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accession-icon GSE40311
A model system for assessing the ability of exon microarray and tag sequencing to detect genes specific for malignant B-cells
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

A model system for assessing and comparing the ability of exon microarray and tag sequencing to detect genes specific for malignant B-cells.

Sample Metadata Fields

Cell line

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accession-icon SRP015013
A model system for assessing the ability of tag sequencing to detect genes specific for malignant B-cells
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer

Description

The purpose of this study was to develop a quantification method that can be used to assess the ability of tag-seq to detect malignant B-cell transcripts. The data support that tumour cell concentration is an important variable with fundamental impact on gene expression pattern. Overall design: We analysed eight serial dilutions of the malignant B-cell line, OCI-Ly8, into the embryonic kidney cell line, HEK293, by tag-sequencing. No technical replicates were performed.

Publication Title

A model system for assessing and comparing the ability of exon microarray and tag sequencing to detect genes specific for malignant B-cells.

Sample Metadata Fields

Cell line, Subject

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accession-icon GSE40309
A model system for assessing the ability of exon microarray to detect genes specific for malignant B-cells
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer

Description

The purpose of this study was to develop a quantification method that can be used to assess the ability of exon microarray to detect malignant B-cell transcripts.

Publication Title

A model system for assessing and comparing the ability of exon microarray and tag sequencing to detect genes specific for malignant B-cells.

Sample Metadata Fields

Cell line

View Samples
accession-icon SRP171159
Transcriptional profiling of dendritic cells in a mouse model of food-antigen induced anaphylaxis using RNA-Seq
  • organism-icon Mus musculus
  • sample-icon 10 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

We used RNA sequencing to study gene expression in lymph node derived DCs from anaphylactic mice sensitized intranasally with the major peach allergen Pru p 3, during the acute reaction phase, induced intraperitoneally. In total, 237 genes changed significantly, 181 showing at least two-fold changes. Almost three quarters of these increased during anaphylaxis Overall design: 5 Female Balb/c mice aged 4-5 weeks, were sensitized to peach using intranasally administered Pru p 3 in combination with LPS and challenged intraperitoneally as described previously . 5 Littermates, treated with intranasally administered PBS (instead of Pru p 3 and LPS), and later given an intraperitoneal challenge as per the anaphylactic mice, were used for comparison.

Publication Title

Transcriptional Profiling of Dendritic Cells in a Mouse Model of Food-Antigen-Induced Anaphylaxis Reveals the Upregulation of Multiple Immune-Related Pathways.

Sample Metadata Fields

Sex, Cell line, Treatment, Subject

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accession-icon GSE36135
Expression data from prostate cancer Docetaxel-resistant cells
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Docetaxel is the standard first line therapy for hormone-refractory prostate cancer patients. Here we generated models of Docetaxel resistance in prostate cancer cells to study the molecular pathways that drive the acquisition of resistance to this therapy. We used microarrays to detail the global program of gene expression underlying the acquisition of Docetaxel resistance in prostate cancer cells.

Publication Title

Suppression of acquired docetaxel resistance in prostate cancer through depletion of notch- and hedgehog-dependent tumor-initiating cells.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE56315
Diffuse Large B-Cell Lymphoma Classification System That Associates Normal B-Cell Subset Phenotypes With Prognosis
  • organism-icon Homo sapiens
  • sample-icon 84 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

Diffuse large B-cell lymphoma classification system that associates normal B-cell subset phenotypes with prognosis.

Sample Metadata Fields

Specimen part

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accession-icon GSE56313
Diffuse Large B-Cell Lymphoma Classification System That Associates Normal B-Cell Subset Phenotypes With Prognosis
  • organism-icon Homo sapiens
  • sample-icon 54 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Purpose

Publication Title

Diffuse large B-cell lymphoma classification system that associates normal B-cell subset phenotypes with prognosis.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE56314
Diffuse Large B-Cell Lymphoma Classification System That Associates Normal B-Cell Subset Phenotypes With Prognosis
  • organism-icon Homo sapiens
  • sample-icon 30 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Purpose

Publication Title

Diffuse large B-cell lymphoma classification system that associates normal B-cell subset phenotypes with prognosis.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE95307
Dual inhibition of G9a and DNMT1 Enhances Cell Reprogramming Promoting Induction of Mesenchymal-to-Epithelial Transition and Facilitating Transcription Factor Engagement in the Genome.
  • organism-icon Homo sapiens
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 2.0 ST Array (hugene20st)

Description

The combination of defined factors with small molecules targeting epigenetic factors is a strategy that has been shown to enhance optimal derivation of human iPSCs and could be used for therapeutic and regenerative medicine applications. In this study, we showed that a new first-in-class dual G9a/DNMT inhibitor CM272 compound improves the standard four-factor reprogramming efficiency of human fibroblast. The use of CM272 facilitates the generation of iPSC with only two factors, OCT4 and SOX2, allowing the removal of potentially oncogenic factors such as cMYC or KLF4. Taking a closer look at the early events occurring during cell reprogramming we demonstrated that treatment with our G9a/DNMT dual inhibitor induces heterochromatin relaxation, facilitates the engagement of OCT4 and SOX2 transcription factors to the genome and promotes mesenchymal to epithelial transition during cell reprogramming. Thus, the use of this new G9a/DNMT dual inhibitor compound may represent an interesting alternative for improving cell reprogramming.

Publication Title

Reversible dual inhibitor against G9a and DNMT1 improves human iPSC derivation enhancing MET and facilitating transcription factor engagement to the genome.

Sample Metadata Fields

Sex, Specimen part, Disease, Cell line

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accession-icon GSE56511
NRG-1 induces mature ventricular cardiac differentiation from iPS cells contributing to cardiac tissue repair
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 2.0 ST Array (mogene20st)

Description

Combined treatment with NRG-1 and DMSO led to efficient differentiation of iPS into mature ventricular-like cardiac cells, which were capable of preserving cardiac function and tissue viability when transplanted into a mouse model of myocardial infarction.

Publication Title

Neuregulin-1β induces mature ventricular cardiac differentiation from induced pluripotent stem cells contributing to cardiac tissue repair.

Sample Metadata Fields

Sex

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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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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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