PubMed · 2005 · 37 citations · 28 references
Life SciencesMolecular BiologyOncologyGene ExpressionGene Expression AnalysisGenomicsCancer GenomicsCancer TranscriptomicsExpression Signature DiscoveryGene Expression ProfilingPediatric LeukemiasTranscriptomic ProfilingAcute Lymphoblastic Leukemia BiologyB-cell LeukemiaCancer Subtype DiscoveryCdna Library ConstructionHematologic NeoplasiaLeukemia ClassificationMicroarray AnalysisMicroarray-based Transcriptomics
BACKGROUND AND OBJECTIVES: Microarray gene expression profiling has been widely applied to characterize hematologic malignancies, has attributed a molecular signature to leukemia subclasses and has allowed new subclasses to be distinguished. We set out to use microarray technology to identify novel genes relevant for leukemogenesis. To this end we used a unique leukemia-enriched cDNA microarray platform. DESIGN AND METHODS: The systematic sequencing of cDNA libraries of normal and leukemic bone marrow allowed us to increase the number of genes to yield a new release of a previously generated cDNA microarray. Using this platform we analyzed the expression profiles of 4,670 genes in bone marrow samples from 18 pediatric patients with acute lymphoblastic leukemia (ALL). RESULTS: Expression profiling consistently distinguished the leukemia patients into three groups, those with T-ALL, B-ALL and B-ALL with MLL/AF4 rearrangement, in agreement with the clinical classification. Our platform identified 30 genes that best discriminate these three subtypes. Using mini-array technology these 30 genes were validated in another cohort of 17 patients. In particular we identified two novel genes not previously reported: endomucin (EMCN) and ubiquitin specific protease 33 (USP33) that appear to be over-expressed in B-ALL relative to their expression in T-ALL. INTERPRETATION AND CONCLUSIONS: Microarray technology not only allows the distinction between disease subclasses but also offers a chance to identify new genes involved in leukemogenesis. Our approach of using a unique platform has proven to be fruitful in identifying new genes and we suggest exploration of other malignancies using this approach.
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