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Identification and functional characterisation of molecular risk factors in acute leukemias
Renate Kirschner1, Michaela Heide1, Peter Rhein1, Leonid Karawajew1, Matthias Nees2, Stephen Breit2, Andreas Kulozik2, Christian Hagemeier1, Wolf-Dieter Ludwig1, Rainer Spang3, Karl Seeger1
1 Charité, Humboldt-Universität Berlin, 2 Universitäts-Kinderklinik Heidelberg, 3 Max-Planck-Institut für molekulare Genetik Berlin,
Initial ALL(ALL-BFM trial)
Relapsed ALL(ALL-REZ BFM trial)
Retrospective Study:
Clinical Outcome Event-free Survival ( 3 years)
1. Relapse Event-free Survival ( 3 years)
2. Relapse Non-Response
Classification
Prospective Study:
Therapy ResponsePrednisone Response1
Minimal Residual Disease (MRD)2
Minimal Residual Disease (MRD)3
Non-Response
Good Poor PositiveNegative PositiveNegative
1 Dördelmann et al. 1999. Blood 94: 1209-1217; 2 van Dongen et al. 1989. Lancet 352: 1731-17383 Eckert et al. 2001. Lancet 358: 1239-1241
Leukemic Cell Sample
1. Pre-enrichment by magnetic cell sorting (MACS™, Miltenyi Biotec)
2. Further isolation by flow sorting(FACS Vantage™, Becton Dickinson)
RNA-Extraction
Linear amplification of cRNAby in vitro transcription
Real time PCR(Candidate Genes)
Gene expression profiling
Isolation of Minor Subpopulations from Heterogeneous Leukemic Samples
Optimising Gene Expression Profiling
• Evaluation and cross-validation of generated data sets with published ALL expression profiles
• RNA Preparation
In order to perform retrospective studies, we isolated RNA from cryopreserved mononuclear cells
(magenta). In a significant number of samples loss of sufficient RNA quality and quantity was observed.
RNA quality was also evaluated on a Bioanalyzer™ and via hybridisation of Affymetrix Test3Arrays™
showing a high degree of consistency. For prospective studies we therefore routinely prepare RNA directly
from incoming bone marrow biopsies with an optimized yet straight forward protocol (light blue). This
should also minimize changes of expression profiles due to cryopreservation. Retrospective studies can only
be performed on a limited number of samples (<25%).
Bone marrow biopsiessent from clinical centers
Lab of the study group:
Isolation of mononuclear cells
RNA Preparation
0-2 days
RNA Preparation
Cryopreservation
18 S
28 S
18 S
28 S
Childhood acute lymphoblastic leukemia (ALL) occurs with an incidence of approximately 600 patients per year in Germany. In general, up to
75% of children can be cured permanently by chemotherapy. ALL relapses (approximately 100 cases per year) are more resistant to treatment with
a cure rate of less than 50%. Therefore, novel approaches in terms of diagnosis and therapy are particularly needful for this group. In order to
identify novel prognostic factors and to unravel molecular mechanisms underlying clinical outcome, we aim to generate gene expression profiles of
initial and relapsed ALL of the Berlin-Frankfurt Münster (ALL-BFM and ALL-REZ BFM) study group by Affymetrix DNA microarray
technology.
In the second part of the project, we focus on distinct, clinically relevant
subpopulations from initially heterogeneous leukemic cell samples. We are
especially interested on minor subpopulations of immature, progenitor-like
leukemic cells as well as on residual leukemic cell populations which have
escaped initial treatment and become more resistant to therapy. In order to
approach this issue experimentally, procedures for identification and
purification of rare leukemic blast cells based on flow cytometric analysis and
flow sorting are under development.
Bone marrow samples for gene
expression profiling are selected from
patients who have been treated
according to the protocols of the
ALL-BFM and ALL-REZ BFM study
groups for intial and relapsed acute
lymphoblastic leukemia, respectively.
For a retrospective study patients are
classified by clinical outcome,
whereas for a prognostic study proven
risk factors as for example ‘minimal
residual disease’ - MRD will be used
to divide patients into subgroups.
MRD sensitively measures the
amount of leukemic cells that are still
present at certain time points during
therapy.
Randomly selected, high quality RNA
cRNA
U95Av2 GeneChip™
U133A GeneChip™
norm
aizi
ng
prof
iles.
Published data sets*
eval
uatio
n
Own data sets
facilitates and improves
Databanks were created containing published genes found to be deregulated in large scale ALL profiling
studies based on Affymetrix U95Av2 GeneChips™ (eg *Yeoh et al. 2002. Cancer Cell 1: 133-143).
Ongoing co-hybridisation of 5 to 10 Probes to U95Av2 and U133A GeneChips™ will allow normalization
of expression profiles for comparing data sets created with “old” and “new” Affymetrix GeneChips.
Databanks and bioinformatic filtering tools can then be used to identify and select against unwanted
signatures in smaller test populations that would otherwise escape recognition. This part therefore aims at
both, utilizing and cross-validating existing data from different laboratories.