1. Identification and functional characterisation of molecular risk factors in acute leukemias Renate Kirschner 1, Michaela Heide 1, Peter Rhein 1, Leonid Karawajew 1, Matthias Nees 2, Stephen Breit 2, Andreas Kulozik 2, Christian Hagemeier 1, Wolf-Dieter Ludwig 1, Rainer Spang 3, Karl Seeger 1 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. RelapseNon-Response Classification Prospective Study: Therapy Response Prednisone Response 1 Minimal Residual Disease (MRD) 2 Minimal Residual Disease (MRD) 3 Non-Response Good PoorPositiveNegative PositiveNegative 1 Dördelmann et al. 1999. Blood 94: 1209-1217; 2 van Dongen et al. 1989. Lancet 352: 1731-1738 3 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 cRNA by 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 biopsies sent 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™ normaizing profiles. Published data sets* evaluation 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.