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Briefings in Functional Genomics Advance Access published online on May 27, 2009
Briefings in Functional Genomics, doi:10.1093/bfgp/elp011
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© The Author 2009. Published by Oxford University Press. For permissions, please email: journals.permissions@oxfordjournals.org

Perspectives of gene expression profiling for diagnosis and therapy in haematological malignancies

Ulrike Bacher, Alexander Kohlmann and Torsten Haferlach

Corresponding author. Torsten Haferlach, MLL Munich Leukemia Laboratory, Max-Lebsche-Platz 31, D-81377 Munich, Germany. Tel: +49 89 99017 100; Fax: +49 89 99017 109; E-mail: torsten.haferlach{at}mll-online.com

Considering the heterogeneity of leukaemias and the widening spectrum of therapeutic strategies, novel diagnostic methods are urgently needed for haematological malignancies. For a decade, gene expression profiling (GEP) has been applied in leukaemia research. Thus, various studies demonstrated worldwide that the majority of genetically defined leukaemia subtypes are accurately predictable by GEP, for example, with respect to reciprocal rearrangements in acute myeloid leukaemia (AML). Moreover, novel prognostically relevant gene classifiers were developed as, for example, in normal karyotype AML. Considering the lymphatic malignancies, GEP studies defined novel clinically relevant subtypes in diffuse large B cell lymphoma (DLBCL), and improved the discrimination of Burkitt lymphoma and DLBCL cases, overcoming considerable overlaps of these entities that exist from morphological and genetic perspectives. Treatment-specific sensitivity assays are being developed for targeted drugs such as farnesyl transferase inhibitors in AML or imatinib in BCR-ABL1 positive acute lymphoblastic leukaemia (ALL). Irrespectively of these proceedings, an introduction of the microarray technology in haematological practice requires diagnostic algorithms and strategies for interaction with currently established diagnostic techniques. Large multicentre studies such as the MILE Study (Microarray Innovations in LEukemia) aim at translating this methodology into clinical routine workflows and to catalyze this process.

Keywords: gene expression profiling (GEP), acute myeloid leukaemia (AML), acute lymphoblastic leukaemia (ALL), lymphatic malignancies, MILE study


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