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accession-icon GSE34714
Routine use of microarray-based gene expression profiling to identify patients with low cytogenetic risk acute myeloid leukemia: accurate results can be obtained even with suboptimal samples. (test samples)
  • organism-icon Homo sapiens
  • sample-icon 117 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V3.0 expression beadchip

Description

Background: Gene expression profiling has shown its ability to identify with high accuracy low cytogenetic risk acute myeloid leukemia such as acute promyelocytic leukemia and leukemias with t(8;21) or inv(16). The aim of this gene expression profiling study was to evaluate to what extent suboptimal samples with low leukemic blast load (range, 2-59%) and/or poor quality control criteria could also be correctly identified. Methods: Specific signatures were first defined so that all 71 acute promyelocytic leukemia, leukemia with t(8;21) or inv(16)-AML as well as cytogenetically normal acute myeloid leukemia samples with at least 60% blasts and good quality control criteria were correctly classified (training set). The classifiers were then evaluated for their ability to assign to the expected class 111 samples considered as suboptimal because of a low leukemic blast load (n=101) and/or poor quality control criteria (n=10) (test set). Results: With 10-marker classifiers, all training set samples as well as 97 of the 101 test samples with a low blast load, and all 10 samples with poor quality control criteria were correctly classified. Regarding test set samples, the overall error rate of the class prediction was below 4 percent, even though the leukemic blast load was as low as 2%. Sensitivity, specificity, negative and positive predictive values of the class assignments ranged from 91% to 100%. Of note, for acute promyelocytic leukemia and leukemias with t(8;21) or inv(16), the confidence level of the class assignment was influenced by the leukemic blast load. Conclusion: Gene expression profiling and a supervised method requiring 10-marker classifiers enable the identification of favorable cytogenetic risk acute myeloid leukemia even when samples contain low leukemic blast loads or display poor quality control criterion.

Publication Title

Routine use of microarray-based gene expression profiling to identify patients with low cytogenetic risk acute myeloid leukemia: accurate results can be obtained even with suboptimal samples.

Sample Metadata Fields

Time

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accession-icon GSE34823
Routine use of microarray-based gene expression profiling to identify patients with low cytogenetic risk acute myeloid leukemia: accurate results can be obtained even with suboptimal samples
  • organism-icon Homo sapiens
  • sample-icon 27 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V3.0 expression beadchip

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Routine use of microarray-based gene expression profiling to identify patients with low cytogenetic risk acute myeloid leukemia: accurate results can be obtained even with suboptimal samples.

Sample Metadata Fields

Specimen part, Time

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accession-icon GSE71425
Gene expression of rat cerebellum in a new animal model of hepatic encephalopathy (HE)
  • organism-icon Rattus norvegicus
  • sample-icon 20 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Gene 1.1 ST Array (ragene11st)

Description

Identify differentially expressed genes related to the neurodegenerative process in a new animal model of hepatic encephalopathy (HE).

Publication Title

Cerebellar neurodegeneration in a new rat model of episodic hepatic encephalopathy.

Sample Metadata Fields

Specimen part, Treatment

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accession-icon GSE40635
Expression data from vehicle or PD-0332991 treated human T-ALL lines
  • organism-icon Homo sapiens
  • sample-icon 16 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Cyclin D3 is critical hematopoiesis and loss of cyclin D3 leads to resistance to transformation of bone marrow progenitors by Notch1-IC.

Publication Title

Therapeutic targeting of the cyclin D3:CDK4/6 complex in T cell leukemia.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE60258
Calcineurin-dependent transcriptome in ICN1 (activated NOTCH1)-induced T cell acute lymphoblastic leukemia (T-ALL)
  • organism-icon Mus musculus
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Activated NOTCH1 induces T-ALL in mice when transduced in bone marrow (BM) cells. T-ALL cells activate the calcineurin/NFAT pathway in vivo (Medyouf H. et al. Nat Med 2007 [PMID 17515895]).

Publication Title

Leukemia-initiating cell activity requires calcineurin in T-cell acute lymphoblastic leukemia.

Sample Metadata Fields

Specimen part, Treatment

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accession-icon GSE44951
Stress-Independent Activation of XBP1s and/or ATF6 Reveals Three Functionally Distinct ER Proteostasis Environments
  • organism-icon Homo sapiens
  • sample-icon 15 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

Stress-independent activation of XBP1s and/or ATF6 reveals three functionally diverse ER proteostasis environments.

Sample Metadata Fields

Specimen part, Treatment

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accession-icon GSE44949
Stress-Independent Activation of XBP1s and/or ATF6 Reveals Three Functionally Distinct ER Proteostasis Environments [HEK293DAX]
  • organism-icon Homo sapiens
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

The unfolded protein response (UPR) maintains endoplasmic reticulum (ER) proteostasis through the activation of transcription factors such as XBP1s and ATF6. The functional consequences of these transcription factors for ER proteostasis remain poorly defined. Here, we describe methodology that enables orthogonal, small molecule-mediated activation of the UPR-associated transcription factors XBP1s and/or ATF6 in the same cell independent of stress. We employ transcriptomics and quantitative proteomics to evaluate ER proteostasis network remodeling owing to the XBP1s and/or ATF6 transcriptional programs. Furthermore, we demonstrate that the three ER proteostasis environments accessible by activating XBP1s and/or ATF6 differentially influence the folding, trafficking, and degradation of destabilized ER client proteins without globally affecting the endogenous proteome. Our data reveal how the ER proteostasis network is remodeled by the XBP1s and/or ATF6 transcriptional programs at the molecular level and demonstrate the potential for selectively restoring aberrant ER proteostasis of pathologic, destabilized proteins through arm-selective UPR-activation.

Publication Title

Stress-independent activation of XBP1s and/or ATF6 reveals three functionally diverse ER proteostasis environments.

Sample Metadata Fields

Specimen part, Treatment

View Samples
accession-icon GSE44950
Stress-Independent Activation of XBP1s and/or ATF6 Reveals Three Functionally Distinct ER Proteostasis Environments [HEK293DYG]
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

The unfolded protein response (UPR) maintains endoplasmic reticulum (ER) proteostasis through the activation of transcription factors such as XBP1s and ATF6. The functional consequences of these transcription factors for ER proteostasis remain poorly defined. Here, we describe methodology that enables orthogonal, small molecule-mediated activation of the UPR-associated transcription factors XBP1s and/or ATF6 in the same cell independent of stress. We employ transcriptomics and quantitative proteomics to evaluate ER proteostasis network remodeling owing to the XBP1s and/or ATF6 transcriptional programs. Furthermore, we demonstrate that the three ER proteostasis environments accessible by activating XBP1s and/or ATF6 differentially influence the folding, trafficking, and degradation of destabilized ER client proteins without globally affecting the endogenous proteome. Our data reveal how the ER proteostasis network is remodeled by the XBP1s and/or ATF6 transcriptional programs at the molecular level and demonstrate the potential for selectively restoring aberrant ER proteostasis of pathologic, destabilized proteins through arm-selective UPR-activation.

Publication Title

Stress-independent activation of XBP1s and/or ATF6 reveals three functionally diverse ER proteostasis environments.

Sample Metadata Fields

Specimen part, Treatment

View Samples
accession-icon GSE107039
Epigenetic and transcriptomic signature of aging in human liver
  • organism-icon Homo sapiens
  • sample-icon 33 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Molecular Aging of Human Liver: An Epigenetic/Transcriptomic Signature.

Sample Metadata Fields

Sex, Age, Specimen part, Disease

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accession-icon GSE107037
Epigenetic and transcriptomic signature of aging in human liver [expression]
  • organism-icon Homo sapiens
  • sample-icon 33 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Gene expression profiling of liver biopsies collected from 33 healthy liver donors ranging from 13 to 90 years old. The Affymetrix HG-U133 Plus 2.0 GeneChip platform was used to evaluate gene-expression.

Publication Title

Molecular Aging of Human Liver: An Epigenetic/Transcriptomic Signature.

Sample Metadata Fields

Sex, Age, Specimen part, Disease

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)

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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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