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accession-icon GSE90922
Expression data in JDCaP prostate cancer xenograft model before and after expression of AR splice variants
  • organism-icon Homo sapiens
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Our previous study using nude rats revealed that the parental JDCaP xenografts predominantly expressed full-length androgen receptor (AR) whereas the relapsed JDCaP xenografts after castration acquired AR splice variants including AR-V7 and ARv567es. To understand molecular mechanisms underlying the acquisition of AR splice variants in the JDCaP model, we performed microarray analysis using RNA samples of the xenografts without castration (Parent), the relapsed xenografts overexpressing full-length AR and AR-V7 (ARhiV7hi), and the relapsed xenografts expressing ARv567es (ARv567es).

Publication Title

The RNA helicase DDX39B and its paralog DDX39A regulate androgen receptor splice variant AR-V7 generation.

Sample Metadata Fields

Specimen part

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accession-icon GSE98364
Expression data in HCT-116 colon cancer cell treated with SCD1 inhibitor or in SCD1 knocked out HCT-116 cell
  • organism-icon Homo sapiens
  • sample-icon 3 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

To understand molecular mechanisms underlying the growth inhibitory ativity of Stearoyl-CoA desaturase-1 (SCD1) inhibitor, we performed microarray analysis using HCT-116 colorectal cancer cells, in which SCD1 was pharmacologically blocked or genetically ablated.

Publication Title

Feedback activation of AMPK-mediated autophagy acceleration is a key resistance mechanism against SCD1 inhibitor-induced cell growth inhibition.

Sample Metadata Fields

Specimen part, Cell line, Treatment

View Samples
accession-icon GSE93777
Multi-omics monitoring of drug response in rheumatoid arthritis.
  • organism-icon Homo sapiens
  • sample-icon 286 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

Multi-omics monitoring of drug response in rheumatoid arthritis in pursuit of molecular remission.

Sample Metadata Fields

Sex, Age, Specimen part, Disease, Disease stage, Subject

View Samples
accession-icon GSE93272
Whole blood gene expression of rheumatoid arthritis
  • organism-icon Homo sapiens
  • sample-icon 238 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Sustained clinical remission (CR) without drug treatment has not been achieved in patients with rheumatoid arthritis (RA). This implies a substantial difference between CR and the healthy state, but it has yet to be quantified. We report a longitudinal monitoring of the drug response at multi-omics levels in the peripheral blood of patients with RA. Our data reveal that drug treatments alter the molecular profile closer to that of HCs at the transcriptome, serum proteome and immunophenotype level. Patient follow-up suggests that the molecular profile after drug treatments is associated with long-term stable CR. In addition, we identify molecular signatures that are resistant to drug treatments. These signatures are associated with RA independently of known disease severity indexes and are largely explained by the imbalance of neutrophils, monocytes, and lymphocytes. This high-dimensional phenotyping provides a quantitative measure of molecular remission and illustrates a multi-omics approach to understanding drug response.

Publication Title

Multi-omics monitoring of drug response in rheumatoid arthritis in pursuit of molecular remission.

Sample Metadata Fields

Sex, Age, Specimen part, Disease, Disease stage, Subject

View Samples
accession-icon GSE93776
Immune cells gene expression from rheumatoid arthritis and healthy donors
  • organism-icon Homo sapiens
  • sample-icon 163 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Sustained clinical remission (CR) without drug treatment has not been achieved in patients with rheumatoid arthritis (RA). This implies a substantial difference between CR and the healthy state, but it has yet to be quantified. We report a longitudinal monitoring of the drug response at multi-omics levels in the peripheral blood of patients with RA. Our data reveal that drug treatments alter the molecular profile closer to that of HCs at the transcriptome, serum proteome and immunophenotype level. Patient follow-up suggests that the molecular profile after drug treatments is associated with long-term stable CR. In addition, we identify molecular signatures that are resistant to drug treatments. These signatures are associated with RA independently of known disease severity indexes and are largely explained by the imbalance of neutrophils, monocytes, and lymphocytes. This high-dimensional phenotyping provides a quantitative measure of molecular remission and illustrates a multi-omics approach to understanding drug response.

Publication Title

Multi-omics monitoring of drug response in rheumatoid arthritis in pursuit of molecular remission.

Sample Metadata Fields

Sex, Age, Specimen part, Disease

View Samples
accession-icon GSE84844
Multi-omics profiling of patients with primary Sjogren's syndrome
  • organism-icon Homo sapiens
  • sample-icon 56 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Multi-omics study was conducted to elucidate the crucial molecular mechanisms of primary Sjgrens syndrome (SS) pathology. We generated multiple data set from well-defined patients with SS, which includes whole-blood transcriptomes, serum proteomes and peripheral immunophenotyping. Based on our newly generated data, we performed an extensive bioinformatic investigation. Our integrative analysis identified SS gene signatures (SGS) dysregulated in widespread omics layers, including epigenomes, mRNAs and proteins. SGS predominantly involved the interferon signature and ADAMs substrates. Besides, SGS was significantly overlapped with SS-causing genes indicated by a genome-wide association study and expression trait loci analyses. Combining the molecular signatures with immunophenotypic profiles revealed that cytotoxic CD8 T cells were associated with SGS. Further, we observed the activation of SGS in cytotoxic CD8 T cells isolated from patients with SS. Our multi-omics investigation identified gene signatures deeply associated with SS pathology and showed the involvement of cytotoxic CD8 T cells. These integrative relations across multiple layers will facilitate our understanding of SS at the system level.

Publication Title

Multiomic disease signatures converge to cytotoxic CD8 T cells in primary Sjögren's syndrome.

Sample Metadata Fields

Sex, Age, Specimen part, Disease

View Samples
accession-icon GSE93683
CD8 T-cells from pSS patients and human healthy volunteers
  • organism-icon Homo sapiens
  • sample-icon 48 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Multi-omics study was conducted to elucidate the crucial molecular mechanisms of primary Sjgrens syndrome (SS) pathology. We generated multiple data set from well-defined patients with SS, which includes whole-blood transcriptomes, serum proteomes and peripheral immunophenotyping. Based on our newly generated data, we performed an extensive bioinformatic investigation. Our integrative analysis identified SS gene signatures (SGS) dysregulated in widespread omics layers, including epigenomes, mRNAs and proteins. SGS predominantly involved the interferon signature and ADAMs substrates. Besides, SGS was significantly overlapped with SS-causing genes indicated by a genome-wide association study and expression trait loci analyses. Combining the molecular signatures with immunophenotypic profiles revealed that cytotoxic CD8 T cells were associated with SGS. Further, we observed the activation of SGS in cytotoxic CD8 T cells isolated from patients with SS. Our multi-omics investigation identified gene signatures deeply associated with SS pathology and showed the involvement of cytotoxic CD8 T cells. These integrative relations across multiple layers will facilitate our understanding of SS at the system level.

Publication Title

Multiomic disease signatures converge to cytotoxic CD8 T cells in primary Sjögren's syndrome.

Sample Metadata Fields

Sex, Specimen part, Disease, Disease stage, Subject

View Samples
accession-icon GSE94510
CD4 T-cells from pSS patients and human healthy volunteers
  • organism-icon Homo sapiens
  • sample-icon 36 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Multi-omics study was conducted to elucidate the crucial molecular mechanisms of primary Sjgrens syndrome (SS) pathology. We generated multiple data set from well-defined patients with SS, which includes whole-blood transcriptomes, serum proteomes and peripheral immunophenotyping. Based on our newly generated data, we performed an extensive bioinformatic investigation. Our integrative analysis identified SS gene signatures (SGS) dysregulated in widespread omics layers, including epigenomes, mRNAs and proteins. SGS predominantly involved the interferon signature and ADAMs substrates. Besides, SGS was significantly overlapped with SS-causing genes indicated by a genome-wide association study and expression trait loci analyses. Combining the molecular signatures with immunophenotypic profiles revealed that cytotoxic CD8 T cells were associated with SGS. Further, we observed the activation of SGS in cytotoxic CD8 T cells isolated from patients with SS. Our multi-omics investigation identified gene signatures deeply associated with SS pathology and showed the involvement of cytotoxic CD8 T cells. These integrative relations across multiple layers will facilitate our understanding of SS at the system level.

Publication Title

Multiomic disease signatures converge to cytotoxic CD8 T cells in primary Sjögren's syndrome.

Sample Metadata Fields

Sex, Specimen part, Disease, Subject

View Samples
accession-icon GSE67905
Expression data in HeLa cells treated with CENP-E siRNA or Eg5 siRNA in the presence of BubR1 siRNA
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The molecular mechanism responsible for cell fate after mitotic slippage is unclear. We investigate the postmitotic effects of different mitotic aberrations, misaligned chromosomes produced by CENP-E siRNA (siCENP-E), and monopolar spindles resulting from Eg5 siRNA (siEg5).

Publication Title

Expression data of HeLa cells treated with CENP-E siRNA or Eg5 siRNA in the presence of BubR1 siRNA.

Sample Metadata Fields

Cell line

View Samples
accession-icon GSE39091
Expression data of A375 melanoma cells after DMSO or MLN4924 +/- Nutlin treatment for 26 hours
  • organism-icon Homo sapiens
  • sample-icon 38 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Microarrays were used to determine the change in gene expression of genes involved in the p53 pathway after siRNA knock down of p53, CDT1 or BRCA1

Publication Title

No associated publication

Sample Metadata Fields

Cell line, Treatment

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)

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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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