorts involving 5q and/or 7q deletions exhibited high levels of genomic complexity when compared to normal karyotype AML (NK-AML). The incidence of copy number gains, losses and junctions was greatest in 5q and 7q co-deletions (5q/7q) (16.5, 25.0, 69.3) and 5q deletions (5q) (9.8, 16.7, 31.6) subtypes compared to 7q deletions (3.4, 7.0, 6.7) and NK-AML (2.6, 4.3, 3.8) (p Discussion: Risk stratifications based on current guidelines using cytogenetic and sequencing results were not adjusted due to MPseq results, which is not surprising when primary abnormalities are observed by conventional cytogenetic methods. NK-AML cases did not appear to benefit from a high resolution genomic evaluation. However, MPseq added value when structural variation required additional characterization, detecting novel rearrangements, such as a KAT6A/SORBS3 fusion. Lastly, we recognized common mischaracterizations made by conventional chromosome studies - including missed TP53 deletions in 7 cases, 5q/7q deletions misinterpreted as monosomies, cryptic NUP98 rearrangements, and unappreciated genomic complexity correlating with poor OS. These mischaracterizations challenge the use of conventional chromosome studies as a gold standard without accompanying FISH or MPseq studies. MPseq, similar to other structural methodologies such as optical mapping and long read sequencing, should be considered important complements to standard cytologic techniques given the important additional genomic information obtained. The additional structural variant characterization will be critical in paving the way for genomic discovery with the overall goal of improving prognostication for patient care. Figure Disclosures Vasmatzis: WholeGenome LLC.: Other: Owner; Mayo Clinic: Membership on an entity's Board of Directors or advisory committees, Research Funding.

Background: Recent studies evaluating tandem autologous transplantation for multiple myeloma (MM) show conflicting results in terms of efficacy. However subgroup analysis suggests that those with high-risk disease may benefit the most from tandem transplant. We used the CMRG database to compare single versus tandem ASCT for patients with MM with high-risk cytogenetics. Methods: The primary objective was to compare PFS in MM patients with high-risk cytogenetics (p53 deletion, t(4;14), t(14;16)) identified from the CMRG database undergoing front-line single or tandem ASCT from 01/2010 to 06/2019. Secondary objectives compared OS, ORR, and outcomes based on whether post-transplant maintenance was given. OS and PFS rates were calculated from the date of first ASCT using the Kaplan-Meier method. ORR was assessed by Chi-square using best response post ASCT. Results: There were 302 single and 125 tandem transplants, followed by maintenance therapy in 190 (63%) and 96 (77%) respectively. Translocation (4;14) was seen in 209 (49%), t(14:16) in 61 (15.6%) and delP53 in 222 (52%) with more than one abnormality in 65 patients. The most common induction regimen consisted of cyclophosphamide, bortezomib, and steroids, (83%) followed by bortezomib and dexamethasone (8%) and dexamethasone alone (4.7%). Forty-seven patients (11%) required reinduction prior to first ASCT with regimens including RVD (49%), Rd (23%) and others (D/DT/VD-PACE, CyBor-D, KRD, VD, IxaRD, 28%). Maintenance was prescribed to 286 patients with regimens including lenalidomide ± dexamethasone (65%), lenalidomide + proteasome inhibitor ± dexamethasone (22%), proteasome inhibitor ± dexamethasone (11%) and others (2%). Patient characteristics are summarised in table 1. The overall response rate was 93.9% (94.5% for single ASCT and 92% for tandem ASCT). The PFS at 3 years was 41.1% (single) and 45.7% (tandem) with median PFS 26 vs 35 months respectively (p=0.0621). Three year OS was 71.5% (single) and 83.8% (tandem), median OS 83 vs 89 months (p=0.0060). Both PFS and OS were improved with the use of maintenance therapy, regardless of single vs tandem transplant. PFS at 3 years was 52.1% for those receiving maintenance therapy compared to 21.7% for no maintenance (median 42 vs 16 months, p Conclusions: Tandem ASCT does improve outcomes for MM with high-risk cytogenetics. However, the main benefit was seen in patients who did not receive maintenance therapy. Our data demonstrate the potent anti-myeloma effect of post-ASCT maintenance and raise the question of the optimal role of tandem ASCT in the modern treatment era. Disclosures Duggan: Novartis: Honoraria; Amgen: Consultancy; Celgene: Consultancy; Astra Zeneca: Consultancy; Jannsen: Consultancy. Reece:Janssen, Bristol-Myers Squibb, Amgen, Takeda: Consultancy, Honoraria; Janssen, Bristol-Myers Squibb: Membership on an entity's Board of Directors or advisory committees; Merck: Honoraria, Research Funding; Otsuka: Research Funding. Song:Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Research Funding; Gilead: Honoraria, Membership on an entity's Board of Directors or advisory committees; GlaxoSmithKline: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene/BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen, Celgene,Takeda: Consultancy, Honoraria; Otsuka: Honoraria. Jimenez-Zepeda:Janssen, Celgene, Amgen, Takeda: Honoraria. McCurdy:Celgene: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Sanofi: Honoraria; GSK: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Janssen: Consultancy, Honoraria. Louzada:Celgene: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria; Janssen: Consultancy, Honoraria. Mian:Takeda: Consultancy, Honoraria; Celgene: Consultancy; Janssen: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Sanofi: Consultancy. Sebag:Celgene: Honoraria; Takeda: Honoraria; Amgen: Honoraria; Janssen: Honoraria, Research Funding. White:Takeda: Honoraria; Sanofi: Honoraria; Janssen: Honoraria; Celgene: Honoraria; Amgen: Honoraria; Karyopharm: Honoraria; Antengene: Honoraria; GSK: Honoraria. Stakiw:Lundbeck: Honoraria; Celgene: Honoraria; BMS: Honoraria; Roche: Research Funding; Janssen: Honoraria, Research Funding; Amgen: Honoraria; Novartis: Honoraria. Leblanc:Celgene Canada; Janssen Inc.; Amgen Canada; Takeda Canada: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding. Kotb:Takeda: Honoraria; Sanofi: Research Funding; Janssen: Honoraria; Amgen: Honoraria; Celgene: Honoraria; Karyopharm: Current equity holder in publicly-traded company; Merck: Honoraria, Research Funding. Venner:Janssen, BMS/Celgene, Sanofi, Takeda, Amgen: Honoraria; Celgene, Amgen: Research Funding.

Adaptive T cell therapy using chimeric antigen receptor (CAR) T cells and bispecific T cell engagers (BiTEs) have demonstrated encouraging responses in heavily pre-treated multiple myeloma (MM) patients. However, the cellular and molecular predictors of clinical response are not fully understood as well as the mediators of acquired resistance remain elusive. Local immune suppression and T cell exhaustion are important mediators of responses therefore, it is plausible to speculate that a tolerant tumor microenvironment and the expansion of specific T cell populations may dictate clinical responses. In this study, we performed at the single cell level a broad immunophenotypic and transcriptomic characterization of the blood and bone marrow (BM) T cells of sensitive and resistant MM patients treated with adaptive T cell therapies. Using cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) we measured the expansion of variable T cell subsets, T cell specific activation and inhibitor markers and their functional states in order to identify cellular mediators of resistance to these adoptive immune therapies. Serial blood samples and BM aspirates (n=12) were collected from patients treated with anti-BCMA CAR-T or BCMA-CD3 BiTEs at variable time points, prior and post initiation of therapy and at relapse. Bone marrow mononuclear fractions were isolated through ficoll density gradients coupled with magnetic sorting of CD3pos T cells. Unbiased mRNA profiling coupled with feature barcoding technology for cell surface protein (TotalSeq-B) of BM CD3pos T cells was then performed by using the chromium single cell (10x Genomics). Paired-end sequencing was performed on Illumina platform. Cell Ranger and Seurat pipeline were used for sample de-multiplexing, barcode processing, single-cell 3′ gene counting, cell surface protein expression and data analysis. CAR-T cells were identified by the expression of the chimeric CAR-T cell transcript. The parallel measurement of transcripts and cell surface protein phenotypes of CD3pos T cells using a panel of 19 immune surface markers underlined the T cell repertoire diversity and identified different T cell subsets among the CD8pos and CD4pos T cells. Notably, the cell surface protein information overlaid on the transcript-generated UMA allowed accurate identification of all main immune clusters, in particular for the CD45RA and CD45RO positive cells. Comparison of CITE-Seq features revealed that the T cells composition of the blood and BM niches differed significantly between sensitive and resistant patients. As such an enrichment of CD4pos T cells with a higher CD4:CD8 ratio was noted in responding patients. Phenotypic (CD45RA, CD45RO, CD95, CCR7, CD62L, CD28, CD27) and transcriptional signatures (TCF7, LEF1, GATA3, EOMES, TBX21, PRDM1) also identified a higher proportion of memory like T cells (Tscm, Tcm) in responding patients. In contrast, T cells of resistant patients were enriched with terminally exhausted (Tex) and senescent cells with loss of CD28, high GMZHand GMZB, CD57pos, CD69pos and CD160pos as well as upregulation of TBX21. Expression of T cell checkpoint inhibitors such as LAG3, TIGIT and PD1 was high in these Tex cells as well as in some Tem. Of note, ex vivo T cell activation studies with TIGIT blockade demonstrated T cell activation in an autologous MM and T cell co-culture system with enhanced MM cells death. An expanded cluster of regulatory T cells (Treg) FOXP3pos,CD25pos was also observed in two resistant patients. Of note, no loss of BCMA transcript or surface expression was noted in MM cells at the time of acquired resistance. Single cell transcriptome of primary MM cells and chromatin accessibility (ATAC-seq) analyses of T cells of these patients are ongoing to investigate the transcriptional programs and epigenetic factors underlying the immune escape. Combined single cell features profiling of the transcriptome and surface protein expression of T cells from MM patients receiving BCMA targeted CAR-T or BiTEs therapies revealed potential mediators of resistance. In particular, T cells composition (low CD4:CD8 ratio and reduced population of Tscm, Tcm) along with an enrichment of terminally exhausted T cells are the main features observed in resistant patients. Delineating these mechanisms will guide future T cells engineering studies to enhance the efficacy and response durability of adoptive immunotherapy in MM. Disclosures McCulloch: Amgen: Honoraria; Sanofi: Honoraria; Celgene: Honoraria; Janssen: Honoraria. Duggan:Jannsen: Consultancy; Amgen: Consultancy; Novartis: Honoraria; Celgene: Consultancy; Astra Zeneca: Consultancy. Jimenez-Zepeda:Janssen, Celgene, Amgen, Takeda: Honoraria. Bahlis:AbbVie: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; GSK: Consultancy, Honoraria; Genentech: Consultancy, Honoraria; BMS/Celgene and Janssen: Consultancy, Honoraria, Other: Travel, Accomodations, Research Funding; Karyopharm Therapeutics: Consultancy, Honoraria; Sanofi: Consultancy, Honoraria. Neri:Celgene/BMS: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Amgen: Consultancy, Honoraria.

Introduction Lenalidomide maintenance following autologous stem cell transplant (ASCT) remains a standard of care among transplant eligible patients with newly diagnosed multiple myeloma (NDMM). Many previous clinical trials done in patients following one prior line of therapy either excluded patients progressing on lenalidomide or included a very small proportion of these patients. Given the paucity of data in this setting, the optimal management of patients progressing on lenalidomide maintenance remains unknown. Daratumumab-containing triplet regimens have recently been introduced for these patients, typically in combination with pomalidomide (DPd), lenalidomide (DRd), or bortezomib (DVd). To our knowledge, there is no prospective data to allow comparison of the efficacy of these three regimens in patients progressing on lenalidomide maintenance, which is an increasingly common clinical scenario. Understanding the comparative efficacy, tolerability and toxicity of these regimens in patients progressing on lenalidomide maintenance in the 'real-world' is needed in order to help clinicians make appropriate decisions and guide future studies. Methods The Canadian Myeloma Research Group Database (formerly known as the Myeloma Canada Research Network Database, MCRN-DB) is a prospectively maintained disease specific database with over 7000 patients enrolled from 14 academic sites across Canada with legacy data collected from 2007. The Munster Myeloma database collects myeloma specific information in a German academic center and currently contains data from 800 patients collected from 2005. All consecutive patients treated with daratumumab based regimens in second line following relapse on lenalidomide maintenance were included in the analysis from the two databases analyzed up to 30/06/2020. Results A total of 1380 NDMM patients on lenalidomide maintenance post autologous stem cell transplant were identified in the two databases. From them, 73 patients were included in this analysis as they were treated with daratumumab containing regimen in second line. Specifically, 18 (24.7%) of these patients were treated with DPd, 32 (43.8%) patients with DRd, and 23 (31.5%) patients with DVd. The baseline characteristics, maintenance details, post-maintenance response rates and toxicity for each regimen are shown in Table 1. The median follow-up for the cohort from the time of daratumumab initiation was 8.3 months (range 0.4 - 40.0). Although, a higher proportion of patients in the DPd arm obtained a CR/VGPR compared to DRd or DVd, it did not reach statistical significance (p-value 0.06). The median PFS of the entire cohort was 16.96 months (95% CI 11.47-23.44). The median PFS of the individual regimens was as follows: DPd 17.65 months, DRd not reached and DVd 11.47 months as demonstrated in Figure 1 (p-value =0.46). Conclusion In summary, our results show that daratumumab-based regimens are effective among patients progressing on lenalidomide maintenance in the real world. Despite the small sample size, the results presented here are in line with recent sub-analyses of phase III studies examining the common daratumumab-based regimens used in this setting (CASTOR with median PFS of DVd between 7.8 months in all lenalidomide refractory patients and 27 months in all patients in first relapse; MM014 with median PFS of DPd after lenalidomide refractoriness of 21.8 months). The efficacy of DRd, in which daratumumab is added to an increased dose of lenalidomide, is notable and warrants further evaluation to identify which patients are most likely to benefit. Additional studies with longer follow-up are required to assess the optimal daratumumab-based regimen to be used in this growing population of patients relapsing after lenalidomide maintenance. Disclosures Mian: Janssen: Consultancy, Honoraria; Celgene: Consultancy; Takeda: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Sanofi: Consultancy. Venner:Celgene, Amgen: Research Funding; Janssen, BMS/Celgene, Sanofi, Takeda, Amgen: Honoraria. Jimenez-Zepeda:Janssen, Celgene, Amgen, Takeda: Honoraria. McCurdy:Sanofi: Honoraria; GSK: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria. Sebag:Celgene: Honoraria; Takeda: Honoraria; Amgen: Honoraria; Janssen: Honoraria, Research Funding. Song:Celgene: Research Funding; Celgene, Janssen, Amgen, Takeda: Honoraria. Leblanc:Celgene: Research Funding; Celgene Canada; Janssen Inc.; Amgen Canada; Takeda Canada: Membership on an entity's Board of Directors or advisory committees. White:Karyopharm: Honoraria; Antengene: Honoraria; GSK: Honoraria; Takeda: Honoraria; Sanofi: Honoraria; Janssen: Honoraria; Celgene: Honoraria; Amgen: Honoraria. Stakiw:Roche: Research Funding; Celgene: Honoraria; Lundbeck: Honoraria; Amgen: Honoraria; Janssen: Honoraria, Research Funding; Novartis: Honoraria; BMS: Honoraria. Louzada:Janssen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Takeda: Consultancy, Honoraria. Kotb:Karyopharm: Current equity holder in publicly-traded company; Celgene: Honoraria; Janssen: Honoraria; Amgen: Honoraria; Takeda: Honoraria; Merck: Honoraria, Research Funding; Sanofi: Research Funding. Reece:Janssen: Consultancy, Honoraria, Research Funding; Karyopharm: Consultancy; Amgen: Consultancy, Honoraria; Millenium: Research Funding; BMS: Research Funding; Takeda: Consultancy, Honoraria, Research Funding; Merck: Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Otsuka: Research Funding.

Using laser microdissection and mass spectrometry (MS)-based proteomics, we subtyped amyloid deposits from 130 cases of hepatic amyloidosis. Although we confirmed that immunoglobulin light chain amyloidosis was the most frequent cause of hepatic amyloidosis, leukocyte cell-derived chemotaxin 2 (LECT2) amyloidosis (ALect2) accounted for 25% of cases. This novel finding was associated with Hispanic ancestry, incidental discovery of amyloid in liver specimens sampled for other unrelated conditions, and a characteristic pattern of hepatic amyloid deposition. Although ALect2 patients had a common LECT2 polymorphism, pathogenic mutations were not discovered, suggesting that constitutive or compensatory LECT2 overexpression led to ALect2 deposition. These findings indicate that ALect2 is a common cause of hepatic amyloidosis in the population of the United States, and subtyping hepatic amyloid deposits by an accurate analytic method such as MS is required for optimal clinical management of hepatic amyloidosis patients and to avoid incorrect and unnecessarily toxic therapies.

Introduction Relapses of diffuse large B-cell lymphoma typically occur within 2-3 years and only 10% of these patients reach a 3-year progression-free survival compared to 65% at diagnosis. Our ability to distinguish patients at risk for relapse remains based on clinical staging. We hypothesized that identifying genetic alterations in serial tumour biopsies at diagnosis and relapse would improve our ability to identify high-risk patients, make therapeutic selections and reveal molecular markers for chemo-immunotherapy resistant tumours. However, relatively few relapsed/refractory biopsies have been sequenced. A unique, clinically annotated, Nordic DLBCL cohort was used to identify significantly mutated genes, assess potential driver genes, comprehensively examine clonal evolution, and gauge the importance of clinical relapsed sampling. Methods To address the lack of information on the molecular foundations of relapsed/refractory DLBCL, we performed whole exome sequencing (WES) on 42 DLBCL cases, with 34% representing relapsed/refractory biopsies and 13 serially sample cases. Enriched with relapsed/refractory diffuse large B-cell lymphoma cases, we performed multiple computational analyses to identify significantly mutated genes (MutSig2CV), mutational signatures (NMF and DeConstructsSig), driver genes (IntOgen and CADD), clonal evolution architecture (SciClone and ClonEvol), druggable gene analysis (DGIdb), and HLA-inference and mutation calling (Polysolver). Results Clonal evolution analysis of 13 paired diagnostic and relapsed biopsies revealed that relapsed/refractory biopsies have remarkable similarities to diagnostic biopsies and often present with late divergent clonal evolution of the tumor. Mutational analysis of 18 serially sampled tumors determined that in the majority of cases druggable oncogenic variants do arise at relapse. In addition, time to relapse correlated with divergence of mutations from the diagnostic biopsy. In addition to being identified as a significantly mutated gene, mutations in HLA-A had an increased incidence in cases that ultimately relapsed. This result led to an in-depth investigation into the mutational prevalence, timing, impact on prognosis, and loss of heterozygosity in the human leukocyte antigen (HLA) haplotypes of relapsed/refractory DLBCL. HLA-A mutagenesis and loss of heterozygosity was discovered as mechanisms of immune evasion in cases that go on to relapse from R-CHOP like therapies (Figure 1). Conclusions Our results yield insight into the development of chemo-immunotherapy resistant diffuse large B-cell lymphoma, and highlight the clinical importance of sampling relapsed biopsies. Analysis of immune evasion through MHC Class I/II, specifically HLA-A, may provide better characterization of patients for relapse prediction. In the age of personalized medicine it will be instrumental to determine if relapsed biopsies offer additional insight for salvage therapy treatment. Divergence of biopsies, as characterized by shared genomic mutations, increase with time and the majority of cases present with new alterations in druggable genes post-therapy. Disclosures Leppa: Roche: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Celgene: Consultancy; Bayer: Research Funding. Holte:Novartis: Honoraria, Other: Advisory board.

BACKGROUND: Phase 3 trials and a meta-analysis have demonstrated that Lenalidomide (Len) administration as maintenance improves the PFS and OS after ASCT performed as part of 1st line therapy. In addition, retrospective and registry studies have suggested efficacy when post-ASCT maintenance is administered after salvage ASCT in relapsed patients. Len maintenance has become the standard approach in many centres, including in Canada where it is routinely funded after 1st line ASCT and Len-base regimens are often used as maintenance after salvage ASCT in pts who have not progressed on this agent previously. The optimal management of patients (pts) progressing on this highly effective agent is less clear, however. We utilized the MCRN Database to investigate which regimens were utilized after pts progressed on Len-based therapy (post-Len Rx) and the outcomes observed with such regimens in the real-world Canadian setting. We included pts receiving Len-based regimens as maintenance following ASCT performed as part of 1st, 2nd or 3rd line therapy in this analysis, as ASCT pts are relatively young and generally tolerate combination regimens for relapsed myeloma well. METHODS: The MCRN Database is an ongoing national Canadian web-based repository of detailed information on over 6000 myeloma patients from 13 academic centres dating back to 2007. In this analysis, we evaluated the characteristics of pts progressing on post-ASCT Len-based maintenance following a transplant performed as part of the first 3 regimens administered. Pts were treated between 01/2007 until 04/2019; 305 pts had undergone 1 ASCT, 59 pts had 2 ASCTs. The next -line therapy administered at this time (post-Len Rx) was classified based on the novel agent utilized. Overall response rates (ORR), PFS from start of post-len Rx to next progression and OS (calculated from post-Len Rx to death) was calculated for these pts. Categorical comparisons were performed using the chi-square test and continuous ones using ANOVA. Survival rates were calculated using the Kaplan-Meier product-limit method; comparisons among regimens were made using the log-rank statistic. RESULTS: We identified 364 pts who had progressed on Len-based regimens given for maintenance, after ASCT, including 306 after 1st line ASCT, 51 after 2nd line ASCT and 7 after 3rd line ASCT. Len-based maintenance included Len alone in 318, Len + dex in 24 and other Len-combinations in 22. Median age was 59 yrs, 58% were male, 43.6% of 243 evaluable pts had high-risk FISH cytogenetics (del 17p, t[4;14], t[14;16]). Median creatinine was 85 µmol/L (32-832), LDH 187 U/L (55-906) and B2M 295 nmol/L (1.8-3805). Post-Len Rx was based on bortezomib (BTZ) in 56 (15%), carfilzomib (CFZ) in 44 (12%), daratumumab (Dara) in 45 (12%), pomalidomide (POM) in 28 (8%), ixazomib (IXA) in 23 (6%), and other regimens in 27 (7%). Thirty-seven (10%) did not receive any post-Len therapy while 104 (28%) received further Len-based therapy with the addition of Dex alone in 73, or with an additional agent (BTZ, cyclophosphamide [Cy] and/or clarithromycin) in 31 (Table 1). The only significant difference in pt characteristics was a higher LDH value in the IXA and POM groups (p=0.0015). The median PFS of 327 patients who received treatment for progression on Len-based maintenance was 11 months (mos) (95% CI 8.1-13.9); OS was 39 mos (95% CI 31-60) from post-Len Rx. For the 92 (42%) pts with high-risk FISH, the median PFS was 7.9 mos (95%CI 5.3 -11.5) and OS 33 mos (95%CI > 23.7) compared with 11.9 mos (95%CI 8.1 -14.2) and 39.7 mos (95% CI>23.9) respectively, for standard-risk pts. The ORR, median PFS and OS of each regimen from the time of post-Len Rx are summarized in Table 1, Fig 1. CONCLUSIONS: 1) the median PFS with post-Len Rx in pts progressing on Len-based maintenance after ASCT as part of 1st, 2nd or 3rd line treatment was almost 1 year for all treated pts, with longer benefit observed in pts treated with the newer proteasome inhibitors or Dara-based regimens; 2) since there was potentially confounding overlap among the agents in used in each treatment group studied-- and the 1st, 2nd and 3rd line transplant settings involved different time points in the disease course--further subset analyses of specific regimens/settings are ongoing; 3) nevertheless, the overall real-world results observed with newer agents approximate the outcomes reported in clinical trials in pts progressing on Len-based regimens after 1-3 prior lines of therapy. Disclosures Reece: Celgene: 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; Merck: Research Funding; Takeda: Consultancy, Honoraria, Research Funding; BMS: Research Funding; Karyopharm: Membership on an entity's Board of Directors or advisory committees, Research Funding; Otsuka: Research Funding; Amgen: Consultancy, Honoraria, Research Funding. McCurdy:Celgene: Honoraria; Janssen: Honoraria. Song:Celgene: Honoraria, Research Funding; Janssen: Honoraria; Amgen: Honoraria; Takeda: Honoraria. Leblanc:Janssen: Membership on an entity's Board of Directors or advisory committees; Amgen: 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; Takeda: Membership on an entity's Board of Directors or advisory committees. Sebag:Amgen: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees. White:Takeda: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Sanofi: Consultancy, Honoraria. Stakiw:Janssen: Honoraria, Research Funding, Speakers Bureau; BMS: Honoraria; Amgen: Honoraria, Speakers Bureau; Novartis: Honoraria, Speakers Bureau; Celgene: Honoraria, Speakers Bureau; Roche: Research Funding; Lundbeck: Honoraria; Sanofi: Honoraria. Louzada:Janssen: Consultancy, Honoraria; Bayer: Honoraria; Celgene: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria; Amgen: Consultancy, Honoraria. Kotb:Merck: Honoraria, Research Funding; Janssen: Honoraria; Amgen: Honoraria; Karyopharm: Equity Ownership; Celgene: Honoraria; Takeda: Honoraria. Venner:Sanofi: Honoraria; Janssen: Honoraria; Amgen: Honoraria, Research Funding; Takeda: Honoraria; Celgene: Honoraria; J&J: Research Funding. OffLabel Disclosure: This abstract describes several combinations not specifically approved by the FDA but utilized in the real-world setting. However, all of the individual drugs in these combinations have been approved as single agents or in other combinations.

Lenalidomide in combination with dex (Len + dex) was introduced as treatment for relapsed/refractory myeloma in Canada over a decade ago; more recently, Len has been routinely available as part of first-line therapy, both in transplant-eligible patients-- as post-ASCT maintenance--and in transplant-ineligible patients as the Len + dex combination, and is typically given until disease progression. The management of patients progressing on Len regimens is evolving as newer anti-myeloma drugs become available. Many questions remain regarding the sequencing of treatments to obtain the longest periods of disease control between repeated relapses. We utilized the national Myeloma Canada Research Network (MCRN) Database to analyze therapy administered immediately after progression on a Len-based regimen in real-world practice. The MCRN Database contains disease-specific information on over 6000 patients reported from 13 academic centres in Canada. Between 2007 and 2019, 1482 patients (pts) progressed on Len-containing regimens in lines 1-3. 57% were male, 23% had light chain myeloma, 38% had high-risk FISH and 43% had undergone prior ASCT. Median values (range) for other pt characteristics included: age 64 range (31-92) yrs, creatinine 93 µmol/L (32-2700), B2M 329 nmol/L (range 1-7193), Hb 104 g/L (3-169), WBC 5.7 (0.12-107.6), platelets 211 (10-832), LDH 191 U/L (55-1908). The next regimen was based on bortezomib (BTZ) in 370, as part of a triplet in 278 (CyBorD, VMP); carfilzomib (CFZ) in 100, triplet in 62(KCD, KRD, KPD); ixazomib (IXA) in 75, triplet in 63 (IxaCD, IxaRD, IxaPomD); daratumumab (Dara) in 80, triplet in 75 (DaraCD, DaraRD, DaraPomD, DaraVD, DaraKD); pomalidomide (POM) in 195, triplet in 79 (PomCD/P, PomVD, PomKD); and continuation of Len in 212, triplet in 124 (RCD, RVD, RVCD). 346 (23%) did not receive any further therapy, including 79 (15%) after 1st line Len, 199 (26%) after 2nd line Len and 68 (33%) after 3rd line Len; other regimens were used in 6%, 18% and 11% of each group, respectively. The overall response rates (ORR)/median duration of treatment in months (mos) for each of the regimens included: BTZ 67%-5.8 mos; CFZ 70%-5.6 mos; IXA 60%-6.7 mos; Dara 86%-6.9 mos; POM 36%-4.0 mos; Len 39%-5.7 mos; and other 48%-3.3 mos. PFS by regimen is shown in Figure 1. 514 pts had progressed after Len as 1st line therapy, 766 after Len as 2nd line therapy and 202 after Len as 3rd line therapy. Median follow-up was 15 mos (1-130) after 1st progression and 55 mos (1-278) from diagnosis. The median PFS (95% CI) and OS (95% CI) after progression following Len as 1st line therapy were 14.5 mos (12.1-17.3) and 31.2 mos (25.3-39.0), as 2nd line therapy 8.6 mos (7.3-9.8) and 14.1 mos (11.6-16.5); and as 3rd line therapy 8.0 mos (6.7-9.9) and 11.0 mos (6.9-14.1), respectively. Figure 2 shows PFS by prior Len subgroup. More detailed analyses to assess outcomes for specific regimens after Len progression in different lines of therapy are in progress. In summary, this analysis provides an overview of treatment patterns following progression on Len in Canada, as well as the ORR, PFS and OS of different regimens. Results appeared better for proteasome inhibitor and Dara regimens after progression on Len, although some pts derived benefit from further Len regimens as well as POM-based ones; further exploration of specific treatment subgroups is ongoing. These data provide benchmarks for real-world outcomes that can be utilized as newer therapies, such as those based on immunotherapy, become available. Disclosures Reece: Amgen: Consultancy, Honoraria, Research Funding; Merck: Research Funding; BMS: Research Funding; Takeda: Consultancy, Honoraria, Research Funding; Otsuka: Research Funding; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Karyopharm: 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. McCurdy:Janssen: Honoraria; Celgene: Honoraria. Song:Janssen: Honoraria; Celgene: Honoraria, Research Funding; Amgen: Honoraria; Takeda: Honoraria. Sebag:Takeda: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees. Leblanc:Janssen: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding. Louzada:Celgene: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria; Bayer: Honoraria; Janssen: Consultancy, Honoraria; Amgen: Consultancy, Honoraria. White:Celgene: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Sanofi: Consultancy, Honoraria; Takeda: Consultancy, Honoraria. Stakiw:Janssen: Honoraria, Research Funding, Speakers Bureau; Roche: Research Funding; BMS: Honoraria; Novartis: Honoraria, Speakers Bureau; Amgen: Honoraria, Speakers Bureau; Celgene: Honoraria, Speakers Bureau; Lundbeck: Honoraria; Sanofi: Honoraria. Kotb:Karyopharm: Equity Ownership; Amgen: Honoraria; Merck: Honoraria, Research Funding; Celgene: Honoraria; Janssen: Honoraria; Takeda: Honoraria. Venner:J&J: Research Funding; Takeda: Honoraria; Sanofi: Honoraria; Celgene: Honoraria; Janssen: Honoraria; Amgen: Honoraria, Research Funding. OffLabel Disclosure: This abstract describes several combinations not specifically approved by the FDA but utilized in the real-world setting. However, all of the individual drugs in these combinations have been approved as single agents or in other combinations.

Cyclophosphamide, bortezomib, and dexamethasone (CyBorD) is highly effective in multiple myeloma. We treated patients with light chain amyloidosis (AL) before stem cell transplantation (ASCT), instead of ASCT in ineligible patients or as salvage. Treatment was a combination of bortezomib (1.5 mg/m2 weekly), cyclophosphamide (300 mg/m2 orally weekly), and dexamethasone (40 mg weekly). Seventeen patients received 2 to 6 cycles of CyBorD. Ten (58%) had symptomatic cardiac involvement, and 14 (82%) had 2 or more organs involved. Response occurred in 16 (94%), with 71% achieving complete hematologic response and 24% a partial response. Time to response was 2 months. Three patients originally not eligible for ASCT became eligible. CyBorD produces rapid and complete hematologic responses in the majority of patients with AL regardless of previous treatment or ASCT candidacy. It is well tolerated with few side effects. CyBorD warrants continued investigation as treatment for AL.

Introduction Monoclonal gammopathy of clinical significance (MGCS) is a newly described entity that defines clinical conditions and organ damage resulting from the effects of monoclonal proteins (Fermand et al., 2018). In MGCS, the underlying clone burden resembles an MGUS state, and does not meet criteria for multiple myeloma or lymphoma. A wide spectrum of conditions has been described in MGCS (Fermand et al., 2018). In this retrospective study, our purpose was to identify the incidences of patients with MGCS at our hematology clinics. Methods We collaborated with three clinicians who see the majority of MGUS patients at the University of Calgary Medical Group clinics (UCMG). Patients who were referred and diagnosed with MGUS at the hematology clinic at UCMG since 2014 were assessed. The diagnosis of MGUS and MGCS were made based on consensus criteria (Rajkumar et al., 2014) and the recent publication (Fermand et al., 2018). Retrospective chart reviews were performed and cases with MGCS were analyzed. MGUS risk stratification score was calculated per previous reports (Katzmann et al., 2013; Kyle et al., 2018). Hematological response was assessed using the International Myeloma Working Group criteria (Rajkumar et al., 2014), and renal response was measured using KDIGO guidelines (Radhakrishnan & Cattran, 2012). Results A total of 606 MGUS patients were seen at our clinic from February 2014 to June 2018. Patients who had MGUS and co-existing conditions which met MGCS criteria (Fermand et al., 2018) were evaluated. There were 25 MGCS patients identified. Median age at diagnosis was 60, and 28% were female. Clinical characteristics are outlined in Table 1. Three patients had light chain MGUS. Among the non-light chain MGUS patients, there were 11 high-intermediate risk (55%), 1 intermediate risk (5%), 5 low-intermediate risk (25%), and 3 low risk MGUS (15%). At the time of analysis all patients were alive, and 3 patients have progressed. Median follow up was 2 years (0-16 years). Renal involvement was the most common with 14 patients having biopsy proven renal pathologies that met criteria for monoclonal gammopathy of renal significance (MGRS) (Leung et al., 2012). Four patients had neuropathies, including Anti-MAG, chronic inflammatory demyelinating polyneuropathy (CIDP), distal acquired demyelinating symmetric neuropathy (DADS-M), and autonomic neuropathy. Three patients had skin manifestations (Schnitzler syndrome, necrobiotic xanthogranuloma, scleromyxedema), 1 patient had corneal involvement (crystalline keratopathy), 1 patient had gastrointestinal manifestation (mixed light chain deposition disease), 1 patient had acquired C1 esterase inhibitor deficiency with angioedema, and 1 patient was diagnosed with Sweet syndrome in 1993 which had led to her original monoclonal gammopathy workup. Five out of the 14 patients with MGRS received plasma cell directed chemotherapy, and 1 patient with crystalloid podocytopathy underwent auto-stem cell transplant. Of these 5 patients, 4 had renal response. Treatment for other MGCS cases are indicated in Table 1. Discussion and Conclusion Our series demonstrates that cases of MGCS represent a small minority within our larger MGUS cohort. The most common organ involvements seen in our MGCS patients were renal, nerve and skin. One of the major diagnostic challenges is confirming that the organ dysfunction and MGUS co-exist by true association, and not by coincidence. In our patient cohort, tissue biopsies were obtained when possible (all renal, skin, and GI cases), and others were diagnosed through review with local experts and relying on published literature. The distinction of MGCS from MGUS is important, as it may change treatment decisions. In renal diseases associated with monoclonal gammopathy, referred to as MGRS, renal prognosis is poor and clone directed treatment is associated with improved renal outcomes (Fermand et al., 2013). As prospective or randomized trials are unavailable for MGRS or MGCS, the treatments given at our center were determined on a case-by-case basis relying on expert opinions, local experiences, and a recent guideline (Fermand et al., 2013). Interdisciplinary care is required for both the diagnosis and management of MGCS. Further studies with long term follow-up are needed. Disclosures McCulloch: Takeda: Other: Travel expenses; Celgene: Honoraria. Neri:Janssen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria.

Background: The addition of immunomodulatory (IMiDs) drugs to monoclonal antibodies targeting the transmembrane glycoprotein CD38 has demonstrated very encouraging and durable responses in myeloma patients. It is believed that the synergistic effects observed with anti-CD38 antibodies and IMiDs are derived from their co-modulation of the host adaptive and innate immunity and therefore it is plausible to speculate that acquired resistance to daratumumab and IMiDs may be largely immune-mediated. The aim of the present study was to 1) interrogate at the single cell level the bone marrow immune repertoire of daratumumab sensitive and resistant patients, 2) identify cellular mediators of resistance to anti-CD38 antibodies and 3) define potential means to reinstate sensitivity to daratumumab and IMiDs. Methods and Results: Serial BM aspirates (n=44) were collected from patients treated with single agent daratumumab (MMY3012 trial) or daratumumab + pomalidomide (MM014 trial) prior to initiation of therapy, C3D1 and at relapse. Bone marrow mononuclear fractions were isolated through ficoll density gradients coupled with magnetic sorting of CD138pos and CD138neg cells. Unbiased mRNA profiling of BM CD138neg cells was performed by single-cell RNA-seq (scRNA-seq) using the GemCode system (10x Genomics). Paired-end sequencing was performed on Illumina NEXTseq and NOVAseq platforms. Cell Ranger Single and Seurat were used for sample de-multiplexing, barcode processing, single-cell 3′ gene counting and data analysis. Sequencing data were analyzed by principal component analysis (PCA), clustering with multi-sample batch correction and then visualized by t-distributed stochastic neighbor embedding (t-SNE) projection. Comparison of the single cell transcriptomes of CD138neg cells from responding patients pre- and post- treatment revealed that Daratumumab and Pomalidomide dramatically modify the immune cells composition (immunome) of the bone marrow niches leading to: 1) expansion of effector T cells (KLRG1high, GZMAhigh, CCL5high), 2) significant depletion of CD38high / FCGR3Ahigh NK cells with retained population of cytotoxic NK cells (CD27high, KLRB1high, NCR3high, GZMApos, PRF1pos), 3) depletion of FCGR3Ahigh / CD14low monocytes, 4) expansion of M1 inflammatory macrophages and depletion of plasmacytoid dendritic cells. Similar changes were seen in patients treated with single agent daratumumab (without IMiDs) however with a lesser expansion of effector T cells and in particular reduced marrow infiltrating inflammatory macrophages. In contrast, the immunome of daratumumab and pomalidomide resistant patients was characterized by a reduced central memory T cells (TCM), and a largely exhausted effector T cells populations that are CD28neg and expressing checkpoint inhibitors (LAG3and TIGIT significantly more than PDCD1) as well as high expression of TIM3 (HAVCR2) on marrow macrophages. Upregulation of LAG3 and TIGIT expression on T cells was also confirmed at the antigenic level by flow cytometry. Consistent with the non-bystander and suppressive effect of LAG3 and TIGIT on the function of effector T cells, activation (CD107a expression) and proliferation of LAGpos and/or TIGITpos sorted bone marrow T cells from resistant patients were significantly reduced in response to autologous myeloma cells stimulation or CD3/CD28 crosslinking. Lastly, a higher proportion and number of clonal T cell (through single cell TCR sequencing) was also observed in responding (≥ PR) vs non-responding (< PR) patients. Interrogation of the myeloma cells transcriptome, showed little to no loss of CD38 transcript at the time of acquired resistance with rather upregulation of complement inhibitory molecule CD59 and NFκB signature genes. Conclusion: A systematic unsupervised interrogation of the bone marrow immunome of daratumumab and IMiDs treated MM patients demonstrated a significant activation of adaptive and innate immunity in responding patients and revealed an expansion of exhausted T cells with upregulation of the checkpoint inhibitors LAG3 and TIGIT in resistant patients. Our findings warrant the exploration of LAG3- and/or TIGIT-blocking strategies as potential means to reinstate sensitivity to daratumumab and IMiDs in myeloma patients. Disclosures Neri: Janssen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria. McCulloch:Celgene: Honoraria; Takeda: Other: Travel expenses. Thakurta:Celgene Corporation: Employment, Equity Ownership. Bahlis:Celgene: Consultancy, Honoraria, Research Funding; Amgen: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Research Funding.

Introduction: Bortezomib-containing regimens (BCRs) have been the standard frontline approach for the treatment of transplant ineligible multiple myeloma (TIMM) patients in Canada for many years. Based on recent randomized clinical trial results lenalidomide and dexamethasone (Ld) has become another provincially funded option in Canada in the same therapeutic space. We aimed to compare the effect of BCRs and Ld for the treatment of TIMM using the newly-formed Myeloma Canada Research Network Multiple Myeloma Database (MCRN-MM-DB) project. This web-based centralized platform can track and characterize real-world outcomes of patients treated at major Canadian institutions and includes both legacy data dating back to 2007 (from 4 centres) as well as ongoing prospective data collection (from 11 centres) analyzed up to 01/07/18. Patients and Methods: The primary objective was to assess the ORR, PFS and OS for TIMM patients treated with CyBorD/CyBorP, Ld, VMP or VD/VP, each given as reported previously but with dose-adjustments at the discretion of the treating physician to maintain patients on therapy. The two-sided Fisher exact test was used to test for differences between categorical variables. Survival curves were constructed according to the Kaplan-Meier method and compared using the log rank test; a p value of Disclosures Arleigh: Celgene: Honoraria; Janssen: Honoraria. Sebag:Janssen Inc.: Membership on an entity's Board of Directors or advisory committees; Amgen Canada: Membership on an entity's Board of Directors or advisory committees; Takeda Canada: Membership on an entity's Board of Directors or advisory committees; Celgene Canada: Membership on an entity's Board of Directors or advisory committees. Leblanc:Celgene Canada: Membership on an entity's Board of Directors or advisory committees; Janssen Inc.: Membership on an entity's Board of Directors or advisory committees; Amgen Canada: Membership on an entity's Board of Directors or advisory committees; Takeda Canada: Membership on an entity's Board of Directors or advisory committees. Louzada:Janssen: Honoraria; Celgene: Honoraria; amgen: Honoraria; pfizer: Honoraria. Venner:Janssen: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Amgen: Honoraria; Takeda: Honoraria.

Introduction Monoclonal gammopathy of undetermined significance (MGUS) is a prevalent hematological condition among elderly population with incidence rates of 3% and 5% over the age of 50 and 70 years, respectively (Kyle et al., 2018). It is considered a premalignant state of multiple myeloma with a risk of progression of 1% per year. It has also been shown that MGUS patients have a shorter survival compared to the age- and sex-matched cohort (Kyle et al., 2018). Recent reports have highlighted the clinical significance of monoclonal gammopathy and the organ injury that may result from the effects of paraproteinemia (Fermand et al., 2018). With new insights into the significance of monoclonal gammopathy, the purpose of our study was to characterize the MGUS patient population referred at our hematology clinics by observing the reason for monoclonal protein testing and assessing patient comorbidities at the time of MGUS diagnosis. Methods We collaborated with three different clinicians who see the majority of MGUS patients at the University of Calgary Medical Group (UCMG) clinics. Patients who were referred and diagnosed with MGUS at the hematology clinic at UCMG since 2014 were assessed. Retrospective chart reviews were performed and reasons for monoclonal testing were recorded as indicated in referral request notes or initial consult notes. Data on patient comorbidities was collected as indicated in the initial consult notes. MGUS risk stratification was calculated per previous reports (Katzmann et al., 2013; Kyle et al., 2018) Results A total of 606 MGUS patients were seen at our clinic from February 2014 to June 2018. There were 565 patient charts available for complete review. 56% of the patients were male. Median age was 72 and median follow up was 2 years. MGUS risk stratification showed that 33.2% had low, 47.9% intermediate-low, 17.8% intermediate-high, and 1.2% high-risk MGUS. There were 55.5% IgG-MGUS, 20.5% IgM-MGUS, 12.3% IgA-MGUS, and 8.4% light chain-MGUS patients. 3% had biclonal gammopathy. Patient comorbidities at time of diagnosis are reported in table 1. The most common conditions were hypertension (50.4%), dyslipidemia (33.1%), chronic kidney disease (22.4%), diabetes (21.6%), coronary artery disease (18.6%), and solid tumors (14.6%). The most common solid tumors were prostate cancer (22/ 83, 25%), colon cancer (12/83, 14.4%), and breast cancer (10/83, 12.0%). Of the 565 patient charts, 140 had either missing referral sheets or had no record of the reasons for paraproteinemia investigations in the notes. In the rest of the 425 patients, the most common reason for monoclonal protein testing by referring physician was for renal dysfunction, which included work up for acute kidney injury, chronic kidney injury, proteinuria and hematuria. The next most common reason was work up of neuropathy, followed by anemia, and constitutional symptoms (figure 1). The patients in the 'Others' group had various reasons for testing including work up for seizure, forgetfulness, stroke, headache, chronic pancreatitis, multiple sclerosis, myasthenia gravis, family history of myeloma, history of venous thromboembolism, splenomegaly, bronchiectasis, chest pain, and as part of routine physical and blood donor testing. Discussion and Conclusion MGUS is often incidentally detected as part of a work up for other medical conditions, and our results reveal that there is a variety of reasons for which monoclonal testing is performed. With recent developments in our understanding of the significance of monoclonal gammopathy and its association with certain renal and organ damage (Fermand et al., 2018; Leung et al., 2012), there may be a change in how the paraproteinemia investigations are utilized by clinicians in different disciplines. It will be important to recognize and establish appropriate indications for testing. Furthermore, MGUS patients present with a wide range of comorbidities at the time of diagnosis. Interdisciplinary care will play a key role in discerning how much of the organ dysfunction and patients' symptoms are secondary to their underlying medical conditions versus the effect of monoclonal gammopathy. Disclosures McCulloch: Celgene: Honoraria; Takeda: Other: Travel expenses. Neri:Celgene: Consultancy, Honoraria; Janssen: Consultancy, Honoraria.

Background: A renewed interest in immune and cellular based therapeutics in multiple myeloma was recently fueled by the development of CD38 targeting monoclonal antibodies as well as the introduction of engineered CAR-T cells. Daratumumab treatment in myeloma patients was demonstrated to expand clonal CD8+T cells and T cell clonality was correlated with the depth of response consistent with a daratumumab mediated cytotoxic T cell effect. However the mechanisms behind this adaptive immune response and the identity of the T cell receptor (TCR) interacting with MHC presented tumoral peptide (pMHC) remains elusive. The large diversity of TCR combinations generated though somatic recombination of the VDJ gene sequences (~ 1015combinations) represents a major challenge for the accurate characterization of the antigen specific TCR. The aim of this study was to define the identity of the adaptive immune repertoire of the bone marrow infiltrating T lymphocytes (single cell TCR α/β paired sequencing) in myeloma patients treated to daratumumab and IMiDs based therapies. Methods and Results: BM aspirates from patients (n=24) treated with daratumumab single agent or in combination with pomalidomide or lenalidomide (MM014, MM3008 and MMY3012 trials) were collected post initiation of therapy (cycle 3, day 1) followed by magnetic beads sorting of CD3pos T cells from Ficoll generated mononuclear cell fractions. Using the 10x Genomics Single cell VDJ solution which combines single cell droplet microfluidics with 5' molecular barcoding, T cells from each patient were partitioned into droplets containing individual cells with primers specific for the constant region of the V(D)J locus allowing the PCR amplification and enrichment of α and β TCR individual cell barcoded cDNA. Paired-end sequencing was performed on Illumina NEXTseq platform. Cell Ranger VDJ pipeline was used for sample de-multiplexing, barcode processing and grouping of T cells into clonotypes with shared TCR α/β sequences. Of note, generated sequences span the full length of V-J genes (including CDR3) allowing faithful reconstruction of TCR transcripts. Consistent with the known high TCR diverse repertoire, we identified 32322 individual clonotypes corresponding to an average of 1346 clonotypes with paired α/β TCR sequences per patient. Clonotypes proportion (> 2%) and number of individual clonotypes did correlate with the depth of response (≥VGPR vs PR vs PD). Analysis of clonotype TCRs and CDR3 sequences identified 11 clonotypes with the exact paired CDR3 αβ sequences that were shared by at least 2 patients. Of interest the CDR3 sequence of one shared clonotype is predicted (https://vdjdb.cdr3.net) to bind an epitope derived for CD317 (also know as BST2 or HM1.24) previously demonstrated to be highly expressed on myeloma cells (Jalili A et al. Blood 2005). Both patients harboring this CD317 reactive T cell clone are in sCR for more than 2 years. Of note, TCRs that recognize the same peptide-MHC complexes do not always share the exact CDR3 sequences but rather have conserved CDR3 sequence features, rendering possible to predictively model epitope specificity. Indeed, recent studies demonstrated that similarity in CDR3 sequences (CDR3 differing by up to one amino acid) or shared CDR3 motifs of 2-4 amino acids in length, define the TCR clusters that are often contact points with the antigenic peptides. Such features in CDR3 sequences facilitates T cell target antigen discovery. Therefore, we applied the GLIPH algorithm (https://github.com/immunoengineer/gliph) to cluster the sequenced TCRs based on their high probability of sharing pMHC specificity owing to both conserved CDR3 motifs and global similarity in their CDR3 sequences. GLIPH grouped the TCRs sequences identified in our study into 171 unique clusters (with a minimum of 3 clones each) that are predicted to recognize the same pMHC ligands. Furthermore, it identified 26 CDR3 motifs that are elevated at least 10-fold over expected frequency in a naïve TCR reference pool (p Conclusion: Single cell TCR profiling identified unique clonotypes that are highly enriched in marrow infiltrating T cells and are predicted to be reactive with myeloma peptides. This work facilitates the future development of TCR engineered T cells targeting myeloma neoepitopes. Disclosures Neri: Celgene: Consultancy, Honoraria; Janssen: Consultancy, Honoraria. McCulloch:Takeda: Other: Travel expenses; Celgene: Honoraria. Bahlis:Janssen: Consultancy, Honoraria, Research Funding; Amgen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding.