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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 GSE33672
Expression data of NCI-H441 cells stably expressing hsa-mir-365-2 vs empty vector
  • organism-icon Homo sapiens
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Hsa-mir-365-2 is one of the two precursors that give rise to miR-365. We discovered that miR-365 directly regulates a lung cancer and developmental gene termed thyroid transcription factor 1 (TTF-1 or NKX2-1).

Publication Title

MiR-365 regulates lung cancer and developmental gene thyroid transcription factor 1.

Sample Metadata Fields

Cell line

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accession-icon GSE16589
Time course profile of umbilical cord blood cells in culture
  • organism-icon Homo sapiens
  • sample-icon 19 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Despite the importance of inter-cellular communication networks in regulating stem cell fate decisions, very little is known about the topology, dynamics, or functional significance. Using human blood stem cell cultures as an experimental paradigm, we present a novel bioinformatic approach to integrate genome-scale molecular profiles (transcriptome and secretome) and publicly available databases to reconstruct soluble factor-mediated inter-cellular signalling networks regulating blood stem cell fate decisions.

Publication Title

Dynamic interaction networks in a hierarchically organized tissue.

Sample Metadata Fields

Specimen part

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accession-icon SRP075293
Nuclear mRNA quality control is bypassed for rapid export of stress responsive transcripts [RNA-Seq]
  • organism-icon Saccharomyces cerevisiae
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Comparative analyses of Mex67 and Npl3 binding to mRNA at normal growth condition (25째C) and upon shift to heat stress (30 min, 42째C). Overall design: Examination of two biological RNA Co-IP replicates of Mex67, Npl3 and no tag control at 25째C and upon shift to 30 min at 42째C (Heat stress) and subsequent Illumina RNA deep-sequencing

Publication Title

mRNA quality control is bypassed for immediate export of stress-responsive transcripts.

Sample Metadata Fields

Cell line, Subject

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accession-icon SRP091764
Modeling signaling-dependent pluripotent cell states with boolean logic can predict cell fate transitions [II]
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Pluripotent stem cells (PSCs) exist in multiple stable states, each with specific cellular properties and molecular signatures. The process by which pluripotency is either maintained or destabilized to initiate specific developmental programs is poorly understood. We have developed a model to predict stabilized PSC gene regulatory network (GRN) states in response to combinations of input signals. While previous attempts to model PSC fate have been limited to static cell compositions, our approach enables simulations of dynamic heterogeneity by combining an Asynchronous Boolean Simulation (ABS) strategy with simulated single cell fate transitions using a Strongly Connected Components (SCCs). This computational framework was applied to a reverse-engineered and curated core GRN for mouse embryonic stem cells (mESCs) to simulate responses to LIF, Wnt/ß-catenin, FGF/ERK, BMP4, and Activin A/Nodal pathway activation. For these input signals, our simulations exhibit strong predictive power for gene expression patterns, cell population composition, and nodes controlling cell fate transitions. The model predictions extend into early PSC differentiation, demonstrating, for example, that a Cdx2-high/Oct4-low state can be efficiently generated from mESCs residing in a naïve and signal-receptive state sustained by combinations of signaling activators and inhibitors. Overall design: Examination of perturbed PSCs versus control PSCs and mesoderm progenitors Mouse pluripotent stem cells were grown on tissue culture plates for two days in serum-containing, feeder free medium supplemented with the following cytokines/small molecules: 2i = CHIR99021 (Reagents Direct 27-H76 – 3µM) & PD0325901 (Reagents Direct 39-C68 – 1µM) Jaki = JAK inhibitor (EMD Millipore 420097 – 2.0µM) BMP = BMP4 (R&D Systems 314-BP-010 – 10ng/ml) Alk5i = ALK5 inhibitor II (Cedarlane ALX-270-445 - 10µM)

Publication Title

Modeling signaling-dependent pluripotency with Boolean logic to predict cell fate transitions.

Sample Metadata Fields

Cell line, Treatment, Subject, Time

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accession-icon GSE84482
Proneurogenic ligands defined by modeling developing cortex growth factor communication networks
  • organism-icon Mus musculus
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 2.0 ST Array (mogene20st)

Description

The neural stem cell decision to self-renew or differentiate is tightly regulated by its microenvironment. Here, we have asked about this microenvironment, focusing on growth factors in the embryonic cortex at a time when it is largely comprised of neural precursor cells (NPCs) and newborn neurons. We show that cortical NPCs secrete factors that promote their maintenance while cortical neurons secrete factors that promote differentiation. To define factors important for these activities, we used transcriptome profiling to identify ligands produced by NPCs and neurons, cell surface mass spectrometry to identify receptors on these cells, and computational modeling to integrate these data. The resultant model predicts a complex growth factor environment with multiple autocrine and paracrine interactions. We tested this communication model, focusing on neurogenesis, and identified IFN, Nrtn and glial-derived neurotrophic factor (GDNF) as ligands with unexpected roles in promoting neurogenic differentiation of NPCs in vivo.

Publication Title

Proneurogenic Ligands Defined by Modeling Developing Cortex Growth Factor Communication Networks.

Sample Metadata Fields

Specimen part

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accession-icon GSE35422
Expression analysis of doxycycline inducible secondary fibroblasts reprogramming under adherent and suspension conditions
  • organism-icon Mus musculus
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Samples of adherent and suspension cells undergoing reprogramming were collected at day 0, day2, day6, day15 (with doxycycline) and day25 (without doxycycline).

Publication Title

Derivation, expansion and differentiation of induced pluripotent stem cells in continuous suspension cultures.

Sample Metadata Fields

Specimen part

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accession-icon GSE43309
InVERT molding for scalable control of tissue micro-architecture
  • organism-icon Homo sapiens
  • sample-icon 5 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

Complex tissues contain multiple cell types that are hierarchically organized within morphologically and functionally distinct compartments. Construction of engineered tissues with optimized tissue architecture has been limited by tissue fabrication techniques, which do not enable versatile microscale organization of multiple cell types in tissues of size adequate for physiologic studies and tissue therapies. Here, we present an Intaglio-Void/Embed-Relief Topographic (InVERT) molding method for microscale organization of many cell types, including induced pluripotent stem cell (iPS)-derived progeny, within a variety of synthetic and natural extracellular matrices and across tissues of sizes appropriate for in vitro, pre-clinical, and clinical biologic studies. We demonstrate that compartmental placement of non-parenchymal cells relative to primary or iPS-derived hepatocytes and hepatic compartment microstructure and cellular composition modulate hepatic functions. Configurations found to be optimal in vitro also result in superior survival and function after transplantation into mice, demonstrating the importance of architectural optimization prior to implantation.

Publication Title

InVERT molding for scalable control of tissue microarchitecture.

Sample Metadata Fields

Specimen part

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accession-icon SRP133326
Single cell RNA-seq of IL-10-producing CD4 T cells during chronic LCMV infection
  • organism-icon Mus musculus
  • sample-icon 1 Downloadable Sample
  • Technology Badge IconNextSeq 500

Description

During chronic viral infection, the inflammatory function of CD4 T cells becomes gradually attenuated. Concurrently, Th1 cells progressively acquire the capacity to secrete the cytokine IL-10, a potent suppressor of antiviral T cell responses. To determine the transcriptional changes that underlie this T cell adaption process, we applied a single-cell RNA-sequencing approach and assessed the heterogeneity of IL-10-expressing CD4 T cells during chronic infection. Unexpectedly, our analyses revealed an IL-10-producing population with a robust Tfh-signature. Using IL-10 and IL-21 double-reporter mice, we further demonstrate that IL-10+IL-21+co-producing Tfh cells arise predominantly during chronic but not acute LCMV infection. Importantly, depletion of IL-10+IL-21+co-producing CD4 T cells or deletion of Il10 specifically in Tfh cells resulted in impaired humoral immunity and viral control. Mechanistically, B cell-intrinsic IL-10 signaling was required for sustaining germinal center reactions. Lastly, we demonstrate that IL-27 and type I IFNs differentially regulate the formation of this protective IL-10-producing Tfh subset. Thus, our findings elucidate a critical role for Tfh-derived IL-10 in promoting humoral immunity during persistent viral infection. Overall design: One sample prepared using 10x Genomics Chromium platform

Publication Title

Single-cell RNA sequencing unveils an IL-10-producing helper subset that sustains humoral immunity during persistent infection.

Sample Metadata Fields

Specimen part, Subject, Time

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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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