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Early Relapse in Childhood Acute Lymphoblastic LeukemiaCollaborators: R. Kirschner-schwabe, G. Henze, W.-D. Ludwig, Ch. Hagemeier, K. Seeger (Charité Medical Center ContextIn childhood acute lymphoblastic leukemia (ALL), approximately 25% of patients suffer from relapse. In recurrent disease, despite intensified therapy, overall cure rates of 40% remain unsatisfactory and survival rates are particularly poor in certain subgroups. The probability of long-term survival after relapse is predicted from well-established prognostic factors, i. e. time and site of relapse, immunophenotype and minimal residual disease. However, the underlying biological determinants of these prognostic factors remain poorly understood. Experimentals and analysisAiming at identifying molecular pathways associated with these clinically well defined prognostic factors we performed gene expression profiling on 60 prospectively collected samples of first relapse patients enrolled on the relapse trial ALL-REZ BFM 2002 of the Berlin-Frankfurt-Münster study group. With respect to the above mentioned clinical factors, we performed differential gene expression analysis, in order to characterize high and low risk patients on a molecular level. In addition, we measured the fraction of proliferating cells by cell sorting and learnt a mathematical model to predict this fraction from gene expression patterns. ResultsWe found that patients with very early relapse of ALL are characterized by a distinctive gene expression pattern. When comparing very early relapsed ALL to late relapses, we discovered 83 differential genes, the vast majority of which are up-regulated and many were late cell cycle genes with a function in mitosis. In addition, samples from patients with very early relapse showed a significant increase in the percentage of S and G/2M phase cells.
We have actually modelled the fraction of genes in S- and G/2M-phase based on the gene expression profiles and evaluated the model on a held out test set of samples. Illustration of regression model predictions vs. measured values for S- and G/2M-cells fraction.Publications
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