Synergistic intracellular iron chelation combinations: mechanisms and conditions for optimizing iron mobilization

Iron chelators are increasingly combined clinically but the optimal conditions for cellular iron mobilization and mechanisms of interaction are unclear. Speciation plots for iron(III) binding of paired combinations of the licensed iron chelators desferrioxamine (DFO), deferiprone (DFP) and deferasirox (DFX) suggest conditions under which chelators can combine as ‘shuttle’ and ‘sink’ molecules but this approach does not consider their relative access and interaction with cellular iron pools. To address this issue, a sensitive ferrozine‐based detection system for intracellular iron removal from the human hepatocyte cell line (HuH‐7) was developed. Antagonism, synergism or additivity with paired chelator combinations was distinguished using mathematical isobologram analysis over clinically relevant chelator concentrations. All combinations showed synergistic iron mobilization at 8 h with clinically achievable concentrations of sink and shuttle chelators. Greatest synergism was achieved by combining DFP with DFX, where about 60% of mobilized iron was attributable to synergistic interaction. These findings predict that the DFX dose required for a half‐maximum effect can be reduced by 3·8‐fold when only 1 μmol/l DFP is added. Mechanisms for the synergy are suggested by consideration of the iron‐chelate speciation plots together with the size, charge and lipid solubilities for each chelator. Hydroxypyridinones with low lipid solubilities but otherwise similar properties to DFP were used to interrogate the mechanistic interactions of chelator pairs. These studies confirm that synergistic cellular iron mobilization requires one chelator to have the physicochemical properties to enter cells, chelate intracellular iron and subsequently donate iron to a second ‘sink’ chelator

Immunophenotypic analysis of cell cycle status in acute myeloid leukaemia: relationship to cytogenetics, genotype and clinical outcome

Cell cycle status may play an important role in directing patient therapy. We therefore determined the cell cycle status of leukaemic cells by immunophenotypic analysis of bone marrow trephine biopsies from 181 patients with acute myeloid leukaemia (AML) and correlated the results with biological features and clinical outcome. There was considerable heterogeneity between patients. The presenting white cell count significantly correlated with the proportion of non-quiescent cells (P < 0·0001), of cycling cells beyond G1 (P < 0·0001) and the speed of cycling (P < 0·0001). Profiles in acute promyelocytic leukaemia (APL) differed from non-APL and were consistent with more differentiated cells with reduced proliferative potential, but no significant differences were observed between non-APL cytogenetic risk groups. NPM1 mutations but not FLT3 internal tandem duplication (FLT3ITD ) were significantly associated with a higher proportion of cells beyond G1 (P = 0·002) and faster speed of cycling (P = 0·003). Resistance to standard cytosine arabinoside and daunorubicin induction chemotherapy was significantly related to a slower speed of cycling (P = 0·0002), as was a higher relapse rate (P = 0·05), but not with the proportion of non-quiescent cells or actively cycling cells. These results show a link between the cycling speed of AML cells and the response to chemotherapy, and help to identify a group with a very poor prognosis

Luspatercept stimulates erythropoiesis, increases iron utilization, and redistributes body iron in transfusion-dependent thalassemia

Luspatercept, a ligand-trapping fusion protein, binds select TGF-β superfamily ligands implicated in thalassemic erythropoiesis, promoting late-stage erythroid maturation. Luspatercept reduced transfusion burden in the BELIEVE trial (NCT02604433) of 336 adults with transfusion-dependent thalassemia (TDT). Analysis of biomarkers in BELIEVE offers novel physiological and clinical insights into benefits offered by luspatercept. Transfusion iron loading rates decreased 20% by 1.4 g (~7 blood units; median iron loading rate difference: −0.05 ± 0.07 mg Fe/kg/day, p< .0001) and serum ferritin (s-ferritin) decreased 19.2% by 269.3 ± 963.7 μg/L (p < .0001), indicating reduced macrophage iron. However, liver iron content (LIC) did not decrease but showed statistically nonsignificant increases from 5.3 to 6.7 mg/g dw. Erythropoietin, growth differentiation factor 15, soluble transferrin receptor 1 (sTfR1), and reticulocytes rose by 93%, 59%, 66%, and 112%, respectively; accordingly, erythroferrone increased by 51% and hepcidin decreased by 53% (all p < .0001). Decreased transfusion with luspatercept in patients with TDT was associated with increased erythropoietic markers and decreasing hepcidin. Furthermore, s-ferritin reduction associated with increased erythroid iron incorporation (marked by sTfR1) allowed increased erythrocyte marrow output, consequently reducing transfusion needs and enhancing rerouting of hemolysis (heme) iron and non-transferrin-bound iron to the liver. LIC increased in patients with intact spleens, consistent with iron redistribution given the hepcidin reduction. Thus, erythropoietic and hepcidin changes with luspatercept in TDT lower transfusion dependency and may redistribute iron from macrophages to hepatocytes, necessitating the use of concomitant chelator cover for effective iron management

Oral ferroportin inhibitor vamifeport for improving iron homeostasis and erythropoiesis in β-thalassemia: current evidence and future clinical development

Introduction: In β-thalassemia, imbalanced globin synthesis causes reduced red blood cell survival and ineffective erythropoiesis. Suppressed hepcidin levels increase ferroportin-mediated iron transport in enterocytes, causing increased iron absorption and potentially iron overload. Low hepcidin also stimulates ferroportin-mediated iron release from macrophages, increasing transferrin saturation (TSAT), potentially forming non-transferrin-bound iron, which can be toxic. Modulating the hepcidin–ferroportin axis is an attractive strategy to improve ineffective erythropoiesis and limit the potential tissue damage resulting from iron overload. There are no oral β-thalassemia treatments that consistently ameliorate anemia and prevent iron overload. / Areas covered: The preclinical and clinical development of vamifeport (VIT-2763), a novel ferroportin inhibitor, was reviewed. PubMed, EMBASE and ClinicalTrials.gov were searched using the search term ‘VIT-2763ʹ. / Expert opinion: Vamifeport is the first oral ferroportin inhibitor in clinical development. In healthy volunteers, vamifeport had comparable safety to placebo, was well tolerated and rapidly decreased iron levels and reduced TSAT, consistent with observations in preclinical models. Data from ongoing/planned Phase II studies are critical to define its potential in β-thalassemia and other conditions associated with iron overabsorption and/or ineffective erythropoiesis. If vamifeport potentially increases hemoglobin and reduces iron-related parameters, it could be a suitable treatment for non-transfusion-dependent and transfusion-dependent β-thalassemia

Outcome predictors for maternal red blood cell alloimmunisation with anti-K and anti-D managed with intrauterine blood transfusion

Red blood cell (RBC) alloimmunisation with anti-D and anti-K comprise the majority of cases of fetal haemolytic disease requiring intrauterine red cell transfusion (IUT). Few studies have investigated which haematological parameters can predict adverse fetal or neonatal outcomes. The aim of the present study was to identify predictors of adverse outcome, including preterm birth, intrauterine fetal demise (IUFD), neonatal death (NND) and/or neonatal transfusion. We reviewed the records of all pregnancies alloimmunised with anti-K and anti-D, requiring IUT over 27 years at a quaternary fetal centre. We reviewed data for 128 pregnancies in 116 women undergoing 425 IUTs. The median gestational age (GA) at first IUT was significantly earlier for anti-K than for anti-D (24·3 vs. 28·7 weeks, P = 0·004). Women with anti-K required more IUTs than women with anti-D (3·84 vs. 3·12 mean IUTs, P = 0·036) and the fetal haemoglobin (Hb) at first IUT was significantly lower (51.0 vs. 70.5 g/l, P = 0·001). The mean estimated daily decrease in Hb did not differ between the two groups. A greater number of IUTs and a slower daily decrease in Hb (g/l/day) between first and second IUTs were predictive of a longer period in utero. Earlier GA at first IUT and a shorter interval from the first IUT until delivery predicted IUFD/NND. Earlier GA and lower Hb at first IUT significantly predicted need for phototherapy and/or blood product use in the neonate. In the anti-K group, a greater number of IUTs was required in women with a higher titre. Furthermore, the higher the titre, the earlier the GA at which an IUT was required in both groups. The rate of fall in fetal Hb between IUTs decreased, as the number of transfusions increased. Our present study identified pregnancies at considerable risk of an unfavourable outcome with anti-D and anti-K RBC alloimmunisation. Identifying such patients can guide pregnancy management, facilitates patient counselling, and can optimise resource use. Prospective studies can also incorporate these characteristics, in addition to laboratory markers, to further identify and improve the outcomes of these pregnancies

The community ecology perspective of omics data

The measurement of uncharacterized pools of biological molecules through techniques such as metabarcoding, metagenomics, metatranscriptomics, metabolomics, and metaproteomics produces large, multivariate datasets. Analyses of these datasets have successfully been borrowed from community ecology to characterize the molecular diversity of samples (ɑ-diversity) and to assess how these profiles change in response to experimental treatments or across gradients (β-diversity). However, sample preparation and data collection methods generate biases and noise which confound molecular diversity estimates and require special attention. Here, we examine how technical biases and noise that are introduced into multivariate molecular data affect the estimation of the components of diversity (i.e., total number of different molecular species, or entities; total number of molecules; and the abundance distribution of molecular entities). We then explore under which conditions these biases affect the measurement of ɑ- and β-diversity and highlight how novel methods commonly used in community ecology can be adopted to improve the interpretation and integration of multivariate molecular data. Video Abstract

Linking changes in species composition and biomass in a globally distributed grassland experiment

Global change drivers, such as anthropogenic nutrient inputs, are increasing globally. Nutrient deposition simultaneously alters plant biodiversity, species composition and ecosystem processes like aboveground biomass production. These changes are underpinned by species extinction, colonisation and shifting relative abundance. Here, we use the Price equation to quantify and link the contributions of species that are lost, gained or that persist to change in aboveground biomass in 59 experimental grassland sites. Under ambient (control) conditions, compositional and biomass turnover was high, and losses (i.e. local extinctions) were balanced by gains (i.e. colonisation). Under fertilisation, the decline in species richness resulted from increased species loss and decreases in species gained. Biomass increase under fertilisation resulted mostly from species that persist and to a lesser extent from species gained. Drivers of ecological change can interact relatively independently with diversity, composition and ecosystem processes and functions such as aboveground biomass due to the individual contributions of species lost, gained or persisting.EEA Santa CruzFil: Ladouceur, Emma. German Centre for Integrative Biodiversity Research (iDiv); AlemaniaFil: Ladouceur, Emma. Helmholtz Centre for Environmental Research – UFZ. Department of Physiological Diversity; AlemaniaFil: Ladouceur, Emma. University of Leipzig. Department of Biology; AlemaniaFil: Ladouceur, Emma. Martin Luther University Halle-Wittenberg. Institute of Computer Science; AlemaniaFil: Blowes, Shane A. German Centre for Integrative Biodiversity Research (iDiv); AlemaniaFil: Blowes, Shane A. Martin Luther University Halle-Wittenberg. Institute of Computer Science; AlemaniaFil: Chase, Jonathan M. German Centre for Integrative Biodiversity Research (iDiv); AlemaniaFil: Chase, Jonathan M. Martin Luther University Halle-Wittenberg. Institute of Computer Science; AlemaniaFil: Clark, Adam T. German Centre for Integrative Biodiversity Research (iDiv); AlemaniaFil: Clark, Adam T. Helmholtz Centre for Environmental Research – UFZ. Department of Physiological Diversity; AlemaniaFil: Clark, Adam T. Karl-Franzens University of Graz. Institute of Biology; Austria.Fil: Garbowski, Magda. German Centre for Integrative Biodiversity Research (iDiv); AlemaniaFil: Garbowski, Magda. Helmholtz Centre for Environmental Research – UFZ. Department of Physiological Diversity; AlemaniaFil: Alberti, Juan. Universidad Nacional de Mar del Plata. Instituto de Investigaciones Marinas y Costeras. Laboratorio de Ecología. Mar del Plata; Argentina.Fil: Alberti, Juan. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Arnillas, Carlos Alberto. University of Toronto. Department of Physical and Environmental Sciences; Canadá.Fil: Bakker, Jonathan D. University of Washington. School of Environmental and Forest Sciences; Estados UnidosFil: Barrio, Isabel C. Agricultural University of Iceland. Faculty of Environmental and Forest Sciences; IslandiaFil: Bharath, Siddharth. Atria University; India.Fil: Peri, Pablo Luis. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; Argentina.Fil: Peri, Pablo Luis. Universidad Nacional de la Patagonia Austral; Argentina.Fil: Peri, Pablo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Harpole, Stanley. German Centre for Integrative Biodiversity Research (iDiv); AlemaniaFil: Harpole, Stanley. Helmholtz Centre for Environmental Research – UFZ. Department of Physiological Diversity; AlemaniaMartin Luther University Halle-Wittenberg. Institute of Computer Science; Alemani

DNA methylation modifies the association between obesity and survival after breast cancer diagnosis

Mechanisms underlying the poor breast cancer prognosis among obese women are unresolved. DNA methylation levels are linked to obesity and to breast cancer survival. We hypothesized that obesity may work in conjunction with the epigenome to alter prognosis. Using a population-based sample of women diagnosed with first primary breast cancer, we examined modification of the obesity-mortality association by DNA methylation. In-person interviews were conducted approximately 3 months after diagnosis. Weight and height were assessed [to estimate body mass index (BMI)], and blood samples collected. Promoter methylation of 13 breast cancer-related genes was assessed in archived tumor by methylation-specific PCR and Methyl Light. Global methylation in white blood cell DNA was assessed by analysis of long interspersed elements-1 (LINE-1) and with the lumino-metric methylation assay (LUMA). Vital status among 1308 patients (with any methylation biomarker and complete BMI assessment) was determined after approximately 15 years of follow-up (N = 194/441 deaths due to breast cancer-specific/all-cause mortality). We used Cox proportional hazards regression to estimate hazard ratios (HRs) and 95 % confidence intervals (CIs) using two-sided p values of 0.05. Breast cancer-specific mortality was higher among obese (BMI ≥ 30) patients with promoter methylation in APC (HR = 2.47; 95 % CI = 1.43–4.27) and TWIST1 (HR = 4.25; 95 % CI = 1.43–12.70) in breast cancer tissue. Estimates were similar, but less pronounced, for all-cause mortality. Increased all-cause (HR =1.81; 95 % CI = 1.19–2.74) and breast cancer-specific (HR = 2.61; 95 % CI = 1.45–4.69) mortality was observed among obese patients with the lowest LUMA levels. The poor breast cancer prognosis associated with obesity may depend on methylation profiles, which warrants further investigation

Deferasirox (Exjade®) significantly improves cardiac T2* in heavily iron-overloaded patients with β-thalassemia major

Noninvasive measurement of tissue iron levels can be assessed using T2* magnetic resonance imaging (MRI) to identify and monitor patients with iron overload. This study monitored cardiac siderosis using T2* MRI in a cohort of 19 heavily iron-overloaded patients with β-thalassemia major receiving iron chelation therapy with deferasirox over an 18-month period. Overall, deferasirox therapy significantly improved mean ± standard deviation cardiac T2* from a baseline of 17.2 ± 10.8 to 21.5 ± 12.8 ms (+25.0%; P = 0.02). A concomitant reduction in median serum ferritin from a baseline of 5,497 to 4,235 ng/mL (−23.0%; P = 0.001), and mean liver iron concentration from 24.2 ± 9.0 to 17.6 ± 12.9 mg Fe/g dry weight (−27.1%; P = 0.01) was also seen. Improvements were seen in patients with various degrees of cardiac siderosis, including those patients with a baseline cardiac T2* of <10 ms, indicative of high cardiac iron burden. These findings therefore support previous observations that deferasirox is effective in the removal of myocardial iron with concomitant reduction in total body iron