Stem Cell Commons

Promoting Discovery and Reproducibility in Stem Cell Research

User Top Menu

Search experiments

Title: 
Acute myeloid leukemia samples of samples =< 60yrs on HG-U133 plus 2
Measurement Type: 
Transcription Profiling (Microarray)
Design Type: 
Case Control Design
Summary: 
The pretreatment karyotype of leukemic blasts is currently the key determinant in therapy decision-making in acute myeloid leukemia (AML). However, approximately fifty percent of AML patients, often carrying a normal karyotype, are currently unclassifiable based these established methods. Gene expression profiling has proven to be valuable for risk stratification of AML. The gene expression profiles of AML samples of two independent cohorts (n=247 and n=214) were determined using Affymetrix U133Plus2.0 GeneChips: all Samples below 4000 are in the training cohort; all Samples higher than 4000 are in the validation cohort. Data analyses were carried out to discover and predict prognostically relevant subtypes in AML (<60 years) based on their gene expression signatures. Statistical analyses were performed to determine the prognostic significance of cases of AML with specific molecular signatures. Unsupervised cluster analyses of the gene expression signatures of both independent cohorts of AML patients confirmed that chromosomal lesions and mutations, often resulting in aberrant transcription factors, induce discriminatory patterns of gene expression. In contrast, however, mutations in signalling molecules do not establish strong molecular signatures. Consequently, prognostically important subtypes, which express mutated transcription factors were predicted with high accuracy using minimal sets of genes. We identified several novel clusters, some consisting of patients with normal karyotypes. Gene expression profiling allows classification of AML subtypes characterized by the expression of abnormal transcription factors, however, prediction of clinically relevant mutations affecting signalling molecules is impossible and thus still requires addition molecular methods.
Contact(s): 

Group

Citations: 
Prediction of molecular subtypes in acute myeloid leukemia based on gene expression profiling.
Verhaak RGW, Wouters BJ, Erpelinck CAJ, Abbas S, H Beverloo B, Lugthart S, Löwenberg B, Delwel R, Valk PJM
Haematologica. 2009 Jan; 94(1):131-4. PMID: 18838472. Abstract
Download: 
Files not yet available.