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accession-icon GSE30219
"Off-context" gene expression in lung cancer identifies a group of metastatic-prone tumors
  • organism-icon Homo sapiens
  • sample-icon 299 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

An unexplored consequence of epigenetic alterations associated with cancer is the ectopic expression of tissue-restricted genes. Here, a new strategy was developed to decipher genome-wide expression data in search for these off-context gene activations, which consisted first, in identifying a large number of tissue-specific genes normally epigenetically silenced in most somatic cells and second, in using them as cancer biomarkers on an on/off basis. Applying this concept to analyze whole-genome transcriptome data in lung cancer, we discovered a specific group of 26 genes whose expression was a strong and independent predictor of poor prognosis in our cohort of 293 lung tumours, as well as in two independent external populations. In addition, these 26 classifying genes enabled us to isolate a homogenous group of metastatic-prone highly aggressive tumours, whose characteristic gene expression profile revealed a high proliferative potential combined to a significant decrease in immune and signaling functions. This work illustrates a new approach for a personalized management of cancer, with applications to any cancer type.

Publication Title

Ectopic activation of germline and placental genes identifies aggressive metastasis-prone lung cancers.

Sample Metadata Fields

Sex, Specimen part

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accession-icon GSE87546
Analysis of gene expression in HIV transgenic mice (TG26) with lymphoma in comparison to asymptomatic TG26 mice, and background control (FVBN).Tg26 carries a pNL4-3 HIV-1 provirus lacking part of the gag-pol region, rendering the virus non-infectious.
  • organism-icon Mus musculus
  • sample-icon 30 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

About 15% of the TG26 mice develop lymphoma. HIV protein expression is observed, particularly the protein p17/Matrix. Total cellular RNA from spleen and lymph nodes from 3 groups of animals: FVB/N controls (n=3), Tg26 asymptomatic (n=6), and Tg26 with lymphoma (n=6). Results provide insights into the gene expression program in animals with lymphoma.

Publication Title

Expression of HIV-1 matrix protein p17 and association with B-cell lymphoma in HIV-1 transgenic mice.

Sample Metadata Fields

Specimen part, Disease

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accession-icon SRP102949
RNA-Seq of ILC2p WT
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

We have generated RNA-seq of ILC2 progenitors form WT bone marrow mice. Overall design: Sorted ILC2p from 8 week-old mice were analysed in RNA-seq. Each replicate is a pool of 8 mice.

Publication Title

Androgen signaling negatively controls group 2 innate lymphoid cells.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon GSE73710
Identification of selective lead compounds for treatment of high-ploidy breast cancer
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

Increased ploidy is common in tumors but treatments for tumors with excess chromosome sets are not available. Here, we characterize high-ploidy breast cancers and identify potential anticancer compounds selective for the high-ploidy state. Among 354 human breast cancers, 10% have mean chromosome copy number exceeding 3, and this is most common in triple negative and HER2-positive types. Women with high-ploidy breast cancers have higher risk of recurrence and death in two patient cohorts, demonstrating that it represents an important group for improved treatment. Because high-ploidy cancers are aneuploid, rather than triploid or tetraploid, we devised a two-step screen to identify selective compounds. The screen was designed to assure both external validity on diverse karyotypic backgrounds and specificity for high-ploidy cell types. This screen identified novel therapies specific to high-ploidy cells. First, we discovered 8-azaguanine, an antimetabolite that is activated by hypoxanthine phosphoribosyltransferase (HPRT), suggesting an elevated gene-dosage of HPRT in high-ploidy tumors can control sensitivity to this drug. Second, we discovered a novel compound, 2,3-Diphenylbenzo[g]quinoxaline-5,10-dione (DPBQ). DPBQ activates p53 and triggers apoptosis in a polyploid-specific manner, but does not inhibit topoisomerase or bind DNA. Mechanistic analysis demonstrates that DPBQ elicits a hypoxia gene signature and its effect is replicated, in part, by enhancing oxidative stress. Structure-function analysis defines the core benzo[g]quinoxaline-5,10 dione as being necessary for the polyploid-specific effects of DPBQ. We conclude that polyploid breast cancers represent a high-risk subgroup and that DPBQ provides a functional core to develop polyploid-selective therapy.

Publication Title

Identification of Selective Lead Compounds for Treatment of High-Ploidy Breast Cancer.

Sample Metadata Fields

Cell line

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accession-icon GSE59422
Effect of Hypertension of Dendritic Cell Gene Expression
  • organism-icon Mus musculus
  • sample-icon 28 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Oxidative injury and inflammation have been implicated in the genesis of hypertension but the mechanisms involved are not fully understood. We describe a new pathway in which angiotensin II promotes dendritic cell (DC) activation of T cells and ultimately hypertension. NADPH oxidase-dependent superoxide production is increased 5-fold in DCs isolated from hypertensive mice as compared to sham-treated mice. This is associated with DC accumulation of protein-isoketal adducts and production of IL-6, IL-1 and IL-23. DCs from hypertensive mice but not sham mice promote survival and proliferation of CD8+ T cells in culture. Chemically diverse isoketal scavengers not only prevent activation and immunogenicity of DCs, but also attenuate angiotensin II-induced hypertension. Moreover, adaptive transfer of DCs from hypertensive mice prime development of hypertension in response to a subpressor dose of angiotensin II. Exposure of DCs to tert butyl hypdroperoxide promoted isoketal formation, DC stimulation of CD8+ T cell proliferation and primed hypertension in response to low dose angiotensin II. Serum isoprostanes, precursors to isoketals, were found to be elevated in humans with treated hypertension and were markedly elevated in patients with resistant hypertension. These studies show that angiotensin II-induced hypertension activates DCs, in large part by causing superoxide production and formation of isoketals. They define a new mechanism of hypertension and identify a potential new therapeutic approach for this disease.

Publication Title

DC isoketal-modified proteins activate T cells and promote hypertension.

Sample Metadata Fields

Age, Specimen part

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accession-icon SRP076671
Transcriptome analysis of mouse IgG1 memory B cell subsets
  • organism-icon Mus musculus
  • sample-icon 20 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

IgE plays an essential role in the pathogenesis of allergies and its production is strongly regulated. A transient IgE germinal center phase and lack of IgE memory cells limit the generation of pathogenic IgE, but this can be overcome by sequential switching of IgG1 cells to IgE. We investigated which population of IgG1 cells can give rise to IgE-producing cells in memory responses. We identified three populations of IgG1 memory B cells (DP:CD73+CD80+, SP:CD73-CD80+, DN:CD73-CD80-) that generate IgE plasma cells of high or low affinity, but none gives rise to IgE germinal center cells or IgE memory cells. The two memory IgG1 populations differ however in their ability to differentiate into IgG1 plasma cells and germinal center cells, and to expand the IgG1 memory B cell pool. To explore the molecular mechanisms that may explain the distinct functions of IgG1 memory B cell subsets we compared their expression by transcriptome analysis using next generation sequencing. Overall design: mRNA profiles of quadruplicates of double positive (DP:CD73+CD80+), single positive (SP:CD73-CD80+), double negative (DN:CD73-CD80-) IgG1 memory B cells along with IgG1 germinal center (GC) cells and naïve B cells were generated using Illumina high throughput sequencing.

Publication Title

IgG1 memory B cells keep the memory of IgE responses.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon GSE49033
Expression data from IgE+ and IgG1+ B lymphocytes in mice infected with Nippostrongylus brasiliensis
  • organism-icon Mus musculus
  • sample-icon 30 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

The mechanisms involved in the maintenance of memory IgE responses are poorly understood, and the role played by germinal center (GC) IgE cells in these memory responses is particularly unclear. IgE B-cell differentiation is characterized by a transient GC phase, a bias towards the plasma cell (PC) fate, and dependence on sequential switching for the production of high-affinity IgE. We show here that IgE GC B cells are unfit to undergo the conventional GC differentiation program due to impaired B-cell receptor function and increased apoptosis. IgE GC cells fail to populate the GC light zone and are unable to contribute to the memory and long-lived PC compartments. Furthermore, we demonstrate that direct and sequential switching are linked to distinct B-cell differentiation fates: direct switching generates IgE GC cells, whereas sequential switching gives rise to IgE plasma cells. We propose a comprehensive model for the generation and memory of IgE responses.

Publication Title

The distinctive germinal center phase of IgE+ B lymphocytes limits their contribution to the classical memory response.

Sample Metadata Fields

Specimen part, Treatment

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accession-icon GSE40488
Treg cells
  • organism-icon Mus musculus
  • sample-icon 8 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

Neuropilin 1 is expressed on thymus-derived natural regulatory T cells, but not mucosa-generated induced Foxp3+ T reg cells.

Sample Metadata Fields

Specimen part

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accession-icon GSE40443
iTreg cells compared to WT Total Treg
  • organism-icon Mus musculus
  • sample-icon 5 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

iTreg cells from Tbmc mLN mice treated with one week of 1% Oral Ova were compared to Total Treg from WT mice.

Publication Title

Neuropilin 1 is expressed on thymus-derived natural regulatory T cells, but not mucosa-generated induced Foxp3+ T reg cells.

Sample Metadata Fields

Specimen part

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accession-icon GSE40441
Comparison of Splenic Nrp1- and Nrp1+ Treg Populations
  • organism-icon Mus musculus
  • sample-icon 3 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

To compare subpopulations of Treg cells in wild type mice based upon Nrp1 Expression, differentiating nTreg and iTreg

Publication Title

Neuropilin 1 is expressed on thymus-derived natural regulatory T cells, but not mucosa-generated induced Foxp3+ T reg cells.

Sample Metadata Fields

Specimen part

View Samples
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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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