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accession-icon GSE63335
Quantitative proteomic analysis reveals maturation as a mechanism underlying glucocorticoid resistance in B lineage ALL and JNK inhibitors as a re-sensitising therapy
  • organism-icon Homo sapiens
  • sample-icon 5 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [CDF:huex10stv2_57_37b_0112.cdf (huex10st)

Description

Glucocorticoids (GC) are pivotal in the treatment of childhood acute lymphoblastic leukaemia (ALL) but resistance is a continuing clinical problem with the underlying mechanisms still unclear. An isobaric tag proteomic approach was used to compare protein profiles of the B lineage ALL GC-sensitive cell line, PreB 697, and its GC-resistant sub-line, R3F9, before and after dexamethasone exposure. Two transcription factors involved in B- cell differentiation, PAX5 and IRF4, were differentially regulated in the PreB 697 compared to the R3F9 cell line in response to GC. PAX5 basal protein expression was less in R3F9 compared to its GC-sensitive parent and was confirmed to be lower in other GC-resistant sub-lines of Pre B697 and was associated with a decreased expression of the PAX5 transcriptional target, CD19. Gene set enrichment analysis of microarray data from the cell lines showed that increasing GC-resistance was associated with differentiation from preB-II to an immature B-lymphocytes stage. GC resistant sub lines were shown to have a higher levels of p-JNK compared to the parent line and JNK inhibition caused re-sensitisation to GC. Reduced CD19 levels accompanying GC resistance was also apparent in some clinical samples, with high levels of MRD persisting after GC containing induction chemotherapy. Thus, quantitative proteomic analysis reveals a role for PAX5 and maturation as a recurrent mechanism underlying glucocorticoid resistance in ALL and identifies JNK inhibitors as a possible re-sensitising therapy.

Publication Title

Quantitative proteomic analysis reveals maturation as a mechanism underlying glucocorticoid resistance in B lineage ALL and re-sensitization by JNK inhibition.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE73618
Spc1/ Spc1K49R overexpression - gene expression changes in S. pombe
  • organism-icon Schizosaccharomyces pombe
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Yeast Genome 2.0 Array (yeast2)

Description

Spc1/ Spc1K49R was overexpressed in wt S. pombe cells for 24 hours and gene expression changes were analysed

Publication Title

Genome wide transcription profiling of the effects of overexpression of Spc1 and its kinase dead mutant in Schizosaccharomyces pombe.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE69306
Significant obesity associated gene expression changes are in the stomach but not intestines in obese mice
  • organism-icon Mus musculus
  • sample-icon 129 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

The gastrointestinal (GI) tract can have significant impact on the regulation of the whole body metabolism and may contribute to the development of obesity and diabetes. To systemically elucidate the role of the GI tract in obesity, we performed a transcriptomic analyses in different parts of the GI tract of two obese mouse models: ob/ob and high-fat diet (HFD) fed mice. Compared to their lean controls, both obese mouse groups had significant amount of gene expression changes in the stomach (ob/ob: 959; HFD: 542), much more than the number of changes in the intestine. Despite the difference in genetic background, the two mouse models shared 296 similar gene expression changes in the stomach. Among those genes, some had known associations to obesity, diabetes and insulin resistance. In addition, the gene expression profile strongly suggested an increased gastric acid secretion in both obese mouse models, probably through an activation of the gastrin pathway. In conclusion, our data reveal a previously unknown dominant connection between the stomach and obesity.

Publication Title

Significant obesity-associated gene expression changes occur in the stomach but not intestines in obese mice.

Sample Metadata Fields

Specimen part

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accession-icon GSE70262
The impact of P53 loss on transcriptome changes following loss of Apc in the intestine
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

BACKGROUND: p53 is an important tumor suppressor with a known role in the later stages of colorectal cancer, but its relevance to the early stages of neoplastic initiation remains somewhat unclear. Although p53-dependent regulation of Wnt signalling activity is known to occur, the importance of these regulatory mechanisms during the early stages of intestinal neoplasia has not been demonstrated.

Publication Title

A limited role for p53 in modulating the immediate phenotype of Apc loss in the intestine.

Sample Metadata Fields

Specimen part

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accession-icon GSE37369
Caco-2 cell gene expression following co-culture with Lactobacillus casei and Bifidobacterium breve
  • organism-icon Homo sapiens
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

To characterize how symbiotic bacteria affect the lolecular and cellular mechanisms of epithelial homeostasis, human colonic Caco-2 cells

Publication Title

Epithelial cell proliferation arrest induced by lactate and acetate from Lactobacillus casei and Bifidobacterium breve.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE12051
Microarray predictor of response to infliximab in rheumatoid arthritis (RA) patients
  • organism-icon Homo sapiens
  • sample-icon 44 Downloadable Samples
  • Technology Badge IconSentrix Human-6 Expression BeadChip

Description

We sought to find a gene-expression multigene predictor of response to infliximab therapy in Rheumatoid Arthritis patients. Using internal and external cross-validation systems we have built and validated an 8-gene predictor for response to infliximab.

Publication Title

An eight-gene blood expression profile predicts the response to infliximab in rheumatoid arthritis.

Sample Metadata Fields

Sex, Specimen part, Disease, Disease stage

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accession-icon GSE9785
Expression data from Newborn mice infected with Shigella flexneri
  • organism-icon Mus musculus
  • sample-icon 36 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Expression 430A Array (moe430a)

Description

In order to identify the developmental changes controlling the switch from disease susceptibility to resistance, we performed global gene expression analysis on non-infected and infected intestinal tissues taken from 4-day- and 7-day-old animals.

Publication Title

Maturation of paneth cells induces the refractory state of newborn mice to Shigella infection.

Sample Metadata Fields

Age

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accession-icon SRP061276
Maize (Zea mays) leaf transcriptome analysis under abiotic stress in wild type and RNA Polymerase IV mutant
  • organism-icon Zea mays
  • sample-icon 29 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Plants have developed complex mechanisms to respond and adapt to abiotic stresses, coupling elaborate modulation of gene expression together with the preservation of genome stability. Epigenetic mechanisms - DNA methylation, chromatin modifications and non coding RNAs - were shown to play a fundamental role in stress-induced gene regulation and may also result in genome destabilization, with the activation and/or the transcription of silenced transposons and retroelements, causing genome rearrangements and novel gene expression patterns. Maize leaf transcriptome was analyzed by total RNA-Seq in both B73 and rmr6 (PolIV mutant involved in siRNA biogenesis and in the RdDM pathway) after drought and salt stress application. Reference annotation based transcript assembly allowed the identification both of new expressed loci and splicing variants, improving the current maize transcriptome annotation. Many antisense transcripts matching on the opposite strand of annotated loci were also identified, while more than the 20% of transcripts represent non coding RNA belonging to four classes: siRNAs, shRNAs, lncRNAs and transposable elements (or their relics). Several lncRNAs are modulated by stress application while TE-related sequences are mainly expressed in rmr6 and up-regulated by the stress. Overall design: Total RNA-Seq analysis of maize leaves from wt and rmr6-1 mutant plants grown under 1) control conditions, 2) drought stress, 3) salt stress, 4) salt+drought stress. Each condition was investigated in triplicate after 10 days of treatment and after 7 days of recovery. Samples derived from replicates 2 and 3 were pooled and sequenced together

Publication Title

Maize RNA PolIV affects the expression of genes with nearby TE insertions and has a genome-wide repressive impact on transcription.

Sample Metadata Fields

Treatment, Subject, Time

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accession-icon GSE62035
The DNMT1 associated lncRNA Dali is an epigenetic regulator of neural differentiation
  • organism-icon Mus musculus
  • sample-icon 24 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

The long non-coding RNA Dali is an epigenetic regulator of neural differentiation.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE34060
Expression data of Sox9+ and Ngn3+ mouse pancreas cells at different stages of development
  • organism-icon Mus musculus
  • sample-icon 15 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Genes specific to Sox9+ pancreatic progenitors were identified by comparing the gene expression in embryonic and adult Sox9+ cells.

Publication Title

A Notch-dependent molecular circuitry initiates pancreatic endocrine and ductal cell differentiation.

Sample Metadata Fields

Specimen part

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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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