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Classification of AML by DNA-Oligonucleotide Microarrays 239<br />
and require skilled expert-level personnel in centralized reference laboratories.<br />
Based on microarray methods, substantial steps forward may be made in the<br />
direction of both optimizing the diagnostic capabilities and reducing financial<br />
reserves that have to be invested. A significant number of today’s diagnostic<br />
approaches can be reproduced by gene expression profiling already. However,<br />
further large trials are needed to assert the validity of this technology.<br />
References<br />
1. Dugas, M., Schoch, C., Schnittger, S., et al. (2001) A comprehensive leukemia<br />
database: integration of cytogenetics, molecular genetics and microarray data with<br />
clinical information, cytomorphology and immunophenotyping. <strong>Leukemia</strong> 15,<br />
1805–1810.<br />
2. Gubler, U. and Hoffman, B. J. (1983) A simple and very efficient method for<br />
generating cDNA libraries. Gene 25, 263–269.<br />
3. Hoffmann, E. P. (2004) Expression profiling—best practices for data generation<br />
and interpretation in clinical trials. Nat. Rev. Genet. 5, 229–237.<br />
4. Lipshutz, R. J., Fodor, S. P., Gingeras, T. R., and Lockhart, D. J. (1999) High<br />
density synthetic oligonucleotide arrays. Nat. Genet. 21, 20–24.<br />
5. Lockhart, D. J., Dong, H., Byrne, M. C., et al. (1996) Expression monitoring by<br />
hybridization to high-density oligonucleotide arrays. Nat. Biotechnol. 14, 1675–<br />
1680.<br />
6. Mei, R., Hubbell, E., Bekiranov, S., et al. (2003) Probe selection for high-density<br />
oligonucleotide arrays. Proc. Natl. Acad. Sci. USA 100, 11,237–11,242.<br />
7. Sambrook, J., Fritsch, E. F., and Maniatis, T. (1989) Molecular Cloning: A Laboratory<br />
Manual (2nd edition). Cold Spring Harbor Laboratory: Cold Spring Harbor,<br />
NY.<br />
8. Slonim, D. K. (2002) From patterns to pathways: gene expression data analysis<br />
comes of age. Nat. Genet. 32 Suppl., 502–508.<br />
9. Golub, T. R., Slonim, D. K., Tamayo, P., et al. (1999) Molecular classification of<br />
cancer: class discovery and class prediction by gene expression monitoring. Science<br />
286, 531–537.<br />
10. Yeoh, E. J., Ross, M. E., Shurtleff, S. A., et al. (2002) Classification, subtype<br />
discovery, and prediction of outcome in pediatric acute lymphoblastic leukemia<br />
by gene expression profiling. Cancer Cell 1, 133–143.<br />
11. Quackenbush, J. (2002) Microarray data normalization and transformation. Nat.<br />
Genet. 32 Suppl, 496–501.<br />
12. Tusher, V. G., Tibshirani, R., and Chu, G. (2001) Significance analysis of<br />
microarrays applied to the ionizing radiation response. Proc. Natl. Acad. Sci. USA<br />
98, 5116–5121.<br />
13. Storey, J. D. and Tibshirani, R. (2003) Statistical significance for genomewide<br />
studies. Proc. Natl. Acad. Sci. USA 100, 9440–9445.<br />
14. Eisen, M. B., Spellman, P. T., Brown, P. O., and Botstein, D. (1998) Cluster analysis<br />
and display of genome-wide expression patterns. Proc. Natl. Acad. Sci. USA<br />
95, 14,863–14,868.
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