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accession-icon GSE61697
Gene expressions of CD4+ T cells in each developmental stages
  • organism-icon Homo sapiens
  • sample-icon 24 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The development of T cells has been characterized as taking place over three stages: nave (Tn), central memory (Tcm), and effector memory (Tem) cells.

Publication Title

Polarization diversity of human CD4+ stem cell memory T cells.

Sample Metadata Fields

Sex, Age

View Samples
accession-icon SRP158491
Gene expressions of T cells in each developmental stages in healthy volunteers and patients with rheumatoid arthritis
  • organism-icon Homo sapiens
  • sample-icon 276 Downloadable Samples
  • Technology Badge IconIon Torrent Proton

Description

We collected and compared samples from the cohort consisted of six groups as follows: methotrexate (MTX) monotherapy, combination therapy of MTX and infliximab (IFX), tocilizumab (TCZ) monotherapy, age- and gender-matched HC, and a small number of synovial fluid samples. In order to reduce variation due to the proportion of cells at each developmental stage, we performed transcriptome analysis after sorting CD4+ and CD8+ T cells according to developmental stage. We created a gene list that was significantly expressed in RA T cells, and revealed that pathways such as mTORC1, IL-2-stat5, Cell cycle and interferon-related genes were significantly enriched among them. Overall design: Examination among healthy controls and patients with rheumatoid arthritis, including before and after treatment

Publication Title

Multi-dimensional analysis identified rheumatoid arthritis-driving pathway in human T cell.

Sample Metadata Fields

Sex, Age, Specimen part, Disease, Subject

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accession-icon SRP140437
Transcriptome change after tocilizumab therapy in rheumatoid arthritis patients
  • organism-icon Homo sapiens
  • sample-icon 22 Downloadable Samples
  • Technology Badge IconIon Torrent Proton

Description

We compared whole CD4+ and CD8+ T cells from frozen PBMC samples that were collected before and after treatment initiation of each patient with rheumatoid arthritis. Lists consisting of 858 and 950 differentially expressed genes were created from CD4 and CD8, respectively, and these were used for enrichment analysis. As a result, we found that certain pathways were downregulated after TCZ treatment in both CD4+ and CD8+ T cells, including mechanistic target of rapamycin complex 1 (mTORC1) signaling, the IL-2 pathway, and IFN-related genes. Overall design: Examination between before and after tocilizumab treatment of CD4 and CD8 T cell in rheumatoid arthritis patients

Publication Title

Multi-dimensional analysis identified rheumatoid arthritis-driving pathway in human T cell.

Sample Metadata Fields

Sex, Age, Specimen part, Disease, Subject

View Samples
accession-icon GSE18778
Comparison of gene expression between wild-type and PTIP deficient chicken DT40 B cells
  • organism-icon Gallus gallus
  • sample-icon 2 Downloadable Samples
  • Technology Badge Icon Affymetrix Chicken Genome Array (chicken)

Description

PTIP (Pax2 transactivation domain-interacting protein) is a nuclear protein containing six BRCT domains. It has been shown that PTIP affects gene expression by controlling the activity of the transcription factor Pax2 and histone H3 lysine 4 methyltransferase complexes. In addition to its role in transcriptional regulation, PTIP has been implicated in DNA damage response. To ask if the depletion of PTIP affects the expression level of genes encoding DNA damage response factors , we compared the whole transcripts between wild-type and PTIP deficient chicken DT40 B cell lines.

Publication Title

PTIP promotes DNA double-strand break repair through homologous recombination.

Sample Metadata Fields

Specimen part, Cell line

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 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
...

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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