These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


PUBMED FOR HANDHELDS

Search MEDLINE/PubMed


  • Title: Gene expression profiling in acute myeloid leukaemia (AML).
    Author: Bacher U, Kohlmann A, Haferlach C, Haferlach T.
    Journal: Best Pract Res Clin Haematol; 2009 Jun; 22(2):169-80. PubMed ID: 19698926.
    Abstract:
    In view of the genetic heterogeneity of acute myeloid leukaemia (AML), gene expression profiling (GEP) with the possibility of investigating the expression of tens of thousands of genes in parallel represents a promising approach to facilitate and improve the diagnostic process in this complex disorder. In the last decade, following the introduction of this methodology in leukaemia research, various studies have demonstrated that classification of the majority of known genetic subclasses in AML can be performed with high accuracy by GEP. Further, GEP allowed for detecting new biologically and prognostically relevant subclasses within the defined subgroups, mainly in the normal karyotype AML. These new classifiers cross the borders of traditionally defined prognostic parameters, and some of these gene expression signatures were independently validated by different study groups. The development of treatment-specific sensitivity assays being able to predict the individual patient's response to targeted therapy is another interesting perspective. With respect to molecular mutations in genes such as FLT3 or NPM1, future studies must outline the definite position of GEP. International multicentre studies such as the MILE study (Microarray Innovations in LEukemia) pave the way to a standardised workflow of GEP in routine diagnostics in AML.
    [Abstract] [Full Text] [Related] [New Search]