Abstract: Introduction: We have previously reported that clinically relevant, dramatic reductions occur in intestinal bacterial diversity during allogeneic hematopoietic stem cell transplant (allo-HSCT). These are likely attributable to antibiotic exposure, nutritional alterations, and intestinal mucosa injury from high-dose chemotherapy. Patients undergoing autologous hematopoietic stem cell transplantation (AHCT) also receive antibiotics and experience nutritional alterations due to mucositis and other gastrointestinal toxicities. We hypothesized that the pattern of dysbiosis seen in AHCT patients would reflect the changes in allo-HSCT patients. Here, we present a novel analysis of microbiota diversity in AHCT patients from two independent institutions. Methods: We retrospectively identified a cohort of 365 patients (median age 60 years) who underwent AHCT for treatment of hematologic malignancy between May 2009 to February 2018 at two large-volume transplant centers in the US. The population was diverse in terms of histology, conditioning regimens and remission status prior to transplant, with 179 (49%) patients diagnosed with multiple myeloma, 153 (42%) patients diagnosed with lymphoma, and 33 (9%) patients with other diseases. Stool samples from the selected patients were collected approximately weekly during inpatient hospitalization. Sequencing of the V4-V5 region of the bacterial 16S rRNA genes from all samples was performed on the Illumina platform at a central site. Microbial diversity was measured by the Simpson reciprocal a-diversity index (S). We defined the pre-AHCT period as days -10 to 0, and computed median values for patients with multiple samples within that period. We additionally defined monodomination of the microbiota as a single operational taxonomic unit comprising 〉 30% of bacterial abundance. For comparison, we sequenced samples from 17 healthy volunteers and used a public dataset of sequences from 313 healthy volunteers from the NIH Human Microbiome Project (HMP). Median pre-transplant microbial diversity in the healthy patient and AHCT groups was compared by a pairwise Wilcox test to a retrospective cohort of allo-HSCT patients. Results: We evaluated 857 samples from 365 adult patients undergoing AHCT, with 316 patients from Memorial Sloan Kettering Cancer Center (MSKCC) and 49 patients from Duke University Medical Center (DUMC). Median pre-transplant diversity in AHCT patients from both centers was significantly lower than in normal controls (Fig 1A) (HMP vs MSKCC AHCT, S=12.05 vs. 9.19, p 〈 0.005; HMP vs DUMC AHCT, S=12.05 vs 6.91, p 〈 0.005) and reduced in both AHCT patients and allo-HSCT patients (MSKCC AHCT vs MSKCC allo-HSCT, S = 12.05 vs 8.74, p=0.53). In samples taken from days -10 to +30 after transplant, diversity decreased comparably after AHCT and allo-HSCT across both centers, while AHCT patients demonstrated a more rapid recovery at day +30 compared to allo-HSCT patients (Fig 1B). Finally, monodominance was observed in the samples (Fig 1C), with Streptococcus as the most common genus. The cumulative incidence of intestinal domination by any organism was 〉 50% by day 0 and was 〉 75% by day +14. Conclusion: Microbial diversity is reduced prior to transplant in both AHCT and allo-HSCT patients. Loss of diversity after AHCT occurs across centers and the degree of injury is comparable to the dysbiosis in allo-HSCT patients. Preliminary analysis suggests that lower diversity may correlate with worse progression-free survival (PFS) in myeloma patients in our diverse AHCT cohort. Given the known associations of alterations in microbiota composition with toxicities and overall survival in allo-HSCT patients, further evaluation of microbiota injury and its associations with toxicities, PFS, and overall survival (OS) in AHCT patients is warranted. Figure 1: A: The median Simpson reciprocal a-diversity index (S) of pre-transplant (days -10 to 0) samples of AHCT and allo-HSCT patients from two centers, as well as two cohorts of healthy volunteers, was plotted and a pairwise Wilcox test was performed, with p-values as indicated. B: (S) was plotted against time relative to allo-HSCT (on L) and AHCT (on R), for samples collected from day -10 to day +30. Larger values indicate greater diversity. C: Microbiota composition and changes in bacterial monodominance after transplant (days -14 to +28); the most common genus post-transplant is Streptococcus. Figure 1. Figure 1. Disclosures Peled: Seres Therapeutics: Research Funding. Sauter:Juno Therapeutics: Consultancy, Research Funding; Sanofi-Genzyme: Consultancy, Research Funding; Spectrum Pharmaceuticals: Consultancy; Novartis: Consultancy; Precision Biosciences: Consultancy; Kite: Consultancy. Shah:Amgen: Research Funding; Janssen: Research Funding. Perales:Novartis: Other: Personal fees; Incyte: Membership on an entity's Board of Directors or advisory committees, Other: Personal fees and Clinical trial support; Merck: Other: Personal fees; Takeda: Other: Personal fees; Abbvie: Other: Personal fees. Jenq:Ziopharm Oncology: Consultancy; Seres Therapeutics, Inc.: Membership on an entity's Board of Directors or advisory committees; MicrobiomeDx: Consultancy; Seres Therapeutics, Inc.: Patents & Royalties.

Abstract: Background: Patients with diffuse large B cell lymphoma (DLBCL) who do not achieve a complete response (CR) following CD19-targeted Chimeric Antigen Receptor T cell (CAR T) therapy are less likely to obtain durable benefit. Greater tumor burden pre-CAR T has been shown to predict lower CR rate and shorter survival. Recently, patterns of failure studies have identified baseline lesion characteristics including size, SUV, and extranodal location as associated with increased risk of post-CAR T failure. It is not yet known how bridging radiotherapy (BRT) prior to CAR T can alter subsequent patterns of failure. Methods: We reviewed DLBCL patients treated from 2017 to 2021 with BRT for any intent in the period from 30d pre-leukapheresis to CAR T infusion. Comprehensive BRT fields were defined as no avidity above liver mean outside of the BRT field. Bulky disease was defined as a max diameter of ≥7.5cm in any dimension. PET response was evaluated by Lugano criteria. Pattern of failure analysis was performed to identify failure sites as pre-existing (present pre-CAR T) vs. new and as in-field, marginal, or distant with respect to BRT. Marginal was defined as failure outside of the area receiving prescription dose but within 1cm of BRT field edge. One patient with a cutaneous target was excluded from size-based analyses. Significance was assessed by Fisher's exact test or T-test. Results: Thirty-five patients were identified with a median age of 66. Most were advanced stage (74%) at BRT with a median of 3 prior lines of systemic therapy. Twelve (35%) had bulky disease at any site pre-BRT (median max diameter 5.9 cm; range 1.1 - 24) with highest overall SUV median 19.8 (range 3.4 - 47); 83% (n=29) had ≥1 extranodal site (bone: n=13; CNS: n=4). Most common BRT sites were head/neck (n=10), pelvis (n=6), and extremity (n=5). BRT targeted the largest lesion in 85% (median 5.8 cm; 32% bulky) and the site of highest SUV in 81% (median 18.7); 49% (n=17) of targets were extranodal. BRT fields were comprehensive in 39%; median radiation treatment volume was 751cc (range 18 - 5856). Twenty-four patients (63%) received ≥30 Gy (median 30 Gy; range 20 - 54). Systemic therapy was given during the bridging period to 31% (n=11). Patients received axicabtagene (n=20), tisagenlecleucel (n=11), lisocabtagene (n=3), or experimental CAR T (n=1). On PET after BRT and pre-infusion (median 12d from BRT), 85% (n=23) had achieved partial response (PR) or better in-field (CR: n=7) though 63% had kinetically active disease with out-of-field progression (PD) and 19% (n=5) had marginal PD. Despite short interval restaging, there was a significant reduction in patients with bulky disease after BRT both within the irradiated field (p=0.007) and at any site (p=0.01). (Fig 1a) A median 81% SUV reduction in the irradiated site was noted with a significant decrease in max SUV in both the irradiated (p & lt;0.001) and any (p=0.03) site. Following CAR T, 82% (n=26) achieved in-field CR and 68% (n=21) overall CR. With median post CAR T follow up of 11.5 mo (range 1.5 - 40), 20 patients (57%) ultimately failed at any site. Most failures (18/20) involved sites distant to the BRT field, however the predominant failure pattern remained within lesions that were present prior to CAR T (16/20). (Fig 1b) Eight patients failed in-field and 8 patients failed marginally; the majority (7/8 in both cases) also experienced distant failure. Comprehensive BRT was not significantly associated with decreased risk of pre-existing site failure. In the subset of patients with a bulky lesion irradiated (n=11; median lesion size 11cm), 73% (n=8) achieved a CR in-field post CAR T and of those 8, only one progressed in-field at 22 mo post CAR T. Conclusion: BRT significantly reduced the number of patients with bulky disease at any site at time of CAR T and significantly reduced the overall highest lesional SUV. Marginal failure rates of 19% and 23% at interim scan post-BRT and after CAR T, respectively in conjunction with the pattern of post CAR T failure predominantly in pre-existing sites, may suggest a need for more generous fields when a BRT approach is used in this population with rapidly proliferating disease. Further work and larger sample sizes are needed to evaluate the impact of dose on local control in bulky lesions as well as to investigate whether comprehensive BRT affects outcomes or patterns of failure. Figure 1 Figure 1. Disclosures Palomba: Juno: Patents & Royalties; Notch: Honoraria, Other: Stock; Novartis: Consultancy; Kite: Consultancy; PCYC: Consultancy; Wolters Kluwer: Patents & Royalties; Seres: Honoraria, Other: Stock, Patents & Royalties, Research Funding; Magenta: Honoraria; Ceramedix: Honoraria; WindMIL: Honoraria; Nektar: Honoraria; Rheos: Honoraria; Priothera: Honoraria; BeiGene: Consultancy; Lygenesis: Honoraria; Pluto: Honoraria. Shouval: Medexus: Consultancy. Batlevi: Kite Pharma: Consultancy; Viatris: Current holder of individual stocks in a privately-held company; Dava Oncology: Honoraria; TG Therapeutics: Consultancy; ADC Therapeutics: Consultancy; Regeneron: Current holder of individual stocks in a privately-held company; TouchIME: Honoraria; Juno/Celgene: Consultancy; Medscape: Honoraria; BMS: Current holder of individual stocks in a privately-held company; Seattle Genetics: Consultancy; Life Sciences: Consultancy; Pfizer: Current holder of individual stocks in a privately-held company; Karyopharm: Consultancy; Moderna: Current holder of individual stocks in a privately-held company; Memorial Sloan Kettering Cancer Center: Current Employment; Bayer: Research Funding; GLG Pharma: Consultancy; Xynomic: Research Funding; Roche/Genentech: Research Funding; Novartis: Research Funding; Epizyme: Research Funding; Janssen: Research Funding; Autolus: Research Funding. Brentjens: Gracell Biotechnologies, Inc: Consultancy, Ended employment in the past 24 months; BMS: Consultancy, Patents & Royalties, Research Funding; sanofi: Patents & Royalties; Caribou: Patents & Royalties. Dahi: Kite / Gilead: Membership on an entity's Board of Directors or advisory committees. Giralt: JAZZ: Membership on an entity's Board of Directors or advisory committees; AMGEN: Membership on an entity's Board of Directors or advisory committees; JENSENN: Membership on an entity's Board of Directors or advisory committees; PFIZER: Membership on an entity's Board of Directors or advisory committees; GSK: Membership on an entity's Board of Directors or advisory committees; SANOFI: Membership on an entity's Board of Directors or advisory committees; BMS: Membership on an entity's Board of Directors or advisory committees; CELGENE: Membership on an entity's Board of Directors or advisory committees; Actinnum: Membership on an entity's Board of Directors or advisory committees. Park: BMS: Consultancy; Kite Pharma: Consultancy; Innate Pharma: Consultancy; Novartis: Consultancy; Minerva: Consultancy; Servier: Consultancy; Kura Oncology: Consultancy; PrecisionBio: Consultancy; Amgen: Consultancy; Intellia: Consultancy; Artiva: Consultancy; Curocel: Consultancy; Autolus: Consultancy; Affyimmune: Consultancy. Scordo: Angiocrine Bioscience: Consultancy, Research Funding; Kite - A Gilead Company: Membership on an entity's Board of Directors or advisory committees; i3 Health: Other: Speaker; Omeros Corporation: Consultancy; McKinsey & Company: Consultancy. Sauter: Bristol-Myers Squibb: Research Funding; GSK: Consultancy; Gamida Cell: Consultancy; Precision Biosciences: Consultancy; Kite/Gilead: Consultancy; Celgene: Consultancy, Research Funding; Genmab: Consultancy; Novartis: Consultancy; Spectrum Pharmaceuticals: Consultancy; Juno Therapeutics: Consultancy, Research Funding; Sanofi-Genzyme: Consultancy, Research Funding. Shah: Amgen: Research Funding; Janssen Pharmaceutica: Research Funding. Perales: Merck: Honoraria; Bristol-Myers Squibb: Honoraria; Celgene: Honoraria; Cidara: Honoraria; Miltenyi Biotec: Honoraria, Other; Kite/Gilead: Honoraria, Other; Equilium: Honoraria; Incyte: Honoraria, Other; Medigene: Honoraria; Karyopharm: Honoraria; Takeda: Honoraria; Servier: Honoraria; NexImmune: Honoraria; Novartis: Honoraria, Other; Nektar Therapeutics: Honoraria, Other; Sellas Life Sciences: Honoraria; Omeros: Honoraria; MorphoSys: Honoraria.

Abstract: Background: Guidelines recommend reimmunization starting 12 months after autologous hematopoietic stem cell transplant (AHCT). However, lymphoma patients routinely receive rituximab, an anti-CD20 monoclonal antibody that depletes CD20+ B-cells and may impair response to vaccination. We have shown that rituximab use may prevent on time vaccination in patients who undergo an allogeneic stem cell transplant (BBMT 2018 S427-S428). We therefore aimed to evaluate the impact of rituximab on responses to revaccination after AHCT and included patients with B-cell Non-Hodgkin Lymphoma (B-NHL) and T-cell NHL (T-NHL) and Hodgkin Lymphoma (HL), with the latter two groups not routinely receiving rituximab. Methods: Lymphoma patients who underwent AHCT between 2012 - 2016 were identified from the institutional database and included if they had completed the primary series and had pre- and post-vaccination titers to evaluate for response. Patients were divided by histology (B-NHL vs T-NHL and HL), and chart reviewed confirmed if they had received pre- or post- AHCT rituximab. Vaccine responses were determined by comparison of pre- and post- vaccination titers. Patients were classified as responders, non-responders, immune by pre-vaccination titer, and not evaluable due to missing data (had not received vaccine or had missed pre- or post-vaccination titers) by previously described criteria (Palazzo BBMT 2017). Descriptive statistics were used to summarize results, and the Fishers exact test was used for comparisons. Results: Of the 161 patients who met our inclusion criteria, 104 (65%) received rituximab pre-AHCT with 20% of these receiving additional rituximab post-HCT. Of the 57 patients who did not receive pre-AHCT rituximab, 2% received post-AHCT rituximab. The median age of the whole group was 53 years (range, 19-73), with patients not receiving rituximab being younger (median age 43 years (range 19-71) vs 58 years (21-73), p 〈 0.001). While 57% of the total population was male, there was a statistically significant difference based on rituximab use (42% of those not receiving rituximab vs 65.5% of those receiving rituximab, p=0.005). The no rituximab group comprised of 67% HL and 33% NHL, while the rituximab receiving group was 83% NHL. The most common conditioning regimen was BEAM (77%, carmustine, etoposide, cytarabine, and melphalan) with 12% receiving TBC (thiotepa, busulfan, and cyclophosphamide). Time to vaccination from AHCT was not different with a median of 12.4 months (range 9.1-21.8) in the no rituximab group compared to 12.6 months (range 11.3 - 45.7) in the rituximab exposed patients (p=0.08). The median time between last pre-AHCT rituximab and first vaccination was 14.1 months (range 12 - 79.8 months). Most patients received the completed series for each vaccine (84% Haemophilus influenzae, 99% pneumococcus, 96% polio, 66% tetanus, 76% diphtheria, 91% pertussis, 78% Hepatitis A, and 84% Hepatitis B), but vaccine responses varied by vaccine type with 48% responding to Haemophilus influenzae, 45% pneumococcus, 32% tetanus, 34% diphtheria, 52% pertussis, 31% Hepatitis A, and 37% Hepatitis B (Figure 1). Response to polio vaccine could not be calculated as 53% retained immunity and the rest of the patients were non-evaluable possibly due to a change in assay. No patients retained immunity to pneumococcus or diphtheria on the pre-vaccine titers. Univariate analyses were performed for pertussis, diphtheria, Hepatitis A, Hepatitis B and Pneumococcal vaccines evaluating the association with age, gender, disease type, and rituximab exposure. More females than males responded to B. pertussis (90% vs 78%, p=0.045). Hepatitis A and Hepatitis B response was associated with a younger age (50.7 years vs 59.6 years, p=0.037 and 54.2 years vs 62.4 years, p=0.007, respectively), and disease type was associated with pneumococcal response (62% HL vs 39% NHL, p=0.022). Patients who did not receive rituximab were more likely to respond to pneumococcus and Hepatitis B (63% vs 35%, p=0.001, and 82% vs 56%, p=0.026, respectively, Figure 2). Conclusions: Response to reimmunization with inactivated vaccines in lymphoma patients after AHCT is similar to previously reported populations, but prior rituximab exposure appears to impact response. Disclosures Matasar: Seattle Genetics: Honoraria. Moskowitz:Merck & Co: Consultancy, Research Funding; Genentech: Consultancy, Research Funding; Pharmacyclics: Research Funding; Seattle Genetics: Consultancy, Research Funding; Celgene: Consultancy. Sauter:Juno Therapeutics: Consultancy, Research Funding; Sanofi-Genzyme: Consultancy, Research Funding; Spectrum Pharmaceuticals: Consultancy; Novartis: Consultancy; Precision Biosciences: Consultancy; Kite: Consultancy. Shah:Amgen: Research Funding; Janssen: Research Funding. Perales:Abbvie: Other: Personal fees; Incyte: Membership on an entity's Board of Directors or advisory committees, Other: Personal fees and Clinical trial support; Takeda: Other: Personal fees; Merck: Other: Personal fees; Novartis: Other: Personal fees.

Abstract: Background : While incorporation of HLA-allele matching has highlighted high degrees of CB unit-recipient HLA-disparity, the less stringent HLA-match requirements extends allograft access to many patients without matched adult donors. The extent to which HLA-mismatch can adversely affect CBT outcomes, & the maximum permitted degree of HLA-mismatch, however, are not established. Methods : We analyzed TRM, relapse & PFS after intermediate intensity myeloablative cyclophosphamide 50 mg/kg, fludarabine 150 mg/m2, thiotepa 5-10 mg/kg, 400 cGy TBI double unit CBT in adults transplanted for hematologic malignancies. Eligible patients (pts) were first allograft recipients ≤ 65 years transplanted for acute leukemia/ MDS/ MPD (≤ 10% blasts pre-CBT), B-cell or T-cell lymphomas between 1/2014 - 12/2017. TNC & CD34+ dose were typically given priority over HLA-match in unit selection. Results : 102 pts [51 (50%) non-European, 59 (58%) CMV seropositive, median age 50 years (range 21-65), median weight 80 kg (range 36-137)] were transplanted. Diagnoses included 71 acute leukemias, 17 CML/ MPD/ MDS, 14 B- or T-cell NHLs. All received double unit grafts comprised of 2 (1%) 6/6 units, 21 (10%) 5/6, 181 (89%) 4/6 HLA-match, median unit-recipient 8-allele HLA-match 5/8 (range 3-7), & median infused viable CD34+ dose 1.3 x 105/kg/unit (range 0.2-8.6). Forty-eight (47%) CB grafts were supplemented with haplo-identical CD34+ cells as a myeloid bridge. The cumulative incidence of sustained CB engraftment was 97% (95%CI 90-99) with 2 pts having graft failure. A dominant (engrafting) unit was identified in all pts but 1 who died on day +14. Day 180 incidences of grades II-IV & III-IV aGVHD were 89% (95%CI 81-94) & 23% (95%CI 15-31), respectively. 1-yr cGVHD was 4% (95%CI 1-9). Cumulative incidence of TRM was 9% (95%CI 4-15) at day 180 & 14% (95%CI 8-22) at 2 yrs. 11% (95%CI 6-19) of pts relapsed by 2 yrs. With a median survivor follow-up of 2 yrs 3 months (range 6 - 51), the 2-yr overall survival is 82% (95%CI 75-90) & PFS is 74% (95%CI 66-84). Causes of death were transplant-related in 16 pts [6 aGVHD, 4 infection (2 viral, 1 bacterial, 1 fungal), 4 organ failure, 1 graft failure, 1 unknown] & due to relapse in 4 pts. By 2-yrs post-CBT, engrafting unit-recipient HLA-allele match had no association with TRM or PFS (Figure). Univariate analysis of the association between recipient variables [age, age adjusted hematopoietic cell transplant-comorbidity index (aaHCT-CI), revised disease risk index (rDRI)] & graft variables [engrafting unit-recipient HLA-allele match & infused CD34+ cell dose] & TRM, relapse & PFS are shown (Table). Age & aaHCT-CI were associated with 2-yr TRM with the 50 younger pts ( 〈 50 years), & the 66 pts with aaHCT-CI 0-3, having especially low 2-yr TRM of 5% & 10%, respectively. Neither engrafting unit-recipient HLA-match nor CD34+ dose were associated with TRM. No pt or graft variable was associated with relapse. The only significant variable associated with 2-yr PFS was aaHCT-CI. The 66 pts with a lower aaHCT-CI score of 0-3 had a higher 2-year PFS [82% (95%CI 73-92)] than the 36 high score 4-9 pts [60% (95%CI 46-79)] . rDRI, engrafting unit-recipient 8-allele HLA-match & CD34+ cell dose had no effect. Multivariate analysis of TRM was precluded by too few events. Multivariate analysis of PFS including aaHCT-CI, rDRI & engrafting unit-recipient HLA-match showed high aaHCT-CI was associated with worse PFS [HR 2.82 (1.28-6.25) if score 4-9 vs 0-3, p = 0.01]; neither rDRI [HR 1.21 (0.54-2.69) if high-very high vs low-intermediate, p = 0.64] nor engrafting unit-recipient HLA-match [HR 2.06 (0.89-4.74) if 5-7/8 vs 3-4/8 matched (p = 0.09] were significant. Conclusions : Our finding that a high level of HLA-allele mismatch of the engrafting unit was not significantly associated with TRM or PFS in adult dCBT for hematologic malignancies has multiple implications. It supports the use of units with a relatively high degree of HLA-mismatch in the dCBT setting if needed in these pts. This facilitates extension of allograft access to the majority of pts including minorities. Moreover, the high PFS supports our centers unit selection strategy that gives unit quality & cell dose a priority in adults with malignancies to optimize engraftment. Finally, this data support CBT in many high-risk or urgent pts even if a well-matched CB graft cannot be identified. This is especially true in younger pts or those with a low 0-3 aaHCT-CI who had high 2-yr PFS. Disclosures Perales: Incyte: Membership on an entity's Board of Directors or advisory committees, Other: Personal fees and Clinical trial support; Novartis: Other: Personal fees; Abbvie: Other: Personal fees; Merck: Other: Personal fees; Takeda: Other: Personal fees. Sauter:Juno Therapeutics: Consultancy, Research Funding; Sanofi-Genzyme: Consultancy, Research Funding; Spectrum Pharmaceuticals: Consultancy; Novartis: Consultancy; Precision Biosciences: Consultancy; Kite: Consultancy. Shah:Janssen: Research Funding; Amgen: Research Funding.