Summary
Accurate diagnosis and classification of leukemias are the bases for the appropriate management of patients. The diagnostic accuracy and efficiency of present methods may be improved by the use of microarrays. The followin g chapter gives an overview of the method of gene expression profiling of leukemia samples, its laboratory procedure, and how to approach the analysis of the data.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsSpringer Nature is developing a new tool to find and evaluate Protocols. Learn more
References
Dugas M., Schoch C., Schnittger S., et al. (2001) A comprehensive leukemia database: integration of cytogenetics, molecular genetics and microarray data with clinical information, cytomorphology and immunophenotyping. Leukemia 15, 1805–1810.
Gubler U. and Hoffman B. J. (1983) A simple and very efficient method for generating cDNA libraries. Gene 25, 263–269.
Hoffmann E. P. (2004) Expression profiling-best practices for data generation and interpretation in clinical trials. Nat. Rev. Genet. 5, 229–237.
Lipshutz R. J., Fodor S. P., Gingeras T. R., and Lockhart D. J. (1999) High density synthetic oligonucleotide arrays. Nat. Genet. 21, 20–24.
Lockhart D. J., Dong H., Byrne M. C., et al. (1996) Expression monitoring by hybridization to high-density oligonucleotide arrays. Nat. Biotechnol. 14, 1675–1680.
Mei R., Hubbell E., Bekiranov S., et al. (2003) Probe selection for high-density oligonucleotide arrays. Proc. Natl. Acad. Sci. USA 100, 11,237–11,242.
Sambrook J., Fritsch E. F., and Maniatis T. (1989) Molecular Cloning: A Laboratory Manual (2nd edition). Cold Spring Harbor Laboratory: Cold Spring Harbor, NY.
Slonim D. K. (2002) From patterns to pathways: gene expression data analysis comes of age. Nat. Genet. 32 Suppl., 502–508.
Golub T. R., Slonim D. K., Tamayo P., et al. (1999) Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science 286, 531–537.
Yeoh E. J., Ross M. E., Shurtleff S. A., et al. (2002) Classification, subtype discovery, and prediction of outcome in pediatric acute lymphoblastic leukemia by gene expression profiling. Cancer Cell 1, 133–143.
Quackenbush J. (2002) Microarray data normalization and transformation. Nat. Genet. 32 Suppl, 496–501.
Tusher V. G., Tibshirani R., and Chu G. (2001) Significance analysis of microarrays applied to the ionizing radiation response. Proc. Natl. Acad. Sci. USA 98, 5116–5121.
Storey J. D. and Tibshirani R. (2003) Statistical significance for genomewide studies. Proc. Natl. Acad. Sci. USA 100, 9440–9445.
Eisen M. B., Spellman P. T., Brown P. O., and Botstein D. (1998) Cluster analysis and display of genome-wide expression patterns. Proc. Natl. Acad. Sci. USA 95, 14,863–14,868.
Jolliffe I. T. (2002) Principal Component Analysis. Springer: New York.
Guyon I., Weston J., Barnhill S., and Vapnik V. (2002) Gene selection for cancer classification using support vector machines. Machine Learning 46, 389–422.
Schölkopf B. and Smola A. J. (2002) Learning with Kernels. MIT Press: Cambridge, MA.
Vapnik V. (1998) Statistical Learning Theory. Wiley: New York.
Kohlmann A., Schoch C., Schnittger S., et al. (2004) Pediatric acute lymphoblastic leukemia (ALL) gene expression signatures classify an independent cohort of adult ALL patients. Leukemia 18, 63–71.
Chang C. C. and Lin C. J. (2001) LIBSVM: a library for support vector machines. Software available at http://www.csie.ntu.edu.tw/~cjlin/libsvm/
Liu G., Loraine A. E., Shigeta R., et al. (2003) NetAffx: Affymetrix probesets and annotations. Nucleic Acids Res. 31, 82–86.
Dudoit S., Gentleman R. C., and Quackenbush J. (2003) Open source software for the analysis of microarray data. Biotechniques March Suppl., 45–51.
Warrington J. A., Nair A., Mahadevappa M., and Tsyganskaya M. (2000) Comparison of human adult and fetal expression and identification of 535 housekeeping/ maintenance genes. Physiol. Genomics 2, 143–147.
Kohlmann A., Schoch C., Schnittger S., et al. (2003) Molecular characterization of acute leukemias by use of microarray technology. Genes Chromosomes Cancer 37, 396–405.
Ross M. E., Zhou X., Song G., Shurtleff S. A., Girtman K., Williams W. K., et al. (2003) Classification of pediatric acute lymphoblastic leukemia by gene expression profiling. Blood 102, 2951–2959.
Ross M. E., Mahfouz R., Onciu M., et al. (2004) Gene expression profiling of pediatric acute myelogenous leukemia. Blood 104, 3679–3687.
Schoch C., Kohlmann A., Schnittger S., et al. (2002) Acute myeloid leukemias with reciprocal rearrangements can be distinguished by specific gene expression profiles. Proc. Natl. Acad. Sci. USA 99, 10,008–10,013.
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Humana Press Inc.
About this protocol
Cite this protocol
Kohlmann, A., Kern, W., Hiddemann, W., Haferlach, T. (2006). Classification of AML by DNA-Oligonucleotide Microarrays. In: Iland, H., Hertzberg, M., Marlton, P. (eds) Myeloid Leukemia. Methods In Molecular Medicine™, vol 125. Humana Press. https://doi.org/10.1385/1-59745-017-0:213
Download citation
DOI: https://doi.org/10.1385/1-59745-017-0:213
Publisher Name: Humana Press
Print ISBN: 978-1-58829-485-2
Online ISBN: 978-1-59745-017-1
eBook Packages: Springer Protocols