Bergsagel, P. Leif

Clinical success with intravenous (IV) oncolytic virotherapy (OV) has to date been anecdotal. Here, we conducted a phase 1 clinical trial of systemic OV therapy and investigated the mechanisms of action in responding T-cell lymphoma (TCL) patients. A single IV dose of VSV-IFNβ-NIS was administered to patients with relapsed refractory hematologic malignancies to determine safety and efficacy across 4 dose levels (DL). Correlative studies were undertaken to evaluate viremia, virus shedding, virus replication and immune responses. Fifteen patients received VSV-IFNβ-NIS (7 multiple myeloma, 7 TCL, 1 acute myeloid leukemia); 3 patients were treated at each DL1 through DL3 (0.05, 0.17, and 0.5 x 1011 TCID50), and 6 at DL4 (1.7 x 1011 TCID50). There were no dose limiting toxicities. 3 of 7 patients with TCL had RECIST responses: a 3-month PR at DL2, a 6-month PR and a durable CR ongoing at 20 months at DL4. Viremia peaked at the end of infusion and no infectious virus shedding was detected. Plasma interferon-β levels, a biomarker of VSV-IFNβ-NIS replication, peaked between 4h and 48h post infusion. The patient with CR had robust viral replication with increased ell free DNA in her plasma, a very high peak IFNβ level of 18,213 pg/ml, a strong anti-VSV neutralizing antibody response, and increased numbers of tumor reactive T-cells. VSV-IFNβ-NIS as a single agent was effective in patients with TCL resulting in durable disease remissions in heavily pretreated patients. Correlative analyses suggest that responses may be due to a combination of direct oncolytic tumor destruction and immune-mediated tumor control. Further clinical testing is warranted. (This trial is registered at www.clinicaltrials.gov as NCT03017820).

Abstract Pivotal clinical trials of B-cell maturation antigen-targeted chimeric antigen receptor T (CART)-cell therapy in patients with relapsed/refractory multiple myeloma (MM) resulted in remarkable initial responses, which led to a recent US Food and Drug Administration approval. Despite the success of this therapy, durable remissions continue to be low, and the predominant mechanism of resistance is loss of CART cells and inhibition by the tumor microenvironment (TME). MM is characterized by an immunosuppressive TME with an abundance of cancer-associated fibroblasts (CAFs). Using MM models, we studied the impact of CAFs on CART-cell efficacy and developed strategies to overcome CART-cell inhibition. We showed that CAFs inhibit CART-cell antitumor activity and promote MM progression. CAFs express molecules such as fibroblast activation protein and signaling lymphocyte activation molecule family-7, which are attractive immunotherapy targets. To overcome CAF-induced CART-cell inhibition, CART cells were generated targeting both MM cells and CAFs. This dual-targeting CART-cell strategy significantly improved the effector functions of CART cells. We show for the first time that dual targeting of both malignant plasma cells and the CAFs within the TME is a novel strategy to overcome resistance to CART-cell therapy in MM.

Abstract Background: trALL is an important secondary primary malignancy (SPM) that has recently been appreciated. While patients (pts) with MM have an 8%-17% risk of developing an SPM while on lenalidomide (R) maintenance following autologous stem cell transplant (ASCT), trALL has been rarely observed. Little is known about the characteristics of trALL in pts with MM compared to pts who had other malignancies prior to the development of trALL. We define tALL as any prior exposure to cytotoxic chemotherapy and/or radiation for another malignancy, and herein, we report a comparative analysis of characteristics and outcomes of pts with trALL with and without MM from the Mayo Clinic Cancer Center (MCCC). Methods: We performed a systematic search in the 3-site MCCC registry and included all pts diagnosed and received at least 1 cycle of ALL-directed therapy and/or underwent allogeneic transplantation (AlloHCT) for ALL between 2007-2020. All cases of trALL in this series are B-ALL. Comparisons of characteristics between trALL patients with and without MM were made using a Wilcoxon rank sum test (continuous variables) or Fisher's exact test (categorical variables). Time-to-event variables were compared using unadjusted Cox proportional hazards regression models. Results: 70 trALL pts (14 MM [20%], 56 non-MM [80%]) were identified during the study period. The median age at trALL diagnosis was 63.9 (range 47-71) for MM pts and 63.1 (range 18.2-84) for non-MM pts. Median follow-up from trALL diagnosis was 1.42 years (range 0.02-10.6 years). The most common prior non-MM malignancies among tALL pts were breast (28.6%), lymphoma (17.9%), myeloid (17.9%), and GU/GYN (14.3%). Amongst the 14 MM pts, 100% (n=10) had ISS-I disease, 8 (57%) had IgG K MM, 1 (n=10) had high risk cytogenetics, 8 (57.1%) received R-based induction , 4 (28.6%) received CyBorD induction, 4(28.6%) received VRD induction, 3 (21.4%) received RD induction. 10 (71.4%) pts were actively on R when they developed trALL, 8 (57.1%) pts received prior ASCT. The median time to develop trALL following ASCT for MM was 46.3 months (m), (95% CI 20.4-67.6), 12 (85.7%) pts received R maintenance with a median duration of 53m (95% CI 16.9-121). The median time to develop trALL after initiation of R maintenance was 61.2m (95% CI 16.9-123.4). The most common trALL induction regimen received was HyperCVAD which was used in 71.4% of MM pts and 51.8% of non-MM pts. In comparison to non-MM pts, MM patients had a significantly lower WBC at diagnosis (Median: 2.0 vs. 5.8, P=0.005),no t(9;22) BCR/ABL1 cytogenetics (0.0% vs. 35.7%, P=0.008), a higher frequency of hypodiploid/near-triploid (Ho-Tri) cytogenetics (42.9% vs. 12.5%, P=0.009), and a lower frequency of prior radiation therapy (7.1% vs. 44.6%, P=0.012). MM pts had a higher frequency of AlloHCT for trALL (71.4% vs. 42.9%, P=0.075) and were more commonly in complete response (CR) at transplant (100.0% vs. 70.8%, P=0.078). No trALL in MM pts were Ph-like ALL. There was a statistically significant difference in time to development of trALL between previous malignancy locations (P=0.018), with GU/GYN (Median: 9 years) having the longest time and myeloid (Median: 3 years) having the shortest time; MM was 6 years. In the overall pt cohort, 56 (80%) pts achieved a complete response after induction and 60% (n=25) were minimal residual disease (MRD)+ after induction. Pts with MM had a significantly lower likelihood of being MRD+ after induction (OR=0.09, P=0.015). Overall, 24.3% of pts relapsed after induction therapy for trALL; 39 (55.5%) died after trALL diagnosis including 43% (n=35) who died after AlloHCT. Although pts with MM tended to have better outcomes compared to non-MM trALL pts in terms of overall survival after trALL diagnosis (Figure 1A), survival after AlloHCT (Figure 1B), relapse rate after trALL diagnosis and non-relapse mortality after AlloHCT, none of these findings were statistically significant in this small cohort (Figure 1C). Conclusion: trALL is a unique SPM that can occur in pts with MM. It is associated with Ho-Tri cytogenetics and is BCR/ABL1 negative. The majority of MM pts that developed trALL had undergone prior ASCT and were on R maintenance when they developed trALL. Despite being more likely to have adverse cytogenetics features, MM-associated trALL has similar survival compared to non-MM-associated trALL which speaks to the poor survival outcomes of this SPM. Further research on trALL in MM pts is merited. Figure 1 Figure 1. Disclosures Litzow: Amgen: Research Funding; Pluristem: Research Funding; AbbVie: Research Funding; Actinium: Research Funding; Astellas: Research Funding; Omeros: Other: Advisory Board; Jazz: Other: Advisory Board; Biosight: Other: Data monitoring committee. Bergsagel: Janssen: Consultancy. Fonseca: Scientific Advisory Board: Adaptive Biotechnologies: Membership on an entity's Board of Directors or advisory committees; Caris Life Sciences: Membership on an entity's Board of Directors or advisory committees; AbbVie: Consultancy; Patent: Prognosticaton of myeloma via FISH: Patents & Royalties; Bayer: Consultancy; Takeda: Consultancy; Celgene: Consultancy; Amgen: Consultancy; BMS: Consultancy; Mayo Clinic in Arizona: Current Employment; Juno: Consultancy; Kite: Consultancy; Aduro: Consultancy; OncoTracker: Consultancy, Membership on an entity's Board of Directors or advisory committees; GSK: Consultancy; Novartis: Consultancy; Merck: Consultancy; Sanofi: Consultancy; Pharmacyclics: Consultancy; Janssen: Consultancy. Dispenzieri: Takeda: Research Funding; Alnylam: Research Funding; Pfizer: Research Funding; Oncopeptides: Consultancy; Sorrento Therapeutics: Consultancy; Janssen: Consultancy, Research Funding. Murthy: CRISPR Therapeutics: Research Funding. Ailawadhi: GSK: Consultancy, Research Funding; Sanofi: Consultancy; Pharmacyclics: Consultancy, Research Funding; Takeda: Consultancy; Medimmune: Research Funding; Xencor: Research Funding; Genentech: Consultancy; Janssen: Consultancy, Research Funding; Amgen: Consultancy, Research Funding; Cellectar: Research Funding; Beigene: Consultancy; BMS: Consultancy, Research Funding; AbbVie: Consultancy; Karyopharm: Consultancy; Ascentage: Research Funding. Foran: actinium: Research Funding; taiho: Honoraria; bms: Honoraria; servier: Honoraria; pfizer: Honoraria; novartis: Honoraria; OncLive: Honoraria; abbvie: Research Funding; boehringer ingelheim: Research Funding; takeda: Research Funding; trillium: Research Funding; aptose: Research Funding; revolution medicine: Honoraria; syros: Honoraria; sanofi aventis: Honoraria; certara: Honoraria; gamida: Honoraria; kura: Research Funding; h3bioscience: Research Funding; aprea: Research Funding; sellas: Research Funding; stemline: Research Funding.

Abstract INTRODUCTION: Belantamab mafodotin (BLMF) is a first-in-class, antibody-drug conjugate targeting B-cell maturation antigen on myeloma cells. BLMF was approved for use in patients (pts) with advanced multiple myeloma (MM). Due to the risk of ocular toxicity, it is made available through a restricted program under a Risk Evaluation and Mitigation Strategy. It is speculated that monomethyl auristatin F (MMAF), the cytotoxic payload of BLMF may be internalised by the corneal epithelium via an off-target mechanism, leading to epithelial changes. In the pivotal DREAMM-2 trial, only 1% of pts permanently discontinued treatment due to keratopathy. Data regarding BLMF-induced ocular toxicity following its commercial availability since August 2020, are sparse, and in this context, we evaluated our clinical experience with BLMF to determine the impact of its ocular toxicity on outcomes when utilized outside of stringent clinical trial settings. METHODS: We reviewed records of pts with advanced MM who were evaluated at Mayo Clinic between 09/01/2020-07/01/2021 and initiated on BLMF monotherapy following a baseline ophthalmic examination that was also performed prior to each dose, and as needed for worsening ocular symptoms. Data pertaining to ocular symptoms, best corrected visual acuity (BCVA) and corneal examinations were collected and analyzed with respect to patient outcomes. Adverse events were graded using the National Cancer Institute Common Toxicity Criteria for Adverse Events v5.0. RESULTS: Thirty-four pts, with median age of 67 (range:49-90) years who received BLMF at the approved 2.5 mg/kg dose as their first infusion and completed at least one cycle were included. All patients were instructed to use preservative-free lubricant eye drops at least 4 times a day, starting with the initial infusion and continuing until the end of therapy, and avoid contact lenses. The median number of prior lines of therapy was 8 (range: 2-15). The median time to BLMF initiation from the diagnosis of MM was 7.5 (range: 1.3-19.7) years. The median follow-up from initiation of BLMF was 7 [95% confidence interval (CI): 5.7-8.6] months, and the median number of BLMF doses administered was 2 (range: 1-6). Twenty-seven (79%) pts experienced ocular toxicity, comprising keratopathy [n=25 (74%)] and/or decreased visual acuity [n=21 (62%)]. Table 1 outlines the keratopathy-related details. Thirteen pts (38%) developed symptomatic xerophthalmia. A clinically significant decrease in BCVA of equal or worse than 20/40 in the better-seeing eye was observed in 12 (35%) pts at a median of 1.7 (95%CI: 1.4-2.2) months of commencing BLMF. In 7 (58%) pts, it improved to better than 20/40 within a median of 3 (range: 0.7-4) months from the time of documentation of impaired BCVA following withholding treatment (n=5), with or without subsequent dose reduction or its permanent discontinuation (n=2). Treatment was permanently discontinued in 5 (15%) pts after a median of 3 doses due to grade ≥2 keratopathy. It was withheld in 9 (26%) due to grade ≥2 keratopathy. Four (12%) pts required dose reduction due to keratopathy (Table 1). Of 14 pts in whom BLMF was held or permanently discontinued due to keratopathy, 10 (77%) had disease progression within a median of 1 month (range 0.4-2.5) following BLMF interruption. Among 11 pts (32%) responded to BLMF, 45% developed grade 2 or higher keratopathy after the first dose compared to 13% of pts who were refractory to BLMF (n=23). The median duration of response was 4 (95%CI: 0.7-NR) months. Among responders, 2 pts (18%) had to permanently discontinue BLMF due to keratopathy, with subsequent progression from partial remission at 1.4 and 4.6 months following its discontinuation. Additionally, 73% of responders required dose withholding due to keratopathy and of those, 50% had evidence of disease progression within a median of 1.2 month (range: 0.7-1.7) following BLMF interruption. DISCUSSION & CONCLUSIONS : Despite efficacy in pts with advanced MM, in routine practice, ocular toxicity of BLMF is a major challenge and a deterrent to its continuous use. While frequent ocular toxicity-related interruptions were observed at expected rates, permanent treatment discontinuation due to keratopathy was observed in a higher proportion of pts than that encountered in the DREAMM-2 trial. Larger prospective studies are warranted to accurately discern the effects of ocular toxicities on outcomes of pts treated with BLMF. Figure 1 Figure 1. Disclosures Patel: Emmecell: Consultancy; GlaxoSmithKline: Consultancy; Senju Pharmaceuticals: Consultancy; Santen, Inc.: Consultancy. Kumar: Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Consultancy, Research Funding; Roche-Genentech: Consultancy, Research Funding; Carsgen: Research Funding; Janssen: 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; Merck: Research Funding; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding; Amgen: Consultancy, Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Tenebio: Research Funding; Beigene: Consultancy; Oncopeptides: Consultancy; Antengene: Consultancy, Honoraria; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bluebird Bio: Consultancy; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding. Ailawadhi: AbbVie: Consultancy; Xencor: Research Funding; Medimmune: Research Funding; Genentech: Consultancy; Ascentage: Research Funding; Takeda: Consultancy; Sanofi: Consultancy; Amgen: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Cellectar: Research Funding; BMS: Consultancy, Research Funding; Pharmacyclics: Consultancy, Research Funding; GSK: Consultancy, Research Funding; Karyopharm: Consultancy; Beigene: Consultancy. Bergsagel: Celgene: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; GSK: Consultancy, Honoraria; Novartis: Consultancy, Honoraria, Patents & Royalties: human CRBN mouse; Genetech: Consultancy, Honoraria; Oncopeptides: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria. Gertz: Ionis Pharmaceuticals: Other: Advisory Board; Akcea Therapeutics, Alnylam Pharmaceuticals Inc, Prothena: Consultancy; Akcea Therapeutics, Ambry Genetics, Amgen Inc, Celgene Corporation, Janssen Biotech Inc, Karyopharm Therapeutics, Pfizer Inc (to Institution), Sanofi Genzyme: Honoraria; Aurora Biopharma: Other: Stock option; AbbVie Inc, Celgene Corporation: Other: Data Safetly & Monitoring. Kapoor: Karyopharm: Consultancy; AbbVie: Research Funding; Sanofi: Research Funding; Takeda: Research Funding; Cellectar: Consultancy; BeiGene: Consultancy; Pharmacyclics: Consultancy; Sanofi: Consultancy; Amgen: Research Funding; Ichnos Sciences: Research Funding; Regeneron Pharmaceuticals: Research Funding; Glaxo SmithKline: Research Funding; Karyopharm: Research Funding.

Abstract Purpose: Multiple myeloma (MM) is a plasma cell malignancy characterized by a collection of cytogenetic abnormalities that drive clinical presentation, response to treatment, and prognosis. The most common immunoglobulin heavy chain (IGH) translocation found in MM, t(11;14), results in CCND1 overexpression. Although t(11;14) is considered a standard risk cytogenetic abnormality, heterogeneity in patient outcomes and response to therapy within the t(11;14) group has been reported. In contrast to t(11;14) mantle cell lymphoma, where most cases (73%) have a typical, balanced t(11;14) rearrangement, only 47% of t(11;14) MM have a typical, balanced t(11;14) FISH pattern; the remaining 53% of MM are characterized by an atypical t(11;14) FISH result (Dalland, Genes Chromosomes Cancer, 2021). Here, we compared the genetic characteristics of typical vs. atypical t(11;14) MM and the association with other genomic abnormalities, CCND1 expression, IGH breakpoint location and patient outcomes. Methods: We performed a retrospective study of newly diagnosed t(11;14) MM patients seen at Mayo Clinic (N=411) or enrolled in the MMRF CoMMpass trial (N=167). The t(11;14) FISH results of the Mayo Clinic samples were segmented into two groups: typical CCND1/IGH signal pattern (n=179, 3 red, 3 green, 2 fusion signals) and atypical CCND1/IGH signal pattern (n=232, any FISH pattern deviating from typical). The CoMMpass cases had both RNAseq and long-insert WGS data and were analyzed to detect gene expression, structural and copy number variants and IGH breakpoint locations. These data were used to classify the t(11;14) as typical (n=63) or atypical (n=104) and whether there was a single t(11;14) fusion (n=107) or a gain of the t(11;14) fusion (n=60), and whether these cases were associated with changes in gene expression or breakpoint location. Differences between the groups were measured using χ2 and Wilcoxon tests. Survival curves were estimated using Kaplan Meier and compared using the Log-Rank test. Statistical significance was determined at p<0.05. Results: Of the Mayo t(11;14) cohort, 232/411 (56%) had an atypical t(11;14) FISH pattern and 179/411 (44%) had a typical t(11;14) FISH pattern. Although an atypical t(11;14) FISH pattern was not significantly associated with monosomy 17/17p deletion, MYC rearrangements, 1q gain or ISS stage III, it was significantly associated with the presence of any trisomy in comparison to typical t(11;14) cases (40/222=18% vs.12/166=7%, p=0.002). Atypical t(11;14) cases had an increase in CCND1 gene expression compared to typical t(11;14) cases (median 375.0 RPKM vs. 266.4 RPKM, p<0.0001) and cases with a gain of the t(11;14) fusion were associated with even greater CCND1 expression compared to cases with a single t(11;14) fusion (median 459.4 RPKM vs. 263.2 RPKM, p<0.0001). We next evaluated whether the t(11:14) FISH pattern was associated with differences in IGH breakpoint locations. Nearly 80.0% of atypical t(11;14) cases had a breakpoint within the constant region of the IGH locus commonly reported for MM, while only 61.0% of the typical cases had constant region breakpoints (p=0.035); the remaining cases had breakpoints involving the VDJ region. We next evaluated the impact of atypical t(11;14) FISH on OS. In Mayo cases, OS was significantly shorter in patients with atypical FISH patterns compared to typical t(11;14) FISH patterns (6.9 years [95% CI: 5.1-7.8] vs. 9.0 years [95% CI: 7.0-11.6], p=0.019). Although atypical t(11;14) was associated with increased risk of death (RR 1.45, p=0.021), this finding was not retained in a multivariate model including high risk abnormalities such as age, ISS stage, 17p deletion and 1q gain demonstrating atypical t(11;14) is not an independent predictor of poor outcome when treated with standard therapies. Conclusions: Atypical t(11;14) FISH in MM is found in approximately half of t(11;14) cases, is associated with trisomies, higher CCND1 expression and is more likely to have a breakpoint involving the constant region of the IGH locus. The enrichment of VDJ breakpoints within typical t(11;14) MM is consistent with enrichment of VDJ IGH breakpoints in MCL, which are mostly characterized by typical t(11;14) FISH patterns. While not an independent predictor of outcome with standard therapies, it remains to be evaluated whether patients with typical or atypical t(11;14) have a differential response to novel agents, such as venetoclax. Disclosures Fonseca: Janssen: Consultancy; Novartis: Consultancy; Pharmacyclics: Consultancy; Sanofi: Consultancy; Merck: Consultancy; Juno: Consultancy; Caris Life Sciences: Membership on an entity's Board of Directors or advisory committees; Kite: Consultancy; Aduro: Consultancy; OncoTracker: Consultancy, Membership on an entity's Board of Directors or advisory committees; GSK: Consultancy; AbbVie: Consultancy; Patent: Prognosticaton of myeloma via FISH: Patents & Royalties; Mayo Clinic in Arizona: Current Employment; Amgen: Consultancy; BMS: Consultancy; Celgene: Consultancy; Takeda: Consultancy; Bayer: Consultancy; Scientific Advisory Board: Adaptive Biotechnologies: Membership on an entity's Board of Directors or advisory committees. Bergsagel: Pfizer: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; GSK: Consultancy, Honoraria; Oncopeptides: Consultancy, Honoraria; Genetech: Consultancy, Honoraria; Novartis: Consultancy, Honoraria, Patents & Royalties: human CRBN mouse. Kumar: Merck: Research Funding; Carsgen: Research Funding; Roche-Genentech: Consultancy, Research Funding; Beigene: Consultancy; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bluebird Bio: Consultancy; Antengene: Consultancy, Honoraria; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncopeptides: Consultancy; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Tenebio: Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, 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; Sanofi: Research Funding.

Abstract Introduction: Multiple Myeloma (MM) is an incurable plasma cell malignancy commonly preceded by the asymptomatic stage smoldering multiple myeloma (SMM). MM is characterized with significant genomic heterogeneity of chromosomal gains and losses (CNVs), translocations, and point mutations (SNVs); alterations that are also observed in SMM patients. However, current SMM risk models rely solely on clinical markers and do not accurately capture progression risk. While incorporating some genomic biomarkers improves prediction, using all MM genomic features to comprehensively stratify patients may increase risk stratification precision in SMM. Methods: We obtained a total of 214 patient samples at SMM diagnosis. We performed whole-exome sequencing on 166 tumors; of these, RNA sequencing was performed on 100. Targeted capture was done on 48 additional tumors. Upon binarization of DNA features, we performed consensus non-negative matrix factorization to identify distinct molecular clusters. We then trained a random forest classifier on translocations, SNVs, and CNVs. The predicted clinical outcomes for the molecular subtypes were further validated in an independent SMM cohort of 74 patients. Results: We identified six genomic subtypes, four with hyperdiploidy (>48 chromosomes, HMC, HKR, HNT, HNF) and two with IgH translocations (FMD, CND) (Table 1). In multivariate analysis accounting for IMWG (20-2-20) clinical risk stages, high-risk (HMC, FMD, HKR) and intermediate-risk (HNT, HNF) genetic subtypes were independent predictors of progression (Hazards ratio [HR]: 3.8 and 5.5, P = 0.016 and 0.001, respectively). The low-risk, CND subtype harboring translocation (11;14) was enriched for the previously defined CD-2 MM signature defined by the B cell markers CD20 and CD79A (FDR = 0.003 ), showed upregulation of CCND1, E2F1, and E2F7 (FDR = 0.01, 0.0004, 0.08), and was enriched for G2M checkpoint, heme metabolism, and monocyte cell signature (FDR = 0.003, 0.003, 0.003, respectively). The FMD subtype with IgH translocations (4;14) and (14;16) was enriched for P53, mTORC1, unfolded protein signaling pathways and plasmacytoid dendritic cell signatures (FDR = 0.01, 0.005, 0.008, respectively). The HKR tumors were enriched for inflammatory cytokine signaling, MYC target genes, T regulatory cell signature, and the MM proliferative (PR) signatures (FDR = 0.02, 0.03, 0.007, 0.02, respectively). The APOBEC mutational signature was enriched in HMC and FMD tumors (P = 0.005), while there was no statistical difference across subtypes in the AID signature. The median follow-up for the primary cohort is 7.1 years. Median TTP for patients in HMC, FMD, and HKR was 3.8, 2.6, and 2.2 years, respectively; TTP for HNT and HNF was 4.3 and 5.2, respectively, while it was 11 years in CND patients (P = 0.007). Moreover, by analyzing the changes in MM clinical biomarkers over time, we found that patients from high-risk subgroups had higher odds of developing evolving hemoglobin and monoclonal protein levels over time (P = 0.01 and 0.002, respectively); Moreover, the absolute increase in M-protein was significantly higher in patients from the high-risk genetic subtypes at one, two, and five years from diagnosis (P = 0.001, 0.03, and 0,01, respectively). Applying the classifier to the external cohort replicated our findings where intermediate and high-risk genetic subgroups conferred increased risk of progression to MM in multivariate analysis after accounting for IMWG staging (HR: 5.5 and 9.8, P = 0.04 and 0.005, respectively). Interestingly, within the intermediate-risk clinical group in the primary cohort, patients in the high-risk genetic subgroups had increased risk of progression (HR: 5.2, 95% CI 1.5 - 17.3, P = 0.007). In the validation cohort, these patients also had an increased risk of progression to MM (HR: 6.7, 95% CI 1.2 - 38.3, P = 0.03), indicating that molecular classification improves the clinical risk-stratification models. Conclusion: We identified and validated in an independent dataset six SMM molecular subgroups with distinct DNA alterations, transcriptional profiles, dysregulated pathways, and risks of progression to active MM. Our results underscore the importance of molecular classification in addition to clinical evaluation in better identifying high-risk SMM patients. Moreover, these subgroups may be used to identify tumor vulnerabilities and target them with precision medicine efforts. Figure 1 Figure 1. Disclosures Bustoros: Janssen, Bristol Myers Squibb: Honoraria, Speakers Bureau; Takeda: Consultancy, Honoraria. Casneuf: Janssen: Current Employment. Kastritis: Amgen: Consultancy, Honoraria, Research Funding; Takeda: Honoraria; Pfizer: Consultancy, Honoraria, Research Funding; Genesis Pharma: Honoraria; Janssen: Consultancy, Honoraria, Research Funding. Walker: Bristol Myers Squibb: Research Funding; Sanofi: Speakers Bureau. Davies: Takeda: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria; BMS: Consultancy, Honoraria; Roche: Consultancy, Honoraria; Janssen: Consultancy, Honoraria. Dimopoulos: Amgen: Honoraria; BMS: Honoraria; Takeda: Honoraria; Beigene: Honoraria; Janssen: Honoraria. Bergsagel: Genetech: Consultancy, Honoraria; Oncopeptides: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria; Novartis: Consultancy, Honoraria, Patents & Royalties: human CRBN mouse; GSK: Consultancy, Honoraria; Celgene: Consultancy, Honoraria. Yong: BMS: Research Funding; Autolus: Research Funding; Takeda: Honoraria; Janssen: Honoraria, Research Funding; Sanofi: Honoraria, Research Funding; GSK: Honoraria; Amgen: Honoraria. Morgan: BMS: Membership on an entity's Board of Directors or advisory committees; Jansen: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; GSK: Membership on an entity's Board of Directors or advisory committees. Getz: IBM, Pharmacyclics: Research Funding; Scorpion Therapeutics: Consultancy, Current holder of individual stocks in a privately-held company, Membership on an entity's Board of Directors or advisory committees. Ghobrial: AbbVie, Adaptive, Aptitude Health, BMS, Cellectar, Curio Science, Genetch, Janssen, Janssen Central American and Caribbean, Karyopharm, Medscape, Oncopeptides, Sanofi, Takeda, The Binding Site, GNS, GSK: Consultancy.

Abstract Introduction: Factors contributing to the antitumor activity of systemic oncolytic virotherapy (OV) include (i) generalized innate immune activation due to virus infusion; (ii) direct oncolytic and/or immune-mediated destruction of OV infected tumor cells due to intratumoral spread of the virus infection; (iii) collateral boosting of tumor antigen-specific T cell responses that target uninfected tumor cells. We investigated the relative contributions of these 3 factors T cell lymphoma (TCL) patients (pts) responding to a single intravenous infusion of Voyager-V1, an oncolytic vesicular stomatitis virus (VSV) encoding IFNβ and sodium iodide symporter (NIS) on NCT03017820. Of relevance, the virally encoded IFNβ enhances tumor specificity, boosts proinflammatory activity & serves as a convenient serum biomarker of infection. Methods: In a first in human trial, a single infusion of Voyager-V1 was administered to 15 pts with relapsed refractory hematologic cancers; 4 dose levels (DL) were tested (5x10 9, 1.7x10 10, 5x10 10, 1.7x10 11 TCID50); 7 pts had TCL. Cytokine levels and CRS symptoms were determined as a measure of generalized immune activation; serum IFNβ levels were monitored as a pharmacodynamic biomarker of virus infection; antitumor T cell responses were measured using ELISPOT assays. Results: Of 8 TCL pts, 3 had RECIST responses: PR at DL 2, a CR & PR at DL 4. Most pts experience short lived CRS typically resolving within 24 hours of virus infusion. Serum IFNβ levels increased post-therapy in all pts, typically peaking by 24 hours post virus infusion and returning to baseline by median day 10. T cell responses could not be accurately determined in most cases due to suboptimal T cell viability and/or function after thawing of frozen PBMC. Factors contributing to tumor regression in each of the responding pts appeared to differ significantly, as exemplified by the case reports below. Pt (I) with CTCL experienced grade 1 CRS followed by brisk regression of multiple cutaneous lesions. The PR lasted 3 mo, after relapse of an eye lesion, but responses at other sites deepened after the relapsed lesion was irradiated; pt remained off active therapy for the next 2 yrs. Peak serum IFNβ 4 hours post infusion was only 182 pg/ml suggesting that disease response may have been driven by nonspecific innate immune activation associated with the virus infusion. Pt (IV) (CD30+ PTCL/ cutaneous relapse) had short lived grade 2 CRS, then developed signs of IFNβ toxicity with AST elevation and thrombocytopenia. Oral ruxolitinib was administered for 5 days as IFNβ toxicity mitigation leading to normalization of AST and platelets. All PET-avid tumors regressed completely. This CR continues 16 months post virus infusion. Peak serum IFNβ was 18,213 pg/ml strongly suggesting that response was driven by extensive intratumoral amplification of the virus and oncolytic tumor destruction. Robust CTL responses to tumor neoantigens were detected in this pt at baseline indicating that collateral boosting of tumor-specific T cells may have been responsible for the long term maintenance of this CR Pt (V) (CD30+ PTCL) had short lived grade 2 CRS followed by response at all disease sites (including complete normalization of an enlarged FDG-avid spleen). Her PR ended after 6 months due to relapse in cervical lymph nodes. Peak serum IFNβ level was modest, 600 pg/ml & sustained over 48 hours suggesting slower intratumoral spread of the virus infection. The deepening of the response long after resolution of the oncolytic phase points strongly to a contribution from antitumor CTL but the assay was technically unsatisfactory in this pt. Conclusion: Analysis of the correlative data supports that intravenous Voyager-V1 therapy can recruit diverse antitumor effector mechanisms to impact tumor response in pts with heavily pretreated TCL. Importantly, intratumoral virus amplification, which results in high circulating concentrations of IFNβ, does not necessarily lead to tumor regression perhaps because of defective immune cell recruitment and/or activation in some tumors but not in others. This will be further evaluated in future study participants by performing CTL assays on fresh, rather than frozen PBMC. In conclusion, a single IV infusion of Voyager-V1 shows highly promising activity against treatment refractory TCL and should be further advanced as a new single-shot or combination therapy for this therapeutically challenging indication. Figure 1 Figure 1. Disclosures Witzig: Karyopharm Therapeutics, Celgene/BMS, Incyte, Epizyme: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene/BMS, Acerta Pharma, Kura Oncology, Acrotech Biopharma, Karyopharm Therapeutics: Research Funding. Paludo: Karyopharm: Research Funding. Patnaik: StemLine: Research Funding; Kura Oncology: Research Funding. Dispenzieri: Takeda: Research Funding; Alnylam: Research Funding; Pfizer: Research Funding; Oncopeptides: Consultancy; Sorrento Therapeutics: Consultancy; Janssen: Consultancy, Research Funding. Bennani: Kymera: Other: Advisory Board; Vividion: Other: Advisory Board; Kyowa Kirin: Other: Advisory Board; Daichii Sankyo Inc: Other: Advisory Board; Purdue Pharma: Other: Advisory Board; Verastem: Other: Advisory Board. Ansell: Bristol Myers Squibb, ADC Therapeutics, Seattle Genetics, Regeneron, Affimed, AI Therapeutics, Pfizer, Trillium and Takeda: Research Funding. Gertz: Aurora Biopharma: Other: Stock option; Akcea Therapeutics, Ambry Genetics, Amgen Inc, Celgene Corporation, Janssen Biotech Inc, Karyopharm Therapeutics, Pfizer Inc (to Institution), Sanofi Genzyme: Honoraria; Akcea Therapeutics, Alnylam Pharmaceuticals Inc, Prothena: Consultancy; AbbVie Inc, Celgene Corporation: Other: Data Safetly & Monitoring; Ionis Pharmaceuticals: Other: Advisory Board. Dingli: Janssen: Consultancy; Sanofi: Consultancy; GSK: Consultancy; Apellis: Consultancy; Novartis: Research Funding; Alexion: Consultancy. Kumar: Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Beigene: Consultancy; Carsgen: Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Consultancy, Research Funding; Merck: Research Funding; Oncopeptides: Consultancy; Roche-Genentech: Consultancy, Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Antengene: Consultancy, Honoraria; Tenebio: Research Funding; Novartis: Research Funding; Bluebird Bio: Consultancy; Amgen: Consultancy, Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Abbvie: 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; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding. Bergsagel: Oncopeptides: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria; Genetech: Consultancy, Honoraria; GSK: Consultancy, Honoraria; Novartis: Consultancy, Honoraria, Patents & Royalties: human CRBN mouse; Janssen: Consultancy, Honoraria. Kapoor: Karyopharm: Consultancy; Cellectar: Consultancy; BeiGene: Consultancy; Pharmacyclics: Consultancy; Sanofi: Consultancy; Amgen: Research Funding; Ichnos Sciences: Research Funding; Regeneron Pharmaceuticals: Research Funding; Glaxo SmithKline: Research Funding; Karyopharm: Research Funding; Sanofi: Research Funding; Takeda: Research Funding; AbbVie: Research Funding. Lin: Sorrento: Consultancy; Vineti: Consultancy; Legend: Consultancy; Novartis: Consultancy; Bluebird Bio: Consultancy, Research Funding; Merck: Research Funding; Juno: Consultancy; Celgene: Consultancy, Research Funding; Kite, a Gilead Company: Consultancy, Research Funding; Gamida Cell: Consultancy; Janssen: Consultancy, Research Funding; Takeda: Research Funding. OffLabel Disclosure: VSV-IFNβ-NIS is an oncolytic virus in clinical trial for systemic administration in hematologic malignancies

Abstract Introduction: Immune checkpoint receptor (ICR) blockade has emerged as an effective anti-tumour modality, but only in a subset of cancer patients. Moreover, in Multiple myeloma (MM), single-agent activity has not been observed, highlighting the need to better understand the mechanism of action of this class of drugs. We recently showed that combinatorial ICR blockade using αLAG3 and αPD-1 delays disease progression and improves survival in the transplantable Vκ*MYC model of MM (Croucher et al. ASH 2018). However, despite this being a controlled study with genetically-homogeneous tumours, anti-tumour immune responses were heterogeneous, with only a subset of mice demonstrating a delay in tumour progression (17/29 mice, response rate = 58.6%). Thus, using this model, we set out to define mechanisms underlying variability in response to ICR blockade. Methods: We established a cohort of mice by engrafting 5-week-old C57BL/6 mice with Vκ12598 cells via tail vein injection. Treatment with αLAG3/αPD-1 or Ig-control was initiated 1-week post-engraftment and bone marrow (BM) samples were collected 3 weeks after the start of treatment. Following FACS-enrichment of T cells and plasma cells (PCs), single cell suspensions were subjected to matched single-cell gene expression (5' scRNA-seq) and T cell receptor (TCR)/B cell receptor (BCR) profiling (10x Genomics). Results: Samples were selected for profiling based on response to treatment, with responders (n=4) defined by significantly lower disease burden compared to non-responders (n=3) and control-treated mice (n=5), as measured by serum M-protein and %PCs in BM/spleen at sacrifice. Unsupervised clustering of scRNA-seq data from PCs (n=3,318 cells) identified no gene expression or BCR repertoire differences between control and treated, or between responder and non-responder samples, supporting that variability in response was not related to malignant Vκ12598 cells themselves. Across all samples, a statistically significant difference was not detected between the total number of unique TCR sequences (clonotypes) comparing control-treated (351-2369), non-responders (1185-2327) and responders (1378-1698), with no overlapping TCR sequences between top clonotypes. Evaluation of TCR repertoire diversity revealed that αLAG3/αPD-1 treatment induces clonal T cell expansion in control versus treated mice, but this was not significantly different between responders and non-responders. Analysis of paired scRNA-seq data (n=21,520 cells) revealed that expanded T cells from αLAG3/αPD-1-treated mice occupy a different cell state in responder vs. non-responder mice. We speculate that underlying differences in the TCR repertoire may dictate the downstream phenotype of expanded, anti-tumour T cells in mice treated with combinatorial αLAG3/αPD-1. Tumour control following treatment was associated with clonal expansion of T cells expressing genes related to cytoxicity and activation (Ccl5, Ifng, Fasl, Gzmb), whereas tumour progression was associated with clonal expansion of proliferative T cells (Cdkn3, Birc5, Ccna2, Aurka, Mki67). Although T cell proliferation is typically a phenotype ascribed to effector T cells, recent studies have similarly observed this proliferative cell state in dysfunctional T cells within melanoma tumours. Moreover, emerging evidence supports suppression of T cell proliferation by CDK4/6 inhibitors as a means to augment anti-tumour activity of ICR-based therapy. Thus, studies exploring whether reversal of the observed proliferative T cell state can restore response to αLAG3/αPD-1 treatment in non-responding Vκ12598 mice are ongoing and will be reported. Conclusions: ICR inhibitors demonstrate significant activity in some cancers, however many patients fail to respond and a similarly promising level of efficacy has not been achieved in MM. Studies aimed at unraveling the mechanisms of response and resistance to ICR inhibitors are therefore needed to improve the utility of this class of drugs for all patients. Our approach of using paired single-cell gene expression and TCR repertoire profiling has enabled identification of molecular cell states specifically in expanded T cells of responder vs. non-responder mice. In turn, our work nominates novel mechanisms that may be used as potential biomarkers for anti-tumour immune responses as well as potential targets to augment responses to ICR blockade therapy. Disclosures Chesi: Abcuro: Patents & Royalties: Genetically engineered mouse model of myeloma; Novartis: Consultancy, Patents & Royalties: human CRBN transgenic mouse; Pfizer: Consultancy; Pi Therapeutics: Patents & Royalties: Genetically engineered mouse model of myeloma; Palleon Pharmaceuticals: Patents & Royalties: Genetically engineered mouse model of myeloma. Bergsagel: GSK: Consultancy, Honoraria; Genetech: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Oncopeptides: Consultancy, Honoraria; Novartis: Consultancy, Honoraria, Patents & Royalties: human CRBN mouse; Pfizer: Consultancy, Honoraria; Celgene: Consultancy, Honoraria. Sebag: Janssen: Research Funding; Bristol Myers-Squibb: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Novartis: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Sanofi: Consultancy, Honoraria; Karyopharm Therapeutics: Consultancy, Honoraria. Trudel: BMS/Celgene: Consultancy, Honoraria, Research Funding; Amgen: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; GlaxoSmithKline: Consultancy, Honoraria, Research Funding; Roche: Consultancy; Sanofi: Honoraria; Pfizer: Honoraria, Research Funding; Genentech: Research Funding.

Abstract Multiple myeloma (MM) is an incurable form of plasma cell cancer in which primary and secondary chromosomal translocations routinely juxtapose oncogenes to plasma cell-specific super-enhancers. Coincidentally, drugs which target super-enhancers have had success clinically. For example, immunomodulatory imide drugs (IMiDs) degrade super-enhancer-binding pioneer factors IKAROS and AIOLOS, while glucocorticoids (Dexamethasone) and proteasome inhibitors (Bortezomib) have the ability to transrepress or block the processing of super-enhancer-forming NF-κB proteins, respectively. Currently, alternative enhancer-targeting drugs are also in clinical development, like p300 inhibitors which target the acetyl-binding bromodomains and/or histone acetyl transferase activity of the chromatin-regulating coactivator homologs CBP and EP300. Despite showing therapeutic promise, our understanding of how these drugs function, alone or together, remains incomplete. Case in point, we find that IMiD-induced degradation of its target proteins IKAROS and AIOLOS does not guarantee a therapeutic response in vitro, and patients successfully treated with IMiDs eventually relapse; meanwhile, coactivator-targeting therapies like p300 inhibitors are often too toxic in vivo, and lack a therapeutic window. To improve the outcomes of MM patients we need to understand the heterogeneous genetics and transcription-factor milieus of the myeloma enhancer landscape, as well as how to increase the precision of enhancer-disrupting drugs. To accomplish this, our lab utilizes more than 60 human myeloma cell lines that have been extensively characterized at the genetic, proteomic, and drug-therapeutic-response levels. Additionally, we have generated a highly-predictive immunocompetent mouse model (Vk*MYC hCRBN+) that develops human-like MM and is sensitive to both IMiDs and a new class of therapeutics termed "degronimids" (normal mice do not respond to IMiDs or degronimids). Our central hypothesis is that combining a broad coactivator-targeting drug (e.g., the p300 inhibitor GNE-781), with a MM-specific transcription factor-targeting drug (e.g., IMiDs) restricts toxicities to myeloma cells and thus improves the therapeutic window. Currently, we are testing a variety of coactivator-targeting compounds alongside traditional IMiD therapies and other preclinical transcription factor-targeting drugs both in vivo and in vitro. We show that Vk*MYC hCRBN+ mice are exquisitely sensitive to GNE-781, requiring one fourth of the dose needed to treat other cancers and therefore avoiding the neutropenia and thrombocytopenia seen at higher doses. Second, we show that although IMiDs and GNE-781 induce an effective but transient response in vivo as single agents, the combination of the two drugs proved curative, with a progressive deepening of the anti-tumor response occurring even after therapy is discontinued. Ongoing experiments aim to determine how this drug combination, and other coactivator + transcription factor-targeting combinations, permanently disrupt myeloma-specific super-enhancers. Disclosures Neri: BMS: Consultancy, Honoraria; Sanofi: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Janssen: Consultancy, Honoraria. Bahlis: Sanofi: Consultancy, Honoraria; GlaxoSmithKline: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria; BMS/Celgene: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Karyopharm: Consultancy, Honoraria; Genentech: Consultancy. Boise: AstraZeneca: Honoraria, Research Funding; AbbVie/Genentech: Membership on an entity's Board of Directors or advisory committees. Chesi: Abcuro: Patents & Royalties: Genetically engineered mouse model of myeloma; Pi Therapeutics: Patents & Royalties: Genetically engineered mouse model of myeloma; Pfizer: Consultancy; Novartis: Consultancy, Patents & Royalties: human CRBN transgenic mouse; Palleon Pharmaceuticals: Patents & Royalties: Genetically engineered mouse model of myeloma.

Abstract Background :COVID-19 adversely affects individuals with cancer. Several studies have found that seroconversion rates among patients with hematologic malignancies are suboptimal when compared to patients without cancer. Among patients with hematologic malignancies, seroconversion rates also appear to be influenced by recent treatment and the type of treatment they have received. Patients with non-Hodgkin lymphoma (NHL) and multiple myeloma (MM) are immunocompromised due to impaired humoral and cellular immunity in addition to prescribed immunosuppressive therapy. Chimeric antigen receptor T-cell (CAR T) therapy is now widely used for NHL and MM, but little is known about seroconversion rates after COVID-19 vaccination among these populations. Current national guidelines recommend COVID-19 vaccination to be offered to CAR T recipients as early as three months thereafter. We retrospectively evaluated SARS-CoV-2 spike-binding IgG antibody levels following COVID-19 vaccination among NHL and MM CAR T therapy recipients. Methods:This retrospective study was conducted at three Mayo Clinic sites on NHL and MM patients that received CAR T infusions from Sept 2016 to June 2021. Baseline characteristics were ascertained from medical records. All NHL and MM patients who had received CAR T at any point and were alive at the time that the COVID-19 vaccine first became available were eligible for inclusion for antibody response evaluation. For antibody response to vaccination, antibody spike values > 0.80 U/mL were considered positive. Results: Out of 104 CAR T infusions, 73 patients are alive at the time of this submission. We have had 7 patients with known COVID-19 pre-CAR T and all 7 are currently alive (5 have antibody titers and 2 have not been tested yet). Nineteen patients developed known COVID infection post-CAR T (13 alive and 6 deceased). The mortality of COVID post-CAR T in our sample was 31.5%. Furthermore, of the 13 patients that survived COVID-19, they received CAR T an average of 416 days prior to COVID-19 infection (median = 337, range = 54 - 1406); the 6 patients who died from COVID-19 had received CAR T an average of 250 days prior to COVID-19 infection (median = 164, range = 7 - 846). All 6 deceased patients did not receive COVID-19 vaccination pre-CAR T. Out of 17 CAR T patients tested for antibody spike titers post COVID-19 vaccination, 76.4% were able to mount an antibody response. More patients with MM had a higher titer response to the vaccine (>250 U/mL) compared to the NHL counterparts (0.80-249 U/mL). All patients that received the vaccine, regardless of antibody response, were alive at the time of this submission. Conclusions:The majority of CAR T recipients with NHL and MM are able to mount an antibody response following COVID-19 vaccination in our relatively small sample. The frequency of seroconversion among CAR T recipients seems to be similar to patients with hematologic malignancy who had received a hematopoietic cell transplant reported elsewhere. These findings are limited by our small sample size and may be influenced by the timing of vaccination relative to CAR T. Furthermore, almost half of our patients received IVIG post CAR T which could potentially cause false positive antibody results as pooled immunoglobulin preparations may contain COVID-19 antibodies from vaccinated healthy donors. To better understand the characteristics of the immunologic response against SARS-CoV-2 in patients post-CAR T, larger multicenter studies exploring both humoral and cellular immunity will be needed. JEWN, MI and JM are co-first authors and PV, HM and AR are co-senior authors. Figure 1 Figure 1. Disclosures Munoz: Physicians' Education Resource: Honoraria; Seattle Genetics: Honoraria; Bayer: Research Funding; Gilead/Kite Pharma: Research Funding; Celgene: Research Funding; Merck: Research Funding; Portola: Research Funding; Incyte: Research Funding; Genentech: Research Funding; Pharmacyclics: Research Funding; Seattle Genetics: Research Funding; Janssen: Research Funding; Millennium: Research Funding; Gilead/Kite Pharma, Kyowa, Bayer, Pharmacyclics/Janssen, Seattle Genetics, Acrotech/Aurobindo, Beigene, Verastem, AstraZeneca, Celgene/BMS, Genentech/Roche.: Speakers Bureau; Pharmacyclics/Abbvie, Bayer, Gilead/Kite Pharma, Pfizer, Janssen, Juno/Celgene, BMS, Kyowa, Alexion, Beigene, Fosunkite, Innovent, Seattle Genetics, Debiopharm, Karyopharm, Genmab, ADC Therapeutics, Epizyme, Beigene, Servier: Consultancy; Targeted Oncology: Honoraria; OncView: Honoraria; Kyowa: Honoraria. Bergsagel: Oncopeptides: Consultancy, Honoraria; Novartis: Consultancy, Honoraria, Patents & Royalties: human CRBN mouse; Pfizer: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Genetech: Consultancy, Honoraria; GSK: Consultancy, Honoraria. Wang: Incyte: Membership on an entity's Board of Directors or advisory committees, Research Funding; LOXO Oncology: Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech: Research Funding; InnoCare: Research Funding; Novartis: Research Funding; MorphoSys: Research Funding; Eli Lilly: Membership on an entity's Board of Directors or advisory committees; TG Therapeutics: Membership on an entity's Board of Directors or advisory committees. Fonseca: Juno: Consultancy; Kite: Consultancy; Aduro: Consultancy; OncoTracker: Consultancy, Membership on an entity's Board of Directors or advisory committees; GSK: Consultancy; AbbVie: Consultancy; Patent: Prognosticaton of myeloma via FISH: Patents & Royalties; Caris Life Sciences: Membership on an entity's Board of Directors or advisory committees; Scientific Advisory Board: Adaptive Biotechnologies: Membership on an entity's Board of Directors or advisory committees; BMS: Consultancy; Amgen: Consultancy; Sanofi: Consultancy; Merck: Consultancy; Mayo Clinic in Arizona: Current Employment; Celgene: Consultancy; Takeda: Consultancy; Bayer: Consultancy; Janssen: Consultancy; Novartis: Consultancy; Pharmacyclics: Consultancy. Palmer: Sierra Oncology: Consultancy, Research Funding; CTI BioPharma: Consultancy, Research Funding; Protagonist: Consultancy, Research Funding; Incyte: Research Funding; PharmaEssentia: Research Funding. Dingli: Novartis: Research Funding; GSK: Consultancy; Apellis: Consultancy; Alexion: Consultancy; Sanofi: Consultancy; Janssen: Consultancy. Kapoor: Sanofi: Research Funding; AbbVie: Research Funding; Takeda: Research Funding; Karyopharm: Consultancy; Cellectar: Consultancy; BeiGene: Consultancy; Pharmacyclics: Consultancy; Sanofi: Consultancy; Amgen: Research Funding; Ichnos Sciences: Research Funding; Regeneron Pharmaceuticals: Research Funding; Glaxo SmithKline: Research Funding; Karyopharm: Research Funding. Kumar: Roche-Genentech: Consultancy, Research Funding; Oncopeptides: Consultancy; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Consultancy, Research Funding; Beigene: Consultancy; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Tenebio: Research Funding; Merck: Research Funding; Carsgen: Research Funding; KITE: 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; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Research Funding; Bluebird Bio: Consultancy; Antengene: Consultancy, Honoraria; Sanofi: Research Funding. Paludo: Karyopharm: Research Funding. Bennani: Kymera: Other: Advisory Board; Vividion: Other: Advisory Board; Kyowa Kirin: Other: Advisory Board; Daichii Sankyo Inc: Other: Advisory Board; Purdue Pharma: Other: Advisory Board; Verastem: Other: Advisory Board. Ansell: Bristol Myers Squibb, ADC Therapeutics, Seattle Genetics, Regeneron, Affimed, AI Therapeutics, Pfizer, Trillium and Takeda: Research Funding. Lin: Kite, a Gilead Company: Consultancy, Research Funding; Merck: Research Funding; Gamida Cell: Consultancy; Takeda: Research Funding; Juno: Consultancy; Bluebird Bio: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Novartis: Consultancy; Janssen: Consultancy, Research Funding; Sorrento: Consultancy; Legend: Consultancy; Vineti: Consultancy. Murthy: CRISPR Therapeutics: Research Funding.