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accession-icon SRP110701
High-Resolution temporal profiling of developing pancreas uncovers the mechanisms of endocrine cell fate determination [MATQ-seq]
  • organism-icon Mus musculus
  • sample-icon 103 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

MATQ-sequencing of single isolated endocrine progenitors (EPs) from the e14.5 and e16.5 mouse pancreas Overall design: MATQ-seq from two litters of Ngn3-eGFP e14.5 and two litters of e16.5 mice, with 15 cells from e14.5 and 12 cells from e16.5. sequenced in two batches of library prep and sequencing

Publication Title

Endocrine lineage biases arise in temporally distinct endocrine progenitors during pancreatic morphogenesis.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon E-MEXP-1310
Transcription profiling of Arabidopsis seedlings treated with NAE(12:0)
  • organism-icon Arabidopsis thaliana
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)

Description

Transcript profiling and gene expression studies in NAE-treated seedlings: Seeds were germinated and seedlings maintained for 4 d in liquid MS media supplemented with 35 uM NAE(12:0)(N-lauroylethanolamine) prior to RNA isolation.

Publication Title

N-Acylethanolamine metabolism interacts with abscisic acid signaling in Arabidopsis thaliana seedlings.

Sample Metadata Fields

Age, Specimen part, Compound

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accession-icon GSE80796
Gene expression profiling of nasal epithelial cells in current and former smokers with and without lung cancer
  • organism-icon Homo sapiens
  • sample-icon 505 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

We previously derived and validated a bronchial epithelial gene expression biomarker to detect lung cancer in current and former smokers. Given that bronchial and nasal epithelium gene expression is similarly altered by cigarette smoke exposure, we sought to determine if cancer-associated gene expression might also be detectable in more readily accessible nasal epithelium. Nasal epithelial brushings were prospectively collected from current and former smokers with pulmonary lesions suspicious for lung cancer in the AEGIS-1 (n=375) and AEGIS-2 (n=130) clinical trials and gene expression profiled using microarrays. Using the 375 AEGIS 1 samples, we identified 535 genes that were differentially expressed in the nasal epithelium of patients who were ultimately diagnosed with lung cancer vs. those with benign disease after one year of follow-up (p<0.001). Using bronchial gene expression data from 299 AEGIS-1 patients (including 157 patients with matched nasal and bronchial expression data), we found significantly concordant cancer-associated gene expression differences between the two airway sites (p<0.001). Differentially expressed genes were enriched for genes associated with the regulation of apoptosis, mitotic cell cycle, and immune system signaling. A nasal lung cancer classifier derived in the AEGIS-1 cohort that combined clinical factors and nasal gene expression had significantly higher AUC (0.80) and sensitivity (0.94) over a clinical-factor only model (p<0.05) in independent samples from the AEGIS-2 cohort (n=130). These results suggest that the airway epithelial field of lung cancer-associated injury in current and former smokers extends to the nose and demonstrates the potential of using nasal gene expression as a non-invasive biomarker for the detection of lung cancer.

Publication Title

Shared Gene Expression Alterations in Nasal and Bronchial Epithelium for Lung Cancer Detection.

Sample Metadata Fields

Sex, Age

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accession-icon GSE32285
Genome-wide analysis of lupus immune complex stimulation and how this response is regulated by C1q
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIllumina HumanRef-8 v3.0 expression beadchip

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Plasmacytoid dendritic cells and C1q differentially regulate inflammatory gene induction by lupus immune complexes.

Sample Metadata Fields

Specimen part, Treatment, Subject

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accession-icon GSE32278
Genome-wide analysis of lupus immune complex stimulation of purified CD14+ monocytes and how this response is regulated by C1q
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIllumina HumanRef-8 v3.0 expression beadchip

Description

The goal of this study was to determine what genes are up- and down-regulated in response to lupus immune complexes in purified CD14+ monocyte stimulations. Our results have shown that novel genes are induced by immune complexes but the response is less robust when using purified monocytes versus total PBMCs

Publication Title

Plasmacytoid dendritic cells and C1q differentially regulate inflammatory gene induction by lupus immune complexes.

Sample Metadata Fields

Specimen part, Treatment, Subject

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accession-icon GSE2457
Control vs Diabetic Penile Tissues
  • organism-icon Rattus norvegicus
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Expression 230A Array (rae230a)

Description

Gene expression analysis in control and diabetic rats. Diabetes-induced erectile dysfunction in rat model of DM. 10 weeks of streptozotocin induced diabetes. F344 Rats.

Publication Title

Microarray analysis reveals novel gene expression changes associated with erectile dysfunction in diabetic rats.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE58722
Checkpoint blockade immunotherapy relies on T-bet but not Eomes to induce effector function in tumor infiltrating CD8+ T cells
  • organism-icon Mus musculus
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Coinhibitory receptor blockade is a promising strategy to boost immunity against a variety of human cancers. However, many patients still do not benefit from this treatment, and responders often experience immune-related toxicities. These issues highlight the need for improved understanding of checkpoint blockade, but the T cell-intrinsic signaling pathways and gene expression profiles engaged during treatment are not well defined, particularly for combination approaches. We utilized a murine model of CD8+ T cell tolerance to address these issues.

Publication Title

Checkpoint blockade immunotherapy relies on T-bet but not Eomes to induce effector function in tumor-infiltrating CD8+ T cells.

Sample Metadata Fields

Specimen part

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accession-icon GSE11906
Quality Control in Microarray Assessment of Gene Expression in Human Airway Epithelium
  • organism-icon Homo sapiens
  • sample-icon 165 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Full Length HuGeneFL Array (hu6800), Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Microarray technology provides a powerful tool for defining gene expression profiles of airway epithelium that lend insight into the pathogenesis of human airway disorders. The focus of this study was to establish rigorous quality control parameters to ensure that microarray assessment of the airway epithelium is not confounded by experimental artifact. Samples (total n=223) of trachea, large and small airway epithelium were collected by fiberoptic bronchoscopy of 144 individuals (42 healthy non-smokers, 49 healthy smokers, 11 symptomatic smokers, 22 smokers with lone emphysema with normal spirometry, and 20 smokers with COPD) were processed and hybridized to Affymetrix HG-U133 2.0 Plus microarrays. The pre- and post-chip quality control (QC) criteria established, included: (1) RNA quality, assessed by RNA Integrity Number (RIN) 7.0 using Agilent 2100 Bioanalyzer software; (2) cRNA transcript integrity, assessed by signal intensity ratio of GAPDH 3' to 5' probe sets 3.0; and (3) the multi-chip normalization scaling factor 10.0

Publication Title

Quality control in microarray assessment of gene expression in human airway epithelium.

Sample Metadata Fields

Sex, Age

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accession-icon GSE20257
Smoking-induced Disarray of the Apical Junctional Complex Gene Expression Architecture in the Human Airway Epithelium
  • organism-icon Homo sapiens
  • sample-icon 118 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Full Length HuGeneFL Array (hu6800), Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The apical junctional complex (AJC), composed of tight junctions and adherens junctions, is essential for maintaining epithelial barrier function. Since cigarette smoking and chronic obstructive pulmonary disease (COPD), the major smoking-induced disease, are both associated with increased lung epithelial permeability, we hypothesized that smoking alters the transcriptional program regulating AJC integrity in the small airway epithelium (SAE), the primary site of pathological changes in COPD. Transcriptome analysis revealed a global down-regulation of physiological AJC gene expression in the SAE of healthy smokers (n=53) compared to healthy nonsmokers (n=59), an observation associated with changes in molecular pathways regulating epithelial differentiation such as PTEN signaling and accompanied by induction of cancer-related AJC genes. Genome-wide co-expression analysis identified a smoking-sensitive AJC transcriptional network. The overall expression of AJC-associated genes was further decreased in COPD smokers (n=23). Exposure of human airway epithelial cells to cigarette smoke extract in vitro resulted in down-regulation of several AJC-related genes, accompanied by decreased transepithelial resistance. Thus, cigarette smoking alters the AJC gene expression architecture in the human airway epithelium, providing a molecular basis for the dysregulation of airway epithelial barrier function during the development of smoking-induced lung disease.

Publication Title

Cigarette smoking reprograms apical junctional complex molecular architecture in the human airway epithelium in vivo.

Sample Metadata Fields

Sex, Age

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accession-icon GSE13933
Trachea Epithelium as a Canary for Cigarette Smoking-induced Biologic Phenotype of Small Airway Epithelium
  • organism-icon Homo sapiens
  • sample-icon 85 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The initial site of smoking-induced lung disease is the small airway epithelium, which is difficult and time consuming to sample by fiberoptic bronchoscopy. We developed a rapid, office-based procedure to obtain trachea epithelium without conscious sedation from healthy nonsmokers (n=26) and healthy smokers (n=19, 27 15 pack-yr). Gene expression differences [fold-change >1.5, p< 0.01, Benjamini-Hochberg correction] were assessed with Affymetrix microarrays. 1,057 probe sets were differentially expressed in healthy smokers vs nonsmokers, representing >500 genes. Trachea gene expression was compared to an independent group of small airway epithelial samples (n=23 healthy nonsmokers, n=19 healthy smokers, 25 12 pack-yr). The trachea epithelium is more sensitive to smoking, responding with 3-fold more differentially-expressed genes than small airway epithelium. The trachea transcriptome paralleled the small airway epithelium, with 156 of 167 (93%) genes that are significantly up- and down-regulated by smoking in the small airway epithelium showing similar direction and magnitude of response to smoking in the trachea. Trachea epithelium can be obtained without conscious sedation, representing a less invasive surrogate canary for smoking-induced changes in the small airway epithelium. This should prove useful in epidemiologic studies correlating gene expression with clinical outcome in assessing smoking-induced lung disease.

Publication Title

Trachea epithelium as a "canary" for cigarette smoking-induced biologic phenotype of the small airway epithelium.

Sample Metadata Fields

Sex, Age

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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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