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accession-icon SRP056593
Global transcriptome analysis of macrophages during Helicobacter pylori infection
  • organism-icon Mus musculus
  • sample-icon 334 Downloadable Samples
  • Technology Badge IconIlluminaGenomeAnalyzerII

Description

Based on preliminary data demonstrating that macrophages are critical regulators of Helicobacter pylori colonization and gastric pathology in mice, we sought to investigate how macrophages may serve as bacterial reservoirs of intracellular H. pylori. Overall design: BMDM were isolated from WT and PPARg-/- mice and cultured with M-CSF for 7 days to promote macrophage differentiation. Fully differentiation macrophages were challenged with H. pylori strains SS1 at an MOI of 10 for 15 minutes. Extracellular bacteria was then eliminated by gentamycin treatment. Cells were collected at 0, 60, 120, 240, 360 and 720 minutes post gentamycin treatment to ascertain whole transcriptome differential gene expression during infection.

Publication Title

Identification of new regulatory genes through expression pattern analysis of a global RNA-seq dataset from a Helicobacter pylori co-culture system.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE21013
Effect of dietary abscisic acid (ABA) supplementation on spleen transcriptome in LPS-challenged mice
  • organism-icon Mus musculus
  • sample-icon 28 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

BACKGROUND: Dietary ABA-supplementation modulates immune and inflammatory responses in mouse models of chronic and infectious disease. However, the underlying mechanisms by which ABA elicits its immune modulatory effects are not well understood. This project used a systems approach in combination with functional and in vivo studies to investigate the target gene pathways modulated by ABA in the context of an inflammatory LPS challenge.

Publication Title

Abscisic acid regulates inflammation via ligand-binding domain-independent activation of peroxisome proliferator-activated receptor gamma.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP014184
Modulation of mucosal immune responses to Clostridium difficile by peroxisome proliferator-activated receptor ? and microRNA-146b
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer II

Description

BACKGROUND: miRNA have been shown to play an important role during immune-mediated diseases such as inflammatory bowel disease. The aim of this study was to assess differential expression of miRNA between uninfected and infected mice with Clostridium difficile strain VPI 10463 RESULTS: MicroRNA (miRNA)-sequencing analysis indicated that miR-146b, miR-1940, and miR-1298 were significantly overexpressed in colons of C. difficile-infected mice Overall design: Colon of uninfected and C.difficile-infected C57BL6/J WT mice were sampled at day 4 post-infection with Clostridium difficile VPI 10463. The infection dose was 107 cfu/mouse.

Publication Title

Modeling the role of peroxisome proliferator-activated receptor γ and microRNA-146 in mucosal immune responses to Clostridium difficile.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon GSE54582
Transcriptomic analysis of mammary tumors from MMTV-ErbB2 transgenic mice
  • organism-icon Mus musculus
  • sample-icon 222 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

The tyrosine kinase ErbB2 positive breast tumors have more aggressive tumor growth, poorer clinical outcome, and more resistance to radiotherapy, chemotherapy and hormone therapy. A humanized anti-ErbB2 monoclonal antibody Herceptin and a small molecules inhibitor Lapatinib were developed and approved by FDA to treat patients with ErbB2 amplification and overexpression. Unfortunately, most ErbB2+ breast cancers do not respond to Herceptin and Lapatinib, and the majority of responders become resistant within 12 months of initial therapy (defined as secondary drug resistance). Such differences in response to Lapatinib treatment is contributed by substantial heterogeneity within ErbB2+ breast cancers. To address this possibility, we carried out transcriptomic analysis of mammary tumors from genetically diverse MMTV-ErbB2 mice. This will help us to have a better understanding of the heterogeneous response to ErbB2 targeted therapy and permit us to design better and more individualized (personalized) treatment strategies for human ErbB2 positive breast cancer.

Publication Title

Unraveling heterogeneous susceptibility and the evolution of breast cancer using a systems biology approach.

Sample Metadata Fields

Specimen part

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accession-icon SRP043525
Extensive crosstalk between lncRNAs and mRNAs in mouse stem cells
  • organism-icon Mus musculus
  • sample-icon 25 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

To determine the temporal variation of mRNA levels, we collected and sequenced poly-adenylated RNA from all cell extracts, cytoplasmic and nuclear fractions of a conditional Dicer mutant [DTCM23/49 XY (Nesterova et al. 2008)] mouse Embryonic Stem Cells before induction of Dicer excision (day 0) and at days 4, 8, 10 and 12 following Dicer loss of function. coverage. Overall design: RNA from whole cell extracts was collected at days 0, 4, 8, 10 and 12 following loss of Dicer function and from the cytoplasmic and nuclear fractions of cell at day 0 and 12. Three biological replicates were obtained for all samples. Poly-adenylated directional 100 base paired-end sequencing libraries were prepared for all extracts and sequenced by BGI solutions (Hong Kong).

Publication Title

Extensive microRNA-mediated crosstalk between lncRNAs and mRNAs in mouse embryonic stem cells.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE179445
Integrative multi-omics approach for mechanism of humidifier disinfectant-associated lung injury [human]
  • organism-icon Homo sapiens
  • sample-icon 2 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 2.0 ST Array (hugene20st)

Description

Inhalation of toxic chemicals, including recent e-cigarettes, often cause life-threatening lung injury. Although exposure to polyhexamethylene guanidine (PHMG)-containing humidifier disinfectant (HD) has been identified as a cause of fatal lung injury, the mechanism underlying HD-associated lung injury (HDLI) is unknown. The present study evaluated global changes in gene expression in lung tissues from patients with PHMG-induced HDLI, and compared gene expression changes in PHMG-induced rat lung tissues. Significantly different expressions in lung tissues between patients with HDLI and unaffected controls were observed. Furthermore, several fibrosis-associated overlapping genes (such as MMP2 and COL1A2) shared between humans with HDLI and rats exposed to PHMG were identified. Interactome network analysis predicted different pathways between children and adults with HDLI: the TGFβ/SMAD signaling pathway was central in adults, whereas other pathways, including integrin signaling, were associated with HDLI in children. Further interactome network analysis revealed that Rap1 and CCKR signaling pathways were significantly enriched in HDLI compared with idiopathic pulmonary fibrosis as well as their recapitulation in the lung tissues of rats exposed to PHMG. Our results suggest that MMP2-mediated different mechanisms between children and adults may be associated with PHMG-induced HDLI development, and Rap1 and CCKR pathways appear to be crucial.

Publication Title

Integrative multi-omics approach for mechanism of humidifier disinfectant-associated lung injury.

Sample Metadata Fields

Age, Specimen part

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accession-icon GSE13861
Gene expression signature-based novel prognostic risk score in gastric cancer
  • organism-icon Homo sapiens
  • sample-icon 90 Downloadable Samples
  • Technology Badge IconIllumina HumanWG-6 v3.0 expression beadchip

Description

Despite continual efforts to establish pre-operative prognostic model of gastric cancer by using clinical and pathological parameters, a staging system that reliably separates patients with early and advanced gastric cancer into homogeneous groups with respect to prognosis does not exist. With use of microarray and quantitative RT-PCR technologies, we exploited series of experiments in combination with complementary data analyses on tumor specimens from 161 gastric cancer patients. Various statistical analyses were applied to gene expression data to uncover subgroups of gastric cancer, to identify potential biomarkers associated with prognosis, and to construct molecular predictor of risk from identified prognostic biomarkers.Two subgroups of gastric cancer with strong association with prognosis were uncovered. The robustness of prognostic gene expression signature was validated in independent patient cohort with use of support vector machines prediction model. For easy translation of our finding to clinics, we develop scoring system based on expression of six genes that can predict the likelihood of recurrence after curative resection of tumors. In multivariate analysis, our novel risk score was an independent predictor of recurrence (P=0.004) in cohort of 96 patients, and its robustness was validated in two other independent cohorts. We identified novel prognostic subgroups of gastric cancer that are distinctive in gene expression patterns. Six-gene signature and risk score derived from them has been validated for predicting the likelihood of survival at diagnosis.

Publication Title

Gene expression signature-based prognostic risk score in gastric cancer.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE77545
Expression data from small intestinal eosinophils and dendritic cells
  • organism-icon Mus musculus
  • sample-icon 2 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Expression 430A Array (moe430a)

Description

Under steady-state conditions, eosinophils are abundantly found in the small intestinal lamina propria, but their physiological function is largely unexplored. We performed a global gene expression analysis to examine which genes are highly expressed by small intestinal eosinophils (CD11b+CD11c(int)MHCII-SiglecF+) compared with dendritic cells (CD11c+MHCII+).

Publication Title

Small intestinal eosinophils regulate Th17 cells by producing IL-1 receptor antagonist.

Sample Metadata Fields

Age, Specimen part

View Samples
accession-icon GSE4107
Expression profiling in early onset colorectal cancer
  • organism-icon Homo sapiens
  • sample-icon 21 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Background: Causative genes for autosomal dominantly inherited familial adenomatous polyposis (FAP) and hereditary non-polyposis colorectal cancer (HNPCC) have been well characterized. There is, however, another 10-15 % early onset colorectal cancer (CRC) whose genetic components are currently unknown. In this study, we used DNA chip technology to systematically search for genes differentially expressed in early onset CRC.

Publication Title

A susceptibility gene set for early onset colorectal cancer that integrates diverse signaling pathways: implication for tumorigenesis.

Sample Metadata Fields

Sex, Age, Specimen part

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accession-icon GSE36118
Recovery of phenotypes obtained by adaptive evolution through inverse metabolic engineering
  • organism-icon Saccharomyces cerevisiae
  • sample-icon 14 Downloadable Samples
  • Technology Badge Icon Affymetrix Yeast Genome 2.0 Array (yeast2)

Description

Reconstructed mutants of yeast by inverse metabolic engineering were characterized by fermentation physiology and tools from systems biology.

Publication Title

Recovery of phenotypes obtained by adaptive evolution through inverse metabolic engineering.

Sample Metadata Fields

Time

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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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