refine.bio
  • Search
      • Normalized Compendia
      • RNA-seq Sample Compendia
  • Docs
  • About
  • My Dataset
github link
Showing
of 17 results
Sort by

Filters

Technology

Platform

accession-icon GSE93940
Intravesical BCG induces CD4+ T Cell Expansion in a Clinically Relevant Immune Competent Model of Bladder Cancer
  • organism-icon Rattus norvegicus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Gene 2.0 ST Array (ragene20st)

Description

Intravesical BCG Immunotherapy is the standard of care in treating non-muscle invasive bladder cancer, yet its mechanism of action remains elusive. Both innate and adaptive immune responses have been implicated in BCG activity. While prior research has indirectly demonstrated the importance of T cells and shown a rise in CD4+ T cells in bladder tissue after BCG, T cell subpopulations have not been fully characterized. We investigated the relationship between effector and regulatory T cells in an immune competent, clinically relevant rodent model of bladder cancer. Our data demonstrate that cancer progression in the MNU rat model of bladder cancer is characterized by a decline in the CD8/FoxP3 ratio, consistent with decreased adaptive immunity. By contrast, treatment with intravesical BCG leads to a large, transient rise in the CD4+ T cell population in the urothelium, and is both more effective and immunogenic compared to intravesical chemotherapy. Interestingly, whole transcriptome expression profiling of post-treatment intravesical CD4+ and CD8+ T cells revealed minimal differences in gene expression after BCG treatment. Together, our results suggest that while BCG induces T cell recruitment to the bladder, the T cell phenotype does not markedly change, implying that combining T cell activating agents with BCG might improve clinical activity.

Publication Title

Intravesical BCG Induces CD4<sup>+</sup> T-Cell Expansion in an Immune Competent Model of Bladder Cancer.

Sample Metadata Fields

Specimen part, Treatment

View Samples
accession-icon GSE7772
Comparison between mRNAs of how germ-line clones embryos and WT embryos at 3-5 h AEL
  • organism-icon Drosophila melanogaster
  • sample-icon 3 Downloadable Samples
  • Technology Badge Icon Affymetrix Drosophila Genome Array (drosgenome1)

Description

Mutant embryos lacking maternal and zygotic HOW exhibit defects in mesoderm development. How is an RNA binding protein that regulates the levels of mRNAs by controling RNA metabolism.

Publication Title

Post-transcriptional repression of the Drosophila midkine and pleiotrophin homolog miple by HOW is essential for correct mesoderm spreading.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP094528
Predominant TRUB1-dependent pseudouridylation of mammalian mRNA via a predictable and conserved code
  • organism-icon Homo sapiens
  • sample-icon 39 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

In this accession we provide pseudouridylation measurements upon knockdown and/or overexpression three pseudouridine synthases, two of which (TRUB1 and PUS7) we find to be with predominant activity on mammalian mRNA. Overall design: Examination of pseudouridylation upon genetic perturbation of three pseudouridine synthases

Publication Title

TRUB1 is the predominant pseudouridine synthase acting on mammalian mRNA via a predictable and conserved code.

Sample Metadata Fields

Cell line, Treatment, Subject

View Samples
accession-icon GSE55902
Expression data from Rice leaves
  • organism-icon Oryza sativa
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Rice Genome Array (rice)

Description

Senescence is a developmental process and chlorophyll is an indicator of leaf senescene. In plants cytokinin plays a role in delaying leaf senescence. Chlorophyll degradation is tightly regulated during senescence and cytokinin might interplay in the chrorophyll degradation pathway to regulate leaf greening.

Publication Title

Cytokinin delays dark-induced senescence in rice by maintaining the chlorophyll cycle and photosynthetic complexes.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE100050
IFN-gamma-dependent tissue immune homeostasis is co-opted in the tumor microenvironment
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Homeostatic programs maintain equilibrium between immune protection, and selftolerance. Such mechanisms impact autoimmunity and tumor formation, respectively. How tissue homeostasis is maintained, and impacts tumor surveillance is unknown. Here we identify that mononuclear phagocytes share conserved programming during homeostatic differentiation, and entry into tissue. IFN is necessary and sufficient to induce these transcripts, revealing a key instructive role. Remarkably, homeostatic and IFN-dependent programs enrich across primary human tumors, including melanoma, and stratify metastatic melanoma survival. Single-cell RNA-sequencing reveals enrichment of these modules in monocytes and DCs in human metastatic melanoma. Suppressor-of-cytokine-2 (SOCS2), a highly conserved transcript in this program is induced by IFN, and expressed in mononuclear phagocytes infiltrating primary melanoma. SOCS2 limits DC adaptive anti-tumoral immunity and T cell priming in vivo, indicating a critical regulatory role. Our findings link homeostasis in peripheral tissue to anti-tumoral immunity and escape, revealing coopting of tissue-specific immune development in the tumor microenvironment.

Publication Title

IFNγ-Dependent Tissue-Immune Homeostasis Is Co-opted in the Tumor Microenvironment.

Sample Metadata Fields

Specimen part, Disease, Disease stage

View Samples
accession-icon GSE45291
Inhibition of Lymphotoxin-LIGHT Signaling Reduces the Interferon Signature in Rheumatoid Arthritis Patients
  • organism-icon Homo sapiens
  • sample-icon 519 Downloadable Samples
  • Technology Badge Icon Affymetrix HT HG-U133+ PM Array Plate (hthgu133pluspm)

Description

Whole blood expression was profiled in Rheumatoid Arthiritis and SLE (Systemic LUPUS Erythomatosus) patients.

Publication Title

Lymphotoxin-LIGHT pathway regulates the interferon signature in rheumatoid arthritis.

Sample Metadata Fields

Specimen part, Disease, Time

View Samples
accession-icon GSE104584
Liver from CSF1-Fc- or PBS-treated neonatal rats and rat bone marrow derived macrophages
  • organism-icon Rattus norvegicus
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Gene 2.1 ST Array (ragene21st)

Description

Signalling via the colony stimulating factor 1 receptor (CSF1R) controls the survival, differentiation and proliferation of macrophages which are a source of the somatic growth factor insulin growth factor 1 (IGF1). Treatment of newborn mice with CSF1 has previously been shown to produce an increase in somatic growth rate and we hypothesised that treatment of neonatal low birth weight (LBW) rats with CSF1 would do the same. Growth rates were not affected, yet CSF1 treatment caused an unexpectedly large, but reversible increase in liver size and hepatic fat deposition in both normal and LBW rats. By transcriptional profiling, we have highlighted numerous CSF1-regulated genes known to be involved in lipid droplet formation in the liver and novel candidate genes for further investigation. In contrast to mice and weaner pigs, CSF1 treatment did not increase hepatocyte proliferation in neonatal rats, rather the data were consistent with increased macrophage proliferation instead. This suggests that Kupffer cells promote lipid accumulation in neonates and treatment to ablate CSF1R signalling may reverse lipid accumulation in the liver.

Publication Title

Macrophage colony-stimulating factor increases hepatic macrophage content, liver growth, and lipid accumulation in neonatal rats.

Sample Metadata Fields

Specimen part, Treatment

View Samples
accession-icon SRP170747
Deciphering the 'm6A code' via quantitative profiling of m6A at single-nucleotide resolution [II]
  • organism-icon Mus musculus
  • sample-icon 10 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

N6-methyladenosine (m6A) is the most abundant modification on mRNA, and is implicated in critical roles in development, physiology and disease. A major challenge in the field has been the inability to quantify m6A stoichiometry and the lack of antibody-independent methodologies for interrogating m6A. Here, we develop MASTER-seq for systematic quantitative profiling of m6A at single nucleotide resolution, building on differential cleavage by an RNAse at methylated sites. MASTER-seq permitted validation and de novo discovery of m6A sites, calibration of the performance of antibody based approaches, and quantitative tracking of m6A dynamics in yeast gametogenesis and mammalian differentiation. We discover that m6A stoichiometry is 'hard-coded' in cis via a simple and predictable code. This code accounts for ~50% of the variability in methylation levels and allows accurate prediction of m6A loss/acquisition events across evolution. MASTER-seq will allow quantitative investigation of m6A regulation in diverse cell types and disease states. Overall design: 10 samples were analyzed: EBS WT and Metll3 -/- with two replicates each and ESC WT and Mettld -/- with three replicates

Publication Title

Deciphering the "m<sup>6</sup>A Code" via Antibody-Independent Quantitative Profiling.

Sample Metadata Fields

Specimen part, Subject

View Samples
accession-icon SRP170748
De novo detection of m6A modification in Saccharomyces cerevisiae at single nucleotide resolution
  • organism-icon Saccharomyces cerevisiae
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

N6-methyladenosine (m6A) is the most abundant modification on mRNA, and is implicated in critical roles in development, physiology and disease. A major challenge in the field has been the inability to quantify m6A stoichiometry and the lack of antibody-independent methodologies for interrogating m6A. Here, we develop MASTER-seq for systematic quantitative profiling of m6A at single nucleotide resolution, building on differential cleavage by an RNAse at methylated sites. MASTER-seq permitted validation and de novo discovery of m6A sites, calibration of the performance of antibody based approaches, and quantitative tracking of m6A dynamics in yeast gametogenesis and mammalian differentiation. We discover that m6A stoichiometry is 'hard-coded' in cis via a simple and predictable code. This code accounts for ~50% of the variability in methylation levels and allows accurate prediction of m6A loss/acquisition events across evolution. MASTER-seq will allow quantitative investigation of m6A regulation in diverse cell types and disease states. Overall design: 8 samples are analyzed: IP and background for IME4 mutant and WT with 2 biological replicates for each condition

Publication Title

Deciphering the "m<sup>6</sup>A Code" via Antibody-Independent Quantitative Profiling.

Sample Metadata Fields

Cell line, Subject

View Samples
accession-icon GSE29044
Expression data from breast tumors in different age-specific cohorts and for different sequentional disease stages
  • organism-icon Homo sapiens
  • sample-icon 108 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Compared transccriptome of breast cancer in young women to those arising in two mature groups to characterize the underlying biological mechanisms of the breast cancer in Middle Eastern young women.

Publication Title

Age-specific gene expression signatures for breast tumors and cross-species conserved potential cancer progression markers in young women.

Sample Metadata Fields

Age, Specimen part, Disease, Disease stage

View Samples

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

Powered by Alex's Lemonade Stand Foundation

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.

BSD 3-Clause LicensePrivacyTerms of UseContact