Citations

Abstract Background: Phospholipid ethers (PLE) provide a novel mechanism to target tumor cells. Tumor cells contain increased amounts of lipid rafts in their cell membranes, which are thought to enhance signaling and resist apoptosis. Phospholipid drug conjugates (PDC) are specifically designed to have high affinity for lipid rafts which upon binding results in trans-membrane inversion with the ability to deliver an attached therapeutic directly to the cytosol. Iopofosine I-131 (formerly identified as CLR 131) is a novel PDC delivering I-131 as a targeted tumor cell radiotherapy. Iopofosine I-131 is being examined in relapsed or refractory multiple myeloma (RRMM) patients through an open-label, Phase 2 trial, CLOVER-1 (NCT02952508). Methods: The primary objective of this study is to determine the safety and efficacy of Iopofosine I-131 in heavily pretreated MM patients. Eligibility criteria for MM patients include progression or relapsed disease that is refractory to at least 1 proteasome inhibitor and 1 immunomodulatory agent unless intolerable/ineligible to receive such agents with no upper limit to the number of prior lines of therapy. Iopofosine I-131 is administered in up to 4 IV infusions (15-20 min) over 3 months, with doses given 1-2 weeks apart each cycle for a maximum of 2 cycles, along with dexamethasone 40 mg weekly (20 mg in patients > 75), for up to 12 weeks. Following iopofosine I-131 administration, no other antineoplastic or targeted therapy was given until clinically indicated by the investigator. Adverse events (AEs) are graded by NCI-CTCAE v4.03; responses are assessed by the 2016 International Myeloma Working Group criteria. Results: Eleven patients with at least triple class refractory (immunomodulatory agent, proteasome inhibitor and monoclonal antibody) MM have been enrolled in this Phase 2 study with data current as of 28 May 2021. Patients had a median age of 72 (range 34-77), mean prior regimens of 7.2 (range 3-17) and received a mean total body dose of 75.4 mCi (range 59.7-118.7) of iopofosine I-131. The overall response rate (ORR) was 45.5% (5/11), the clinical benefit rate (CBR) was 72.7% (8/11) and disease control rate (DCR) was 100%. Median progression free survival (PFS) was 3.4 months. In a subset of patients who are quad/penta drug refractory, efficacy increased with an ORR of 80.0% (4/5) and CBR of 100% (5/5). The primary treatment emergent AEs in patients with MM included cytopenias (87.5%), in line with prior experience with iopofosine I-131. The most commonly observed cytopenias included Grade 3 or 4 thrombocytopenia (62.5%), anemia (62.5%), neutropenia (62.5%) and decreased white blood cell count (50%). There were no infusion-related reactions or AEs. Conclusions: Initial results for iopofosine I-131 show efficacy with a promising ORR of 45.5% and a CBR or 72.7% in heavily pretreated triple class refractory multiple myeloma patients. Interestingly, iopofosine I-131 showed its highest efficacy in patients that were quad/penta drug refractory with ORR of 80%, highlighting its potential as a later line therapy. Iopofosine I-131 is a novel cancer radiotherapeutic that may provide benefit to patients that are refractory/unresponsive to traditional MM therapies. CLOVER-1 is actively enrolling MM patients that are at least triple class refractory across the United States. Disclosures Ailawadhi: AbbVie: Consultancy; Pharmacyclics: Consultancy, Research Funding; Ascentage: Research Funding; Cellectar: Research Funding; GSK: Consultancy, Research Funding; Genentech: Consultancy; BMS: Consultancy, Research Funding; Karyopharm: Consultancy; Sanofi: Consultancy; Medimmune: Research Funding; Janssen: Consultancy, Research Funding; Amgen: Consultancy, Research Funding; Xencor: Research Funding; Takeda: Consultancy; Beigene: Consultancy. Stiff: CRISPR: Consultancy; Gamida-Cell, Atara, Amgen, Incyte, Takeda, Macrogenetics, Eisai: Research Funding; Cellectar: Research Funding. Green: Seagen Inc.: Research Funding; bristol myers squibb: Membership on an entity's Board of Directors or advisory committees, Patents & Royalties, Research Funding; Cellectar Biosciences: Research Funding; GSK: Membership on an entity's Board of Directors or advisory committees; Janssen Biotech: Membership on an entity's Board of Directors or advisory committees, Research Funding; Juno Therapeutics: Patents & Royalties, Research Funding; Legend Biotech: Consultancy; Neoleukin Therapeutics: Membership on an entity's Board of Directors or advisory committees; Seattle Genetics: Membership on an entity's Board of Directors or advisory committees, Research Funding; SpringWorks Therapeutics: Research Funding. Lipe: Seagen Inc.: Research Funding; BMS: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; sanofi: Consultancy; GlaxoSmithKline: Consultancy; amgen: Research Funding; Cellectar: Research Funding; Karyopharm: Research Funding; Harpoon: Research Funding. Cull: Aptevo: Research Funding. Friend: Cellectar: Current Employment. Longcor: Cellectar: Current Employment. Oliver: Cellectar: Current Employment.

Abstract Background: CD19 CAR T cell therapies have demonstrated high initial complete remission (CR) rates of 70-80% in relapsed or refractory (R/R) B-cell acute lymphoblastic leukemia (B-ALL) with durable remissions observed in a subset of patients. Despite the remarkable initial CR rate, relapses occur in 20-45% of patients and with increasing use of CD19 CAR T cell therapies in ALL, a key remaining clinical question is the role of post-CAR HCT. Methods: Patients up to 26 years treated with the commercial (i.e., tisagenlecleucel) or investigational CD19 CAR T cell products from 2014 to 2019 in the United States were included. The objectives were to examine the impact of post-CAR HCT on mortality, disease-free survival (DFS), leukemia relapse, GVHD and transplant related mortality among HCT recipients. The intent of HCT was analyzed as consolidation when there was no evidence of post-CAR T cell relapse prior to HCT. Cox regression multivariable analysis used HCT as time-dependent variable along with age, performance status and time from diagnosis to CAR-T cell infusion to evaluate its impact on outcomes. Results: We identified 347 patients who received CD19 CAR T cells from 86 centers. Median age was 13 (range, 0.4-26 years) with 39% of patients from Hispanic or Latino ethnic origin. Patients were high risk and heavily pretreated; 56% had poor cytogenetics, 51% had ≥3 line of prior therapies and 34% had prior HCT. Most of the patients (74%) received tisagenlecleucel. Disease burden at the time of CAR T cell infusion included morphologic disease (≥5% bone marrow blasts) (65%), measurable residual disease (MRD) positive (16%) and negative CR (18%). CRS of all grades was observed in 57.6% and grade 3-4 CRS in 13%; neurotoxicity of all grades was observed in 25% and grade 3-4 in 8%. With a median follow-up of 12.7 months (range, 2.2-60.3), DFS at 3, 6 and 12 months following CAR T cell infusion was 80.9% % (95% CI: 76.6%-84.9%), 71.2% (95% CI: 66.1%-76.0%) and 57.6% (95% CI: 51.8%-63.3%), respectively. OS at 3, 6 and 12 months was 93.6% (95% CI: 90.8%-96.0%), 89.8% (95% CI: 86.4%-92.8%) and 79.4% (95% CI: 74.7%-83.6%), respectively. Incidences of relapse without censoring at subsequent HCT at month 3, 6 and 12 were 18.5% (95% CI: 14.5%-22.8%), 28.2% (95% CI: 23.5%-33.3%), and 40.6% (95% CI: 35.0%-46.3%), respectively. Of the 347 patients who received CD19 CAR therapy, 62 patients (18%) had subsequent HCT in CR as a consolidation post-CAR with a median time from CAR T to HCT of 4.7 months (range, 1.1-18.6). 36% had a prior HCT (i.e., pre-CAR), 87% received myeloablative regimen and among the 57 patients with MRD evaluation 56 were negative (98%). Frequencies of post-CAR HCT did not change during the 5-year study period. Overall, transplant related mortality (TRM) at month 6 was 8.9% (95% CI: 3.6-16.1), and grade 2-4 acute GvHD was observed in 38.0% (95% CI: 28.4-48.2) of patients at month 6. Post-CAR HCT used as a consolidation was associated with lower relapse (hazard ratio (HR) 0.37; p=0.037) but no significant impact on mortality (HR 0.75, p=0.51) or DFS (HR=0.46, p=0.057). When accounting for any HCT performed after CAR T cell, HCT was associated with higher mortality (Figure). Conclusions: This is the largest clinical series to date examining the impact of post-CAR HCT on clinical outcome of R/R B-ALL patients. We found that 18% of the patients had post-CAR HCT as a consolidation therapy with a favorable safety profile of 8.9% TRM rate despite a prior transplant rate of 36%. Consolidation HCT after CAR T cell resulted in significant reduction in leukemia relapse with a trend towards better DFS. Consolidation HCT seem safe and incurred a benefit by reducing disease relapse. Further studies in understanding the role of consolidation HCT as planned, or post-CAR T cell response-based strategy or treatment for early B-cell recovery are needed to further define the best candidates for HCT after tisagenlecleucel . Figure 1 Figure 1. Disclosures Park: BMS: Consultancy; Affyimmune: Consultancy; Kite Pharma: Consultancy; Curocel: Consultancy; Novartis: Consultancy; Minerva: Consultancy; Innate Pharma: Consultancy; PrecisionBio: Consultancy; Intellia: Consultancy; Amgen: Consultancy; Autolus: Consultancy; Servier: Consultancy; Artiva: Consultancy; Kura Oncology: Consultancy. Nikiforow: Kite/Gilead: Other: ad HOC Advisory Boards; Novartis: Other: ad Hoc Advisory Boards; Iovance: Other: ad Hoc Advisory Boards; Glaxo Smith Kline (GSK): Other: ad Hoc Advisory Boards. Hu: Kite/Gilead: Research Funding; Novartis: Research Funding; Celgene: Research Funding. Ahmed: Merck: Research Funding; Tessa Therapeutics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Seagen: Research Funding; Xencor: Research Funding. Badar: Pfizer Hematology-Oncology: Membership on an entity's Board of Directors or advisory committees. Cairo: Servier: Speakers Bureau; Sanofi: Speakers Bureau; Amgen: Speakers Bureau; Jazz Pharmaceutical: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Sobi: Speakers Bureau; Omeros: Membership on an entity's Board of Directors or advisory committees; Nektar: Membership on an entity's Board of Directors or advisory committees. Dholaria: Janssen: Research Funding; Takeda: Research Funding; Jazz: Speakers Bureau; MEI: Research Funding; Pfizer: Research Funding; Angiocrine: Research Funding; Poseida: Research Funding; Celgene: Speakers Bureau. Grover: Kite: Other: Advisory Board; Genentech: Research Funding; ADC: Other: Advisory Board; Tessa: Consultancy; Novartis: Consultancy. Locke: Gerson Lehrman Group: Consultancy; Emerging Therapy Solutions: Consultancy; Moffitt Cancer Center: Patents & Royalties: field of cellular immunotherapy; Calibr: Consultancy, Other: Scientific Advisory Role; BMS/Celgene: Consultancy, Other: Scientific Advisory Role; Wugen: Consultancy, Other; Legend Biotech: Consultancy, Other; Janssen: Consultancy, Other: Scientific Advisory Role; Iovance Biotherapeutics: Consultancy, Other: Scientific Advisory Role; Novartis: Consultancy, Other, Research Funding; GammaDelta Therapeutics: Consultancy, Other: Scientific Advisory Role; Takeda: Consultancy, Other; EcoR1: Consultancy; Cowen: Consultancy; Umoja: Consultancy, Other; Kite, a Gilead Company: Consultancy, Other: Scientific Advisory Role, Research Funding; Cellular Biomedicine Group: Consultancy, Other: Scientific Advisory Role; Bluebird Bio: Consultancy, Other: Scientific Advisory Role; Amgen: Consultancy, Other: Scientific Advisory Role; Allogene Therapeutics: Consultancy, Other: Scientific Advisory Role, Research Funding. Murthy: CRISPR Therapeutics: Research Funding. Mussetti: GILEAD: Other: Clinical trials participation, Research Funding; TAKEDA: Honoraria; NOVARTIS: Honoraria, Other: Clinical trials participation. Pulsipher: Jasper Therapeutics: Honoraria; Adaptive: Research Funding; Equillium: Membership on an entity's Board of Directors or advisory committees. Qayed: Novartis: Membership on an entity's Board of Directors or advisory committees; Medexus: Membership on an entity's Board of Directors or advisory committees; Mesoblast: Membership on an entity's Board of Directors or advisory committees; Jazz: Membership on an entity's Board of Directors or advisory committees; BMS: Other. Reshef: Gilead, BMS, Precision, Immatics, Atara, Takeda, Shire, Pharmacyclics, Incyte: Research Funding; Gilead and Novartis: Honoraria; Bayer, BMS, Regeneron, TScan, Synthekine, Atara, Jasper: Consultancy. Rizzieri: Kite: Honoraria, Speakers Bureau; Incyte: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Stemline: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Seattle Genetics: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Acrotech: Membership on an entity's Board of Directors or advisory committees; Teva: Membership on an entity's Board of Directors or advisory committees; Sanofi: Membership on an entity's Board of Directors or advisory committees; Bayer: Membership on an entity's Board of Directors or advisory committees; AROG: Membership on an entity's Board of Directors or advisory committees; AbbVie: Membership on an entity's Board of Directors or advisory committees; Gilead: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Karyopharm: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: Membership on an entity's Board of Directors or advisory committees; Celltrion: Membership on an entity's Board of Directors or advisory committees; Mustang: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Jazz: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Amgen: Honoraria; Pharmacyclics: Honoraria. Sharma: Vertex Pharmaceuticals/CRISPR Therapeutics: Other: Salary support paid to institution; Medexus Inc: Consultancy; CRISPR Therapeutics: Other, Research Funding; Vindico Medical Education: Honoraria; Spotlight Therapeutics: Consultancy; Novartis: Other: Salary support paid to institution. Schultz: BMS DSMB: Other: payment; Sobi: Membership on an entity's Board of Directors or advisory committees. Turtle: Century Therapeutics Ad hoc advisory boards (last 12 months): Nektar Therapeutics, Allogene, PACT Pharma, Astra Zeneca, Amgen: Membership on an entity's Board of Directors or advisory committees; Precision Biosciences: Membership on an entity's Board of Directors or advisory committees; Eureka Therapeutics: Membership on an entity's Board of Directors or advisory committees; Caribou Biosciences: Membership on an entity's Board of Directors or advisory committees; T-CURX: Membership on an entity's Board of Directors or advisory committees; Myeloid Therapeutics: Membership on an entity's Board of Directors or advisory committees; ArsenalBio: Membership on an entity's Board of Directors or advisory committees; Minerva: Other; Nektar Therapeutics: Other; Juno Therapeutics/BMS: Other: Payments, Patents & Royalties: Patent licensed to Juno Therapeutics.; Precision Biosciences, Eureka Therapeutics, Caribou Biosciences, Myeloid Therapeutics, ArsenalBio: Current holder of stock options in a privately-held company. Pasquini: Kite Pharma: Research Funding; Novartis: Research Funding; Bristol Myers Squibb: Consultancy, Research Funding; GlaxoSmithKline: Research Funding. Perales: MorphoSys: Honoraria; Cidara: Honoraria; Bristol-Myers Squibb: Honoraria; Miltenyi Biotec: Honoraria, Other; Sellas Life Sciences: Honoraria; Takeda: Honoraria; Karyopharm: Honoraria; Celgene: Honoraria; Omeros: Honoraria; Nektar Therapeutics: Honoraria, Other; Equilium: Honoraria; Novartis: Honoraria, Other; NexImmune: Honoraria; Incyte: Honoraria, Other; Kite/Gilead: Honoraria, Other; Merck: Honoraria; Servier: Honoraria; Medigene: Honoraria.

Abstract Introduction: CAR T-cell therapy has revolutionized the treatment of patients with relapsed/refractory (R/R) acute leukemia, NHL, and multiple myeloma. However, there are still areas of improvement in their clinical activity, source of the effector cells, prevention, and management of adverse events that require particular attention. Because of those reasons, NK cells appear as a viable effector cell alternative that can help address these challenges. NK cells offer a profile of activation, expansion, persistence, and cytotoxicity that is different from T cells and, when modified to bear CAR constructs, may provide significant advantages. However, the preclinical development of NK-CARs is challenging mainly because of the difficulty of generating large quantities of cells for testing and well-established pathways for CAR optimization before in vivo evaluation. Therefore, we developed a CAR optimization platform using the NK-92 cell line. NK-92 cells conserve their cytotoxic ability and can be easily expanded in vitro and used for functional and phenotypical evaluations of novel CAR-NK constructs. Here we present a rechallenge cytotoxic assay that mimics repetitive in vivo effector interactions with the target cells and its use for optimization, comparison, and development of NK-based cellular therapies. Methods: We generated lentivirus transduced CD19 CARs (FMC63-41BB-z) using T cells from healthy donors and NK-92 cells for comparison.T cells were expanded for 12 days, and a 41.9% CAR+ expression was achieved (CART19). Transduced NK-92 cells were sorted by FACS to obtain a population of 98.3 % CAR+ cells (CARNK19) and subsequently expanded for 12 days. JeKo-1 cells were used as CD19+ targets and BxPC3 cells as CD19 neg control (both cell types were GFP-Luc-PuroR). We developed a Luciferase-based rechallenge cytotoxicity assay. For this, we diluted the effector to target (E/T) ratio to obtain a logarithmic trendline of the cells' cytotoxicity. E/T ratio to get viability of 50% (IC50) measured at 4h (for CARNK19) and 24h (for CART19) was used as a proxy of the product's potency. Both CAR Immune Effector Cells (IECs) were co-cultured with their targets at an E/T ratio to obtain 70% cytotoxicity. After 24 hours with the target, we estimated the remaining IEC amount in the culture using GFP exclusion in flow analysis (IEC cells/mL = total cells/mL x GFP neg%). We repeated the plating of E/T ratio dilutions to perform daily IC50 curves using this rechallenge strategy for a total of 5 days. CAR and PD1 expression were measured on Day 0 and Day 5 by flow cytometry. Results: CART19 showed a higher IC50 than CARNK19 at baseline, 1.7 vs. 0.19 (Figure 1A). The IC50 trend of both IECs over time showed an uptrend that suggests progressive functional exhaustion (Figure 1B). At 5 days of rechallenge, it was 29 times higher in T cells than in NK-92 (12.07 vs. 0.42) and with a slope 265 times higher (10.6 vs. 0.04). Furthermore, we observed that when comparing the levels of CAR expression on Day 0 vs. Day 5, CART19 showed a decrease in CAR expression that was not present in CARNK19 (41.9 to 10.9% vs. 98.3 to 95.5%) (Figure 1C). In addition, there was a higher increase in PD1 expression in CART19 cells than CARNK19 cells from Day 0 to Day 5 of the in vitro rechallenge (9.9 to 46.8% vs. 0.88 to 8.88%) (Figure 1D). Conclusion: Our data shows the use of NK-92 cells as a tool for optimization and preclinical development of NK cell-based cellular therapies. We demonstrated that it is feasible to set up repetitive cytotoxic challenges that mimic closer in vivo E/T engagement. Moreover, using the cytotoxic IC50 calculated with this platform, we show increased cytotoxicity, less functional exhaustion, and less expression of PD1 in CARNK19 than in its T cell counterpart. Overall, the NK-92 rechallenge cytotoxicity assay platform constitutes a helpful tool for research, development, and optimization of cellular therapies based on NK cell effector function. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

Abstract Background: Chimeric Antigen Receptor (CAR) T cell therapy is arguably one of the most significant breakthroughs in cancer treatment. There are currently five FDA-approved products that are commercially available. However, despite their success, these CAR T-cell therapies cannot induce long-term durable responses in approximately 50% of leukemia or lymphoma-treated patients. Similarly, the results of CAR T-cells in solid tumors have been somewhat disappointing. Therefore, there is an urgent need to design and develop novel CAR T cells with improved efficacy in hematologic malignancies and solid tumors. ROR1 is a carcinoembryonic antigen expressed in different cancers and is associated with tumor stemness, proliferation, metastatic transformation, and treatment resistance. In this project, we optimize an anti-ROR1 CAR using a humanized single-chain variable fragment (scFv) with second (2G) or third-generation (3G) costimulatory domains. Methods: Several optimization steps in silico were performed using a selected scFv binding domain that targets ROR1. Those included codon optimizations, positional arrangement of heavy-light chains, evaluation of the ideal length of linkers based on tridimensional modeling of the docking between the antibody-like paratope with the target antigen (Figure 1A). After this initial scFv optimization process, we constructed a lentiviral vector that encodes CARs using the selected scFv linked to a transmembrane domain CD28 and different signaling endodomains for 2G and 3G variants (CD28, 41BB, ICOS, OX40), each linked to the T cell receptor CD3z domain. The cytotoxic activity of these constructs was evaluated using an in vitro rechallenge luciferase assay in ROR1 expressing JeKo-1 cells and ROR1(negative) controls. Results: The 2G 41BB-z construct with V H-V L scFv orientation and a long linker (V H-L-V L) showed optimal cytotoxicity with a CAR expression level in T cells of 36% (Range 28-49% for other constructs, Figure 1B-C). The V H-L-V L 41BB-z construct was evaluated comparatively using a rechallenge cytotoxic assay with 3G constructs that expressed CD28, ICOS, or OX40 signaling domains using JeKo-1 and ROR1(negative) target cells as controls. All the tested constructs showed specific ROR1 medicated cytotoxicity. CD28-41BB-z and ICOS-41BB-z showed the lowest cytotoxicity levels during the Day 1 of the repetitive rechallenge. However, the cytotoxicity levels of those constructs gradually increased during the 7 days of rechallenge and were closed to the levels induced by the 2G- 41BB-z construct (>80% of cytotoxicity). There were no significant differences in CAR T cells subsets generated by the different constructs during the 7 days of rechallenge with a predominance of effector memory phenotype (CCR7-, CD45RA-) and no difference in PD1 expression. Conclusions: Our results demonstrate that optimization of the CAR constructs enhances T-cell effector function and cytotoxicity against ROR1+ target cells. In previous studies, 3G CARs have shown longer persistence of the transduced T cells in peripheral blood, sustained and regulated cellular activation, improved solid tumor infiltration, and positive modulation of the tumor microenvironment. Our preclinical in vitro optimization demonstrates strategies to generate 3G constructs with a progressive and modulated cytotoxic profile that may confer benefits when tested in vivo in terms of enhanced persistence and lower adverse events profile. Additional experiments in vivo will be presented during the meeting to corroborate our findings. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

Abstract Background: MM that is refractory to a proteasome inhibitor (PI), an immunomodulatory agent (IMiD) and an anti-CD38 monoclonal antibody (CD38MoAb) is labeled triple-class refractory (TCR) and recognized as a modern therapeutic challenge. In recent years, new agents have shown activity in this setting in single arm trials and many more are in development. The assessment of the impact of new agents in the TCR setting is impaired by limited information on the therapeutic outcomes of these patients when treated with non-investigational therapies. Methods: We utilized an independent RWD dataset of patients with MM refractory to CD38MoAb built from academic collaboration (MAMMOTH study) to identify patients with TCR MM who received subsequent therapy. Patients with MM that was CD38MoAb refractory but not TCR were followed longitudinally and only included if, after subsequent lines of therapy, MM became TCR. Patients were excluded if they had plasma cell leukemia, poor renal function (serum creatinine > 2 mg/dl) or if next therapy after TCR status included experimental agents. Refractoriness to a MM agent was defined as lack of objective response and/or progression while receiving therapy or within 60 days of last dose as per International Myeloma Working Group (IMWG) criteria. Time zero for analysis was initiation of next therapy after MM became TCR. Response to therapy and progression were adjudicated utilizing IMWG criteria. MM that was TCR but also exposed to 2 PIs, 2 IMiDs and a CD38MoAb was considered penta-exposed, and when refractory to 2 PIs, 2 IMiDs and a CD38MoAb, it was considered penta-refractory. Results: Data collection occurred between 2016 and 2018 (prior to commercial availability of selinexor, belantamab mafodotin, melflufen or ide-cel). Of 275 patients in the MAMMOTH study, 177 were included. Median age was 65 years (range 27-90), 53% were male, 76% white, 28 % had International Staging System stage 3, and 29% high risk cytogenetics [t(4;14), t(14;16) or del(17p)]. Median number of prior lines of therapy was 5 (range 3-17), median time from diagnosis to TCR was 4.8 years (range 0.9-19.4), 73% had received prior autologous hematopoietic cell transplantation, 84% were refractory to bortezomib or ixazomib, 58% were refractory to carfilzomib, 87% to lenalidomide and 74% to pomalidomide. Penta-exposed patients were 58% and penta-refractory 30%. The first regimen after MM became TCR included cytotoxic chemotherapy in 45%, CD38MoAb in 25%, SLAMF7 MoAb in 7%, carfilzomib in 24%, and pomalidomide in 34% of cases. Overall response rate (ORR) was 30% (20.9% PR, 7.3% VGPR and 1.7% CR). Median progression-free survival (PFS) was 2.8 mo. (95% C.I. 2.3-3.2) and overall survival (OS) 8.6 mo. (95% C.I. 6.8-10.3),(Figure). For Patients with MM that was penta-exposed (N=102), ORR was 30%, median PFS was 2.7 mo (95% C.I 2.1-3.2), and median OS 7.7 mo (95% C.I. 6.0-9.4). For patients with penta-refractory MM (N=53), ORR was 32%, median PFS was 2.5 mo. (95% C.I. 1.7-3.3), and median OS 6.9 mo. (95% C.I. 4.9-8.9). PFS or OS was similar among patients who were TCR but not penta-exposed, TCR plus penta-exposed but not penta- refractory or TCR plus penta-refractory (Figure). Outcomes according to next regimen after MM became TCR are outlined in the Table. In multivariable analysis, no factor was predictor of PFS while refractoriness to carfilzomib (HR 2.2, 95% C.I. 1.5-3.3), presence of high-risk chromosome abnormalities (HR 1.5, 95% C.I. 1.0-2.2) and short interval from diagnosis to TCR (HR 0.92, 95% C.I. 0.85-0.99) were predictors of shorter OS. Conclusions: Patients with TCR MM have a uniformly low chance of response to subsequent conventional therapy with short PFS and OS even when not penta-exposed or penta-refractory. This dataset provides efficacy benchmark for new therapies being developed in this setting. Figure 1 Figure 1. Disclosures Costa: BMS: Consultancy, Honoraria, Research Funding; Karyopharm: Consultancy, Honoraria; Sanofi: Consultancy, Honoraria, Speakers Bureau; Janssen: Consultancy, Honoraria, Research Funding; Pfizer: Consultancy, Honoraria; Amgen: Consultancy, Honoraria, Research Funding, Speakers Bureau. Cornell: Abvvie: Current Employment. Chhabra: GSK: Honoraria. Liedtke: Janssen Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Caelum: Membership on an entity's Board of Directors or advisory committees, Other: Clinical Trial Funding; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; Kite: Membership on an entity's Board of Directors or advisory committees; Kura Oncology: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Pfizer: Honoraria; GlaxoSmithKline: Membership on an entity's Board of Directors or advisory committees; Sanofi: Membership on an entity's Board of Directors or advisory committees; Alnylam: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees. Kansagra: GSK: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees; Sanofi: Membership on an entity's Board of Directors or advisory committees; Cota Health: Membership on an entity's Board of Directors or advisory committees; BMS: Membership on an entity's Board of Directors or advisory committees; Alynylam: Membership on an entity's Board of Directors or advisory committees. Giri: PackHealth: Research Funding; CareVive: Honoraria, Research Funding. Malek: Amgen: Honoraria; Janssen: Other: Advisory board ; Cumberland Inc.: Research Funding; Bluespark Inc.: Research Funding; BMS: Honoraria, Research Funding; Sanofi: Other: Advisory Board; Medpacto Inc.: Research Funding; Takeda: Honoraria. Vij: BMS: Research Funding; Takeda: Honoraria, Research Funding; Sanofi: Honoraria, Research Funding; BMS: Honoraria; GSK: Honoraria; Oncopeptides: Honoraria; Karyopharm: Honoraria; CareDx: Honoraria; Legend: Honoraria; Biegene: Honoraria; Adaptive: Honoraria; Harpoon: Honoraria. Usmani: Celgene/BMS: Consultancy, Research Funding, Speakers Bureau; Array BioPharma: Consultancy, Research Funding; Amgen: Consultancy, Research Funding, Speakers Bureau; Abbvie: Consultancy; EdoPharma: Consultancy; GSK: Consultancy, Research Funding; Janssen: Consultancy, Research Funding, Speakers Bureau; Sanofi: Consultancy, Research Funding, Speakers Bureau; Merck: Consultancy, Research Funding; Pharmacyclics: Consultancy, Research Funding; SkylineDX: Consultancy, Research Funding; Seattle Genetics: Consultancy, Research Funding; Takeda: Consultancy, Research Funding, Speakers Bureau; Janssen Oncology: Consultancy, Research Funding; Bristol-Myers Squibb: Research Funding. Hari: Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other, Research Funding, Speakers Bureau; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other, Research Funding, Speakers Bureau; GSK: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other, Research Funding, Speakers Bureau; Adaptive Biotech: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Oncopeptides: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Millenium: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other, Research Funding, Speakers Bureau; Karyopharm: Consultancy; Celgene-BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other, Research Funding, Speakers Bureau. Kumar: Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: 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; Carsgen: Research Funding; Novartis: Research Funding; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche-Genentech: Consultancy, Research Funding; Bluebird Bio: Consultancy; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Consultancy, Research Funding; Amgen: Consultancy, Research Funding; Abbvie: 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; Tenebio: Research Funding; Antengene: Consultancy, Honoraria; Beigene: Consultancy; Oncopeptides: Consultancy; Sanofi: Research Funding.

Abstract Background It is unclear how acute coronavirus disease 2019 (COVID-19)-directed therapies are used in children with life-threatening COVID-19 in US hospitals. We described characteristics of children hospitalized in the intensive care unit or step-down unit (ICU/SDU) who received COVID-19-directed therapies and the specific therapies administered. Methods Between March 15, 2020 and December 27, 2020, children <18 years of age in the ICU/SDU with acute COVID-19 at 48 pediatric hospitals in the United States were identified. Demographics, laboratory values, and clinical course were compared in children who did and did not receive COVID-19-directed therapies. Trends in COVID-19-directed therapies over time were evaluated. Results Of 424 children in the ICU/SDU, 235 (55%) received COVID-19-directed therapies. Children who received COVID-19-directed therapies were older than those who did not receive COVID-19-directed therapies (13.3 [5.6-16.2] vs 9.8 [0.65-15.9] years), more had underlying medical conditions (188 [80%] vs 104 [55%]; difference = 25% [95% CI: 16% to 34%]), more received respiratory support (206 [88%] vs 71 [38%]; difference = 50% [95% CI: 34% to 56%]), and more died (8 [3.4%] vs 0). Of the 235 children receiving COVID-19-directed therapies, 172 (73%) received systemic steroids and 150 (64%) received remdesivir, with rising remdesivir use over the study period (14% in March/April to 57% November/December). Conclusion Despite the lack of pediatric data evaluating treatments for COVID-19 in critically ill children, more than half of children requiring intensive or high acuity care received COVID-19-directed therapies.

AimThe Cockcroft‐Gault (CG) creatinine‐based equation is still used to estimate glomerular filtration rate (eGFR) for drug dosage adjustment. Incorrect eGFR may lead to hazardous over‐ or underdosing.MethodsIn a cross‐sectional analysis, CG was validated against measured GFR (mGFR) in 14 804 participants and compared with the Modification‐of‐Diet‐in‐Renal‐Diseases (MDRD), Chronic‐Kidney‐Disease‐Epidemiology (CKD‐EPI), Lund‐Malmö‐Revised (LMR) and European‐Kidney‐Function‐Consortium (EKFC) equations. Validation focused on bias, imprecision and accuracy (percentage of estimates within ±30% of mGFR, P30), overall and stratified for mGFR, age and body mass index at mGFR <60 mL/min, as well as classification in mGFR stages.ResultsThe CG equation performed worse than the other equations, overall and in mGFR, age and BMI subgroups in terms of bias (systematic overestimation), imprecision and accuracy except for patients ≥65 years where bias and P30 were similar to MDRD and CKD‐EPI, but worse than LMR and EKFC. In subjects with mGFR <60 mL/min and at BMI 18.5‐25 kg/m2, all equations performed similarly, and for BMI < 18.5 kg/m2 CG and LMR had the best results though all equations had poor P30‐accuracy. At BMI ≥ 25 kg/m2 the bias of the CG increased with increasing BMI (+17.2 mL/min at BMI ≥ 40 kg/m2). The four more recent equations also classified mGFR stages better than CG.ConclusionsThe CG equation showed poor ability to estimate GFR overall and in analyses stratified for mGFR, age and BMI. CG was inferior to correctly classify the patients in the mGFR staging compared to more recent creatinine‐based equations.

With novel mutant SARS-CoV-2 variants of concern on the rise, knowledge of immune specificities against SARS-CoV-2 proteins is increasingly important for understanding the impact of structural changes in antibody-reactive protein epitopes on naturally acquired and vaccine-induced immunity, as well as broader topics of cross-reactivity and viral evolution. A multi-coronavirus protein microarray used to map the binding of COVID-19 patient antibodies to SARS-CoV-2 proteins and protein fragments as well as to the proteins of four other coronaviruses that infect humans has shown specific regions of SARS-CoV-2 proteins that are highly reactive with patient antibodies and revealed cross-reactivity of these antibodies with other human coronaviruses.

Abstract The congenital heart care community faces a myriad of public health issues that act as barriers toward optimum patient outcomes. In this article, we attempt to define advocacy and policy initiatives meant to spotlight and potentially address these challenges. Issues are organized into the following 3 key facets of our community: patient population, health care delivery, and workforce. We discuss the social determinants of health and health care disparities that affect patients in the community that require the attention of policy makers. Furthermore, we highlight the many needs of the growing adults with congenital heart disease and those with comorbidities, highlighting concerns regarding the inequities in access to cardiac care and the need for multidisciplinary care. We also recognize the problems of transparency in outcomes reporting and the promising application of telehealth. Finally, we highlight the training of providers, measures of productivity, diversity in the workforce, and the importance of patient–family centered organizations in advocating for patients. Although all of these issues remain relevant to many subspecialties in medicine, this article attempts to illustrate the unique needs of this population and highlight ways in which to work together to address important opportunities for change in the cardiac care community and beyond. This article provides a framework for policy and advocacy efforts for the next decade.

Background: Peripheral artery disease (PAD) affects >200 million people worldwide and is associated with high mortality and morbidity. We sought to identify genomic variants associated with PAD overall and in the contexts of diabetes and smoking status. Methods: We identified genetic variants associated with PAD and then meta-analyzed with published summary statistics from the Million Veterans Program and UK Biobank to replicate their findings. Next, we ran stratified genome-wide association analysis in ever smokers, never smokers, individuals with diabetes, and individuals with no history of diabetes and corresponding interaction analyses, to identify variants that modify the risk of PAD by diabetic or smoking status. Results: We identified 5 genome-wide significant ( P association ≤5×10 −8 ) associations with PAD in 449 548 (N cases =12 086) individuals of European ancestry near LPA (lipoprotein [a]), CDKN2BAS1 (CDKN2B antisense RNA 1), SH2B3 (SH2B adaptor protein 3) - PTPN11 (protein tyrosine phosphatase non-receptor type 11), HDAC9 (histone deacetylase 9), and CHRNA3 (cholinergic receptor nicotinic alpha 3 subunit ) loci (which overlapped previously reported associations). Meta-analysis with variants previously associated with PAD showed that 18 of 19 published variants remained genome-wide significant. In individuals with diabetes, rs116405693 at the CCSER1 (coiled-coil serine rich protein 1 ) locus was associated with PAD (odds ratio [95% CI], 1.51 [1.32–1.74], P diabetes =2.5×10 −9 , P interactionwithdiabetes =5.3×10 −7 ). Furthermore, in smokers, rs12910984 at the CHRNA3 locus was associated with PAD (odds ratio [95% CI], 1.15 [1.11–1.19], P smokers =9.3×10 −10 , P interactionwithsmoking =3.9×10 −5 ). Conclusions: Our analyses confirm the published genetic associations with PAD and identify novel variants that may influence susceptibility to PAD in the context of diabetes or smoking status.