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accession-icon GSE21521
Immature cell populations and an erythropoiesis gene expression signature in systemic juvenile idiopathic arthritis: Implications for pathogenesis
  • organism-icon Homo sapiens
  • sample-icon 146 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Objective. Previous observations suggest that active systemic juvenile idiopathic arthritis (sJIA) is associated with a prominent erythropoiesis gene expression signature. The aim of this study was to determine the association of this signature with peripheral blood mononuclear cell (PBMC) subpopulations and its specificity for sJIA as compared to related conditions.

Publication Title

Immature cell populations and an erythropoiesis gene-expression signature in systemic juvenile idiopathic arthritis: implications for pathogenesis.

Sample Metadata Fields

Sex, Specimen part, Race

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accession-icon GSE13849
Expression Signatures in Polyarticular JIA Show Heterogeneity and Offer a Molecular Classification of Disease Subsets
  • organism-icon Homo sapiens
  • sample-icon 110 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Objective. Microarray analysis was used to determine whether children with recent onset polyarticular juvenile idiopathic arthritis (JIA) exhibit biologically or clinically informative gene expression signatures in peripheral blood mononuclear cells (PBMC). Methods. Peripheral blood samples were obtained from 59 healthy children and 61 children with polyarticular JIA prior to treatment with second-line medications, such as methotrexate or biological agents. RNA was purified from Ficoll-isolated mononuclear cells, fluorescently labeled and then hybridized to Affymetrix U133 Plus 2.0 GeneChips. Data were analyzed using ANOVA at a 5% false discovery rate threshold after Robust Multi-Array Average pre-processing and Distance Weighted Discrimination normalization. Results. Initial analysis revealed 873 probe sets for genes that were differentially expressed between polyarticular JIA and controls. Hierarchical clustering of these probe sets distinguished three subgroups within polyarticular JIA. Prototypical subjects within each subgroup were identified and used to define subgroup-specific gene expression signatures. One of these signatures was associated with monocyte markers, another with transforming growth factor-beta-inducible genes, and a third with immediate-early genes. Correlation of these gene expression signatures with clinical and biological features of JIA subgroups suggests direct relevance to aspects of disease activity and supports the division of polyarticular JIA into distinct subsets. Conclusions. PBMC gene expression signatures in recent onset polyarticular JIA reflect discrete disease processes and offer a molecular classification of disease.

Publication Title

Gene expression signatures in polyarticular juvenile idiopathic arthritis demonstrate disease heterogeneity and offer a molecular classification of disease subsets.

Sample Metadata Fields

Sex, Specimen part, Race

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accession-icon GSE87769
Identification of Tfcp2l1 target genes in the mouse kidney
  • organism-icon Mus musculus, Rattus norvegicus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Transcription factor <i>TFCP2L1</i> patterns cells in the mouse kidney collecting ducts.

Sample Metadata Fields

Specimen part

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accession-icon GSE85325
Tfcp2l1 controls cellular patterning of the collecting duct.
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Gene expression analysis of mouse kidney after conditional inactivation of transcription factor Tfcp2l1

Publication Title

Transcription factor <i>TFCP2L1</i> patterns cells in the mouse kidney collecting ducts.

Sample Metadata Fields

Specimen part

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accession-icon GSE13501
Subtype-specific peripheral blood gene expression profiles in recent onset JIA
  • organism-icon Homo sapiens
  • sample-icon 183 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Objective: A multi-center study of recent onset juvenile idiopathic arthritis (JIA) subjects prior to treatment with DMARDS or biologics was undertaken to identify peripheral blood gene expression differences between JIA subclasses and controls. Methods: PBMC from 59 healthy children and 136 JIA subjects (28 enthesitis-related arthritis[ERA], 42 persistent oligoarthritis, 45 RF- polyarthritis, and 21 systemic) were isolated on Ficoll. Poly-A RNA was labeled using NuGEN Ovation and gene expression profiles were obtained using Affymetrix HG-U133 plus 2.0 Arrays. Results: 9,501 differentially expressed probe sets were identified among JIA subtypes and controls (ANOVA, FDR 5%). Specifically, 193, 1036, 873 and 7595 probe sets were different between controls and ERA, persistent oligoarthritis, RF- polyarthritis and systemic JIA samples respectively. In persistent oligoarthritis, RF- polyarthritis and systemic JIA subtypes, up-regulation of gene associated with IL-10 signaling was prominent. A hemoglobin cluster was identified that was under-expressed in ERA patients but over-expressed in systemic JIA. The influence of JAK/STAT, ERK/MAPK, IL-2 and B cell receptor signaling pathways was evident in persistent oligoarthritis. In systemic JIA, up regulation of innate immune pathways, including IL-6, TLR/IL1R, and PPAR signaling were noted, along with down regulation of gene networks related to NK and T cells. Complement and coagulation pathways were up-regulated in systemic JIA with a subset of these components differentially-expressed in the other three subtypes. Conclusions: Expression analysis identified differentially expressed genes in PBMCs between subclasses of JIA early in disease and controls, thus providing evidence for immunobiologic differences between these forms of childhood arthritis.

Publication Title

Subtype-specific peripheral blood gene expression profiles in recent-onset juvenile idiopathic arthritis.

Sample Metadata Fields

Sex, Specimen part, Race

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accession-icon SRP014213
A receptor tyrosine kinase network comprised of FGFRs, EGFR, ERBB2, and MET drives growth and survival of HNSCC cell lines.
  • organism-icon Homo sapiens
  • sample-icon 21 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer IIx

Description

We have previously shown that some gefitinib insensitive head and neck squamous cell carcinoma (HNSCC) cell lines exhibit dominant autocrine fibroblast growth factor receptor (FGFR) signaling. Herein, we deployed a whole genome loss-of-function screen to identify genes whose knockdown potentiated the inhibitory effect of the FGFR inhibitor, AZ12908010, in HNSCC cell lines. Three HNSCC cell lines expressing a genome-wide shRNA library were treated with AZ8010 and the abundance of shRNA sequences was assessed by deep sequencing. Synthetic lethal hits were validated through use of specific inhibitors and independent shRNAs. We found that multiple alternate receptors provided protection from FGFR inhibition, including the receptor tyrosine kinases (RTKs), epidermal growth factor receptor 2 (ERBB2) and hepatocyte growth factor receptor (MET). We showed that specific knockdown of either ERBB2 or MET in combination with FGFR inhibition led to increased inhibition of growth relative to FGFR tyrosine kinase inhibitor (TKI) treatment alone. These results were confirmed using specific small molecule inhibitors of either ERBB family members or MET. Moreover, the combination of FGFR, MET and ERBB family inhibitors showed the largest inhibition of growth as compared to the double combinations. These results reveal a role for alternate RTKs in maintaining pro-growth and survival signaling in HNSCC cells in the setting of FGFR inhibition. Thus, improved therapies for HNSCC patients could involve rationally designed combinations of TKIs targeting FGFR, ERBB family members and MET. Overall design: Using a genome-wide shRNA library in combination with deep sequencing, we screened for gene targets that were synthetic lethal with the FGFR inhibitor, AZ12908010 in HNSCC cells. Three HNSCC cell lines were screened in triplicate and the abundance of shRNA sequences in drug treated cells was compared to control treated cells.

Publication Title

A receptor tyrosine kinase network composed of fibroblast growth factor receptors, epidermal growth factor receptor, v-erb-b2 erythroblastic leukemia viral oncogene homolog 2, and hepatocyte growth factor receptor drives growth and survival of head and neck squamous carcinoma cell lines.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon GSE67999
Secreted frizzled related protein 3 (SFRP3) is required for tumorigenesis of PAX3-FOXO1-positive alveolar rhabdomyosarcoma
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

Alveolar rhabdomyosarcoma (aRMS) is a soft tissue sarcoma associated with the skeletal muscle lineage. The majority of aRMS tumors express the fusion protein PAX3-FOXO1 (PF), which has proven chemically intractable. As such, we identified proteins downstream from or cooperate with PF to support tumorigenesis, including SFRP3 (FRZB). Suppression of SFRP3 using lentivirally transduced shRNAs inhibits cell growth in vitro and tumor growth in vivo. This study aims to identify the genetic changes that underlie the SFRP3 suppression-mediated decreased cell growth. We analyzed changes using Gene Ontology (GO) enrichment and found the induced genes were enriched in striated muscle development/differentiation. In contrast, the repressed genes were enriched in response to stimulus and cell cycle/mitosis genes. We also observed as expected downregulation of SFRP3 (FRZB) but also downregulation of Wnt pathway-repressing genes such as CTBP2 (a transcriptional repressor of TCF, similar to CTBP1 ) and NAV2 (which is downstream from APC). Conversely, we noted upregulation of genes including CCND1 (cyclin D1) and SNAI2 (SLUG), both Wnt signaling target genes and WNT6, which is known to inhibit myoblast proliferation but induce myoblast elongation.

Publication Title

Secreted Frizzled-Related Protein 3 (SFRP3) Is Required for Tumorigenesis of PAX3-FOXO1-Positive Alveolar Rhabdomyosarcoma.

Sample Metadata Fields

Disease, Cell line, Treatment

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accession-icon GSE23206
NSCLC cells treated with Gefitinib
  • organism-icon Homo sapiens
  • sample-icon 2 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

About 10% of all NSCLC patients respond to gefitnib treatment and all of these patients will acquire resistance to the EGFR TKI.

Publication Title

Rapidly acquired resistance to EGFR tyrosine kinase inhibitors in NSCLC cell lines through de-repression of FGFR2 and FGFR3 expression.

Sample Metadata Fields

Cell line, Treatment

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accession-icon SRP066197
Transcriptional profiling of TH2 cells identifies pathogenic features associated with asthma
  • organism-icon Homo sapiens
  • sample-icon 160 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Allergic asthma and rhinitis are two common chronic allergic diseases that affect the lungs and nose, respectively. Both diseases share clinical and pathological features characteristic of excessive allergen-induced type 2 inflammation, orchestrated by memory CD4+ T cells that produce type 2 cytokines (TH2 cells). However, a large majority of subjects with allergic rhinitis do not develop asthma, suggesting divergence in disease mechanisms. Since TH2 cells play a pathogenic role in both these diseases and are also present in healthy non-allergic subjects, we performed global transcriptional profiling to determine whether there are qualitative differences in TH2 cells from subjects with allergic asthma, rhinitis and healthy controls. TH2 cells from asthmatic subjects expressed higher levels of several genes that promote their survival as well as alter their metabolic pathways to favor persistence at sites of allergic inflammation. In addition, genes that enhanced TH2 polarization and TH2 cytokine production were also upregulated in asthma. Several genes that oppose T cell activation were downregulated in asthma, suggesting enhanced activation potential of TH2 cells from asthmatic subjects. Many novel genes with poorly defined functions were also differentially expressed in asthma. Thus, our transcriptomic analysis of circulating TH2 cells has identified several molecules that are likely to confer pathogenic features to TH2 cells that are either unique or common to both asthma and rhinitis. Overall design: RNA-sequencing of circulating TH2 cells isolated from a cohort of patients with allergic rhinitis (25), asthma (40) patients and healthy non allergic subjects (15). Cells were directly isolated from blood by flow cytometry. Total RNA was extracted, messenger RNA was selected and cDNA was amplified linearly with a PCR based method (Picelli et al. 2014). Libraries were prepared using the NexteraXT Illumina sequencing platform.

Publication Title

Transcriptional Profiling of Th2 Cells Identifies Pathogenic Features Associated with Asthma.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP144188
RNA Sequencing of Human iPS derived Cardiomyocytes
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

To investigate transcriptional differences between HCM and WT cells Overall design: Examination of HCM vs WT Cells, with 3 replicates of each sample

Publication Title

A Contraction Stress Model of Hypertrophic Cardiomyopathy due to Sarcomere Mutations.

Sample Metadata Fields

Specimen part, Disease, Disease stage, Subject

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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)

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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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