Morris, Lawrence E.

Abstract Despite concerns about the toxicity of allogeneic hematopoietic cell transplantation (alloHCT) in older patients, prospective data characterizing prevalence or risk stratification for geriatric morbidity such as disability or frailty are limited. We prospectively assessed the prognostic impact of the novel composite health assessment risk model (CHARM), a score established to predict 1-year nonrelapse mortality (NRM), among 1105 patients aged ≥60 years enrolled on the Bone Marrow Transplant Clinical Trials Network Study 1704. Secondary end points were assessed post-alloHCT at day 100 (D100), D180, and D365 in multivariable models adjusted with predetermined clinical variables. Among alloHCT survivors, the prevalence of disability by instrumental activities of daily living (IADL), frailty by the Physical Frailty Phenotype, and physical function impairment by Patient Reported Measurement Information System (PROMIS) was highest at D100 and lower on D180 and D365. Higher CHARM scores were independently associated with greater disability (coefficient, −0.64; 95% confidence interval [CI], −0.85 to −0.43; P< .001), increased frailty (coefficient, 0.19; CI, 0.081-0.31; P< .001), worse PROMIS physical function, greater PROMIS depression, increased serious organ toxicity by D100, more cognitive decline at D100, and higher mortality after acute graft-versus-host disease (GVHD) but not significantly associated with PROMIS anxiety or acute GVHD. Higher CHARM scores predicted worse disability-free survival (odds ratio [OR], 2.03; CI, 1.66-2.48; P< .001) and lower frailty-free survival (OR, 2.00; CI, 1.61-2.49). In summary, CHARM is an independent prognostic scoring system not only for NRM but also for geriatric morbidity and functional limitation–free survival through 1 year after alloHCT. Pre-alloHCT CHARM is a novel tool to aid shared decision-making for older patients. This trial was registered at www.clinicaltrials.gov as #NCT03992352.

Abstract Allogeneic hematopoietic cell transplantation (allo-HCT) is potentially curative for older adults with hematologic malignancies. Concerns on nonrelapse mortality (NRM) in older adults limit allo-HCT utilization. We executed a prospective, observational study BMT-CTN 1704 (Blood and Marrow Transplant Clinical Trials Network) enrolling allo-HCT recipients aged ≥60 years from 49 centers in the United States. We analyzed associations between 13 measurements of older adult health and NRM within 1 year to construct a comprehensive health assessment risk model (primary-CHARM) using multivariate Fine-Gray model and grouped penalized variable selection. Two machine learning (ML) models (Cox and pseudo-value boosting) were also explored. Models’ performances were compared using area under the curve (AUC), with bootstrap and cross-validation sampling to correct for optimism, decision curve analysis (DCA), calibration, and Brier scores. Among 1105 patients with median age of 67 (range, 60-82) years who received allo-HCT, NRM was 14.4% and overall survival (OS) 71.7% at 1 year. Factors statistically selected for inclusion in primary-CHARM were higher comorbidity burden, lower albumin, higher C-reactive protein, older age, higher weight-loss percentage, lower patient-reported performance score, and cognitive impairment. Primary-CHARM scores were independently associated with higher NRM (hazard ratio [HR], 2.72; P < .0001) and worse OS (HR, 2.09; P < .0001). Bootstrap bias–corrected AUC for primary-CHARM was 0.591. Comparing primary-CHARM with HCT-comorbidity index and 2 ML-CHARM models, calibration, Brier score, and DCA analysis favored primary-CHARM. Primary-CHARM, with mostly simple and readily available parameters, risk stratifies older adults for allo-HCT. Adopting primary-CHARM in practice may promote broader use of HCT by quantifying risk and enhance the design of strategies to improve outcomes. This trial was registered at www.ClinicalTrials.gov as #NCT03992352.

Introduction: The BMT CTN 1704 study developed and validated the CHARM that stratified risk for non-relapse mortality and overall mortality among older adults, performing better than the HCT-CI alone (Artz A et al, Blood. 2023;142:109) and equally to two machine learning models. CHARM assigns a total score for 7 health variables: increasing age, higher HCT-CI scores, lower albumin, higher C-reactive protein, higher percent of weight loss over the preceding year, lower patient-reported performance status scores, and lower cognitive score per Montreal cognitive assessment (MoCA). A CHARM calculator is available at:https://cibmtr.org/CIBMTR/OffNav/DevSandbox/CHARM-Risk-NRM-Calculator No multi-institutional prospective data exist on functional trajectories and morbidity after HCT in older patients. We now report on the association of CHARM to trajectories of secondary morbidity outcomes among allo-HCT survivors of this large, prospective study. Patients and Methods: Allo-HCT candidates, aged ≥60 years (yrs), were enrolled (n=1226) from 49 centers in the US between 2019 - 2021. The primary analysis includes 1105 patients proceeding to allo-HCT on study and secondary endpoints were assessed at day (D) 100, 180 and 365 except MoCA and organ toxicity were restricted to D100 and frailty had inadequate data for D100. A sequential multiple imputation strategy was implemented to impute endpoints for survivors at each time point with missing data. Analyses on multiply imputed datasets were conducted and the results combined using Rubin's rule. Associations between CHARM scores and secondary outcomes were analyzed using a multivariable Cox, Fine-Gray, Generalized Estimating Equations, and logistic regression model for survival, competing risks, continuous, and binary outcomes, respectively, with latter two focused on surviving patients. Models were adjusted for other variables including conditioning intensity, graft-versus-host disease (GVHD) prophylaxis regimen, disease-risk index, donor-recipient gender match, ethnicity, baseline value of the dependent variable, and visit timepoints. Results: Higher CHARM scores were associated with development of serious organ toxicities by D100 (OR: 2.05, [1.52-2.78], p<0.0001) and ≥2 worsening score on the MoCA (odds ratio (OR) 1.55 [1.16-2.1], p=0.003). Among survivors at all timepoints, higher CHARM scores were associated with greater disability by instrumental activities of daily living (IADL) (Slope -0.640 [-0.433-0.846], p<0.001) and worsening Patient-Reported Outcomes Measurement Reporting System (PROMIS) physical function (Slope -0.981 [-0.057 - -1.904], p=0.037), depression (Slope 0.763 [0.042-1.484], p=0.038) and in a lesser magnitude anxiety (Slope 0.659, p=0.076). Among survivors at D180 and D365, higher CHARM scores were associated with worse frailty (Slope 0.193 [0.081-0.305], p<0.001). CHARM scores were not associated with development of acute GVHD grades 2-4 or 3-4 but were associated with post-GVHD increased mortality (HR: 1.61, [1.25-2.08], p=0.0002). Higher CHARM scores are associated with a lower incidence of chronic GVHD (HR: 0.83, p=0.026), likely due to the effect of CHARM on the competing risk of death leaving fewer patients at risk for chronic GVHD. Conclusions: The novel primary CHARM, originally developed to predict risks of NRM, also predicts worse frailty, disability, cognitive decline, and serious organ toxicities; outcomes that are critically important to older recipients of allo-HCT. CHARM therefore informs risks of transplant morbidity, separate from risks of developing acute GVHD. Results further support adopting CHARM in practice to counsel patients, expedite HCT referrals for lower risk CHARM, and design trials for high CHARM score patients.

Introduction: Allogeneic hematopoietic cell transplantation (HCT) remains the only therapy for long-term disease control for many high-risk hematologic malignancies (HM). HCT use in older HM patients (pts) continues to increase. However, concerns of excessive transplant-related morbidity and non-relapse mortality (NRM) limit referrals and broader application of curative intent HCT. The HCT-comorbidity index (HCT-CI) was initially developed to improve risk-stratification of NRM. More recently, geriatric assessment (GA) and biomarkers have emerged as promising additional tools that may refine estimates of these risks. We hypothesized that a combination of health assessments by GA and biomarkers would constitute a robust and valid model, CHARM, for accurate personalized estimation of one-year (1-yr) NRM. Here, we report the results of the largest, first of its kind, prospective study of older recipients of HCT through the Blood and Marrow Transplant Clinical Trials Network (BMT CTN) 1704 study (NCT03992352). Patients and Methods: Adults aged ≥60 years (yrs) with HM institutionally eligible for HCT were enrolled (n=1226) from 49 centers in the US between 2019 - 2021. Within 21 days of conditioning, 13 prospectively identified older pt.-specific health variables, informed from prior studies, were collected: age, HCT-CI, % of weight loss over the past yr, pt reported Karnofsky performance status, PROMIS physical function scale, instrumental activities of daily living (IADL), number of falls, PROMIS depression scale, number of prescribed medications, 4-meter walk speed, cognition by the Montreal Cognitive Assessment (MoCA), C-reactive protein (CRP) and albumin. The CHARM score to predict NRM within 1 yr was built using a multivariable (MVA) Fine-Gray model, with multiple imputation to handle modest missingness in covariates and grouped penalized variable selection using SCAD to identify variables to retain in the model. Final variables were used as continuous. The model further considered adjustment for conditioning intensity, CMV serostatus, and donor type. Area under the ROC curve (AUC) was calculated to validate the CHARM and compare to HCT-CI alone, with bootstrap sampling to correct for optimism in the within-sample AUC. MVA of overall survival (OS) within 1 yr used the CHARM score and adjusted for other significant variables derived from stepwise regression. Results: The primary analysis included 1105 pts who were confirmed eligible and proceeded to transplant. Median age was 67 (range 60-82) and 32% were ≥ 70 yrs. AML (45%) and MDS (30%) were the most common indications and matched donors the most frequent donor type at 72%. Reduced intensity conditioning with fludarabine (flu)-melphalan (38%) and flu-busulfan (20%) were the most common regimens. Baseline geriatric vulnerabilities among evaluable pts were frequent including slow walk speed (<0.8 meter/second) in 22%, any IADL limitation in 37%, and cognitive impairment (MoCA < 23) in 12%. 1-yr NRM was lower than expected at 14.4% with 1-yr OS of 72%. In the MVA model, albumin, CRP, HCT-CI, and weight loss were independently associated with NRM (Table) and comprised the CHARM. Of note, increasing age did not significantly affect NRM. The CHARM had within sample and bootstrap corrected AUC of 0.641 and 0.607 whereas the HCT-CI alone achieved corresponding AUC values of 0.601 and 0.598. NRM by tertiles is shown in Figure. Each point increase in the CHARM (median -2.2504, range -3.6327 to 0.1381), was associated with a hazard ratio (HR) of 2.83 (95% CI 2.12 - 3.78, p < 0.0001) for NRM. The CHARM also predicted overall mortality within 1-yr with a HR of 2.04 (1.65- 2.53, p <0.0001) per one point increase, independent of the disease risk index, which had a HR of 1.5 (95% CI 1.12 - 1.99, p =0.0059) for high/very high vs low/intermediate categories. Conclusions: We report on the first prospectively established tool, CHARM, to risk-stratify older adult HCT comprised of simple and readily available parameters in transplant and oncology clinics. Adopting CHARM in practice may promote HCT referrals and access for older pts, given low risks of NRM among CHARM lower 2/3 rd tertiles. Identifying high-risk CHARM pts pre-HCT will promote developing novel strategies to reduce NRM. Further analysis of the impacts of the 13 health assessment variables on geriatric morbidity such as disability trajectories is in-process.

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.

PURPOSEStandard cytotoxic induction chemotherapy for acute myeloid leukemia (AML) results in prolonged neutropenia and risk of infection. Romyelocel-L is a universal, allogeneic myeloid progenitor cell product being studied to reduce infection during induction chemotherapy.PATIENTS AND METHODSOne hundred sixty-three patients with de novo AML (age ≥ 55 years) receiving induction chemotherapy were randomly assigned on day 0 (d0), of whom 120 were evaluable. Subjects received either romyelocel-L infusion on d9 with granulocyte colony-stimulating factor (G-CSF) starting daily d14 (treatment group) or G-CSF daily alone on d14 (control) until absolute neutrophil count recovery to 500/µL. End points included days in febrile episode, microbiologically defined infections, clinically diagnosed infection, and days in hospital.RESULTSMean days in febrile episode was shorter in the treatment arm from d15 through d28 (2.36 v 3.90; P = .02). Similarly, a trend toward decreased microbiologically defined infections and clinically diagnosed infection in the treatment arm was observed from d9 to d28 (35.6% v 47.5%; P = .09), reaching a statistically significant difference from d15 to d28 (6.8% v 27.9%; P = .002). Because of this, antibacterial or antifungal use for treatment of an infection was significantly less in the treatment group (d9-d28: 44.1% v 63.9%; P = .01). Significantly fewer patients in the treatment arm received empiric antifungals from d9 tod28 (42.4% v 63.9%; P = .02) and d15-d28 (42.4% v 62.3%; P = .02). Patients in the treatment arm also had 3.2 fewer hospital days compared with control (25.5 v 28.7; P = .001). Remission rates and days to absolute neutrophil count recovery were similar in the two groups. No patients in the romyelocel-L plus G-CSF group died because of infection compared with two patients in the control arm. No graft-versus-host disease was observed.CONCLUSIONSubjects receiving romyelocel-L showed a decreased incidence of infections, antimicrobial use, and hospitalization, suggesting that romyelocel-L may provide a new option to reduce infections in patients with AML undergoing induction therapy.

Abstract T is a Farnesyltransferase inhibitor with clinical activity in elderly adults with newly diagnosed AML who are not candidates for TCC. For adults ≥ age 65 with poor-risk AML, T 600 mg BID for 21 out of every 28–63 days induces complete remissions (CR) in 15%, median duration 7.3 mos, median survival 18 mos. In vitro, T+E exhibits synergistic anti-AML effects. In an attempt to increase CR rates in elderly AML pts, we are conducting a Phase I trial of oral T+E, with escalating doses of both drugs and 14 vs. 21 days of T every 28–63 days (median time to beginning cycle 2 is Day 31, range 29–43). To date, 60 adults ≥ age 70 (median 77, range 71–91) have been treated at 10 dose levels of T (300, 400 or 600 mg BID, 14 or 21 days) + E (100, 150 or 200 mg daily days 1–3 and 8–10) and have received 145 cycles (median 3, range 1–7). A total of 35 (58%) have had secondary AML and 31 (52%) have had adverse cytogenetics. Marrow blast percent was median 55% (range 20–96%), with 75% >30,000 blasts. Nonhematologic toxicities include oropharyngeal mucositis (15% ≥ grade 2), CNS (overall 30%, with 80% of those ≤ grade 2), renal (6%), hyperbilirubinemia (6%), rash (20%) and fatigue (20%). Toxicities occurred across all T+E dose levels tested to date. Documented infections occurred in 16 (27%) pts during cycle 1 and 22/145 (14%) cycles. Twenty six pts (43%) required hospitalization during cycle 1 for median 7 days (range 2–28). Overall hospitalization rate for all cycles was 28% (41/145). Ten pts (17%) died on study: 6 during cycle 1 (4 infection, 1 emphysema, 1 cerebrovascular) and 4 during cycles 2–4 (3 acute myocardial infarctions, 1 ventricular arrhythmia). For 56 evaluable pts, 12 (21%) have achieved CR and 11(20%) have achieved partial remission/hematologic improvement (PR/HI). All pts achieving CR have done so within 2 cycles (9/12 after cycle 1). Eight of 30 pts (27%) receiving T ≥ 400 mg BID have achieved CR. Median age of CR pts is 79 (range 71–86), 8 (67%) have secondary AML, and 5 (42%) have complex cytogenetics. CR durations to date range from 2+ to 13.5+ mos, with median 7+ months. Three of 12 have relapsed at 3, 10, and 11 mos, 2 have been retreated with T+E, and both have achieved 2nd CRs. In sum, the oral regimen of T+E is tolerable and feasible on an outpatient basis for elderly adults with newly diagnosed AML who are not candidates for TCC, with the suggestion of improvement of CR rates over T alone.

Background: The DIAL study is testing the efficacy of dual immunomodulation in patients with advanced aggressive B cell non-Hodgkin lymphoma (B-NHL). Sponsored by the Cancer Therapy Evaluation Program (CTEP), the trial combines the use of a programmed cell death protein 1 (PD-1) inhibitor (nivolumab) with an agonist of the CD27 receptor (varlilumab) in a randomized phase 2 design. CD27, a co-stimulatory receptor, regulates T cell activation in the context of T cell receptor (TCR) engagement through interaction with CD70. T cell exhaustion plays a major role in immune evasion in B-NHL. Varlilumab is an agonistic IgG1 monoclonal antibody that recognizes CD27 leading to prevention or reversal of exhaustion in pre-clinical models. Varlilumab also demonstrates direct anti-tumoral activity in xenograft models of human lymphoma cell lines via antibody-dependent cell-mediated cytotoxicity. Phase 1 data supports the safety and tolerability of single-agent varlilumab in advanced hematologic malignancies (NCT01460134). We hypothesize that CD27 activation synergizes with PD-1 inhibition resulting in a superior anti-lymphoma effect compared to PD-1 blockade alone. The study will also evaluate the effect of these agents on tumor and immune cells using immunohistochemistry (IHC), mass cytometry (CyTOF), multiplex ELISA, imaging mass cytometry (IMC), and whole exome sequencing. Methods: The trial is enrolling patients with advanced aggressive B-NHL. Standard inclusion criteria and prior treatment with at least 2 lines of standard therapy are required. Prior autologous stem cell transplant and/or chimeric antigen receptor (CAR) T cell therapy is allowed. Patients with active CNS disease are excluded. Eligible patients are randomized to treatment with single-agent nivolumab (group 1) or dual immunotherapy with nivolumab and varlilumab. Group 1 is allowed to cross-over at the time of progression. Nivolumab will be administered intravenously (IV) every 2 weeks (240 mg) for 4 months followed by monthly dosing thereafter (480 mg). Varlilumab will be given IV every 4 weeks (3 mg/kg). Response assessment will be done by PET-CT scan every 12 weeks. Primary outcome is overall response rate (ORR) according to the LYRIC criteria. The trial will enroll 48 patients per arm, allowing 80% power to detect at least 20% increase in ORR in the experimental arm (group 2) assuming a 25% ORR in the control arm (group 1). The trial is registered (NCT03038672) and open to participation to members of the Experimental Therapeutics Clinical Trials Network (ETCTN) and Early Drug Development Opportunity Program (EDDOP). Figure Disclosures Tun: BMS: Research Funding; Celgene: Research Funding; Curis: Research Funding; TG Therapeutics: Research Funding; Mundi-pharma: Research Funding; DTRM Biopharma: Research Funding. Bartlett:Pharmacyclics: Research Funding; Merck: Research Funding; Incyte: Research Funding; ADC Therapeutics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Research Funding; Millennium: Research Funding; Kite Pharma: Research Funding; Janssen: Research Funding; Immune Design: Research Funding; Affimed: Research Funding; Autolus: Research Funding; Bristol-Myers Squibb: Research Funding; Celgene: Research Funding; Forty Seven: Research Funding; Genentech, Inc.: Research Funding; Gilead: Research Funding. Kline:Merck: Honoraria; Merck: Research Funding. Awan:Janssen: Consultancy; Gilead: Consultancy; Sunesis: Consultancy; Genentech: Consultancy; Abbvie: Consultancy, Speakers Bureau; Pharmacyclics: Consultancy, Research Funding; AstraZeneca: Consultancy, Speakers Bureau. Lazaryan:Kadmon: Consultancy. Ansell:Affimed: Research Funding; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; Mayo Clinic Rochester: Employment; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Affimed: Research Funding; Affimed: Research Funding; Affimed: Research Funding; LAM Therapeutics: Research Funding; Mayo Clinic Rochester: Employment; LAM Therapeutics: Research Funding; LAM Therapeutics: Research Funding; Seattle Genetics: Research Funding; LAM Therapeutics: Research Funding; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; Trillium: Research Funding; Regeneron: Research Funding; Regeneron: Research Funding; Regeneron: Research Funding; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; Seattle Genetics: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding; LAM Therapeutics: Research Funding; Seattle Genetics: Research Funding; Affimed: Research Funding; Trillium: Research Funding; Trillium: Research Funding; LAM Therapeutics: Research Funding; Trillium: Research Funding; Trillium: Research Funding; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; Mayo Clinic Rochester: Employment; Mayo Clinic Rochester: Employment; Trillium: Research Funding; Seattle Genetics: Research Funding; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Trillium: Research Funding; Mayo Clinic Rochester: Employment; LAM Therapeutics: Research Funding; Trillium: Research Funding; Seattle Genetics: Research Funding; Bristol-Myers Squibb: Research Funding; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; Regeneron: Research Funding; Trillium: Research Funding. Diefenbach:Bristol-Myers Squibb: Consultancy, Research Funding; Denovo: Research Funding; Genentech: Consultancy, Research Funding; Incyte: Research Funding; LAM Therapeutics: Research Funding; MEI: Research Funding; Merck: Consultancy, Research Funding; Seattle Genetics: Consultancy, Research Funding; Millenium/Takeda: Research Funding; Trillium: Research Funding.

Introduction. Our previous flow cytometry-based comparison of HIV(+) and HIV(-) autologous hematopoietic stem cell transplant (auto-HSCT) recipient immunomes at 56, 180 and 365 days post-transplant to each other and to healthy controls (HCs) showed that both sets of auto-HSCT recipient immunomes approached HCs over time, but retained significant differences. HIV(+), but not HIV(-), auto-AHCT recipients retained pro-inflammatory features consistent with chronic HIV infection. Here, we report the results of a quantitative and functional analysis of immune reconstitution in HIV(+) patients treated with allogeneic hematopoietic stem cell transplant (allo-HSCT), in comparison with HIV(+) auto-HSCT recipients and HCs. Methods. Blood samples were collected for analysis at days 56, 180 and 365 post-transplant from HIV(+) transplant recipients and at 1 time point from HCs. Whole blood analysis was performed by five-color flow cytometry across 100 immune marker combinations. Comparisons were made between HIV(+) allo-HSCT recipients (n=17, acute myeloid leukemia, acute lymphocytic leukemia, myelodysplastic syndrome, Hodgkin and non-Hodgkin lymphoma that received myeloablative or reduced intensity conditioning on the BMT-CTN-0903/AMC-080 trial), HIV(+) auto-HSCT recipients (n=36, aggressive B cell non-Hodgkin lymphoma or Hodgkin lymphoma that received myeloablative conditioning on the BMT-CTN-0803/AMC-071 trial) and 71 HCs. Unsupervised principal component analysis (PCA) examined differences in immune cell proportions, identified by flow cytometry across 100 cell subsets at each time point. Wilcoxon rank-sum tests compared median absolute counts and median proportions of cell subsets. An independent feature importance score analysis (FIS) identified contributions of immune cell populations expressing specific immune marker combinations to the differences between HIV(+) auto-HSCT recipients, HIV(+) allo-HSCT recipients and HCs. Functional responsiveness of HIV(+) allo-HSCT recipients' T cells to stimulation with CD3- and CD28-directed antibodies, NK cells to stimulation with IL-12 and IL-18 and monocytes to stimulation with lipopolysaccharide (LPS) was assessed in a preliminary mass cytometry on peripheral blood mononuclear cells isolated at the same time points (n=2) and compared to HCs (n=2). Results. PCA showed that immunomes of HIV(+) allo-HSCT recipients and HIV(+) auto-HSCT recipients clustered together with each other, but away from HCs at all time points throughout the post-transplant year. FIS identified: 1) 13 cell subsets that defined the difference between HIV(+) allo-HSCT recipients (all visits) and HCs, and 2) 11 immune cell subsets that defined the difference between HIV(+) auto-HSCT recipients (all visits) and HCs; in both of these comparisons, activated CD3+/HLA-DR+ T cells had the greatest impact on the difference between HIV(+) and HC immunomes. At 1 year, both HIV(+) transplant recipient cohorts had higher absolute numbers of activated T cells, effector T cells and CD8+ T cells than HCs (Wilcoxon rank-sum test, p<0.0031). HIV(+) autologous and allogeneic HSCT recipients also had lower numbers of CD4+ T cells, naïve T cells and activated NK cells compared to HCs (p<0.0031). FIS also identified 20 immune cell subsets that defined the difference between HIV(+) autologous and allogeneic HSCT recipients immunomes at 1 year, with CD8+/CD27- effector T cell subset exerting the highest impact on the difference. Preliminary functional mass cytometry analysis of 2 HIV(+) allo-HSCT recipients and 2 HCs showed that: 1) IFNʏ production by CD8+ T cells was increased above that of HCs at all time points. 2) Expanded populations of CD4+/T-bet+ cytotoxic cells expressing granzyme B and perforin, and CD8+ cytotoxic T cells expressing granzyme B and perforin, persisted in HIV(+) allo-HSCT recipients at all time points, but not in HCs. 3) NK cells retained an ability to produce IFNʏ in response to stimulation with IL-12 and IL-18 in HIV(+) allo-SCT recipients. 4) Monocytes showed an enhanced production of TNFα in response to stimulation with LPS in HIV(+) allo-HSCT recipients compared to HCs at 1 year post-HSCT. Conclusion. Chronic HIV infection confers the pro-inflammatory immune features on the phenotypic and functional profiling of the T lymphocyte immunome of stem cell transplant recipients, irrespective of allogeneic or autologous stem cell donor source. Disclosures Devine: Bristol Myers: Other: Grant for monitoring support & travel support; Kiadis Pharma: Other: Protocol development (via institution); Magenta Therapeutics: Other: Travel support for advisory board; My employer (National Marrow Donor Program) has equity interest in Magenta. Noy:Janssen: Consultancy; Medscape: Honoraria; Prime Oncology: Honoraria; NIH: Research Funding; Pharamcyclics: Research Funding; Raphael Pharma: Research Funding. Popat:Bayer: Research Funding; Incyte: Research Funding; Jazz: Consultancy. Hofmeister:Celgene: Honoraria; Janssen: Membership on an entity's Board of Directors or advisory committees; Nektar: Honoraria, Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Imbrium: Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Membership on an entity's Board of Directors or advisory committees. Navarro:Atara Biotherapeutics: Employment, Equity Ownership. Behbehani:Fluidigm corporation: Other: Travel funding. Lozanski:Boehringer Ingelheim: Research Funding; Beckman Coulter: Research Funding; Stemline Therapeutics Inc.: Research Funding; Genentec: Research Funding. Baiocchi:Prelude: Consultancy.

Abstract Background: Cytosine arabinoside (ara-C) remains the backbone of most regimens for the treatment of AML. The incorporation of ara-C into DNA activates checkpoint kinase 1 (Chk1) causing replication fork slowing, the accumulation of cells in S phase, and diminished ara-C cytotoxicity. The selective Chk1 inhibitor MK-8776 abrogates ara-C-induced S-phase arrest, thereby enhancing ara-C-induced apoptosis in vitro.1 A phase I trial demonstrated the safety of MK-8876 in combination with infusional ara-C and correlative studies demonstrated increased ara-C-induced H2Ax phosphorylation in AML cells, consistent with unrepaired DNA damage.2 Herein, we report data from a phase II trial comparing ara-C plus MK8876 with ara-C alone. Methods: Patients with relapsed or refractory AML were randomized to receive either ara-C 2 gm/m2 via continuous infusion (CIV) over 72 hours on days 1 and 10 with MK-8776 100 mg flat dose infused over 30 minutes on days 2, 3, 11, and 12 (combo); or ara-C alone on the same schedule (control). The primary end point was response rate (CR+CRi). Adverse events (AEs) for all patients were reported according to the NCI-CTCAE version 4.0. Correlative studies were performed on blood and marrow samples collected prior to treatment on days 1, 2 and 3 and at one hour after MK-8776 infusion (PB only). Marrow and circulating blasts were analyzed using semi-quantitative flow cytometric determinations of blast cell gH2AX expression, a marker of DNA damage. Results: Thirty-two patients were treated at 4 sites with 14 assigned to the combo arm and 18 to the control arm. The study was stopped early due to lack of drug availability. The median age was 60 (range 29-72) and 17 (53%) were male. Nine (28%) had refractory AML, 16 (50%) were in first relapse, and 7 (22%) were in second relapse. Eleven (34%) had undergone a prior bone marrow transplant (BMT). Risk stratification classified 1 (3%) patient as favorable risk disease, 11 (34%) as intermediate-1, 8 (25%) as intermediate-2, and 11 (34%) as adverse risk. There were 5 (36%) responses (CR/CRi) and 1 (7%) partial response (PR) in the combo arm, and 8 (44%) responses and 1 (6%) PR in the control arm. Median survival did not differ significantly between the two groups (5.9 months in the combo arm vs. 4.2 months in the control arm). Sub-group analysis showed increased responses in the combo arm for the patients in first relapse (50% vs. 40%) and those with a prior BMT (50% vs. 29%). Most non-hematologic grade 3/4 treatment-related AEs were similar in the two groups including febrile neutropenia (64% vs. 61%), infectious complications (50% vs. 50%), and sepsis (21% vs. 17%). Patients in the combo arm experienced more QT prolongation (21% vs. 0%), hypertension (21% vs. 0%), and GI toxicities (21% vs. 0%); while those in the control arm had increased renal (0% vs. 11%) and liver toxicity (7% vs. 17%). Two deaths were attributed to treatment, and both were in the control arm. Eight combo patients had serial PB samples and 2 had serial marrow samples studied by flow cytometry. There was an increase in the percentage of gH2AX+ CD34+ cells on Day 2 directly after MK-8876 infusion (16.9% prior and 36.4% at one hour), which occurred to a lesser extent on Day 3 after MK-8876 infusion (12.7% prior and 15.6% at one hour). Three of eight patients demonstrated a sustained increase in gH2AX+ CD34+ from Day 2 to Day 3, and all three achieved either a PR or CR. Conclusion: This is the first phase II study building on prior work suggesting that inhibition of Chk1 would increase response to ara-C in patients with relapsed or refractory AML. The study confirmed that treatment with the combination is feasible with similar toxicities between the treatment and control groups. The response rates were similar between the two groups with improved responses in patients receiving the combo in first relapse and following BMT. Correlative studies support the finding that responding patients show a sustained increase in DNA damage and this may serve as a biomarker in future studies. Chk1 remains a potential target to improve treatment outcomes with ara-C. References: 1. Schenk EL et al. Clin Cancer Res. 2012 Oct 1; 18(19):5364-73. 2. Karp JE et al. Clin Cancer Res. 2012 Dec 15; 18(24):6723-31. Disclosures No relevant conflicts of interest to declare.