18 research outputs found
Caprolactam production from cylcohexanone oxime under diluted acidic conditions in micellar media
No full textDelftChemTechApplied Science
The mutational landscape and microenvironment in myelodysplastic syndromes with deletion of chromosome 5q
No full textMyelodysplastic Syndromes (MDS) with deletion of chromosome 5q (del(5q) are malignant bone marrow disorders characterized by macrocytic anemia, chronic transfusion dependency and an increased risk of progression to acute myeloid leukemia. A high proportion of patients with lower-risk del(5q) myelodysplastic syndromes will respond to lenalidomide treatment, but more than 40% of patients have progressed to acute leukemia five years after starting treatment. In this thesis, we characterized the rare MDS stem cells and bone marrow microenvironment of low-risk del(5q) MDS and studied whether certain somatic mutations are associated with disease progression.We isolated stem and progenitor cells from lower-risk MDS patients by flow cytometric cell sorting and characterized these populations functionally and molecularly. By fluorescence in situ hybridisation we found the distinct stem and progenitor cells to be clonally involved. This allowed us to determine that the hierarchical organization in del(5q) MDS is similar to that of healthy bone marrow. Exploiting the fact that the vast majority of MDS cases harbour somatic mutations we employed a fate-mapping approach and observed that all somatic mutations found in the bulk bone marrow could be traced back to MDS stem cells. We observed that the del(5q) abnormality preceded the acquisition of additional mutations. Hypothesizing that the acquisition of certain somatic mutations might help explain progression in del(5q) MDS, we used a cohort of 35 longitudinally sampled patients to study whether certain mutations are associated with disease progression. Overall, the mutational landscape in a pure del(5q) cohort differed from low-risk MDS in general. Thirteen patients progressed to high-risk MDS or leukemia at a median of 85 months after diagnosis. We found progression to be associated with the detection of a limited subset of new mutations, i.e., TP53, TET2, and RUNX1. Of nine patients who progressed to AML, all were treated with lenalidomide and 7 were found to have mutations in TP53, which were present in the earliest sample in one case and acquired in the remaining six cases. Importantly, the new mutations were detected well before signs of clinical progression occurred.Whether or not the microenvironment is perturbed or merely a bystander has been a heavily contentious issue in the literature - not only for MDS but for myeloid diseases in general. Comparing gene expression in cultured mesenchymal stromal cells from del(5q) and normal patients demonstrated no significant differences. Bone marrow biopsies in del(5q) MDS patients before and during lenalidomide treatment revealed significantly higher microvessel density (MVD) in del(5q) MDS compared to normal controls. In all patients analyzed, MVD decreased upon lenalidomide treatment, increasing again upon therapeutic failure. Analysis of staining patterns did not reveal quantitative differences in the expression of previously associated MSC markers between del(5q) MDS and normal bone marrow, suggesting that lenalidomide's main therapeutic effect is independent of reshaping the cellular composition of the microenvironment. Furthermore, as abnormal megakaryocytes with hypolobated nuclei constitute one of the hallmarks of del(5q) MDS and as megakaryocytes have recently been implicated as important niche cells in the regulation of HSC, we studied megakaryocytes as a component of the non-mesenchymal niche in MDS. We provide evidence that the pathognomonic hypolobation is directly associated with the clonal del(5q) aberration. Despite lenalidomide leading to complete clinical and cytogenetic responses, the pathognomonic megakaryocytes with hypolobated nuclei persisted in all patients. Our observation of high clonal involvement in MEP suggests that the entire megakaryocytic lineage from HSC to MEP to megakaryocytes might be resistant to treatment with lenalidomide.In aggregate, our findings indicate no major perturbations in the mesenchymal niche. Instead, we find hematopoietic niche cells in the form of megakaryocytes to be treatment-resistant. As HSC continue to acquire somatic mutations, the risk of progression is associated with a limited set of mutations, warranting regular mutational profiling in patients treated with lenalidomide.List of scientific papersI. MYELODYSPLASTIC SYNDROMES ARE PROPAGATED BY RARE AND DISTINCT HUMAN CANCER STEM CELLS IN VIVO. Woll, P.S., Kjällquist, U., Chowdhury, O., Doolittle, H., Wedge, D.C., Thongjuea, S., Erlandsson, R., Ngara, M., Anderson, K., Deng, Q., Mead, A.J., Stenson, L., Giustacchini, A., Duarte, S., Giannoulatou, E., Taylor, S., Karimi, M., Scharenberg, C., Mortera-Blanco, T., Macaulay, I.C., Clark, S.-A., Dybedal, I., Josefsen, D., Fenaux, P., Hokland, P., Holm, M.S., Cazzola, M., Malcovati, L., Tauro, S., Bowen, D., Boultwood, J., Pellagatti, A., Pimanda, J.E., Unnikrishnan, A., Vyas, P., Göhring, G., Schlegelberger, B., Tobiasson, M., Kvalheim, G., Constantinescu, S.N., Nerlov, C., Nilsson, L., Campbell, P.J., Sandberg, R., Papaemmanuil, E., Hellström-Lindberg, E., Linnarsson, S., and Jacobsen, S.E.W. (2014). Cancer Cell. 25, 794–808. https://doi.org/10.1016/j.ccr.2014.03.036 II. PROGRESSION IN PATIENTS WITH LOW- AND INTERMEDIATE-1-RISK DEL(5Q) MYELODYSPLASTIC SYNDROMES IS PREDICTED BY A LIMITED SUBSET OF MUTATIONS. Scharenberg, C., Giai, V., Pellagatti, A., Saft, L., Dimitriou, M., Jansson, M., Jädersten, M., Grandien, A., Douagi, I., Neuberg, D.S., LeBlanc, K., Boultwood, J., Karimi, M., Jacobsen, S.E.W., Woll, P. S., and HellströmLindberg, E. (2017). Haematologica. 102, 498–508. https://doi.org/10.3324/haematol.2016.152025 III. MEGAKARYOCYTES HARBOUR THE DEL(5Q) ABNORMALITY DESPITE COMPLETE CLINICAL AND CYTOGENETIC REMISSION INDUCED BY LENALIDOMIDE TREATMENT. Scharenberg C., Jansson M., Saft L., Hellström-Lindberg E. (2017). British Journal of Haematology. [Accepted] https://doi.org/10.1111/bjh.15094 </p
GA4GH: International policies and standards for data sharing across genomic research and healthcare
No full textThe Global Alliance for Genomics and Health (GA4GH) aims to accelerate biomedical advances by enabling the responsible sharing of clinical and genomic data through both harmonized data aggregation and federated approaches. The decreasing cost of genomic sequencing (along with other genome-wide molecular assays) and increasing evidence of its clinical utility will soon drive the generation of sequence data from tens of millions of humans, with increasing levels of diversity. In this perspective, we present the GA4GH strategies for addressing the major challenges of this data revolution. We describe the GA4GH organization, which is fueled by the development efforts of eight Work Streams and informed by the needs of 24 Driver Projects and other key stakeholders. We present the GA4GH suite of secure, interoperable technical standards and policy frameworks and review the current status of standards, their relevance to key domains of research and clinical care, and future plans of GA4GH. Broad international participation in building, adopting, and deploying GA4GH standards and frameworks will catalyze an unprecedented effort in data sharing that will be critical to advancing genomic medicine and ensuring that all populations can access its benefits.B.P.C. acknowledges funding from Abigail Wexner Research Institute at Nationwide Children’s Hospital; T.H. Nyrönen acknowledges funding from Academy of Finland grant #31996; A.M.-J., K.N., T.F.B., O.M.H., and Z.S. acknowledge funding from Australian Medical Research Future Fund; M.S. acknowledges funding from Biobank Japan; D. Bujold and S.J.M.J. acknowledge funding from Canada Foundation for Innovation; L.J.D. acknowledges funding from Canada Foundation for Innovation Cyber Infrastructure grant #34860; D. Bujold and G.B. acknowledge funding from CANARIE; L.J.D. acknowledges funding from CANARIE Research Data Management contract #RDM-090 (CHORD) and #RDM2-053 (ClinDIG); K.K.-L. acknowledges funding from CanSHARE; T.L.T. acknowledges funding from Chan Zuckerberg Initiative; T. Burdett acknowledges funding from Chan Zuckerberg Initiative grant #2017-171671; D. Bujold, G.B., and L.D.S. acknowledge funding from CIHR; L.J.D. acknowledges funding from CIHR grant #404896; M.J.S.B. acknowledges funding from CIHR grant #SBD-163124; M. Courtot and M. Linden acknowledge funding from CINECA project EU Horizon 2020 grant #825775; D. Bujold and G.B. acknowledge funding from Compute Canada; F.M.-G. acknowledges funding from the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – NFDI 1/1 “GHGA – German Human Genome-Phenome Archive; R.M.H.-S. acknowledges funding from Duke-Margolis Center for Health Policy; S.B. and A.J.B. acknowledge funding from EJP-RD EU Horizon 2020 grant #825575; A. Niewielska, A.K., D.S., G.I.S., J.A.T., J.R., M.A.K., M. Baudis, M. Linden, S.B., S.S., T.H. Nyrönen, and T.M.K. acknowledge funding from ELIXIR; A. Niewielska acknowledges funding from EOSC-Life EU Horizon 2020 grant #824087; J.-P.H. acknowledges funding from ETH Domain Strategic Focal Area “Personalized Health and Related Technologies (PHRT)” grant #2017-201; F.M.-G. acknowledges funding from EUCANCan EU Horizon 2020 grant #825835; B.M.K., D. Bujold, G.B., L.D.S., M.J.S.B., N.S., S.E.W., and Y.J. acknowledge funding from Genome Canada; B.M.K., M.J.S.B., S.E.W., and Y.J. acknowledge funding from Genome Quebec; F.M.-G. acknowledges funding from German Human Genome-Phenome Archive; C. Voisin acknowledges funding from Google; A.J.B. acknowledges funding from Health Data Research UK Substantive Site Award; D.H. acknowledges funding from Howard Hughes Medical Institute; S.B. acknowledges funding from Instituto de Salud Carlos III; S.-S.K. and K.T. acknowledge funding from Japan Agency for Medical Research and Development (AMED); S. Ogishima acknowledges funding from Japan Agency for Medical Research and Development (AMED) grant #20kk0205014h0005; C.Y. and K. Kosaki acknowledge funding from Japan Agency for Medical Research and Development (AMED) grant #JP18kk0205012; GEM Japan acknowledges funding from Japan Agency for Medical Research and Development (AMED) grants #19kk0205014h0004, #20kk0205014h0005, #20kk0205013h0005, #20kk0205012h0005, #20km0405401h0003, and #19km0405001h0104; J.R. acknowledges funding from La Caixa Foundation under project #LCF/PR/GN13/50260009; R.R.F. acknowledges funding from Mayo Clinic Center for Individualized Medicine; Y.J. and S.E.W. acknowledge funding from Ministère de l’Économie et de l’Innovation du Québec for the Can-SHARE Connect Project; S.E.W. and S.O.M.D. acknowledge funding from Ministère de l’Économie et de l’Innovation du Québec for the Can-SHARE grant #141210; M.A.H., M.C.M.-T., J.O.J., H.E.P., and P.N.R. acknowledge funding from Monarch Initiative grant #R24OD011883 and Phenomics First NHGRI grant #1RM1HG010860; A.L.M. and E.B. acknowledge funding from MRC grant #MC_PC_19024; P.T. acknowledges funding from National University of Singapore and Agency for Science, Technology and Research; J.M.C. acknowledges funding from NHGRI; A.H.W. acknowledges funding from NHGRI awards K99HG010157, R00HG010157, and R35HG011949; A.M.-J., K.N., D.P.H., O.M.H., T.F.B., and Z.S. acknowledge funding from NHMRC grants #GNT1113531 and #GNT2000001; D.L.C. acknowledges funding from NHMRC Ideas grant #1188098; A.B.S. acknowledges funding from NHMRC Investigator Fellowship grant #APP177524; J.M.C. and L.D.S. acknowledge funding from NIH; A.A.P. acknowledges funding from NIH Anvil; A.V.S. acknowledges funding from NIH contract #HHSN268201800002I (TOPMed Informatics Research Center); S.U. acknowledges funding from NIH ENCODE grant #UM1HG009443; M.C.M.-T. and M.A.H. acknowledge funding from NIH grant #1U13CA221044; R.J.C. acknowledges funding from NIH grants #1U24HG010262 and #1U2COD023196; M.G. acknowledges funding from NIH grant #R00HG007940; J.B.A., S.L., P.G., E.B., H.L.R., and L.S. acknowledge funding from NIH grant #U24HG011025; K.P.E. acknowledges funding from NIH grant #U2C-RM-160010; J.A.E. acknowledges funding from NIH NCATS grant #U24TR002306; M.M. acknowledges funding from NIH NCI contract #HHSN261201400008c and ID/IQ Agreement #17X146 under contract #HHSN2612015000031 and #75N91019D00024; R.M.C.-D. acknowledges funding from NIH NCI grant #R01CA237118; M. Cline acknowledges funding from NIH NCI grant #U01CA242954; K.P.E. acknowledges funding from NIH NCI ITCR grant #1U24CA231877-01; O.L.G. acknowledges funding from NIH NCI ITCR grant #U24CA237719; R.L.G. acknowledges funding from NIH NCI task order #17X147F10 under contract #HHSN261200800001E; A.F.R. acknowledges funding from NIH NHGRI grant #RM1HG010461; N.M. and L.J.Z. acknowledge funding from NIH NHGRI grant #U24HG006941; R.R.F., T.H. Nelson, L.J.B., and H.L.R. acknowledge funding from NIH NHGRI grant #U41HG006834; B.J.W. acknowledges funding from NIH NHGRI grant #UM1HG009443A; M. Cline acknowledges funding from NIH NHLBI BioData Catalyst Fellowship grant #5118777; M.M. acknowledges funding from NIH NHLBI BioData Catalyst Program grant #1OT3HL142478-01; N.C.S. acknowledges funding from NIH NIGMS grant #R35-GM128636; M.C.M.-T., M.A.H., P.N.R., and R.R.F. acknowledge funding from NIH NLM contract #75N97019P00280; E.B. and A.L.M. acknowledge funding from NIHR; R.G. acknowledges funding from Project Ris3CAT VEIS; S.B. acknowledges funding from RD-Connect, Seventh Framework Program grant #305444; J.K. acknowledges funding from Robertson Foundation; S.B. and A.J.B. acknowledge funding from Solve-RD, EU Horizon 2020 grant #779257; T.S. and S. Oesterle acknowledge funding from Swiss Institute of Bioinformatics (SIB) and Swiss Personalized Health Network (SPHN), supported by the Swiss State Secretariat for Education, Research and Innovation SERI; S.J.M.J. acknowledges funding from Terry Fox Research Institute; A.E.H., M.P.B., M. Cupak, M.F., and J.F. acknowledge funding from the Digital Technology Supercluster; D.F.V. acknowledges funding from the Australian Medical Research Future Fund, as part of the Genomics Health Futures Mission grant #76749; M. Baudis acknowledges funding from the BioMedIT Network project of Swiss Institute of Bioinformatics (SIB) and Swiss Personalized Health Network (SPHN); B.M.K. acknowledges funding from the Canada Research Chair in Law and Medicine and CIHR grant #SBD-163124; D.S., G.I.S., M.A.K., S.B., S.S., and T.H. Nyrönen acknowledge funding from the EU Horizon 2020 Beyond 1 Million Genomes (B1MG) Project grant #951724; P.F., A.D.Y., F.C., H.S., I.U.L., D. Gupta, M. Courtot, S.E.H., T. Burdett, T.M.K., and S.F. acknowledge funding from the European Molecular Biology Laboratory; Y.J. and S.E.W. acknowledge funding from the Government of Canada; P.G. acknowledges funding from the Government of Canada through Genome Canada and the Ontario Genomics Institute (OGI-206); J.Z. acknowledges funding from the Government of Ontario; C.K.Y. acknowledges funding from the Government of Ontario, Canada Foundation for Innovation; C. Viner and M.M.H. acknowledge funding from the Natural Sciences and Engineering Research Council of Canada (grant #RGPIN-2015-03948 to M.M.H. and Alexander Graham Bell Canada Graduate Scholarship to C.V.); K.K.-L. acknowledges funding from the Program for Integrated Database of Clinical and Genomic Information; J.K. acknowledges funding from the Robertson Foundation; D.F.V. acknowledges funding from the Victorian State Government through the Operational Infrastructure Support (OIS) Program; A.M.L., R.N., and H.V.F. acknowledge funding from Wellcome (collaborative award); F.C., H.S., P.F., and S.E.H. acknowledge funding from Wellcome Trust grant #108749/Z/15/Z; A.D.Y., H.S., I.U.L., M. Courtot, H.E.P., P.F., and T.M.K. acknowledge funding from Wellcome Trust grant #201535/Z/16/Z; A.M., J.K.B., R.J.M., R.M.D., and T.M.K. acknowledge funding from Wellcome Trust grant #206194; E.B., P.F., P.G., and S.F. acknowledge funding from Wellcome Trust grant #220544/Z/20/Z; A. Hamosh acknowledges funding from NIH NHGRI grant U41HG006627 and U54HG006542; J.S.H. acknowledges funding from National Taiwan University #91F701-45C and #109T098-02; the work of K.W.R. was supported by the Intramural Research Program of the National Library of Medicine, NIH. For the purpose of open access, the author has applied a CC BY public copyright license to any Author Accepted Manuscript version arising from this submission. H.V.F. acknowledges funding from Wellcome Grant 200990/A/16/Z ‘Designing, developing and delivering integrated foundations for genomic medicine'
Autophagy preserves hematopoietic stem cells by restraining mTORC1-mediated cellular anabolism
No full textAdult stem cells are long-lived and quiescent with unique metabolic requirements. Macroautophagy/autophagy is a fundamental survival mechanism that allows cells to adapt to metabolic changes by degrading and recycling intracellular components. Here we address why autophagy depletion leads to a drastic loss of the stem cell compartment. Using inducible deletion of autophagy specifically in adult hematopoietic stem cells (HSCs) and in mice chimeric for autophagy-deficient and normal HSCs, we demonstrate that the stem cell loss is cell-intrinsic. Mechanistically, autophagy-deficient HSCs showed higher expression of several amino acid transporters (AAT) when compared to autophagy-competent cells, resulting in increased amino acid (AA) uptake. This was followed by sustained mTOR (mammalian target of rapamycin) activation, with enlarged cell size, glucose uptake and translation, which is detrimental to the quiescent HSCs. mTOR inhibition by rapamycin treatment in vivo was able to rescue autophagy-deficient HSC loss and bone marrow failure and resulted in better reconstitution after transplantation. Our results suggest that targeting mTOR may improve aged stem cell function, promote reprogramming and stem cell transplantation
Autophagy limits proliferation and glycolytic metabolism in acute myeloid leukemia.
No full textDecreased autophagy contributes to malignancies, however it is unclear how autophagy impacts on tumour growth. Acute myeloid leukemia (AML) is an ideal model to address this as (i) patient samples are easily accessible, (ii) the hematopoietic stem and progenitor population (HSPC) where transformation occurs is well characterized, and (iii) loss of the key autophagy gene Atg7 in hematopoietic stem and progenitor cells (HSPCs) leads to a lethal pre-leukemic phenotype in mice. Here we demonstrate that loss of Atg5 results in an identical HSPC phenotype as loss of Atg7, confirming a general role for autophagy in HSPC regulation. Compared to more committed/mature hematopoietic cells, healthy human and mouse HSCs displayed enhanced basal autophagic flux, limiting mitochondrial damage and reactive oxygen species in this long-lived population. Taken together, with our previous findings these data are compatible with autophagy limiting leukemic transformation. In line with this, autophagy gene losses are found within chromosomal regions that are commonly deleted in human AML. Moreover, human AML blasts showed reduced expression of autophagy genes, and displayed decreased autophagic flux with accumulation of unhealthy mitochondria indicating that deficient autophagy may be beneficial to human AML. Crucially, heterozygous loss of autophagy in an MLL-ENL model of AML led to increased proliferation in vitro, a glycolytic shift, and more aggressive leukemias in vivo. With autophagy gene losses also identified in multiple other malignancies, these findings point to low autophagy providing a general advantage for tumour growth
Modelling ineffective erythropoiesis in myelodysplastic syndromes with ring sideroblasts
No full textMyelodysplastic syndromes with ring sideroblast (MDS-RS) is a clonal hematological malignancy characterized by accumulation of iron filled erythroblasts called ring sideroblasts in the bone marrow, and recurrent somatic mutations in the splicing factor gene SF3B1. The disease mainly affects elderly individuals, causing severe anemia in patients for which no curative treatment exists. An important requisite to develop new treatments for MDS-RS is to identify the cell population that propagates and sustains the disease clone, as well as its functional downstream effects on erythropoiesis. Modelling the ineffective erythropoiesis of MDS-RS has been problematic both in vitro and in vivo, in particular the generation of ring sideroblasts, which has hampered functional studies of the disease. The focus of this thesis was to determine at which stage of the hematopoietic hierarchy SF3B1 mutations originate in MDS-RS patients, and to provide experimental models recapitulating the disease phenotype, allowing for functional studies and testing of new therapeutic options.In study I we demonstrated that SF3B1 mutations in MDS-RS patients originate in the hematopoietic stem cell (HSC) compartment, before division into the myeloid and lymphoid lineages. We found clonal involvement in B-cell progenitors resulting in a negative effect on lymphoid development. Furthermore, we found that only HSCs and no other investigated progenitor populations isolated from MDS-RS patients could propagate the SF3B1 mutated clone both in vitro and in vivo. Transplantation of HSCs from MDS-RS patients into immunodeficient mice resulted in ring sideroblast formation, providing a novel in vivo model to study the disease. In study II we established a three-dimensional (3D) culture model capable of recapitulating healthy and aberrant terminal erythropoiesis. Suspension cultures of CD34+ progenitor cells from MDS-RS patients had thus far failed to generate mature erythroid cells, including ring sideroblasts. We therefore decided to compare long term cultures of CD34+ cells and mononuclear cells (MNCs) from healthy individuals and MDS-RS patients either in suspension (2D) or in 3D scaffolds that mimic the structure of the bone marrow. We found that the scaffolds provided the CD34+ cells with proliferative advantage and enabled them to preserve their selfrenewal potential. By comparison, the same cells did not survive beyond three weeks in 2D cultures. Additionally, the CD34+ 3D cultures predominantly facilitated erythropoiesis, including enucleation and erythroid island generation. MNC cultures maintained stable proliferation for the four-week culture period, supporting multi-lineage hematopoietic differentiation and cytokine secretion relevant to erythropoiesis and MDS-RS. The CD34+ 3D, MNC 3D and MNC 2D cultures maintained the SF3B1 mutated clone and generated ring sideroblasts de novo from the second week of culture, providing a novel in vitro model to assess therapeutic compounds aiming to alleviate the anemia in MDS-RS patients.In study III we treated primary cells from healthy individuals and MDS-RS patients with luspatercept, a relatively new treatment option for MDS-RS, in the 3D model established in study II. Luspatercept is a transforming growth factor beta family ligand trap that has been shown to alleviate anemia in MDS-RS patients although its mechanism has not been elucidated. We found that luspatercept enhances proliferation and erythroid output of CD34+ cells and MNCs from healthy individuals in vitro, demonstrating that it can have a direct effect on hematopoietic progenitor cells. By contrast, luspatercept had no direct effect on hemopoiesis in the MDS-RS cultures, nor did it inhibit the SF3B1 mutated clone or ring sideroblast generation. This indicates that the drug may not directly target the disease clone although this will have to be confirmed in a larger population of responding patients. Interestingly, we found that luspatercept completely inhibited IL-6 secretion of CD34+ cells from healthy individuals in vitro, indicating that the drug can affect cytokine secretion. Since IL-6 can have a negative effect on erythropoiesis and is upregulated in a proportion of MDS patients it is worth exploring if it is upregulated in MDS-RS patients that respond to the drug.List of scientific papersI. SF3B1-initiating Mutations in MDS-RSs Target Lymphomyeloid Hematopoietic Stem Cells. Mortera-Blanco, T., Dimitriou, M., Woll, P.S., Karimi, M., Elvarsdottir, E., Conte, S., Tobiasson, M., Jansson, M., Douagi, I., Moarii, M., Saft, L., Papaemmanuil, E., Jacobsen, S.E.W., Hellström-Lindberg, E. (2017). Blood. 130(7): 881-890. https://doi.org/10.1182/blood-2017-03-776070 II. A Three-dimensional In Vitro Model of Erythropoiesis Recapitulates Erythroid Failure in Myelodysplastic Syndromes. Elvarsdottir, E., Mortera-Blanco, T., Dimitriou, M., Bouderlique, T., Jansson, M., Hofman, I.J.F., Conte, S., Karimi, M., Sander, B., Douagi, I., Woll, P.S., HellströmLindberg, E. (2019). Leukemia. https://doi.org/10.1038/s41375-019-0532-7 III. In Vitro Effects of Luspatercept on Bone Marrow from Healthy Individuals and Patients with MDS-RS. Elvarsdottir, E., Creignou, M., Mortera-Blanco, T., Hofman, I.J.F., Nikougoftar Zarif, M., Sander, B., Dimitriou, M., Woll, P.S., Hellström-Lindberg, E. [Manuscript]</p
A T cell receptor targeting a recurrent driver mutation in FLT3 mediates elimination of primary human acute myeloid leukemia in vivo
No full text Acute myeloid leukemia (AML), the most frequent leukemia in adults, is driven by recurrent somatically acquired genetic lesions in a restricted number of genes. Treatment with tyrosine kinase inhibitors has demonstrated that targeting of prevalent FMS-related receptor tyrosine kinase 3 (FLT3) gain-of-function mutations can provide significant survival benefits for patients, although the efficacy of FLT3 inhibitors in eliminating FLT3-mutated clones is variable. We identified a T cell receptor (TCR) reactive to the recurrent D835Y driver mutation in the FLT3 tyrosine kinase domain (TCRFLT3D/Y). TCRFLT3D/Y-redirected T cells selectively eliminated primary human AML cells harboring the FLT3D835Y mutation in vitro and in vivo. TCRFLT3D/Y cells rejected both CD34+ and CD34− AML in mice engrafted with primary leukemia from patients, reaching minimal residual disease-negative levels, and eliminated primary CD34+ AML leukemia-propagating cells in vivo. Thus, T cells targeting a single shared mutation can provide efficient immunotherapy toward selective elimination of clonally involved primary AML cells in vivo. Immunobiology of allogeneic stem cell transplantation and immunotherapy of hematological disease
Environmental signals rather than layered ontogeny imprint the function of type 2 conventional dendritic cells in young and adult mice.
No full textConventional dendritic cells (cDC) are key activators of naive T cells, and can be targeted in adults to induce adaptive immunity, but in early life are considered under-developed or functionally immature. Here we show that, in early life, when the immune system develops, cDC2 exhibit a dual hematopoietic origin and, like other myeloid and lymphoid cells, develop in waves. Developmentally distinct cDC2 in early life, despite being distinguishable by fate mapping, are transcriptionally and functionally similar. cDC2 in early and adult life, however, are exposed to distinct cytokine environments that shape their transcriptional profile and alter their ability to sense pathogens, secrete cytokines and polarize T cells. We further show that cDC2 in early life, despite being distinct from cDC2 in adult life, are functionally competent and can induce T cell responses. Our results thus highlight the potential of harnessing cDC2 for boosting immunity in early life
The autophagy protein Atg7 is essential for hematopoietic stem cell maintenance
No full textThe role of autophagy, a lysosomal degradation pathway which prevents cellular damage, in the maintenance of adult mouse hematopoietic stem cells (HSCs) remains unknown. Although normal HSCs sustain life-long hematopoiesis, malignant transformation of HSCs leads to leukemia. Therefore, mechanisms protecting HSCs from cellular damage are essential to prevent hematopoietic malignancies. In this study, we crippled autophagy in HSCs by conditionally deleting the essential autophagy gene Atg7 in the hematopoietic system. This resulted in the loss of normal HSC functions, a severe myeloproliferation, and death of the mice within weeks. The hematopoietic stem and progenitor cell compartment displayed an accumulation of mitochondria and reactive oxygen species, as well as increased proliferation and DNA damage. HSCs within the Lin(-)Sca-1(+)c-Kit(+) (LSK) compartment were significantly reduced. Although the overall LSK compartment was expanded, Atg7-deficient LSK cells failed to reconstitute the hematopoietic system of lethally irradiated mice. Consistent with loss of HSC functions, the production of both lymphoid and myeloid progenitors was impaired in the absence of Atg7. Collectively, these data show that Atg7 is an essential regulator of adult HSC maintenance
Impact of gene dosage, loss of wild-type allele, and FLT3 ligand on Flt3-ITD-induced myeloproliferation.
No full textAcquisition of homozygous activating growth factor receptor mutations might accelerate cancer progression through a simple gene-dosage effect. Internal tandem duplications (ITDs) of FLT3 occur in approximately 25% cases of acute myeloid leukemia and induce ligand-independent constitutive signaling. Homozygous FLT3-ITDs confer an adverse prognosis and are frequently detected at relapse. Using a mouse knockin model of Flt3-internal tandem duplication (Flt3-ITD)-induced myeloproliferation, we herein demonstrate that the enhanced myeloid phenotype and expansion of granulocyte-monocyte and primitive Lin(-)Sca1(+)c-Kit(+) progenitors in Flt3-ITD homozygous mice can in part be mediated through the loss of the second wild-type allele. Further, whereas autocrine FLT3 ligand production has been implicated in FLT3-ITD myeloid malignancies and resistance to FLT3 inhibitors, we demonstrate here that the mouse Flt3(ITD/ITD) myeloid phenotype is FLT3 ligand-independent
