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Généralités sur les SMD Pierre FENAUX, Hopital St Louis Université Paris 7 et GFM 2015

Généralités sur les SMD - OVHcluster013.ovh.net/~aihemato/AIH/documents/DES231015/Generalites... · Généralités sur les SMD Pierre FENAUX, Hopital St Louis Université Paris

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Page 1: Généralités sur les SMD - OVHcluster013.ovh.net/~aihemato/AIH/documents/DES231015/Generalites... · Généralités sur les SMD Pierre FENAUX, Hopital St Louis Université Paris

Généralités sur les SMD

Pierre FENAUX, Hopital St Louis Université Paris 7 et GFM

2015

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SMD: généralités

Hémopathies clonales des cellules souches hématopoiétiques caractérisées par: • une hématopoièse inefficace, avec des cytopénies contrastant avec une moelle riche • 1/3 d’évolution en LAM • Maladie du sujet agé (médiane d’âge 65 -70 ans)

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SMD  •  Épidémiologie  

•  Physiopathologie  

•  Diagnos4c  

•  Classifica4on  et  pronos4c  

•  Traitement  

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SMD  •  Épidémiologie  

•  Physiopathologie  

•  Diagnos4c  

•  Classifica4on  et  pronos4c  

•  Traitement  

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Incidence and prevalence of myelodysplastic syndromes: Düsseldorf MDS-registry.

(Neukirchen J, 2011 ))

incidence rate 4.15/100,000/year point prevalence 7 per 100,000 persons

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SMD: épidémiologie Cause généralement inconnue, sauf: -Maladies constitutionnelles: trisomie 21, Fanconi, neurofibromatose -Expositions : chimio (alkylants, analogues de purines), conditionnements d’autogreffe,radiothérapie, benzène -association à des pathologies immunologiques

Polychondrite atrophiante Vascularites Arthrites séro négatives Maladie de Crohn, Behcet

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Mutations prédisposant aux SMD /LAM

•  Fanconi anemia (FAN…) •  Bloom’s syndrome (BLM) •  Telomerase complex genes (TERT, TERC,DKC1) •  Schwachman –Diamond syndrome (SBDS) •  RUNX 1/ AML 1 gene (FPD)* •  TP 53 gene (Li Fraumeni)* •  CEBPa gene* •  GATA 2 gene* •  DDX41 gene •  G-CSF R Glu785Lys mutation

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SMD  •  Épidémiologie  

•  Physiopathologie  

•  Diagnos4c  

•  Classifica4on  et  pronos4c  

•  Traitement  

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Mécanismes physiopathologiques dans les SMD

Tefferi A, Vardiman J. N Engl J Med 2009;361:1872-1885

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Physiopathologie des SMD

•  Apoptose accrue •  Anomalies Cytogénétiques •  Anomalies Epigenetiques •  Anomalies Moléculaires •  Anomalies immunologiques •  Anomalies du microenvironment

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Haase, D. et al. Blood 2007;110:4385-4395

Figure 1 Frequencies of most common cytogenetic anomalies subdivided into isolated, with 1 additional anomaly, and complex anomalies

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MDS versus de novo AML

14 MDS 15 de novo AML

Figueroa M, Blood 2009

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© 2013 Macmillan Publishers Limited. All rights reserved.

•  944 patients 104 genes •  89.5% had at least one mutation (median, 3 per patient; range, 0-12). •  47 genes significantly mutated •  TET2, SF3B1, ASXL1, SRSF2, DNMT3A, and RUNX1 mutated in >10% of

cases.

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Mutations somatiques et SMD

•  Gènes impliqués dans l’épigénétique: ASXL1,TET2, DNMT3a

•  Gènes d’épissage: SF3B1, SRSF2

•  Gènes facteurs de transcription: RUNX 1, TP 53

•  Gènes rarement mutés : JAK 2, CAL R, MPL,FLT3-ITD, NPM1

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Mutations du complexe d’épissage

« autres SMD »  

Frequen Mutations

FAV RARS and RARS-T +++

UNFAV CMML +++ U2AF1

Reproduit d’après Abdel-Wahab et al. Cancer Cell 2008

Rare Mutations

Other MDS

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Cancer Cell

Article

Mutant U2AF1 Expression Alters Hematopoiesisand Pre-mRNA Splicing In VivoCara Lunn Shirai,1 James N. Ley,1 Brian S. White,1,2 Sanghyun Kim,1 Justin Tibbitts,1 Jin Shao,1 Matthew Ndonwi,1

Brian Wadugu,1 Eric J. Duncavage,3 Theresa Okeyo-Owuor,1 Tuoen Liu,1 Malachi Griffith,2 Sean McGrath,2

Vincent Magrini,2 Robert S. Fulton,2 Catrina Fronick,2 Michelle O’Laughlin,2 Timothy A. Graubert,4

and Matthew J. Walter1,*1Division of Oncology, Department of Medicine, Washington University, St. Louis, MO 63110, USA2The Genome Institute, Washington University, St. Louis, MO 63110, USA3Department of Pathology and Immunology, Washington University, St. Louis, MO 63110, USA4Massachusetts General Hospital/Harvard Medical School, Boston, MA 02114, USA*Correspondence: [email protected]://dx.doi.org/10.1016/j.ccell.2015.04.008

SUMMARY

Heterozygous somatic mutations in the spliceosome gene U2AF1 occur in !11% of patients with myelodys-plastic syndromes (MDS), the most common adult myeloid malignancy. It is unclear how these mutationscontribute to disease. We examined in vivo hematopoietic consequences of the most common U2AF1mutation using a doxycycline-inducible transgenic mouse model. Mice expressing mutant U2AF1(S34F)display altered hematopoiesis and changes in pre-mRNA splicing in hematopoietic progenitor cells by wholetranscriptome analysis (RNA-seq). Integration with human RNA-seq datasets determined that commonmutant U2AF1-induced splicing alterations are enriched in RNA processing genes, ribosomal genes, andrecurrently mutatedMDS and acutemyeloid leukemia-associated genes. These findings support the hypoth-esis that mutant U2AF1 alters downstream gene isoform expression, thereby contributing to abnormal hema-topoiesis in patients with MDS.

INTRODUCTION

Myelodysplastic syndromes (MDS) are the most commonmyeloid malignancy of the elderly, with approximately 10,000new cases occurring in the United States annually (Ma, 2012).MDS are a heterogeneous group of clonal hematopoietic stemcell disorders characterized by peripheral blood cytopenias,with up to 30% of patients experiencing progression to second-ary acutemyeloid leukemia (AML) (Troy et al., 2014). Mutations inspliceosome genes have been identified in over half of MDS pa-tient bonemarrow samples, making it the most common class ofgenes mutated in MDS (Damm et al., 2012; Graubert et al., 2012;Papaemmanuil et al., 2011; Thol et al., 2012; Visconte et al.,2012; Walter et al., 2013; Yoshida et al., 2011). The recurrently-

mutated spliceosome genes encode factors that are involvedin the recognition of the 30-intronic splice site and are mutuallyexclusive of one another in patient samples (Haferlach et al.,2014; Papaemmanuil et al., 2013; Walter et al., 2013; Yoshidaet al., 2011), implying that they may contribute similarly to MDSpathogenesis or, alternatively, may not be tolerated by a cellwhen they co-occur.Our group and others identified mutations in U2AF1 (U2 small

nuclear RNA auxiliary factor 1) in 11% of patients with MDS,making it one of the most commonly mutated genes in thisdisease (Graubert et al., 2012; Yoshida et al., 2011). In addition,U2AF1mutations typically occur in the founding clone, suggest-ing they may play an important role in disease initiation (Hafer-lach et al., 2014; Papaemmanuil et al., 2013; Walter et al.,

Significance

Mutations in spliceosome genes occur in up to !50% of patients with myelodysplastic syndromes (MDS), suggesting thatperturbations in pre-mRNA splicing contribute to disease pathogenesis. We generated amurinemodel of themost commonmutation in the spliceosome gene U2AF1 and observed hematopoietic phenotypes and pre-mRNA splicing alterations thatalso occur in patients with MDS or acute myeloid leukemia. Concordant changes in isoform expression of RNA processinggenes, ribosomal genes, and recurrently mutated genes in myeloid cancers in the mouse and human highlight cellular pro-cesses and pathways that may functionally contribute tomutant U2AF1-associated diseases. Determining whether splicingchanges in the same genes are induced by other MDS-associated spliceosome gene mutations may further prioritize keytarget genes in MDS.

Cancer Cell 27, 631–643, May 11, 2015 ª2015 Elsevier Inc. 631

Cancer Cell

Article

SRSF2 Mutations Contribute to Myelodysplasiaby Mutant-Specific Effects on Exon RecognitionEunheeKim,1,16 JanineO. Ilagan,2,3,16 Yang Liang,4,16 GerritM. Daubner,5,16 Stanley C.-W. Lee,1 Aravind Ramakrishnan,6,7

Yue Li,8 YoungRockChung,1 Jean-BaptisteMicol,1Michele E.Murphy,6 HanaCho,1Min-KyungKim,1 AhmadS. Zebari,2,3

Shlomzion Aumann,1 Christopher Y. Park,1,9 Silvia Buonamici,10 Peter G. Smith,10 H. Joachim Deeg,6,7 Camille Lobry,11,12

Iannis Aifantis,13 Yorgo Modis,8,14 Frederic H.-T. Allain,5 Stephanie Halene,4,17 Robert K. Bradley,2,3,17,*and Omar Abdel-Wahab1,15,17,*1Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA2Computational Biology Program, Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA3Basic Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA4Hematology, Yale Comprehensive Cancer Center and Department of Internal Medicine, Yale University School of Medicine, New Haven, CT06520, USA5Institute for Molecular Biology and Biophysics, ETH, 8093 Zurich, Switzerland6Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA7Division of Medical Oncology, School of Medicine, University of Washington, Seattle, WA 98109, USA8Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA9Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA10H3 Biomedicine, Cambridge, MA 03129, USA11Institut National de la Sante et de la Recherche Medicale (INSERM) U1009, Institut Gustave Roussy, 94805 Villejuif, France12Universite Paris-Sud, 91400 Orsay, France13Howard Hughes Medical Institute and Department of Pathology, New York University School of Medicine, New York, NY 10016, USA14Department of Medicine, University of Cambridge, MRC Laboratory of Molecular Biology, Cambridge CB2 0QH, UK15Leukemia Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA16Co-first author17Co-senior author*Correspondence: [email protected] (R.K.B.), [email protected] (O.A.-W.)http://dx.doi.org/10.1016/j.ccell.2015.04.006

SUMMARY

Mutations affecting spliceosomal proteins are the most common mutations in patients with myelodysplasticsyndromes (MDS), but their role inMDS pathogenesis has not been delineated. Herewe report that mutationsaffecting the splicing factor SRSF2 directly impair hematopoietic differentiation in vivo, which is not due toSRSF2 loss of function. By contrast, SRSF2mutations alter SRSF2’s normal sequence-specific RNA bindingactivity, thereby altering the recognition of specific exonic splicing enhancer motifs to drive recurrent mis-splicing of key hematopoietic regulators. This includes SRSF2 mutation-dependent splicing of EZH2, whichtriggers nonsense-mediated decay, which, in turn, results in impaired hematopoietic differentiation. Thesedata provide amechanistic link between a mutant spliceosomal protein, alterations in the splicing of key reg-ulators, and impaired hematopoiesis.

INTRODUCTION

Somatic mutations in genes encoding components of the spli-ceosome have been identified in a spectrum of human malig-nancies, including !60% of patients with myelodysplastic

syndromes (MDS) (Bejar et al., 2012; Papaemmanuil et al.,2013; Yoshida et al., 2011). These mutations occur mostcommonly in SF3B1 (Splicing Factor 3b Subunit 1), SRSF2(Serine/arginine-Rich Splicing Factor 2), and U2AF1 (U2 SmallNuclear RNA Auxiliary Factor 1) and almost always as

Significance

Frequent somatic mutations affecting components of the spliceosome have been identified in hematologic malignancies;however, the functional role of these mutations is not known. Here we identify that commonly occurring mutations in thespliceosomal gene SRSF2 impair hematopoietic differentiation and promote myelodysplasia by altering SRSF2’s prefer-ence for specific exonic splicing enhancer motifs. This results in consistent mis-splicing in a manner that promotes theexpression of abnormal isoforms of a number of key hematopoietic regulators, some of which have been linked previouslyto leukemogenesis (including BCOR and EZH2). These data provide amechanistic basis for the enrichment of spliceosomalmutations in myelodysplasia and identify altered RNA recognition as an important driver of leukemogenesis.

Cancer Cell 27, 617–630, May 11, 2015 ª2015 Elsevier Inc. 617

Accepted Article Preview: Published ahead of advance online publication

Disruption of SF3B1 results in deregulated expression andsplicing of key genes and pathways in myelodysplastic syndromehematopoietic stem and progenitor cells OPEN

H Dolatshad, A Pellagatti, M Fernandez-Mercado, B H Yip,L Malcovati, M Attwood, B Przychodzen, N Sahgal, A AKanapin, H Lockstone, L Scifo, P Vandenberghe, EPapaemmanuil, C W J Smith, P J Campbell, S Ogawa, J PMaciejewski, M Cazzola, K I Savage, J Boultwood

Cite this article as: H Dolatshad, A Pellagatti, M Fernandez-Mercado, B H Yip, LMalcovati, M Attwood, B Przychodzen, N Sahgal, A A Kanapin, H Lockstone, LScifo, P Vandenberghe, E Papaemmanuil, C W J Smith, P J Campbell, S Ogawa, JP Maciejewski, M Cazzola, K I Savage, J Boultwood, Disruption of SF3B1 resultsin deregulated expression and splicing of key genes and pathways in myelodys-plastic syndrome hematopoietic stem and progenitor cells, Leukemia acceptedarticle preview 27 November 2014; doi: 10.1038/leu.2014.331.

This is a PDF file of an unedited peer-reviewed manuscript that has been acceptedfor publication. NPG are providing this early version of the manuscript as a serviceto our customers. The manuscript will undergo copyediting, typesetting and a proofreview before it is published in its final form. Please note that during the productionprocess errors may be discovered which could affect the content, and all legaldisclaimers apply.

This work is licensed under a Creative Commons Attribution 4.0 InternationalLicense. The images or other third party material in this article are included in the article’sCreative Commons license, unless indicated otherwise in the credit line; if the material is notincluded under the Creative Commons license, users will need to obtain permission from thelicense holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

Received 14 July 2014; revised 30 October 2014; accepted 19 November 2014;Accepted article preview online 27 November 2014

© 2014 Macmillan Publishers Limited. All rights reserved.

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HDACs

HMT

DNMT

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PRC1  complex  

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PRC1  complex   PRC1  complex  

HDM

HATs

TET proteins

PRC1 added

transcription

repression

Co-activators

Co-repressors

PRC1 removed

ASXL1

UTX

TET2

IDH2

IDH1

Genes that (theoretically) contribute to gene activation

=> Loss of function or dominant negative mutation induces silencing

EZH2

DNMT3A

Genes that (theoretically) contribute to gene repression

=> Loss of function induces activation

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Immune defects in MDS •  Association between MDS and « auto immune »

disorders » –  Relapsing polychondritis –  vasculitis, Sweet’s syndrome –  seronegative arthritis –  Crohn’s disease

•  anomalies of the immune system in MDS –  hypergammaglobulinamie, monoclonal Ig –  B, T cell anomalies –  Autoantibodies –  NK cells

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Alterations inmunologiques dans les SMD

•  SMD phase précoce: –  Augmentation de cytokines pro-apoptotiques –  Diminution des T reg , augmentation des Th17 –  Inhibition de l’hematopoïèse par les celulles T –  excès de cellules suppressives myéloides

•  SMD plus évolués –  anomalies des celulles NK –  augmentation des Tregs

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Bone progenitor dysfunction induces myelodysplasia and secondary leukaemia. Raaijmakers MH Nature 2010

Primary stromal dysfunction can result in secondary neoplastic disease, supporting the concept of niche-induced oncogenesis.

•  deletion of Dicer 1 in mouse osteoprogenitors results in MDS having intact Dicer1.

•  reduced expression of Sbds ( Schwachman-Bodian-Diamond syndrome) protein in osteoprogenitors

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LETTERdoi:10.1038/nature12883

Leukaemogenesis inducedbyanactivating b-cateninmutation in osteoblastsAruna Kode1, John S. Manavalan1, Ioanna Mosialou1, Govind Bhagat2, Chozha V. Rathinam3, Na Luo1, Hossein Khiabanian4,Albert Lee4, Vundavalli V. Murty5, Richard Friedman6, Andrea Brum1,7, David Park8, Naomi Galili9, Siddhartha Mukherjee10,Julie Teruya-Feldstein8, Azra Raza9, Raul Rabadan4, Ellin Berman11 & Stavroula Kousteni1,12

Cells of the osteoblast lineage affect the homing1,2 and the numberof long-term repopulating haematopoietic stem cells3,4, haemato-poietic stem cell mobilization and lineage determination and B celllymphopoiesis5–7.Osteoblastswere recently implicated inpre-leukaemicconditions inmice8,9.However, a single genetic change inosteoblaststhat can induce leukaemogenesis has not been shown.Herewe showthat an activatingmutation of b-catenin inmouse osteoblasts altersthe differentiation potential of myeloid and lymphoid progenitorsleading to development of acute myeloid leukaemia with commonchromosomal aberrations andcell autonomousprogression.Activatedb-catenin stimulates expression of theNotch ligand jagged 1 in osteo-blasts. Subsequent activation of Notch signalling in haematopoieticstemcell progenitors induces themalignant changes.Genetic orphar-macological inhibitionofNotch signallingameliorates acutemyeloidleukaemia and demonstrates the pathogenic role of the Notch path-way. In 38% of patients with myelodysplastic syndromes or acutemyeloid leukaemia, increasedb-catenin signalling andnuclear accumu-lationwas identified inosteoblasts andthesepatients showed increasedNotch signalling in haematopoietic cells. These findings demonstratethat genetic alterations in osteoblasts can induce acute myeloid leuk-aemia, identifymolecular signals leading to this transformationandsuggest a potential novel pharmacotherapeutic approach to acutemyeloid leukaemia.Mice expressing a constitutively activeb-catenin allele in osteoblasts,

referred to here as Ctnnb1CAosb (CA, constitutively active; osb, osteo-blast specific constitutive activity) are osteopetrotic10, and die before6weeks of age (Fig. 1a) for unknown reasons. Upon further examina-tion,Ctnnb1CAosb mice were anaemic at 2weeks of age with peripheralbloodmonocytosis, neutrophilia, lymphocytopenia and thrombocyto-penia (Extended Data Fig. 1a). Erythroid cells were decreased in themarrow and extramedullary haematopoiesis was observed in the liver(Fig. 1c and Extended Data Fig. 1b, l, m). Although the number ofmyeloid (CD11b1/Gr11) cells decreased due to osteopetrosis, theirrelative percentage increased, indicating a shift in the differentiationof HSCs to the myeloid lineage (Fig. 1d and Extended Data Fig. 1c, d).The haematopoietic stem and progenitor cell (HSPC) populationin the bone marrow (Lin2Sca1c-Kit1, LSK) cells decreased twofoldin Ctnnb1CAosb mice, but their percentage was twofold greater than inwild-type littermates (Fig. 1e and ExtendedData Fig. 1e, f). The long-termrepopulating HSC progenitors (LT-HSCs) increased in numbers andpercentage, whereas the lymphoid-biased multipotential progenitors,LSK1/FLT31, and thegranulocyte/monocyteprogenitors (GMP)(ExtendedData Fig. 1g–j) decreased. The GMP percentage increased (Fig. 1f).Identical abnormalities were observed in the spleen of Ctnnb1CAosb

mice (Extended Data Fig. 1n–p). The mutation was introduced inosteoblasts but not in any cells of the haematopoietic compartment(Extended Data Fig. 1q–t) of Ctnnb1CAosb mice.Blasts (12–90%) and dysplastic neutrophils (13–81%) were noted in

the blood and therewas dense anddiffuse infiltrationwithmyeloid andmonocytic cells, blasts (30–53% for n5 12 mice) and dysplastic neu-trophils in the marrow and spleen of Ctnnb1CAosb mice (Fig. 1g–k,Extended Data Fig. 2a–c). In the liver, clusters of immature cells withatypical nuclear appearancewere seen (Fig. 1l). The increase in immaturemyeloid cellswas confirmedby stainingwithmyeloidmarkers in bones,spleen and liver (ExtendedData Fig. 2d–h). ReducedB-cell lymphopoi-esis without changes inT-cell populationswas observed inCtnnb1CAosb

mice (Extended Data Fig. 2i–t). Differentiation blockade was demon-strated by the presence of immaturemyeloid progenitors inCtnnb1CAosb

marrow and differentiation cultures (Fig. 1m, n and Extended DataFig. 2u–x). These cellular abnormalities fulfil the criteria of AML dia-gnosis in mice11 with principle features of human AML12,13.A clonal abnormality involving aRobertsonian translocationRb(1;19)

was identified in myeloid cells of the spleen of a Ctnnb1CAosb mouse(Extended Data Fig. 2y). Recurrent numerical and structural chromo-somal alterations were also detected inmyeloid cells of the spleen of allmutant mice examined (Fig. 2a and Extended Data Table 1). Frequentabnormalities were detected in chromosome 5, the mouse orthologueof human chromosome 7q associatedwith common cytogenetic abnor-malities in patients with myelodysplastic syndromes (MDS) or acutemyeloid leukaemia (AML)14. Whole-exome sequencing identified 4non-silent somatic mutations in myeloid cells from 3 Ctnnb1CAosb

mice (Fig. 2b and Extended Data Fig. 2z), including a recurrent onein Tnfrsf21 and a single somatic mutation in Crb1 previously reportedin human AML15, but sample size has insufficient statistical power todetermine if it is a driver or passenger mutation. Hence, constitutiveactivation of b-catenin in osteoblasts facilitates clonal progression andis associated with somatic mutations in myeloid progenitors.Transplantation of bone marrow cells from Ctnnb1CAosb leukaemic

mice into lethally irradiatedwild-type recipients induced all features ofhaematopoietic dysfunction and AML observed in Ctnnb1CAosb miceincluding blasts (15–80%) and dysplastic neutrophils (15–75%) in theblood and blasts (30–40%) and abnormal megakaryocytes in the mar-row and early lethality (Extended Data Fig. 3a–i). Transplantation ofwild-type bone marrow cells to lethally irradiated Ctnnb1CAosb micealso resulted in AML with early lethality (Extended Data Fig. 3j–r).Transplantation of LT-HSCs, but not other haematopoietic popula-tions, from Ctnnb1CAosb mice to sub-lethally irradiated wild-type reci-pients resulted in AML with early lethality (Fig. 2c, d and Extended

1Department of Medicine, Division of Endocrinology, College of Physicians & Surgeons, Columbia University, New York, New York 10032, USA. 2Department of Pathology and Cell Biology, College ofPhysicians & Surgeons, Columbia University, New York, New York 10032, USA. 3Department of Genetics and Development College of Physicians & Surgeons, Columbia University, New York, New York10032,USA. 4Department of Biomedical Informatics andCenter for Computational Biology andBioinformatics, ColumbiaUniversity, NewYork, NewYork10032, USA. 5Department of Pathology& Institutefor Cancer Genetics Irving Cancer Research Center, Columbia University, New York, New York 10032, USA. 6Biomedical Informatics Shared Resource, Herbert Irving Comprehensive Cancer Center andDepartment of Biomedical Informatics, College of Physicians&Surgeons, ColumbiaUniversity, NewYork, NewYork 10032, USA. 7Department of InternalMedicine, ErasmusMC, Dr.Molewaterplein50, NL-3015GERotterdam,TheNetherlands. 8DepartmentofPathology,Memorial Sloan-KetteringCancerCenter,NewYork,NewYork10021,USA. 9MyelodysplasticSyndromesCenter, ColumbiaUniversityNewYork, New York 10032, USA. 10Departments of Medicine Hematology & Oncology Columbia University New York, New York 10032, USA. 11Leukemia Service, Department of Medicine, Memorial Sloan-Kettering Cancer Center, New York, New York 10021, USA. 12Department of Physiology & Cellular Biophysics, College of Physicians & Surgeons, Columbia University, New York, New York 10032, USA.

0 0 M O N T H 2 0 1 4 | V O L 0 0 0 | N A T U R E | 1

Macmillan Publishers Limited. All rights reserved©2014

Here we show that an activating mutation of b-catenin in mouse osteoblasts alters the differentiation potential of myeloid and lymphoid progenitors leading to development of acute myeloid leukaemia with common chromosomal aberrations and cell autonomous progression

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Research article

The Journal of Clinical Investigation http://www.jci.org Volume 123 Number 11 November 2013 4595

Induction of myelodysplasia by myeloid-derived suppressor cells

Xianghong Chen,1 Erika A. Eksioglu,1 Junmin Zhou,1 Ling Zhang,1 Julie Djeu,1 Nicole Fortenbery,1 Pearlie Epling-Burnette,1 Sandra Van Bijnen,2 Harry Dolstra,2

John Cannon,3 Je-in Youn,1 Sarah S. Donatelli,1 Dahui Qin,1 Theo De Witte,2 Jianguo Tao,1 Huaquan Wang,4 Pingyan Cheng,1 Dmitry I. Gabrilovich,1 Alan List,1 and Sheng Wei1,4

1H. Lee Moffitt Cancer Center, Tampa, Florida, USA. 2Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands. 3Department of Pediatrics, Children’s Research Institute, University of South Florida, Tampa, Florida, USA. 4Tianjin Medical University Cancer Hospital, Tianjin, China.

Myelodysplastic syndromes (MDS) are age-dependent stem cell malignancies that share biological features of activated adaptive immune response and ineffective hematopoiesis. Here we report that myeloid-derived suppressor cells (MDSC), which are classically linked to immunosuppression, inflammation, and cancer, were markedly expanded in the bone marrow of MDS patients and played a pathogenetic role in the development of ineffective hematopoiesis. These clonally distinct MDSC overproduce hematopoietic suppressive cytokines and function as potent apoptotic effectors targeting autologous hematopoietic progenitors. Using multiple transfected cell models, we found that MDSC expansion is driven by the interaction of the proinflammatory molecule S100A9 with CD33. These 2 proteins formed a functional ligand/receptor pair that recruited compo-nents to CD33’s immunoreceptor tyrosine-based inhibition motif (ITIM), inducing secretion of the suppres-sive cytokines IL-10 and TGF- by immature myeloid cells. S100A9 transgenic mice displayed bone marrow accumulation of MDSC accompanied by development of progressive multilineage cytopenias and cytological dysplasia. Importantly, early forced maturation of MDSC by either all-trans-retinoic acid treatment or active immunoreceptor tyrosine-based activation motif–bearing (ITAM-bearing) adapter protein (DAP12) interrup-tion of CD33 signaling rescued the hematologic phenotype. These findings indicate that primary bone mar-row expansion of MDSC driven by the S100A9/CD33 pathway perturbs hematopoiesis and contributes to the development of MDS.

IntroductionUnderstanding the selective pressures and mechanisms involved in the initiation of stem cell malignancies is critical to development of effective strategies for prevention and treatment. Inflammatory molecules have long been implicated as regulatory cues driving the proliferation and apoptotic death of hematopoietic progenitors in myelodysplastic syndromes (MDS) (1–3). Chronic immune stimu-lation, coupled with senescence dependent changes in both hema-topoietic stem/progenitor cells (HSPC) and the BM microenviron-ment, are believed to be critical to the pathogenesis of the disease (4). Increasing evidence implicates the activation of innate immune signaling in both hematopoietic senescence and the pathobiology of MDS (5). TLR4, for instance, is overexpressed in MDS BM HSPC and is implicated in progenitor apoptosis and subsequent develop-ment of cytopenias (6). Furthermore, gene expression of the TLR adaptor E3 ubiquitin ligase, TNF receptor-associated factor-6 (TRAF6), is markedly upregulated in MDS CD34+ cells (7) accom-panied in some cases by amplification of genomic regions encod-ing TRAF6 or the Toll IL-1 receptor domain-containing adap-tor protein (TIRAP), key intermediates in TLR4 signaling (8, 9). Recent investigations showed that TLR signaling is constitu-tively activated in MDS with chromosome 5q deletion [del(5q)] as a result of allelic deletion of microRNA 145 (miRNA-145) and

miRNA-146a and consequent upregulation of their respective targets, TIRAP and TRAF6 (10). Moreover, knockdown of these specific miRNAs or overexpression of Traf6 in murine HSPC reca-pitulates the hematologic features of del(5q) MDS in a transplant model (10), providing convincing evidence that sustained TLR activation is a critical factor driving the malignant phenotype. More recent findings indicate that TRAF6 is essential for survival and proliferation of MDS HSPC (11) and sustained TLR activa-tion skews their commitment toward the myeloid lineage while suppressing osteoblast differentiation (12, 13), analogous to the senescence-dependent changes observed with normal aging (14).

Immature myeloid-derived suppressor cells (MDSC), known to accumulate in tumor-bearing mice and cancer patients, are site-specific inflammatory and T cell immunosuppressive effector cells that contribute to cancer progression (15, 16). Their suppres-sive activity is in part driven by inflammation-associated signal-ing molecules, such as the danger-associated molecular pattern (DAMP) heterodimer S100A8/S100A9 (also known as myeloid-related protein 8 [MRP-8] and MRP-14, respectively), which inter-act with several innate immune receptors that are involved in the biology of MDSC activation (17–20). Murine CD11b+Gr1+ MDSC form the basis of the vast majority of the mechanistic studies; how-ever, much less has been reported on their human counterparts. Human MDSC lack most markers of mature immune cells (LIN–, HLA-DR–) but possess CD33, the prototypical member of sialic acid–binding Ig-like super-family of lectins (Siglec) (15, 21–23). Importantly, while its precise action is unknown, CD33 possesses an immunoreceptor tyrosine-based inhibition motif (ITIM) that is associated with immune suppression (23).

Authorship note: Xianghong Chen, Erika A. Eksioglu, and Junmin Zhou contrib-uted equally to this work. Dmitry I. Gabrilovich, Alan List, and Sheng Wei Share are co–senior authors.

Conflict of interest: The authors have declared that no conflict of interest exists.

Citation for this article: J Clin Invest. 2013;123(11):4595–4611. doi:10.1172/JCI67580.

-primary bone marrow expansion of MDSC driven by the S100A9/CD33 pathway perturbs hematopoiesis and contributes to the development of MDS -treatment with anti CD 33 drugs considered

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SMD  •  Épidémiologie  

•  Physiopathologie  

•  Diagnos4c  

•  Classifica4on  et  pronos4c  

•  Traitement  

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SMD diagnostic positif: hemogramme+ myelogramme

•  Clinique: conséquence des cytopénies •  Hémogramme: cytopénies

–  Anémie (macrocytaire arégénérative) –  Neutropénie –  Thrombopénie –  (blastes circulants, monocytose) –  Dysmyélopoièse

•  Myélogramme –  Richesse médullaire élevée –  Dysmyélopoièse sur un nombre variable de lignées –  Évaluer % blastes (B1, B2, B3) –  Evaluer % sidéroblastes en couronne

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Blasts in MDS (J Goasguen) Subtype

Example Description Remarks

Agranular blast

Agranular blast with basophilic cytoplasm fine chromatin and nuleoli

Type I blast in the FAB classification

Granular blast

A subtype but with azurophilic granulations and absence of Golgi zone

Includes Type II blast in FAB classification and Type III blast as defined by Goasguen et al

Promyelocyte

Azurophilic granulations and A clear visible Golgi zone characteristic in promyelocytes

Myelodysplastic promyelocyte

Promyelocyte with an irregular distribution of granulations and reduced number of granules

These cells are often seen in MDS and need to be distinguished from granular blasts !"

#$#%&'()*+&,#

)-./(*&

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Blast cells in MDS (J Goasguen)

!" !"

#" #" #" #" #"

$%&" $%&"

!'($%&" !'($%&" !'($%&" !'($%&"

$)*+*,"-./(0"#*/123.("

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SMD:diagnostic différentiel ?

•  Autres insuffisances médullaires qualititatives: carence en B12 ou folates

•  Aplasie (biopsie médullaire) •  LAM (<20% blastes médullaires) •  Devant une cytopénie isolée:

–  (Anémie) –  thrombopénie

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SMD: autres outils diagnostiques ?

•  Biopsie médullaire (richesse médullaire,myélofibrose)

•  Caryotype +/- FISH

•  Mutations somatiques ? •  Cytométrie de flux ?

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Rôle diagnostique du caryotype: SMD sans dysplasie caractéristique mais anomalie

cytogénétique?

•  Femme âgée avec anémie modérée et del 5q

•  Thrombopénie et del 20q

•  Cytopénies moderées et -7 ou +8

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FISH for chromosome 8

Mitose

Nucleus

CEP8

CEP8

normal

Trisomie 8

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T h e n e w e ngl a nd j o u r na l o f m e dic i n e

n engl j med nejm.org 1

original article

Age-Related Clonal Hematopoiesis Associated with Adverse Outcomes

Siddhartha Jaiswal, M.D., Ph.D., Pierre Fontanillas, Ph.D., Jason Flannick, Ph.D., Alisa Manning, Ph.D., Peter V. Grauman, B.A., Brenton G. Mar, M.D., Ph.D.,

R. Coleman Lindsley, M.D., Ph.D., Craig H. Mermel, M.D., Ph.D., Noel Burtt, B.S., Alejandro Chavez, M.D., Ph.D., John M. Higgins, M.D., Vladislav Moltchanov, Ph.D., Frank C. Kuo, M.D., Ph.D., Michael J. Kluk, M.D., Ph.D., Brian Henderson, M.D., Leena Kinnunen M.Sc., Heikki A. Koistinen, M.D., Ph.D., Claes Ladenvall, Ph.D.,

Gad Getz, Ph.D., Adolfo Correa, M.D., Ph.D., Benjamin F. Banahan, Ph.D., Stacey Gabriel, Ph.D., Sekar Kathiresan, M.D., Heather M. Stringham, Ph.D.,

Mark I. McCarthy, M.D.,* Michael Boehnke, Ph.D.,* Jaakko Tuomilehto, M.D., Ph.D., Christopher Haiman, Sc.D., Leif Groop, M.D., Ph.D., Gil Atzmon, Ph.D.,

James G. Wilson, M.D., Donna Neuberg, Sc.D., David Altshuler, M.D., Ph.D.,* and Benjamin L. Ebert, M.D., Ph.D.†

The authors’ affiliations are listed in the Appendix. Address reprint requests to Dr. Ebert at the Department of Medicine, Division of Hematology, Brigham and Women’s Hospital, Harvard Medical School, 1 Blackfan Cir., Karp 5.210, Boston, MA 02115, or at [email protected].

* Dr. McCarthy is listed on behalf of the Type 2 Diabetes (T2D) Genetic Explora-tion by Next-Generation Sequencing in Multi-Ethnic Samples (T2D-GENES) study investigators; Dr. Boehnke, on be-half of the Genetics of Type 2 Diabetes (GoT2D) study investigators; and Dr. Altshuler, on behalf of the SIGMA T2D study investigators.

† A complete list of investigators in the T2D-GENES, GoT2D, and SIGMA T2D studies is provided in the Supplemen-tary Appendix, available at NEJM.org.

This article was published on November 26, 2014, at NEJM.org.

DOI:!10.1056/NEJMoa1408617Copyright © 2014 Massachusetts Medical Society.

A BS TR AC T

BackgroundThe incidence of hematologic cancers increases with age. These cancers are associ-ated with recurrent somatic mutations in specific genes. We hypothesized that such mutations would be detectable in the blood of some persons who are not known to have hematologic disorders.

MethodsWe analyzed whole-exome sequencing data from DNA in the peripheral-blood cells of 17,182 persons who were unselected for hematologic phenotypes. We looked for somatic mutations by identifying previously characterized single-nucleotide vari-ants and small insertions or deletions in 160 genes that are recurrently mutated in hematologic cancers. The presence of mutations was analyzed for an association with hematologic phenotypes, survival, and cardiovascular events.

ResultsDetectable somatic mutations were rare in persons younger than 40 years of age but rose appreciably in frequency with age. Among persons 70 to 79 years of age, 80 to 89 years of age, and 90 to 108 years of age, these clonal mutations were observed in 9.5% (219 of 2300 persons), 11.7% (37 of 317), and 18.4% (19 of 103), respec-tively. The majority of the variants occurred in three genes: DNMT3A, TET2, and ASXL1. The presence of a somatic mutation was associated with an increase in the risk of hematologic cancer (hazard ratio, 11.1; 95% confidence interval [CI], 3.9 to 32.6), an increase in all-cause mortality (hazard ratio, 1.4; 95% CI, 1.1 to 1.8), and increases in the risks of incident coronary heart disease (hazard ratio, 2.0; 95% CI, 1.2 to 3.4) and ischemic stroke (hazard ratio, 2.6; 95% CI, 1.4 to 4.8).

ConclusionsAge-related clonal hematopoiesis is a common condition that is associated with increases in the risk of hematologic cancer and in all-cause mortality, with the lat-ter possibly due to an increased risk of cardiovascular disease. (Funded by the Na-tional Institutes of Health and others.)

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•  Mainly  DNMT3A,  TET2,  and  ASXL1  •   70  to  79  years  of  age,  9.5%  •   80  to  89  years  :  11.7%    •   90  to  108  years  :18.4%  

   

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Age-Related Clonal Hematopoiesis and Adverse Outcomes

n engl j med nejm.org 3

The identification of somatic driver mutations in cancer has come largely from studies that have compared differences in DNA sequence between tumor and normal tissue obtained from the same person. Once mutations are identified, investiga-tors may genotype samples for these somatic vari-ants without relying on matched normal tissue. Because we had DNA from only one source (blood), we limited our examination to variants that had been described previously in the litera-ture in 160 recurrently mutated candidate genes in myeloid and lymphoid cancers (Table S2 in the Supplementary Appendix). We removed potential false positive variants by using variant-calling algorithms that had filters for known artifacts such as strand-bias and clustered reads, as well as by performing additional filtering for rare error modes using a “panel of normals” (sequence data from a panel of normal persons).25 The lower limit of detection for variants depended on the depth of coverage. The median average sequenc-ing depth for exons from the 160 genes was 84 reads (range, 13 to 144). At a sequencing depth of 84 reads, the limit of detection for SNVs was at a variant allele fraction of 0.035; the limit of detection for indels was 0.070.

With this approach, we identified a total of 805 candidate somatic variants (hereafter referred to as mutations) in 73 genes from 746 persons (Table S3 in the Supplementary Appendix). As a negative control, we searched for previously de-scribed, nonhematologic cancer-associated vari-ants in 40 genes (Table S4 in the Supplementary Appendix)27 and found only 10 such variants in these genes (Table S5 in the Supplementary Ap-pendix), indicating that the rate of false discovery due to technical artifacts was low. We also verified a subset of the variants using amplicon-based, targeted sequencing; 18 of 18 variants were con-firmed, with a correlation coefficient of 0.97 for the variant allele fraction between the two meth-ods (Fig. S1 in the Supplementary Appendix).

Increase in the Frequency of Clonal Somatic Mutations with Age

Hematologic cancers, as well as other cancers and premalignant states, increase in frequency with age. Mutations were very rare in samples obtained from patients younger than 40 years of age but rose in frequency with each decade of life thereafter (Fig. 1). Mutations in genes implicated in hematologic cancers were found in 5.6% (95%

confidence interval [CI], 5.0 to 6.3) of persons 60 to 69 years of age, 9.5% (95% CI, 8.4 to 10.8) of persons 70 to 79 years of age (219 of 2300 per-sons), 11.7% (95% CI, 8.6 to 15.7) of persons 80 to 89 years of age (37 of 317), and 18.4% (95% CI, 12.1 to 27.0) of persons 90 years of age or older (19 of 103). These rates greatly exceed the inci-dence of clinically diagnosed hematologic cancer in the general population.28

Though we searched for mutations in genes implicated in many different hematologic can-cers, we primarily identified genes that were most frequently mutated in AML and the myelodys-plastic syndrome. The most commonly mutated gene was DNMT3A (403 variants) (Fig. 2A, and Fig. S2 in the Supplementary Appendix), fol-lowed by TET2 (72 variants) and ASXL1 (62 vari-ants). In TET2, only exon 3 was obtained by exon capture (corresponding to approximately 50% of the coding region), and the portion of exon 12 of ASXL1 that accounts for approximately 50% of the mutations in this gene had poor coverage depth. Thus, mutations in TET2 and ASXL1 are probably underrepresented in this study. Other frequently mutated genes included TP53 (33 vari-ants), JAK2 (31 variants), and SF3B1 (27 variants).

In sequencing studies of the myelodysplastic syndrome and AML, most patients have mutations in two or more driver genes (the median number of recurrently mutated genes in patients with de

Freq

uenc

y

0.5

0.3

0.4

0.2

0.1

0.0

20–2

930

–39

40–4

950

–59

60–6

970

–79

80–8

990

–99

100–

108

Age!(yr)

No.!with!MutationTotal

0240

517

1486

37317

2192300

2825002

1385441

502894

1855

Figure!1.!Prevalence!of!Somatic!Mutations,!According!to!Age.

Colored bands, in increasingly lighter shades, represent the 50th, 75th, and 95th percentiles.

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T h e n e w e ngl a nd j o u r na l o f m e dic i n e

n engl j med nejm.org4

novo AML is five17). In this study, we found that 693 of 746 persons with a detectable mutation had only one mutation in the set of genes we examined (Fig. 2B, and Fig. S2 in the Supplemen-tary Appendix), a finding that was consistent with the hypothesis that these persons had clones har-boring only an initiating lesion.

The most common base-pair change in the somatic variants was a cytosine-to-thymine (C!T) transition (Fig. 2C), which is considered to be a somatic mutational signature of aging.16,29 The

median variant allele fraction for the identified mutations was 0.09 (Fig. 2D), suggesting that the variants are present in only a subset of blood cells and supporting their somatic rather than germ-line origin.

Persistence of Somatic Mutations over TimeBlood-cell DNA obtained 4 to 8 years after the initial DNA collection was available for targeted sequencing in 13 persons with 17 somatic muta-tions (4 persons had 2 mutations). In all cases,

No.

400

300

200

100

0

DNMT3A

TET2

ASXL1TP53

JAK2

SF3B1

GNB1CBL

SRSF2GNAS

Gene

Prop

ortio

n!of

!Var

iant

s

Den

sity

0.6

0.5

0.4

0.3

0.2

0.1

0.0C"A C"G C"T T"A T"C T"G

6

4

2

00.0 0.2 0.4 0.6 0.8 1.0 0.8 1.0

6

4

88

2

00.0 0.2 0.4 0.6

Den

sity

6

4

2

00.0 0.2 0.4 0.6 0.8 1.0 0.8 1.0

6

4

88

2

00.0 0.2 0.4 0.6

Allele!Fraction

Nonsense!Variants Indel!Variants

Splice-Site!Variants Missense!Variants

C D

A403

72 6233 31 27 22 12 11 8

693

492 2

No.

!of!P

atie

nts

800

600

400

200

01 2 3 4

Mutations

B

Mean AF=0.12Median AF=0.09

Mean AF=0.14Median AF=0.10

Mean AF=0.12Median AF=0.10

Mean AF=0.14Median AF=0.09

Figure!2.!Characteristics!of!Candidate!Somatic!Variants.

Panel A shows the 10 most frequently mutated genes implicated in hematologic cancers. Panel B shows the number of persons with 1, 2, 3, or 4 candidate variants. Panel C shows the distribution of the types of single-nucleotide base-pair changes seen in the candidate variants. Panel D shows the allele fractions (AFs) of candidate somatic variants. The allele fraction was calculated as the number of vari-ant reads divided by the number of variant-plus-reference reads. For variants on the X chromosome in men, this number was divided by 2. Indel denotes insertions and deletions.

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Copyright © 2014 Massachusetts Medical Society. All rights reserved.

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ORIGINAL ARTICLE

Flow cytometric detection of dyserythropoiesis: a sensitiveand powerful diagnostic tool for myelodysplastic syndromesS Mathis1,2,7, N Chapuis1,2,7, C Debord1, A Rouquette3, I Radford-Weiss4, S Park2,5, F Dreyfus2,5, C Lacombe1,2, MC Bene6, O Kosmider1,2,M Fontenay1,2 and V Bardet1,2

Several groups have published flow cytometry scores useful for the diagnosis or prognosis of myelodysplastic syndromes (MDS),mainly based on the detection of immunophenotypic abnormalities in the maturation of granulocytic/monocytic and lymphoidlineages. As anemia is the most frequent symptom of early MDS, the aim of this study was to identify markers of dyserythropoiesisrelevant for the diagnosis of MDS analyzed by selecting erythroblasts in a whole no-lysis bone marrow strategy by using a nucleardye. This prospective study included 163 patients, including 126 with cytopenias leading to MDS suspicion and 46 controls withoutMDS. In a learning cohort of 53 unequivocal MDS with specific markers, there was a significant difference between the coefficientsof variation of mean fluorescence intensities of CD71 and CD36 in MDS patients compared with controls. These two parameters andthe hemoglobin level were used to build a RED-score strongly suggestive of MDS if X3. Using the RED-score in the whole cohort,80% of MDS or non-MDS patients were correctly classified. When combined with the flow score described by Ogata et al., thisstrategy allowed to reach a very high sensitivity of 88% of patients correctly classified.

Leukemia (2013) 27, 1981–1987; doi:10.1038/leu.2013.178

Keywords: myelodysplastic syndromes; flow cytometry; dyserythropoiesis

INTRODUCTIONMorphology remains the gold standard for the diagnosis ofmyelodysplastic syndromes (MDS). The current WHO (WorldHealth Organization) classification1 relies on the quantification ofblast cells in bone marrow (BM) or peripheral blood and on theevaluation of BM dysplasia to stratify MDS patients. The diagnosisof MDS is straightforward if obvious morphological abnormalitiesare seen after standard or specific Perls’ iron staining, or ifspecific cytogenetic abnormalities are present. If not, the patientis classified as having idiopathic cytopenia of undeterminedsignificance (ICUS).2 Over the past 20 years, several groups havedeveloped new approaches in multiparameter flow cytometry(MFC) as diagnostic or prognostic tools in MDS.3,4 At present,although the respective value of several markers has beenacknowledged, there is no consensus about a MFC panelvalidated to establish robust diagnosis or prognosis in MDS andno single immunophenotypic marker has proven to be able todiscriminate accurately between MDS and other pathologicalconditions leading to cytopenia. Among the different studiespublished, very few relate specifically to the erythroidcompartment. Yet, abnormalities in CD71 (transferrin receptor),CD36 (thrombospondin receptor) or CD235a (glycophorin-A)expression have long been reported in MDS.5–9 Indeed, severalauthors have emphasized the specificity and consistency ofdecreased CD71 expression in MDS patients.8,10,11

An important caveat in the quantification of erythroidprecursors is the modifications induced by red blood cell (RBC)lysis. Elimination of mature non-nucleated erythroid cells isroutinely performed in MFC with various reagents. The latter,

however, can induce the lysis of some of the most matureacidophilic or polychromatophilic erythroblasts and/or result in anincomplete lysis of RBC impairing a proper analysis of the mostimmature cells. An alternative approach to study the erythroidcompartment would be to use whole peripheral blood or BM withthe addition of a nuclear dye in the MFC panel. To this avail, DRAQ5or DRAQ7 (Biostatus Limited, Shepshed, UK)12,13 for instance, allowto discriminate nucleated and non-nucleated cells in MFC.In this study, we developed a whole BM MFC protocol using

the recently developed nuclear dye CyTRAK orange (BiostatusLimited) to gate nucleated cells.14 This new protocol, avoidingRBC lysis, could enhance the accuracy of the MFC approach asdiagnostic tool in MDS. The aim of this study was thus to developthis approach and propose a reproducible and simple MFC tooluseful within the diagnostic work-up of patients suspectedof MDS.

MATERIALS AND METHODSThis study comprised two stages corresponding to phases I and III of adiagnostic test development process.15 The aim of phase I is to identifymarkers able to discriminate between cases (MDS) and control subjects.Phase III is a pragmatic one aiming at developing a diagnostic score usingthese markers and evaluating its diagnostic properties (sensitivity,specificity and predictive values) in routine practice.

PatientsAs described in the flow chart (Figure 1), this prospective study included allpatients (n! 132) with cytopenias but without circulating blasts (to focus

1Service d0Hematologie Biologique, Hopitaux Universitaires Paris Centre-Cochin, Paris, France; 2Inserm U1016, UMR 8104, Universite Paris Descartes, Hopitaux Universitaires ParisCentre-Cochin, Paris, France; 3Unite de Biostatistique et d’Epidemiologie, Universite Paris Descartes, Hopitaux Universitaires Paris Centre-Hotel Dieu, Paris, France; 4Service deCytogenetique, Groupe Hospitalier Necker-Enfants malades, Paris, France; 5Unite fonctionnelle d0Hematologie Clinique, Hopitaux Universitaires Paris Centre-Cochin, Paris, Franceand 6Service d0Hematologie Biologique, CHU, Nantes, France. Correspondence: Dr V Bardet, Service d0Hematologie Biologique, Hopitaux Universitaires Paris Centre-Cochin, Paris,France or Inserm U1016, UMR 8104, Universite Paris Descartes, Hopitaux Universitaires Paris Centre-Cochin, 27 rue du Faubourg Saint Jacques, Paris 75014, France.E-mail: [email protected] authors contributed equally to this work.Received 26 March 2013; revised 05 June 2013; accepted 10 June 2013; accepted article preview online 14 June 2013; advance online publication, 12 July 2013

Leukemia (2013) 27, 1981–1987& 2013 Macmillan Publishers Limited All rights reserved 0887-6924/13

www.nature.com/leu

•  significant difference of mean fluorescence intensities of CD71 and CD36 in MDS patients compared with controls

•  CD71,CD36, Hb level used to build a RED-score strongly suggestive of MDS

•  Using the RED-score 80% of MDS or non-MDS patients were correctly classified.

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In this cohort, 101 patients were tested with both scores. Forty-one of 83 MDS patients displayed an Ogata MFC-scoreX2reflecting the weaker sensitivity of this test. Among the 42patients with an Ogata MFC-scoreo2, a RED-scoreX3 washowever observed for 32. Conversely, of 15 patients with aRED-scoreo3, 5 had an Ogata MFC-scoreX2. Interestingly, 73 of83 (88%) MDS patients had either a RED-scoreX3 or an OgataMFC-scoreX2. Comparison of both scores and their combinationare detailed in Supplementary Table 1. With this approach,the sensitivity was significantly increased (87.9%), whereas thespecificity remained high (88.9%); positive predictive value andnegative predictive value were therefore of 97% (73/75) and 61%(16/26), respectively.

DISCUSSIONThis study demonstrates that analysis of erythroblasts in no-lysiswhole-BM approach is feasible, after exclusion of non-nucleatedcells by their absence of staining with CyTRAK orange. This yieldedthe observation of both a significant decreased fluorescence andbroader peaks for CD71 and CD36 in MDS samples compared withcontrol BM. This is likely due to the coexistence of pathologicaland normal erythropoiesis in MDS patients, where the decreasedexpression of these markers in the pathological clone induceincreased GMFI CVs. CVs are statistical parameters directlyavailable from flow cytometers analysis software. CVs are lessaffected than GMFI by intrinsic variations between patients orbetween instruments and provided here the best discriminationbetween patients and controls.A preliminary step in our approach was to determine the best

analytical process in order to detect with the highest sensitivitydifferences between MDS patients and controls. As shown here,RBC lysis is deleterious not only for enucleated RBC but also forerythroblasts that have a drastic reduction in size (60%), whereasother nucleated cells are not significantly affected. Indeed, afterred cell lysis, erythroblasts are reduced to cells almost devoid ofcytoplasm or even to naked nuclei, therefore possibly compro-mising the detection of surface antigens.

In a first step, comparison of four surface markers oferythroblasts between 53 unequivocal MDS patients and 46controls allowed to identify CD71 and CD36 CVs as highly sensitiveand robust discriminative tools for MDS diagnosis. Using a simplealgorithm combining the two CV and the degree of anemia, MFCby itself was able to predict the correct diagnosis in 80% patientsof a larger cohort of 110 patients in the second step of the study.Interestingly, both CVs are highly negatively correlated with Hblevels, indicating that this approach will be particularly successfulfor patients presenting with anemia, who represent the majority ofpatients with suspected MDS. Indeed, 16 of 20 patients with MDSfor whom the RED-score was o3 did not suffer from anemia. Nineof these patients had an abnormal CD36 CV and could thereforehave been diagnosed if they had been anemic. Among the fourremaining patients who had anemia, two were ultimatelydiagnosed with 5q-syndrome. It can be hypothesized that themechanism of anemia can be different in these patients and morerelated with erythroblastopenia rather than with dysplasia.Conversely, the two non-MDS patients, classified as false positivewith a RED-scoreX3, were initially diagnosed with ICUS, had noanemia and mainly suffered from moderate thrombocytopenia. Inthese patients with slight or absent dysplasia, there was noelement for a diagnosis of MDS and they were finally consideredas non-MDS patients after 6-month follow-up. It cannot, however,be excluded that they indeed suffered from an early-stage MDSand will develop overt MDS with long-term follow-up. Veryrecently, the Munich Leukemia Laboratory team demonstratedthat with longer follow-up, half of patients with MFC abnormalitiesand without proof of myelodysplasia by cytomorphology orcytogenetics indeed developed overt disease, enhancing the roleof MFC in the early diagnosis of MDS.24

When combining the results of the new RED-score with those ofthe Ogata MFC-score,17 a very high sensitivity was reachedin the diagnosis of MDS by MFC as 88% of patients were correctlyclassified. We thus believe that MFC can be a useful tool in thediagnosis of MDS, particularly for patients with no obviousdysplasia in cytomorphology. Of note, MFC provided a diagnosisin this series, for the 28% of cases where cytomorphology and

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Area under ROC curve = 0.7011

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Area under ROC curve = 0.9053

Figure 7. ROC curves for the Ogata MFC-score and the new RED-score in the whole cohort areas under ROC curves for the Ogata MFC-scoreand for RED-score are 0.7011(panel a; 95% CI! (0.5857–0.8165)) and 0.9053 (panel b; 95% CI! (0.8524–0.9583)) respectively. With a thresholdequal to 3, sensitivity and specificity are 0.77, 95% CI! (0.6886–0.8620) and 0.9048, 95% CI! (0.7793–1), respectively.

RED-scoreparameter

Threshold Points

CD71CV (%)<80 0!80 3

CD36CV (%)<65 0!65 2

Hb level (g/dL)

>10.5 (F) or>11.5 (M) 0

"10.5 (F) or"11.5 (M)

2

0 10 20 30 40 50 60 70 80

0

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3

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7

MDS non MDS Controls

Figure 6. RED-score quantification in the 110 patients of the cohort and the 46 controls. Panel a shows the details of the score. Panel b showsthe results in 89 MDS patients, 21 non-MDS patients and 46 controls as percentage of total for each population.

MDS dyserythropoiesis detection in flow cytometryS Mathis et al

1986

Leukemia (2013) 1981 – 1987 & 2013 Macmillan Publishers Limited

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SMD  •  Épidémiologie  

•  Physiopathologie  

•  Diagnos4c  

•  Classifica4on  et  pronos4c  

•  Traitement  

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Facteurs  pronos4ques  dans  les  SMD  

•  Score  IPSS  et  IPSS-­‐R  •  Muta4ons  soma4ques  •  Cytométrie  de  flux  ?  •  Scores  de  comorbidités  et  analyse  de  la  qualité  de  vie  

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Interna4onal  Prognos4c    Scoring  System  (IPSS)  

Score Value

Prognostic variable 0 0.5 1.0 1.5 2.0

Blasts MO, % <5 5–10 — 11–20

21–30

Caryotype* Good

Interm.

Poor

Cytopenies 0/1 2/3 —

Scores Low 0 Int-1 0.5–1.0 Int-2 1.5–2.0 High ≥2.5

Cytogenetics

FAV Normal –y del(5q) del(20q)

DEFAV Complex (≥3 abn)

chrom 7 abn INT Other

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1994 84: 3148-3157

FenauxE Wattel, C Preudhomme, B Hecquet, M Vanrumbeke, B Quesnel, I Dervite, P Morel and P short survival in hematologic malignanciesp53 mutations are associated with resistance to chemotherapy and

http://bloodjournal.hematologylibrary.org/content/84/9/3148.full.htmlUpdated information and services can be found at:

Articles on similar topics can be found in the following Blood collections

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Copyright 2011 by The American Society of Hematology; all rights reserved.Society of Hematology, 2021 L St, NW, Suite 900, Washington DC 20036.Blood (print ISSN 0006-4971, online ISSN 1528-0020), is published weekly by the American

For personal use only. on March 30, 2014. at INSERM DISC bloodjournal.hematologylibrary.orgFrom For personal use only. on March 30, 2014. at INSERM DISC bloodjournal.hematologylibrary.orgFrom

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MUT WT

OS selon les mutations de p53 (p =0.0054)

TP53 mutations and results of AZA in MDS (Bally,Leuk Res, 2013)

Poor prognosis of TP53/p53 mutations with all available treatments

Somatic Mutations Predict Poor Outcome in PatientsWith Myelodysplastic Syndrome After HematopoieticStem-Cell TransplantationRafael Bejar, Kristen E. Stevenson, Bennett Caughey, R. Coleman Lindsley, Brenton G. Mar, Petar Stojanov,Gad Getz, David P. Steensma, Jerome Ritz, Robert Soiffer, Joseph H. Antin, Edwin Alyea, Philippe Armand,Vincent Ho, John Koreth, Donna Neuberg, Corey S. Cutler, and Benjamin L. Ebert

Listen to the podcast by Dr Estey at www.jco.org/podcasts

Rafael Bejar and Bennett Caughey,University of California at San Diego, LaJolla, CA; Kristen E. Stevenson, R.Coleman Lindsley, Brenton G. Mar,David P. Steensma, Jerome Ritz,Robert Soiffer, Joseph H. Antin, EdwinAlyea, Philippe Armand, Vincent Ho,John Koreth, Donna Neuberg, andCorey S. Cutler, Dana-Farber CancerInstitute; R. Coleman Lindsley andBenjamin L. Ebert, Brigham andWomen’s Hospital, Harvard MedicalSchool, Boston; Petar Stojanov, GadGetz, and Benjamin L. Ebert, BroadInstitute, Cambridge, MA.

Published online ahead of print atwww.jco.org on August 4, 2014.

Processed as a Rapid Communicationmanuscript

Supported by National Institute ofDiabetes and Digestive and KidneyDiseases Grant No. 5K08DK091360 andan American Society of Hematologyscholar award (R.B.) and by NationalHeart, Lung, and Blood Institute GrantNo. R01HL082945, a Leukemia andLymphoma Society scholar award, andthe Yellow Diamond FoundationFund (B.L.E.).

Terms in blue are defined in the glos-sary, found at the end of this articleand online at www.jco.org.

Authors’ disclosures of potential con-flicts of interest and author contribu-tions are found at the end of thisarticle.

Corresponding author: Benjamin L.Ebert, MD, PhD, Brigham andWomen’s Hospital, 1 Blackfan Circle,Karp CHRB 5.211, Boston, MA 02115;e-mail:[email protected].

© 2014 by American Society of ClinicalOncology

0732-183X/14/3225w-2691w/$20.00

DOI: 10.1200/JCO.2013.52.3381

A B S T R A C T

PurposeRecurrently mutated genes in myelodysplastic syndrome (MDS) are pathogenic drivers andpowerfully associated with clinical phenotype and prognosis. Whether these types of mutationspredict outcome after allogeneic hematopoietic stem-cell transplantation (HSCT) in patients withMDS is not known.

Patients and MethodsWe used massively parallel sequencing to examine tumor samples collected from 87 patients withMDS before HSCT for coding mutations in 40 recurrently mutated MDS genes.

ResultsMutations were identified in 92% of patients, most frequently in the ASXL1 (29%), TP53 (21%),DNMT3A (18%), and RUNX1 (16%) genes. In univariable analyses, only TP53 mutations wereassociated with shorter overall (OS; hazard ratio [HR], 3.74; P ! .001) and progression-free survival(HR, 3.97; P ! .001). After adjustment for clinical variables associated with these end points,mutations in TP53 (HR, 2.30; P " .027), TET2 (HR, 2.40; P " .033), and DNMT3A (HR, 2.08; P ".049) were associated with decreased OS. In multivariable analysis including clinical variables,complex karyotype status, and candidate genes, mutations in TP53 (HR, 4.22; P ! .001) and TET2(HR, 1.68; P " .037) were each independently associated with shorter OS. Nearly one half ofpatients (46%) carried a mutation in TP53, DNMT3A, or TET2 and accounted for 64% of deaths.Three-year OS in patients without these mutations was 59% (95% CI, 43% to 72%), versus 19%(95% CI, 9% to 33%) in patients with these mutations.

ConclusionMutations in TP53, TET2, or DNMT3A identify patients with MDS with shorter OS after HSCT.

J Clin Oncol 32:2691-2698. © 2014 by American Society of Clinical Oncology

INTRODUCTION

Diagnosis and predicted prognosis of patients withmyelodysplastic syndrome (MDS) are largely deter-mined by morphologic and clinical measures.1,2 Re-current somatic mutations, which are drivers ofMDS pathogenesis and can be powerfully associatedwith clinical phenotype, are not currently incorpo-rated into the routine clinical care of patients withthis disorder.3,4 Somatic mutations are common inMDS, with#75% of patients carrying"one abnor-mality in the 30 most frequently mutated genes.5-7

Abnormalities in specific genes, such as NRAS,RUNX1, and TP53, have been associated with prog-nostically important variables, including elevatedbone marrow blast proportion and severe thrombo-

cytopenia.3 Therefore, it is likely that acquired mu-tations could also predict response to specificinterventions, such as treatment with hypomethy-lating agents or survival after hematopoietic stem-cell transplantation (HSCT).8

Calculation of risks, benefits, and timing ofHSCT is often difficult in MDS.9-11 Older age andcomorbidities typical of patients with MDS are fre-quently associated with unacceptable risk of earlydeath after transplantation. Even in younger andgenerally healthier patients, deciding when HSCT isappropriate can be challenging. In particular, pa-tients with poor prognostic features may be directedto transplantation because they have few treatmentoptions available or because standard therapeuticsare not expected to provide durable responses.

JOURNAL OF CLINICAL ONCOLOGY O R I G I N A L R E P O R T

VOLUME 32 ! NUMBER 25 ! SEPTEMBER 1 2014

© 2014 by American Society of Clinical Oncology 2691Information downloaded from jco.ascopubs.org and provided by at INSERM on September 11, 2014 from 193.54.110.33

Copyright © 2014 American Society of Clinical Oncology. All rights reserved.

these genes were found in nearly one half of patients in this cohort.Mutations of other genes associated with poor prognosis in priorstudies, such as RUNX1, ASXL1, SRSF2, and U2AF1, were not associ-ated with differences in OS in our cohort of patients who underwentHSCT (Data Supplement).3,22-24 This may have been the result ofdisease-modifying effects of conditioning and transplantation or be-cause of the fact that the prognostic significance of these gene muta-tions is more pronounced in lower-risk patients, of whom there werefew in this study. In contrast, TP53 mutations have independentprognostic value, even in higher-risk patients with MDS, in whomthey are most commonly found.3,21

The DNMT3A and TET2 genes encode epigenetic modifiers thatregulate DNA methylation, and both are recurrently mutated in MDS,acute myeloid leukemia, and other hematologic malignancies. Inacute myeloid leukemia, mutations of both genes are enriched inpatients with intermediate-risk karyotypes and are associated withpoor prognosis.25,26 In MDS, the clinical significance of DNMT3Amutations is less clear but also seems to be unfavorable, whereas TET2mutations are not associated with survival.5,7,18,19,27,28 Both TET2 andDNMT3A mutations are relatively promiscuous and often co-occurwith other mutated genes that can predict outcomes. For example, ina study of lower-risk patients with MDS, DNMT3A mutations werenot associated with OS in univariable analysis. However, theDNMT3A-mutant/SF3B1-wild-type subgroup did have shorter OS.19

In our transplantation cohort of largely higher-risk patients, SF3B1mutations were rare, and most DNMT3A-mutant samples wereSF3B1 wild type (88%).

DNMT3A and TET2 mutations identified in pretransplantationsamples were largely from patients without adverse clinical featuresknown to predict poor outcome. Most of these patients did not have acomplex karyotype and were not more likely to have an elevated bonemarrow blast percentage before transplantation. Nevertheless, wefound that patients with a TET2 or DNMT3A mutation were at in-creased risk of relapse and death after transplantation, particularlywhen other predictive variables were considered. We conclude thatconsideration of TET2 and DNMT3A mutation status can help pre-dict the risk of mortality in patients with MDS.

In MDS, TP53 mutations have long been known to be associatedwith karyotype, elevated bone marrow blast percentage, and severethrombocytopenia.3,29-31 Despite these links with prognostically ad-verse clinical features, TP53 mutations have strong and independent

A

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TP53 18

TET2 11

DNMT3A 16

Fig 2. Overall survival (OS) by TP53 and DNMT3A mutation status. OS ofpatients (A) with and without complex karyotype and (B) with complex karyotypestratified by TP53 mutation status and compared with survival of patients withnoncomplex karyotype; (C) OS and mutation distribution showing overlap be-tween patients with TP53, TET2, and DNMT3A mutations. Each column indicatesindividual patient; colored bars represent mutations of genes in that row.

Table 3. Multivariable! Models Identifying Independent SignificantRisk Factors for OS

Variable HR 95% CI P

Entire cohort (N ! 87)Genetic mutation (present v absent)

TP53 4.22 2.30 to 7.76 " .001TET2 2.29 1.05 to 5.00 .037

Day-100 landmark analysis (n ! 72)Karyotype (complex v other) 2.85 1.35 to 6.47 .013Genetic mutation (present v absent)

TP53 3.78 1.81 to 7.89 " .001DNMT3A 2.62 1.15 to 5.96 .022

Abbreviations: HR, hazard ratio; OS, overall survival.!Final model obtained from backward-elimination selection algorithm candi-

dates included variables with univariable P " .20.

Somatic Mutations Predict Survival After Transplantation for MDS

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Copyright © 2014 American Society of Clinical Oncology. All rights reserved.

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haematologica | 2011; 96(3)

DECISION MAKING AND PROBLEM SOLVING

441

Risk stratification based on both disease status and extra-hematologic comorbidities in patients with myelodysplastic syndrome Matteo G. Della Porta,1 Luca Malcovati,1 Corinna Strupp,2 Ilaria Ambaglio,1 Andrea Kuendgen,2 Esther Zipperer,2Erica Travaglino,3 Rosangela Invernizzi,3 Cristiana Pascutto,1 Mario Lazzarino,1 Ulrich Germing,2 and Mario Cazzola1

1Department of Hematology Oncology, University of Pavia and Fondazione IRCCS Policlinico San Matteo, Pavia, Italy; 2Department of Hematology, Oncology and Clinical Immunology, Heinrich-Heine-University, Dusseldorf, Germany; and 3Department of Medicine, University of Pavia & Fondazione IRCCS Policlinico San Matteo, Pavia, Italy

The incidence of myelodysplastic syndromes increases withage and a high prevalence of co-morbid conditions has beenreported in these patients. So far, risk assessment in myelodys-plastic syndromes has been mainly based on disease status.We studied the prognostic impact of comorbidity on the nat-ural history of myelodysplastic syndrome with the aim ofdeveloping novel tools for risk assessment. The study popula-tion included a learning cohort of 840 patients diagnosed withmyelodysplastic syndrome in Pavia, Italy, and a validationcohort of 504 patients followed in Duesseldorf, Germany.Information on comorbidity was extracted from detailedreview of the patients’ medical charts and laboratory values atdiagnosis and during the course of the disease. Univariableand multivariable survival analyses with both fixed and time-dependent covariates were performed using Cox’s proportion-al hazards regression models. Comorbidity was present in54% of patients in the learning cohort. Cardiac disease wasthe most frequent comorbidity and the main cause of non-leukemic death. In multivariable analysis, comorbidity had asignificant impact on both non-leukemic death (P=0.01) andoverall survival (P=0.02). Cardiac, liver, renal, pulmonary dis-ease and solid tumors were found to independently affect therisk of non-leukemic death. A time-dependent myelodysplas-tic syndrome-specific comorbidity index (MDS-CI) was devel-

oped for predicting the effect of comorbidity on outcome.This identified three groups of patients which showed signif-icantly different probabilities of non-leukemic death (P<0.001)and survival (P=0.005) also in the validation cohort. Landmarksurvival analyses at fixed time points from diagnosis showedthat the MDS-CI can better define the life expectancy ofpatients with myelodysplastic syndrome stratified accordingto the WHO-classification based Prognostic Scoring System(WPSS).Comorbidities have a significant impact on the out-come of patients with myelodysplastic syndrome. Accountingfor both disease status by means of the WPSS and comorbidi-ty through the MDS-CI considerably improves risk stratifica-tion in myelodysplastic syndromes.

Key words: risk stratification, comorbidity, myelodysplasticsyndrome.

Citation: Della Porta MG, Malcovati L, Strupp C, Ambaglio I,Kuendgen A, Zipperer E, Travaglino E, Invernizzi R, Pascutto C,Lazzarino M, Germing U and Cazzola M. Risk stratificationbased on both disease status and extra-hematologic comorbiditiesin patients with myelodysplastic syndrome. Haematologica2011;96(3):441-449. doi:10.3324/haematol.2010.033506

©2011 Ferrata Storti Foundation. This is an open-access paper.

ABSTRACT

The first two authors equally contributed to this work.Funding: this study was supported by grants from the Associazione Italiana per la Ricerca sul Cancro (AIRC), Fondazione Cariplo, and Regione Lombardia,Milan, Italy to MC. Manuscript received on September 12, 2010. Revised version arrived on November 16, 2010. Manuscript accepted November 19, 2010.Correspondence: Mario Cazzola, MD, Department of Hematology Oncology, University of Pavia Medical School & Fondazione IRCCS Policlinico San Matteo,27100 Pavia, Italy. E-mail: [email protected]

Introduction

Myelodysplastic syndromes (MDS) represent one of themost common hematologic malignancies in Western coun-tries.1 Their annual incidence increases dramatically with age,from 0.4 cases per 100,000 under the age of 30 to about 40cases per 100,000 population over the age of 65.2-4 These fig-ures might nevertheless underestimate the real incidence ofmyelodysplastic syndromes, as a recent study conducted with-in US Medicare beneficiaries aged 65 years or more calculatedan incidence of 162 per 100,000 for 2003,5 yielding a total of45,000 new cases per year in the US.

Myelodysplastic syndromes are heterogeneous disordersranging from indolent conditions with a near-normal life

expectancy to forms approaching acute myeloid leukemia(AML).1 The World Health Organization (WHO) classificationof myeloid neoplasms6 represents a very useful tool for defin-ing the different subtypes, and also provides prognostic infor-mation.7 In fact, unilineage dysplasia is associated with a betterprognosis compared with multilineage dysplasia, while thepresence of excess blasts involves a worse prognosis.7

Additional disease-related factors of considerable prognosticrelevance include cytogenetic abnormalities,8 degree of bonemarrow failure, i.e. number and severity of peripheral cytope-nias, and bone marrow fibrosis.9

In 1997, Greenberg et al.10 developed the InternationalPrognostic Scoring System (IPSS) for myelodysplastic syn-dromes, based on percentage of bone marrow blasts, cytoge-

(P=0.002). The negative effect of comorbidity on the prob-ability of non-leukemic death was noticed in all WHO cat-egories (HR 1.94-2.25, P values 0.023-<0.001), while theeffect on overall survival was mainly noticeable in sub-groups without blast excess (HR=1.8, P<0.001).

We then evaluated the prognostic effect of comorbidityby a multivariable Cox’s analysis including age, sex, WHOcategory, cytogenetics and transfusion-dependency, allassessed at the time of diagnosis. Comorbidity showed asignificant effect on both overall survival (HR 1.42, P=0.024)and probability of non-leukemic death (HR 1.55, P=0.01).When stratifying by WPSS category, the impact of comor-bidity on overall survival and risk of non-leukemic deathwas significant in the very-low, low, and intermediateWPSS risk groups (OS: HR 3.56-1.95, P values 0.02-0.031;NLD: HR 3.89-2.45, P values 0.01-0.026).

Two-hundred and three patients (24%) developedcomorbidity during follow up, the occurrence of cardiac dis-ease representing the most frequent event (39%). In multi-variable analysis with time-dependent covariates, the onsetof comorbidity at any time during the clinical course had asignificant effect on overall survival (HR=1.51, P=0.01) andrisk of non-leukemic death (HR=2.29, P<0.001).

Prognostic effect of currently available comorbidityindices and development of an MDS-specificcomorbidity index (MDS-CI)

We calculated the HCT-CI and CCI in the learning cohortat the time of diagnosis. In multivariable analysis includingage, sex, WHO category, cytogenetics and transfusion-dependency, the CCI did not show any significant effect onthe risk of non-leukemic death and overall survival (P=0.13

and P=0.11, respectively), while the HCT-CI showed a bor-derline effect on the risk of non-leukemic death (HR 1.32,P=0.064) and no effect on overall survival (HR 1.18, P=0.10).

In order to define the MDS-CI, we performed multivari-able Cox’s survival analyses with fixed and time-dependentcovariates in the learning cohort, including all the comor-bidities that were found to have a significant effect on non-leukemic death in univariable analysis (cardiac disease, dia-betes, cerebrovascular disease, moderate-to-severe hepaticdisease, severe pulmonary disease, renal disease and solidtumor; HR 2.49-4.82, P values ranging between 0.018 and<0.001). Cardiac disease (HR 3.57, P<0.001), moderate tosevere liver disease (HR 2.55, P=0.01), severe pulmonarydisease (HR 2.44, P=0.005), renal disease (HR 1.97, P=0.04)and solid tumors (HR 2.61, P<0.001) were found to inde-pendently affect the risk of non-leukemic death, while dia-betes and cerebrovascular disease did not retain their prog-nostic value. As shown in Table 3, each comorbidity wasassigned a score proportional to the regression coefficient ofthe multivariable Cox’s proportional hazards model. TheMDS-CI score was calculated as the sum of these weightedscores, and then categorized into three risk groups: low(score equal to 0), intermediate (score equal to 1 or 2), andhigh risk (score equal to 3 or higher).

In the learning cohort, 546 (65%) patients were classifiedas low, 244 (29%) as intermediate, and 50 (6%) as high riskat diagnosis. The MDS-CI risk groups showed significantlydifferent probabilities of overall survival (P<0.001) and non-leukemic death (P<0.001) (Figure 1A). In multivariableanalysis considering age, sex, WHO categories, cytogenet-ics and transfusion-dependency, the MDS-CI maintained asignificant effect on both non-leukemic death (HR 1.89,P<0.001) and overall survival (HR 1.67, P<0.001). We car-ried out the same multivariable analysis without censoringfollow up at the time of therapeutic intervention (14% ofpatients in the learning cohort received erythropoiesis stim-ulating agents, 1% received immunosuppressive therapy, 4patients received lenalidomide, 8% received low-dosechemotherapy, 5% underwent AML-like chemotherapy atthe time of leukemic evolution, 4% underwent allo-stemcell transplantation, while no patient received treatmentwith hypomethylating agents). In this model, the MDS-CIretained a significant effect on both non-leukemic death(HR 1.81, P<0.001) and overall survival (HR 1.62, P<0.001).

We then evaluated the effect of changes over time of theMDS-CI by time-dependent Cox’s survival analyses.Longitudinal data on comorbidity were available for 725patients. To exclude potential selection bias, we comparedthe repeated-measures cohort and patients evaluated atdiagnosis only, and found no statistically significant differ-ence in characteristics at diagnosis and overall survival. Inunivariable analysis, the MDS-CI significantly affected therisk of non-leukemic death (HR 2.80, P<0.001) and overallsurvival (HR 1.92, P<0.001) (Figure 1A and B). These resultswere confirmed in multivariable analysis, including age,sex, WHO categories, cytogenetics and transfusion-depen-dency as time-dependent covariates (NLD: HR 2.89,P<0.001; overall survival: HR 2.41, P<0.001).

Finally, we calculated the risk of progression to a higherMDS-CI category during the course of the disease. Thecumulative hazard of MDS-CI progression was 0.32 for thewhole MDS population. A significantly higher risk of MDS-CI progression was found in transfusion-dependent com-pared with transfusion-independent patients (cumulativehazard: 0.71 vs. 0.09, P<0.001) (Figure 2).

M.G. Della Porta et al.

444 haematologica | 2011; 96(3)

Table 3. Calculation of the MDS-specific comorbidity index (MDS-CI).The five comorbidities listed were found to be independently associat-ed with the risk of NLD in multivariable analysis, and each of them wasassigned a score proportional to the regression coefficient of the mul-tivariable Cox’s proportional hazards model. This score is taken intoaccount if the specific comorbidity is present, and the MDS-CI isobtained as the sum of individual variable scores.Comorbidity HR obtained through a Variable weighted multivariable Cox’s score (to be taken survival analysis into account if with NLD the specific as an outcome comorbidity is present)

Cardiac disease 3.57 (P<0.001) 2Moderate-to-severe 2.55 (P=0.01) 1hepatic disease Severe pulmonary disease 2.44 (P=0.005) 1Renal disease 1.97 (P=0.04) 1Solid tumor 2.61 (P<0.001) 1

MDS-CI risk Sum of individual variable Proportion of scores patients in the learning cohort belonging to the risk group (%)

Low risk 0 546/840 (65%)Intermediate risk 1-2 244/840 (29%)High risk >2 50/840 (6%)

NLD: non-leukemic death.

Validation of MDS-CIThe prognostic value of MDS-CI was tested in an inde-

pendent cohort of 504 patients diagnosed at the Heinrich-Heine-University Hospital, Dusseldorf, Germany. A signifi-cant difference between the learning and validation cohortswas found in age (median age 73 years in the German vs. 66years in the Italian cohorts, P<0.001) as well as in WPSSsubgroups, with a higher proportion of higher risk patientsin the validation cohort (P<0.001). These differences result-ed in Italian patients having a better survival (P=0.001). Asignificantly higher prevalence of cardiac (39% vs. 25%,P<0.001) and severe pulmonary disease (9% vs. 2%,P<0.001) was found in the validation as compared to thelearning cohort.

At diagnosis, 245 out of 504 (49%) patients of the valida-tion cohort were classified as low-risk, 194 (38%) as inter-mediate-risk and 65 (13%) as high-risk according to theMDS-CI, with a significantly higher proportion of high-riskpatients compared to the learning cohort (P<0.001). TheMDS-CI risk groups showed significantly different proba-bilities of overall survival (P=0.005) and non-leukemic death(P<0.001). In multivariable analysis, MDS-CI showed anindependent negative effect on both non-leukemic death(HR 1.44, P<0.001) and overall survival (HR 1.30, P<0.001).

We next evaluated the effect of changes over time of theMDS-CI through time-dependent Cox’s survival analyses.Longitudinal data on comorbidity were available for 192patients. No significant differences in the clinical character-istics at diagnosis and in overall survival were foundbetween the repeated-measures cohort and patients evalu-ated at diagnosis only. In univariable analysis, the MDS-CIsignificantly affected the risk of overall survival (HR 2.09,P<0.001) and non-leukemic death (HR 2.46, P<0.001)(Figure 1C and D). These effects were maintained in multi-variable analysis (NLD: HR 1.49, P<0.001; OS: HR 1.31,P<0.001).

A comparison of hazard ratios obtained for overall sur-vival and non-leukemic death in the learning and in the val-idation cohort showed no relevant differences. This wasconfirmed by a multivariable analysis on the pooled datasetin which there was no significant difference in the effect ofthe MDS-CI on patient outcome between the two cohorts.

Risk stratification of MDS patients based on both disease status and extra-hematologic comorbidities

In order to verify whether the comorbidity assessmentprovided by the MDS-CI could improve the WPSS prognos-tic stratification of myelodysplastic syndrome patients, wefitted two separate multivariable Cox’s time-dependentanalyses including age, sex and WPSS category as covariateswith and without MDS-CI, respectively, and compared

Risk assessment in MDS

haematologica | 2011; 96(3) 445

Figure 1. Relationshipbetween MDS-CI catego-ry, risk of non-leukemicdeath and overall sur-vival in the learning andvalidation cohorts ofMDS patients. (A-B)Italian learning cohort;(A) Probability of overallsurvival according totime-dependent MDS-CIrisk. (B) Probability ofnon-leukemic deathaccording to time-depen-dent MDS-CI risk. (C-D);German validationcohort. (C) Probability ofoverall survival accordingto time-dependent MDS-CI risk. (D) Probability ofnon-leukemic deathaccording to time-depen-dent MDS-CI risk.

Figure 2. Risk of progression to a higher MDS-CI category during thecourse of the disease. Cumulative hazard of MDS-CI progression inthe Italian cohort according to the presence or absence of transfu-sion dependency.

1.00.90.80.70.60.50.40.30.20.10.0

0 24 48 72 96 120 144 168 192 216 240 264 288 312Time (months)

0 24 48 72 96 120 144 168 192 216 240 264 288 312Time (months)

0 24 48 72 96 120 144 168 192 216 240 264 288 312Time (months)

0 24 48 72 96 120 144 168 192 216 240 264 288 312Time (months)

0 24 48 72 96 120 144 168 192 216 240Time (months)

Low riskIntermediate riskHigh risk

Cum

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Transfusion-independent patientsTransfusion-dependent patients

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Low riskIntermediate riskHigh risk

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SMD  •  Épidémiologie  

•  Physiopathologie  

•  Diagnos4c  

•  Classifica4on  et  pronos4c  

•  Traitement  

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Pour le traitement, on divise schématiquement les SMD en:

1. SMD de faible risque: •  IPSS faible ou int 1

2. SMD de risque élevé •  IPSS int 2 ou élevé

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SMD: buts du traitement

•  Éviter l’évolution en LAM

•  Prolonger la survie

•  Corriger les cytopénies

•  Améliorer la qualité de vie

LAM, leucémie aiguë myéloblastique

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SMD: buts du traitement (haut risque)

•  Éviter l’évolution en LAM

•  Prolonger la survie

•  Corriger les cytopénies

•  Améliorer la qualité de vie

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SMD: buts du traitement (faible risque)

•  Éviter l’évolution en LAM •  Prolonger la survie •  Corriger les cytopénies •  Améliorer la qualité de vie

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Traitement des SMD de haut risque

•  Allogreffe de moelle •  Chimiothérapie •  Agents hypométhylants

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Traitement des SMD de faible risque

•  Anémie +++ •  Thrombopénie •  neutropénie

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0 30 60 90 120 150 180 210

Hb

(g/d

L)

Days of treatment

8

12

14

10

4

6

Transfusion given

Active drug

Blood transfusion

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Quality of Life is correlated to Hb levels

Hb level (g/dl) LASA: Linear Analog Scale Assessment

Qua

lity

of L

ife

(LA

SA, m

m)

45

50

55

60

65

7 8 9 10 11 12 13 14

Crawford et al. Cancer 2002; 95: 888–95

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Anemia and risk of falling

(1)   Dharmarajan et al., Hematology, 2005, Vol. 60, p 24 (2)   Dharmarajan et al., J Am Med Dir Assoc, 2004, Vol. 5, p 395-400

N=500

+1g/dl Hb = 45% reduction in the risk of fractures (2)

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Traitement de l’anémie des SMD •  Première ligne

–  Agents stimulants l’érythropoièse (Erythropoiétine, darbepoiétine)

–  Lenalidomide (Revlimid) (del 5q)

•  Traitements de 2ème ligne

•  Chélation du fer ?

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Groupe francophone des myélodysplasies (GFM)

•  Centres en France, Belgique, Suisse, •  Activation d’essais cliniques •  Registre des SMD •  Liens avec les autorités de santé (HAS, CNAM) •  Liens avec les groupes internationaux

–  MDS Foundation –  European Leukemia Net

•  Liens avec CCM