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.
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.
Time
View SamplesThis SuperSeries is composed of the SubSeries listed below.
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.
Specimen part, Time
View SamplesIdentify differentially expressed genes related to the neurodegenerative process in a new animal model of hepatic encephalopathy (HE).
Cerebellar neurodegeneration in a new rat model of episodic hepatic encephalopathy.
Specimen part, Treatment
View SamplesCyclin D3 is critical hematopoiesis and loss of cyclin D3 leads to resistance to transformation of bone marrow progenitors by Notch1-IC.
Therapeutic targeting of the cyclin D3:CDK4/6 complex in T cell leukemia.
Specimen part, Cell line
View SamplesActivated 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]).
Leukemia-initiating cell activity requires calcineurin in T-cell acute lymphoblastic leukemia.
Specimen part, Treatment
View SamplesThis SuperSeries is composed of the SubSeries listed below.
Stress-independent activation of XBP1s and/or ATF6 reveals three functionally diverse ER proteostasis environments.
Specimen part, Treatment
View SamplesThe 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.
Stress-independent activation of XBP1s and/or ATF6 reveals three functionally diverse ER proteostasis environments.
Specimen part, Treatment
View SamplesThe 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.
Stress-independent activation of XBP1s and/or ATF6 reveals three functionally diverse ER proteostasis environments.
Specimen part, Treatment
View SamplesThis SuperSeries is composed of the SubSeries listed below.
Molecular Aging of Human Liver: An Epigenetic/Transcriptomic Signature.
Sex, Age, Specimen part, Disease
View SamplesGene 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.
Molecular Aging of Human Liver: An Epigenetic/Transcriptomic Signature.
Sex, Age, Specimen part, Disease
View Samples