Abstract
The current systems of risk grouping in pediatric acute lymphoblastic leukemia (ALL) fail to predict therapeutic success in 10–35% of patients. To identify better predictive markers of clinical behavior in ALL, we have developed an integrated approach for gene expression profiling that couples suppression subtractive hybridization, concatenated cDNA sequencing, and reverse transcriptase real-time quantitative PCR. Using this approach, a total of 600 differentially expressed genes were identified between t(4;11) ALL and pre-B ALL with no determinant chromosomal translocation. The expression of 67 genes was analyzed in different cytogenetic ALL subgroups and B lymphocytes isolated from healthy donors. Three genes, BACH1, TP53BPL, and H2B/S, were consistently expressed as a significant cluster associated with the low-risk ALL subgroups. A total of 42 genes were differentially expressed in ALL vs normal B lymphocytes, with no specific association with any particular ALL subgroups. The remaining 22 genes were part of a specific expression profile associated with the hyperdiploid, t(12;21), or t(4;11) subgroups. Using an unsupervised hierarchical cluster analysis, the discriminating power of these specific expression profiles allowed the clustering of patients according to their subgroups. These genes could help to understand the difference in treatment response and become therapeutical targets to improve ALL clinical outcomes.
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Acknowledgements
We thank Dr C Philip Steuber and the TCCC Leukemia team for their collaboration, and Mary-Ann A Mastangelo for the technical support and advice with the RT-RQ-PCR technique. We acknowledge the contributions of the BCM-HGSC production team headed by Donna Muzny, the library team headed by Erica Sodergren, and the sequence instrumentation team headed by Graham Scott. We also thank Keelan Hamilton for providing the oligonucleotides used for primer walking and acknowledge the contribution of the cDNA group. We are also grateful to several members of the bio-informatics department including David Wheeler, Kim Worley, David Stefan, and Paul Havlak for their contributions toward this study.
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Qiu, J., Gunaratne, P., Peterson, L. et al. Novel potential ALL low-risk markers revealed by gene expression profiling with new high-throughput SSH–CCS–PCR. Leukemia 17, 1891–1900 (2003). https://doi.org/10.1038/sj.leu.2403073
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DOI: https://doi.org/10.1038/sj.leu.2403073
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