Rezvani, Andrew R.

Abstract Allogeneic hematopoietic cell transplantation (allo-HCT) is a potentially curative treatment for many hematological malignancies, but graft-versus-host disease (GVHD) is a common complication. Low gut microbiome diversity is associated with higher GVHD risk and shorter survival in multiple studies. Recently, the BMT CTN 1703 clinical trial demonstrated superiority of a GVHD-prophylaxis regimen including post-transplant cyclophosphamide (PTCy) compared to the standard prophylaxis (tacrolimus and methotrexate, Tac/MTX) in terms of GVHD-free, relapse-free survival at one year among reduced intensity conditioning allo-HCT recipients. However, the effect of PTCy on the gut microbiome and its association with clinical outcome have not been described. Here, we report on a companion randomized clinical controlled trial (BMT CTN 1801), which collected 2575 longitudinal stool samples from 304 study participants. Samples were obtained up to weekly up to day 84 post allo-HCT and at less frequent intervals thereafter, up to 2 years. Microbiome diversity and absolute microbial load were lower in the PTCy group compared to the Tac/MTX group on days 14–28 post-HCT. However, diversity at the timepoint closest to neutrophil engraftment was not significantly associated with non-relapse mortality after one year or other clinical outcomes, contrary to expectations from previous studies. Microbial domination events, when a single species exceeds 30% relative abundance, were comparable across treatment arms and reflected both pathogen blooms as well as less severe disruptions of the microbial community. Clostridium scindens and secondary bile acid metabolism pathways were less prevalent in the PTCy arm than in the Tac/MTX arm post-HCT, yet presence of secondary bile acid metabolism pathways was associated with a lower risk of chronic GVHD. Given that PTCy was associated with a greater disruption of the microbiome as measured by diversity, absolute microbial abundance, and bile acid metabolism capability, but better clinical outcomes overall, these data suggest that the importance of the microbiome in modulating the host immune systems after allo-HCT is specific to different types of GVHD prophylaxis.

Abstract Background: A randomized multicenter trial (BMT CTN 1703) demonstrated that after reduced intensity conditioning HCT, PT-Cy-based GVHD prophylaxis led to significant reductions in acute and chronic GVHD, but was associated with significantly more Grade 2 (moderate) infections and similar overall survival vs Tac/MTX. A linked mechanistic study (BMT CTN 1801) found that PT-Cy led to pan-T cell depletion and reduced T cell receptor (TCR) repertoire diversity vs Tac/MTX. To discover the molecular mechanisms driving the association of PT-Cy with increased infections, we examined pathogen-specific T cell reconstitution in BMT CTN 1801 patients (n=165 PT-Cy, n=159 Tac/MTX). Methods: We performed deep TCR sequencing on 2,369 blood samples collected pre-HCT (recipient baseline) and on Days +7, 14, 28, 63, 100, 180, 270, 365, 730, and from the graft infusion product. We then applied a novel set of TCR classifiers (Adaptive Biotechnologies) capable of identifying pathogen-specific clones associated with CMV, EBV, SARS-CoV-2, HSV-1, HSV-2, parvovirus, RSV, influenza A, rhinovirus, adenovirus, HHV-6B, norovirus and Toxoplasma. Single-cell (sc) TCR/RNA-sequencing on a sample subset (n=26) was performed to determine the phenotype of pathogen-specific T cells. Results. By linking scRNA-seq with pathogen-specific TCR barcoding, we identified CD4 and CD8 memory T cells as their predominant T cell reservoir. We found that the total number of pathogen-specific singleton TCRs was significantly lower with PT-Cy, starting early post-HCT and persisting through 2 years. For example, at Day +14, PT-Cy patients had 7.8-fold fewer pathogen-specific singleton TCRs vs Tac/MTX (mean of 6.9 vs 54.1, p<0.001). Consistent differences between PT-Cy and Tac/MTX were observed for TCRs specific for each pathogen individually. Patients who developed Grade 3 (severe) viral infections had significantly fewer pathogen-specific singleton TCRs at Day +14 compared to those who had no viral infections (mean of 4.0 vs 32.5, p=0.03). Leveraging intrinsic TCR barcoding of the HCT infusion (“graft”) and of the patient's baseline samples (“recipient”), we could assign the graft/recipient origin of the pathogen-specific cells with high fidelity. This analysis revealed pronounced differences in the origin of pathogen-specific T cells with PT-Cy vs Tac/MTX, especially prior to Day +100. The absolute number of pathogen-specific TCRs originating from the graft was significantly higher with Tac/MTX vs PT-Cy. This difference was observed from day +7 through 6 months post-HCT, with up to 7.1-fold more graft-derived pathogen-specific TCRs in Tac/MTX vs PT-Cy (p<0.001 at each timepoint before day +100). Within patients who received Tac/MTX, the balance of graft vs recipient pathogen-specific clones significantly favored graft clones (for example, a mean of 14.9 graft vs 8.6 recipient pathogen-specific TCRs at Day+14, p=0.02). By contrast, with PT-Cy, in addition to having substantially fewer pathogen-specific TCRs overall, the proportion of these TCRs was not significantly different between graft and recipient clones (mean of 2.1 graft vs 3.3 recipient pathogen-specific TCRs at Day+14, p=0.42). These data uncover that, in addition to the reduction in pathogen-specific T cells with PT-Cy, there was a relative skewing of the anti-microbial T cell reservoir towards recipient cells that persisted after conditioning. Conclusions: PT-Cy led to in vivo T cell depletion across all T cell subsets, which prominently included clones tracked from the allograft itself into the HCT recipient, with a relative sparing of recipient T cell clones that survived transplant conditioning. While the mechanism for relative sparing of recipient cells has not yet been determined, these conditioning-exposed cells may be less proliferative than newly infused graft T cells. The depletion of graft T cells included CD4 and CD8 memory cells specific for infections, which may have contributed to relative deficits in protective immunity against infection in patients receiving PT-Cy. Importantly, these data suggest that with PT-Cy, persisting recipient TCRs may play a key role in preserving anti-infectious immunity. Taken together, these results provide a mechanistic basis for key post-transplant clinical outcomes of the landmark BMT CTN 1703 study. They also underscore the importance of recipient immune status with PT-Cy, creating the opportunity for targeted infection risk assessment in these patients.

Abstract Introduction: Graft Failure (GF) is a rare but devastating outcome of HCT. Primary GF (PGF), defined as a failure of neutrophil recovery by Day+28, is straightforward to diagnose. Diagnosing secondary GF (SGF) is more challenging, with its broad time-range, multiple confounding diagnoses, and lack of predictive biomarkers. In BMT CTN1703/1801, we analyzed patients receiving RIC HCT for heme malignancies with either Tac/MTX (n=159) or PT-Cy (n=165) GVHD prophylaxis. SGF was defined as donor chimerism <5% after initial donor engraftment. With Tac/MTX, there were 3 PGF and 1 SGF diagnoses. With PT-Cy, there were 4 PGF and 6 SGF. Median SGF diagnosis was Day +64 (range: Day+28-215). There were too few Tac/MTX patients to analyze SGF, but sufficient events with PT-Cy. To identify PT-Cy SGF predictors, we leveraged lymphocyte, T, B, and NK cell reconstitution analysis. In SGF we found an early, profound deficit in the reconstitution of all major lymphocyte populations, including total lymphocytes, T, B, and NK cells, as early as Day+28. This enabled the modeling of a SGF risk classifier based on the Absolute Lymphocyte Count (ALC). Methods: Clinical ALC measurements were performed on all SGF patients (n=6) and on non-GF controls with ALCs available (146 of 155 non-GF patients). Flow cytometry was performed on all PT-Cy SGF patients (n = 6) and from a subset of non-GF controls (n = 18: controls were chosen as patients without relapse or severe GVHD, to reduce confounders introduced by immunologic interventions, and for whom all samples, including from the graft infusion, were available). T, B, and NK counts, as well as T cell subsets, were compared (using Welch's T test) on Days 7, 14, 21, 28, 42, 63, 98, 180, 270, 365, 730, with SGF patients censored on the day of GF diagnosis. To interrogate the optimal ALC cutoff, the cumulative incidence of SGF was computed at Days +28 and +42, with death without GF as a competing risk. Results: We have previously demonstrated that, compared to Tac/MTX, PT-Cy patients exhibited an early decrease in reconstitution of all T cell populations (with normal NK and B cell reconstitution). Here we focused specifically on PT-Cy patients with or without SGF. Graft CD34 counts/kg were not different between SGF patients and non-GF patients (mean CD34/kg = 1.38 x10e6 (SGF) vs 0.67 x10e6 (non-GF, p = 0.61) However, even amidst the overarching early suppression in T cell reconstitution with PT-Cy, SGF patients could be easily distinguished from the larger PT-Cy cohort, based on more profound deficits in ALC, T, B and NK cells reconstitution, measured using 2 strategies: (1) SGF patients demonstrated significant early (Day +28) quantitative defects in the reconstitution of the ALC (mean +/- SEM 262+/-32 cells/µL (non-GF) vs 60 +/- 25 (SGF, p<0.0001), CD4 T cells (62 +/- 12 cells/µL vs 19+/-15, p=0.048), CD8 T cells (15 +/-3 cells/µL vs 3.5 +/-1 p=0.0009), all CD8 T cell subpopulations, as well as NK cells (116+/-31 cells/µL vs 2.9+/-1.4 cells/µL, p= 0.002) and B cells (3.5 +/-1.4 cells/µL vs 0.16+/-0.07 p =0.03). (2) In SGF, there was a significant deficit in the rate of rise of all major lymphocyte populations between Days 28-42-60 vs non-GF, including CD4 T cells (p<0.0001), CD8 T cells (p = 0.0002), B cells (p<0.0001), and NK cells (p =0.048). These discoveries suggested that a classifier could be identified to risk-stratify patients for SGF. We explored an ALC cutpoint, amenable to standard clinical lab analysis. A statistically significant threshold was identified at both Days+28 and +42, with Day+42 being most predictive: A threshold of 120 cells/µL was identified as optimal, with landmark analysis documenting a SGF rate of 34.7% below the cutpoint, and SGF of 1% above it (HR = 45.9, 95% CI 5.7 - 366). Conclusions: Despite the small number of events, PT-Cy patients with SGF demonstrated a distinctive reconstitution trajectory that encompassed an early, substantial, and sustained deficit in all lymphocyte counts, as well as a lack of their longitudinal expansion. This enabled the discovery of a candidate ALC biomarker cutpoint at Day+42 that could distinguish patients who were more likely to develop SGF. If confirmed, these data could generate a predictive biomarker for SGF, which would enable the design of trials evaluating early interventions (e.g. CD34+ boosts, DLI, modification of immunosuppression) to improve outcomes for these patients.

Background: BMT CTN 1703 was a Phase 3 trial comparing Tac/MTX (n = 217) to post-transplant cyclophosphamide (PT-Cy)/Tac/MMF (n = 214) GVHD prophylaxis after reduced intensity conditioning unrelated donor hematopoietic cell transplant (HCT). PT-Cy significantly improved GVHD-free Relapse-Free Survival (Bolanos-Meade et al NEJM 2023). However overall survival was not significantly different and the # of Grade 2 infections was higher with PT-Cy. To investigate its biologic underpinnings 1703 was linked to a mechanistic study, BMT CTN 1801, which co-enrolled 324 pts (159 CNI/MTX 165 PT-Cy). The resulting dataset enabled an analysis of post-HCT T cell reconstitution at an unprecedented level of detail. Methods: Samples were collected from the HCT infusion and on D+7, 14, 28, 63, 98, 180, 270, 1- and 2-yr. We extracted DNA (2,225 samples) and performed Adaptive Biotech β-strand T Cell Receptor (TCR) Immunosequencing (TCR-Seq). We profiled 44,077 (median) TCRs/sample resulting in 215,155,719 T cells analyzed. We evaluated multiple TCR diversity measures longitudinally and before/after cGVHD and infections. Each measure evaluates a specific aspect of TCR diversity, including Simpsons Clonality (focuses on the most expanded clones) Diversity Slope (mid-range clones) Richness (both mid-range and less-expanded clones) and Singletons (the TCR-Seq equivalent of naïve T cells). This analysis was robust to the full range (1000-50,000) of down-sampled TCRs sequenced. Results: We identified major differences in TCR reconstitution in Tac/MTX vs PT-Cy that begin early and persist through 2 yr post-HCT. These resulted in a significantly less diverse TCR repertoire with PT-Cy with substantial implications for its efficacy and toxicity. The most salient differences are: (1) PT-Cy caused significant in-vivo T cell depletion early post-HCT (% T cells/total WBC at D+28: 8.2% (Tac/MTX) vs 2.2% (PT-Cy) p=2.2x10 -23). (2) The remaining donor T cells in PT-Cy undergo substantial clonal expansion ( Fig 1) resulting in significantly constrained TCR diversity measured by Clonality, Slope, Richness, Singletons (not shown) and Singletons/Richness ( Fig 2) which began early (D+14) and persisted for 2 yr. (3) Linked T cell depletion and clonal expansion resulted in a TCR diversity bottleneck after PT-Cy ( Fig 1). Due to the bottleneck, while the fraction of T cells originating from the transplant infusion at =/> 1 yr was similar between arms (18% vs 24%, p=0.7) there were significantly fewer Singleton TCRs in PT-Cy, suggesting a reduction in naïve T cells ( Fig 2), an outcome that has critical consequences for both cGVHD and infection. Thus while cGVHD onset with Tac/MTX was linked to a significant drop in TCR diversity due to singleton clonal expansion (median log-2 fold change in singletons with Tac/MTX = -0.25 p = 0.01) this drop was not observed with PT-Cy (log-2 fold change = -0.05, p = 0.1). Along with the significantly decreased # singletons at all time-points in PT-Cy ( Fig 2) this suggests that while cGVHD after Tac/MTX is linked to substantial naïve T cell expansion, the same is not true with PT-Cy, identifying a novel mechanism for cGVHD control with PT-Cy. The substantially fewer singletons in PT-Cy vs Tac/MTX may also increase the risk of Grade 2+ infections. T cell responses to new infections rely on antigen recognition/effector maturation of naïve (singleton TCR) T cells. After infection, the TCR repertoire became less diverse for both Tac/MTX and PT-Cy (log-2-fold singleton change -0.17 and -1.2 p = 0.0006 and 0.01) indicating that singletons in both cohorts were capable of expanding to pathogens. However the markedly decreased # singletons in PT-Cy at all timepoints was associated with significantly fewer singletons prior to infection (mean 3979 at 5K read-depth for Tac/MTX vs 2820 for PT-Cy p<0.001). This singleton deficit would place PT-Cy patients at higher risk of missing the critical mass of TCRs required to respond effectively to infections, consistent with their increased rate of Gr 2 infections. Conclusions: We performed longitudinal TCR-Seq on >200 million T cells from 324 HCT patients, representing the largest post-HCT TCR-Seq analysis in the history of the field, and enabling novel insights into TCR dynamics. These data identify a previously unappreciated global TCR diversity bottleneck with PT-Cy that simultaneously protects patients from cGVHD and places them at higher risk of infectious complications.

SummaryThere have been no large studies comparing reduced‐intensity/non‐myeloablative conditioning (RIC/NMA) to myeloablative conditioning (MAC) regimens in T‐cell non‐Hodgkin lymphoma (T‐NHL) patients undergoing allogeneic transplant (allo‐HCT). A total of 803 adults with peripheral T‐cell lymphoma, anaplastic large cell lymphoma and angioimmunoblastic T‐cell lymphoma (age 18–65 years), undergoing allo‐HCT between 2008–2019 and reported to the Center for International Blood and Marrow Transplant Research with either MAC (n = 258) or RIC/NMA regimens (n = 545) were evaluated. There were no significant differences between the two cohorts in terms of patient sex, race and performance scores. Significantly more patients in the RIC/NMA cohort had peripheral blood grafts, haematopoietic cell transplantation‐specific comorbidity index (HCT‐CI) of ≥3 and chemosensitive disease compared to the MAC cohort. On multivariate analysis, overall survival (OS) was not significantly different in the RIC/NMA cohort compared to the MAC cohort (hazard ratio (HR) = 1.01, 95% confidence interval (CI) = 0.79–1.29; p = 0.95). Similarly, non‐relapse mortality (NRM) (HR = 0.85, 95% CI = 0.61–1.19; p = 0.34), risk of progression/relapse (HR = 1.29; 95% CI = 0.98–1.70; p = 0.07) and therapy failure (HR = 1.14; 95% CI = 0.92–1.41, p = 0.23) were not significantly different between the two cohorts. Relative to MAC, RIC/NMA was associated with a significantly lower risk of grade 3–4 acute graft‐versus‐host disease (HR = 0.67; 95% CI = 0.46–0.99, p = 0.04). Among chemorefractory patients, there was no difference in OS, therapy failure, relapse, or NRM between RIC/NMA and MAC regimens. In conclusion, we found no association between conditioning intensity and outcomes after allo‐HCT for T‐cell NHL.

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: MGTA-145, a CXCR2 agonist, has shown promising activity for hematopoietic stem cell (HSC) mobilization with plerixafor in pre-clinical models and healthy volunteers. It has the potential to become the first GCSF free regimen for HSC mobilization/apheresis in preparation for transplant, with fewer side effects, better patient experience and optimal resource utilization. Methods: We conducted a single center phase 2 trial of MGTA-145 + plerixafor for HSC mobilization in patients with multiple myeloma (MM), NCT04552743. Primary endpoint was collection of ≥2 x 10 6 CD34+ cells/kg in up to 2 days of mobilization/apheresis. Secondary endpoints were collection of 4 and 6 x 10 6 CD34+ cells/kg, safety and engraftment. Patients with MM, 18-70 years of age, within 1 year of starting treatment & CrCl > 30 ml/min were eligible. Patients received plerixafor 0.24 mg/kg (0.16 mg/kg if renal dysfunction) SQ, followed 2 hours later by MGTA-145 (0.03 mg/kg) IV over 3-10 minutes and apheresis within 30 minutes. Mobilization and collection were repeated for a second consecutive day if day 1 yield was < 6 x 10 6 CD34+ cells/kg. The study was open-label single arm trial of 15 patients. If 13 or more patients met primary endpoint, an expansion cohort of 10 patients was planned. The trial has 85% power at a 5% one-sided type I error rate. Our analysis is based on aggregated results from total cohort of 25 patients. Results: Median age was 62 years, 52% were female, 24% had ISS stage 3, 57% had high-risk FISH (primarily gain1q). Induction therapy was VRD in 68% (17), daratumumab VRD in 24% (6), CyBorD in 8% (2) patients. Median duration of induction was 4 months (3-6) and median lenalidomide exposure was 5 cycles (1-8), with > VGPR in 88% of patients. (Table 1) Plerixafor 0.24 mg/kg was given in 24 (96%) patients. Median pre-apheresis CD34 count was day 1, 24/uL (3-99) & day 2, 15/uL (5-46). Median total HSC cell yield (CD34+ cells/kg x 10 6) was 5.0 (1.1-16.2), day 1 yield was 3.4 (0.3-16.2) and day 2 yield was 1.9 (0.5-4.6) (Fig1). 88% (n=22) of patients met the primary endpoint of collecting sufficient HSCs in < 2 days of mobilization + apheresis to proceed to transplant, 68% (17) in 1 day (2 x 10 6 CD34+ cells/kg). 3 patients who did not meet primary endpoint successfully collected HSCs with standard GCSF + plerixafor dosing & 2-3 apheresis sessions. Secondary endpoints of 4 and 6 x 10 6 CD34+ cells/kg in < 2 days were met in 68% (17) and 40% (10) patients. MGTA-145+plerixafor was well tolerated. At least 1 treatment emergent AE (TEAE) with MGTA-145 was seen in 60% of patients (grade 1, n= 14, grade 2, n=1). Pain (all grade 1) was most common, seen in 44% (11), with 38% (9) patients experiencing acute onset transient bone pain with MGTA-145 (duration: 7 minutes, range: 3-28). Using the validated Brief Pain Inventory, 56% (14) patients self-reported pain with mobilization vs 40% (10) at baseline. 7/15 patients without baseline pain reported pain with mobilization. An increase for worst pain was seen on mobilization day 1, that returned to the baseline, but no difference for aggregate score of pain severity/interference (linear mixed effects model). At last follow-up, 18 patients have completed transplant with MGTA-145 mobilized graft, with melphalan 200 mg/m 2 in 15 (83%) patients. Median of 3.5 (2.2-8.1) x 10 6 CD34+ cells/kg were infused. All patients have engrafted. Median time to neutrophil engraftment of 12 days (range: 11-15) & platelet engraftment (platelets > 20,000, no transfusion in 7 days) of 17.5 days (15-33) are comparable to historical data (DiPersio et al. 2009). RBC transfusion was needed in 3 (17%) patients. 14 patients have day 100 follow-up, all with durable engraftment. MGTA-145 + plerixafor mobilized grafts had a favorable graft composition. We observed high enrichment for CD90+CD45RA- among CD34+ cells, a CD34 subset of long term engrafting HSCs (median: 36% of CD34+ cells, range 10-66%, N=25). 74% (17 of 23) grafts were minimal residual disease negative with next generation flow cytometry. Conclusions: This is the first study to evaluate the novel G-CSF-free regimen of MGTA-145 + plerixafor for HSC cell mobilization & collection for hematologic malignancies. The study cohort was representative of transplant eligible patients with MM, with 88% patients meeting the primary endpoint. The regimen was well tolerated. Patients achieved timely & durable engraftment. Our data support further development of this regimen for rapid HSC mobilization. Figure 1 Figure 1. Disclosures Sidana: Janssen: Consultancy, Research Funding; Allogene: Research Funding; Magenta Therapeutics: Consultancy, Research Funding; BMS: Consultancy. Kumar: Bluebird Bio: Consultancy; Adaptive: 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; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Research Funding; Oncopeptides: Consultancy; KITE: Consultancy, 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; Beigene: Consultancy; Antengene: Consultancy, Honoraria; Amgen: Consultancy, Research Funding; Roche-Genentech: Consultancy, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding; BMS: Consultancy, Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding. Muffly: Pfizer, Amgen, Jazz, Medexus, Pfizer: Consultancy; Astellas, Jasper, Adaptive, Baxalta: Research Funding; Adaptive: Honoraria, Other: fees for non-CME/CE services: , Research Funding. Arai: Magenta Therapeutics: Research Funding. Meyer: Indee, Jura: Consultancy; Orca Biosystems: Research Funding; GigaImmune: Current holder of stock options in a privately-held company; Triursus Therapeutics: Current holder of stock options in a privately-held company. Rezvani: US Department of Justice: Consultancy; Kaleido: Other: One-time scientific advisory board; Nohla Therapeutics: Other: One-time scientific advisory board; Pharmacyclics-Abbvie: Research Funding. Weng: Kite Pharma: Research Funding. Frank: Kite-Gilead: Membership on an entity's Board of Directors or advisory committees; Allogene Therapeutics: Research Funding; Adaptive Biotechnologies: Research Funding. Shiraz: Kite Pharma-Gilead: Research Funding. Girgenti: Magenta Therapeutics: Current Employment. Goncalves: Magenta Therapeutics: Current Employment, Current equity holder in publicly-traded company, Patents & Royalties. Schmelmer: Magenta Therapeutics: Current Employment, Current equity holder in publicly-traded company, Patents & Royalties. Davis: Magenta Therapeutics: Current equity holder in publicly-traded company, Ended employment in the past 24 months. Shizuru: Jasper Therapeutics, Inc.: Current holder of stock options in a privately-held company, Membership on an entity's Board of Directors or advisory committees, Other: Chair of scientific advisory board; Forty seven Inc: Other: Inventor on a patent licenses by Forty Seven. Forty seven was acquired by Gilead in 2020. 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.

Abstract BACKGROUND: Our group recently reported on the results of Blood and Marrow Transplant (BMT) Clinical Trials Network (CTN) 1101 a randomized comparison between double umbilical cord blood (dUCB) and haploidentical bone marrow (haplo) with post-transplant cyclophosphamide (ptCy) in the nonmyeloablative setting that showed similar progression free survival (PFS) between the two treatment groups, but lower non-relapse mortality (NRM) and better of overall survival (OS) in the haplo arm. In this secondary analysis we sought to investigate if transplant center experience with haplo and or cord blood HCT had an impact on outcomes. PATIENTS AND METHODS: All patient randomized in BMT CTN 1101 were included. In order to determine the transplant center experience with either haplo or dUCB we queried the Center for International Blood and Marrow Transplant Research (CIBMTR) for number of transplants with each platform in the year prior to initiation of the study. Centers were then grouped as dUCB center (> 10 dUCB, n=117, 10 centers), Haplo center (>10 haplo and ≤10 dUCB, n=110, 2 centers), and ≤10 haplo and ≤10 dUCB HCTs (other center, n=140, 21 centers). Further analysis considered the alternative cut-off for haplo (> 5 vs ≤ 5) experience, and considered the outcomes based on the donor experience vs. others (e.g. dUCB > 10 vs. ≤ 10; haplo > 5 vs. ≤ 5). RESULTS: The effect of center experience on HCT outcomes shown in Figure, below . After adjusting for age, Karnofsky performance score and, disease risk index we found that there was no difference in outcomes between haplo and dUCB for centers that were experienced with dUCB or had limited to no experience with either dUCB or haplo. In contrast, in centers that were primarily experienced with haplo had better outcomes with this donor type, as compared to dUCB. The higher risk of treatment failure (relapse or death) and overall mortality in dUCB in haplo experienced centers was driven by significantly higher risk of relapse. We then considered the transplant experience with each of the donor types separately. In transplant centers that had performed > 10 dUCB, there were similar outcomes for recipients of both dUCB and haplo. Similarly, centers that had ≤ 5 haplo HCTs had no difference in outcomes between donor types suggesting an overlap with centers that had performed > 10 dUCB HCTs. Overall mortality was higher among dUCB recipients in centers that had performed ≤ 10 dUCB. Notably, the hazard ratio of non-relapse mortality favored haplo in all four donor experience type of transplant center, albeit not statistically significant. CONCLUSION: Except for dUCB recipients in centers with < 10 dUCB/year had worse overall mortality, primarily driven by relapse, the transplant center experience in the year prior to the initiation of BMT CTN 1101 had limited impact on the outcomes of this randomized clinical trial. Figure 1 Figure 1. Disclosures Brunstein: NANT: Research Funding; FATE: Research Funding; GamidaCell: Research Funding; BlueRock: Research Funding; AlloVir: Consultancy. Costa: Amgen: Consultancy, Honoraria, Research Funding, Speakers Bureau; Janssen: Consultancy, Honoraria, Research Funding; Sanofi: Consultancy, Honoraria, Speakers Bureau; Pfizer: Consultancy, Honoraria; BMS: Consultancy, Honoraria, Research Funding; Karyopharm: Consultancy, Honoraria. Cutler: Deciphera: Consultancy; Cimeio: Consultancy; Editas: Consultancy; Kadmon: Consultancy; Pfizer: Consultancy; Mallinckrodt: Consultancy; CareDx: Consultancy; Incyte: Consultancy; Omeros: Consultancy; Syndax: Consultancy; Mesoblast: Consultancy; Jazz: Consultancy. Horowitz: Sobi: Research Funding; Regeneron: Research Funding; Orca Biosystems: Research Funding; Tscan: Research Funding; Xenikos: Research Funding; Miltenyi Biotech: Research Funding; Stemcyte: Research Funding; Medac: Research Funding; Vor Biopharma: Research Funding; Kite/Gilead: Research Funding; Janssen: Research Funding; Pharmacyclics: Research Funding; Kiadis: Research Funding; Seattle Genetics: Research Funding; Mesoblast: Research Funding; GlaxoSmithKline: Research Funding; Sanofi: Research Funding; Pfizer, Inc: Research Funding; Omeros: Research Funding; Magenta: Consultancy, Research Funding; Jazz Pharmaceuticals: Research Funding; Vertex: Research Funding; Genentech: Research Funding; Takeda: Research Funding; Novartis: Research Funding; Shire: Research Funding; Gamida Cell: Research Funding; Daiicho Sankyo: Research Funding; CSL Behring: 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. Horwitz: Gamida Cell: Research Funding. McGuirk: Novartis: Research Funding; Magenta Therapeutics: Consultancy, Honoraria, Research Funding; EcoR1 Capital: Consultancy; Pluristem Therapeutics: Research Funding; Novartis: Research Funding; Bellicum Pharmaceuticals: Research Funding; Astelllas Pharma: Research Funding; Gamida Cell: Research Funding; Fresenius Biotech: Research Funding; Allovir: Consultancy, Honoraria, Research Funding; Juno Therapeutics: Consultancy, Honoraria, Research Funding; Kite/ Gilead: Consultancy, Honoraria, Other: travel accommodations, expense, Kite a Gilead company, Research Funding, Speakers Bureau. Rezvani: US Department of Justice: Consultancy; Kaleido: Other: One-time scientific advisory board; Nohla Therapeutics: Other: One-time scientific advisory board; Pharmacyclics-Abbvie: Research Funding. Rybka: Spark Therapeutics: Consultancy; Merck: Consultancy. Vasu: Kiadis, Inc.: Research Funding; Boehringer Ingelheim: Other: Travel support; Seattle Genetics: Other: travel support; Omeros, Inc.: Membership on an entity's Board of Directors or advisory committees.

8023 Background: MGTA-145 (GroβT), a CXCR2 agonist, has shown promising activity for HSC mobilization with plerixafor in pre-clinical models and healthy volunteers. Methods: This phase 2 single center study evaluates HSC mobilization with MGTA-145 + plerixafor and same day apheresis in patients with multiple myeloma. Patients received plerixafor 0.24 mg/kg (0.16 mg/kg if renal dysfunction) SQ, followed 2 hours later by MGTA-145 (0.03 mg/kg) IV over 3-10 minutes and apheresis within 30 minutes. Mobilization was repeated for a second day if day 1 yield was < 6 x 106 CD34+ cells/kg. This interim analysis reports on mobilization in 10 patients (of 25 planned), including safety cohort of first 6 patients completing transplant. Primary endpoint is collection of 2 x 106 CD34+ cells/kg. Results: Median age was 63 years (range: 46-68), 50% were female, 22% had ISS stage 3 & 50% had high-risk FISH. Induction therapy was VRD in 7 and daratumumab + VRD in 3 patients; median induction duration: 4 months (3-6) & median lenalidomide exposure: 6 cycles (4-6), with > VGPR in 70%. Median total stem cell yield (CD34+ cells/kg x 106) was 7.1 (3-16.2), day 1 yield was 5.4 (1.1-16.2) & yield per apheresis session was 4 (1.1-16.2). 100% of patients met the primary endpoint of collecting sufficient HSCs in < 2 days of mobilization + apheresis to proceed to transplant (2 x 106 CD34+ cells/kg). Secondary endpoints of 4 and 6 x 106 CD34+ cells/kg in < 2 days were met in 90% & 80% patients. 30% patients underwent 1 apheresis, while 70% underwent 2 sessions. MGTA-145 was well tolerated. At least 1 adverse event (AE) was seen in 90% of patients, 20% had grade 2 AEs (anemia, hypokalemia) and 20% had grade 3 AEs (worsening of baseline grade 3 anemia; hypocalcemia); all resolved. Acute & transient bone pain was seen in 40% of patients (back-2, hip-1, sternum-1), all grade 1, all on day 1, & resolved without intervention after 6 minutes (3-10). All 6 patients in the safety cohort have completed transplant with melphalan 200 mg/m2. Median of 4.1 (3.4-5.6) x 106 CD34+ cells/kg were infused. All patients have engrafted timely (DiPersio Blood 2009); median time to neutrophil engraftment: 12 days (11-13) & platelet engraftment: 17 days (16-19). Apheresis graft analysis is available in these 6 patients. Grafts with MGTA-145+plerixafor showed high enrichment for CD90+CD45RA- among CD34+ cells, a CD34 subset of long term engrafting HSCs (median: 31% of CD34+ cells, 27-52), higher than seen with G-CSF (6%, Goncalves TCT 2021). 67% of grafts were minimal residual disease negative with next generation flow cytometry. Conclusions: This is the first study to evaluate the novel regimen of MGTA-145 + plerixafor for same day stem cell mobilization & collection in myeloma/hematologic malignancies, with 100% efficacy in interim analysis and the first to demonstrate successful engraftment in patients with cells collected with this GCSF free regimen. Clinical trial information: NCT04552743.