Prognostically Useful Gene-Expression Profiles in Acute Myeloid Leukemia

Valk, Peter J.M.; Verhaak, Roel G.W.; Beijen, M. Antoinette; Erpelinck, Claudia; Doorn-Khosrovani, Sahar van Waalwijk van Barjesteh; Boer, Judith M.; Beverloo, H. Berna; Moorhouse, Michael; Spek, Peter J. van der; Löwenberg, Bob; Delwel, Ruud

doi:10.1056/nejmoa040465

Cited by 1,244 publications

(1,306 citation statements)

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“…Gene expression profiling studies of various cancers have discovered consistent gene expression patterns associated with a histological or clinical phenotype and discovering subtypes of cancers previously unidentified with conventional technologies (Alizadeh et al, 2000;van de Vijver et al, 2002;Bullinger et al, 2004;Dave et al, 2004;Lapointe et al, 2004;Valk et al, 2004;Lee et al, 2004a;Roepman et al, 2005). This approach promises to provide diagnostic and prognostic markers that can be clinically used in the near future (Lossos et al, 2004).…”

Section: Integrative Functional Genomicsmentioning

confidence: 99%

“…In addition to large-scale DNA sequencing projects that have accomplished tremendous success in providing molecular architecture of genes and genomes, high-throughput gene expression profiling projects will continue to be the primary driver behind the comprehensive molecular catalogs of human disease. This new technology has been successfully used to predict the clinical outcome and survival as well as to classify different types of cancer (Alizadeh et al, 2000;Bittner et al, 2000;Beer et al, 2002;Lee and Thorgeirsson, 2002;van't Veer et al, 2002;Valk et al, 2004;Lee et al, 2004a;Roepman et al, 2005). This review summarizes recent studies on gene expression profiling of HCC aimed at better understanding the molecular pathogenesis of the disease, the promising clinical applications of the gene expression data as well as addressing the potential future use of this new technology.…”

Section: Introductionmentioning

confidence: 99%

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Comparative and integrative functional genomics of HCC

2006

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Global gene expression profiling of hepatocellular carcinoma (HCC) is a promising new technology that has already refined the diagnosis and prognostic predictions of HCC patients. This has been accomplished by identifying genes whose expression pattern is associated with clinicopathological features of HCC tumors. Molecular characterization of HCC from gene expression profiling studies will undoubtedly improve the prediction of treatment responses, selection of treatments for specific molecular subtypes of HCC and ultimately the clinical outcome of HCC patients. The research focus is now shifting toward the identification of genetic determinants that are components of the specific regulatory pathways altered in cancers, and that may constitute novel therapeutic targets. Here we review the recent advances in gene expression profiling of HCC and discuss the future strategies for analysing large and complicated data sets from microarray studies and how to integrate these with diverse genomic data.

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Section: Integrative Functional Genomicsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Comparative and integrative functional genomics of HCC

2006

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“…For microarray analysis, a total of 285 AML patients were collected at the Erasmus University of Rotterdam, The Netherlands, as previously reported (AML cohort 2). 21 This cohort is also characterized with respect to mutations in NRAS, KRAS, NPM1, CEBPA, the FLT3 tyrosine kinase domain (FLT3-TKD) as well as to FLT3 internal tandem duplications (FLT3-ITD).…”

Section: Introductionmentioning

confidence: 99%

Frequent loss of RAF kinase inhibitor protein expression in acute myeloid leukemia

et al. 2012

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RAF kinase inhibitor protein (RKIP) is a negative regulator of the RAS-mitogen-activated protein kinase/extracellular signalregulated kinase signaling cascade. We investigated its role in acute myeloid leukemia (AML), an aggressive malignancy arising from hematopoietic stem and progenitor cells (HSPCs). Western blot analysis revealed loss of RKIP expression in 19/103 (18%) primary AML samples and 4/17 (24%) AML cell lines but not in 10 CD34 þ HSPC specimens. In in-vitro experiments with myeloid cell lines, RKIP overexpression inhibited cellular proliferation and colony formation in soft agar. Analysis of two cohorts with 103 and 285 AML patients, respectively, established a correlation of decreased RKIP expression with monocytic phenotypes. RKIP loss was associated with RAS mutations and in transformation assays, RKIP decreased the oncogenic potential of mutant RAS. Loss of RKIP further related to a significantly longer relapse-free survival and overall survival in uni-and multivariate analyses. Our data show that RKIP is frequently lost in AML and correlates with monocytic phenotypes and mutations in RAS. RKIP inhibits proliferation and transformation of myeloid cells and decreases transformation induced by mutant RAS. Finally, loss of RKIP seems to be a favorable prognostic parameter in patients with AML.

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“…However, these findings must be interpreted with caution and in full view of critical differences between normal and diseased cellular biology. [1][2][3] Several fundamental issues (outlined below) must be addressed to effectively design experiments and to appropriately interpret results.…”

Section: Introductionmentioning

confidence: 99%

Gene expression changes in normal haematopoietic cells

Lionberger¹,

Stirewalt²

2009

Best Practice & Research Clinical Haematology

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The complexity of the healthy hematopoietic system is immense, and as such, one must understand the biology driving normal hematopoietic expression profiles when designing experiments and interpreting expression data that involves normal cells. This chapter seeks to present an organized approach to the use and interpretation of gene profiling in normal hematopoiesis and broadly illustrates the challenges of selecting appropriate controls for high-throughput expression studies.

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Prognostically Useful Gene-Expression Profiles in Acute Myeloid Leukemia

Abstract: Gene-expression profiling allows a comprehensive classification of AML that includes previously identified genetically defined subgroups and a novel cluster with an adverse prognosis.

Cited by 1,244 publications

References 25 publications

Comparative and integrative functional genomics of HCC

Comparative and integrative functional genomics of HCC

Frequent loss of RAF kinase inhibitor protein expression in acute myeloid leukemia

Gene expression changes in normal haematopoietic cells

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