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accession-icon SRP133658
RNA sequencing of LNZ308 glioma cells treated under differential conditions including monotherapies, dual therapy and synergistic triple regimen employing ?-irradiation, temozolomide and oncolytic measles virus.
  • organism-icon Homo sapiens
  • sample-icon 44 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

The synergistic regimen CT-VT-RT triggers proinflammatory antiviral signalling with activation of apoptotic cascades resulting in tumor cell death. Overall design: The experiment was designed to elicit individual treatment effects using monotherapies to understand the combinatorial sequential effect of dual and triple regimen using appropriate controls.

Publication Title

Measles Virus-Based Treatments Trigger a Pro-inflammatory Cascade and a Distinctive Immunopeptidome in Glioblastoma.

Sample Metadata Fields

Specimen part, Cell line, Treatment, Subject, Time

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accession-icon SRP092280
Transcriptome analysis of tumor-specific CD8 T cells in murine solid tumors
  • organism-icon Mus musculus
  • sample-icon 36 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

RNAseq analysis of CD8 T cells becoming dysfunctional in progressing tumors. The overall goal of this study was to elucidate the molecular program that mediates functional unresponsiveness in tumor-specific CD8 T cells. In comparison, we also investigated CD8 T cells differentiating to functional effector and memory T cells during an acute listeria infection. Overall design: T cells were sorted by flow cytometry and RNA-seq was performed.

Publication Title

Chromatin states define tumour-specific T cell dysfunction and reprogramming.

Sample Metadata Fields

Disease, Disease stage, Cell line, Subject

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accession-icon SRP163643
Inherent DNA binding specificities of the HIF-1a and HIF-2a transcription factors in chromatin (RNA-seq)
  • organism-icon Homo sapiens
  • sample-icon 24 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 4000

Description

Hypoxia inducible factor (HIF) is the major transcriptional regulator of cellular responses to hypoxia. The two principal HIF-a isoforms, HIF-1a and HIF-2a, are progressively stabilized in response to hypoxia and form heterodimers with HIF-1b to activate a broad range of transcriptional responses. Here we report on the pan-genomic distribution of isoform-specific HIF binding in response to hypoxia of varying severity and duration, and in response to genetic ablation of each HIF-a isoform. Our findings reveal that, despite an identical consensus recognition sequence in DNA, each HIF heterodimer loads progressively at a distinct repertoire of cell-type specific sites across the genome, with little evidence of redistribution under any of the conditions examined. Marked biases towards promoter proximal binding of HIF-1 and promoter distant binding of HIF-2 were observed under all conditions and were consistent in multiple cell type. The findings imply that each HIF isoform has an inherent property that determines its binding distribution across the genome, which might be exploited to therapeutically target the specific transcriptional output of each isoform independently. Overall design: RNA_seq analysis of hypoxic gene regulation in HKC8 and HepG2 cell lines and in RCC4 cell lines stably transfected with wtVHL

Publication Title

Hypoxia drives glucose transporter 3 expression through hypoxia-inducible transcription factor (HIF)-mediated induction of the long noncoding RNA NICI.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon GSE81189
Expression data from Tbet+ and Tbet- Memory B cells
  • organism-icon Mus musculus
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 2.0 ST Array (mogene20st)

Description

The role of antibody and B cells in preventing infection is established. In contrast, the role of B cell responses in containing chronic infections remains poorly understood. IgG2a (IgG1 in humans) can prevent acute infections and T-bet promotes IgG2a isotype switching. However, whether IgG2a and B cell-expressed T-bet influence the host-pathogen balance during persisting infections is unclear. Here we demonstrate that B cell specific loss of T-bet prevents control of persisting viral infection. T-bet in B cells not only controlled IgG2a production, but also mucosal localization, proliferation, glycosylation, and a broad transcriptional program. T-bet controlled a broad antiviral program in addition to IgG2a since T-bet in B cells was important even in the presence of virus-specific IgG2a. Our data supports a model in which T-bet is a universal controller of antiviral immunity across multiple immune lineages.

Publication Title

Cutting Edge: B Cell-Intrinsic T-bet Expression Is Required To Control Chronic Viral Infection.

Sample Metadata Fields

Specimen part

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accession-icon GSE52348
Retinas from the Pex1-G844D mouse model of Zellweger spectrum disorder
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430A 2.0 Array (mouse430a2)

Description

Gene expression analysis of retinas from a mouse model of the mild form of Zellweger spectrum disorder (ZSD). Mice homozygous for the hypomorphic Pex1-G844D allele, the murine ortholog of the human PEX1-G843D mutation found in a subset of patients with autosomal recessive ZSD, develop phenotypes found in humans with a milder form of ZSD, including retinal degeneration and vision loss. Similar to humans, mice heterozygous for the hypomorphic Pex1-G844D allele do not display age-related retinal abnormalities.

Publication Title

The Pex1-G844D mouse: a model for mild human Zellweger spectrum disorder.

Sample Metadata Fields

Sex, Age, Specimen part

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accession-icon GSE33425
Human MAIT and CD8++ cell development
  • organism-icon Homo sapiens
  • sample-icon 17 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

Human MAIT and CD8αα cells develop from a pool of type-17 precommitted CD8+ T cells.

Sample Metadata Fields

Specimen part, Disease, Disease stage

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accession-icon GSE72752
CD39 expression identifies terminally exhausted CD8+ T cells
  • organism-icon Homo sapiens
  • sample-icon 15 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

Exhausted T cells express multiple co-inhibitory molecules that impair their function and limit immunity to chronic viral infection. Defining novel markers of exhaustion is important both for identifying and potentially reversing T cell exhaustion. Herein, we show that the ectonucleotidse CD39 is a marker of exhausted CD8+ T cells. CD8+ T cells specific for HCV or HIV express high levels of CD39, but those specific for EBV and CMV do not. CD39 expressed by CD8+ T cells in chronic infection is enzymatically active, co-expressed with PD-1, marks cells with a transcriptional signature of T cell exhaustion and correlates with viral load in HIV and HCV. In the mouse model of chronic Lymphocytic Choriomeningitis Virus infection, virus-specific CD8+ T cells contain a population of CD39high CD8+ T cells that is absent in functional memory cells elicited by acute infection. This CD39high CD8+ T cell population is enriched for cells with the phenotypic and functional profile of terminal exhaustion. These findings provide a new marker of T cell exhaustion, and implicate the purinergic pathway in the regulation of T cell exhaustion.

Publication Title

CD39 Expression Identifies Terminally Exhausted CD8+ T Cells.

Sample Metadata Fields

Specimen part, Subject

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accession-icon GSE33424
Expression data from human cord blood CD161++/CD161+/CD161- CD8+ T cell subsets
  • organism-icon Homo sapiens
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We used microarray to compare gene expression between CD161++/CD161+/CD161-CD8+ T cells from human cord blood.

Publication Title

Human MAIT and CD8αα cells develop from a pool of type-17 precommitted CD8+ T cells.

Sample Metadata Fields

Specimen part

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accession-icon GSE33374
Expression data from healthy human CD161++CD8aa and CD161++CD8ab T cells
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We used microarrays to compare gene expression between healthy human CD161++CD8aa and CD161++CD8ab T cells.

Publication Title

Human MAIT and CD8αα cells develop from a pool of type-17 precommitted CD8+ T cells.

Sample Metadata Fields

Specimen part, Disease, Disease stage

View Samples
accession-icon GSE14328
Three non-invasive protein biomarkers for solid-organ transplant rejection found through integrative genomics
  • organism-icon Homo sapiens
  • sample-icon 36 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We integrated three transplant rejection microarray studies examining gene expression in samples from pediatric renal, adult renal, and adult heart transplants. We performed one study ourselves and retrieved two others from the NCBI Gene Expression Omnibus (GEO)(GSE4470 and GSE1563). We identified 45 genes that were upregulated in common in acute rejection. Half were involved in one immune-related pathway. Among ten proteins we tested by serum ELISA, three successfully distinguished acute rejection from stable transplants. These were CXCL9, PECAM1, and CD44, with areas under the receiver operating characteristic curves of 0.844, 0.802, and 0.738, respectively. Immunohistochemistry showed that the PECAM1 protein was increased in acute rejection in renal, liver and heart transplants versus normal tissues. Our results show that integrating publicly-available gene expression data sets is a fast, powerful, and cost-effective way to identify serum-detectable diagnostic biomarkers.

Publication Title

Integrative urinary peptidomics in renal transplantation identifies biomarkers for acute rejection.

Sample Metadata Fields

No sample metadata fields

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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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