22 research outputs found

    Immune Senescence and Exhaustion Correlate with Response to Flotetuzumab, an Investigational CD123×CD3 Bispecific Dart® Molecule, in Acute Myeloid Leukemia

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    We have recently shown that bone marrow (BM) RNA profiles stratify patients with acute myeloid leukemia (AML) into immune-infiltrated and immune-depleted subtypes and that type I/II interferon (IFN)-related gene signatures associate with complete response to flotetuzumab (FLZ), an investigational CD123×CD3 bispecific DART molecule. Within the AML tumor microenvironment CD8+ T cells exhibit features of immune exhaustion and senescence (IES). IES are dysfunctional states driven by metabolic alterations in the tumor microenvironment (TME) and emerging targets for cancer immunotherapy. The aim of the current study was to determine whether IES predicts response of relapsed-refractory (R/R) AML to FLZ in the CP-MGD006-01 clinical trial. Based on prior knowledge and gene set enrichment analysis, we derived a 61-gene IES signature score from RNA-sequencing datasets (TCGA and Beat-AML Master Trial; 162 and 281 patients, respectively). The immunotherapy cohort included 139 BM samples from 71 patients with R/R AML treated with FLZ at the RP2D of 500 ng/kg/day (NCT02152956). BM samples were collected at time of study entry (n=71; n=66 with response data) and longitudinally post-cycle (PC)1 (n=40), PC2 (n=18), PC3 and 4 (n=4) and end of treatment (n=6). AML status at study entry was classified as primary induction failure (PIF, defined as lack of response to at least 2 induction treatment cycles), and early (ER) or late relapse (LR), defined as complete remission (CR) of \u3c6-month or ≥6-month duration, respectively. Overall response rate (ORR), collectively complete response, was defined as \u3c5% BM blasts (CR, CRh, CRi or MLFS), and partial response (PR) was defined as \u3e50% decrease or decrease to 5-25% BM blasts. RNAs were profiled on the PanCancer IO 360™ gene expression panel on the nCounter® platform. Formalin-fixed paraffin embedded BM biopsies were profiled using the human IO protein and RNA panels on the GeoMx® digital spatial profiler (DSP). The 61 genes in the IES signature included T/NK-cell markers (granzymes, CD8A, KLRD1, KLRK1), immune checkpoints (ICOS, CTLA4, EOMES), IFNG and IFN-stimulated genes (CXCR6, IFIH1, IL10RA, GBP1), and were enriched in KEGG pathways related to Th1/Th2 differentiation, TCR signaling, cytokine-cytokine receptor interaction, NK-mediated cytotoxicity and CD28 costimulation (false discovery rate\u3c0.001 for all; Fig. 1A). Unsupervised hierarchical clustering of gene expression allowed the identification of BM samples with high, intermediate and low IES scores at time of study enrollment (Fig. 1B). Ninety-five percent (18/19) of patients in the IEShigh cluster had PIF/ER AML, congruent with prior studies showing enhanced immune infiltration and IFN signaling in the TME of patients with PIF. Notably, ORR to FLZ (complete response, n=18 or PR, n=5) were documented in 11/19 (58%), 10/32 (31.2%) and 2/15 (13.3%) of patients in the IEShigh, IESint and IESlow cluster, respectively (Fig. 1B). The IES signature score was significantly higher at baseline in patients who responded to FLZ compared with non-responders (P=0.0052; Fig. 1C). High-dimensional flow cytometry of sequential BM samples collected at time of study entry and PC1 of FLZ showed the on-treatment upregulation on both CD4 and CD8 T cells of early activation markers CD69 and CD38 (but not the late activation marker HLA-DR), as well as immune checkpoints LAG3 and Tim-3, and proliferation marker Ki-67, indicating FLZ-mediated modulation of the immune TME. To determine the variation in co-expression of T-cell markers associated with FLZ treatment, we also measured lymphocytes obtained from 21 BM samples prior to and post-FLZ using an unsupervised multivariate analysis. Qualitative comparisons of the principal component analysis (PCA) showed distinct phenotypic changes in BM samples post-treatment (Fig. 1D). Characterization of BM biopsies using GeoMx DSP showed distinct T-cell clustering in responders (Fig. 1E). PCA showed enhanced CD45, CD3, CD4 and PDL1 in situ RNA/protein expression (fold change 1.96, 2.83, 3.32, 4.7, respectively, P\u3c0.05 for all) at PC1 of FLZ in OR versus non-responders (Fig. 1F). In conclusion, features of IES were associated with response to FLZ. T-cell functional rejuvenation by FLZ could benefit patients with R/R AML by counteracting pre-existing immune dysfunction

    Prophylactic Ruxolitinib for Cytokine Release Syndrome in Relapse/Refractory AML Patients Treated with Flotetuzumab.

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    2817 Prophylactic Ruxolitinib for Cytokine Release Syndrome (CRS) in Relapse/Refractory (R/R) AML Patients Treated with Flotetuzumab Program: Oral and Poster AbstractsSession: 613. Acute Myeloid Leukemia: Clinical Studies: Poster IIIHematology Disease Topics & Pathways:AML, antibodies, Biological, CRS, Adult, Diseases, Therapies, Adverse Events, Biological Processes, Study Population, Myeloid Malignancies, Clinically relevant, TKI Monday, December 7, 2020, 7:00 AM-3:30 PM Geoffrey L Uy, MD1, Michael P. Rettig, PhD2, Stephanie Christ, MS3*, Ibrahim Aldoss, MD4, Michael T. Byrne, DO5, Harry P. Erba, MD, PhD6, Martha L. Arellano, MD7, Matthew C Foster, MD8, John E. Godwin, MD9, Farhad Ravandi, MBBS10, Peter H. Sayre, MD, PhD11, Anjali S Advani, MD12, Matthew J. Wieduwilt, MD, PhD13, Ashkan Emadi, M.D., Ph.D.14, Laura C. Michaelis, MD15, Patrick J. Stiff, MD16, Martin Wermke17*, Norbert Vey, MD18, Patrice Chevalier, MD, PhD19*, Emmanuel Gyan, MD, PhD20, Christian Recher, MD, PhD21, Fabio Ciceri, MD22*, Matteo Giovanni Carrabba, MD23*, Antonio Curti, MD PhD24, Geert Huls, MD, PhD25, Max S. Topp, MD26, Mojca Jongen-Lavrencic, MD, PhD27, John Muth, MS28*, Teia Curtis29*, Mary Beth Collins30*, Erin Timmeny31*, Kuo Guo, MSc32*, Jian Zhao, PhD32*, Kathy Tran28*, Patrick Kaminker, PhD33*, Priyanka Patel, PharmD30*, Ouiam Bakkacha, MD34*, Kenneth Jacobs, MD35*, Maya Kostova, PhD32*, Jennifer Seiler, PhD, RAC30*, Bob Lowenberg, MD, PhD36, Sergio Rutella, MD, PhD, FRCPath37, Roland B. Walter, MD, PhD, MS38, Ezio Bonvini, MD33, Jan K Davidson-Moncada, MD, PhD39 and John F. DiPersio, MD1 1Washington University School of Medicine, Saint Louis, MO2Department of Internal Medicine, Division of Oncology, Washington Univ. School of Med., Saint Louis, MO3Department of Medicine, Division of Oncology, Washington University School of Medicine, Saint Louis, MO4Gehr Family Center for Leukemia Research, City of Hope, Duarte, CA5Department of Medicine, Division of Hematology-Oncology, Vanderbilt University Medical Center, Nashville, TN6University of Alabama at Birmingham, Birmingham, AL7Winship Cancer Institute, Emory University School of Medicine, Atlanta, GA8Lineberger Comprehensive Cancer Center, UNC, Chapel Hill, Chapel Hill, NC9Providence Portland Medical Center, Portland, OR10Department of Leukemia, University of Texas- MD Anderson Cancer Center, Houston, TX11University of California, San Francisco, San Francisco, CA12Cleveland Clinic, Taussig Cancer Institute, Cleveland, OH13Moores Cancer Center, University of California, San Diego, La Jolla, CA14University of Maryland Greenebaum Comprehensive Cancer Center, Baltimore, MD15Division of Hematology/Oncology, Department of Medicine, The Medical College of Wisconsin Inc., Milwaukee, WI16Loyola University Chicago Stritch School of Medicine, Maywood, IL17NCT/UCC Early Clinical Trial Unit, University Hospital Carl Gustav Carus, Dresden, Germany18Hematologie clinique, Institut Paoli Clamettes, Marseille, France19Department of Hematology and Cell Therapy, CHU Nantes, Nantes, France20CHU de Tours - Hôpital Bretonneau, Tours, France21Service d\u27Hématologie, Centre Hospitalier Universitaire de Toulouse, Institut Universitaire du Cancer de Toulouse Oncopole, Toulouse, France22Haematology and BMT Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy23Hematology and Bone Marrow Transplantation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy24Hematology/Oncology L. e A. Seràgnoli , Sant’Orsola-Malpighi University Hospital, Bologna, Bologna, Italy25Department of Hematology, University Medical Center Groningen, Groningen, GZ, Netherlands26Medizinische Klinik Und Poliklinik II, Universitätsklinikum Würzburg, Würzburg, Germany27Erasmus University Medical Center, Rotterdam, Netherlands28MacroGenics, Inc., Rockville, MD29MacroGenics, Inc., Frederick, MD30MacroGenics, Rockville31MacroGenics, Inc., ROCKVILLE, MD32MacroGenics, Rockville, MD33Macrogenics, Rockville, MD34Macrogenics,Inc, ROCKVILLE, MD35MacroGenics, Inc, Rockville, MD36Department of Hematology, Erasmus University Medical Center, Rotterdam, Netherlands37John van Geest Cancer Centre School of Science and Technology, Nottingham Trent University, Nottingham, ENG, United Kingdom38Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA39MacroGenics, Inc., Washington, DC Introduction: CRS is a potentially life-threatening toxicity observed following T cell-redirecting therapies. CRS is associated with elevated cytokines, including IL6, IFNγ, TNFα, IL2 and GM-CSF. Glucocorticosteroids (GC) and the IL6 receptor blocking antibody tocilizumab (TCZ) can reduce CRS severity; however, CRS may still occur and limit the therapeutic window of novel immunotherapeutic agents. Disruption of cytokine signaling via Janus kinase (JAK) pathway interference may represent a complementary approach to blocking CRS. Ruxolitinib (RUX), an oral JAK1/2 inhibitor approved for the treatment of myelofibrosis and polycythemia vera, interferes with signaling of several cytokines, including IFNγ and IL6, via blockade of the JAK/STAT pathway. We hypothesized that RUX may reduce the frequency and severity of CRS in R/R AML patients (pts) undergoing treatment with flotetuzumab (FLZ), an investigational CD123 x CD3 bispecific DART® molecule. Methods: Relapse/refractory (including primary induction failure, early relapse and late relapse) AML pts were included in this study. RUX pts were treated at a single site, Washington University, St. Louis, MO. RUX was dosed at 10 mg or 20mg BID days -1 through 14. Comparator (non-RUX) pts (n=23) were treated at other clinical sites. FLZ was administered at 500 ng/kg/day continuously in 28-day cycles following multi-step lead-in dosing in week 1 of cycle 1. CRS was graded per Lee criteria1. Results: As of July 1st, 2020, 10 R/R AML pts, median age 65 (range 40-82) years, have been enrolled and treated in the RUX cohort (6 at 10mg, 4 at 20 mg of RUX). All pts had non-favorable risk by ELN 2017 criteria (8 adverse and 2 intermediate); 1 (10.0%) pt had secondary AML; pt characteristics in the RUX and non-RUX cohorts were balanced, except for median baseline BM blasts which was higher in non-RUX pts: 15% (range 5-72) vs (40% (range 7-84), RUX and non-RUX pts respectively. Cytokine analysis showed statistically significant (p\u3c0.05) lower levels of IL4, IL12p70, IL13, IL15, IL17A, IFNα2, but higher levels of GM-CSF were measured in RUX vs non-RUX pts, specifically during co-administration with FLZ (Fig. 1). However, incidence and severity of CRS events were similar. In the RUX cohort, 9 (90%) pts experienced mild to moderate (grade ≤ 2; 48.6% of events were grade 1) CRS events whereas no grade ≥ 3 CRS were reported; in the non-RUX cohort, 23 (100%) pts experienced mild to moderate (grade ≤ 2; 73.1% of events were grade 1) CRS events, 1 (4.3%) grade ≥ 3 CRS was reported. Most CRS events occurred in the first 2 weeks of FLZ administration (75% and 92%, respectively). No differences in duration of CRS events were noted. However, more CRS-directed treatment was used in the RUX cohort. Five (50%) pts received a total of 12 doses of TCZ, 1 (10%) pt received GC and 1 (10%) pts received vasopressors in the RUX cohort. In the non-RUX cohort, 5 (21.7%) pts received 8 doses of TCZ, 3 (13.0%) pts received GC and 1 (3.7%) pt received vasopressors. Dose intensity (DI) at FLZ dose of 500 ng/kg/day was comparable, with median DI of 97.6% and 98.0% in RUX and non-RUX cohorts, respectively. Time to first response (TTFR; BM \u3c 5% blasts) and time on treatment (ToT) were similar between both groups. Median TTFR was 1 cycle for both groups (range 1-2 cycles), and median ToT was 1.4 (range 0.9-5.1) and 1.8 (range 1.3-5.1) months, for RUX and non-RUX pts, respectively. Complete response rate (BM \u3c 5% blasts) was similar: 4 (40%) in RUX pts, and 8 (34.8%) in non-RUX pts; 2 RUX (50%) and 5 non-RUX (62.5%) responders transitioned to stem cell transplant. Conclusion: Prophylactic RUX produced a clear difference in cytokine profiles but no discernable improvement in clinical CRS or response rates in FLZ treated patients. A larger study may be required to determine the prophylactic role of RUX in CRS

    Foraging behaviour of mulga birds in Western Australia. II. Community structure and conservation

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    Mulga (Acacia aneura) woodlands dominate much of arid and semiarid Australia. Although mulga woodlands are floristically and structurally diverse, the composition of the mulga avifauna is consistent across the continent, with 50–70% of bird species shared between sites and a high proportion of migratory and nomadic species. A comparison of avian foraging guilds in mulga woodlands in the Murchison and Gascoyne Bioregions of Western Australia with those in the Northern Territory identified nine guilds. All guilds occurred at the three locations studied during wet years. The number of bird species, species’ abundances, and the number of guilds declined on the Western Australian sites when there was less rain. Despite the commonality of guilds and species between sites, there were differences between sites and years in the grouping of species, with many species best associated with two or more guilds. These differences reflected differences between locations and wet and dry years in the food resources available to birds, which affected how species foraged. Particularly noticeable were the differences between sites and years in migratory and nomadic birds, which in Western Australia and the Northern Territory were the most abundant birds during wet conditions, but largely absent when conditions were drier

    Field guides, bird names, and conservation

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    This is an essay that began as a book review. The book reviewed is: ‘The Australian Bird Guide’ by Peter Menkhorst, Danny Rogers, Rohan Clarke, Jeff Davies, Peter Marsack and Kim Franklin, and published in 2017 by CSIRO Publishing, Clayton, Victoria, Australia (paperback, AU$49.95, ISBN 9780643097544). I enjoy reviewing books and particularly enjoyed reading and reviewing this one. I enjoyed it because the illustrations of birds are superb and because the decision of the authors to follow a global list of bird names provided me with an opportunity to once again raise questions about the names given to Australian birds. Thus, the review morphed into an essay: in part an account of my experiences over the past 60 years with field guides, names, and nomenclature, in part a book review, and in part a bit about the conservation of Australia’s birds

    Suicide by population

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    Editoria

    Ecology of honeyeaters (Meliphagidae) in Western Australian eucalypt woodlands I: Resource allocation among species in the Great Western woodland during spring

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    Nectar-feeding birds are commonly the most abundant birds in Australian eucalypt forests and woodlands, where they play a key role as pollinators of native plants. Among the nectar-feeders, honeyeaters (Meliphagidae) are particularly aggressive and may exclude other birds from the habitats they occupy thereby affecting the composition of avian communities and the distribution of species on a landscape scale. Such behaviour has cascading effects on ecosystems, changing the abundances and kinds of planteating arthropods. A comprehensive knowledge of the ecology of honeyeaters is therefore basic to the conservation management of Australia\u27s natural environments. In this paper, we describe the foraging ecology of honeyeaters in the Great Western Woodland (GWW) during the spring comparing the use of resources between species and locations. Species of honeyeaters in the GWW differ morphologically, and in social and dispersive behaviour, but aggregate in multi-species flocks on blossoming eucalypts (Eucalyptus spp.), the main source of nectar.There are differences among the species of honeyeaters in the eucalypts frequented as nectar sources, with these differences reflecting differences among species in habitat Species also differ in foraging manoeuvres (the way food is taken), substrates, and heights, as well as the plant species visited when feeding on foods other than nectar (e.g., lerp, arthropods, and fruit).The use of substrates and foraging manoeuvres differed between locations. Differences in foraging ecology between locations were primarily related to differences in flowering phenology and vegetation structure (e.g, height, type of bark) and floristics, which in turn affected the food resources available to honeyeaters. Our observations support arguments that the long-term conservation of nectar-feeders cannot be achieved by relying on a fragmented system of widely dispersed conservation reserves. This is especially true in an era of accelerated climate change. Instead, a landscape scale, if not a continental scale, approach to ecosystem conservation that emphasizes habitat connectivity is required

    The Role of Connectivity in Australian Conservation

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    The existing system of nature reserves in Australia is inadequate for the long-term conservation and restoration of native biological diversity because it fails to accommodate, among other elements, large scale and long-term ecological processes and change, including physical and biotic transport in the landscape. This paper is an overview of the connectivity elements that inform a scientific framework for significantly improving the prospects for the long-term conservation of Australia's biodiversity. The framework forms the basis for the WildCountry programme. This programme has identified connectivity at landscape, regional and continental scales as a critical component of an effective conservation system. Seven categories of ecological phenomena are reviewed that require landscape permeability and that must be considered when planning for the maintenance of biological diversity and ecological resilience in Australia: (1) trophic relations at regional scales; (2) animal migration, dispersal, and other large scale movements of individuals and propagules; (3) fire and other forms of disturbance at regional scales; (4) climate variability in space and time and human forced rapid climate change; (5) hydroecological relations and flows at all scales; (6) coastal zone fluxes of organisms, matter, and energy; and, (7) spatially-dependent evolutionary processes at all scales. Finally, we mention eight cross-cutting themes that further illuminate the interactions and implications of the seven connectivity-related phenomena for conservation assessment, planning, research, and management, and we suggest how the results might be applied by analysts, planners, scientists, and community conservationists
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