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accession-icon GSE788
Comparison of microarray to RT-PCR
  • organism-icon Rattus norvegicus
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Genome U34 Array (rgu34a)

Description

mRNA used for the analysis of these microarrays were previously analyzed for 34 genes by reverse transcription - polymerase chain reaction in Desai BJ et al., J.Orthop.Trauma 17: 689-698, 2003. These two data sets were subsequently studied to compare the results from these two different methods for mRNA quantitation. The comparison was publised in "Comparison of mRNA gene expression by RT-PCR and DNA microarray" by W. Etienne, M.H. Meyer, J. Peppers, and R.A. Meyer, Jr., BioTechniques 36 (4): 618-626, April 2004.

Publication Title

Comparison of mRNA gene expression by RT-PCR and DNA microarray.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE77532
Genome-wide analysis of gene expression during adipogenesis in human adipose-derived mesenchymal stromal cells reveals novel patterns of gene expression during adipocyte differentiation
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 2.0 ST Array (hugene20st)

Description

To better understand the scale of gene expression changes that occur during the formation of mature adipocytes from preadipocytes, we compared and characterised the transcriptome profile of mesenchymal stromal cells derived from human adipose tissue, otherwise known as adipose-derived stromal cells (ASCs), undergoing adipocyte differentiation on day 1, 7, 14 and 21 (representing the early to late stage process of adipogenesis). Microarray technique was systematically employed to study gene expression in adipose-derived stromal cells during adipogenic differentiation over a 21 day period to identify genes that are important in driving adipogenesis in humans.

Publication Title

Genome-wide analysis of gene expression during adipogenesis in human adipose-derived stromal cells reveals novel patterns of gene expression during adipocyte differentiation.

Sample Metadata Fields

Sex, Age, Specimen part, Subject

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accession-icon SRP080946
Expansion of an FCRL5+ B cell subset resembling atypical memory B cells in an animal model of malaria
  • organism-icon Mus musculus
  • sample-icon 10 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Background: In human malaria, parasites of the genus Plasmodium elicit expansion of atypical memory B cells (atMBCs), which lack the classical markers CD21 and CD27. We have identified a putative population of analogous B cells in a murine model of infection with P. chabaudi, delineated by the marker FCRL5. We performed RNA-Seq on FCRL5+ and FCRL5- B cells sorted from infected mice, so as to characterize the transcriptional profile of these cells and permit comparison to atMBCs in humans. Results: FCRL5+ B cells were found to have distinct transcriptional profiles from FCRL5- B cells, with approximately 400 genes exhibiting significant differences between the two groups. Additionally, about 25% of these differentially expressed genes were also differentially expressed in human atMBCs versus classical MBCs, as previously described by Sullivan et al (PLoS Pathogens 2015). Conclusions: FCRL5+ class-switched B cells are a transcriptionally distinct subset arising in P. chabaudi infection, with transcriptional similarities to human atMBCs that develop in chronic malaria settings. Overall design: Class-switched B cells (IgM- IgD- CD19+) were isolated into FCRL5+ and FCRL5- populations by double-sorting from the blood of C57BL/6 adult female mice 21 days post-infection with Plasmodium chabaudi. Pools of ~1000 cells were isolated and processed for RNA sequencing. 5 biological replicates were analyzed for each sample type.

Publication Title

FCRL5<sup>+</sup> Memory B Cells Exhibit Robust Recall Responses.

Sample Metadata Fields

Specimen part, Subject

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accession-icon GSE48258
Changes in gene expression induced by CDK9 inhibition alone and in combination with fludarabine
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Using a transcriptomics approach we explored the mechanism(s) of synergy observed between CDKI-73 and fludarabine in primary CLL cells. The cytotoxic effects of CDKI-73 were associated with transcriptional inhibition of cdk9 target genes including MCL1 and XIAP. In contrast, fludarabine induced the transcription of these genes, an effect that was reversed by the combination of CDKI-73 and fludarabine.

Publication Title

A novel Cdk9 inhibitor preferentially targets tumor cells and synergizes with fludarabine.

Sample Metadata Fields

Specimen part, Treatment

View Samples
accession-icon GSE27388
Exon-array profiling of squamous cell carcinoma and adenocarcinoma in human cervical FFPE samples
  • organism-icon Homo sapiens
  • sample-icon 28 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [probe set (exon) version (huex10st)

Description

Degradation and chemical modification of RNA in formalin-fixed paraffin-embedded (FFPE) samples hamper their use in expression profiling studies. In this study, we investigated the feasibility of gene expression signature generation from archival FFPE materials. Nineteen cervical squamous cell carcinoma (SCC) and nine adenocarcinoma (AC) 10~16-year-old FFPE samples were profiled using Affymetrix Exon 1.0 ST arrays. A comparison of the global gene expression changes between SCC and AC revealed 1217 differentially expressed genes. Of these, 1062 showed significantly higher expression levels in SCC relative to AC, and 155 genes were found to be specifically upregulated in AC. When the 1217-gene signature was tested on a fresh-frozen human non-small cell lung cancer (NSCLC) series, it correctly separated the 58 NSCLC samples into SCC and AC. In conclusion, our results showed that clinically and biologically relevant gene expression profiles can be derived from FFPE samples with Exon array profiling.

Publication Title

Exon-array profiling unlocks clinically and biologically relevant gene signatures from formalin-fixed paraffin-embedded tumour samples.

Sample Metadata Fields

Disease, Disease stage

View Samples
accession-icon GSE6321
Analysis of CD38+ and CD38- sub-clones derived from the same CLL patient
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

CD38 expression is an important prognostic marker in CLL with high levels of CD38 associated with shorter overall survival. In this study, we used gene expression profiling and protein analysis of highly purified cell-sorted CD38+ and CD38- chronic lymphocytic leukemia cells to elucidate a molecular basis for the association between CD38 expression and inferior clinical outcome. Paired CD38+ and CD38- CLL cells derived from the same patient were shown to be monoclonal by VH gene sequencing but despite this, CD38+ CLL cells possessed a distinct gene expression profile when compared with their CD38- sub-clones.

Publication Title

Highly purified CD38+ and CD38- sub-clones derived from the same chronic lymphocytic leukemia patient have distinct gene expression signatures despite their monoclonal origin.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP151779
Gene expression in WT and Thpok-deficient LCMV-specific memory T cells
  • organism-icon Mus musculus
  • sample-icon 77 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Gene expression of memory CD4+ and CD8+ T cells determined by RNAseq 30 days after LCMV Armstrong infection Overall design: 30 days post-infection with LCMV Arm spleen GP66:I-Ab+ T cells from Zbtb7bAD (CD4 Zbtb7bAD) or Tnfrsf4-Cre– (CD4 Ctrl) mice and of spleen GP33:H-2Db+ T cells from Tnfrsf4-Cre– animals (CD8 Ctrl) were sorted and gene expression was determined by RNAseq

Publication Title

The Emergence and Functional Fitness of Memory CD4<sup>+</sup> T Cells Require the Transcription Factor Thpok.

Sample Metadata Fields

Subject

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accession-icon SRP164943
Single-cell gene expression of anti-viral WT and Thpok-deficient effector and memory T cells
  • organism-icon Mus musculus
  • sample-icon 38 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

Single-cell gene expression of effector and memory CD4+ and CD8+ T cells from WT or Thppok-deficient animals was determined by sRNAseq after LCMV Armstrong infection Overall design: 7 and 30 days post-infection with LCMV Arm spleen T cells were sorted and gene expression was determined by scRNAseq

Publication Title

The Emergence and Functional Fitness of Memory CD4<sup>+</sup> T Cells Require the Transcription Factor Thpok.

Sample Metadata Fields

Specimen part, Subject

View Samples
accession-icon GSE52717
Flexible multiplatform RNA profiling at the single cell level applied to enriched cancer initiating cells
  • organism-icon Homo sapiens
  • sample-icon 20 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

Evaluation and validation of a robust single cell RNA-amplification protocol through transcriptional profiling of enriched lung cancer initiating cells.

Sample Metadata Fields

Specimen part, Disease, Cell line

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accession-icon GSE52712
Flexible multiplatform RNA profiling at the single cell level applied to enriched cancer initiating cells: Affymetrix array data
  • organism-icon Homo sapiens
  • sample-icon 20 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Accurate profiling of RNA expression of single cells is a valuable approach for broadening our understanding of cancer biology and mechanisms of dissemination, but requires the development of reliable methods for their molecular characterization. Here we evaluate a single cell methodology which generates microgram amounts of cDNA suitable for next generation sequencing (RNA-Seq), high throughput RT-qPCR and Affymetrix array analysis. The approach was tested by comparing expression profiles of amplified single MCF7 and MCF10A cells to profiles generated from unamplified RNA. The expression profiles were compared by Affymetrix-U133 arrays, RNA-Seq and high-density qPCR. There were strong cross-platform correlations of >80% and concordance between single cell and unamplified material of >70%. We exemplify the approach through analysis of rare sorted cancer initiating cells (CICs) derived from a NSCLC patient-derived xenograft. Populations of 10 cells from total tumour and two distinct subsets of CIC, putatively involved in primary tumor maintenance or metastasis formation were FACS sorted then directly amplified. CIC expression profiles strongly correlated with published stem-cell and epithelial-mesenchymal transition (EMT) signatures. Our results confirm the utility of the amplification system and our methodology to detect and distinguish RNA profiles in rare cell populations that inform on EMT and stem-cell characteristics. This GEO dataset comprises the Affymetrix U-133 Plus 2.0 data for MCF7 and MCF10A cDNA amplified from 1ng RNA and single cell samples.

Publication Title

Evaluation and validation of a robust single cell RNA-amplification protocol through transcriptional profiling of enriched lung cancer initiating cells.

Sample Metadata Fields

Disease, Cell line

View Samples

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)

fund-icon Fund the CCDL

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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