Gene expression profiling as a tool for the diagnosis of acute leukemias

The standard methods to diagnose leukemia are cytomorphology and, in some cases, histology, which both are supplemented by cytochemistry and multiparameter immunophenotyping. Cytogenetics, fluorescence in situ hybridisation (FISH), and polymerase chain reaction (PCR) assays add important information and allow comprehensive diagnosis of well-defined subentities today. In the clinic, better understanding of the course of distinct, biologically defined disease subtypes is the basis for a selection of specific therapeutic approaches. As knowledge on deregulated pathways in leukemia accelerates the development of new therapeutics, a detailed and comprehensive diagnostic tool is required. The microarray technology that quantifies gene expression intensities of thousands of genes in a single analysis has the potential to become essential for the molecular classification of leukemias. Microarrays may be used routinely for diagnostic purposes in the near future. Gene expression profiling should also lead to the detection of new biological and clinically relevant subtypes in leukemia and therefore guide therapeutic decisions.     

Gene expression profiling of pediatric acute myelogenous leukemia

Contemporary treatment of pediatric acute myeloid leukemia (AML) requires the assignment of patients to specific risk groups. To explore whether expression profiling of leukemic blasts could accurately distinguish between the known risk groups of AML, we analyzed 130 pediatric and 20 adult AML diagnostic bone marrow or peripheral blood samples using the Affymetrix U133A microarray. Class discriminating genes were identified for each of the major prognostic subtypes of pediatric AML, including t(15;17)[PML-RARalpha], t(8;21)[AML1-ETO], inv(16) [CBFbeta-MYH11], MLL chimeric fusion genes, and cases classified as FAB-M7. When subsets of these genes were used in supervised learning algorithms, an overall classification accuracy of more than 93% was achieved. Moreover, we were able to use the expression signatures generated from the pediatric samples to accurately classify adult de novo AMLs with the same genetic lesions. The class discriminating genes also provided novel insights into the molecular pathobiology of these leukemias. Finally, using a combined pediatric data set of 130 AMLs and 137 acute lymphoblastic leukemias, we identified an expression signature for cases with MLL chimeric fusion genes irrespective of lineage. Surprisingly, AMLs containing partial tandem duplications of MLL failed to cluster with MLL chimeric fusion gene cases, suggesting a significant difference in their underlying mechanism of transformation.     

Gene expression profiling in rheumatoid arthritis: current concepts and future directions

Over the last years microarray technologies have generated new perspectives for the high-throughput analysis of biological systems. Nowadays, it is possible to monitor thousands of genes in a single experiment. This molecular profiling technology combined with standardised and validated clinical measurements can allow a more precise characterisation of a patient's phenotype, and may lead to the design of therapeutic protocols and procedures better tailored to an individual patient's needs. In this report we provide an overview of expression profiling studies in rheumatoid arthritis (RA). RA is a chronic inflammatory disease in which both genetic and environmental factors are involved. The precise molecular mechanisms underlying RA are not fully understood. A systematic literature search revealed nine array-based expression profiling studies in patients with RA. Findings from these studies were compared with those of linkage and genome-wide association (GWA) studies. Although we observed many differences in study design, analysis and interpretation of results between the different studies, we extracted two sets of genes: (1) those differentially expressed in more than one study, and (2) genes differentially expressed in at least one of the reviewed studies and present in RA linkage or GWA loci. We suggest that both sets of genes include interesting candidate genes for further study in RA.