Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Expression profiles of normal hematopoietic stem and progenitor cells and acute myeloid leukemia sub-populations

ABSTRACT: Acute Myeloid Leukemia AML is a cancer in which the process of normal cell hematopoietic differentiation is disrupted. Evidence exists that AML comprises a hierarchy with leukemic stem cells giving rise to more differentiated, but immature and functionally incompetent populations. The similarity of these AML subpopulations to normal stages of hematopoietic differentiation has not been dissected comprehensively at the transcriptional level. Here we introduce Normal Memory Analysis (NorMA), a data analysis method that extracts from omic data the remnants of the healthy normal-like phenotype. Applying NorMA to gene expression data from AML uncovered a wealth of information in the normal-like component of data: the normal hematopoietic memory of AML tumor cells. We found significant variation within the patient population, and we found strong association of this normal hematopoietic memory with survival. We found that undifferentiated NorMA phenotype has significantly worse survival than differentiated NorMA phenotype, showing that the NorMA classification of tumors captures a biologically meaningful stratification of patients, with highly significant survival association. Patients with NorMA phenotype in the undifferentiated Hematopoietic Stem Cell HSC stage had the worst survival, with median survival time under 6 months. We further found significant survival differences between tumor groups with differentiated NorMA phenotype, depending on their hematopoietic path: AML patients with NorMA phenotype in megakaryocyte-erythroid progenitor MEP stage had significantly better survival than those with NorMA phenotype in granulocyte-macrophage progenitor GMP stage. Thus NorMA produced a stratification of AML cohorts by differentiation stage, with significant outcome differences. It also provided clean molecular signatures for these stages. NorMA can be used in many other contexts, to explore for example the tumor cell of origin, or disease predisposition. Expression profiles of 104 normal and leukemic populations were obtained using Affymetrix microarrays

ORGANISM(S): Homo sapiens

SUBMITTER: Andrew Gentles

PROVIDER: E-GEOD-63270 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

An LSC epigenetic signature is largely mutation independent and implicates the HOXA cluster in AML pathogenesis.

Jung Namyoung N Dai Bo B Gentles Andrew J AJ Majeti Ravindra R Feinberg Andrew P AP

Nature communications 20151007

Acute myeloid leukaemia (AML) is characterized by subpopulations of leukaemia stem cells (LSCs) that are defined by their ability to engraft in immunodeficient mice. Here we show an LSC DNA methylation signature, derived from xenografts and integration with gene expression that is comprised of 71 genes and identifies a key role for the HOXA cluster. Most of the genes are epigenetically regulated independently of underlying mutations, although several are downstream targets of epigenetic modifier ...[more]

PMID: 26444494

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Project description:Acute Myeloid Leukemia AML is a cancer in which the process of normal cell hematopoietic differentiation is disrupted. Evidence exists that AML comprises a hierarchy with leukemic stem cells giving rise to more differentiated, but immature and functionally incompetent populations. The similarity of these AML subpopulations to normal stages of hematopoietic differentiation has not been dissected comprehensively at the transcriptional level. Here we introduce Normal Memory Analysis (NorMA), a data analysis method that extracts from omic data the remnants of the healthy normal-like phenotype. Applying NorMA to gene expression data from AML uncovered a wealth of information in the normal-like component of data: the normal hematopoietic memory of AML tumor cells. We found significant variation within the patient population, and we found strong association of this normal hematopoietic memory with survival. We found that undifferentiated NorMA phenotype has significantly worse survival than differentiated NorMA phenotype, showing that the NorMA classification of tumors captures a biologically meaningful stratification of patients, with highly significant survival association. Patients with NorMA phenotype in the undifferentiated Hematopoietic Stem Cell HSC stage had the worst survival, with median survival time under 6 months. We further found significant survival differences between tumor groups with differentiated NorMA phenotype, depending on their hematopoietic path: AML patients with NorMA phenotype in megakaryocyte-erythroid progenitor MEP stage had significantly better survival than those with NorMA phenotype in granulocyte-macrophage progenitor GMP stage. Thus NorMA produced a stratification of AML cohorts by differentiation stage, with significant outcome differences. It also provided clean molecular signatures for these stages. NorMA can be used in many other contexts, to explore for example the tumor cell of origin, or disease predisposition.

Dataset Information

Expression profiles of normal hematopoietic stem and progenitor cells and acute myeloid leukemia sub-populations

Publications

An LSC epigenetic signature is largely mutation independent and implicates the HOXA cluster in AML pathogenesis.

Similar Datasets

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