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Blood, 1 March 2006, Vol. 107, No. 5, pp. 2061-2069.
Prepublished online as a Blood First Edition Paper on November 17, 2005; DOI 10.1182/blood-2005-07-2853.
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Submitted July 19, 2005
Accepted October 19, 2005
Identification of glucocorticoid-response genes in children with acute lymphoblastic leukemia
Stefan Schmidt, Johannes Rainer, Stefan Riml, Christian Ploner, Simone Jesacher, Clemens Achmuller, Elisabeth Presul, Sergej Skvortsov, Roman Crazzolara, Michael Fiegl, Taneli Raivio, Olli A Janne, Stephan Geley, Bernhard Meister, and Reinhard Kofler*
Tyrolean Cancer Research Institute, Innsbruck, Austria
Division of Molecular Pathophysiology, Biocenter, Innsbruck, Austria
Tyrolean Cancer Research Institute, Innsbruck, Austria; Division of Molecular Pathophysiology, Biocenter, Innsbruck, Austria
Tyrolean Cancer Research Institute, Innsbruck, Austria; Department of Pediatrics, Innsbruck Medical University, Innsbruck, Austria
Department of Haematology and Oncology, Innsbruck Medical University, Innsbruck, Austria
Biomedicum Helsinki, Institute of Biomedicine, University of Helsinki, Helsinki, Finland
* Corresponding author; email: Reinhard.Kofler{at}uibk.ac.at.
The ability of glucocorticoids (GC) to kill lymphoid cells led to their inclusion in essentially all chemotherapy protocols for lymphoid malignancies, particularly childhood acute lymphoblastic leukemia (ALL). GC mediate apoptosis via their cognate receptor and subsequent alterations in gene expression. Previous investigations, including expression profiling studies with sub-genome microarrays in model systems, have led to a number of attractive, but conflicting, hypotheses which have never been tested in a clinical setting. Here, we present a comparative whole genome expression profiling approach using lymphoblasts (purified at three time points) from 13 GC-sensitive children under therapy for ALL. For comparisons, expression profiles were generated from an adult ALL, peripheral blood lymphocytes from GC-exposed healthy donors, GC-sensitive and resistant ALL cell lines and mouse thymocytes treated with GC in vivo and in vitro. This generated an essentially complete list of GC-regulated candidate genes in clinical settings and experimental systems, allowing immediate analysis of any gene for its potential significance to GC-induced apoptosis. Our analysis argued against most of the model-based hypotheses and instead identified a small number of novel candidate genes, including PFKFB2, a key regulator of glucose metabolism, ZBTB16, a putative transcription factor and SNF1LK, a protein kinase implicated in cell cycle regulation.
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