Citations

BRCA2 is essential for homologous recombination DNA repair. BRCA2 mutations lead to genome instability and increased risk of breast and ovarian cancer. Similarly, mutations in BRCA2-interacting proteins are also known to modulate sensitivity to DNA damage agents and are established cancer risk factors. Here we identify the tumor suppressor CDK5RAP3 as a novel BRCA2 helical domain-interacting protein. CDK5RAP3 depletion induced DNA damage resistance, homologous recombination and single-strand annealing upregulation, and reduced spontaneous and DNA damage-induced genomic instability, suggesting that CDK5RAP3 negatively regulates double-strand break repair in the S-phase. Consistent with this cellular phenotype, analysis of transcriptomic data revealed an association between low CDK5RAP3 tumor expression and poor survival of breast cancer patients. Finally, we identified common genetic variations in the CDK5RAP3 locus as potentially associated with breast and ovarian cancer risk in BRCA1 and BRCA2 mutation carriers. Our results uncover CDK5RAP3 as a critical player in DNA repair and breast cancer outcomes.

Abstract Purpose: Diffuse large B-cell lymphoma (DLBCL) is molecularly and clinically heterogeneous, and can be subtyped according to genetic alterations, cell-of-origin, or microenvironmental signatures using high-throughput genomic data at the DNA or RNA level. Although high-throughput proteomic profiling has not been available for DLBCL subtyping, MYC/BCL2 protein double expression (DE) is an established prognostic biomarker in DLBCL. The purpose of this study is to reveal the relative prognostic roles of DLBCL genetic, phenotypic, and microenvironmental biomarkers. Experimental Design: We performed targeted next-generation sequencing; IHC for MYC, BCL2, and FN1; and fluorescent multiplex IHC for microenvironmental markers in a large cohort of DLBCL. We performed correlative and prognostic analyses within and across DLBCL genetic subtypes and MYC/BCL2 double expressors. Results: We found that MYC/BCL2 double-high-expression (DhE) had significant adverse prognostic impact within the EZB genetic subtype and LymphGen-unclassified DLBCL cases but not within MCD and ST2 genetic subtypes. Conversely, KMT2D mutations significantly stratified DhE but not non-DhE DLBCL. T-cell infiltration showed favorable prognostic effects within BN2, MCD, and DhE but unfavorable effects within ST2 and LymphGen-unclassified cases. FN1 and PD-1–high expression had significant adverse prognostic effects within multiple DLBCL genetic/phenotypic subgroups. The prognostic effects of DhE and immune biomarkers within DLBCL genetic subtypes were independent although DhE and high Ki-67 were significantly associated with lower T-cell infiltration in LymphGen-unclassified cases. Conclusions: Together, these results demonstrated independent and additive prognostic effects of phenotypic MYC/BCL2 and microenvironment biomarkers and genetic subtyping in DLBCL prognostication, important for improving DLBCL classification and identifying prognostic determinants and therapeutic targets.

Introduction : Fetal posterior cerebral artery (FPCA) occlusion is a rare but potentially disabling cause of stroke. While endovascular treatment is established for acute large vessel occlusion (LVO) stroke, FPCA occlusions were excluded from acute ischemic stroke trials. We aim to report the feasibility, safety and outcome of mechanical thrombectomy (MT) in acute FPCA occlusions. Methods : We performed a multi‐center retrospective review of consecutive patients who underwent MT of acute FPCA occlusion. Primary FPCA occlusion was defined as an occlusion that was identified on the pre‐procedure CT angiogram or baseline angiogram whereas a secondary FPCA occlusion was defined as an occlusion that occurred secondary to embolization to a new territory after recanalization of a different LVO. Demographics, clinical presentation, imaging findings, endovascular treatment and outcome were reviewed. Results : There were twenty‐five patients with acute FPCA occlusion who underwent MT, distributed across 14 centers. Median NIHSS on presentation was 16. There were 76% (19/25) of patients who presented with primary FPCA occlusion and 24% (6/25) of patients who had a secondary FPCA occlusion. The configuration of the FPCA was full in 64% patients and partial or “fetal‐type” in 36% of patients. FPCA occlusion was missed on initial CTA in 21% of patients with primary FPCA occlusion (4/19). The site of occlusion was posterior communicating artery in 52%, P2 segment in 40% and P3 in 8% of patients. TICI 2b/3 reperfusion was achieved in 96% of FPCA patients. There were no intra‐procedural complications. At 90 days, 48% (12/25) were functionally independent as defined by mRS≤2. Conclusions : Endovascular treatment of acute FPCA occlusion is safe and technically feasible. A high index of suspicion is important to detect occlusion of the fetal posterior cerebral artery in patients presenting with anterior circulation stroke syndrome and patent anterior circulation.

PURPOSE Palbociclib is a cyclin-dependent kinase 4 and 6 inhibitor approved for advanced breast cancer. In the adjuvant setting, the potential value of adding palbociclib to endocrine therapy for hormone receptor–positive breast cancer has not been confirmed. PATIENTS AND METHODS In the prospective, randomized, phase III PALLAS trial, patients with hormone receptor–positive, human epidermal growth factor receptor 2–negative early breast cancer were randomly assigned to receive 2 years of palbociclib (125 mg orally once daily, days 1-21 of a 28-day cycle) with adjuvant endocrine therapy or adjuvant endocrine therapy alone (for at least 5 years). The primary end point of the study was invasive disease-free survival (iDFS); secondary end points were invasive breast cancer–free survival, distant recurrence-free survival, locoregional cancer-free survival, and overall survival. RESULTS Among 5,796 patients enrolled at 406 centers in 21 countries worldwide over 3 years, 5,761 were included in the intention-to-treat population. At the final protocol-defined analysis, at a median follow-up of 31 months, iDFS events occurred in 253 of 2,884 (8.8%) patients who received palbociclib plus endocrine therapy and in 263 of 2,877 (9.1%) patients who received endocrine therapy alone, with similar results between the two treatment groups (iDFS at 4 years: 84.2% v 84.5%; hazard ratio, 0.96; CI, 0.81 to 1.14; P = .65). No significant differences were observed for secondary time-to-event end points, and subgroup analyses did not show any differences by subgroup. There were no new safety signals for palbociclib in this trial. CONCLUSION At this final analysis of the PALLAS trial, the addition of adjuvant palbociclib to standard endocrine therapy did not improve outcomes over endocrine therapy alone in patients with early hormone receptor–positive breast cancer.

PURPOSE Calcineurin inhibitors (CNI) are standard components of graft-versus-host disease (GVHD) prophylaxis after hematopoietic cell transplantation (HCT). Prior data suggested that CNI-free approaches using donor T-cell depletion, either by ex vivo CD34 selection or in vivo post-transplant cyclophosphamide (PTCy) as a single agent, are associated with lower rates of chronic GVHD (cGVHD). METHODS This multicenter phase III trial randomly assigned patients with acute leukemia or myelodysplasia and an HLA-matched donor to receive CD34-selected peripheral blood stem cell, PTCy after a bone marrow (BM) graft, or tacrolimus and methotrexate after BM graft (control). The primary end point was cGVHD (moderate or severe) or relapse-free survival (CRFS). RESULTS Among 346 patients enrolled, 327 received HCT, 300 per protocol. Intent-to-treat rates of 2-year CRFS were 50.6% for CD34 selection (hazard ratio [HR] compared with control, 0.80; 95% CI, 0.56 to 1.15; P = .24), 48.1% for PTCy (HR, 0.86; 0.61 to 1.23; P = .41), and 41.0% for control. Corresponding rates of overall survival were 60.1% (HR, 1.74; 1.09 to 2.80; P = .02), 76.2% (HR, 1.02; 0.60 to 1.72; P = .95), and 76.1%. CD34 selection was associated with lower moderate to severe cGVHD (HR, 0.25; 0.12 to 0.52; P = .02) but higher transplant-related mortality (HR, 2.76; 1.26 to 6.06; P = .01). PTCy was associated with comparable cGVHD and survival outcomes to control, and a trend toward lower disease relapse (HR, 0.52; 0.28 to 0.96; P = .037). CONCLUSION CNI-free interventions as performed herein did not result in superior CRFS compared with tacrolimus and methotrexate with BM. Lower rates of moderate and severe cGVHD did not translate into improved survival.

Abstract Introduction: Multiple studies have demonstrated that diffuse large B-cell lymphoma (DLBCL) can be divided into subgroups based on their biology. However, these biological subgroups overlap clinically. While R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone) remains the standard of care for treating patients with DLBCL, predicting which patients will not benefit from such therapy is important so that alternative therapy or clinical trials can be considered. Most of the studies stratifying patients select biomarkers first, then explore how these biomarkers can stratify patients based on outcome. We explored the potential of using machine learning to first group patients with DLBCL based on survival, then isolating the biomarkers necessary for predicting these survival subgroups. Methods: RNA was extracted from tissue paraffin blocks from 379 R-CHOP treated patients with de novo DLBCL, and from 247 patients with extranodal DLBCL. A targeted hybrid capture RNA panel of 1408 genes was used for next generation sequencing (NGS). Sequencing was performed using an Illumina NextSeq 550 System platform. Ten million reads per sample in a single run were required, and the read length was 2 × 150 bp. An expression profile was generated from the sequencing coverage profile of each individual sample using Cufflinks. A machine learning system was developed to classify patients into four groups based on their overall survival. This machine learning approach based on Naïve Bayesian algorithm was also used to discover the relevant subset of genes with which to classify patients into each of the four survival groups. To eliminate the underflow problem commonly associated with the standard Naïve Bayesian classifiers, we applied Geometric Mean Naïve Bayesian (GMNB) as the classifier to predict the survival group for each patient. Results: Using machine learning, patients were first divided into two groups: short survival (S) and long survival (L). To refine this model, we used the same approach and divided the patients in each group into two subgroups, generating four groups: long survival in the long group (LL), short survival in the long group (LS), long survival in the short group (SL), and short survival in the short group (SS). The hazard ratio for this model was 0.174 (confidence interval: 0.120-0.251), and P-value <0.0001. After defining these four groups, a machine learning algorithm was used to discover the biomarkers from the expression data of the 1408 genes from NGS data. To reduce the effects of noise and avoid overfitting, we employed a 12-step cross validation to obtain a robust measure. For an individual gene, a generalized Naïve Bayesian classifier was constructed on the training of one of the 12 subsets and tested on the other 11 testing subsets. This allowed us to limit the prediction process to 60 genes for each separation step. Using the selected biomarkers, we classified the patients in the original set (379 patients) into LL, LS, SL, and SS groups and then evaluated the survival pattern of these groups. As shown in Fig. 1A, the selected biomarkers predicted survival as expected in the overall survival groups prior to biomarker selection. For additional validation of the system, we used the selected biomarkers to classify a completely new set of 247 samples of patients with extranodal DLBCL. As shown in Fig. 1B, these selected biomarkers successfully predicted the overall survival in this group of patients with an HR of 0.530 (confidence interval: 0.234-1.197, P=0.005). This classification correlated with cell of origin classification, TP53 mutation status, MYC expression, and IRF4 expression. However, in a multivariate analysis, only TP53 mutation was independent in predicting prognosis (P=0.005) and age (below or over 60) (P=0.01) along with the survival grouping (P<0.000001). Conclusions: Using a novel machine learning approach with the expression levels of 180 genes, we developed a model that can reliably stratify patients with DLBCL treated with R-CHOP into four survival subgroups. This model can be used to identify patients who may not respond well to R-CHOP to be considered for alternative therapy and clinical trials. Figure 1 Figure 1. Disclosures Hsi: AbbVie Inc, Eli Lilly: Research Funding. Ferreri: Ospedale San Raffaele srl: Patents & Royalties; BMS: Research Funding; Pfizer: Research Funding; Beigene: Research Funding; Hutchison Medipharma: Research Funding; Amgen: Research Funding; Genmab: Research Funding; ADC Therapeutics: Research Funding; Gilead: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche: Membership on an entity's Board of Directors or advisory committees, Research Funding; PletixaPharm: Membership on an entity's Board of Directors or advisory committees; x Incyte: Membership on an entity's Board of Directors or advisory committees; Adienne: Membership on an entity's Board of Directors or advisory committees. Piris: Millenium/Takeda, EUSA, Jansen, NanoString, Kyowa Kirin, Gilead and Celgene.: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Winter: BMS: Other: Husband: Data and Safety Monitoring Board; Actinium Pharma: Consultancy; Janssen: Other: Husband: Consultancy; Agios: Other: Husband: Consultancy; Gilead: Other: Husband: Consultancy; Epizyme: Other: Husband: Data and Safety Monitoring Board; Ariad/Takeda: Other: Husband: Data and Safety Monitoring Board; Merck: Consultancy, Honoraria, Research Funding; Novartis: Other: Husband: Consultancy, Data and Safety Monitoring Board; Karyopharm (Curio Science): Honoraria.

Abstract Introduction: The gut microbiome is a potentially modifiable factor in treatment related outcomes in allogeneic hematopoietic cell transplant (HCT). Prior studies have linked pre- or mid-treatment gut microbiome diversity with risk for treatment related morbidity and mortality. However, these studies have been limited by the inclusion of one or only a few institutions and the lack of longitudinal sampling with high quality metadata. These limitations complicate the interpretation of microbiome alterations over the course of HCT. Methods: To overcome these, we devised and implemented a large-scale biospecimen collection protocol in conjunction with BMT CTN 1703, a randomized, multicenter, Phase III trial of tacrolimus/methotrexate vs. post-transplant cyclophosphamide/tacrolimus/mycophenolate mofetil in reduced intensity conditioning (RIC) allogeneic HCT (NCT03959241). Patients enrolled on 1703 were optionally co-enrolled in the companion immune and microbiome profiling study, 1801 (MI-IMMUNE). This involved blood, urine and stool sampling before conditioning (PCON), then weekly starting on day 0 through day 77 (through day 84 for blood), and on days 98, 180, 270, 365 and 730. For all enrolled participants where the donor consented, residual donor cells were saved from the empty hematopoietic stem cell product bag for later analysis. Additionally, the protocol included one-time blood, urine and stool sample collection from consented matched related donors (MRDs) prior to stem cell collection. Starting with protocol version 4.0 on February 1, 2021, participation in 1801 stool collection was required for the first six out of eighteen sample collection timepoints. Participation in later stool and urine timepoint collections remained optional. Here we review the feasibility of creating a multi-institutional biobank. Additionally, we assess the success of our strategies by calculating sample collection compliance and standard deviation in compliance across centers for each timepoint. Results: On June 18, 2021, BMT CTN 1703/1801 closed to accrual with 431 patients enrolled on 1703; 323 patients from 36 centers were co-enrolled on 1801. 304 (94%) provided study samples, making this the largest prospective microbiome and immune profiling study in HCT patients to date. As of July 6, 2021, 3,683 blood, 2,668 urine, and 2,098 stool samples had been collected. Across the first 6 timepoints for all participating centers, blood, urine and stool sample collection averaged 93%, 82%, and 74% compliance, respectively. Of the 99 (30%) patients enrolled on 1801 with a MRD, 34 (34%) donors consented to sample collection. Sample collection compliance was lower for MRDs than for patients on the study with 76%, 74%, and 62% of expected blood, urine and stool samples collected, respectively, from this group. For stool collection exclusively, a median of 5 samples were collected per patient across the first 6 timepoints (median of 6 across all timepoints) with 93 (31%) of patients completing a full sample set through Day 28. 139 (46%) patients provided at least one sample after day 28; these represented 37% of the total samples collected to date. The PCON sample, which provides an important measure of pre-treatment gut microbiome diversity, had the third highest compliance with 74% of patients providing a sample. Surprisingly, Day 28 had the lowest compliance (66%) and highest standard deviation (37%) possibly because this timepoint often falls around the time of hospital discharge. Between PCON and day 28, the standard deviation between sites in the average collection compliance (24%) and number of samples collected per patient (1.1) was small indicating the successful adoption of stool collection across institutions. Table 1 summarizes sample collection statistics. Conclusion: Overall this study has resulted in a large, novel biobank of blood, urine and stool samples from patients undergoing RIC allogeneic HCT at 36 centers across the US. This will serve as a valuable resource for investigating the role of the gut microbiome in long term health outcomes following HCT. Although the results of 1801 are forthcoming given ongoing sample collection, the size and composition of the biobank to date clearly demonstrate the feasibility of implementing multi-institutional stool collection. This study represents a critical step towards the large-scale adoption of microbiome sampling as a diagnostic tool. Figure 1 Figure 1. Disclosures Chhabra: GSK: Honoraria. Clark: Kadmon: Consultancy. Horowitz: Mesoblast: Research Funding; Shire: Research Funding; Vertex: Research Funding; Stemcyte: Research Funding; Vor Biopharma: Research Funding; Janssen: Research Funding; Miltenyi Biotech: Research Funding; Kiadis: Research Funding; Sobi: Research Funding; Kite/Gilead: Research Funding; Pfizer, Inc: Research Funding; Jazz Pharmaceuticals: Research Funding; Magenta: Consultancy, Research Funding; Medac: Research Funding; Novartis: Research Funding; GlaxoSmithKline: Research Funding; Daiicho Sankyo: Research Funding; Xenikos: Research Funding; Omeros: Research Funding; Orca Biosystems: Research Funding; Pharmacyclics: Research Funding; Regeneron: Research Funding; Tscan: Research Funding; Takeda: Research Funding; CSL Behring: Research Funding; Genentech: Research Funding; Gamida Cell: Research Funding; Chimerix: Research Funding; Bristol-Myers Squibb: Research Funding; bluebird bio: Research Funding; Astellas: Research Funding; Amgen: Research Funding; Allovir: Consultancy; Actinium: Research Funding; Sanofi: Research Funding; Seattle Genetics: Research Funding. Jenq: Microbiome DX: Consultancy; Merck: Consultancy; Prolacta: Consultancy, Membership on an entity's Board of Directors or advisory committees; Kaleido: Consultancy, Current holder of stock options in a privately-held company, Membership on an entity's Board of Directors or advisory committees, Research Funding; Seres: Consultancy, Current holder of stock options in a privately-held company, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties, Research Funding; LisCure: Consultancy, Membership on an entity's Board of Directors or advisory committees; MaaT Pharma: Consultancy, Membership on an entity's Board of Directors or advisory committees; Karius: Consultancy. Levine: Equillium Bio: Membership on an entity's Board of Directors or advisory committees; Incyte: Consultancy, Research Funding; Kamada: Research Funding; Biogen: Research Funding; Omeros: Membership on an entity's Board of Directors or advisory committees; Symbio: Membership on an entity's Board of Directors or advisory committees; Jazz Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Talaris Therapeutics: Membership on an entity's Board of Directors or advisory committees; Viracor: Patents & Royalties: GVHD biomarker patent with royalties from Viracor; Mesoblast: Consultancy, Research Funding; X4 Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees. Murthy: CRISPR Therapeutics: Research Funding. Riches: ATARA Biotherapeutics: Other: Payment; BioIntelect: Membership on an entity's Board of Directors or advisory committees; Jazz Pharmaceuticals: Other: Payment. Sung: Merck: Research Funding; Novartis: Research Funding; Enterome: Research Funding; Seres: Research Funding; AVROBIO: Consultancy; Abbott Nutrition: Honoraria; Clasado: Other: Research Product; DSM: Other: Research Product. Al Malki: Neximmune: Consultancy; Jazz Pharmaceuticals, Inc.: Consultancy; Rigel Pharma: Consultancy; Hansa Biopharma: Consultancy; CareDx: Consultancy. Rezvani: Kaleido: Other: One-time scientific advisory board; Nohla Therapeutics: Other: One-time scientific advisory board; Pharmacyclics-Abbvie: Research Funding; US Department of Justice: Consultancy. Bolaños-Meade: Incyte Corp: Consultancy. Holtan: Incyte: Consultancy, Research Funding; Generon: Consultancy. Saber: Govt. COI: Other. Hamadani: Sanofi, Genzyme, AstraZeneca, BeiGene: Speakers Bureau; Janssen, Incyte, ADC Therapeutics, Omeros, Morphosys, Kite: Consultancy; Takeda, Spectrum Pharmaceuticals and Astellas Pharma: Research Funding. Kean: Bluebird Bio: Research Funding; Bristol Myers Squibb: Patents & Royalties: From clinical trial data, Research Funding; Vertex: Consultancy; Novartis: Consultancy; Gilead: Research Funding; Regeneron: Research Funding; EMD Serono: Consultancy. Perales: Cidara: Honoraria; Servier: Honoraria; Incyte: Honoraria, Other; Equilium: Honoraria; Takeda: Honoraria; Novartis: Honoraria, Other; Nektar Therapeutics: Honoraria, Other; NexImmune: Honoraria; MorphoSys: Honoraria; Omeros: Honoraria; Karyopharm: Honoraria; Sellas Life Sciences: Honoraria; Merck: Honoraria; Miltenyi Biotec: Honoraria, Other; Medigene: Honoraria; Bristol-Myers Squibb: Honoraria; Kite/Gilead: Honoraria, Other; Celgene: Honoraria.

Abstract Background and Rationale: Axi-cel is a standard-of-care treatment for relapsed or refractory LBCL after 2 or more lines of systemic therapy. Some patients who would have been ineligible for ZUMA-1 criteria due to comorbidities have been treated with axi-cel in the real-world setting. We interrogated a large registry of patients treated with standard-of-care axi-cel for a definitive report on the impact of age or certain comorbidities on safety and efficacy outcomes after axi-cel infusion. Methods: From October 2017 to August 2020, 1500 patients were enrolled in the postapproval safety observational study of axi-cel treated at 79 centers. Patients eligible for the protocol and followed up for at least 6 months with complete data entry by the time of analyses were included. One patient rescinded consent and 1 was deemed ineligible. Patients previously treated with immune effector cell therapy (n=31), with incomplete follow-up reporting (n=92), or alive but last contacted <180 days postinfusion (n=32) were excluded from analysis. Main efficacy outcomes included complete and objective response rates (CR and ORR), duration of response (DOR), progression-free and overall survival (PFS and OS). Safety endpoints of interest included cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS). Outcomes were assessed and compared by age and preselected coexisting disease or organ impairment within 3 months prior to the infusion included in the hematopoietic cell transplantation comorbidity index. Multivariate logistic and Cox regression models were used to assess the impact of age or coexistent organ dysfunction on outcomes via odds ratio (OR) or hazard ratio (HR) and their 95% CIs. Results A total of 1343 patients were included in the analysis with a median 25.1 months (range, 10.3-42.7 months) for potential follow-up, defined from infusion to data cutoff date, and a median 11.8 months (range, 0.1-38.8 months) for actual follow-up time, defined from infusion to date of death or last contact. Of these, 38% were 65 years or older (median 62 years), 4% had a performance score ≥2, 13% had cardiac comorbidities, 16% had a prior cancer, 9% were obese, 2% had moderate to severe hepatic comorbidities, and 2% had renal comorbidities. Transformed lymphoma, double or triple-hit by fluorescence in situ hybridization, prior autologous transplant and refractory disease were present in 28%, 15%, 27% and 66%, respectively. Bridging therapy was administered in 21% of patients. Overall, ORR was 74%, (CR 56%), and probabilities of DOR, PFS, and OS at 18 months were 61% (95% CI, 57-65%), 42% (95% CI, 39-45%) and 52% (95% CI, 49-55%), respectively. Overall rates of CRS and ICANS were 83% and 55%, respectively. ORR was 78% (CR 62%, median OS 17.5 [95% CI, 16.0-not evaluated (NE)] months) for patients ≥65 years, ORR 57% (CR 29%; median OS 4.3 [95% CI, 2.5-8.3] months) for patients with hepatic dysfunction, ORR 70% (CR 43%; median OS 8.9 [95% CI, 3.8-NE] months) for patients with renal dysfunction; and ORR 47% (CR 20%, median OS 4 [95% CI, 2.6-6.9] months) for patients with Eastern Cooperative Oncology Group (ECOG) 2 or 3. Multivariate analyses indicated that advanced age (≥65 years vs <65 years; OR 1.38; 95% CI, 1.05-1.83), moderate to severe pulmonary disease (yes vs no; OR 0.74; 95% CI, 0.55-0.98), and ECOG (2-3 vs 0-1; OR 0.31, 95% CI, 0.18-0.53) impacted ORR (Table). Age ≥65 years did not have an impact on survival (HR 1.05, 95% CI, 0.88-1.26), although it was associated with CRS (OR 1.42, 95% CI, 1.03-1.96) and ICANS (OR 1.78, 95% CI, 1.39-2.28). Coexistent cardiac disease (HR 1.44, 95% CI, 1.12-1.83), renal disease (HR 2.13, 95% CI, 1.32-3.46) and hepatic dysfunction (HR 2.65, 95% CI, 1.69-4.14) had an impact on OS, but not on response, CRS, and ICANS. ECOG significantly impacted all efficacy outcomes. None of the other comorbidities tested significantly impacted outcomes. Conclusion: Advanced age (≥65 years) was not associated with worse efficacy outcomes after axi-cel, despite higher rates of CRS and ICANS, which require closer monitoring. Performance status rather than age should be accounted for in patient selection and treatment decisions with axi-cel. Most coexistent organ dysfunctions have no clinically significant impact on axi-cel objective response and safety outcomes. Figure 1 Figure 1. Disclosures Locke: Moffitt Cancer Center: Patents & Royalties: field of cellular immunotherapy; Allogene Therapeutics: Consultancy, Other: Scientific Advisory Role, Research Funding; Amgen: Consultancy, Other: Scientific Advisory Role; Bluebird Bio: Consultancy, Other: Scientific Advisory Role; EcoR1: Consultancy; Emerging Therapy Solutions: Consultancy; Gerson Lehrman Group: Consultancy; Iovance Biotherapeutics: Consultancy, Other: Scientific Advisory Role; Takeda: Consultancy, Other; Novartis: Consultancy, Other, Research Funding; Wugen: Consultancy, Other; GammaDelta Therapeutics: Consultancy, Other: Scientific Advisory Role; Umoja: Consultancy, Other; Cellular Biomedicine Group: Consultancy, Other: Scientific Advisory Role; Calibr: Consultancy, Other: Scientific Advisory Role; Cowen: Consultancy; BMS/Celgene: Consultancy, Other: Scientific Advisory Role; Legend Biotech: Consultancy, Other; Kite, a Gilead Company: Consultancy, Other: Scientific Advisory Role, Research Funding; Janssen: Consultancy, Other: Scientific Advisory Role. Jacobson: Axis: Speakers Bureau; Nkarta: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria, Other: Travel support, Research Funding; AbbVie: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Other: Travel support; Novartis Pharmaceuticals Corporation: Consultancy, Honoraria, Other: Travel support; Precision Biosciences: Consultancy, Honoraria, Other: Travel support; Kite, a Gilead Company: Consultancy, Honoraria, Other: Travel support; Lonza: Consultancy, Honoraria, Other: Travel support; Humanigen: Consultancy, Honoraria, Other: Travel support; Clinical Care Options: Speakers Bureau. Ma: Kite, a Gilead Company: Current Employment. Dong: Kite, a Gilead Company: Current Employment. Hu: Kite, a Gilead Company: Research Funding; Novartis: Research Funding; Celgene: Research Funding. Siddiqi: BMS: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Oncternal: Research Funding; Janssen: Speakers Bureau; Juno Therapeutics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Kite Pharma: Membership on an entity's Board of Directors or advisory committees, Research Funding; BeiGene: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; AstraZeneca: 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; Pharmacyclics LLC, an AbbVie Company: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; TG Therapeutics: Research Funding. Ahmed: Seagen: Research Funding; Tessa Therapeutics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Research Funding; Xencor: Research Funding. Ghobadi: Atara: Consultancy; Wugen: Consultancy; Amgen: Consultancy, Research Funding; Kite, a Gilead Company: Consultancy, Honoraria, Research Funding; Celgene: Consultancy. Miklos: Pharmacyclics: Patents & Royalties; Kite, a Gilead Company, Amgen, Atara, Wugen, Celgene, Novartis, Juno-Celgene-Bristol Myers Squibb, Allogene, Precision Bioscience, Adicet, Pharmacyclics, Janssen, Takeda, Adaptive Biotechnologies and Miltenyi Biotechnologies: Consultancy; Pharmacyclics, Amgen, Kite, a Gilead Company, Novartis, Roche, Genentech, Becton Dickinson, Isoplexis, Miltenyi, Juno-Celgene-Bristol Myers Squibb, Allogene, Precision Biosciences, Adicet, Adaptive Biotechnologies: Research Funding; Adaptive Biotechnologies, Novartis, Juno/Celgene-BMS, Kite, a Gilead Company, Pharmacyclics-AbbVie, Janssen, Pharmacyclics, AlloGene, Precision Bioscience, Miltenyi Biotech, Adicet, Takeda: Membership on an entity's Board of Directors or advisory committees. Lin: Kite, a Gilead Company: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Legend: Consultancy; Vineti: Consultancy; Sorrento: Consultancy; Gamida Cell: Consultancy; Janssen: Consultancy, Research Funding; Juno: Consultancy; Bluebird Bio: Consultancy, Research Funding; Novartis: Consultancy; Merck: Research Funding; Takeda: Research Funding. Perales: Bristol-Myers Squibb: Honoraria; Takeda: Honoraria; Nektar Therapeutics: Honoraria, Other; Miltenyi Biotec: Honoraria, Other; MorphoSys: Honoraria; NexImmune: Honoraria; Sellas Life Sciences: Honoraria; Cidara: Honoraria; Merck: Honoraria; Omeros: Honoraria; Servier: Honoraria; Celgene: Honoraria; Novartis: Honoraria, Other; Kite/Gilead: Honoraria, Other; Incyte: Honoraria, Other; Medigene: Honoraria; Karyopharm: Honoraria; Equilium: Honoraria. Lunning: Daiichi-Sankyo: Consultancy; TG Therapeutics: Consultancy; Kite, a Gilead Company: Consultancy; ADC Therapeutics: Consultancy; Spectrum: Consultancy; Beigene: Consultancy; Celgene, a Bristol Myers Squibb Co.: Consultancy; Legend: Consultancy; AbbVie: Consultancy; AstraZeneca: Consultancy; Morphosys: Consultancy; Verastem: Consultancy; Novartis: Consultancy; Myeloid Therapeutics: Consultancy; Janssen: Consultancy; Acrotech: Consultancy; Kyowa Kirin: Consultancy; Karyopharm: Consultancy. Hill: Gentenech: Consultancy, Honoraria, Research Funding; Incyte/Morphysis: Consultancy, Honoraria, Research Funding; Beigene: Consultancy, Honoraria, Research Funding; Pfizer: Consultancy, Honoraria; Kite, a Gilead Company: Consultancy, Honoraria, Other: Travel Support, Research Funding; Karyopharm: Consultancy, Honoraria, Research Funding; AstraZenica: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria, Research Funding; Epizyme: Consultancy, Honoraria; Celgene (BMS): Consultancy, Honoraria, Research Funding. 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. Xu: Gilead Sciences: Other: stock or other ownership ; Kite, A Gilead Company: Current Employment. Pasquini: Bristol Myers Squibb: Consultancy, Research Funding; Novartis: Research Funding; Kite Pharma: Research Funding; GlaxoSmithKline: Research Funding.

Abstract Introduction Tafasitamab is a humanized, Fc-modified, anti-CD19 monoclonal antibody (mAb) shown to enhance antibody-dependent cellular cytotoxicity and phagocytosis. It is approved by the FDA under accelerated approval (July 2020) in combination with lenalidomide (LEN) for treatment of relapsed/refractory diffuse large B-cell lymphoma (R/R DLBCL) in adult patients ineligible for autologous stem cell transplantation. To evaluate if newly diagnosed DLBCL patients would also benefit from this regimen, this Phase Ib study (First-MIND; NCT04134936) was designed to first assess the safety and tolerability of tafasitamab ± LEN in addition to rituximab, cyclophosphamide, doxorubicin, vincristine and prednisone (R-CHOP) in newly diagnosed DLBCL patients. Methods Eligible patients were ≥18 years old, with treatment-naïve DLBCL, international prognostic index (IPI) 2-5 and Eastern Cooperative Oncology Group performance status (ECOG PS) 0-2. Patients with known double- or triple-hit and transformed lymphoma were excluded. Patients were randomized 1:1 to either six 21-day [D] cycles of R-CHOP (R-CHO, D1; P, D1-5) + tafasitamab (12 mg/kg IV, D1, 8, 15) (Arm A) or R-CHOP + tafasitamab + LEN (25 mg orally, D1-10) (Arm B). Granulocyte colony-stimulating factor and venous thromboembolism prophylaxis was mandatory. The primary safety endpoint was incidence of treatment-emergent adverse events (TEAEs); secondary endpoints included overall response rate (ORR), positron emission tomography (PET)-complete response (CR) rate, and partial response (PR) rate at end of treatment (EOT). Tumor measurements by PET/CT or PET/MRI at EOT were performed according to Lugano 2014 criteria within 6±2 weeks after Day 21 of the last treatment cycle the patient started. Results From December 2019 to August 2020, 83 patients were screened in nine countries across 34 sites in Europe and the US; 66 were randomized (Arm A, n=33; Arm B, n=33). Data cut-off for this analysis: 13 March 2021. Median age was 64.5 years (range 20-86). Many patients had high-risk disease: IPI 2: 24/66 (36.4%), IPI 3: 29/66 (43.9%), IPI 4: 11/66 (16.7%), IPI 5: 2/66 (3.0%); ECOG PS ≥2: 6/66 (9.1%). Most patients had Stage III/IV disease 62/66 (93.9%); 29/66 (43.9%) had bulky disease. All patients experienced at least one TEAE. The most frequent Grade ≥3 TEAEs by system organ class were blood and lymphatic disorders (81.8% patients overall), experienced by 24 patients (72.7%) in Arm A and 30 patients (90.9%) in Arm B. Grade ≥3 neutropenia and thrombocytopenia occurred in 19/33 (57.6%) and 4/33 (12.1%) (Arm A), and 28/33 (84.8%) and 12/33 (36.4%) (Arm B) patients, respectively; Grade ≥3 febrile neutropenia was experienced by 6/33 (18.2%) patients in each arm. Grade ≥3 infusion-related reactions to both rituximab and tafasitamab occurred in no patients in Arm A and one patient (3.0%) in Arm B, and 7/33 (21.2%) (Arm A) and 9/33 (27.3%) (Arm B) patients had a Grade ≥3 infection and/or infestation (Figure 1). Serious TEAEs occurred in 14/33 (42.4%) patients in Arm A and 17/33 (51.5%) patients in Arm B. Two out of 33 (6.1%) and one out of 33 (3.0%) patients discontinued study treatment due to TEAEs in Arms A and B, respectively. There were four deaths unrelated to tafasitamab and/or LEN (COVID-19 pneumonia, sepsis, and urosepsis). The average relative dose intensity of R-CHOP in each cycle was maintained in both arms. ORR at EOT was observed in 25/33 patients (75.8%; 95% confidence interval [CI]: 57.7-88.9) in Arm A and 27/33 patients (81.8%; 95% CI: 64.5-93.0) in Arm B. Conclusion These data suggest that both regimens are tolerable and do not impair dosing and scheduling of R-CHOP. Toxicities were similar to those expected with R-CHOP with or without LEN. With tumor follow-up still ongoing, the ORR at EOT suggests that patients with treatment-naïve DLBCL may achieve clinically meaningful efficacy tafasitamab and LEN in addition to standard treatment. A Phase III, multicenter, randomized, double-blind, placebo-controlled trial will assess efficacy and safety of R-CHOP + tafasitamab + LEN vs R-CHOP in newly diagnosed patients with high intermediate and high risk DLBCL, and is currently recruiting (frontMIND study; NCT04824092). Funding: MorphoSys AG. Figure 1 Figure 1. Disclosures Belada: Roche: Consultancy, Other: Travel, Accommodations, Expenses, Research Funding; Gilead Sciences: Consultancy, Other: Travel, Accommodations, Expenses, Research Funding; Janssen-Cilag: Consultancy, Research Funding; Takeda: Consultancy, Other: Travel, Accommodations, Expenses, Research Funding; MorphoSys AG: Consultancy, Research Funding; Debiopharm Group: Consultancy; Pharmacyclics: Research Funding; Archigen Biotech: Research Funding; Reddys: Research Funding. André: Johnson & Johnson: Research Funding; Roche: Other: Travel/accomodation/expenses, Research Funding; Incyte: Consultancy; Gilead: Consultancy, Other: Travel/Accommodations/Expenses; Karyopharm: Consultancy; Bristol-Myers-Squibb: Consultancy, Other: Travel/Accommodations/Expenses; Takeda: Consultancy, Research Funding; Celgene: Other: Travel/accomodation/expenses; AbbVie: Other: Travel/accomodation/expenses. Pérez Persona: Amgen: Consultancy, Other: Support for attending meetings and/or travel, Speakers Bureau; BMS/Celgene: Consultancy, Other: Support for attending meetings and/or travel, Speakers Bureau; AbbVie: Other: Support for attending meetings and/or travel, Speakers Bureau; Takeda: Speakers Bureau; Sanofi: Consultancy, Speakers Bureau; AstraZeneca: Speakers Bureau; GSK: Consultancy; Incyte: Consultancy. Staber: Roche: Consultancy, Honoraria, Research Funding; AbbVie: Consultancy, Honoraria; Gilead: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Astra Zeneca: Consultancy, Honoraria; Takeda: Consultancy, Research Funding; MSD: Consultancy, Honoraria; BMS: Consultancy, Honoraria; Incyte: Consultancy, Honoraria, Research Funding; Beigene: Consultancy, Honoraria. Trneny: AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Accommodations, Expenses; Amgen: Consultancy, Honoraria; Bristol-Myers Squibb: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Accommodations, Expenses; Gilead Sciences: Consultancy, Honoraria, Other: Travel, Accommodations, Expenses; Incyte: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Accommodations, Expenses; MorphoSys: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Roche: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Accommodations, Expenses; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Accommodations, Expenses; Celgene: Consultancy; 1st Faculty of Medicine, Charles University, General Hospital in Prague: Current Employment; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Portola: Honoraria, Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Honoraria. Brackertz: MorphoSys AG: Current Employment. Shah: MorphoSys AG: Current Employment. Sporchia: MorphoSys AG: Current Employment. Burke: MorphoSys: Consultancy; Adaptive Biotechnologies: Consultancy; Verastem: Consultancy; AstraZeneca: Consultancy; Bristol Myers Squibb: Consultancy; Kymera: Consultancy; X4 Pharmaceuticals: Consultancy; AbbVie: Consultancy; SeaGen: Consultancy, Speakers Bureau; Kura: Consultancy; Roche/Genentech: Consultancy; Epizyme: Consultancy; Beigene: Consultancy, Speakers Bureau. Nowakowski: Celgene, NanoString Technologies, MorphoSys: Research Funding; Celgene, MorphoSys, Genentech, Selvita, Debiopharm Group, Kite/Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees. OffLabel Disclosure: Tafasitamab is a humanized Fc-modified cytolytic CD19 targeting monoclonal antibody. In combination with lenalidomide (LEN), it received accelerated approval in July 2020 for adult patients with relapsed/refractory (R/R) diffuse large B-cell lymphoma (DLBCL) not otherwise specified (NOS), including arising from lowâ€'grade lymphoma, who are ineligible for autologous stem cell transplant (ASCT). Following FDA approval, we are now evaluating the safety and efficacy of tafasitamab in combination with LEN as an add-on to first-line therapy with R-CHOP in newly diagnosed patients with DLBCL.