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accession-icon GSE24006
A Leukemic Stem Cell Expression Signature is Associated with Clinical Outcomes in Acute Myeloid Leukemia
  • organism-icon Homo sapiens
  • sample-icon 45 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Context: In many cancers, specific subpopulations of cells appear to be uniquely capable of initiating and maintaining tumors. The strongest support for this cancer stem cell model comes from transplantation assays in immune-deficient mice indicating that human acute myeloid leukemia (AML) is organized as a cellular hierarchy driven by self-renewing leukemia stem cells (LSC). This model has significant implications for the development of novel therapies, but its clinical significance remains unclear.

Publication Title

Association of a leukemic stem cell gene expression signature with clinical outcomes in acute myeloid leukemia.

Sample Metadata Fields

Disease, Disease stage, Subject

View Samples
accession-icon GSE34908
Genetic and epigenetic determinants of neurogenesis and myogenesis
  • organism-icon Mus musculus
  • sample-icon 24 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Genetic and epigenetic determinants of neurogenesis and myogenesis.

Sample Metadata Fields

Specimen part

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accession-icon GSE34907
Genetic and epigenetic determinants of neurogenesis and myogenesis [expression profiling]
  • organism-icon Mus musculus
  • sample-icon 24 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

The regulatory networks of differentiation programs have been partly characterized; however, the molecular mechanisms of lineage-specific gene regulation by highly similar transcription factors remain largely unknown. Here we compare the genome-wide binding and transcription profiles of NEUROD2-mediated neurogenesis with MYOD-mediated myogenesis. We demonstrate that NEUROD2 and MYOD bind a shared CAGCTG E-box motif and E-box motifs specific for each factor: CAGGTG for MYOD and CAGATG for NEUROD2. Binding at factor-specific motifs is associated with gene transcription, whereas binding at shared sites is associated with regional epigenetic modifications but not as strongly associated with gene transcription. Binding is largely constrained to E-boxes pre-set in an accessible chromatin context that determines the set of target genes activated in each cell type. These findings demonstrate that the differentiation program is genetically determined by E-box sequence whereas cell lineage epigenetically determines the availability of E-boxes for each differentiation program.

Publication Title

Genetic and epigenetic determinants of neurogenesis and myogenesis.

Sample Metadata Fields

Specimen part

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accession-icon GSE63270
Expression profiles of normal hematopoietic stem and progenitor cells and acute myeloid leukemia sub-populations
  • organism-icon Homo sapiens
  • sample-icon 98 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

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.

Publication Title

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

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE66792
Reprogramming of primary human Philadelphia chromosome-positive B cell acute lymphoblastic leukemia cells into nonleukemic macrophages
  • organism-icon Homo sapiens
  • sample-icon 15 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

BCRABL1+ precursor B-cell acute lymphoblastic leukemia (BCR ABL1+ B-ALL) is an aggressive hematopoietic neoplasm characterized by a block in differentiation due in part to the somatic loss of transcription factors required for B-cell development. We hypothesized that overcoming this differentiation block by forcing cells to reprogram to the myeloid lineage would reduce the leukemogenicity of these cells. We found that primary human BCRABL1+ B-ALL cells could be induced to reprogram into macrophage-like cells by exposure to myeloid differentiation-promoting cytokines in vitro or by transient expression of the myeloid transcription factor C/EBP or PU.1. The resultant cells were clonally related to the primary leukemic blasts but resembled normal macrophages in appearance, immunophenotype, gene expression, and function. Most importantly, these macrophage-like cells were unable to establish disease in xenograft hosts, indicating that lineage reprogramming eliminates the leukemogenicity of BCRABL1+ B-ALL cells, and suggesting a previously unidentified therapeutic strategy for this disease. Finally, we determined that myeloid reprogramming may occur to some degree in human patients by identifying primary CD14+ monocytes/ macrophages in BCRABL1+ B-ALL patient samples that possess the BCRABL1+ translocation and clonally recombined VDJ regions.

Publication Title

Reprogramming of primary human Philadelphia chromosome-positive B cell acute lymphoblastic leukemia cells into nonleukemic macrophages.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE33799
DUX4 activates germline genes, retroelements and immune-mediators: Implications for facioscapulohumeral dystrophy
  • organism-icon Homo sapiens
  • sample-icon 36 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

Facioscapulohumeral dystrophy (FSHD) is one of the most common inherited muscular dystrophies. The causative gene remains controversial and the mechanism of pathophysiology unknown. Here we identify genes associated with germline and early stem cell development as targets of the DUX4 transcription factor, a leading candidate gene for FSHD. The genes regulated by DUX4 are reliably detected in FSHD muscle but not in controls, providing direct support for the model that misexpression of DUX4 is a causal factor for FSHD. Additionally, we show that DUX4 binds and activates LTR elements from a class of MaLR endogenous primate retrotransposons and suppresses the innate immune response to viral infection, at least in part through the activation of DEFB103, a human defensin that can inhibit muscle differentiation. These findings suggest specific mechanisms of FSHD pathology and identify candidate biomarkers for disease diagnosis and progression.

Publication Title

DUX4 activates germline genes, retroelements, and immune mediators: implications for facioscapulohumeral dystrophy.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE65136
Robust enumeration of cell subsets from tissue expression profiles
  • organism-icon Homo sapiens
  • sample-icon 23 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a), Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Robust enumeration of cell subsets from tissue expression profiles.

Sample Metadata Fields

Specimen part, Disease, Disease stage

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accession-icon GSE65135
Robust enumeration of cell subsets from tissue expression profiles (HGU133Plus2)
  • organism-icon Homo sapiens
  • sample-icon 16 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a), Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We introduce CIBERSORT, a method for characterizing cell composition of complex tissues from their gene expression profiles. When applied to enumeration of hematopoietic subsets in RNA mixtures from fresh, frozen, and fixed tissues, including solid tumors, CIBERSORT outperformed other methods with respect to noise, unknown mixture content, and closely related cell types. CIBERSORT should enable large-scale analysis of RNA specimens for cellular biomarkers and therapeutic targets (http://cibersort.stanford.edu).

Publication Title

Robust enumeration of cell subsets from tissue expression profiles.

Sample Metadata Fields

Specimen part, Disease, Disease stage

View Samples
accession-icon GSE65134
Robust enumeration of cell subsets from tissue expression profiles (HGU133A)
  • organism-icon Homo sapiens
  • sample-icon 7 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

We introduce CIBERSORT, a method for characterizing cell composition of complex tissues from their gene expression profiles. When applied to enumeration of hematopoietic subsets in RNA mixtures from fresh, frozen, and fixed tissues, including solid tumors, CIBERSORT outperformed other methods with respect to noise, unknown mixture content, and closely related cell types. CIBERSORT should enable large-scale analysis of RNA specimens for cellular biomarkers and therapeutic targets (http://cibersort.stanford.edu).

Publication Title

Robust enumeration of cell subsets from tissue expression profiles.

Sample Metadata Fields

Specimen part, Disease

View Samples
accession-icon GSE20546
TAL1 knock down
  • organism-icon Homo sapiens
  • sample-icon 20 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Differential genomic targeting of the transcription factor TAL1 in alternate haematopoietic lineages.

Sample Metadata Fields

No sample metadata fields

View Samples
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refine.bio is a repository of uniformly processed and normalized, ready-to-use transcriptome data from publicly available sources. refine.bio is a project of the Childhood Cancer Data Lab (CCDL)

fund-icon Fund the CCDL

Developed by the Childhood Cancer Data Lab

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Cite refine.bio

Casey S. Greene, Dongbo Hu, Richard W. W. Jones, Stephanie Liu, David S. Mejia, Rob Patro, Stephen R. Piccolo, Ariel Rodriguez Romero, Hirak Sarkar, Candace L. Savonen, Jaclyn N. Taroni, William E. Vauclain, Deepashree Venkatesh Prasad, Kurt G. Wheeler. refine.bio: a resource of uniformly processed publicly available gene expression datasets.
URL: https://www.refine.bio

Note that the contributor list is in alphabetical order as we prepare a manuscript for submission.

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