2nd Workgroup and 3rd Management Committee Meeting...

and

5th ELN Workshop “Genetics of MDS”

2nd Workgroup and 3rd Management Committee Meeting

of the EuGESMA COST Action BM0801:

European Genetic and Epigenetic Study on MDS and AML

Hotel Mercure Atrium Hannover, Germany12 – 13 October, 2009

__________________________________________________________________________________________ COST/ELN Meeting, Hannover, Germany, 12-13 October, 2009 1

Organizers COST Action Chair Ken Mills Queen’s University Belfast Centre for Cancer Research & Cell Biology Lisburn Road Belfast BT9 7BL Northern Ireland Tel.: +44 28 9097 2786 Email: [email protected] Local Organizer Brigitte Schlegelberger Hannover Medical School Institute of Cell and Molecular Pathology Carl-Neuberg-Str. 1 30625 Hannover Germany Tel.: +49 511 532 4522 Email: [email protected] Organizing Secretariat Gill Teicke Hannover Medical School Institute of Cell and Molecular Pathology Carl-Neuberg-Str. 1 30625 Hannover Germany Tel.: +49 511 532 4523 (office); +49 177 417 6066 (mobile) Email: [email protected] Hotel Details Hotel Mercure Atrium Hannover Karl-Wiechert-Allee 68, 30625 Hannover Tel : +49 511/54070 Fax : +49 511/5407826 Email: [email protected]


PROGRAM


Program at a glance Monday, 12 October, 2009 12:00 Registration and Buffet Lunch

13:00 Welcome

Ken Mills, COST Action Chair

13:15 Invited Speaker:

Myelodysplastic syndromes – from bedside to bench

Eva Hellström-Lindberg (Karolinska Institutet)

14:15 Individual Workgroup Sessions in separate meeting rooms (see notice board)

15:45 Coffee Break

16:15 Individual Workgroup Sessions contd.

18:30 End of Workgroup Sessions

19:30 Reception and Dinner

Tuesday, 13 October, 2009 09:00 Meeting of all Workgroups

10:30 Invited Speaker:

MDS/AML in individuals with underlying genetic predispositions

Christian Kratz (NCI, NIH)

11:30 Coffee Break

12:00 Management Committee Meeting

13:30 Buffet Lunch

15:00 Depart


Monday, 12 October, 2009: Workgroup Session WG1 Chairs: Lars Bullinger (Germany), Margarita Guenova (Bulgaria)

14:15 Introduction Lars Bullinger

14:30 Brief introduction of participants

14:45 Identification of aberrantly regulated genes and candidate drugs in APL Kim Theilgaard-Mönch (Denmark)

15:00 Characterization of a gene expression classifier of normal myeloid differentiation stages, to select sub-groups of myeloid leukemias with different alteration of cellular pathways, prognostic courses and/or by different responses to advanced molecular therapies: preliminary data Enrico Tagliafico (Italy)

15:15 Definition of all-trans retinoic acid gene expression signature in acute myeloid leukemia patients bearing nucleophosmin mutation (NPM1mut) without FMS-like tyrosine kinase 3- internal tandem duplication (FLT3-ITD) Krzysztof Giannopoulos (Poland)

15:30 Cytogenetic subtypes in pediatric acute myeloid leukemia are highly accurately predicted with gene expression profiling Marry M.van den Heuvel-Eibrink (Netherlands)

15:45 Coffee Break

16:15 GEP – AML Olivier Nibourel (France)

16:30 Exon microarray technology: genome-wide analysis of alternative splicing points to novel leukemia relevant genes in AML Lars Bullinger (Germany)

16:45 Gene expression profiling in the myelodysplastic syndromes James S. Wainscoat (UK)

17:00 Molecular diagnosis of low-risk myelodysplastic syndromes: from diagnostic criteria to the genetic profiles. The GEP shows important biological differences between low risk. Jesus M. Hernández (Spain)

17:15 Discussion: possible interactions, definition of a working program of WG1 All participants


Monday, 12 October, 2009: Workgroup Session WG2 Chairs: Sophie Raynaud (France), Cristina Mecucci (Italy)

14:15 Introduction Sophie Raynaud

Brief introduction of participants

14:25 Summary of EUGESMA Antwerp meeting Sophie Raynaud

MDS and ELN Chair: Cristina Mecucci

14:40 Summary of joint activity of WP8 (MDS) and WP11 (cytogenetics) of the European LeukemiaNet Christina Mecucci (Italy)

15:10 New insights into the prognosis impact of cytogenetic abnormalities in MDS Detlef Haase (Germany)

15:45 Coffee Break

ELN and EUGESMA Chair: Sophie Raynaud

16:15 Acquired segmental UPD in relapsed AML Manoj Raghavan (UK)

16:30 Genetic pathways in t-MDS and t-AML Morten T. Andersen (Denmark)

16:55 Novel prognostic subgroups in childhood 11q23/MLL-rearranged acute myeloid leukemia: results of an international retrospective study Marry M.van den Heuvel-Eibrink (Netherlands)

17:15 Hidden genomic abnormalities in karyotypically normal and del5q MDS using oligonucleotide array CGH Brigitte Royer-Pokora (Germany)

Perspectives for collaborative scientific projects Chairs: Cristina Mecucci and Sophie Raynaud

17:30 High resolution genomic karyotyping of monosomy 7/del(7q) Azim Mohamedali (UK)

17:45 Round Table

18:20 Workgroup summary, concluding remarks Sophie Raynaud


Monday, 12 October, 2009: Workgroup Session WG3 Chairs: Brigitte Schlegelberger (Germany), Sören Lehmann (Sweden)

14:15 Introduction Brigitte Schlegelberger

14:30 Brief introduction of participants

14:40 Gene specific and global methylation patterns predict out come in patients with acute myeloid leukemia Sören Lehmann (Sweden)

14:50 Epigenetic profiling in AML Christoph Plass (Germany)

15:10 Current approaches for the analyses of histone modification patterns in hematopoiesis and leukemia Carsten Müller-Tidow (Germany)

15:30 Equitoxic doses of 5-azacytidine and 5-aza-2’-deoxycytidine upregulate an overlapping subset of cancer/testis antigens and microRNAs Kirsten Grønbæk (Denmark)

15:45 Coffee Break

16:15 New methods to study DNA methylation Giovanni Perini (Italy)

16:30 Lineage-specific DNA methylation in T cells correlates with histone methylation and enhancer activity Christian Schmidl (Germany)

16:45 MicroRNA-196a and –196b are differentially expressed between and within cytogenetic and molecular subtypes of pediatric AML, and high expression is correlated to overexpression of HOX genes Jenny Kuipers (Netherlands)

17:00 Global and gene specific hypermethylation in bone marrow samples from MDS patients Ulrich Lehmann (Germany)

17:15 Telomere shortening and chromosomal instability in myelodysplastic syndromes Gudrun Göhring (Germany)


17:30 Aberrant DNA methylation characterizes juvenile myelomonocytic leukemia (JMML) with poor outcome Christian Flotho (Germany)

17:45 Proposal: Review on epigenetics in AML/MDS Sören Lehmann, Brigitte Schlegelberger

18:00 Discussion: possible interactions, definition of a working program of WG3 All participants


Monday, 12 October, 2009: Workgroup Session WG4 Chairs: Rose Ann Padua (France), Nevena Veljkovic (Serbia)

14:15 Introduction Rose Ann Padua


14:25 Retrovirally modified hematopoietic cells in murine leukemia models Christopher Baum (Germany)

14:50 A Phase II study to assess efficacy and safety of a DNA based vaccine associated with ATRA as add-on therapy in patients with chronic hematological diseases Philippe Rousselot (France)

15:15 A novel anti-Wilms-Tumour-1 (WT1) vaccination strategy in haematological cancer using DNA fusion vaccines delivered with electroporation Christian Ottensmeier (UK)

15:45 Coffee Break

16:15 A phase I study to assess safety of WT1 peptide vaccination in nonmyeloablative chemotherapy-induced lymphopenic acute myeloid leukemia patients in complete remission Antonio Curti (Italy)

16:40 Molecular and clinical features of refractory anemia with ringed sideroblasts associated with marked thrombocytosis (RARS-T) Matteo Della Porta (Italy)

17:05 Clonality studies using acquired mitochondrial DNA point mutations Norbert Gattermann (Germany)

17:30 Mislocalized activation of Flt3-ITD switches downstream signaling outcomes Hubert Serve (Germany)

17:55 General discussion: FP7 2009 and 2010 All participants


Monday, 12 October, 2009: Workgroup Session WG5 Chair: Martin Dugas (Germany)

14:15 Introduction Martin Dugas


14:25 Leukemia Gene Atlas Martin Dugas (Germany)

14:45 Machine learning applied to unravel a biomarker gene network associated to AMLs in contrast to other leukemias Javier De Las Rivas (Spain)

15:05 Analysis of transcriptional and post-transcriptional regulatory networks Silvio Bicciato (Italy)

15:25 Discussion of WG outcomes All participants

15:45 Coffee Break

16:15 Data fusion for cancer genomics Leo Lahti (Finland)

16:35 Filtering of low-signal probesets improves enrichment analysis in microarray studies Lucjan S. Wyrwicz (Poland)

16:55 Independence screening approaches for Cox models with high dimensionality Axel Benner (Germany)

17:15 Mediante: a web-based microarray data manager Chimène Moreilhon-Brest (France)

17:35 Discussion of WG outcomes All participants


ABSTRACTS


Workgroup 1: miRNA/mRNA Expression Profiling

Identification of aberrantly regulated genes and candidate drugs in APL

Troels T Marstrand 1,2, Rehannah Borup3, Anton Willer Skov1,5, Lars C Jacobsen4, Niels Borregaard4, Bo T

Porse1,5, Albin Sandelin1,2, Kim Theilgaard-Mönch1,5,6

1Biotech and Research Innovation Center, 2 The Bioinformatics Centre, Department of Biology, 3Department of Clinical Biochemistry, Rigshospitalet, 4The Granulocyte Research Laboratory, Department

of Hematology, Rigshospitalet, 5The Laboratory for Gene Therapy Research, Rigshospitalet, all at

University of Copenhagen, Copenhagen, Denmark. 6 Deparment of Hematology, University Hospital of

Lund, Lund, Sweden.

Chromosomal translocations of transcription factors generating fusion proteins with aberrant

transcriptional activity are common in acute leukemia. In acute promyelocytic leukemia (APL) the PML-

RARA fusion protein acts as a transcriptional repressor that blocks neutrophil differentiation at the

promyelocyte (PM) stage. Here, we performed a comprehensive comparison of gene expression profiles

and promoter features of APL cells (i.e. “leukemic” PMs) and normal PMs to uncover the global gene

expression signature and the underlying regulatory regimen that emerges as a consequence of PML-

RARA expression and secondary genetic aberrations in human APL.

Comparison of gene expression profiles of APL cells and promyelocytes (PMs) identified an APL

signature of dysregulated genes including well-characterized oncogenes and tumor suppressors.

Promoter analysis of the aberrantly expressed genes in APL identified a transcriptional regime that can

promote malignant transformation and HSC maintenance/self-renewal but lacked the ability to direct

neutrophil differentiation. Consistent with these findings, gene set enrichment analysis demonstrated

that APL cells differ from PMs by partial expression of a stemness signature, which suggests that genes

critical for HSC maintenance/self-renewal are associated with malignant transformation in human APL

cells. Correlating these expression signatures with expression profiles resulting from drug treatments

identified three candidate drugs that might be used as supplements in current APL treatment protocols.

Collectively, the present study provides a conceptual framework for the identification of dysregulated

genes in acute leukemia as well as novel candidate drugs for treatment.


Characterization of a gene expression classifier of normal myeloid differentiation stages, to select sub-groups of myeloid leukemias with different alteration of cellular pathways, prognostic courses and/or by different responses to advanced molecular therapies: preliminary data

Enrico Tagliafico, Silvio Bicciato, Sergio Ferrari

Center for Genome Research, University of Modena and Reggio Emilia, Via G. Campi 287, 41125

Modena, Italy

A differentiation block and an accumulation of blast cells in the hematopoietic compartment distinguish

acute myelogenous leukemia (AML) from other neoplasias. In perspective, the identification of the

molecular mechanisms behind the differentiation block could disclosure novel strategies of therapeutic

intervention to cure myeloid leukemia. Unfortunately, the extreme complexity and the context specificity

of these mechanisms are still hampering the formulation of a mechanistic model that can, in turn, be

translated into a therapeutic target. This heterogeneity can be explained by the fact that the

differentiation block occurring in different myeloid leukemias is definitely mediated by mechanisms,

which are different from each level of myeloid maturation. We have already approached this field

identifying a signature predictive of in vitro sensitivity to differentiation induction in acute myeloid

leukemia. Now we are trying to validate an “in vivo” signature, in collaboration with Lars Bullinger

(University of Ulm, Germany), using a gene expression dataset obtained from AML patients enrolled in a

clinical trial, coordinated by the Ulm University, testing the efficacy of ATRA in combination with

standard induction in older patients. In addition, since the identification of the mechanisms interfering

with myeloid maturation were so far studied without any systematic comparison between each level of

differentiation block in normal and pathological state, we are testing a gene expression classifier

validated on a normal hematopoietic meta-dataset, able to classify the different differentiation stages of

normal myelopoiesis, to select sub-groups of myeloid leukemias that resemble, at the genomic level,

known differentiation levels. These sub-groups could in turn be characterized by different alteration of

cellular pathways, prognostic courses and/or by different responses to advanced molecular therapies.


Definition of all-trans retinoic acid gene expression signature in acute myeloid leukemia patients bearing nucleophosmin mutation (NPM1mut) without FMS-like tyrosine kinase 3- internal tandem duplication (FLT3-ITD)

Krzysztof Giannopoulos, Lars Bullinger

Clinical Immunology Department, Medical University of Lublin, Lublin, Poland

Internal Medicine III Department, University of Ulm, Ulm, Germany

Nucleophosmin (NPM) is a nuclear molecule that is involved with several important mechanisms such as

control of cell cycle, proliferation or differentiation. Mutations of the NPM1 (NPM1mut) in exon 12 lead

to the expression of a cytoplasmic mutant protein. NPM1mut represents the most frequent genetic

abnormality found in about 30% of acute myeloid leukemia (AML) patients. Cytoplasmic localization of

NPM1mut disables interaction with nuclear ARF, thereby inhibiting antioncogenic and suppressing effect

of ARF-MDM2-p53 signaling pathway. Clinically, NPM1mut seems not only to bear prognostic value, but

also to be predictive of therapeutic response to therapy with all-trans retinoic acid (ATRA). Especially,

AML patients with NPM1mut lacking FMS-like tyrosine kinase 3- internal tandem duplication (FLT3-ITD)

seem to benefit to the highest extent of the ATRA treatment as was recently shown by increased

relapse-free and overall survival (Schlenk et al. Haematologica 2009). This important clinical

observation suggests not only that patients bearing positive prognosis respond to therapy better, but

also that some signal transduction pathways are specifically targeted by ATRA. Identification of gene

expression signature might help not only to define specific targets of ATRA but also provide novel

targets for therapy for this particular group of AML patients. In the current project, we plan to assess

gene expression of primary AML samples treated in vitro with ATRA, especially samples derived form

patients with NPM1mut and without FLT3-ITD. These signatures will then be compared to diagnostic

profiles of AML patients who responded to ATRA with the idea to gain novel insights into the

mechanisms underlying both NPM1mut and the response to ATRA treatment in non-APL leukemia. These

studies will be performed in collaboration with Enrico Tagliafico and Silvio Bicciato.


Cytogenetic subtypes in pediatric acute myeloid leukemia are highly accurately predicted with gene expression profiling

B.V. Balgobind, M.M. Van den Heuvel-Eibrink, R.X. Menezes, D. Reinhardt, I.H.I.M. Hollink,

T.J.C.M. Peters, E.R. van Wering, G.J.L. Kaspers, J. Cloos, E. de Bont, J. Cayuela, A. Baruchel, J. Trka, J.

Stary, H.B. Beverloo, R. Pieters, C.M. Zwaan and M.L. den Boer

Pediatric acute myeloid leukemia (AML) is a heterogeneous disease, in which early treatment response

and cytogenetic abnormalities are the most important prognostic factors. AML is thought to arise from

two different types of genetic aberrations, i.e. type-I (proliferation enhancing) mutations and type-II

(differentiation impairing) mutations. Conventional karyotyping, FISH and RT-PCR are performed to

detect these aberrations. However sensitivity of these techniques is not 100%, resulting in false-

negative results. Therefore new diagnostic tools are needed. Recent studies have focused on the

potential to use gene expression profiling (GEP) to classify AML.

To determine whether gene expression signatures could correctly predict cytogenetic and molecular

subtypes in a second and independent group of pediatric AML cases, we used Affymetrix Humane

Genome U133 plus 2.0 oligonucleotide microarrays to generate gene expression profiles of 257

children with AML. Probe set intensities were normalized using the variance stabilization (VSN)

procedure of R (version 2.2.0). This group was divided into a training cohort (n=170) and a validation

cohort (n=87). The training cohort was further subdivided into a group of patients to identify the

number of predictive genes to build a classifier and a 2nd group to test the accuracy of this classifier.

Differentially expressed genes between AML subtypes were calculated using an empirical Bayes linear

regression model corrected for random effects, and corrected for multiple testing (Bioconductor

package: Limma).

The classifier was built with 75 probe sets, based on MLL-gene rearrangements, t(8;21), inv(16),

t(15;17) and t(7;12). This classifier could reliably predict these subtypes, representing 50% of the

patients. Moreover, when applied to the independent validation cohort of 87 patients, this classifier

achieved a mean accuracy and sensitivity of more than 99% to correctly predict the cytogenetic

subtypes in this independent validation cohort. Although it was not possible to classify the molecular

aberrations NPM1, CEBPa, MLL-PTD, FLT3, C-KIT, RAS or PTPN11 after controlling for cytogenetic

subtypes, we observed different gene expression signatures in patients with FLT3-ITD depending on the

cytogenetic subtype. Especially a high expression of the HOXB-cluster was specific for FLT3-ITD in

patients with normal cytogenetics.


In conclusion, GEP can correctly predict 50% of the patients in pediatric AML, with a high accuracy and

high sensitivity. Therefore GEP could be a powerful new diagnostic tool in pediatric AML and replace

current diagnostic strategies. More prospective studies are needed to confirm this first major step in the

classification of pediatric AML.

___________________________________________________________________________

No abstract available for:

GEP – AML

Olivier Nibourel


Exon microarray technology: genome-wide analysis of alternative splicing points to novel leukemia relevant genes in AML

Anna Dolnik1, Andreas Gerhardinger2, Ulla Botzenhardt1, Sabrina Heinrich1, Richard F. Schlenk1,

Hartmut Döhner1, Konstanze Döhner1, Karlheinz Holzmann2, Lars Bullinger1 1Department of Internal Medicine III, University Hospital of Ulm, Ulm, Germany 2Chip Facility/ZKF, University Hospital Ulm, 89069 Ulm, Germany.

Alternative mRNA splicing represents an effective mechanism of regulating gene function as well as a

key element to increase the coding capacity of the human genome. Today, an increasing number of

reports illustrates that aberrant splicing events can contribute to human disease and that alterations in

the splicing machinery are common and functionally important for cancer development. Aberrant splice

forms can for example have genome-wide effects by deregulating key signaling pathways. However, for

most of the aberrant mRNA transcripts detected it remains unclear whether they directly contribute to

the malignant phenotype or just represent a by-product of cellular transformation. Thus, more

comprehensive analyses of the transcriptome splicing are warranted in order to get novel insights into

the biology underlying malignancies like, e.g., acute myeloid leukemia (AML).

Here, we performed a genome-wide screening of splicing events in AML using the Exon microarray

platform GeneChip Human Exon 1.0 ST (Affymetrix). We analyzed forty AML cases with complex

karyotypes and twenty Core Binding Factor (CBF) AML cases using this microarray approach allowing

the detection of splice variants. In order to detect alternative splicing events distinguishing different

leukemia subgroups we applied a commercial and an open source software tool: XRAY version 3.9

(Biotique Systems) and the OneChannelGUI package for R (version 1.10.7 available at

http://www.bioinformatica.unito.it/ oneChannelGUI/). Using XRAY supervised analysis comparing

subgroups of CBF and complex karyotype AML we identified 1120 transcripts to be potentially

alternatively spliced. In parallel, the analysis of the same AML subgroups using the OneChannelGUI

package in R revealed 1439 candidates with an overlap of only 211 genes. Of these transcripts, that

have been indicated by both programs as potentially alternatively spliced, selected candidates were

further investigated by RT-PCR, quantitative RT-PCR and sequence analysis for the presence of splice-

variants. Of 26 candidate genes studied, we could confirm alternative splice forms for 5 genes that

might potentially be involved in driving leukemogenesis, such as the protein coding gene arginine

methyltransferase 1 (PRMT1), which regulates transcription through histone methylation and

participates in DNA damage response. Furthermore, we could confirm differential exon usage in the

protein tyrosine phosphatase non-receptor type (PTPN6) transcript, which encodes for a negative

regulator of numerous signaling pathways involved in cell cycle control and apoptosis. Similarly, the


mRNA of the protein Rho GTPase activating protein 4 (ARHGAP4), which has been shown to regulate

cell motility, was alternatively spliced between CBF and complex karyotype subgroups.

In summary, these first gene expression data demonstrate that the attempt to elucidate the splicing of

transcriptome in AML by applying Exon microarray technology is challenging in particular with regard to

the currently available software solutions. Nevertheless, our results show that this approach offers the

ability to detect novel alternatively spliced candidate genes. Being involved in cell cycle control,

regulation of transcription or remodeling of the cytoskeleton, alternative splicing of these genes might

play a potential role in the pathomechanism of distinct AML subgroups. Thus, in the future more

extensive Exon array profiling with more sophisticated software solutions at hand is likely to provide

additional insights into the molecular mechanisms of leukemogenesis and might reveal novel targets for

refined therapeutic strategies in AML.


Gene expression profiling in the myelodysplastic syndromes

James S. Wainscoat, LRF Molecular Haematology Unit, Nuffield Department of Clinical Laboratory

Sciences, University of Oxford, John Radcliffe Hospital, Oxford, UK

In order to gain insight into the molecular pathogenesis of the MDS, we have determined the

transcriptome of the hematopoietic stem cells (HSC) of 183 MDS patients and 17 healthy controls. The

CD34+ cells obtained from MDS patients and healthy individuals were analyzed using Affymetrix U133

Plus2.0 arrays. Global pathway analysis using the Ingenuity software and the DAVID database has

identified critical deregulated gene pathways and gene ontology (functional) groups perturbed in MDS

HSC compared with normal HSC. The most significantly deregulated pathways in MDS include

interferon signaling, thrombopoietin signaling and the Wnt pathway. Moreover, we have identified

multiple pathways that are deregulated in specific MDS karyotypic groups and between early (subtype

RA) and advanced MDS (subtype RAEB2). Among the most significantly deregulated gene pathways

and ontology groups in early MDS are immunodeficiency, apoptosis and chemokine signaling, whereas

advanced MDS is characterized by deregulation of the cell cycle, DNA damage response and checkpoint

pathways. The clinical behavior of patients with del(5q), +8 or –7/del(7q) is different and we have

identified distinct gene expression profiles and deregulated gene pathways for MDS defined by these

major karyotypic groups. The most significantly deregulated gene pathways in del(5q) MDS include

primary immunodeficiency signaling, Wnt/beta-catenin signaling, integrin signaling, cell cycle regulation

and Huntington’s disease signaling. Patients with the 5q- syndrome also show deregulation of the p53

pathway. Moreover, chromatin assembly and translation are among the most significant gene ontology

groups in del(5q) MDS. We have found that MDS with the –7/del(7q) is characterized by deregulation of

multiple pathways involved in cell survival, differentiation, apoptosis and growth, and include

SAPK/JNK, NF-kB, PI3K/AKT and ceramide signaling pathways. Strikingly, all of the most significantly

deregulated gene pathways in trisomy 8 MDS in our study concern or are associated with the immune

response, and include B-cell receptor signaling, antigen presentation and CTLA4 signaling in Cytotoxic T

lymphocytes pathways. These data are consistent with an immune system role in the pathogenesis of

MDS with trisomy 8. Importantly, much of the deregulated pathway data generated in this study is in

accord with the known biology of MDS. On the basis of our observations, we suggest a model for MDS

in which immune deregulation and activation of apoptosis pathways in early MDS cells, consistent with

clinically observed ineffective hematopoiesis, functions as a barrier to prevent leukemic transformation.

Disruption of the DNA damage check points in advanced MDS results in an increase in the error rate of

DNA repair with a concomitant increase in genomic instability, leading to evolution to AML. This is the

first study to determine deregulated gene pathways and ontology groups in the HSC compartment of a

large group of patients with MDS. The deregulated pathways identified are likely to be critical to the

MDS HSC phenotype, provide important new insights into the molecular pathogenesis of this disorder,

and may represent new targets for therapeutic intervention.


Molecular diagnosis of low-risk myelodysplastic syndromes: from diagnostic criteria to the genetic profiles. The GEP shows important biological differences between low risk MDS

M del Rey, C Fontanillo, J de las Rivas, M Abaigar, K Mills, JM Hernández

Myelodysplastic syndromes (MDS) are a heterogeneous group of diseases. The diagnosis is based on

morphological and cytogenetic criteria. According to these data MDS are classified as low-risk MDS and

high-risk MDS. Diagnosis in low-risk MDS is difficult and hence other procedures that could help such

diagnoses should be evaluated.

For this reason, we have analysed the gene expression profiles in low-risk MDS: Refractory Anaemia

(RA) and Refractory Anaemia with Ring Sideroblasts (RARS), and to compare them with those of bone

marrow (BM) samples from patients without malignant haemopathies.

The RNA of BM cells separated by density gradient (ficoll) of 100 samples was analysed. Thirty nine had

a RA, 30 had a RARS while the remaining 31 samples were from patients without malignant

haemopathies (control group). In all cases, the RNA was isolated from mononucleate cells and

hybridised with the Human Genome Expression Array (U133 Plus) from Affymetrix. All comparisons

were made indepently in duplicate, with a test group and a control group for each entity (RA, RAS and

normal BM).

The expression profile of the low-risk MDS patients differed from that of the controls. Supervised

analysis of the low-risk MDS samples as compared with the non-leukaemic samples allowed the

identification of 1,763 differentially expressed genes. A total of 1,334 differentially expressed genes

were identified when RA group was compared with control group and 1,750 in the comparison

between RARS and healthy controls. The RARS patients displayed more differences respect the two

other groups and 148 genes involved in iron and mitochondrial metabolism were identified.

In summary, patients with RA and RARS show a characteristic and different gene expression profile

from that of the BM of patients without malignant haemopathies. These differences affect cell

processes involved in the patients’ physiopathology. The expression arrays could provide a procedure for

better diagnosis of low-risk MDS.


Workgroup 2: Whole Genome Mutations and Abnormalities

New insights into the prognosis impact of cytogenetic abnormalities in MDS

D. Haase, Dept. of Hematology and Oncology, University of Goettingen. Germany

The International Prognostic Scoring System (IPSS) still defines the gold standard to estimate the clinical

course in patients with primary MDS. The original cytogenetic component of the IPSS was based on 816

pts. (327 abnormal and 489 normal karyotypes) and consisted of 3 prognostic subgroups. Re-

evaluation of the cytogenetic component of the IPSS is now appropriate to: 1) provide updated/revised

prognostic information of well-known MDS cytogenetic subgroups, 2) expand the data to include as

much less frequent karyotypic abnormalities as possible, 3) include combinations of abnormalities, and

lastly, 4) revise the weight of poor risk cytogenetics.

In an attempt to substantially improve the cytogenetic basis of prognostic scoring 3 large, well-

characterized international databases (German-Austrian (GA), Spanish MDS-registry, IMRAW) and rare

abnormalities from the International cytogenetics Working Group (ICWG) of the MFD Foundation were

merged. Thus 2650 pts. fulfilled the inclusion criteria which were defined as follows: Primary MDS, age

>=16, no treatment except supportive care and bone marrow blasts <30%. Databases were balanced

for age, gender, blasts and cytogenetics. 1210 pts. (45.7%) had an abnormal karyotype and 237

(8.9%) had complex changes. A total of 22 cytogenetic subgroups proposed by the GA-study group

(ASH 2008) were examined and divided into the 4 prognostic subgroups: Favorable (5q-, 12p-, 20q-,

+21, -Y, 11q-, t(11)(q23), normal, 2 abnormalities including 5q-), intermediate-1 (+1q, 3q21/q26-

abnormalities, +8, t(7q), +19, -21, any other single, any other double), int-2 (-X, -7/7q-, 2

abnormalities incl. -7/7q-, complex = 3 abnormalities) and unfavorable (complex >3 abnormalities).

Kaplan-Meier calculations resulted in median survival of 51 months (favorable), 29 months (Int-1), 15.6

months (Int-2) and 5.9 months (unfavorable). The median time to 25% AML-transformation was 71.9

months in the favorable, 16 in Int-1, 6.0 in Int-2 and 2.8 months in the unfavorable group. Differences

in median survival (p<0.0001) and AML transformation rates (p<0.0001) were highly significant

different between all subgroups. In a multivariate analysis the relative risk for death and AML-

transformation related to the normal karyotype was calculated for every subgroup and supported the

findings of the univariate analyses.

These updated cytogenetic dataset may serve as the basis for a revised cytogenetic component in the

upcoming reassessment of the IPSS.


Acquired segmental UPD in relapsed AML Manoj Raghavan, Molecular Genomics Group, Centre for Medical Oncology, Institute of Cancer and

the CR-UK Clinical Centre, Barts and The London School of Medicine and Dentistry, London, UK

Despite advances in the curative treatment of acute myeloid leukemia (AML), recurrence will occur in

the majority of cases. At diagnosis, acquisition of segmental uniparental disomy (UPD) by mitotic

recombination has been reported in 15% to 20% of AML cases, associated with homozygous

mutations in the region of loss of heterozygosity. This study aimed to discover if clonal evolution from

heterozygous to homozygous mutations by mitotic recombination provides a mechanism for relapse.

DNA from 27 paired diagnostic and relapsed AML samples were analyzed using genotyping arrays.

Newly acquired segmental UPDs were observed at relapse in 11 AML samples (40%). Six were

segmental UPDs of chromosome 13q, which were shown to lead to a change from heterozygosity to

homozygosity for internal tandem duplication mutation of FLT3 (FLT3 ITD). Three further AML samples

had evidence of acquired segmental UPD of 13q in a subclone of the relapsed leukemia. One patient

acquired segmental UPD of 19q that led to homozygosity for a CEBPA mutation 207C>T. Finally, a

single patient with AML acquired segmental UPD of chromosome 4q, for which the candidate gene is

currently unknown. We conclude that acquisition of segmental UPD and the resulting homozygous

mutation is a common event associated with relapse of AML.


Genetic pathways in t-MDS and t-AML

Morten T. Andersen, Mette K. Andersen and Jens Pedersen-Bjergaard

This overview will highlight the results of almost three decades of research leading to the definition and

refinement of alternative genetic pathways in the development of therapy-related myelodysplasia

(t-MDS) and acute myeloid leukaemia (t-AML). The association between recurring distinctive

chromosomal aberrations, disease presentation, type of previous therapy and characteristic gene

mutations will be covered and parallels will be drawn to de novo diseases.


Novel prognostic subgroups in childhood 11q23/MLL-rearranged acute myeloid leukemia: results of an international retrospective study

Brian V. Balgobind, Susana C. Raimondi, Jochen Harbott, Martin Zimmermann, Todd A. Alonzo, Anne

Auvrignon, H. Berna Beverloo, Myron Chang, Ursula Creutzig, Michael N. Dworzak, Erik Forestier,

Brenda Gibson, Henrik Hasle, Christine J. Harrison, Nyla A. Heerema, Gertjan J.L. Kaspers, Anna Leszl,

Nathalia Litvinko, Luca Lo Nigro, Akira Morimoto, Christine Perot, Rob Pieters, Dirk Reinhardt, Jeffrey E.

Rubnitz, Franklin O. Smith, Jan Stary, Irina Stasevich, Sabine Strehl, Takashi Taga, Daisuke Tomizawa,

David Webb, Zuzana Zemanova, C. Michel Zwaan and Marry M. van den Heuvel-Eibrink

Translocations involving chromosome 11q23 frequently occur in pediatric AML and are associated with

poor prognosis. In most cases, the MLL-gene localized at 11q23 is involved, and more than 50

translocation partners have been described. Clinical outcome data of the 11q23-rearranged subgroups

are scarce, because most collaborative group 11q23 series are too small for meaningful analysis of

subgroups, though some studies suggest that patients with t(9;11)(p22;q23) have a more favorable

prognosis. We retrospectively collected outcome data of 756 children with 11q23- or MLL-rearranged

AML from 11 collaborative groups (15 countries) to identify differences in outcome based on

translocation partners. All karyotypes were centrally reviewed before assigning patients to subgroups.

The event-free survival of 11q23/MLL-rearranged pediatric AML at 5 years from diagnosis was

44%±5%, with large differences across subgroups (11%±5% to 92%±5%). Multivariate analysis

identified the following subgroups as independent predictors of prognosis: t(1;11)(q21;q23), (HR

0.1,p=0.004); t(6;11)(q27;q23), (HR 2.2,p<0.001); t(10;11)(p12;q23), (HR 1.5,p=0.005); and

t(10;11)(p11.2;q23), (HR 2.5,p=0.005). We could not confirm the favorable prognosis of the

t(9;11)(p22;q23) subgroup. We identified large differences in outcome within 11q23/MLL-rearranged

pediatric AML and novel subgroups based on translocation partners that independently predict clinical

outcome. Screening for these translocation partners is needed for accurate treatment stratification at

diagnosis.


Hidden genomic abnormalities in karyotypically normal and del5q MDS using oligonucleotide array CGH

Brigitte Royer-Pokora1, Anne Pölitz1, Manfred Beier1 , Deborah Ingenhagen1, Vera Möller1, Christina

Evers, Ulrich Germing2, Aristoteles Giagounidis3, Barbara Hildebrandt1, 1Institute of Human Genetics, Heinrich Heine University of Duesseldorf, 2Department of Haematology,

Oncology and Clinical Immunology, Heinrich Heine University, Duesseldorf, 3Johannes Hospital Duisburg

Approximately 50% of MDS patients have a normal karyotype. Among the most frequent karyotypic

abnormalities in MDS are deletions of the long arm of chromosome 5 (del5q). Our aim was to study

how often hidden abnormalities can be detected in MDS with normal karyotype or isolated del5q and

whether there are recurrent aberrations.

Our first project was to determine the frequency of hidden DNA copy number alterations in MDS

patients with an isolated del5q. For this study we have used Agilent microarrays consisting of 44K,

105K or 244K 60-mer oligonucleotide probes spanning the human genome with an average spatial

resolution of approximately 43, 22 and 9 kb, respectively. Array CGH allowed a precise localisation of

the breakpoints in 5q, revealing several clustered breakpoints. Hidden chromosomal aberrations larger

than 1 Mb were observed in 3 of 21 del5q cases. Smaller aberrations were also detected and several

were confirmed by FISH or Q-PCR. In the next step we have designed custom arrays containing a dense

coverage of alterations that were observed in more than two cases. With these the breakpoints in 5q

were cloned in 10 cases and the sequences are currently analyzed. Other recurrent aberrations were

identified that are studied at present.

In the next step we have analyzed 105 patients with a normal karyotype using aCGH. Four alterations

were observed in >2 cases, del5q, del7q, del21q and del4q. Larger alterations were verified by FISH

and smaller alterations with Q-PCR. So far 40 aberrations were verified with other methods. Zoom in

custom arrays are currently hybridized to identify and characterize the breakpoints. In conclusion,

hidden aberrations in MDS can be identified and smaller recurrent alterations are currently analyzed in

more detail.


High resolution genomic karyotyping of monosomy 7/del(7q) Azim M. Mohamedali, Dept of Haematological Medicine,Kings College London, UK

The myelodysplastic syndrome (MDS) comprise a relatively common and complex group of clonal

haematological diseases, that are increasingly been recognised as a leading cause of mortality and

morbidity particularly in patients over the age of 70 years. One of the most frequent chromosomal

aberrations characteristic to MDS is monosomy 7 occurring in 25% of cases with abnormal cytogenetics

resulting in poor prognosis. This entity can occur either as a complete loss or interstitial deletion of the

long arm of chromosome 7and with no prognostic significance associated with the position of the

deletion. Two major break points at 7q22 and 7q35-q36 have been identified using FISH and

microsatellite analysis. It can be assumed that a tumour suppressor gene(s) may be localised to the

haplo-insufficient region, however unlike 5q- Syndrome, none has yet been identified. With the advent

of high resolution SNP arrays, cryptic aberrations have been identified and common deleted regions

(CDR’s) have been defined for most chromosomal aberrations in MDS. These cryptic aberrations show a

significant correlation with prognosis both in low and high risk MDS. Furthermore, the identification of

a high frequency of copy neutral regions of homozygosity and novel association with gene aberrations

(TET2 and c-CBL) has cemented the utility of using SNP arrays for detecting chromosomal aberrations in

MDS. We have analysed a small group of monosomy 7 patients using high resolution Affymetrix SNP6

arrays and identified distinct proximal and distal breakpoints. Furthermore, a subset of these patients

have frequent regions of copy neutral runs of homozygosity on 7q detected b SNP arrays. Interestingly,

patients having cryptic aberrations on chromosome 7 had a poorer prognosis when compared to

patients with chromosome 7 abnormalities detected by metaphase ctyogenetic analysis. These results

need to be corroborated in an expanded cohort of patients that would identify the minimal common

deleted region on chromosome 7 and focus on the identification of a putative tumour suppressor

gene(s) in this CDR.


Workgroup 3: Epigenetic Scanning

Gene specific and global methylation patterns predict out come in patients with acute myeloid leukemia

Stefan Deneberg1, Mikael Grövdahl1, Mohsen Karimi1, 3, Monika Jansson1, Hareth Nahi1, Andrea

Corbacioglu2, Verena Gaidzik2, Konstanze Döhner2, Christer Paul1, Tomas J. Ekström3, Eva Hellström-

Lindberg1, Sören Lehmann1 1Hematology Center, Karolinska University Hospital, Huddinge, Stockholm, Sweden. 2Department of

Internal Medicine III, University Hospital of Ulm, Ulm, Germany. 3Molecular Medicine; Karolinska

Institutet; Karolinska University Hospital; Stockholm, Sweden.

BACKGROUND: The development of malignant diseases is associated with changes in DNA methylation

patterns. The biological and prognostic role of DNA methylation in acute myeloid leukemia (AML) is

unclear. AIM: This study was designed to investigate the impact of different DNA methylation patterns

on clinical outcome and to correlate DNA methylation to other genetic events.

MATERIALS AND METHODS: Methylation of p15, CDH and HIC promoters were analyzed by denaturing

gradient gel electrophoresis (DGGE), validated by pyrosequencing and melting curve methylation

analysis (MS-MCA) in a clinically and genetically well-characterized cohort of 107 previously untreated

AML patients. Global methylation was analyzed by luminometric assay (LUMA) and genome wide CpG

island promotor methylation by Illumina HumanMethylation27 Bead Chip in a subset of the patients.

RESULTS: Promoter methylation was discovered in 66%, 66% and 52% of the samples in p15, CDH

and HIC1, respectively. In multivariate analysis, low global methylation was associated with better

complete remission rate (Hazard ratio (HR) 5.9, p=0.005) and p15 methylation was associated with

better overall (HR 0.4, p=0.001) and disease-free survival (HR 0.4, p=0.016). Methylation of HIC and

CDH had no impact on CR rate, DFS or OS in multivariate analysis. The relationship between LUMA and

CR was age-dependent with significantly better CR rate in patients with low global LUMA methylation

levels among patients <65 (p=0.019), a difference that was not found in patients >65 (p=0.66).

Furthermore, global hypomethylation by LUMA correlated significantly to increased promoter CpG

island methylation as assessed by Illumina HumanMethylation27 Bead Chip. Hypermethylation as

measured as increased number of methylated genes by Illumina HumanMethylation27 correlated to

better DFS and OS (p=0.015 and 0.005, respectively). There were no associations between methylation

patterns and the cytogenetic risk groups or the mutational status of FLT3, NPM1, CEBPA and NRAS.

Deletions of chromosome 5q or 7 were associated with less p15 methylation and global DNA


hypermethylation (p=0.019 and 0.041, respectively). However, when Bonferroni correction was

performed due to multiple correlations, none of the associations were found to be statistically

significant.

CONCLUSION: We conclude that global and gene-specific methylation patterns independently predict

outcome in AML patients.


Epigenetic profiling in AML Christoph Plass, German Cancer Research Center, Heidelberg

Acute myeloid leukemia (AML) is a disease characterized by uncontrolled proliferation of clonal

neoplastic hematopoietic precursor cells. This leads to the disruption of normal hematopoiesis and bone

marrow failure. In the past, major breakthroughs have been made to understand the genetic failures

and the changed biology in AML cells underlying the initiation and progression of the disease. It is now

realized in the field that not only genetic but also epigenetic alterations are similarly important in this

process. Since epigenetic alterations do not change the DNA sequences they are considered reversible,

which offers a unique opportunity for what is now known as epigenetic therapy. In this presentation,

our current understanding of normal epigenetic processes will be discussed and contrasted to our

current understanding of global epigenetic alterations in the disease process. Data will be summarized

indicating the magnitude of global epigenetic changes especially in CpG island sequences. Furthermore,

the complexity of altered DNA methylation patterns will be discussed using epigenetic alteration in the

promoter of C/EBPα, a master regulatory transcription factor in the hematopoietic system, as an

example.


Current approaches for the analyses of histone modification patterns in hematopoiesis and leukemia

Carsten Müller-Tidow, University of Münster, Germany

Gene expression in hematopoiesis is tightly regulated at multiple levels. The spatial and temporal

regulation of transcription factor activity provides a cornerstone of transcriptional regulation.

Transcription factor activity at promoters and enhancers depends on specific cis-acting DNA binding

sites. Transcription factors often recruit co-factors that enzymatically modify the N-termini of histone

proteins. Histone proteins can be post-translationally modified by acetylation, methylation,

phosphorylation and ubiquitinylation. The number of enzymes and transcriptional co-factors that are

known to influence these processes is steadily increasing. In addition, several histone modifications are

linked to CpG DNA methylation and provide another layer e.g. of gene silencing. The resulting patterns

of histone modifications might form a specific “histone code” that is passed on to daughter cells and

specifies the function of genomic regions, e.g. promoters, enhancers, or exonic sequences. Histone

modifications and other epigenetic features, e.g. DNA methylation are frequently altered in malignant

diseases. In leukemia, only a small number of genetic mutations is usually found in patient samples. On

the other hand, a high number of epigenetic changes occurs in leukemic cells. An in depth

characterization of these changes in leukemia cells and the functional consequences are important

steps in assessing the importance of epigenetic changes in leukemia pathogenesis. Recent years have

seen several new approaches to analyse histone modifications in normal hematopoiesis and in leukemia

cells. Most of these approaches rely on the immunoprecipitation of specific histone modifications (Fig.

1).

Fig. 1: ChIP-Chip and ChIP-Sequencing.

Chromatin-Immunoprecipitation with antibodies specific for histone modifications can be coupled with microarray

hybridization or deep sequencing to identify the genomic localization of specific histone modifications.


Subsequently, the enriched DNA within the immunoprecipitate is purified, amplified and finally either

hybridized onto genomic microarrays or directly sequenced using second generation sequencing. These

methods have already led to important insights into normal hematopoiesis and several studies have

shown that histone modification patterns are associated with specific leukemia subentities. Our own

analyses indicate that leukemia specific histone modification patterns exist for histone H3 acetylation

and histone H3 lysine 9 trimethylation. These patterns are associated with altered transcription factor

activity. Interestingly, a signature derived from H3K9me3 patterns was derived that predicted AML

patients´ prognosis independent from known clinical varibles and cytogenetics. The origin of the altered

histone modification patterns might not only rely on changes in specific transcription factors. In several

instances, histone modifying enzymes are themselves altered in leukemias and might thus lead to

altered histone modifications.

In conclusion, the epigenome analysis in terms of histone modification patterns in leukemia has

emerged as a new field of study. Altered histone modifications at specific loci might be of pathogenetic

relevance in leukemia. The possibility to influence histone modifications e.g. by HDAC-inhibitors might

offer new possibilities to treat leukemias.


Equitoxic doses of 5-azacytidine and 5-aza-2’-deoxycytidine upregulate an overlapping subset of cancer/testis antigens and microRNAs 1Christoffer Hother*, 3Xiangning Qiu*, 1Marianne B Treppendahl, 4Anne O Gang 3Gangning Liang, 2Christopher Workman, 4Sine Reker, 3Peter A Jones, and 1Kirsten Grønbæk 1 The Epi-/Genome laboratory, Dept. of Hematology, Copenhagen, Denmark, 2Center for Biological

Sequence Analysis, Technical University of Denmark, 3Dept. of Biochemistry and Molecular Biology,

USC, Los Angeles, USA., 4 Center for Cancer Immunotherapy, Herlev Hospital, Copenhagen Denmark.

Introduction: In two recent clinical studies conventional care regimens (CCR) were compared to the

DNA methyltransferase inhibitors (DNMTi), 5-azacytidine (5-aza-CR) and 5-aza-2’-deoxycytidine (5-aza-

CdR), respectively, for the treatment of high-risk myelodysplastic syndrome. 5-Aza-CR showed a

significant survival benefit as compared to CCR, while 5-aza-CdR did not. Since 5-aza-CR gets

incorporated into both RNA and DNA and 5-aza-CdR gets incorporated into DNA only, we investigated

whether this difference in nucleic acid incorporation influences the biological effect of the drugs, and

thereby explains the different outcome of the two studies.

Methods: The MDS/AML cell line P39 was treated with equitoxic doses of 5-aza-CR and 5-aza-CdR for

24 hours. mRNA (Illumina platform) and miR arrays (Exiqon platform) were performed with RNA

extracted from cells harvested on day 2 and day 8. For selected genes and miRs, array data were

confirmed by RT-qPCR. Methylation status of miRs was investigated by methylation specific melting

curve analysis.

Results and further analyses: 5-Aza-CdR derepressed more genes and miRs compared to 5-aza-CR.

This was particularly evident on day 8. More than 85% of genes and 100% of miRs upregulated by 5-

aza-CR are also upregulated by 5-aza-CdR on day 8. This observation is in contrast to an earlier report

(Flotho et al., 2009) in which different sets of genes are derepressed by the two DNMTi. The effects of

the two drugs on miR expression have not previously been directly compared. Interestingly, 5-aza-CR

derepressed most miRs on day 2. Since long non-coding RNAs (ncRNA) have recently been suggested as

key factors for the establishment of epigenetic silencing by DNA- and histone methylation, we are

currently investigating the effects of the two drugs on the expression of ncRNAs (Agilent platform).

Cancer/Testis-Antigens (CTA) are significantly overrepresented among the commonly upregulated genes

(10% on day 2 and 6% on day 8), and a time and dose dependent effect was observed. Interestingly,

the CTA transcription factor CTCFL (BORIS), was among the genes upregulated by both DNMTis. Since

CTAs are known to be potent tumor antigens, we are currently investigating the induction of a cytotoxic

T-cell response by 5-aza-CR in sequential blood and bone marrow samples of from patients treated

with 5-aza-CR (Hadrup et al., 2009).


All but one of the commonly upregulated miRs carry a CpG island in their 5’ region. We have

investigated and found methylation of the 5’regions in several of the miRs, which are unmethylated in

normal CD34+ cells. For one miR, which locates to a fragile site in MDS, 5’RACE determination of the

transcription start site has been performed. We are currently looking into the prognostic impact of

methylation of this miR promoter. The specific mRNA targets of the 5p and 3p mature miRs encoded by

this miR gene are being identified by transfection studies, western blotting and luciferase assays.

Reference List

Flotho,C., Claus,R., Batz,C., Schneider,M., Sandrock,I., Ihde,S., Plass,C., Niemeyer,C.M., and

Lubbert,M. (2009). The DNA methyltransferase inhibitors azacitidine, decitabine and zebularine exert

differential effects on cancer gene expression in acute myeloid leukemia cells. Leukemia 23, 1019-

1028.

Hadrup,S.R., Bakker,A.H., Shu,C.J., Andersen,R.S., van,V.J., Hombrink,P., Castermans,E., thor,S.P.,

Blank,C., Haanen,J.B., Heemskerk,M.H., and Schumacher,T.N. (2009). Parallel detection of antigen-

specific T-cell responses by multidimensional encoding of MHC multimers. Nat. Methods 6, 520-526.

* These authors contributed equally to this study.


New methods to study DNA methylation Giovanni Perini, University of Bologna, Dept. of Biology, via F. Selmi 3, 40126 Bologna, Italy

The pattern of gene expression in a given cell under particular circumstances is determined by several

factors including the epigenetic marking of the genome. These marks include DNA methylation and

post-translational modification of the histones around which DNA is wrapped when packaged in the

nucleus. DNA methylation has been shown to be critical for many physiological as well as pathological

conditions; particularly it plays an important role in tumorigenesis and tumor progression. The DNA

methylation profile significantly changes during cancer formation with a general loss of DNA

methylation in the genome and occurrence of hypermethylation at some gene promoters mostly, at

promoters of tumor suppressor genes and genes involved either in DNA repair or genome integrity. It is

not yet clear whether such modifications in DNA methylation profiles are generated through random

events favoring selection of more aggressive tumor cells or instead whether such modifications follow

some genetic program which has yet to be identified. The past few years have seen the birth of many

molecular methods employed to study DNA methylation. These methods are varied and address

different issues which go from determining gross modifications of the DNA methylation content in the

cancer cell genome, to methods that can precisely register any change occurring at distinctive

cytosines. Furthermore, the possibility of identifying proteins that bind methylated cytosine has allowed

to intersect the realm of DNA methylation with that of chromatin modifications and allow to understand

the contribution of DNA methylation to chromatin remodelling.

Here I will summarize on recent molecular methods that are employed to study DNA methylation in

cancer mostly focusing on their applications, advantages and technical and conceptual limits.


Lineage-specific DNA methylation in T cells correlates with histone methylation and enhancer activity

Christian Schmidl, Maja Klug, Tina J. Boeld, Reinhard Andreesen, Petra Hoffmann, Matthias Edinger,

Michael Rehli.

Department of Hematology, University Hospital Regensburg, 93042 Regensburg, Germany

DNA methylation participates in establishing and maintaining chromatin structures and regulates gene

transcription during mammalian development and cellular differentiation. With few exceptions, research

thus far focused on gene promoters, and little is known about the extent, functional relevance and

regulation of cell type-specific DNA methylation at promoter-distal sites. Here, we present a

comprehensive analysis of differential DNA methylation in human conventional CD4+ T cells (Tconv)

and CD4+CD25+ regulatory T cells (Treg), cell types whose differentiation and function are known to

be controlled by epigenetic mechanisms. Using a novel approach that is based on the separation of a

genome into methylated and unmethylated fractions, we examined the extent of lineage-specific DNA

methylation across whole gene loci. More than one hundred differentially methylated regions (DMR)

were identified that are mainly present in cell type-specific genes (e.g. FOXP3, IL2RA, CTLA4, CD40LG

and IFNG), and show differential patterns of histone H3 lysine 4 methylation. Interestingly, the majority

of DMR was located at promoter-distal sites and many of these areas harbor DNA methylation-

dependent enhancer activity in reporter gene assays. Thus, our study provides a comprehensive, locus-

wide analysis of lineage-specific methylation patterns in Treg and Tconv cells, links cell type-specific

DNA methylation with histone methylation and regulatory function and identifies a number of cell-type

specific, CpG methylation-sensitive enhancers in immunologically relevant genes.


MicroRNA-196a and –196b are differentially expressed between and within cytogenetic and molecular subtypes of pediatric AML, and high expression is correlated to overexpression of HOX genes

J. Kuipers, A.A. Danen-van Oorschot, D. Kreuger, V. De Haas, D. Reinhardt, J. Stary, A. Baruchel, C.M.

Zwaan, M.M. van den Heuvel-Eibrink

In recent years miRNA expression patterns have been shown to be related to tumor (sub)type and

disease outcome in various types of cancer, including acute myeloid leukemia (AML). Therefore, miRNA

profiling may provide information for better classification of AML subtypes, allowing for more tailored

therapies. To date large scale miRNA profiling has only been performed in adult AML, which differs

from childhood AML in many ways, reflected in differences in response to therapy and prognosis.

However, knowledge on the role of miRNAs in childhood AML is limited.

To answer the question if differential expression of miRNAs can also be observed in subtypes of

pediatric AML, we used quantitative RT-PCR to determine the expression levels of miR-29a, -155, -

196a and -196b in de novo pediatric AML patients (n=57-84). These miRNAs have been reported to be

differentially expressed in cytogenetic and morphological subtypes of adult AML.

In contrast to what was found in adults, differences in expression of miR-29a were small, albeit

significant. MiR-29a was only 1.5-fold lower in MLL-rearranged AML (n=18, p=0.008), and 1.3-fold

higher in FLT3-ITD-mutated AML (n= 10, p=0.039) versus all other AML samples. Larger differences

were observed for miR-155, which was upregulated 3.5-fold (p<0.0001) in FLT3-ITD-mutated AML

(n=10) compared to all other AML samples, consistent to what has been reported for adult AML. The

expression of both miRNA-196a and –196b differed extremely between patients. High expression of

both miRNAs was observed in patients carrying MLL-gene rearrangements, NPM1 mutations, or FLT3-

ITD mutations in a normal karyotype background. Low expression was found in t(8;21), inv(16), and

t(15;17) subtypes (including those with FLT3-ITD mutations), and in patients with mutated CEBPA. The

median difference between these groups of patients was 177-fold for miR-196a (n=78, p<0.0001),

and 785-fold for miR-196b (n=65, p<0.0001). A moderate to strong correlation was found with mRNA

levels of several genes of the HOXA and HOXB cluster, and MEIS1, based on gene expression profiling

data (Spearman’s correlation coefficient = 0.504-0.818). Correlation was highest with HOXA9,

HOXA10 and HOXB9, which was confirmed by quantitative RT-PCR adjacent to which these miR-genes

are located. In almost all patients, both miRNAs are overexpressed at the same time, and expression

levels of miR-196a and –196b were highly correlated to each other (Spearman’s = 0.865).

Upregulation of miR-196a and 196b has also been reported in MLL-rearranged and NPM1-mutated

AML in adults. MiR-196b has been implicated to play a role in myeloid differentiation. However, further

studies are required to determine if these miRNAs also play a role in leukemogenesis.


Our results confirm subgroup specific miRNA expression in pediatric AML, and are mostly but not

always consistent to what has been described for adult AML. This underlines the importance to further

analyze the expression of known and novel miRNA genes in childhood AML.


Global and gene specific hypermethylation in bone marrow samples from MDS patients Ulrich Lehmann, Daniel Römermann, Britta Hasemeier, Gudrun Göhring, Brigitte Schlegelberger,

Florian Länger, Hans Kreipe

Epigenetic aberrations are now well-recognized as very frequent and also early events in the process of

malignant transformation. It is very often reported that gene-specific hypermethylation occurs in the

context of global hypomethylation. Accordingly, experimentally induced reduction of global methylation

levels increases tumour formation in mice under certain circumstances. Somewhat contradictory, in MDS

patients the induction of hypomethylation using DNA methyltransferase inhibitors leads to very

promising clinical response rates and haematological improvement. Therefore, we analysed the global

methylation level in a large cohort of MDS patients comprising all subgroups (n = 127), in order to

figure out the molecular mechanisms underlying this unexpected finding. Results were compared to an

age-matched control group of healthy subjects (n = 26).

Unexpectedly, the methylation level of the LINE-1 sequences demonstrated a distinct and statistically

highly significant increase in global DNA methylation in MDS patients compared to the control group.

This hypermethylation correlates highly significantly with the risk score according to the International

Prognostic Scoring System (IPSS), the blast count and the karyotype. Measuring the nucleotide

incorporation after methylation-sensitive restriction digest using LUMA methodology very similar results

were obtained. In a small subset of patients (n = 12) this absence of hypomethylation could be

confirmed by Southern blotting.

In order to obtain a more detailed picture of gene-specific hypermethylation in Myelodysplastic

syndromes Pyrosequencing™ technology was used for the analysis of the methylation status of 68 CpG

sites in the CpG island of the p15INK4b gene in a series of bone marrow samples from patients with

myelodysplasia and myeloid leukemia (n = 82) and 32 controls. Altogether, 7762 individual methylation

sites were quantitatively evaluated. Extensive statistical analyses of the whole CpG island revealed for

the first time disease-specific methylation patterns of the p15INK4b gene in myeloid malignancies and

small regions of differential methylation with high discriminatory power, which could discriminate even

low grade Myelodysplastic Syndrome (MDS) samples from the controls. This was confirmed in an

independent group of 9 control and 36 patient samples.

The identification of small regions with high discriminatory relevance implies that large areas of the

CpG island do not have discriminatory relevance. This demonstrates the necessity for a comprehensive

quantitative methylation analysis before high-throughput assays targeting only a few potential

methylation sites (e.g. Methylation Specific PCR) can be developed and implemented into the routine

diagnostics.


Telomere shortening and chromosomal instability in myelodysplastic syndromes

Kathrin Lange1, Lisa Holm1, Kirsten Vang Nielsen2, Andreas Hahn3, Winfried Hofmann1, Hans Kreipe4,

Brigitte Schlegelberger1, Gudrun Göhring1 1 Institute of Cell and Molecular Pathology, Hannover Medical School, Germany 2 Dako Denmark A/S, Glostrup, Denmark 3 Institute of Biometrics, Hannover Medical School, Germany 4 Institute of Pathology, Hannover Medical School, Germany

Telomere shortening and chromosomal instability are believed to play an important role in the

development of myeloid neoplasia. So far, published data are only available on the average telomere

length in myelodysplastic syndromes (MDS) and acute myeloid leukemia (AML), but not on the telomere

length of individual chromosomes. We used a new technique, telomere/centromere-fluorescence in-situ

hybridization (T/C-FISH), which combines fluorescence R-banding and FISH using a probe against the

telomere repeats to measure the telomere length of each chromosome arm in 78 patients with MDS. In

line with previous results, patients with MDS showed significantly shorter telomeres than those of

healthy controls. Telomere lengths did not differ significantly between distinct morphological subtypes

of MDS. However, there was a significant difference in telomere length between patients with an

isolated monosomy 7 and patients with a normal karyotype (p<0.05). Notably, patients with an

isolated monosomy 7 showed significantly longer telomeres than patients with a normal karyotype in

many chromosome arms, among them 7p and 7q. Neo-telomeres were found in two patients with a

complex karyotype, in one case at the fusion site of a dic(14;20). Normal and aberrant metaphases of

the same patient did not differ in telomere length, thus indicating to telomere shortening as a basic

mechanism affecting all hematopoietic cells in MDS patients. In some MDS subtypes, like MDS with

isolated monosomy 7, telomeres may be stabilized and even increase in length due to the activation of

telomerase or alternative mechanisms.


Aberrant DNA methylation characterizes juvenile myelomonocytic leukemia (JMML) with poor outcome

Christiane Batz1, Inga Sandrock1, Peter Nöllke1, Brigitte Strahm1, Henrik Hasle2, Marco Zecca3, Jan

Starý4, Eva Bergsträsser5, Monika Trebo6, Marry M. van den Heuvel7, Dorota Wojcik8, Franco Locatelli3,

Charlotte M. Niemeyer1 and Christian Flotho1

1Pediatric Hematology-Oncology, University Medical Center, Freiburg, Germany; 2Pediatrics, University

Hospital Skejby, Aarhus, Denmark; 3Pediatric Hematology-Oncology, University of Pavia, Italy; 4Pediatric

Hematology and Oncology, Charles University Prague, Czech Republic; 5Pediatric Hematology-Oncology,

University Children's Hospital, Zürich, Switzerland; 6Pediatrics, St. Anna Children's Hospital, Vienna,

Austria; 7Pediatric Oncology-Hematology, Erasmus Medical Center, Rotterdam, Netherlands; 8Pediatric

Hematology-Oncology, Wroclaw Medical University, Poland

Aberrant DNA methylation contributes to the malignant phenotype in cancer including

myeloproliferative neoplasms and myeloid leukemia. We hypothesized that aberrant DNA methylation

also occurs in juvenile myelomonocytic leukemia (JMML) and asked whether it is associated with

clinical, hematologic or prognostic features of the disease. A liquid chromatography-based method was

used to analyze peripheral blood or bone marrow samples from 87 children with JMML for changes in

DNA methylation at 14 candidate loci. Four of 14 gene promoters were aberrantly methylated: BMP4

(34% of patients), CALCA (30%), CDKN2B (28%), and RARB (23%). The pattern of hypermethylation

allowed the categorization of JMML cases into three groups: no methylation (40/87 patients),

intermediate methylation (1 or 2 genes; 29/87 patients) or high methylation (3 or 4 genes; 18/87

patients). Aberrant methylation was restricted to clonal cell populations and could be traced back to the

CD34+ JMML progenitor cell compartment. High methylation was strongly associated with older age

and increased hemoglobin F level at diagnosis. There was a significant association between high

methylation and poor prognosis; the 5-year overall survival was 0.63/0.52/0.24 in the

no/intermediate/high methylation groups. Among patients with hematopoietic stem cell transplantation,

the 5-year relapse incidence was 0.22/0.21/0.69 in the no/intermediate/high methylation groups. The

predictive power of high methylation was also reflected in a multivariate Cox model. Furthermore,

longitudinal analyses indicated that some cases had acquired a higher methylation phenotype at

relapse. In conclusion, we report aberrant DNA methylation as the most important molecular predictor

of outcome in JMML. We suggest that a high-methylation phenotype characterizes an aggressive

biologic variant of this leukemia.


Workgroup 4: Novel Drugs

Retrovirally modified hematopoietic cells in murine leukemia models

Christopher Baum, Dept. Experimental Hematology, Hannover Medical School, Germany

Replication-deficient retroviral vectors are widely used to assess the transforming potential of

(proto-)oncogenes. Typically, the gene of interest is cloned under control of a strong retroviral promoter,

and often co-expressed with a fluorescent protein to facilitate cell tracking after transduction into

repopulating hematopoietic cells. Recipients of these gene-modified cells are conditioned by lethal or

robust sublethal irradiation, thus promoting engraftment with gene-modified stem cells and

immunological tolerance to the foreign transgene products. As each retroviral integration site (RIS)

introduces a unique genetic footprint, RIS sequencing establishes powerful genetic markers for kinetic

clonality studies. Furthermore, genes harbouring or neighbouring the RIS may be truncated or

deregulated, resulting in insertional mutagenesis. Mapping large numbers of RIS in independent clonal

tumors may thus allow the identification of collaborating genetic events. In our work, we have

extensively used insertional mutagenesis by retroviral vectors expressing neutral marker genes (EGFP,

dsRed, tCD34, dLNGFR), proto-oncogenes (Mpl) or overt oncogenes (SV40LargeT, caMpl, ΔTrkA) to

identify novel leukemogenic mechanisms. Recently, RIS analysis was accomplished using high-

throughput sequencing coupled with automated bioinformatical analysis. Conceptual and technical

challenges encountered in this approach will be discussed.


A Phase II study to assess efficacy and safety of a DNA based vaccine associated with ATRA as add-on therapy in patients with chronic hematological diseases

Ph Rousselot, P Fenaux, C Chomienne and RA Padua.

Despite achievement of considerable progress in chronic hematological diseases such as chronic

myelogenous leukemia (CML) and myelodysplasic syndromes (MDS), therapeutic improvements are still

needed. In CML, Imatinib mesylate (Gleevec®) is the gold standard in chronic phase and results in an

overall survival rate of 95% at 5 years but less than 10% of the patients will have achieved a complete

molecular response (CMR). Treatment discontinuation in patients treated by imatinib and in CMR for

more than 2 years yield molecular relapses within 6 months indicating the persistence of CML

progenitor cells. In MDS, another stem cell disorder, survival of high risk patients has been improved by

the hypomethylating agent azacytidine (AZA). However, not all patients respond and most responders

relapse. Lower risk MDS are characterized by recurrent blood cytopenias, mainly anemia, that respond

only transiently to erythropoietic stimulating agents (ESAs) and subsequently requires repeated red

blood cells transfusions. We developed a PML/RARA targeted DNA-based vaccine and showed in an

acute promyelocytic leukaemia (APL) mice model that our specific DNA vaccine combined with ATRA

induced a pronounced survival advantage. We recently demonstrated that DNA vaccination with ATRA

conferred the effective boosting of IFN-γ-producing and cytotoxic T-cells. An unexpected finding was

the observation that a non specific DNA vaccine (so called “generic vaccine”) combined with ATRA

produces the same results in the APL model and also in a mouse MDS model. We thus decided to run a

phase II clinical trial in order to assess the value of generic DNA vaccination combined with ATRA in

patients with CML and MDS.

The primary endpoint of the trial is to evaluate the response rate of the generic vaccination procedure

assessed in CML patients by the rate of CMR and in MDS by the duration of response to AZA in high

risk patients and by the rate of haematological response in lower risk patients having failed ESAs (IWG

2006 criteria). The secondary endpoints are to evaluate the safety and the tolerability of the vaccine

and to evaluate in vivo and in vitro immunological activity.

Eligible patients with CML in complete cytogenetic response (CCR) under imatinib for more than two

years and patients with high risk MDS responding to AZA or low risk MDS failing to ESAs will receive

the generic DNA vaccine (5 mg per injection in the two deltoids) for 6 vaccinations every 2 weeks

followed by 3 vaccinations every month in combination with ATRA 45 mg/m²/d from day 1 to day 15 at

weeks 1, 5, 9 weeks. Additional boosts will be administered in responding patients.

A sample size of 45 assessable CML patients was calculated using a Minimax two-stage Simon design.

With a level of α=5% and to ensure 90% power, considering a 20% rate of CMR (p0) to conclude to


insufficient efficacy (H0), a 40% rate of CMR (p1) to conclude to the sufficient efficacy (H1), it will be

necessary to include 24 assessable patients in the first step of the study. If 6 cases of CMR are

observed, the trial will be continued. By the end of the study, the vaccination therapy will be considered

for further investigations if 14 cases of CMR are observed among the 45 assessable patients.

In the high risk MDS group, to demonstrate an improvement in response duration of 6 months given

the mean response of 14.5 months with azacytidine alone, assuming the standard deviation in response

time of 10, setting a Type I error risk of 5% and 80% power, will require two groups of 44 subjects. In

the low risk group, a difference in terms of response rate of 25%, setting a type I error risk of 5% and a

power of 80%, requires two groups of 44 subjects to test 5% versus 30%, or two groups of 38 subjects

to test 1% versus 25%.

Vaccination procedure:

Induction

Week1 W3 W5 W7 W9 W11

Vivavacs1 Vivavacs2 Vivavacs3 Vivavacs4 Vivavacs5 Vivavacs6

ATRA ATRA ATRA

Maintenance

Month1 Month2 Month3 Response

Vivavacs7 Vivavacs8 Vivavacs9 Additional boosts


A novel anti-Wilms-Tumour-1 (WT1) vaccination strategy in haematological cancer using DNA fusion vaccines delivered with electroporation Christian Ottensmeier1, Katy Rezvani2 and Freda Stevenson1 on behalf of the WIN trial investigators 1Cancer Sciences Division, University of Southampton, SO16 6YD and 2Imperial College, Hammersmith

Hospital, London W12 0NN, UK

In chronic myeloid leukaemia (CML) until quite recently only allogeneic stem cell transplantation could

offer long term disease free survival. The ‘curative’ effect of is mediated in large part through the allo-

immune graft versus-leukaemia effect. However, transplantation carries a substantial risk of mortality

and is only available to a minority of younger patients. Recently tyrosine kinase inhibitors (TKI), have

replaced allo-SCT as first-line therapy for CML. About 85% of imatinib-treated patients with chronic

phase (CP) CML achieve a complete cytogenetic response (CCyR) but the majority of patients have

persisting molecular disease detectable by quantitative real-time quantitative polymerase chain reaction

(qRT-PCR) for BCR-ABL transcripts. Functional leukaemic CD34+ progenitor cells have been identified

in such patients in complete cytogenetic remission, suggesting the presence of a reservoir of cells

resistant to the TKI [1]. In contrast long-term survivors of allo-SCT do not have easily detectable

molecular disease, indicating that all leukaemic cells must be susceptible to immune destruction.

We propose to control CML by precision attack of the tumour by CD8+ T cells by DNA fusion gene

vaccination by intramuscular injection and electroporation. DNA fusion vaccines were initially

developed in Southampton to treat B-cell malignancies. The key novel element in the design is the

inclusion of a sequence derived from tetanus toxin fused to the tumour-derived target sequence. The

function of this addition is to amplify immune responses and to break tolerance [2]. In follicular

lymphoma, the vaccines were safe and 40% of patients responded between 500-2500μg vaccine/dose

there was no evidence of a dose/response [2]. The levels of response were relatively low and

improvements were sought. An important development has been electroporation (EP) which

dramatically increased DNA vaccine performance in mice. A variant vaccine design was developed

specifically to induce CD8+ T-cell responses by minimizing the tetanus toxin-derived domain (DOM)

and fusing to it a tumour-derived epitope sequence. In multiple models [2], this design induced high

levels of epitope-specific CD8+ T cells, even in the tolerant settings [2]. The preclinical data appears to

predict for responses in humans. In prostate cancer patients a p-DOM-epitope vaccine, directed against

PSMA, has induced high levels of epitope-specific IFN-gamma producing CD8+ T cell responses in 60%

(19/32) of patients [3, 4]. This was the first ever vaccine study to deliver DNA by electroporation. We

found this approach to be safe and readily accepted by our patients. CD8 T cell responses were robust

and persistent to 18 months. Again there was no suggestion of a dose-response, supporting the choice

of 1mg/ dose as intended here.


We now wish to explore the effectiveness of dual tumour cell attack, using two p-DOM-epitope design

for the treatment of myeloid malignancies. Wilms’ Tumour gene 1 (WT1) has emerged as one of the

most promising targets for immunotherapy of haematological malignancies including CML. WT1

expression in normal individuals is limited to renal podocytes, gonadal cells and a small proportion of

CD34+ cells, where expression is significantly lower (10-100 fold) [5]. The available preclinical and

human data document selective attack against tumour cells, sparing the CD34+ cells [6, 7] and without

any evidence of autoimmune-toxicity in patients [8-11]. WT1 peptide vaccine clinical trials [8-12] also

show that T cell responses against WT1 can safely be induced, with transient clinical responses.

However a key problem with these vaccines was the lack of provision of CD4 T cell help, crucial for the

maintenance of tumour antigen specific CD8 T cell populations. This resulted in poor persistence of CD8

responses, in contrast to our own study in prostate cancer. Pre-clinically we have shown that p-DOM-

epitope vaccines, WT1-derived, HLA-A2-restricted peptides [13] induce CD8+ T cell responses in

“humanized”, HLA-A2+ and presumably tolerized (antigen-expressing) mice. These CD8 T cells killed

human WT1+ leukemic cells ex vivo. A direct comparison with a WT1 peptide vaccine showed a clear

superiority of the DNA fusion vaccine [13]. WT1.37 and WT1.126 peptides were selected for current

studies as we anticipate that dual attack against more than one epitope will provide added clinical

benefit. Vaccination with p-DOM-WT1.37 and p-DOM-WT1-126 into different locations will allow us to

avoid antigenic competition. Given the effect in the prostate study, we wish to continue using

electroporation as a delivery strategy.

Our hypothesis is that DNA vaccination, directed against the WT1 antigen can reduce measurable

BCR-ABL transcripts in CML in stable cytogenetic remission on imatinib but with measurable BCR-ABL

transcripts (CML in CCyR). We will show that this is mediated by immunological attack, specifically by

WT1 specific cytotoxic T cells.

The specific research questions are:

a) What is the effect of DNA vaccination on levels of tumour-derived BCR-ABL transcripts?

b) What is the effect of DNA vaccination on levels of tumour-derived WT1 transcripts?

c) Can DNA fusion gene vaccination with two p-DOM-WT1 vaccines induce high and persistent levels of

CD8+ cytotoxic T cells against two target epitopes from WT1 in patients with CML?

d) How do these molecular and immunological effects correlate to the quality and level of remission?

Trial design and population: This is a single dose, open label, phase II study of intramuscular DNA

vaccination in patients with CML in cytogenetic remission (CCyR) but not complete molecular response.

These have leukaemia still detectable by qRT-PCR but will be on a stable dose of imatinib and by the

very fact of being stable will not need a change drug from imatinib to one of the newer tyrosine kinase

inhibitors. Two epitope-specific DNA vaccines will be administered: p.DOM-WT37 and p.DOM-WT126

in HLA A2+ patients with CML.

Interventions, follow up: Based on our clinical dose finding studies (Rice, Ottensmeier et al. 2008;


Low, Mander et al. 2009), the DNA vaccines will be administered at 1mg per vaccine (WT37 and

WT126 into separate locations) 6 times at monthly intervals (weeks 0,4,8,12,16,20) intramuscularly

and using electroporation (EP). Responders (molecular or immunological) may continue vaccination 3

monthly to maximum response or 24 months. Molecular data (BCR-ABL for primary endpoint; WT1

transcripts for secondary endpoint) and clinical data will be collected monthly from baseline to 6

months thereafter 3 monthly to 24 months or progression. Sample storage for immunological follow up

will be undertaken to 1 year after the last dose of vaccine or end of study participation (24 months),

whichever comes earlier. Post study follow up will be as per clinical practice including molecular

monitoring; data on transcript levels, next treatment and survival data will be collected for all patients

after study end wherever possible.

Sample Size: We have used Simon’s optimal two stage design for Phase II trials for clinical

development of therapeutic cancer vaccines. This allows us to recruit patients to Stage 1, followed by

an interim evaluation to determine if there is evidence of efficacy by molecular monitoring, before

recruitment to Stage 2 of the design. If molecular responses are detected, 25 (giving a total of 37) more

patients will be recruited in Stage 2 of the design. Any patient lost to follow-up before 6 months will be

replaced by new recruits to ensure that we have 12 and 37 evaluable patients at Stage 1 and Stage 2,

respectively.

Based on the safety of DNA vaccines using our fusion vaccines and additionally the safety of WT1

vaccination with peptides, recommendation of early termination by the TMG/DSMB due to toxicity is not

anticipated.

HLA A2 negative patients will also be followed in parallel. The purpose of this is to allow us to: 1)

prospectively confirm our existing data that in unvaccinated patients the BCR-ABL transcripts change by

less than 0.2 log/ annum, 2) prospectively validate WT1-transcript analysis as an informative biomarker

for vaccine success and 3) to estimate a possible size of effect from the vaccine that may inform study

design (including sample size calculations) for a future Phase III clinical trial.

Planned analyses, outcome measures: Primary endpoint is molecular response in BCR-ABL

transcripts by qPCR. A responder will have a 1+ log decrease in transcript at two or more time-points in

the 6 months following vaccination. Secondary endpoints: change in WT1 transcript levels;

immunological response, defined by frequency, phenotype and function of WT1-epitope specific T cells.

A responder will have >2fold increase in WT1 specific CD8 T cells at 1 or more timepoints, using

validated assays for CD8 responses to WT1 epitopes by ELISPOT and tetramer staining. Cytotoxicity

assays against autologous tumour cells and multi-parametric characterization of T cell responses by

FACS will be undertaken; DTH responses will test T cell homing to peptide challenge. Consent to collect

information on time to disease progression and survival beyond the 24 months trial participation will be

sought. We will use summary statistics and plots to examine secondary endpoints, to characterize the

level, kinetics and responses rates of molecular/clinical responses and time to progression.


Immunological responses will be correlated to molecular response data and to time to progression. We

will not make inferences from comparisons between the vaccinated and control groups, but use the

data to inform the design of future Phase III trial if it is warranted. Toxicity/safety data will be collected

at each study visit.


1. Bhatia, R., Holtz, M., Niu, N., Gray, R., Snyder, D. S., Sawyers, C. L., Arber, D. A., Slovak, M. L.,

Forman, S. J. (2003). Persistence of malignant hematopoietic progenitors in chronic myelogenous

leukemia patients in complete cytogenetic remission following imatinib mesylate treatment. Blood 101:

4701-4707.

2. Rice, J., Ottensmeier, C. H., Stevenson, F. K. (2008). DNA vaccines: precision tools for activating

effective immunity against cancer. Nat Rev Cancer 8: 108-120.

3. Low, L., Mander, A., McCann, K. J., Dearnaley, D., Tjelle, T. E., Mathiesen, I., Stevenson, F. K.,

Ottensmeier, C. H. (2009). DNA vaccination with electroporation induces increased antibody responses

in patients with prostate cancer. Hum Gene Ther.

4. Ottensmeier, C. H. H., Low, L., Mander, A., Williams, A., Tjelle, T., Campos-Perez, J., Heath, C.,

Dearnaley, D. P., Mathiesen, I., Stevenson, F. (2008). DNA fusion gene vaccination, delivered with or

without in vivo electroporation - a potent and safe strategy for inducing anti-tumor immune responses

in prostate cancer. . American Association for Cancer Research Annual Meeting. 2008: abstract 300.

5. Inoue, K., Ogawa, H., Sonoda, Y., Kimura, T., Sakabe, H., Oka, Y., Miyake, S., Tamaki, H., Oji,

Y., Yamagami, T., Tatekawa, T., Soma, T., Kishimoto, T., Sugiyama, H. (1997). Aberrant overexpression

of the Wilms tumor gene (WT1) in human leukemia. Blood 89: 1405-1412.

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(2000). Selective elimination of leukemic CD34(+) progenitor cells by cytotoxic T lymphocytes specific

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Asada, M., Ueda, K., Maruya, E., Saji, H., Kishimoto, T., Udaka, K., Sugiyama, H. (2000). Human

cytotoxic T-lymphocyte responses specific for peptides of the wild-type Wilms' tumor gene (WT1 )

product. Immunogenetics 51: 99-107.

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Shirakata, T., Nishida, S., Nakajima, H., Morita, S., Sakamoto, J., Kawase, I., Oji, Y., Sugiyama, H.

(2007). Clinical and immunologic responses to very low-dose vaccination with WT1 peptide (5

microg/body) in a patient with chronic myelomonocytic leukemia. Int J Hematol 85: 426-429.

9. Oka, Y., Tsuboi, A., Murakami, M., Hirai, M., Tominaga, N., Nakajima, H., Elisseeva, O. A.,

Masuda, T., Nakano, A., Kawakami, M., Oji, Y., Ikegame, K., Hosen, N., Udaka, K., Yasukawa, M.,

Ogawa, H., Kawase, I., Sugiyama, H. (2003). Wilms tumor gene peptide-based immunotherapy for

patients with overt leukemia from myelodysplastic syndrome (MDS) or MDS with myelofibrosis. Int J

Hematol 78: 56-61.


10. Rezvani, K., Yong, A. S., Mielke, S., Savani, B. N., Musse, L., Superata, J., Jafarpour, B., Boss,

C., Barrett, A. J. (2008). Leukemia-associated antigen-specific T-cell responses following combined PR1

and WT1 peptide vaccination in patients with myeloid malignancies. Blood 111: 236-242.

11. Tsuboi, A., Oka, Y., Udaka, K., Murakami, M., Masuda, T., Nakano, A., Nakajima, H.,

Yasukawa, M., Hiraki, A., Oji, Y., Kawakami, M., Hosen, N., Fujioka, T., Wu, F., Taniguchi, Y., Nishida,

S., Asada, M., Ogawa, H., Kawase, I., Sugiyama, H. (2002). Enhanced induction of human WT1-specific

cytotoxic T lymphocytes with a 9-mer WT1 peptide modified at HLA-A*2402-binding residues. Cancer

Immunol Immunother 51: 614-620.

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Nishida, S., Shirakata, T., Nakatsuka, S., Sasaki, A., Udaka, K., Dohy, H., Aozasa, K., Noguchi, S.,

Kawase, I., Sugiyama, H. (2004). Induction of WT1 (Wilms' tumor gene)-specific cytotoxic T

lymphocytes by WT1 peptide vaccine and the resultant cancer regression. Proc Natl Acad Sci U S A 101:

13885-13890.

13. Chaise, C., Buchan, S. L., Rice, J., Marquet, J., Rouard, H., Kuentz, M., Vittes, G. E., Molinier-

Frenkel, V., Farcet, J. P., Stauss, H. J., Delfau-Larue, M. H., Stevenson, F. K. (2008). DNA Vaccination

Induces Wt1-Specific T-Cell Responses with Potential Clinical Relevance. Blood.


A Phase I study to assess safety of WT1 peptide vaccination in nonmyeloablative chemotherapy-induced lymphophenic acute myeloid leukemia patients in complete remission

Antonio Curti, Institute of Hematology and Medical Oncology “L. and A. Seràgnoli”, Bologna, Italy

This study is a spontaneous, prospectic, non-randomized, open-label, multicenter, Phase I study of a

Wilms’ tumor 1 (WT1)-derived vaccine (WT1-VAX) administered before and after nonmyeloablative

conventional chemotherapy, which includes antracyclines and cytarabine as part of post-remission

consolidation strategy. AML patients fulfilling the inclusion criteria will be enrolled in the study. In

particular Adult (≥ 18 and ≤ 70 years old) AML patients in hematological complere remission (CR), who

are considered fit for a chemotherapy-based consolidation program, with expression of WT1 mRNA in

BM blasts at diagnosis and HLA-A*0201–positivity will be enrolled.

The primary endpoints of the trial are to evaluate the feasibility and toxicity associated with the

immunotherapy approach of nonmyeloablative chemotherapy-induced lymphodepletion, followed by

lymphocyte infusion and WT1 peptide vaccination (WT1-VAX) in AML patients with CR. The secondary

endpoints are: 1) to evaluate the anti-leukemia efficacy of lymphodepletion followed by lymphocyte

infusion and WT1-VAX in terms of overall survival and time to relapse; 2) to evaluate in vivo and in vitro

peptide-specific immune response induced by the vaccinations after immunization at different time

points; 3) in patients with hematologic, but not molecular CR, to evaluate the molecular response to

treatment. The molecular response to WT1-VAX is defined as reduction by at least 50% of the

peripheral blood and/or bone marrow WT1 transcript; 4) in patients with hematologic, but not

molecular CR, to evaluate the rate of complete molecular response observed at any time after

immunization (complete molecular response = WT1 negative quantitative-RT-PCR)

Treatment plan will consist in:

1) one prechemotherapy vaccination, followed by the collection of vaccine-primed lymphocytes;

2) chemotherapy administration followed by reinfusion of vaccine-primed lymphocytes;

3)post-chemotherapy vaccination consisting in 6 vaccinations, each every two weeks (“immunization”)

followed by 3 monthly boosts of vaccine (“reinforcement” boosts) and 2 further boosts every 3 months

(“maintenance” boosts) for a total of 1 year (study core).

WT1-VAX is made of two components, which include two WT1-derived peptides (WT1 126-134, WT1

235-243) and GM-CSF. WT1 peptides will be emulsified in incomplete Freund’s adjuvant (Montanide

ISA-51 VG).

Twenty-five patients are expected to be enrolled within 36 months. The expected number of eligible

patients per year is 15 with a proportion of patients who will accept to enter the trial of 80-90%.


Molecular and clinical features of refractory anemia with ringed sideroblasts associated with marked thrombocytosis (RARS-T)

Matteo G. Della Porta, Department of Hematology Oncology, University of Pavia & Fondazione

IRCCS Policlinico San Matteo, Pavia, Italy

Within myeloid neoplasms, myelodysplastic syndromes (MDS) are characterized by ineffective

hematopoiesis and cytopenia, while myeloproliferative neoplasms (MPN) are typically associated with

overproduction of mature blood cells. However, the existence of conditions with overlapping features is

well established. The World Health Organization (WHO) classification comprises the category of

myelodysplastic/myeloproliferative neoplasms (MDS/MPN): one of these conditions is the provisional

entity defined as refractory anemia with ringed sideroblasts (RARS) associated with marked

thrombocytosis (RARS-T). (1)

Mutations in JAK2 and/or MPL have been detected in a substantial portion of patients with RARS-T,

suggesting a potential relationship between these mutant genes and the myelodysplastic syndrome

characterized by ringed sideroblasts. (2-4) At the same time, the presence of these mutations has raised

the question whether RARS-T is a form of essential thrombocythemia rather than a separate disorder.

(4)

In order to gain a deeper insight into the pathophysiology of RARS-T, we studied a

cohort of patients with myeloid neoplasms and investigated the relationship between

thrombocytosis, ringed sideroblasts, JAK2 or MPL mutations, clonality of haematopoiesis and CD34+

cell gene expression profiles. (5)

We studied 187 patients diagnosed with BCR/ABL1-negative myeloid neoplasm at the

Department of Hematology Oncology, University of Pavia Medical School, between 2001 and 2006.

RARS-T was defined according to the following WHO criteria: i) refractory anemia associated with

erythroid dysplasia and ringed sideroblasts ≥ 15%; ii) < 5% blasts in the bone marrow; iii) platelet

count ≥ 450 X 109/L; iv) presence of large atypical

megakaryocytes; v) absence of del(5q), t(3;3)(q21;q26) or inv(3)(q21q26). 19 cases of RARS-T were

identified in the study cohort. Three patients with MPN (all affected with primary myelofibrosis) had

ringed sideroblasts (at least 15%) and thrombocytosis.

JAK2 (V617F) mutation was detected in circulating granulocytes from 10 of 19 RARS-T patients, and in

two of five patients with MDS/MPN, whereas this somatic mutation was not found in any of the RARS

patients. Three RARS patients progressed to RARS-T, and two of them acquired JAK2 (V617F) at this

time. The median percentage of mutant alleles in granulocytes of RARS-T patients was 10.4% (range

1.1-27.7%). JAK2 (V617F) mutation was also detected in purified bone marrow CD34+ cells. By

contrast, JAK2 or MPL mutations were never found in T lymphocytes. Two patients carrying JAK2


(V617F) also carried the MPL (W515L) mutation (20% and 25% of mutant alleles, respectively). A

patient who was negative for JAK2 (V617F) was found to carry a JAK2 exon 12 mutation, with about

10% of mutant alleles.

Clonality of haematopoiesis was evaluated by X-chromosome inactivation patterns (XCIP) analysis. Of 8

informative female patients with RARS-T, 7 had clonal XCIP based on studies of circulating granulocytes

and T lymphocytes, and these patterns were confirmed in purified CD34+ cells. Three of the 7 RARS-T

patients with clonal XCIP carried JAK2 (V617F). The proportion of clonal granulocytes ranged from 95%

to 100%, while the proportion of granulocytes carrying JAK2 (V617F) ranged from 11.2% to 55.4%

(median value 27%). Therefore, granulocytes carrying the JAK2 (V617F) mutation represented only a

fraction of clonal granulocytes in these women.

Finally we compared gene expression profiles of CD34+ cells from 12 patients with

RARS and 6 patients with RARS-T. 255 genes were found to be differentially

expressed. Forty-six genes were found to be differentially expressed in all 6 cases of RARS-T, and eight

of these showed a relative expression ratio >=2. In particular, CXCR4, a gene encoding a CXC

chemokine receptor specific for stromal cell-derived factor-1 and reported to be down-regulated in

primary myelofibrosis, was markedly down-regulated in RARS-T patients. JCTSG (encoding cathepsin)

and JLTF (encoding lactoferrin and inhibited by STAT5 activation) were also markedly down-regulated.

A series of genes involved in cytoskeleton organization and megakaryocyte differentiation/maturation

(like CDC2L5, ARHGAP12, and PLDN) were found to be differentially expressed. On the other hand,

both RARS and RARS-T patient groups consistently showed up-regulation of ALAS2 (6) and

downregulation of ABCB7 in CD34+ cells.

In conclusion, our observations indicate that RARS-T is a myeloid neoplasm with

both myelodysplastic (RARS-like) and myeloproliferative (essential thrombocythemia-like)

features at the molecular and clinical level, and that it may develop from a preexisting

RARS through the acquisition of somatic mutations of JAK2, MPL or other

as-yet-unknown genes. Thus, the current designation of MDS/MPN appears to

accurately reflect the underlying biology of RARS-T.

References

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Clonality studies using acquired mitochondrial DNA point mutations Norbert Gattermann, Dept. of Hematology/Oncology, Heinrich-Heine-University, Düsseldorf

In myelodysplastic syndromes it is sometimes possible to achieve cytogenetic remissions, e.g. by

epigenetic treatment. However, it remains unclear whether these cytogenetic responses reflect a return

to polyclonal normal hematopoiesis, or reflect suppression/eradication of the most malignant subclone

that became dominant during clonal evolution. In the latter case, the bone marrow would remain clonal

even though the chromosomal marker of clonality disappears. The persistence of myelodysplastic

morphological features in the bone marrow of patients achieving cytogenetic remission can provide a

hint that clonality may indeed persist. This should not be interpreted as treatment failure, because

return to a less advanced stage of MDS may significantly improve the patient’s prognosis. Nevertheless,

in order to better understand the mechanism of action of a new treatment approach in MDS, it would

be interesting to find out whether a substantial proportion of patients achieve a true polyclonal

remission.

How can clonality be assessed in the bone marrow? Analysis of X-chromosome inactivation patterns

(XCIP) can only be employed in female patients. Furthermore, this method has a low sensitivity. A

reliable diagnosis of clonality requires more than 50% of bone marrow cells to belong to the same

clone. A new option for clonality analysis arises from the fact that about 40% of patients with various

types of leukemia (He et al., 2003) and about 50-60% of patients with MDS (Wulfert et al., 2008) have

an acquired mutation of mitochondrial DNA in their clonal hematopoietic cells. There is reason to

believe that the mitochondrial DNA mutation occurred in the respective hematopoietic stem cell long

before the latter suffers (pre)leukemic transformation. Accordingly, mtDNA mutations present early

events in the clonal evolution of MDS, which, in contrast to some late-acquired chromosomal

abnormalities, will not be lost when MDS returns to a less advanced stage after treatment.

Efficient scanning for mtDNA mutations can be based on heteroduplex analysis of mtDNA with

denaturing HPLC, followed by DNA sequencing of suspicious fragments (Wulfert et al., 2006). This

technique allows detection of clones comprising less than 10% of bone marrow cells. Therefore, follow-

up of a clonal mtDNA marker, in addition to cytogenetic follow-up, should allow to answer the question

whether cytogenetic remission, or in fact any type of clinical remission, is associated with reversal of

clonality.

Mutation discovery by heteroduplex analysis is based on the following principle: If a PCR product

contains a mixture of wild-type and mutant DNA, heat denaturation of the amplified material followed

by renaturation will not only allow reannealing of the perfectly matched, fully complementary strands

(homoduplexes), but will also allow the formation of heteroduplexes, which have a pair of non-fitting

bases (mismatch) at one position. Since a nucleotide mismatch reduces the thermodynamic stability of


double stranded DNA, heteroduplexes have a lower melting temperature than homoduplexes. At a

certain temperature, homoduplexes are still double-stranded while heteroduplexes are already partially

denatured. At that temperature, the two DNA species can be separated by dHPLC because their binding

to the dHPLC column differs. The difference in melting temperature between homo- and heteroduplexes

is strongly dependent on the nucleotide sequence of the respective DNA fragment. Therefore, length

and position of DNA fragments must be chosen quite carefully to favour large differences in melting

temperatures, thus enabling all possible point mutations to be detected.

Denaturing HPLC can be performed with the WAVE-System (Transgenomic, Crewe, UK), which allows

the conformation-dependent separation of nucleic acids by means of ion-pair reversed-phase liquid

chromatography.

Heteroduplex analysis of the mitochondrial genome has been successfully performed in our laboratory

for several years. We propose to use this method for clonality studies in the planned VIVAVACS

vaccination trial.

He L, Luo L, Proctor SJ, Middleton PG, Blakely EL, Taylor RW, et al. Somatic mitochondrial DNA

mutations in adult-onset leukaemia. Leukemia 2003; 17: 2487-2491.

Gattermann N: Mitochondrial DNA mutations in the hematopoietic system. Leukemia 18: 18-22, 2004

Gattermann, N., Wulfert, M., Junge, B., Germing, G., Haas, R., Hofhaus, G.: Ineffective hematopoiesis

linked with a mitochondrial tRNA mutation (G3242A) in a patient with myelodysplastic syndrome.

Blood 103: 1499-1502, 2004.

Wulfert M, Tapprich C, Gattermann N: Optimized PCR fragments for heteroduplex analysis of the whole

human mitochondrial genome with denaturing HPLC. J Chromatogr B Analyt Technol Biomed Life Sc.

2006 831:236-47

Wulfert M, Küpper AC, Tapprich C, Bottomley SS, Bowen D, Germing U, Haas R, Gattermann N:

Analysis of mitochondrial DNA in 104 patients with myelodysplastic syndromes. Experimental

Hematology 2008; 36:577-586


Mislocalized activation of Flt3-ITD switches downstream signaling outcomes Hubert Serve1, Christian Brandts1, Matthias Mann2, Chunaram Choudhary3

1Department of Medicine, Hematology/Oncology, Goethe-University of Frankfurt, Germany 2Max-Planck-Institute for Biochemistry, Munich, Germany 3The NNF Center for Protein Research, University of Copenhagen, Denmark

Transformation in AML is caused by a combination of oncogenic events involving transcription factor

mutations, epigenetic changes and mutations leading to activated growth factor receptor signaling.

Mutations of the receptor tyrosine kinase FLT3 have been shown to be the cause of constitutive signal

activation in many AML cases. However, the most frequent of these mutations, internal tandem

duplications (Flt3-ITD) induce an intracellular signal that is significantly different from ligand-activated

wild-type FLT3 (FLT3-WT). For example, FLT3-ITD aberrantly activates Wnt signaling, inhibits myeloid

transcription factors and strongly activates STAT5, possibly contributing to leukemic transformation on

multiple levels. We were interested in the molecular mechanism responsible for the mutational change

in FLT3 signal specificity and hypothesized that signal compartmentalization is important for this

phenomenon. Therefore, we analyzed FLT3-ITD signal transduction after pharmacologically trapping the

receptor in different cellular compartments. Endoplasmic reticulum retained FLT3-ITD activates STAT5

and upregulates its targets Pim-1/2 but fails to activate PI3-K and MAPK. Conversely, membrane

targeting of Flt3-ITD strongly activates the MAPK and PI3-K pathways with diminished activation of

STAT5. Global, quantitative phosphoproteomics confirmed compartment-specific activation of these

pathways and discovered many components of Flt3 signaling and their spatial activation. Furthermore,

these experiments revealed unique, compartment-specific phosphorylation patterns of different tyrosine

residues of the receptor itself. The data suggest a new paradigm in oncogenic signaling where major

signaling nodes are organized in a compartment-specific manner that can be exploited by oncogenic

RTKs to activate aberrant signaling and to evade negative regulation. Understanding these mechanisms

will be essential to design therapeutic strategies that specifically target oncogenic RTK signal

transduction.


Workgroup 5: e-Technologies

Leukemia Gene Atlas

Martin Dugas, Christian Ruckert, Hans-Ulrich Klein

Department of Medical Informatics and Biomathematics, University of Münster, Germany

This project aims to provide a database of all relevant published molecular leukemia data (genetic as

well as epigenetic) in conjunction with available laboratory and clinical information. It follows a similar

approach like the project REMBRANDT (http://rembrandt.nci.nih.gov) of the National Cancer Institute

regarding data on brain tumors.

All available molecular data types shall be included: in particular gene expression, single-nucleotide-

polymorphisms (SNP), chromatin immunoprecipitation with microarray technology (ChIP-chip) and

chromatin immunoprecipitation with massively parallel DNA sequencing (ChIP-Seq).

The basic function of the leukemia gene atlas will be a browser with flexible search methods. In

contrast to general repositories like GEO or ArrayExpress, a leukemia-specific annotation and

classification of experiments and clinical data will be provided. Manually curated gene lists and gene

signatures will be collected and structured according to an ontology of leukemias. It is intended to

provide a system for semi-automated, cross-platform analysis of new experimental molecular leukemia

data. New findings can be compared with published gene signatures to identify similar or divergent

results. The overall goal is to improve interpretation of new molecular data on leukemia, in particular

from high-throughput platforms.

Acknowledgements

Leukemia Gene Atlas is funded by the Deutsche José Carreras Leukämie-Stiftung.

Collaborating partners: Carsten Müller-Tidow, Münster; Torsten Haferlach, Munich;

Phillip Koeffler, Los Angeles; Christian Thiede, Dresden; Wolf-Karsten Hofmann, Mannheim; Lars

Bullinger, Ulm


Machine learning applied to unravel a biomarker gene network associated to AMLs in contrast to other leukemias

C. Fontanillo, A. Risueño, J.M. Hernandez-Rivas and J. De Las Rivas

Bioinformatics and Functional Genomic Group, Cancer Research Center, Salamanca, Spain

A major focus of machine learning (ML) research applied to biomedical studies is to automatically learn

to recognize complex patterns and make intelligent decisions based on biomolecular data that

characterize a certain disease type or sub-type. Gene expression profiles derived from genome-wide

microarray data have been efficiently applied to build disease classifiers using ML methods.

We have designed a robust ML method to find not only the set of genes – i.e. variable features – that

best predict a given bio-pathological state, but which allows to identify all genes associated to a

disease with certain significance and build classifiers that are based on groups of genes where gene-to-

gene association is kept and identified. We applied this strategy to a collection leukemia samples and

we identified a gene network specifically associated to each disease type. The method provides a multi-

class classifier and we used bone marrow samples from the 4 major types of leukemia (ALL, AML, CLL,

CML) patients plus a set of normal bone marrow samples. We focus on the analysis of acute myeloid

leukemias (AML) with normal karyotype data and we identify ANGPT1 and DEPDC6 as the genes with

best discriminant power for this class. This genes are upregulated and closely linked both by interaction

and correlation derived from the expression profiles.


Analysis of transcriptional and post-transcriptional regulatory networks

Silvio Bicciato1, Stefania Bortoluzzi2, Massimo Marchiori3, Antonino Neri4 1Dipartimento di Scienze Biomediche, Università di Modena, Italy 2Dipartimento di Biologia, Università di Padova, Italy 3Dipartimento di Matematica Pura ed Applicata, Università di Padova, Italy 4Dipartimento di Scienze Mediche, Università di Milano, Italy

Reconstructing regulatory network from expression data is a crucial step to understand the mechanisms

underlying biological systems. However, the high number of genes and interactions still represents a

challenging issue for the extraction of relevant targets and relationships from such large systems. A

standard approach is searching targets among the most connected genes (hubs) or among sub groups

of genes known to be relevant in the analyzed phenotype. The goal of this type of analysis is to identify

previously unknown relationships that can be the object of a subsequent experimental validation. An

alternative approach is studying the network characteristics to identify groups of genes organized in

sub-networks, which may suggest novel interactions and shed light on regulatory modules involving

these genes or their common targets. Although effective, both strategies require the prior knowledge of

the genes of interest, thus hampering the capacity of extracting de-novo knowledge from the network.

A way to overcome this limitation could be adapting techniques commonly used in the analysis of

communication and infrastructure networks. In these fields, a key analysis is the resilience of the

network to external disturbances and to malfunctioning. Network robustness strongly relies on the

network structure and, in particular, on the existence of paths between the nodes. When nodes or links

are removed, the lengths of these paths can increase and some nodes will become disconnected. It is

therefore interesting to find the critical component of the network, i.e. the nodes or edges that are

really important for the functioning of the network. Applying this concept to regulatory network, critical

nodes and edges are critical genes and critical regulatory interaction, respectively. Usually the most

important nodes are considered the most connected ones (hubs), but this is not always the case. In

genetic networks a gene can be connected to many genes simply because it is a transcription factor that

normally controls many targets or a gene that is controlled by many other genes.

The critical analysis of network components has been applied to inspect the transcriptional and post-

transcriptional regulatory networks reconstructed from mRNA and miRNA expression data of multiple

myeloma samples. The transcriptional and post-transcriptional networks were reconstructed using

ARACNe and the Pearson correlation coefficient of the expression vectors of miRNA target genes,

respectively. Both networks showed a scale free structure, i.e. a type of structure reported with evidence

in lower organisms, but still argument of debate in eukaryotes. Both networks are also slightly


assortative, meaning that they tend to have an aristocratic behavior where nodes with high degree tend

to connect with nodes with similar degree. This suggests a hierarchical control mechanism. The analysis

of critical components revealed that genes with a limited number of connections could be critical for the

structure of the network and that hubs are not necessarily critical nodes. Indeed, about one half of most

connected nodes in each considered network were not included in the corresponding list of most critical

nodes and some genes, characterized by a low node degree, were instead critical. These non-hub

critical nodes would have been disregarded as putative regulatory targets due to their limited number of

connections although they may open new clues to the detection of key regulatory circuits. Finally, the

integration of the transcriptional and post-transcriptional levels allowed identifying critical genes for

both types of regulatory interactions and dissecting direct critical relationships at transcriptional level

from interaction that are instead indirect since mediated by post-transcriptional regulation.


Data fusion for cancer genomics

Leo Lahti

Department of Information and Computer Science, Helsinki University of Technology TKK, Finland

Different measurement techniques provide complementary views to biological phenomena. Inherent

noise in high-throughput data sets and the complexity of living organisms set challenges for data

analysis. By combining information over multiple sources it is possible to guide the analysis and reduce

uncertainty.

The presentation gives an overview of our recent probabilistic approaches for detecting functional copy

number changes and tumor-specific gene expression signatures in pathway interaction networks. These

provide general computational tools for functional genomics in cancer studies.


Filtering of low-signal probesets improves enrichment analysis in microarray studies

Krzysztof Goryca 1,2, Lucjan S. Wyrwicz2 1 Medical Center for Postgraduate Education, Warszawa, Poland 2 Maria Skłodowska-Curie Memorial Cancer Center, Warszawa, Poland

One of the main concerns of microarray experiments is a translation of gene expression measurements

into biological hypotheses. The typical approach is identification of differentially expressed genes in two

groups of samples (eg. diseased and controls). Application of various functional classifications of genes

(Gene Ontology, KEGG) is used to select such groups of genes (e.g. pathways, components of specific

macromolecular complex), which are significantly enriched in a given set of differentially expressed

genes.

Unfortunately, Gene Ontology (GO) enrichment tests performed for oligonucleotide microarrays

measurements are biased by microarray construction and physiological RNA concentration distribution.

High noise level during measurement process makes it difficult to detect changes in expression of low

abundant transcripts. Because of low signal-to-noise ratio, most genes for which differential expression

is detected are those with high signal level. This shifts GO enrichment analysis of differential versus

constant genes toward high abundant versus low abundant comparison.

We show that identification of various biological processes in uncorrected GO enrichment analysis can

lead to partially incorrect conclusions. Among the processes with high overrepresentation affected by

this bias are RNA processing, translation, protein folding and others belonging to basic cellular

metabolism. Moreover, filtration of low-signal probesets reduces the mentioned bias without significant

loss of sensitivity of analyses.


Independence screening approaches for Cox models with high dimensionality

Manuela Zucknick, Thomas Hielscher, Axel Benner

Division of Biostatistics, German Cancer Research Centre, Heidelberg, Germany

Sparse penalised likelihood methods can perform variable selection in very high-dimensional

applications. For methods like SCAD or adaptive lasso, model consistency as well as asymptotic

unbiasedness of the relevant regression coefficients have been proven under certain conditions.

However, in high-dimensional situations both SCAD and adaptive lasso require an initial screening step

to reduce the number of potential predictors to a number smaller than the sample size. Approaches that

have been used for initial screening include univariate thresholding and lasso, but until the recent

important paper by Fan and Lv (2008) not much research had been available on properties of a good

screening method.

The iterative sure independence screening (ISIS) method proposed by Fan and Lv is related to lasso via

the LARS algorithm and its connection to componentwise L2-boosting. This connection and the

asymptotic results given by Fan and Lv give indications, in which data situations lasso and related

approaches might perform well as screening methods and when the methods might fail.

Sure independence screening was developed within the context of the linear model. However, we are

here interested in censored data applications. We adopt existing screening approaches for survival

analysis (e.g. Tibshirani, 2009) and relate them to the concepts outlined by Fan and Lv. We present

results of simulations and real data applications, in which we investigate the impact of different initial

screening methods in the context of Cox proportional hazards regression. We compare the approaches

with respect to variable selection performance as well as prediction accuracy of fitted models.

References

Fan, J. and Lv, J. (2008). Sure independence screening for ultrahigh dimensional feature space. Journal

of the Royal Statistical Society, Series B: Statistical Methodology, 70: 849–911.

Fan J, Samworth R, Wu Y (2009). Ultra-dimensional variable selection via independent learning: beyond

the linear model. Journal of Machine Learning Research, to appear.

Tibshirani R (2009). Univariate shrinkage in the Cox model for high dimensional data. SAGMB 8:21.


Mediante: a web-based microarray data manager

Chimène Moreilhon1,2,3, Kevin Lebrigand2,3, Sophie Raynaud1,3, Pascal Barbry2,3

1CHU de Nice, Laboratoire d'oncohématologie, Hôpital Pasteur, Nice, France 2CNRS, IPMC, UMR6097, Sophia Antipolis, France 3Université de Nice Sophia-Antipolis, IPMC, UMR6097, Sophia Antipolis, France

Mediante (http://www.microarray.fr) is a MIAME-compliant microarray data manager that integrates:

a management system for production of DNA microarrays,

an experimental data repository suitable for home-made or commercial microarrays

(Agilent, Affymetrix, Phalanx,…),

a user interface dedicated to the management of microarrays projects.

several tools for assessment of probes quality, quality control of hybridizations, data

analysis and submission of validated data to public repositories.

Mediante has recently been extended with the miRSuite web portal

(http://www.microarray.fr:8080/merge/index ) that integrates four distinct tools:

MicroCible visualizes the interactions between one or several miRNAs and a list of transcripts,

based on exact matches between the “seed” region of the miRNA and the 5’-UTR, 3’-UTR, or

CDS of the transcripts. Output lists miRNA/transcript interactions according to decreasing

energy of the complexes.

MicroTopTable looks into an output of microarray analysis whether a miRNA can contribute

to the down-regulation of mRNA expression. The approach is similar to the one developed by

van Dongen et al. (2008) for detecting miRNA binding (and also siRNA off-target) effects from

expression data.

TargetPrediction summarizes the different predictions made by the mostly used target

prediction programs (TargetScan, mirbase target, picTar, or perfect seed-match). The user can

select either a specific miRNA or a gene symbol.

MicroSite provides information about the genomic location and precursors of a putative

miRNA sequence.


List of Participants Abáigar Alvarado, María C/Cuarta n° 6, 5°B 37007 Salamanca Spain Tel.: +34 606817847 Email: [email protected] Andersen, Morten T. Rigshospitalet, Copenhagen University Hospital Department of Clinical Genetics Haematology-Oncology Section 4052 Blegdamsvej 9 2100 Copenhagen Denmark Tel.: +45 3545 4587 Email: [email protected] Barkadottir, Rosa Björk Department of Pathology Molecular Biology Unit HOUSE 9 v/Baronstig Landspitali-University Hospital Reykjavik Iceland Tel.: +354 822 1610 Email: [email protected] Baum, Christopher Hannover Medical School Department of Experimental Hematology Carl-Neuberg-Str. 1 30625 Hannover Germany Tel.: +49 511 532 6067 Email: [email protected]


Béné, Marie-Christine PU-PH en Immunologie CHU et Faculté de Médecine de Nancy Nancy Université 9 Avenue de la Forêt de Haye 54500 Vandoeuvre les Nancy France Tel.: +33 3 83 68 36 60 Email: [email protected] Benner, Axel Biostatistik (C060) DKFZ INF 280 69120 Heidelberg Germany Tel.: +49 6221 42 2390 Email: [email protected] Bicciato, Silvio Dept. of Biomedical Sciences University of Modena and Reggio Emilia Via G. Campi, 287 41100 Modena Italy Tel.: +39 059 205 5219 Email: [email protected] Birger, Yehudit 12 Bashan St. Ramat Hasharon 47213 Israel Tel.: +972 3 5308137 Email: [email protected] Boehrer, Simone Service d’hématologie clinique Hôpital Avicenne 125, rue de Stalingrad 93009 Bobigny France Tel.: +33 6 12 98 78 36 Email: [email protected]


Bullinger, Lars Albert-Einstein-Allee 23 89081 Ulm Germany Tel.: +49 731 500 45501 Email: [email protected] Cockerill, Peter Experimental Haematology Leeds Institute of Molecular Medicine University of Leeds St. James’s Hospital Leeds LS9 7TF UK Tel.:+44 113 3438639 Email: [email protected] Crescenzi, Barbara Hematology University of Perugia University Hospital S. Maria della Misericordia Bl. B, piano -2 06156 Perugia Italy Tel.: +39 075 578 3808 Email: [email protected] Curti, Antonio Institute of Hematology and Medical Oncology “L. and A. Seràgnoli” Via Massarenti, 9 40137 Bologna Italy Tel.: +39 051 636 3680 Email: [email protected] Danen-van Oorschot, Astrid Dept. of Pediatric Oncology/Hematology Erasmus MC – Sophia Children’s Hospital Dr. Molewaterplein 50 3015 GE Rotterdam The Netherlands Tel.: +31 10 704 4640 Email: [email protected]


De Las Rivas, Javier Cancer Research Center (CiC-IBMCC, CSIC/USAL) 37007 Salamanca Spain Tel.: +34 923 294819 Email: [email protected] Della Porta, Matteo Division of Hematology IRCCS Fondazione Policlinico San Matteo University of Pavia Medical School P. le Golgi 19 27100 Pavia Italy Tel.: +39 0382 503062 Email: [email protected] Del Rey Gonzalez, Monica Centro de Investigación del Cancer Campus Miguel de Unamuno S/N 37007 Salamanca Spain Tel.: +34 6868 53122 Email: [email protected] De Vries, Andrica Erasmus MC – Sophia Children’s Hospital Dr. Molewaterplein 60 3015 GJ Rotterdam The Netherlands Tel.: +31 10 703 6691 Email: [email protected] Dugas, Martin University of Münster Department of Medical Informatics and Biomathematics Domagkstr. 9 48149 Münster Germany Tel.: +49 251 83 55262 Email: [email protected]


Ferrari, Sergio Dept. of Biomedical Sciences University of Modena and Reggio Emilia Via G. Campi, 287 41100 Modena Italy Tel.: +39 059 205 5400 Email: [email protected] Fitzgibbon, Jude Centre for Medical Oncology 3rd Floor John Vane Science Building Institute of Cancer Barts and the London Medical School Charterhouse Square London EC1M 6BQ UK Tel.: +44 207 882 3814 Email: [email protected] Fliegauf, Manfred Uniklinik Freiburg Innere Medizin I, Hämatologie/Onkologie AG Prof. Lübbert Breisacherstr. 117, Labor Nothnagel 79106 Freiburg Germany Tel.: 0761 270 7197 Email: [email protected] Flotho, Christian Pediatric Hematology and Oncology University of Freiburg Mathildenstr. 1 79106 Freiburg Germany Tel.: +49 761 270 4628 Email: [email protected]


Gattermann, Norbert Klinik für Hämatologie, Onkologie und klin. Immunologie Universitätsklinikum Düsseldorf Moorenstr. 5 40225 Düsseldorf Germany Tel.: +49 211 81 16500 Email: [email protected] Gemovic, Branislava Center for Multidisciplinary Research Institute of Nuclear Sciences VINCA P.O. Box 522 11001 Belgrade Serbia Tel.: +381 11 245 3686 Email: [email protected] Giannopoulos, Krzysztof Ul. Slavinkowska 16/3 20-810 Lublin Poland Tel.: +485 0203 8268 Email: [email protected] Gjertsen, Bjørn Tore Institute of Medicine Hematology Section University of Bergen Haukeland University Hospital 5021 Bergen Norway Tel.: +47 5597 5000 Email: [email protected] Glisic, Sanja Center for Multidisciplinary Research Institute of Nuclear Sciences VINCA P.O. Box 522 11001 Belgrade Serbia Tel.: +381 11 245 3686 Email: [email protected]


Göhring, Gudrun Hannover Medical School Institute of Cell and Molecular Pathology Carl-Neuberg-Str. 1 30625 Hannover Germany Tel.: +49 511 532 4517 Email: [email protected] Grønbæk, Kirsten Department of Hematology, L4042 Rigshospitalet Blegdamsvej 9 2100 Copenhagen Denmark Tel.: +45 3545 8895 Email: [email protected] Guenova, Margarita Lubenova National Hospital for Active Treatment of Haematological Diseases Laboratory of Haematopathology and Immunology 6 Plovdisko pole St. 1756 Sofia Bulgaria Tel.: +359 2 970 1222 Email: [email protected] Haase, Detlef Georg-August-Universität Robert-Koch-Str. 40 37075 Göttingen Germany Tel.: +49 551 39 8891 Email: [email protected] Hájková, Hana U Nemocnice 2094/1 12820 Prague 2 Czech Republic Tel.: +420 221 977 231 Email: [email protected]


Hellström-Lindberg, Eva Karolinska Institutet Department of Medicine/Hematology Karolinska University Hospital Huddinge 141 86 Stockholm Sweden Tel.: +46 8 5858 2506 Email: [email protected] Hernández, Jesus M. Department of Hematology Hospital Universitario de Salamanca Paseo San Vicente 58 37007 Salamanca Spain Tel.: +34 923 291384 Email: [email protected] Hofmann, Winfried Hannover Medical School Institute of Cell and Molecular Pathology Carl-Neuberg-Str. 1 30625 Hannover Germany Tel.: +49 511 532 9252 Email: [email protected] Iacobucci, Ilaria Department of Hematology and Oncological Sciences “L. and A. Seràgnoli” Via Massarenti, 9 40137 Bologna Italy Tel.: +39 348 762 2848 Email: [email protected] Iakovaki, Despina 3-5 Ilission Str. 115 28 Athens Greece Tel.: +30 210 77 70 870 Email: [email protected]


Knuutila, Sakari Haartman Institute Department of Pathology / CMG P.O. Box 21 (Haartmaninkatu 3) University of Helsinki 00014 Helsinki Finland Tel.: +358 9 191 26527 Email: [email protected] Kratz, Christian Clinical Genetics Branch Division of Cancer Epidemiology and Genetics National Cancer Institute National Institutes of Health Rockville, MD 20892 USA Tel.: +1 301-402-2183 Email: [email protected] Kreipe, Hans H. Hannover Medical School Institute of Pathology Carl-Neuberg-Str. 1 30625 Hannover Germany Tel.: +49 511 532 4500 Email: [email protected] Kuipers, Jenny Erasmus MC – Sophia Children’s Hospital Dr. Molewaterplein 50 3015 GE Rotterdam The Netherlands Tel.: +31 10 703 4054 Email: [email protected] Lahti, Leo P.O. Box 5400 02015 TKK Finland Tel.: +358 40 565 5872 Email: [email protected]


Lange Kathrin Hannover Medical School Institute of Cell and Molecular Pathology Carl-Neuberg-Str. 1 30625 Hannover Germany Tel.: +49 511 532 4516 Email: [email protected] Lehmann, Sören Department of Hematology, M54 Karolinska Institute Karolinska University Hospital, Huddinge 141 86 Stockholm Sweden Tel.: +46 8 58580000 Email: [email protected] Lehmann, Ulrich Hannover Medical School Institute of Pathology Carl-Neuberg-Str. 1 30625 Hannover Germany Tel.: +49 511 532 4475 Email: [email protected] Mecucci, Cristina Hematology University of Perugia University Hospital S. Maria della Misericordia Bl. B, piano -2 06156 Perugia Italy Tel.: +39 075 578 3808 Email: [email protected] Mills, Ken Queen’s University Belfast Centre for Cancer Research & Cell Biology Lisburn Road Belfast BT9 7BL Northern Ireland Tel.: +44 28 9097 2786 Email: [email protected]


Mohamedali, Azim M. King’s College London Dept. of Haematological Medicine The Rayne Institute 123 Coldharbour Lane London SE5 9NU UK Tel.: +44 207 848 5835 Email: [email protected] Moreilhon-Brest, Chimène Laboratoire oncohématologie Hôpital Pasteur Pavillon J niveau 0 30 voie Romaine 06002 Nice Cedex 2 France Tel.: +33 4 92 03 78 97 Email: [email protected] Müller-Tidow, Carsten Universitätsklinikum Münster (UKM) Medizinische Klinik und Poliklinik für Innere Medizin A Hämatologie und Onkologie Albert-Schweitzer-Straße 33 48149 Münster Tel.: +49 251-835 2995 Email: [email protected] Nedjalkow, Mihail Institute for Parallel Processing / Bulgarian Academy of Sciences ‘Acad. G. Bontchev Str. BL25A’ 1113 Sofia Bulgaria Tel.: +359 887202611 Email: [email protected] / [email protected] Nibourel, Olivier Laboratoire d’Hématologie CBP CHRU de Lille Bd du Pr Leclercq 59037 Lille Cedex France Tel.: +33 3 20 44 47 83 Email: [email protected]


Nomdedeu, Josep F. Laboratori d’Hematologia Hospital de la Santa Creu i Sant Pau Avda. Sant Antoni M. Claret, 167 08025 Barcelona Spain Tel.: +34 2919000 ext 2424 Email: [email protected] Nowak, Daniel Hämatologie und Onkologie Universitätsmedizin Mannheim Theodor-Kutzer-Ufer 1-3 68167 Mannheim Germany Tel.: +49 621-383 4115 Email: [email protected] Ottensmeier, Christian Cancer Sciences Division Southampton University Hospitals Tremona Road Southampton SO16 6YD UK Tel.: +44 2380 796184 Email: [email protected] Padua, Rose Ann Inserm U940 Insitut Universitaire d`Hématologie Hôpital St Louis 1 Avenue Claude Vellefaux 75010 Paris France Tel.: +33 1 53 72 40 72 Email: [email protected] Papancheva, Rumyana Faculty of Social Sciences University “Prof. Dr. A. Zlatarov” Prof. Yakimov bul. 1 8000 Burgas Bulgaria Tel.: +359 888 272944 Email: [email protected]


Perini, Giovanni University of Bologna Dept. of Biology via F. Selmi 340126 Bologna Italy Tel.: +39 051 209 4286 Email: [email protected] Plass, Christoph Deutsches Krebsforschungszentrum (DKFZ) C010 – Epigenomik und Krebsrisikofaktoren Im Neuenheimer Feld 280 69120 Heidelberg Germany Tel.: +49 6221 423300 Email: [email protected] Porse, Bo Copenhagen Biocenter BRIC, 3rd Floor Ole Maaløes Vej 5 2200 Copenhagen N Denmark Tel.: +45 3532 5620 Email: [email protected] Rack, Katrina Laboratoire Cytogénétique Institut de Pathologie et de Génétique Avenue Georges Lemaitre 25 6280 Gosselies Belgium Tel.: +32 71 447185 Email: [email protected] Raghavan, Manoj Centre for Medical Oncology Barts and The London School of Medicine and Dentistry Queen Mary’s School of Medicine Charterhouse Square London EC1M 6BQ UK Tel.: +44 797 1964979 Email: [email protected]


Raynaud, Sophie Laboratoire d’Oncohématologie Hôpital Pasteur CHU de Nice 30 avenue de la Voie Romaine 06000 Nice France Tel.: +33 4 92 03 88 75 Email: [email protected] Rezvani, Katy Imperial College Hammersmith Hospital 4th Floor Commonwealth Building Du Cane Road London W12 0NN UK Tel.: +44 208 383 2175 Email: [email protected] Ripperger, Tim Hannover Medical School Institute of Cell and Molecular Pathology Carl-Neuberg-Str. 1 30625 Hannover Germany Tel.: +49 511 532 4669 Email: [email protected] Roumier, Christophe Laboratoire d’Hématologie CBP CHRU de Lille Bd du Pr Leclercq 59037 Lille Cedex France Tel.: +33 3 20 44 58 80 Email: [email protected] Rousselot, Philippe Service d’Hématologie et d’Oncologie Hôpital Mignot 177 rue de Versailles 78157 Le Chesnay France Tel.: +33 1 39 63 86 22 Email: [email protected]


Royer-Pokora, Brigitte Institut für Humangenetik und Anthropologie Heinrich Heine University Düsseldorf Postfach 101007 40001 Düsseldorf Germany Tel.: +49 211 8112350 Email: [email protected] Rudolph, Cornelia Hannover Medical School Institute of Cell and Molecular Pathology Carl-Neuberg-Str. 1 30625 Hannover Germany Tel.: +49 511 532 4526 Email: [email protected] Sambani, Constantina NCSRD (National Centre for Scientific Research “DEMOKRITOS”) Health Physics / Cytogenetics 15310 Aghia Paraskevi Athens Greece Tel.: +30 210 650 3866 Email: [email protected] Schlegelberger, Brigitte Hannover Medical School Institute of Cell and Molecular Pathology Carl-Neuberg-Str. 1 30625 Hannover Germany Tel.: +49 511 532 4522 Email: [email protected] Schmidl, Christian University Hospital Regensburg Dept. of Hematology and Oncology Franz-Josef-Strauss Allee 11 93053 Regensburg Germany Tel. +49 941 944 5591 Email: [email protected] / [email protected]


Seedhouse, Claire Academic Haematology Clinical Services Building Nottingham University Hospitals – City Campus Hucknall Road Nottingham NG5 1PB UK Tel.: +44 115 823 1822 Email: [email protected] Serve, Hubert Medizinische Klinik II Hämatologie, Onkologie, Rheumatologie, Infektiologie Klinikum der Johann-Wolfgang Goethe-Universität Theodor-Stern-Kai 7 60590 Frankfurt am Main Germany Tel.: +49 69 6301 4634 Email: [email protected] Steinemann, Doris Hannover Medical School Institute of Cell and Molecular Pathology Carl-Neuberg-Str. 1 30625 Hannover Germany Tel.: +49 511 532 4669 Email: [email protected] Tagliafico, Enrico Center for Genome Research University of Modena and Reggio Emilia Via G. Campi 287 41125 Modena Italy Tel.: +39 059 205 5387 Email: [email protected] Te Kronnie, Geertruy Department of Paediatrics University of Padova via Giustiniani 3 35128 Padova Italy Tel.: +30 049 821 1455 Email: [email protected]


Theilgaard-Mönch, Kim Biotech Research and Innovation Center, Porse Group Copenhagen Biocenter, 3rd Floor University of Copenhagen Ole Maaløes Vej 5 2200 Copenhagen-N Denmark & Department of Hematology Lund University Hospital Getingevägen 4 221 85 Lund Sweden Tel.: +45 33325633, +46 70494690 Email: [email protected] / [email protected] Tordai, Attila National Blood Transfusion Service Molecular Diagnostics Laboratory Karolina u. 19 1113 Budapest Hungary Tel.: +36 1 372 4285 Email: [email protected] Trangas, Theoni Department of Biological Applications and Technologies University of Ioannina Greece Tel.: +30 210 77 70 870 Email: [email protected] Trka, Jan CLIP – Childhood Leukaemia Investigation Prague Dept. Paediatric Haematology/Oncology 2nd Faculty of Medicine Charles University Prague V uvalu 84 15006 Prague 5 Czech Republic Tel.: +420224436580 Email: [email protected]


Van den Heuvel-Eibrink, Marry M. Erasmus MC – Sophia Children’s Hospital Rm Sp 2568 Dr. Molewaterplein 60 3015 GJ Rotterdam The Netherlands Tel.: +31 10 703 6691 Email: [email protected] Veljkovic, Nevena Center for Multidisciplinary Research Institute of Nuclear Sciences VINCA Mihaila Petrovica 14-16 11001 Belgrade Serbia Tel.: +381 11 340 8471 Email: [email protected] Wainscoat, James S. LRF Molecular Haematology Unit Nuffield Department of Clinical Laboratory Sciences University of Oxford John Radcliffe Hospital Oxford OX3 9DU UK Tel.: +44 1865 762928 Email: [email protected] Wyrwicz, Lucjan Laboratory of Bioinformatics and Systems Biology Maria Skłodowska-Curie Cancer Memorial Center Ul. Roentgena 5 Warsaw Poland Tel.: +48 506 159 219 Email: [email protected]


Zemanova, Zuzana Center of Oncocytogenetics Department of Clinical Biochemistry and Laboratory Medicine General Teaching Hospital and First Faculty of Medicine Charles University U nemocnice 2 128 08 Prague 2 Czech Republic Tel.: +420 224 962 935 Email: [email protected]


The Organizers also wish to thank

and

Cluster of Excellence REBIRTH "From Regenerative Biology to Reconstructive Therapy" for their generous support

2nd Workgroup and 3rd Management Committee Meeting...

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