Abstract
In a recent interesting article, analysis of gene expression between phenotypically defined acute myeloid leukemia (AML) leukemia stem cells (LSCs) and more mature leukemia progenitor cells is used to generate a differentially expressed gene signature for LSCs. Through clever bioinformatic weighting analysis, the authors describe a method to convert this signature into a single score for any given sample and then test the prognostic utility of this 'LSC score' in publicly available gene expression profiles from bulk AML samples. They demonstrate that a high LSC score is associated with poor prognosis in AML patients and further demonstrate that the score is independent of known prognostic factors, including age, karyotype and mutation of the FLT3 or NPM1 genes. These findings are important and directly relate transcriptional dysregulation in AML LSCs with the outcome in patient samples, thus reinforcing the belief that these cellular populations are crucial for the initial propagation and subsequent relapse and resistance of leukemia.