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accession-icon GSE10970
Efficient Array-based Identification of Novel Cardiac Genes through Differentiation of Mouse ESCs
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Cardiac disease accounts for the largest proportion of adult mortality and morbidity in the industrialized world. However, progress toward improved clinical treatments is hampered by an incomplete understanding of the genetic programs controlling early cardiogenesis. To better understand this process, we set out to identify genes whose expression is enriched within early cardiac fated populations, obtaining the transcriptional signatures of mouse embryonic stem cells (mESCs) differentiating along a cardiac path.

Publication Title

Efficient array-based identification of novel cardiac genes through differentiation of mouse ESCs.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE33232
Cancer Outlier Gene Profile Sets Elucidate Pathways and Patient-Specific Targets in Head and Neck Squamous Cell Carcinoma
  • organism-icon Homo sapiens
  • sample-icon 126 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Toward Signaling-Driven Biomarkers Immune to Normal Tissue Contamination.

Sample Metadata Fields

Disease, Disease stage

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accession-icon GSE64664
Human basophil expression profiles
  • organism-icon Homo sapiens
  • sample-icon 33 Downloadable Samples
  • Technology Badge IconIllumina HumanRef-8 v3.0 expression beadchip

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Expression profiling of human basophils: modulation by cytokines and secretagogues.

Sample Metadata Fields

Specimen part, Treatment

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accession-icon GSE80667
CoGAPS matrix factorization algorithm identifies AP-2alpha as a feedback mechanism from therapeutic inhibition of the EGFR network
  • organism-icon Homo sapiens
  • sample-icon 92 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Patients with oncogene driven tumors are currently treated with targeted therapeutics such as epidermal growth factor receptor (EGFR) inhibitors. The inhibited oncogenic pathway often interacts with other signaling pathways and alters predicted therapeutic response. Genomic data from The Cancer Genome Atlas (TCGA) demonstrates pervasive molecular alterations to EGFR, MAPK, and PI3K signaling in previously untreated tumors. Therefore, this study uses bioinformatics algorithms to infer the complex pathway interactions that result from EGFR inhibitor use in cancer cells that contain these these common EGFR network genetic alterations. To do this, we modified the HaCaT keratinocyte cell line model of premalignancy to simulate cancer cells with constitutive activation of EGFR, HRAS, and PI3K in a controlled genetic background. We then measured gene expression after treating modified HaCaT cells with three EGFR targeted agents (gefitinib, afatinib, and cetuximab) for 24 hours.

Publication Title

CoGAPS matrix factorization algorithm identifies transcriptional changes in AP-2alpha target genes in feedback from therapeutic inhibition of the EGFR network.

Sample Metadata Fields

Cell line, Treatment

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accession-icon GSE33650
Gene Expression differences in Hepatic Parenchyma and Portal Tracts in Hepatitis C Virus Infected Subjects with High and Low Fibrosis
  • organism-icon Homo sapiens
  • sample-icon 65 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Background & Aims: Chronic hepatitis C virus (HCV) infection is complicated by hepatic fibrosis. Hypothesizing that fibrogenic signals may originate in cells susceptible to HCV infection, gene expression of hepatocytes was analyzed from persons with chronic HCV at different stages of liver fibrosis. Methods: HCV-infected subjects with significant liver fibrosis (Ishak fibrosis 3) were matched for age, race, and gender to subjects with minimal fibrosis (Ishak fibrosis 0-1). RNA from portal tracts and hepatic parenchyma was isolated from biopsies by laser capture and transcriptome profiling was performed using hybridization arrays. Results: Portal tracts from both groups were enriched for immune related genes when compared to hepatocytes but high fibrosis subjects showed a loss of this enrichment. Hepatocytes from persons with high fibrosis were depleted for genes involved in small molecule and drug metabolism, especially butyrylcholinesterase (BCHE), a gene involved in the metabolism of drugs of abuse. Differential expression of BCHE was validated in the same tissues using qPCR. Cross-sectional and longitudinal testing in an expanded cohort of HCV-infected individuals showed that serum BCHE activity decreased in advance of progression to fibrosis. Conclusion: Chronic HCV infection is associated with a loss of hepatocyte metabolic function, decreased enrichment of immune-related genes in portal tracts and downregulation of BCHE in hepatocytes. Our results indicate that BCHE may be involved in the progression of fibrosis during HCV infection among injection drug users and may serve as a useful marker for fibrosis progression.

Publication Title

Laser captured hepatocytes show association of butyrylcholinesterase gene loss and fibrosis progression in hepatitis C-infected drug users.

Sample Metadata Fields

Sex, Age, Race

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accession-icon GSE33205
Cancer Outlier Gene Profile Sets Elucidate Pathways and Patient-Specific Targets in Head and Neck Squamous Cell Carcinoma [Affymetrix HuEx1.0]
  • organism-icon Homo sapiens
  • sample-icon 69 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)

Description

This study integrated Affymetrix SNPchip data for CNV estimation, Affymetrix HuEx1.0 data for gene expression estimation, and Illumina HumanMethylation27k BeadChip data for promoter methylation to estimate pathway activity

Publication Title

Activation of the NOTCH pathway in head and neck cancer.

Sample Metadata Fields

Disease, Disease stage

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accession-icon GSE32975
Gene expression signatures modulated by epidermal growth factor receptor activation and their relationship to cetuximab resistance in head and neck squamous cell carcinoma
  • organism-icon Homo sapiens
  • sample-icon 58 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Aberrant activation of signaling pathways controlled in normal epithelial cells by the epidermal growth factor receptor (EGFR) has been linked to cetuximab (a monoclonal antibody against EGFR) resistance in head and neck squamous cell carcinoma (HNSCC). To infer relevant and specific pathway activation downstream of EGFR from gene expression in HNSCC, we generated gene expression signatures using immortalized keratinocytes (HaCaT) subjected to either ligand stimulation or pharmacological inhibition of the signaling intermediaries PI-3-Kinase and MEK or transfected with EGFR, RELA/p65, or HRASVal12. The gene expression patterns that distinguished the various HaCaT variants and conditions were inferred using the Markov chain Monte Carlo (MCMC) matrix factorization algorithm Coordinated Gene Activity in Pattern Sets (CoGAPS). This approach inferred gene expression signatures with greater relevance to cell signaling pathway activation than the expression signatures inferred with standard linear models. Furthermore, the pathway signature generated using HaCaT-HRASVal12 further associated with the cetuximab treatment response in isogenic cetuximab-sensitive (UMSCC1) and -resistant (1CC8) cell lines. Our data suggest that the CoGAPS algorithm can generate gene expression signatures that are pertinent to downstream effects of receptor signaling pathway activation and potentially be useful in modeling resistance mechanisms to targeted therapies.

Publication Title

Gene expression signatures modulated by epidermal growth factor receptor activation and their relationship to cetuximab resistance in head and neck squamous cell carcinoma.

Sample Metadata Fields

Cell line, Treatment

View Samples
accession-icon GSE12711
Differential gene expression profiles are dependent upon method of peripheral blood RNA isolation
  • organism-icon Homo sapiens
  • sample-icon 45 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

Differential gene expression profiles are dependent upon method of peripheral blood collection and RNA isolation.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE15240
Gene expression in laboratory models and primary tumors in Small Cell Lung Cancer
  • organism-icon Homo sapiens
  • sample-icon 45 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Gene expression was measured on the Affymetrix platform in primary xenografts, xenograft-derived cell lines, secondary xenografts, normal lung, and primary tumors obtained from chemotherapy naive Small Cell Lung Cancer (SCLC). The SCLC primary xenografts were serially propagated in vivo in immunodeficient mice. Cell lines were derived from each xenograft and grown for 6 months using conventional tissue culture conditions. Secondary xenografts were obtained from cell cultures by re-implantation in immunodeficient mice. Such SCLC laboratory models were analyzed along with conventional SCLC cell lines and the derivative secondary xenografts, with normal lung and primary tumors, to assess irreversible gene expression changes induced by culturing conditions.

Publication Title

A primary xenograft model of small-cell lung cancer reveals irreversible changes in gene expression imposed by culture in vitro.

Sample Metadata Fields

Disease, Disease stage, Cell line

View Samples
accession-icon GSE53355
Preserving biological heterogeneity with personalized genomics batch correction
  • organism-icon Homo sapiens
  • sample-icon 39 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Motivation: Sample source, procurement process, and other technical variations introduce batch effects into genomics data. Algorithms to remove these artifacts enhance differences between known biological covariates, but also carry potential concern of removing intra-group biological heterogeneity and thus any personalized genomic signatures. As a result, accurate identification of novel subtypes from batch corrected genomics data is challenging using standard algorithms designed to remove batch effects for class comparison analyses. Nor can batch effects be corrected reliably in future applications of genomics-based clinical tests, in which the biological groups are by definition unknown a priori.

Publication Title

Preserving biological heterogeneity with a permuted surrogate variable analysis for genomics batch correction.

Sample Metadata Fields

Sex, Specimen part, Disease, Disease stage, Race

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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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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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