Reshef, Ran

Abstract Steroid-refractory (SR) acute graft-versus-host disease (GVHD) remains a major cause of nonrelapse mortality (NRM) after allogeneic hematopoietic cell transplantation (HCT), but its occurrence is not accurately predicted by pre-HCT clinical risk factors. The Mount Sinai Acute GVHD International Consortium (MAGIC) algorithm probability (MAP) identifies patients who are at high risk for developing SR GVHD as early as 7 days after HCT based on the extent of intestinal crypt damage as measured by the concentrations of 2 serum biomarkers, suppressor of tumorigenesis 2 and regenerating islet-derived 3α. We conducted a multicenter proof-of-concept “preemptive” treatment trial of α-1-antitrypsin (AAT), a serine protease inhibitor with demonstrated activity against GVHD, in patients at high risk for developing SR GVHD. Patients were eligible if they possessed a high-risk MAP on day 7 after HCT or, if initially low risk, became high risk on repeat testing at day 14. Thirty high-risk patients were treated with twice-weekly infusions of AAT for a total of 16 doses, and their outcomes were compared with 90 high-risk near-contemporaneous MAGIC control patients. AAT treatment was well tolerated with few toxicities, but it did not lower the incidence of SR GVHD compared with controls (20% vs 14%, P = .56). We conclude that real-time biomarker-based risk assignment is feasible early after allogeneic HCT but that this dose and schedule of AAT did not change the incidence of SR acute GVHD. This trial was registered at www.clinicaltrials.gov as #NCT03459040.

Background: Axi-cel is an autologous anti-CD19 chimeric antigen receptor (CAR) T cell therapy approved for pts with R/R LBCL with ≥ 2 prior systemic therapies. With a median follow-up of 27.1 months in ZUMA-1, the objective response rate (ORR) with axi-cel was 83% (58% complete response rate) in pts with refractory LBCL. Grade ≥ 3 cytokine release syndrome (CRS) and neurologic events (NEs) occurred in 11% and 32% of pts, respectively (Locke FL, et al. LancetOncol. 2019). Although CRS can be ameliorated with use of the anti-IL-6 receptor antibody tocilizumab, NEs may be unaffected or worsened by tocilizumab (Gust J, et al. Cancer Discov. 2017; Lee DW, et al. Blood. 2014; Santomasso BD, et al. Cancer Discov. 2018; Locke FL, et al. ASH 2017. #1547). Identification of mitigation strategies for NEs is complicated by a significant association between CAR T cell expansion and both ORR and Grade ≥ 3 NEs, suggesting a correlation between efficacy and adverse events (AEs; Neelapu SS, et al. N EnglJ Med. 2017). ZUMA-1 Cohort 4 suggested that earlier utilization of systemic corticosteroids for broad immune system suppression in pts with mild NEs and low-grade CRS may reduce the incidence of Grade ≥ 2 NEs without significant impact on efficacy (Topp MS, et al. ASH 2019. #243). However, this reactive approach has not fully abrogated NEs; as such, proactive strategies to further improve safety management with CAR T cell therapy without negatively impacting efficacy are needed. Upon tumor challenge, CAR T cells produce granulocyte-macrophage colony-stimulating factor (GM-CSF; Giavridis T, et al. Nat Med. 2018), which acts to promote myeloid activation, expansion, and cytokine production (Spath S, et al. Immunity. 2017). GM-CSF was among the cytokines significantly associated with Grade ≥ 3 NEs in ZUMA-1 (Neelapu SS, et al. N Engl J Med. 2017). Notably, peak GM-CSF levels occurred before those of most other cytokines, and no direct association was observed between GMCSF levels and ORR (Rossi JM, et al. EMA Workshop, 2016). These findings suggest that GM-CSF may initiate inflammatory events that cause NEs and that GM-CSF inhibition has the potential to improve the safety of CAR T cells, without impacting efficacy. GM-CSF depletion with lenzilumab, a humanized monoclonal antibody that neutralizes GM-CSF, prevented CRS and NEs in preclinical models of CAR T cell toxicity (Sterner RM, et al. Blood2019). The Phase 1/2 ZUMA19 study is evaluating sequenced therapy with lenzilumab and axi-cel to prevent axi-cel-related CRS and NEs in pts with R/R LBCL. Methods: Eligible pts are adults (≥ 18 y) with LBCL who relapsed after ≥ 2 systemic lines of therapy or are chemorefractory - defined as i) a best response of progressive disease (PD) or stable disease (SD) to ≥ 4 cycles of first-line systemic therapy (SD duration ≤ 6 months); or ii) a best response of PD or SD after ≥ 2 cycles of the most recent second-or-later line of systemic therapy. Prior therapy must have included an anti-CD20 monoclonal antibody and an anthracycline-containing regimen. Pts will undergo leukapheresis and may receive optional corticosteroid bridging therapy. Pts will then receive lymphodepleting chemotherapy on Days ‒3 to ‒5 followed by Day 0 administration of lenzilumab and, 6 hours later, a single infusion of axi-cel (target dose, 2 × 106 CAR T cells/kg). Phase 1 will initially enroll pts in 2 dose-escalation cohorts; each will receive a single infusion of lenzilumab. Safety data will be reviewed after 3 and 6 (if needed) pts in each cohort have been followed for 28 days. The recommended Phase 2 dose (RP2D) of lenzilumab will be based on the dose-limiting toxicity rate (phase 1 primary endpoint), and, if necessary, translational assessment of GM-CSF axis suppression. Phase 2 will assume a Simon 2-stage design. The primary endpoint for phase 2 is the incidence of Grade ≥ 2 NEs within 28 days of axi-cel administration. Efficacy, safety (including CRS and NEs), and blood levels of CAR T cells and cytokines (including GM-CSF) will be evaluated as secondary endpoints. An interim analysis will be performed when 14 subjects have received the RP2D in Phase 1 or 2 and are followed for ≥ 28 days after axi-cel infusion. If futility criteria are not met, enrollment will continue. Primary analysis will be performed after 30 pts are treated with RP2D of lenzilumab and have ≥ 6 months of follow up. ZUMA-19 is open and actively recruiting pts. Disclosures Kenderian: Mettaforge: Patents & Royalties; Humanigen: Consultancy, Patents & Royalties, Research Funding; Lentigen: Research Funding; MorphoSys: Research Funding; Sunesis: Research Funding; Tolero: Research Funding; BMS: Research Funding; Juno: Research Funding; Gilead: Research Funding; Kite: Research Funding; Novartis: Patents & Royalties, Research Funding; Torque: Consultancy. Oluwole:Bayer: Consultancy; Pfizer: Consultancy; Kite, a Gilead Company: Consultancy, Honoraria, Research Funding; Spectrum Pharmaceuticals: Consultancy. McCarthy:Genentech: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Advisory Board; Juno Therapeutics, a Bristol-Myers Squibb Company: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Advisory Board , Research Funding is to Roswell Park, Research Funding; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Advisory Board; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Advisory Board; Karyopharm: Consultancy, Honoraria; Magenta: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Advisory Board; Starton: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Advisory Board. Reshef:Celgene: Consultancy; Pharmacyclics: Research Funding; Shire: Research Funding; Bluebird: Research Funding; Kiadis: Research Funding; Monsanto: Consultancy; Takeda: Research Funding; Atara: Consultancy, Research Funding; Incyte: Research Funding; Bristol-Myers Squibb: Research Funding; Immatics: Research Funding; Gilead: Consultancy, Honoraria, Other: Travel support, Research Funding; Novartis: Honoraria; Magenta: Consultancy. Shiraz:Kite, a Gilead Company: Research Funding; ORCA BioSystems: Research Funding. Ahmed:Humanigen, Inc.: Current Employment, Current equity holder in publicly-traded company. Le Gall:Kite, a Gilead Company: Ended employment in the past 24 months; Gilead Sciences: Current equity holder in publicly-traded company. Nahas:Gilead Sciences: Current equity holder in publicly-traded company; Kite, a Gilead Company: Current Employment. Tang:Kite, a Gilead Company: Current Employment; Gilead Sciences: Current equity holder in publicly-traded company. Neelapu:Takeda Pharmaceuticals: Patents & Royalties; Cellectis: Research Funding; Calibr: Other; Precision Biosciences: Other: personal fees, Research Funding; Bristol-Myers Squibb: Other: personal fees, Research Funding; Merck: Other: personal fees, Research Funding; Kite, a Gilead Company: Other: personal fees, Research Funding; Acerta: Research Funding; Karus Therapeutics: Research Funding; Poseida: Research Funding; Cell Medica/Kuur: Other: personal fees; Incyte: Other: personal fees; Unum Therapeutics: Other, Research Funding; N/A: Other; Adicet Bio: Other; Legend Biotech: Other; Allogene Therapeutics: Other: personal fees, Research Funding; Pfizer: Other: personal fees; Celgene: Other: personal fees, Research Funding; Novartis: Other: personal fees.

Systemic glucocorticoids are the principal treatment for acute graft-versus-host disease (GVHD), which remains the major cause of non-relapse mortality (NRM) after allogeneic hematopoietic cell transplantation (HCT). However, there are no validated biomarkers that measure a patient's response to glucocorticoid therapy, and thus response is evaluated by the change in clinical symptom severity. A major weakness in the predictive power of clinical responses is that changes to all organs are weighted equally even though the major driver of NRM is irreversible damage to the crypts of the GI tract. Recent studies from the Mount Sinai Acute GVHD International Consortium (MAGIC) have validated an algorithm probability (MAP) that combines serum concentrations of two biomarkers of GVHD (REG3α and ST2) to generate an estimated probability of 6 month NRM for individual patients. The MAP has been considered a "liquid biopsy" that estimates the damage caused by GVHD to crypts throughout the lower GI tract (Hartwell et al., JCI Insight, 2017; Major-Monfried et al., Blood, 2018). We hypothesized that the change in MAP between start of treatment and 28 days later could serve as a response biomarker for GVHD and might compare favorably to the change in clinical symptoms that measures response to GVHD treatment, which is widely used as a surrogate for long term survival and is the primary endpoint in most GVHD treatment trials (Martin et al., BBMT, 2009; MacMillan et al., Blood, 2010). We prospectively collected serum samples and clinical staging from 368 sequential HCT patients who received systemic treatment for acute GVHD in one of 20 MAGIC centers between January 2016 and February 2018. We measured the serum concentrations of REG3α and ST2 before and after systemic therapy for acute GVHD and computed MAPs, the changes in MAPs, and clinical responses for each patient. MAPs of patients who experienced 6 month NRM showed significantly greater increases than MAPs of patients who survived (p=0.0004). In patients whose MAPs at the start of treatment were low (Ann Arbor 1, MAP < 0.141) or intermediate (Ann Arbor 2, 0.141 ≤ MAP ≤ 0.290), 6 month NRM clustered among those who had the greatest increases in MAP after 28 days (Fig 1A,B). In patients with high MAPs at the start of treatment (Ann Arbor 3, MAP > 0.290), those who survived tended to have the largest decreases in MAP (Fig 1C). These changes in MAP suggested crossing a single threshold could predict risk of mortality. We found that patients whose MAPs rose above a threshold MAP of 0.290 (5% of Ann Arbor 1, 27% of Ann Arbor 2) had significantly worse survival compared to those who remained below it, whereas the large number patients with initially high MAPs that remained above the threshold (66% of Ann Arbor 3) had a large increases in mortality (Fig 2). When measured at day 28, the MAP was significantly more accurate in predicting NRM than the gold standard of the clinical response, with areas under the receiver operating characteristic curve (AUC) of 0.86 and 0.70, respectively (p<0.0001). An algorithm that combined clinical response with biomarkers generated the same AUC as the MAP alone (0.83 v 0.86, p = NS). We next tested whether the same MAP threshold of 0.290 could predict risk within clinical response subsets. A significant minority (10%) of clinical responders had high MAPs and experienced three-fold greater NRM than those with low MAPs (40% v 12%, p<0.0001) whereas the majority (57%) of non-responders had low MAPs and experienced almost three-fold lower NRM than those with high MAPs (24% v 65%, p<0.0001) (Fig 3). Thus the MAP provides important prognostic information over and above the change in clinical symptoms, further stratifying both responders and non-responders at four weeks of treatment. The MAP threshold classified patients both with and without significant lower GI symptoms because the MAP is a more specific measure of irreversible cryptic damage in patients with copious diarrhea and more sensitive in patients with less than 0.5 liters of daily diarrhea (Fig 4). We conclude that the MAP is, to our knowledge, the first validated laboratory test to serve as response biomarker for the treatment for acute GVHD and a more accurate predictor of survival than clinical response after four weeks of treatment. The MAP may serve as a novel endpoint and an important complement to changes in clinical symptom severity in future trials of GVHD treatment. Disclosures Srinagesh: National Institutes of Health: Research Funding. Ozbek:Viracor: Patents & Royalties: Biomarker Patent. Ayuk:Novartis: Honoraria, Other: Advisory Board, Research Funding. Aziz:Doris Duke Charitable Foundation: Research Funding. Defilipp:Incyte: Research Funding. Grupp:Novartis: Consultancy, Research Funding; Roche: Consultancy; GSK: Consultancy; CBMG: Consultancy; Novartis: Research Funding; Kite: Research Funding; Servier: Research Funding; Jazz: Other: study steering committees or scientific advisory boards; Adaptimmune: Other: study steering committees or scientific advisory boards; Cure Genetics: Consultancy; Humanigen: Consultancy. Hexner:novartis: Research Funding. Kitko:Mallinckrodt: Honoraria; Novartis: Consultancy, Honoraria. Mielke:EBMT/EHA: Other: Travel support; ISCT: Other: Travel support; Miltenyi: Consultancy, Honoraria, Other: Travel and speakers fee (via institution), Speakers Bureau; Jazz Pharma: Honoraria, Other: Travel support, Speakers Bureau; IACH: Other: Travel support; Kiadis Pharma: Consultancy, Honoraria, Other: Travel support (via institution), Speakers Bureau; DGHO: Other: Travel support; Bellicum: Consultancy, Honoraria, Other: Travel (via institution); GILEAD: Consultancy, Honoraria, Other: travel (via institution), Speakers Bureau; Celgene: Honoraria, Other: Travel support (via institution), Speakers Bureau. Merli:Sobi: Consultancy; Amgen: Honoraria; Novartis: Honoraria; Bellicum: Consultancy. Pulsipher:Amgen: Other: Lecture; Miltenyi: Research Funding; Bellicum: Consultancy; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Jazz: Other: Education for employees; CSL Behring: Membership on an entity's Board of Directors or advisory committees; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Medac: Honoraria. Qayed:Bristol-Myers Squibb: Honoraria. Reshef:Pfizer: Consultancy; Magenta: Consultancy; Kite: Consultancy, Research Funding; Atara: Consultancy, Research Funding; BMS: Consultancy; Pharmacyclics: Consultancy, Research Funding; Incyte: Consultancy, Research Funding; Celgene: Research Funding; Shire: Research Funding. Levine:Incyte: Consultancy, Research Funding; Biogen: Other: non-financial support; Viracor: Patents & Royalties: biomarker patent; Ironwood: Honoraria; bluebird bio: Consultancy; National Cancer Institute: Research Funding; Novartis: Honoraria; Kamada: Research Funding. Ferrara:National Institutes of Health: Research Funding; ViraCor: Consultancy; Incyte: Consultancy; Kamada: Consultancy; Mallinckrodt: Consultancy; Enlivex: Consultancy; Xenikos: Consultancy; CSL Behring: Consultancy.

Key Points The MAGIC algorithm probability, computed from 2 serum biomarkers, predicts mortality in all GVHD grades after 4 weeks of treatment. Dynamic changes in the MAGIC algorithm probability occur within all biomarker risk groups and can guide therapy.

Background: Axicabtagene ciloleucel (axi-cel) is an autologous anti-CD19 chimeric antigen receptor (CAR) T cell therapy approved for the treatment of adult patients who have relapsed/refractory large B cell lymphoma (LBCL) and have had ≥ 2 prior systemic therapies. In ZUMA-1, the registrational study of axi-cel in patients with refractory LBCL, the objective response rate was 83% (complete response rate, 58%), with ongoing responses in 39% after a median follow-up of 27.1 months (Locke FL, et al. Lancet Oncol. 2019). Despite the success of axi-cel, approximately 60% of patients have no response or relapse after treatment, indicating that additional strategies are needed for patients with relapsed/refractory LBCL. Preclinical murine studies have shown that rituximab augmented the tumor-suppressing effects of anti-CD19 CAR T cells, and the combination led to higher rates of tumor reduction (Mihara K, et al. Br J Haematol. 2010; Rufener GA, et al. Cancer Immunol Res. 2016). The IMiD® immunomodulatory agent lenalidomide has shown activity in patients with relapsed/refractory diffuse large B cell lymphoma and has also been shown to enhance the antitumor functions of anti-CD19 and anti-CD20 CAR T cells in mice (Otahal P, et al. Oncoimmunology. 2016). In ZUMA-14, the aim is to investigate the efficacy and safety of axi-cel in combination with rituximab or lenalidomide in adult patients with refractory LBCL. Methods: This Phase 2 study (NCT04002401) has a planned enrollment of approximately 60 patients aged ≥ 18 years with refractory LBCL, defined as a response of either progressive disease or stable disease to previous chemotherapy or progressive disease or relapse ≤ 12 months after an autologous stem cell transplant. Patients with prior IMiD® treatment, including lenalidomide, prior CAR T cell therapy, and/or prior CD19-targeted therapy are excluded. After leukapheresis, patients will be assigned 1:1 to receive axi-cel with either rituximab (Cohort 1) or lenalidomide (Cohort 2). Patients will receive lymphodepleting chemotherapy of fludarabine (30 mg/m2) and cyclophosphamide (500 mg/m2) on days -5 to -3 before axi-cel infusion (2 × 106 cells/kg) on Day 0. Cohort 1 will receive rituximab (375 mg/m2) every 28 days starting on Day -5 for a total of 6 doses. Cohort 2 will receive lenalidomide (10 mg) daily starting 7 days after leukapheresis through Day 3 and for 5 additional cycles (20 mg, first 21 days of each 28-day cycle) beginning after axi-cel infusion starting on Day 21. Patients may not receive any therapy other than conditioning therapy and rituximab or lenalidomide, as specified by cohort, between leukapheresis and axi-cel infusion. The primary endpoint is investigator-assessed complete response rate per the Lugano classification (Cheson BD, et al. J Clin Oncol. 2014). Key secondary endpoints include safety, objective response rate, duration of response, progression-free survival, overall survival, and pharmacokinetics (levels of blood CAR T cells over time). Exploratory endpoints for both cohorts include pharmacodynamic assessment of cytokine profiles and the rate of CD19-negative relapses. An additional exploratory endpoint for Cohort 2 is to investigate immunomodulation of the tumor microenvironment, including the number and activation of T cells and natural killer cells. Enrollment is expected to start in September 2019. Disclosures Neelapu: Cell Medica: Consultancy; Pfizer: Consultancy; BMS: Research Funding; Kite, a Gilead Company: Consultancy, Research Funding; Novartis: Consultancy; Precision Biosciences: Consultancy; Acerta: Research Funding; Karus: Research Funding; Incyte: Consultancy; Merck: Consultancy, Research Funding; Unum Therapeutics: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Cellectis: Research Funding; Allogene: Consultancy; Poseida: Research Funding. Kharfan-Dabaja:Daiichi Sankyo: Consultancy; Pharmacyclics: Consultancy. Oluwole:Pfizer: Consultancy; Spectrum: Consultancy; Gilead Sciences: Consultancy; Bayer: Consultancy. Krish:Celgene: Consultancy, Research Funding, Speakers Bureau; Genetech: Consultancy, Speakers Bureau; Pharmacyclics: Consultancy, Research Funding, Speakers Bureau; Takeda: Research Funding; Curis: Research Funding; MEI Pharma: Research Funding; Bristol Meyers Squibb: Research Funding; Xencor: Research Funding; Roche: Research Funding; AstraZeneca: Consultancy, Research Funding, Speakers Bureau; Sunesis: Consultancy, Research Funding. Reshef:BMS: Consultancy; Shire: Research Funding; Incyte: Consultancy, Research Funding; Kite, a Gilead Company: Consultancy, Honoraria, Research Funding; Atara: Consultancy, Research Funding; Magenta: Consultancy; Pfizer: Consultancy; Pharmacyclics: Consultancy, Research Funding; Celgene: Research Funding. Riedell:Bayer: Honoraria, Speakers Bureau; Kite/Gilead: Honoraria, Research Funding, Speakers Bureau; Verastem: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding. Stiff:Amgen: Research Funding; Gamida-Cell: Research Funding; Incyte: Research Funding; Cellectar: Research Funding; Unum: Research Funding; Gilead/Kite Pharma: Consultancy, Honoraria, Research Funding. Goyal:Kite, a Gilead Company: Employment. Kawashima:Kite, a Gilead Company: Employment, Equity Ownership. Milletti:Roche: Employment, Equity Ownership, Other: Travel Expenses, Patents & Royalties; Gilead: Employment, Equity Ownership, Other: Travel Expenses, Patents & Royalties; Kite, a Gilead Company: Employment. Oliva:Kite, a Gilead Company: Employment. Sun:Kite, A Gilead Company: Employment. Munoz:Pharmacyclics /Janssen: Consultancy, Research Funding, Speakers Bureau; Bayer: Consultancy, Speakers Bureau; Merck: Consultancy; Kyowa: Consultancy, Honoraria, Speakers Bureau; Seattle Genetics: Consultancy, Honoraria, Research Funding, Speakers Bureau; Celgene/Juno: Consultancy, Research Funding; Genentech: Consultancy, Research Funding, Speakers Bureau; Kite/Gilead: Consultancy, Research Funding, Speakers Bureau; Bristol-Myers Squibb: Consultancy; Alexion: Consultancy; Pfizer: Consultancy; Fosunkite: Speakers Bureau; AstraZeneca: Speakers Bureau; Portola: Research Funding; Incyte: Research Funding. OffLabel Disclosure: ZUMA-14 is a clinical trial evaluating the investigational combination of axicabtagene ciloleucel with either rituximab or lenalidomide in refractory large B cell lymphoma

Background: Relapsed/refractory (R/R) large B cell lymphoma (LBCL) is associated with poor outcomes to standard salvage therapy (Crump M, et al. Blood. 2017). In SCHOLAR-1, a large multicenter, patient-level, retrospective study, patients with R/R diffuse LBCL had a 26% objective response rate (ORR) to the next line of therapy, a 7% complete response (CR) rate, and a median overall survival of 6.3 months (Crump M, et al. Blood 2017). Axicabtagene ciloleucel (axi-cel) is an autologous anti-CD19 chimeric antigen receptor (CAR) T cell therapy approved for patients with R/R LBCL with ≥ 2 prior systemic therapies. With a median follow-up of 27.1 months in ZUMA-1, the ORR with axi-cel was 83% (58% CR rate) in patients with refractory LBCL (Locke FL, et al. Lancet Oncol. 2019). Activation of the costimulatory receptor 4-1BB (CD137) on CAR T cells may enhance axi-cel antitumor activity by enhancing T cell proliferation, function, and survival. Utomilumab (uto), an investigational monoclonal antibody agonist of the 4-1BB pathway, enhanced T cell function and survival in preclinical studies (Fisher TS, et al. Cancer Immunol Immunother. 2012) and had favorable single-agent safety in patients (Segal NH, et al. Clin Cancer Res. 2018). Possible mechanisms of resistance to axi-cel are thought to be suboptimal CAR T cell expansion an exclusionary tumor microenvironment and CD19 target antigen loss (Neelapu SS, et al. Blood 2017, Rossi JM, et al J Immunother Cancer. 2018). Combination strategies that increase proliferation, expansion, and persistence of CAR T cells or prevent activation-induced cell death of CAR T cells may improve clinical outcomes observed with axi-cel. ZUMA-11 is a Phase 1/2 study investigating the efficacy and safety of axi-cel + uto in patients with refractory LBCL. Methods: The primary objectives of this study are to determine the safety, recommended Phase 2 dosing and timing (Phase 1), and efficacy (Phase 2) of axi-cel + uto in adult patients with refractory LBCL. Patients with progressive or stable disease as the best response to second-line chemotherapy or relapse ≤ 12 months after autologous stem cell transplantation, a prior anti-CD20 antibody and anthracycline-containing regimen, and Eastern Cooperative Oncology Group performance status 0-1 are eligible. Patients with histologically proven primary mediastinal B cell lymphoma, history of Richter's transformation or chronic lymphocytic lymphoma, prior CAR T cell therapy, or central nervous system involvement of lymphoma are ineligible. In Phase 1, ≈24 patients in ≤ 3 cohorts will receive a single dose of axi-cel and escalating doses of uto (10, 30, or 100 mg) using a 3 + 3 design in up to 4 of 6 cohorts. The recommended uto dose will be based on dose-limiting toxicities and other factors. Patients will be leukapheresed and may receive optional, nonchemotherapy bridging therapy per investigator decision. After conditioning chemotherapy, patients will receive a single infusion of axi-cel (target dose, 2 × 106 CAR T cells/kg) on Day 0 followed by uto on Day 1 and every 4 weeks for 6 months or until progressive disease. Patients will be treated one at a time during Phase 1, and patients treated with axi-cel will be staggered by ≥ 2 weeks. Day 21 uto administration will be explored if toxicity is unacceptable with Day 1 administration. The primary endpoints are incidence of dose-limiting toxicities in Phase 1 and CR rate in Phase 2. Secondary endpoints include ORR, duration of response, progression-free survival, overall survival, safety, and levels of CAR T cells and cytokines in blood. This study uses a single-arm design to estimate the true CR rate; with a sample size of 27 patients, of which ≤ 3 patients will have been treated in the Phase 1 portion, the maximum half-width of the 95% confidence interval about response will be ≥ 21%. ZUMA-11 is open and accruing patients. Disclosures Reshef: Kite, a Gilead Company: Consultancy, Honoraria, Research Funding; Celgene: Research Funding; Incyte: Consultancy, Research Funding; Shire: Research Funding; BMS: Consultancy; Atara: Consultancy, Research Funding; Magenta: Consultancy; Pfizer: Consultancy; Pharmacyclics: Consultancy, Research Funding. Miklos:Pharmacyclics: Consultancy, Patents & Royalties, Research Funding; Precision Bioscience: Consultancy; Adaptive Biotechnologies: Consultancy, Research Funding; Miltenyi: Consultancy, Research Funding; Becton Dickinson: Consultancy; Janssen: Consultancy; AlloGene: Consultancy; Novartis: Consultancy; Kite, A Gilead Company: Consultancy, Research Funding; Celgene-Juno: Consultancy. Timmerman:Spectrum Pharmaceuticals: Research Funding; Kite, A Gilead Company: Consultancy, Honoraria, Other: travel support, Research Funding; ImmunGene: Research Funding; Merck: Research Funding; Bristol-Myers Squibb: Consultancy, Honoraria, Other: travel support, Research Funding. Jacobson:Novartis: Consultancy, Honoraria, Other: travel support; Bayer: Consultancy, Other: travel support; Precision Biosciences: Consultancy, Other: travel support; Humanigen: Consultancy, Other: travel support; Celgene: Consultancy, Other: travel support; Pfizer: Research Funding; Kite, a Gilead Company: Consultancy, Honoraria, Other: travel support. Bennani:Kite, A Gilead Company: Consultancy, Research Funding. Rossi:Kite, A Gilead Company: Employment. Sherman:Kite, A Gilead Company: Employment. Sun:Kite, A Gilead Company: Employment. Palluconi:Kite, A Gilead Company: Employment. Kim:Kite, A Gilead Company: Employment. Jain:Kite/Gilead: Consultancy.

Abstract Relapse of malignancy and lethal graft versus host disease (GVHD) are the principal causes of failure of allogeneic hematopoietic cell transplant (HCT). Recently we have shown that at seven days after HCT an algorithm using two serum biomarkers (ST2 and REG3α) can predict severe GVHD (Hartwell et al. JCI Insight 2017). We determined whether serial testing (in the first month following HCT) of patients with low probability biomarkers would improve the predictive accuracy of the algorithm and identify patients with different risks of relapse and lethal GVHD. Patients who received an HCT at 18 centers in the Mount Sinai Acute GVHD International Consortium (MAGIC) for hematologic malignancy and who supplied three blood samples were divided into a training set and validation set with equal numbers of lethal GVHD events, which was defined as death from GVHD or infection during treatment for GVHD. Patients in the training set (n=702) underwent HCT from January 1, 2006 until June 30, 2015, whereas patients in the validation set (n=906) underwent HCT from July 1, 2015 to May 1, 2017. Serum samples were analyzed using the previously published algorithm of two biomarkers up to three times (day 7, day 14, day 28 or GVHD onset, if onset occurred within the first 28 days). The algorithm generates a predicted probability of lethal GVHD between 0 and 1 for each patient. Patients were categorized as either low probability (LP) or high probability (HP) for lethal GVHD. HP thresholds of 0.20 and 0.16 were used to classify patients with and without GVHD symptoms, respectively (once categorized as HP, patients remained in that category and were not retested). All results were similar between training and validation sets, and we present here the validation set results. Serial testing identified 28% of patients as HP with a three-fold greater cumulative incidence of lethal GVHD at one year (13% vs 4%, p<0.001, Figure 1). Relapse rates were the same in both probability groups, and thus LP patients experienced significantly better relapse free survival (RFS) (69% vs 53%, p<0.001). As expected, significantly fewer LP patients experienced severe GVHD at onset (as measured by Minnesota risk), maximum grade III/IV GVHD, or steroid resistant GVHD by day 180 after HCT (Figure 2, p<0.001 for all three parameters). To measure the accuracy of prediction, at each timepoint we calculated the area under the curve (AUC) of receiver operating characteristic curves; the AUC increased significantly with each subsequent evaluation, from 0.59 at one timepoint (dotted line) to 0.74 at the third timepoint (solid line) (p<0.001), with a final sensitivity of 65% and specificity of 74% (Figure 3A). Early development of GVHD (by day 28) is a risk factor for lethal GVHD. Therefore, we next plotted RFS (dashed line), relapse (solid line), and lethal GVHD (dotted line) rates in patients who developed GVHD by day 28. 25% of patients with GVHD were categorized as HP and had a cumulative incidence of lethal GVHD more than four times higher (28%) than that of relapse (6%); however the risks were reversed for the 75% of patients who were LP, where relapse (15%) occurred twice as often as lethal GVHD (7%) (Figure 3B). In patients who did not develop GVHD in the first month, this reversal of risks was even more dramatic. Approximately half (53%) of the entire validation cohort did not develop GVHD by day 28 and was LP at all three evaluations. These patients had an exceptionally low risk of lethal GVHD and thus they relapsed (25%) much more often than they died from GVHD (3%). When malignancies were classified according to risk for relapse by the disease risk index (DRI) (Figure 3C), the probability of relapse was three fold higher than lethal GVHD in malignancies with a low DRI (12%), six fold higher for intermediate DRI (20%), and eleven fold higher for high/very high DRI (33%). We conclude that a serial monitoring strategy using GVHD biomarkers for one month after HCT is able to identify two groups of patients with very different risks of lethal GVHD and relapse. For these patients, the intensity of immunosuppression after day 28 could be tailored according to the probabilities of developing lethal GVHD and relapse in the context of clinical trials. Disclosures Aziz: Doris Duke Charitable Foundation: Research Funding. Ayuk:Therakos (Mallinckrodt): Honoraria; Novartis: Honoraria; Celgene: Consultancy; Gilead: Consultancy. Chen:REGiMMUNE: Consultancy; Incyte: Consultancy, Membership on an entity's Board of Directors or advisory committees; Magenta Therapeutics: Consultancy; Takeda Pharmaceuticals: Consultancy. Merli:Neovii Biotech: Honoraria; AMGEN: Honoraria. Roesler:Sanofi: Other: Travel, Accommodations, Expenses; Amgen: Equity Ownership; Jazz Pharmaceuticals: Other: Travel, Accommodations, Expenses; Immunomedics: Equity Ownership; Biogen: Equity Ownership; Merck: Consultancy; Pfizer: Consultancy. Kitko:Novartis: Consultancy, Honoraria; Mallinckrodt: Honoraria, Other: Travel, Accommodations, Expenses. Qayed:Novartis: Consultancy. Wölfl:Bristol-myers Squibb: Equity Ownership; Novartis: Equity Ownership; Taheda: Equity Ownership; Juno: Equity Ownership; Neovii: Other: Travel, Accommodations, Expenses. Mielke:Celgene: Speakers Bureau; DGHO: Speakers Bureau; EHA: Speakers Bureau; Kiadis Pharma: Speakers Bureau; Miltenyi: Speakers Bureau. Wudhikarn:Takeda Oncology: Other: Travel, Accommodations, Expenses. Nakamura:Celgene: Honoraria; Molmed: Honoraria; Merck: Consultancy; Pharmacyclics: Consultancy; Atara: Consultancy; Jazz Pharmaceuticals: Consultancy. Pulsipher:CSL Behring: Consultancy; Novartis: Consultancy, Honoraria, Speakers Bureau; Adaptive Biotech: Consultancy, Research Funding; Amgen: Honoraria. Reshef:Pfizer: Consultancy; Atara Biotherapeutics: Consultancy; Kite Pharma: Consultancy; Takeda Pharmaceuticals: Consultancy; Bristol-Myers Squibb: Consultancy; Incyte: Consultancy. Levine:Therakos: Consultancy; Novartis: Consultancy; Bluebird: Consultancy; Incyte: Consultancy; Kamada: Research Funding; Viracor: Patents & Royalties. Ferrara:Incyte: Consultancy, Honoraria, Other: Travel, Accommodations, Expenses; Xenikos: Consultancy, Other: Travel, Accommodations, Expenses; Kamada: Consultancy, Research Funding; Viracor: Consultancy, Patents & Royalties.

Abstract Graft-versus-host disease (GVHD), the primary cause of non-relapse mortality (NRM) following allogeneic hematopoietic stem cell transplantation, does not always respond to treatment with high dose systemic corticosteroids. We have recently shown that a combination of three biomarkers (TNFR1, ST2, and REG3α) measured at onset of GVHD can predict day 28 response to treatment and 6-month NRM (Levine, Lancet Haem, 2015). Our goal in the current study was to determine if the same biomarker-based Ann Arbor GVHD algorithm can alsopredict treatment response andmortality whenapplied after one week of systemic corticosteroid treatment. The study population consisted of 378 patients (pts) with acute GVHD from 11 centers in the Mount Sinai Acute GVHD International Consortium. All pts were treated with systemic steroids and provided a plasma or serum sample obtained after one week of treatment (±3 days). The median starting dose of systemic steroids for Grade II-IV GVHD was 2.0 mg/kg/day and for Grade I was 1.0 mg/kg/day, after which treatment varied. Patients were divided into test (n=236) and validation (n=142) cohorts. We applied the Ann Arbor GVHD algorithm to concentrations of TNFR1, ST2, and REG3α measured after one week of treatment to generate a predicted probability of 6-month NRM, which we term the treatment score (TS). We employed unsupervised k-medoidclustering to partition TS values from the test cohort into two groups (high and low). This unbiased approach identified a high score group made up of 25% of pts (n=58) in the test cohort. We observed that the day 28 response rate (complete, CR + partial, PR) was significantly lower in pts with high scores compared to low scores in the test cohort (24% vs 65%, p<0.0001) (Fig 1A). Analysis of the validation cohort using the same TS definitions showed similar differences in response rates (22% vs 61%, p<0.0001) (Fig 1B). Further, nearly four times as many pts with high scores in both cohorts died within 6 months from non-relapse causes compared to pts with low scores (test: 57% vs 17%, p<0.0001; validation: 57% vs 14%, p<0.0001) (Fig 1C/D). As expected, the majority of non-relapse deaths in pts treated for GVHD were directly attributable to GVHD (test: 95%; validation: 89%). Relapse rates for high and low score pts were similar (data not shown), and thus pts with a high TS experienced significantly worse overall survival in both cohorts (test: 37% vs 72%, p<0.0001; validation: 38% vs 79%, p<0.0001) (Fig 1E/F). Approximately half of the pts in each cohort (test: 48%; validation: 44%) responded (CR+PR) to the first week of steroids and these ptshad significantly lower 6-month NRM than non-responders (NR) (test: 17% vs 36%, p=0.0002; validation: 13% vs 36%, p=0.0014). Yet the TS continued to stratify mortality risk independently of clinical response. In the test cohort, pts with a high score comprised 16% of all early responders and experienced more than twice the NRM of early responders with a low score (33% vs 13%, p=0.022) (Fig 2A). Conversely, test cohort pts who did not respond by day 7, but had a low score, fared much better than non-responders with a high score (NRM 21% vs 68%, p<0.0001) (Fig 2B). Two thirds of early non-responders comprised this more favorable group. These highly significant results reproduced in the independent validation cohort in similar proportions (CR+PR: 45% vs 6%, p=0.0003; NR: 61% vs 22%, p=0.0001) (Fig 2C/D). Finally, a subset analysis revealed that pts classified as NR after one week of steroids due to isolated, yet persistent, grade I skin GVHD (24/378, 6%) overwhelmingly had low treatment scores (22/24, 92%) and experienced rates of NRM (9%) comparable to responders with low scores, thus forming a distinct, albeit small, subset of pts with non-responsive GVHD that fares particularly well (Fig 3). In conclusion, a treatment score based on three GVHD biomarkers measured after one week of steroids stratifies pts into two groups with distinct risks for treatment failure and 6-month NRM. It is particularly noteworthy that the TS identifies two subsets of pts with steroid refractory (SR) GVHD who have highly different outcomes (Fig 2B/D). The much larger group, approximately two thirds of all SR pts, may not need the same degree of treatment escalation as is traditional for clinical non-response, and thus overtreatment might be avoided. Because the TSis measured at a common decision making time point, it may prove useful to guide risk-adapted therapy. Disclosures Mielke: Novartis: Consultancy; MSD: Consultancy, Other: Travel grants; Celgene: Other: Travel grants, Speakers Bureau; Gilead: Other: Travel grants; JAZZ Pharma: Speakers Bureau. Kroeger:Novartis: Honoraria, Research Funding. Chen:Incyte Corporation: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding. Jagasia:Therakos: Consultancy. Kitko:Therakos: Honoraria, Speakers Bureau. Ferrara:Viracor: Patents & Royalties: GVHD biomarker patent. Levine:Viracor: Patents & Royalties: GVHD biomarker patent.

Abstract Background: Chronic GVHD contributes to morbidity and mortality after allogeneic transplantation. Several phase 2 and 3 open label studies suggested that ATLG (formerly referred to as ATG-F) reduces cGVHD without impacting relapse or survival. This report describes the first prospective randomized double blind phase 3 trial to assess the effect of ATLG (Neovii) when added to tacrolimus / methotrexate prophylaxis on cGVHD free survival. Patients and Methods: This study was conducted at 27 sites in the United States and Australia. 260 patients were randomized (132 placebo, 128 ATLG). 6 patients who were randomized never received ATLG/placebo (4 placebo and 2 ATLG). Data presented include the 128 placebo and 126 ATLG patients who underwent treatment and transplant. Patients were ages 18-65 years with a diagnosis of acute myeloid (AML, 64%) or lymphoblastic (ALL, 21%) leukemia in first or subsequent complete remission or myelodysplastic syndrome (MDS, 15%) with less than 10% marrow blasts. Median age was 48 years (18-65) with 55% males. All patients received 8/8 HLA (A, B, C, DR) allele matched unrelated products (80% mobilized peripheral blood, 20% bone marrow). Myeloablative conditioning was with cyclophosphamide and total body irradiation (Cy/TBI, 27%), busulfan and cyclophosphamide (Bu/Cy, 33%), or busulfan and fludarabine (Bu/Flu, 40%). All patients received tacrolimus starting on Day -1 and standard mtx on days 1, 3, 6, and 11 for GVHD prophylaxis. Patients received ATLG or placebo on Days -3, -2, -1 at an ATLG dose of 20 mg/kg per day (60 mg/kg total). The primary endpoint of the study was moderate/severe chronic GVHD free survival. cGVHD was scored by the investigator and then confirmed or overturned by an independent adjudication committee. Secondary endpoints included engraftment, acute GVHD , moderate/severe cGVHD, non-relapse mortality, GVHD and relapse free survival (GRFS), progression free (PFS) and overall survival (OS). The impact of ATLG on immune reconstitution was assessed in 91 patients. Results: Treatment arms were balanced with respect to age, diagnosis, remission status, cytogenetics, graft source (PB or BM), CMV serostatus and conditioning regimen. Median follow up of survivors was 745 days (61, 1425). Regarding the primary endpoint, there was no difference in 2 year moderate/severe cGVHD free survival between ATLG and placebo (48 vs 44%, p = 0.57), nor was there a difference in GRFS (Table 1). Neutrophil engraftment at Day 30 was less in the ATLG arm (85% vs 95%, p=0.00001). Grade 2 or higher infusion reactions were higher in the ATLG arm (16% vs 2.3%, p=0.0001). Reactivation of CMV was similar (27% vs 31%, p=0.58). The Day 180 cumulative incidence of grades 2-4 acute GVHD was lower in the ATLG arm (23 vs 40%, p = 0.003) as was the 2-year cumulative incidence of moderate/severe cGVHD (12 vs 33%, p = 0.000006). However, both 2-year OS and PFS were lower in ATLG treated patients (58 v 76% and 47 vs 67%, respectively) due in part to a higher incidence of relapse (32 vs 19%, p=0.068). Multivariable models confirmed that ATLG was associated with inferior OS, HR 1.85 (1.1-2.9, p=.0075) and PFS, HR 1.63 (1.1-2.41, p=0.015). We then conducted an unplanned post-hoc analysis and discovered a striking influence of conditioning regimen on outcomes. There were no differences in OS or PFS between ATLG and placebo arms in patients receiving Bu/Cy or Bu/Flu but a dramatic difference in patients receiving Cy/TBI conditioning (OS, 88% vs 48% p =0.006 and PFS, 75 vs 29%, p=0.007 in placebo and ATLG arms, respectively). 91 patients (44 ATLG, 47 placebo) participated in the immune reconstitution study. ATLG treatment was associated with lower CD3, CD4, and CD8 counts at Days 30, 100, and 360, respectively. In turn lower CD3, CD4, and CD8 counts assessed as time dependent variables were all associated with inferior OS and PFS as well as higher NRM (data not shown). Conclusion: In this first ever prospective, randomized, double blind trial of ATLG added to tacrolimus /methotrexate in recipients of matched unrelated donor grafts after myeloablative conditioning, there was no significant difference in 2 year moderate/severe cGVHD free survival or GRFS. ATLG did significantly reduce grades 2-4 acute and moderate/severe chronic GVHD. However, overall survival was higher in the placebo arm, driven mainly by patients who received Cy/TBI conditioning. Further analyses are needed to understand the proper role for ATLG in HCT. Disclosures Soiffer: Juno: Membership on an entity's Board of Directors or advisory committees; Kiadis: Membership on an entity's Board of Directors or advisory committees; Jazz Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees. Porter:Genentech: Employment; Novartis: Patents & Royalties, Research Funding. Jagasia:Therakos: Consultancy. Szer:Alnylam: Honoraria, Membership on an entity's Board of Directors or advisory committees; Ra Pharma: Honoraria, Membership on an entity's Board of Directors or advisory committees; Alexion Pharmaceuticals, Inc.: Honoraria, Membership on an entity's Board of Directors or advisory committees. Ritz:Kiadis: Membership on an entity's Board of Directors or advisory committees. Glavin:Neovii Biotech: Employment. Chen:Incyte Corporation: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding.

Abstract No laboratory test can predict non-relapse mortality (NRM) after hematopoietic cellular transplantation (HCT) prior to the onset graft-versus-host disease (GVHD). Recently, we have shown that a signature of three GVHD plasma biomarkers (TNFR1, ST2, and REG3α) can predict response to GVHD therapy and NRM at the onset of clinical GVHD (Levine, Lancet Haem, 2015). Our goal in the current study was to identify a blood biomarker signature that could predict lethal GVHD and six-month NRM well in advance of the onset of GVHD symptoms. Patient samples on day +7 after HCT were obtained from 1,287 patients from 11 HCT centers in the Mount Sinai Acute GVHD International Consortium (MAGIC). Samples from two large centers (n = 929) were combined and randomly assigned to a training set (n = 620) and test set (n = 309). 358 patients from nine others centers constituted an independent validation set. The overall cumulative incidences of 6-month NRM were 11%, 12%, and 13% for the training, test, and validation sets respectively. The incidence of lethal GVHD, defined as death without preceding relapse while under steroid treatment for acute GVHD, were 18%, 24%, and 14% in the same groups, respectively. The median day of GVHD onset was 28 days in the training set and 29 days in the test and validation sets. We measured four GVHD related biomarkers [ST2, REG3α, TNFR1, and IL2Rα] in all samples and used the training set alone to develop competing risks regression models that used all 13 possible combinations of one to four biomarkers to predict 6-month NRM. The best algorithm, which we rigorously confirmed through Monte Carlo cross-validation of 75 different combinations of training sets, included ST2 and REG3α. No combination of one, three, or four biomarkers was superior to the combination of these two biomarkers. The day 7 algorithm identified high risk (HR) and low risk (LR) groups with 6-month NRMs of 28% and 7%, respectively (p<0.001) (Fig 1A). The relapse rates did not differ between risk groups so that overall survival (OS) was 60% for HR and 84% for LR (p<0.001) (Fig 1B). When applied to the test set (Fig 1C/D), the algorithm identified 54/309 (17%) of the patients as HR with an NRM of 33% vs 7% for LR patients (p<0.001) and 6-month OS of 57% and 81% for HR and LR patients, respectively (p<0.001). In the independent validation set (Fig 1 E/F), the algorithm identified 72/358 (20%) of the patients as HR with an NRM of 26% vs 10% for LR patients (p<0.001) and OS of 68% and 85% for HR and LR patients, respectively (p<0.001). High risk patients were three times more likely to die from GVHD than LR patients in each cohort (p<0.001) (Fig 2). The GI tract is the GVHD target organ that is most resistant to treatment and represents a major cause of NRM, and we observed twice as much severe GI GVHD (stage 3 or 4) in HR patients as in LR patients (p<0.001, data not shown). The algorithm successfully separated HR and LR strata for 6 month NRM in several groups with differing risks for GVHD and NRM, including donor type, degree. of HLA-match, age group, and conditioning regimen intensity (Fig 3). In conclusion, we have developed a blood biomarker algorithm that predicts the development of lethal GVHD seven days after HCT, which performed successfully in large multicenter validation sets. The GVH reaction is already in progress by day +7, even though clinical symptoms may not occur until days or weeks later. We speculate that the blood biomarker concentrations at this early time point reflect subclinical GI pathology, a notion that is reinforced by the fact that ST2 and REG3α, the two biomarkers in the algorithm, are closely associated with GI GVHD. The algorithm identified HR and LR strata in several patient groups with different overall risk for lethal GVHD (donor, HLA match, conditioning regimen intensity, age). This day +7 algorithm should prove useful in clinical BMT research by identifying patients at high risk for lethal GVHD who might benefit from aggressive preemptive treatment strategies. Disclosures Chen: Novartis: Research Funding; Incyte Corporation: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Jagasia:Therakos: Consultancy. Kitko:Therakos: Honoraria, Speakers Bureau. Kroeger:Novartis: Honoraria, Research Funding. Levine:Viracor: Patents & Royalties: GVHD biomarkers patent. Ferrara:Viracor: Patents & Royalties: GVHD biomarkers patent.