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accession-icon GSE81136
Expression data from MeGRX232-OE and MeGRX360-OE Arabidopsis
  • organism-icon Arabidopsis thaliana
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)

Description

MeGRX232 and MeGRX360 are drought-inducible CC-type glutaredoxins in cassava. Overexpression of them in Arabidopsis caused different effects on plant growth.

Publication Title

No associated publication

Alternate Accession IDs

E-GEOD-81136

Sample Metadata Fields

Age, Specimen part

View Samples
accession-icon GSE26244
Expression data from cytoplasmic hybrid (cybrid) and rho0 cells
  • organism-icon Homo sapiens
  • sample-icon 54 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Mitochondria have been implicated in insulin resistance and beta cell dysfunction, both of which comprise the core pathophysiology of type 2 diabetes mellitus (T2DM). It has also recently been found that mtDNA haplogroups are distinctively associated with susceptibility to T2DM at least in Koreans and Japanese.

Publication Title

Gene expression pattern in transmitochondrial cytoplasmic hybrid cells harboring type 2 diabetes-associated mitochondrial DNA haplogroups.

Alternate Accession IDs

E-GEOD-26244

Sample Metadata Fields

Specimen part

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accession-icon SRP115993
Transcriptome sequence of RAW264.7 cell by Burkholderia pseudomallei infection
  • organism-icon Mus musculus
  • sample-icon 4 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Aims to find out differential expression genes (DEGs)in RAW264.7 cells during infection by Burkholderia pseudomallei infection

Publication Title

No associated publication

Alternate Accession IDs

None

Sample Metadata Fields

Sex, Specimen part, Cell line, Treatment

View Samples
accession-icon GSE26876
Time kinetics of gene expression in NK92 cells after Plasmodium falciparum-iRBC encounter
  • organism-icon Homo sapiens
  • sample-icon 21 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

To study the effect of Plasmodium falciparum-infected erythrocytes on gene expression in NK92 cells, microarray analysis after 6, 12 and 24 hours of co-culture with either uRBC or iRBC was performed. The aim was to identify pathways in NK92 cells that are switched on after iRBC encounter in a time-dependent manner that will help to understand the mechanisms in innate immune defenses against Plasmodium falciparum infection.

Publication Title

No associated publication

Alternate Accession IDs

E-GEOD-26876

Sample Metadata Fields

Cell line, Time

View Samples
accession-icon GSE19010
Gene expression profiling of Plasmodium falciparum after co-culture with NK cells
  • organism-icon Plasmodium falciparum
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Plasmodium/Anopheles Genome Array (plasmodiumanopheles)

Description

The aim of the study was to determine the effect of natural killer (NK) cells on the global gene expression in Plasmodium falciparum.

Publication Title

No associated publication

Alternate Accession IDs

E-GEOD-19010

Sample Metadata Fields

Treatment

View Samples
accession-icon GSE13507
Predective Value of Prognosis-Related Gene Expression Study in Primary Bladder Cancer
  • organism-icon Homo sapiens
  • sample-icon 244 Downloadable Samples
  • Technology Badge IconIllumina human-6 v2.0 expression beadchip

Description

This study aimed to identify the genetic signatures associated with disease prognosis in bladder cancer. We used 165 primary bladder cancer samples, 23 recurrent non-muscle invasive tumor tissues, 58 normal looking bladder mucosae surrounding cancer and 10 normal bladder mucosae for microarray analysis. Hierarchical clustering was used to stratify the prognosis-related gene classifiers. For validation, real-time reverse-transcriptase polymerase chain reaction (RT-PCR) of top-ranked 14 genes was performed. On unsupervised hierarchical clustering using prognosis related gene-classifier, tumors were divided into 2 groups. The high risk gene signatures had significantly poor prognosis compared to low risk gene signatures (P<0.001 by the log-rank test, respectively). The prognosis-related gene classifiers correlated significantly with recurrence of non-muscle invasive bladder cancer (hazard ratio, 4.09; 95% confidence interval [CI], 1.94 to 8.64; P<0.001), and progression (hazard ratio, 23.68; 95% confidence interval [CI], 4.91 to 114.30; P<0.001), cancer-specific survival (hazard ratio, 29.25; 95% confidence interval [CI], 3.47 to 246.98; P=0.002) and overall survival (hazard ratio, 23.33; 95% confidence interval [CI], 4.97 to 109.50; P<0.001) of muscle invasive bladder cancer (p < 0.001, respectively). No patient with non-muscle invasive bladder cancer experienced cancer progression in low risk gene signature group. Prognosis-related gene classifiers validated by RT- PCR showed identical results. Prognosis related gene-classifiers provided strong predictive value for disease outcome. These gene classifiers could assist in selecting patients who might benefit from more aggressive therapeutic intervention or surveillance.

Publication Title

Predictive value of progression-related gene classifier in primary non-muscle invasive bladder cancer.

Alternate Accession IDs

E-GEOD-13507

Sample Metadata Fields

Sex, Age, Specimen part, Disease stage

View Samples
accession-icon GSE16757
Gene expression study in hepatocellular carcinoma
  • organism-icon Homo sapiens
  • sample-icon 100 Downloadable Samples
  • Technology Badge IconIllumina human-6 v2.0 expression beadchip

Description

Gene expression data from 100 human hepatocellular carcinomas (HCC) were generated and analyzed as part of effort for validating prognostic gene expression signatures from previous studies. Using four different classification algorithms and leave-one-out cross-validation approaches, four different prognostic signatures were applied to test the robustness and concordance of predicted outcome in individual patients. All four tumor-derived signatures were significantly associated with prognosis and had a high rate of concordance with predicted outcomes for individual patients.

Publication Title

Sixty-five gene-based risk score classifier predicts overall survival in hepatocellular carcinoma.

Alternate Accession IDs

E-GEOD-16757

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE22633
Genome-Wide Molecular Signature of Cholangiocarcinoma and Its Trandifferentation-Related Genes
  • organism-icon Homo sapiens
  • sample-icon 63 Downloadable Samples
  • Technology Badge IconIllumina human-6 v2.0 expression beadchip

Description

Cholangiocarcinoma (CC) is an aggressive tumor that shows a poor survival rate even after resection. The present study aimed at identification of the genome-wide expressed genes related to CC oncogenesis and its sarcomatous transdifferentiation using DNA microarray technology. The differentially expressed genes in 9 cholangiocarcinoma cell lines (Choi.CK, Cho.CK, J.CK, S.CK, CK.L1, CK.L2, CK.P1, CK.P2 and CK.Y1) were analyzed in comparison with 4 kinds of cultured biliary epithelial cells (ND.1, ND.2, ND.3 and ND.4) using the Illumina Human-6 v2 BeadChip (48 K). Unsupervised hierachical clustering analysis perfectively classified the 13 cell samples into two groups, normal biliary epithelial (N) and immortalized biliary epithelial cells and CC (T) cells. We identified 120 commonly upregulated ( > 2.5 fold) genes and 340 commonly downregulated ( < 0.4-fold) genes in the two groups. Hierachical clustering analysis of sarcomatoid CC cells (S.CK) revealed 316 differentially upregulated genes (> 4-fold) and 335 downregulated genes (< 0.25-fold).) compared with 3 CC cell lines (Choi.CK, Cho.CK, and J.CK). In conclusion, these data will contribute to better understand the molecular mechanisms of oncogenesis and transdifferentiation in CC and provide the molecular targets for CC diagnosis and therapy.

Publication Title

Genome-wide expression patterns associated with oncogenesis and sarcomatous transdifferentation of cholangiocarcinoma.

Alternate Accession IDs

E-GEOD-22633

Sample Metadata Fields

Specimen part, Cell line, Treatment

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accession-icon GSE19423
Predictive Gene Signatures as Strong Prognostic Indicators of the Effectiveness of BCG Immunotherapy
  • organism-icon Homo sapiens
  • sample-icon 42 Downloadable Samples
  • Technology Badge IconIllumina human-6 v2.0 expression beadchip

Description

Full title: Predictive Gene Signatures as Strong Prognostic Indicators of the Effectiveness of Bacillus CalmetteGurin (BCG) Immunotherapy in Primary pT1 Bladder Cancers

Publication Title

Gene signatures for the prediction of response to Bacillus Calmette-Guerin immunotherapy in primary pT1 bladder cancers.

Alternate Accession IDs

E-GEOD-19423

Sample Metadata Fields

Sex, Age, Disease stage

View Samples
accession-icon GSE37817
DNA methylation and expression profiling study for bladder cancer
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina human-6 v2.0 expression beadchip

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

HOXA9, ISL1 and ALDH1A3 methylation patterns as prognostic markers for nonmuscle invasive bladder cancer: array-based DNA methylation and expression profiling.

Alternate Accession IDs

E-GEOD-37817

Sample Metadata Fields

Sex, Age, Specimen part, Disease stage

View Samples
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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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