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accession-icon GSE100112
B-cell activating factor (BAFF) stimulation of Burkitt Lymphoma cell line
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st), Illumina HiSeq 2000

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

A comparative study of RNA-Seq and microarray data analysis on the two examples of rectal-cancer patients and Burkitt Lymphoma cells.

Sample Metadata Fields

Cell line, Treatment

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accession-icon SRP108761
B-cell activating factor (BAFF) stimulation of Burkitt Lymphoma cell line [RNA-Seq]
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

RNA-Seq profiling of Burkitt Lymphoma cell line (BL2) with B-cell activating factor (BAFF) for 24 hrs . The Burkitt Lymphoma cell line were either only cultured in cell culture medium supplemented with 10 mM HEPES at 1 × 106 cells/ml or additionally incubated with B-cell activating factor (BAFF) for 24 hrs Overall design: Two conditions of BL2 cells each in 3 replicates: 1. non-stimulated control (BL2), 2. Baff stimulated (BL2Baff)

Publication Title

A comparative study of RNA-Seq and microarray data analysis on the two examples of rectal-cancer patients and Burkitt Lymphoma cells.

Sample Metadata Fields

Treatment, Subject

View Samples
accession-icon GSE100111
B-cell activating factor (BAFF) stimulation of Burkitt Lymphoma cell line [Affymetrix]
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Microarray profiling of Burkitt Lymphoma cell line (BL2) with B-cell activating factor (BAFF) for 24 hrs .

Publication Title

A comparative study of RNA-Seq and microarray data analysis on the two examples of rectal-cancer patients and Burkitt Lymphoma cells.

Sample Metadata Fields

Cell line

View Samples
accession-icon GSE78229
Microarray gene-expression profiles of 50 pancreatic tumors tissue from patients with pancreatic ductal adenocarcinoma
  • organism-icon Homo sapiens
  • sample-icon 50 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

In order to identify biologically relevant tumor markers, and novel therapeutic target we have compared the tumor gene expression profiles of long (OS>=24 months,n=14) and short (OS <=7months, n=11) survival patients. Then we conducted Kaplan-Meier survival analysis using all the 50 samples listed here. The Affymetrix gene-expression data of these 50 samples were also included in the earlier submission by us as GEO accession number GSE62452.

Publication Title

Endothelial Nitric Oxide Synthase Traffic Inducer (NOSTRIN) is a Negative Regulator of Disease Aggressiveness in Pancreatic Cancer.

Sample Metadata Fields

Specimen part

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accession-icon GSE28735
Microarray gene-expression profiles of 45 matching pairs of pancreatic tumor and adjacent non-tumor tissues from 45 patients with pancreatic ductal adenocarcinoma
  • organism-icon Homo sapiens
  • sample-icon 90 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

In order to identify biologically relevant tumor markers with prognostic significance, we set out to analyze gene expression profiling of tumor and adjacent non-tumor tissues from PDAC cases.

Publication Title

DPEP1 inhibits tumor cell invasiveness, enhances chemosensitivity and predicts clinical outcome in pancreatic ductal adenocarcinoma.

Sample Metadata Fields

Specimen part

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accession-icon GSE62452
Microarray gene-expression profiles of 69 pancreatic tumors and 61 adjacent non-tumor tissue from patients with pancreatic ductal adenocarcinoma
  • organism-icon Homo sapiens
  • sample-icon 127 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

In order to identify biologically relevant tumor markers , we analyzed gene expression profiling of tumor and adjacent non-tumor tissues from PDAC cases. We compared the microarray gene-expression profiles of MIF-high and MIF low expressing tumors as detrmined by qRT-PCR. Affymetrix gene-expression analysis was done in two sets. Affymetrix data from sample number 1-90 were earlier submited by us as GEO accession#: GSE28735. The batch effect between the two sets of data was removed using Partek Genomic Suite and this normalized data was submitted to GEO in this submission. All the analysis was performed using the merged data set.

Publication Title

A Novel MIF Signaling Pathway Drives the Malignant Character of Pancreatic Cancer by Targeting NR3C2.

Sample Metadata Fields

Specimen part

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accession-icon SRP074601
The RNA-binding protein TTP is a global post-transcriptional regulator of feedback control in inflammation [RNA-seq]
  • organism-icon Mus musculus
  • sample-icon 9 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

RNA-binding proteins (RBPs) facilitate post-transcriptional control of eukaryotic gene expression at multiple levels. The RBP tristetraprolin (TTP/Zfp36) is a signal-induced phosphorylated anti-inflammatory protein guiding unstable mRNAs of pro-inflammatory proteins for degradation and preventing translation. Using iCLIP, we have identified numerous mRNA targets bound by wild-type TTP and by a non-MK2-phosphorylatable TTP mutant (TTP-AA) in 1h LPS-stimulated macrophages and correlated their interaction with TTP to changes at the level of mRNA abundance and translation in a transcriptome-wide manner. The close similarity of the transcriptome of TTP-deficient and TTP-expressing macrophages upon short LPS stimulation suggested an effective inactivation of TTP by MK2 under these conditions whereas retained RNA-binding capacity of TTP-AA to 3’UTRs caused profound changes in the transcriptome and translatome, altered NF-?B-activation and induced cell death. Increased TTP binding to the 3''UTR of feedback inhibitor mRNAs, such as Ier3, Dusp1 or Tnfaip3, in the absence of MK2-dependent TTP neutralization resulted in a strong reduction of their protein synthesis contributing to the deregulation of the NF-?B-signaling pathway. Taken together, our study uncovers a role for TTP in NF-?B-signaling and highlights the importance of fine-tuned TTP activity-regulation by MK2 in order to control feedback signaling during the inflammatory response. Overall design: Comparison of the transcriptomes of TTP knockout macrophages inducibly expressing GFP, GFP-TTP or GFP-TTP-AA (S52A, S178A) phosphorylation mutant during 1h LPS stimulation. 3 biological replicates per genotype and condition.

Publication Title

The RNA-binding protein TTP is a global post-transcriptional regulator of feedback control in inflammation.

Sample Metadata Fields

Specimen part, Subject

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accession-icon GSE14334
Transcriptomic analysis of human lung development
  • organism-icon Homo sapiens
  • sample-icon 38 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We decompose the genome-wide expression patterns in 38 embryonic human lung (53-154 days post conception/dpc) into their independent, dominant directions of transcriptomic sample variation in order togain global insight of the developing human lung transcriptome.The characteristic genes and their corresponding bioontologic attribute profile for the latter were identified. We noted the overrepresentation of lung specific attributes (e.g., surfactant proteins) traditionally associated with later developmental stages, and highly ranked attributes (e.g., chemokineimmunologic processes) not previously reported nor immediately apparent in an early lung development context. We defined the 3,223gene union of the characteristic genes of the 3 most dominant sources of variation as the developing lung characteristic subtranscriptome (DLCS). It may be regarded as the minimal gene set describing the essential biology of this process. The developing lung series in this transcriptomic variation perspectiveform a contiguous trajectory with critical time points that both correlate with the 2 traditional morphologic stages overlapping -154 dpc and suggest the existence of 2 novel phases within the pseudoglandular stage. To demonstrate that this characterization is robust, we showed that the model could be used to estimate the gestational age of independent human lung tissue samples with a median absolute error of 5 days, based on the DLCS of their lung profile alone. Repeating this procedure on the homologous transcriptome profiles of developing mouse lung 1419 dpc, we were able to recover their correct developmental chronology.

Publication Title

Transcriptomic analysis of human lung development.

Sample Metadata Fields

Sex, Disease, Race

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accession-icon GSE68896
Age, sexual dimorphism and disease associations in the developing human fetal lung transcriptome
  • organism-icon Homo sapiens
  • sample-icon 313 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Whole human fetal lung transcriptome profiles from estimated gestational ages 54 to 137 days post conception. Maternal cigarette smoking status is indicated by cotinine levels measured in the corresponding placenta.

Publication Title

Age, Sexual Dimorphism, and Disease Associations in the Developing Human Fetal Lung Transcriptome.

Sample Metadata Fields

Sex, Specimen part, Subject

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accession-icon GSE47796
CEMA, a platform to define cell states
  • organism-icon Homo sapiens
  • sample-icon 82 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

gene expression database and algorithm to define cell expression modules

Publication Title

Identifying gene expression modules that define human cell fates.

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)

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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