title: Integrative meta-analysis of differential gene expression in acute myeloid leukemia.
abstract: BACKGROUND
  Acute myeloid leukemia (AML) is a heterogeneous disease with an overall poor prognosis. Gene expression profiling studies of patients with AML has provided key insights into disease pathogenesis while exposing potential diagnostic and prognostic markers and therapeutic targets. A systematic comparison of the large body of gene expression profiling studies in AML has the potential to test the extensibility of conclusions based on single studies and provide further insights into AML.
  
  
  RESULTS
  In this study, we systematically compared 25 published reports of gene expression profiling in AML. There were a total of 4,918 reported genes of which one third were reported in more than one study. We found that only a minority of reported prognostically-associated genes (9.6%) were replicated in at least one other study. In a combined analysis, we comprehensively identified both gene sets and functional gene categories and pathways that exhibited significant differential regulation in distinct prognostic categories, including many previously unreported associations.
  
  
  CONCLUSIONS
  We developed a novel approach for granular, cross-study analysis of gene-by-gene data and their relationships with established prognostic features and patient outcome. We identified many robust novel prognostic molecular features in AML that were undetected in prior studies, and which provide insights into AML pathogenesis with potential diagnostic, prognostic, and therapeutic implications. Our database and integrative analysis are available online (http://gat.stamlab.org).
authors.affiliation: Department of Hematology, University of Washington, Seattle, Washington, United States of America.
authors.forename: Brady G
authors.initials: BG
authors.lastname: Miller
authors.forename: John A
authors.initials: JA
authors.lastname: Stamatoyannopoulos
mesh_terms: D002874:Chromosome Mapping; D016000:Cluster Analysis; D003582:Cytogenetics; D030541:Databases, Genetic; D020869:Gene Expression Profiling; D015973:Gene Expression Regulation, Leukemic; D006801:Humans; D015470:Leukemia, Myeloid, Acute / Q000235:genetics* / Q000378:metabolism*; D011379:Prognosis