Abstract: Background: Patients (pts) with MDS or AML who relapse after allogeneic transplantation (allo-HCT) have a very poor prognosis. Hypomethylating agents (HMA) and checkpoint blockade with the anti-CTLA4 blocking antibody ipilimumab (IPI) have each induced responses with acceptable toxicity in AML pts who relapse after allo-HCT. We hypothesized that adding decitabine (DAC) would improve response compared with IPI alone by activating and promoting T cell-mediated anti-leukemic immune reactivity. We are conducting a multicenter phase I study (CTEP 10026) of DAC plus IPI in pts with R/R MDS/AML in both post allo-HCT and transplant-naïve settings to assess safety and estimate efficacy. Methods: The primary objective is to determine the maximum tolerated dose (MTD) or RP2D of combination DAC + IPI in pts with R/R MDS/AML who are post allo-HCT (Arm A) or transplant-naïve (Arm B). Cohorts of 3-6 are sequentially enrolled in 3 dose levels (DL) of IPI using a 3+3 design with expansion in each arm; DLs 0-2 are 3, 5 and 10 mg/kg, respectively. Eligibility for both arms: relapsed AML (extramedullary or ≥ 5% blasts) or R/R MDS (≥ 5% blasts) or unfit elderly AML; Arm A only: ≥ 2 wks off systemic immunosuppressive (IS) therapy, T cell chimerism ≥ 20%, and no prior acute GVHD ≥ gr III. DLT is defined as ≥ gr 3 non-heme, ≥ gr 3 acute GVHD or ≥ gr 3 steroid-refractory immune-related adverse events (AEs) occurring within 8 weeks from first IPI dose. Epigenetic priming with DAC lead-in cycle 0 was followed by combination cycles of DAC + IPI. DAC is given at 20 mg/m2 days 1-5 q 28 days. IPI is given on day 1 of cycles 1-4 and every other cycle in cycles 5-12. Pts who discontinued study either in cycle 0 or DLT period without IPI-toxicity were replaced. Arm A opened after safety was confirmed at DL0 in Arm B. Results: As of June 9, 2019, 26 pts (15M, 11 F) have enrolled in this on-going trial. Of the 12 pts (11 AML and 1 MDS) enrolled in Arm A (post allo-HCT), median age was 66.5 (range 29-74) and 9 had previously received HMA. 7 of 8 pts in DL0 (1 progressed in cycle 0) and 3 of 4 pts in DL1 (1 died from pneumonia in cycle 0) received DAC + IPI. DL0 was expanded to 6 to confirm safety without DLT. Median treatment duration after first IPI dose was 5 cycles (range 1-7); 4 pts continue on trial. Common AEs were gr 1-2 dyspnea (n=4), gr 1-3 fatigue (n=4), and gr 1-2 fever (n=4). Gr 3 AEs were febrile neutropenia (n=2), pneumonia (n=1), and candidemia (n=1). Gr 1 immune-related dermatitis (n=1) reversed with steroids. Acute GVHD was not observed. Moderate-severe chronic GVHD was noted in 2 pts mainly involving skin, which was responsive to photopheresis and oral IS. Though 1 CR and 1 marrow CR have been observed at DL0, dose-escalation up to DL2 is on-going to determine MTD. Of the 14 pts (11 AML and 3 MDS) enrolled in Arm B (transplant naïve), median age was 75.5 (range 34-82) and 9 had previously received HMA. 4 of 6 pts in DL0 (1 progressed and 1 withdrew in cycle 0), 3 of 5 pts in DL1 (2 withdrew in cycle 0) and 3 of 3 pts in DL2 received DAC + IPI. Median treatment duration after first IPI dose was 4 cycles (range 1-8); 3 pts remain on study. Common AEs were gr 1-3 fatigue (n=9), gr 1-2 anorexia (n=5), and gr 3 febrile neutropenia (n=8). Immune-related gr 2 colitis (n=1) and gr 2/3 (n=4) dermatitis were all steroid-responsive. Of the 10 pts who received at least one IPI dose, 5 (50%) achieved an objective response including 3 CR, 1 CRi and 1 PR. All responses were observed in AML pts, including 1 with only skin involved. Expansion to confirm MTD is underway. No treatment-related deaths or DLTs were observed in either Arm. Reasons for discontinuation after IPI: progression (n=9), proceeding to allo-HCT or DLI (n=2), withdrawal (n=1), stroke due to underlying atrial fibrillation (n=1) and disseminated nocardiosis (n=1). In both Arms, multiplex immunofluorescence (MIF) staining of BM biopsies revealed a higher density of CD3+CD4+ cells after 4 cycles of DAC + IPI in 4 responders (R) compared to 4 non-responders (NR) (p=0.0433). Longitudinal MIF IHC in an Arm B responder identified the increasing presence of a tumor immune infiltrate composed of CD3+CD8+GZMB+ T cells prior to achieving CR (Fig 1). Conclusions: Combination DAC + IPI is tolerable and has encouraging clinical activity in post allo-HCT and transplant naïve pts with R/R MDS/AML. Ongoing studies focus on comparing the immunologic and genetic characteristics of the tumor immune infiltrate in each cohort to understand the contribution of alloimmunity to treatment response. Disclosures Garcia: Abbvie: Research Funding; Genentech: Research Funding. Keng:agios: Membership on an entity's Board of Directors or advisory committees. Brunner:Jazz Pharma: Membership on an entity's Board of Directors or advisory committees; Forty Seven Inc: Membership on an entity's Board of Directors or advisory committees; Novartis: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Astra Zeneca: Research Funding. Khaled:Omeros: Consultancy; Alexion: Consultancy, Speakers Bureau; Daiichi Sankyo: Other: Travel support. Steensma:H3 Biosciences: Other: Research funding to institution, not investigator.; Arrowhead: Equity Ownership; Onconova: Consultancy; Stemline: Consultancy; Aprea: Research Funding; Pfizer: Consultancy; Summer Road: Consultancy; Astex: Consultancy. Winer:Jazz Pharmaceuticals, Pfizer: Consultancy. Cutler:Omeros: Consultancy; Kadmon: Consultancy; BiolineRx: Other: DSMB; Cellect: Other: DSMB; Kalytera: Other: DSMB; ElsaLys: Consultancy; Genentech: Consultancy; Pharmacyclics: Consultancy; Fate Therapeutics: Consultancy; Incyte: Consultancy; Jazz: Consultancy; BMS: Consultancy. Ho:Omeros Corporation: Membership on an entity's Board of Directors or advisory committees; Jazz Pharmaceuticals: Research Funding; Jazz Pharmaceuticals: Consultancy. Neuberg:Madrigal Pharmaceuticals: Equity Ownership; Pharmacyclics: Research Funding; Celgene: Research Funding. Lindsley:Takeda Pharmaceuticals: Consultancy; Jazz Pharmaceuticals: Research Funding; Medlmmune: Research Funding. Galinsky:ABIM: Other: Member of specialty oncology board; Merus Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; AbbVie Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Pfizer Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees. Ritz:TScan Therapeutics: Consultancy; LifeVault Bio: Consultancy; Kite Pharma: Research Funding; Talaris Therapeutics: Consultancy; Draper Labs: Consultancy; Avrobio: Consultancy; Celgene: Consultancy; Merck: Research Funding; Equillium: Research Funding; Aleta Biotherapeutics: Consultancy. Davids:AbbVie, Acerta Pharma, Adaptive, Biotechnologies, Astra-Zeneca, Genentech, Gilead Sciences, Janssen, Pharmacyclics, TG therapeutics: Membership on an entity's Board of Directors or advisory committees; AbbVie, Astra-Zeneca, Genentech, Janssen, MEI, Pharmacyclics, Syros Pharmaceuticals, Verastem: Consultancy; Acerta Pharma, Ascentage Pharma, Genentech, MEI pharma, Pharmacyclics, Surface Oncology, TG Therapeutics, Verastem: Research Funding; Research to Practice: Honoraria. Wu:Pharmacyclics: Research Funding; Neon Therapeutics: Other: Member, Advisory Board. Stone:AbbVie, Actinium, Agios, Argenx, Arog, Astellas, AstraZeneca, Biolinerx, Celgene, Cornerstone Biopharma, Fujifilm, Jazz Pharmaceuticals, Amgen, Ono, Orsenix, Otsuka, Merck, Novartis, Pfizer, Sumitomo, Trovagene: Consultancy; Argenx, Celgene, Takeda Oncology: Other: Data and Safety Monitoring Board/Committee: ; Novartis, Agios, Arog: Research Funding. DeAngelo:Blueprint: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; Abbvie: Research Funding; Glycomimetics: Research Funding; Amgen, Autolus, Celgene, Forty-seven, Incyte, Jazzs, Pfizer, Shire, Takeda: Consultancy. Soiffer:Jazz: Consultancy; Gilead, Mana therapeutic, Cugene, Jazz: Consultancy; Juno, kiadis: Membership on an entity's Board of Directors or advisory committees, Other: DSMB; Kiadis: Other: supervisory board; Mana therapeutic: Consultancy; Cugene: Consultancy. OffLabel Disclosure: Combination of ipilimumab and decitabine for MDS/AML treatment for patients who are post-transplant or transplant naive

Abstract: Although the GvL effect is the curative basis for allogeneic hematopoietic stem cell transplantation, the key cellular and molecular mechanisms driving GvL sensitivity and resistance remain incompletely understood. Using genomic approaches, we systematically characterized the changes in cellular composition and state of CLL and non-CLL cells in two settings of effective GvL: reduced intensity conditioning regimens (RIC) and donor lymphocyte infusion (DLI). We identified 10 patients with CLL progression after RIC, 6 of whom had complete responses before relapse. To define the evolutionary trajectories of CLL cells after RIC, we generated paired whole-exome sequencing data from pre- and post-RIC CLL cells sorted from PBMCs. We used DNA from autologous CD4+ T cells for germline comparison and the algorithms MuTect2 and ABSOLUTE to identify somatic alterations with corresponding cancer cell fractions (CCFs). 5 of the 10 patients had clonal mutations in TP53 and/or SF3B1 pre-transplant. Mutation burden was higher at baseline than previously described for CLL (mean 29.7 vs 17.9 non-silent SNVs/exome, p 〈 0.0001, Student's t-test) but not different from post-transplant. Neither mutations nor altered expression (based on RNA sequencing) of HLA class 1 or 2, or B2M were observed. 8 relapse pairs exhibited complex branched evolution involving CCF shifts of subclonal and clonal mutations whereas two relapse pairs showed CCF shifts only in subclonal mutations. Presence of clonal shifts associated with active immunity (off immune suppression or presence of chronic graft-vs-host disease; p=0.02, Fisher's exact test), longer time to relapse ( 〉 1 vs 〈 1 year; p=0.02), and achievement of complete response (p=0.05). These data suggest that immune selective pressure by GvL can lead to gain of resistance capability, potentially facilitated by the replacement of dominant clones. We likewise saw diverse clonal trajectories in 2 index cases of DLI response followed by relapse, either 11 [branched evolution] or 1.5 [linear] years after DLI. To deeply examine co-evolution of CLL and immune cells during DLI-relapse, we performed single cell RNA sequencing of both cell types collected from 4 paired PBMC samples representing either pre- or post-(relapsed)-DLI time points. Using the inDrop platform, we profiled a median of 11,686 (range: 9,101-16,756) cells per sample with a median of 5,363 CD19+ CD5+ expressing CLL cells (range: 3,622-9,463). We first sought to define the transcriptional heterogeneity underlying CLL cells during DLI relapse. Data visualization using t-distributed stochastic neighbor embedding plots revealed broad transcriptional shifts in CLL clusters from pre- to post-DLI and also showed the complexity of transcriptional substructure to more closely relate to a patient's own genomic structure rather than a common CLL phenotype, in contrast to prior studies. DLI-relapsed CLL cells in both patients were marked by upregulation of CXCR4 and members of the RhoGTPase family, suggesting migration capacity and cytoskeletal remodeling to play a role in GvL escape. GO term enrichment analysis identified DLI sensitive CLL cells in these cases to associate with regulation of lipid and lipoprotein metabolism and interferon signaling. We then determined parallel changes in PBMC immune states over time, which were subtle and not related to time point. To determine if the leukemic microenvironment can differentially affect immune states, we profiled, in total, 32,777 single bone marrow mononuclear cells (BMMC) from pre-DLI, during DLI response, and post-DLI relapse for one patient. Unlike PBMCs, BMMC-derived T cells clustered preferentially by time point, then state of differentiation. DLI response induced a pronounced shift in all T cell states, reflected by upregulation of NFKB and PI3K-AKT signaling; a dysfunctional state marked by metallothionein family expression, recently discovered in murine single cell studies, was unique to the post-DLI relapse timepoint in this patient. Altogether, these data suggest that GvL selective pressure can shape genetic evolutionary trajectories; scRNA-seq analysis of the 2 informative DLI cases is consistent with the notion that the CLL microenvironment shapes immune states during GvL response and relapse. Ongoing studies will dissect the molecular pathways governing these trajectories to suggest therapeutic strategies for overcoming GvL resistance. Disclosures Brown: Boehringer: Consultancy; Sunesis: Consultancy; Morphosys: Membership on an entity's Board of Directors or advisory committees; Gilead: Consultancy, Research Funding; Invectys: Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy; Verastem: Consultancy, Research Funding; Celgene: Consultancy; Beigene: Membership on an entity's Board of Directors or advisory committees; Genentech: Consultancy; Loxo: Consultancy; TG Therapeutics: Consultancy; Sun Pharmaceutical Industries: Research Funding; Roche/Genentech: Consultancy; Acerta / Astra-Zeneca: Membership on an entity's Board of Directors or advisory committees; Abbvie: Consultancy; Pharmacyclics: Consultancy. Ho:Jazz Pharmaceuticals: Consultancy. Soiffer:Jazz Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees. Wu:Neon Therapeutics: Equity Ownership.

Abstract: Microwave emissions at the L-band (1–2 GHz) in Antarctica are characterized by a significant contribution of ice layers at great depth, from hundreds to a thousand meters. Brightness temperatures, thus, could provide the internal temperature of the ice sheet. However, there are two difficulties to overcome in developing an accurate retrieval algorithm. First, it is difficult to know precisely from which depths waves are emanating because the ice-absorption coefficient is uncertain at the L-band, despite several formulations proposed in the literature over the past few decades. Second, emissivity potentially varies in Antarctica due to remnant scattering in firn (or ice), even at the Brewster angle, and despite the low frequency, limiting the accuracy of the estimate of the physical temperature. Here, we present a retrieval method able to disentangle the absorption and emissivity effects from brightness temperature over the whole continent. We exploit the fact that scattering and absorption are controlled by different physical parameters and phenomena that can be considered as statistically independent. This independence provides a constraint to the retrieval method, that is then well-conditioned and solvable. Our results show that (1) the retrieved absorption agrees with the permittivity model proposed by Mätzler et al. (2006), and (2) emissivity shows significant variations, up to 6% over the continent, which are correlated with wind speed and accumulation patterns. A possible cause of this latter point is density heterogeneity and sastrugi buried in the firn. These two results are an important step forward for the accurate retrieval of internal temperature using low-frequency microwave radiometers.

Abstract: Abstract. In this paper, we present the GRISLI (Grenoble ice sheet and land ice) model in its newest revision (version 2.0). Whilst GRISLI is applicable to any given ice sheet, we focus here on the Antarctic ice sheet because it highlights the importance of grounding line dynamics. Important improvements have been implemented in the model since its original version (Ritz et al., 2001). Notably, GRISLI now includes a basal hydrology model and an explicit flux computation at the grounding line based on the analytical formulations of Schoof (2007) or Tsai et al. (2015). We perform a full calibration of the model based on an ensemble of 300 simulations sampling mechanical parameter space using a Latin hypercube method. Performance of individual members is assessed relative to the deviation from present-day observed Antarctic ice thickness. To assess the ability of the model to simulate grounding line migration, we also present glacial–interglacial ice sheet changes throughout the last 400 kyr using the best ensemble members taking advantage of the capacity of the model to perform multi-millennial long-term integrations. To achieve this goal, we construct a simple climatic perturbation of present-day climate forcing fields based on two climate proxies: atmospheric and oceanic. The model is able to reproduce expected grounding line advances during glacial periods and subsequent retreats during terminations with reasonable glacial–interglacial ice volume changes.