Abstract
Today, the classification systems for myelodysplastic syndromes (MDS) and acute myeloid leukemia (AML) already incorporate cytogenetic and molecular genetic aberrations in an attempt to better reflect disease biology. However, in many MDS/AML patients no genetic aberrations have been identified yet, and even within some cytogenetically well-defined subclasses there is considerable clinical heterogeneity. Recent advances in genomics technologies such as gene expression profiling (GEP) provide powerful tools to further characterize myeloid malignancies at the molecular level, with the goal to refine the MDS/AML classification system, incorporating as yet unknown molecular genetic and epigenetic pathomechanisms, which are likely reflected by aberrant gene expression patterns. In this study, we provide a comprehensive review on how GEP has contributed to a refined molecular taxonomy of MDS and AML with regard to diagnosis, prediction of clinical outcome, discovery of novel subclasses and identification of novel therapeutic targets and novel drugs. As many challenges remain ahead, we discuss the pitfalls of this technology and its potential including future integrative studies with other genomics technologies, which will continue to improve our understanding of malignant transformation in myeloid malignancies and thereby contribute to individualized risk-adapted treatment strategies for MDS and AML patients.Leukemia advance online publication, 29 March 2011; doi:10.1038/leu.2011.48.
Original language | English |
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Pages (from-to) | 909-920 |
Journal | Leukemia |
Volume | 25 |
Issue number | 6 |
DOIs | |
Publication status | Published - 2011 |
Bibliographical note
The information about affiliations in this record was updated in December 2015.The record was previously connected to the following departments: Hematology/Transplantation (013022014), Stem Cell Center (013022011)
Subject classification (UKÄ)
- Cancer and Oncology
Free keywords
- gene expression profiling
- acute myeloid leukemia
- myelodysplastic syndrome
- microarray
- connectivity MAP
- drug discovery